Exposu
EPA/600/R-09/052F 

September 2011 

EXPOSURE FACTORS HANDBOOK:
 

2011 EDITION
 

National Center for Environmental Assessment
 

Office of Research and Development
 

U.S. Environmental Protection Agency
 

Washington, DC 20460 
 

Exposure Factors Handbook 

Front Matter 

DISCLAIMER 

This document has been reviewed in accordance with U.S. Environmental Protection Agency policy and 

approved for publication. Mention of trade names or commercial products does not constitute endorsement or 

recommendation for use. 

Preferred Citation: 

U.S. Environmental Protection Agency (EPA). (2011) Exposure Factors Handbook: 2011 Edition. National Center 

for Environmental Assessment, Washington, DC; EPA/600/R-09/052F. Available from the National Technical 

Information Service, Springfield, VA, and online at http://www.epa.gov/ncea/efh. 

Page Exposure Factors Handbook 

ii September 2011 
 

 

 

 

Exposure Factors Handbook 

Front Matter 

FOREWORD 

The U.S. Environmental Protection Agency (U.S. EPA), Office of Research and Development (ORD), 

National Center for Environmental Assessment’s (NCEA) mission is to provide guidance and risk assessments 

aimed at protecting human health and the environment. To accomplish this mission, NCEA works to develop and 

improve the models, databases, tools, assumptions, and extrapolations used in risk assessments. NCEA established 

the Exposure Factors Program to develop tools and databases that improve the scientific basis of exposure and risk 

assessment by (1) identifying exposure factors needs in consultation with clients, and exploring ways for filling data 

gaps; (2) compiling existing data on exposure factors needed for assessing exposures/risks; and (3) assisting clients 

in the use of exposure factors data. The Exposure Factors Handbook and the Child-Specific Exposure Factors 

Handbook, as well as other companion documents such as Example Exposure Scenarios, are products of the 

Exposure Factors Program. 

The Exposure Factors Handbook provides information on various physiological and behavioral factors 

commonly used in assessing exposure to environmental chemicals. The handbook was first published in 1989 and 

was updated in 1997. Since then, new data have become available. This updated edition incorporates data available 

since 1997 up to July 2011. It also reflects the revisions made to the Child-Specific Exposure Factors Handbook, 

which was updated and published in 2008. This edition of the handbook supersedes the information presented in the 

2008 Child-Specific Exposure Factors Handbook. Each chapter in the 2011 edition of the Exposure Factors 

Handbook presents recommended values for the exposure factors covered in the chapter as well as a discussion of 

the underlying data used in developing the recommendations. These recommended values are based solely on 

NCEA’s interpretations of the available data. In many situations, different values may be appropriate to use in 

consideration of policy, precedent, or other factors. 

David Bussard 

Director, Washington Division 

National Center for Environmental Assessment 

Exposure Factors Handbook Page 

September 2011 iii 
 

 

 

 

Exposure Factors Handbook 

Front Matter 

AUTHORS, CONTRIBUTORS, AND REVIEWERS 

The National Center for Environmental Assessment (NCEA), Office of Research and Development was 

responsible for the preparation of this handbook. Jacqueline Moya served as the Work Assignment Manager for the 

current updated edition, providing overall direction and technical assistance, and is a contributing author. The 

current draft was prepared by Westat Inc. under contract with the U.S. EPA (contract number GS-23F-8144H). 

Earlier drafts of this report were prepared by Versar, Inc. 

AUTHORS 

U.S. EPA 

Jacqueline Moya 

Linda Phillips 

Laurie Schuda 

Versar, Inc. 

Patricia Wood 

Adria Diaz 

Ron Lee 

Westat, Inc. 

Robert Clickner 

Rebecca Jeffries Birch 

Naa Adjei 

Peter Blood 

Kathleen Chapman 

Rey de Castro 

Kathryn Mahaffey 

WORD PROCESSING 

Versar, Inc. 

Malikah Moore 

Westat, Inc. 

Annmarie Winkler 

ECFlex, Inc. 

Debbie Kleiser 

Crystal Lewis 

Lana Wood 

IntelliTech Systems, Inc. 

Kathleen Secor 

TECHNICAL EDITNG 

ECFlex, Inc. 

Heidi Glick 

IntelliTech Systems, Inc. 

Cristopher Boyles 

Page Exposure Factors Handbook 

iv September 2011 
 

Exposure Factors Handbook 

Front Matter 

AUTHORS, CONTRIBUTORS, AND REVIEWERS (continued) 

REVIEWERS 

The following U.S. EPA individuals reviewed earlier drafts of this document and provided valuable 

comments: 

Ted Berner, NCEA 

Heidi Bethel, OW 

Margot Brown, OCHP 

Lisa Conner, OAQPS 

Mark Corrales, OPEI 

Dave Crawford, OSWER 

Becky Cuthbertson, OSW 

Lynn Delpire, OPPTS 

Cathy Fehrenbacher, OPPTS 

Gary Foureman, NCEA (retired) 

Ann Johnson, OPEI 

Henry Kahn, NCEA 

Youngmoo Kim, Region 6 

Lon Kissinger, Region 10 

John Langstaff, OAQPS 

Sarah Levinson, Region 1 

Matthew Lorber, NCEA 

Tom McCurdy, NERL 

Robert McGaughy, NCEA (retired) 

Marian Olsen, Region 2 

David Riley, Region 6 

Rita Schoeny, OW 

Marc Stifelman, Region 10 

Zachary Pekar, OAQPS 

Aaron Yeow, OSWER 

Linda Watson, Region 3 

Valerie Zartarian, NERL 

Exposure Factors Handbook Page 

September 2011 v 
 

Exposure Factors Handbook 

Front Matter 

AUTHORS, CONTRIBUTORS, AND REVIEWERS (continued) 

This document was reviewed by an external panel of experts. The panel was composed of the following 

individuals: 

•	 Henry Anderson, MD, Wisconsin Division of Public Health, Madison 

•	 Paloma Beamer, PhD, Environmental Health Sciences, University of Arizona 

•	 Deborah H. Bennett, PhD, Department of Public Health Sciences, University of California, Davis 

•	 Robert J. Blaisdell, PhD, Office of Environmental Health Hazard Assessment, California Environmental 

Protection Agency 

•	 Alesia Ferguson, PhD, College of Public Health, University of Arkansas Medical Services 

•	 Brent L. Finley, PhD, ChemRisk 

•	 David W. Gaylor, PhD, Gaylor and Associates, LLC 

•	 Panos G. Georgopoulus, PhD, Robert Wood Johnson Medical School, University of Medicine and 

Dentistry of New Jersey 

•	 Annette Guiseppi-Ellie, PhD, Dupont Engineering, Corporate Remediation Group 

•	 Michael D. Lebowitz, PhC, PhD, University of Arizona, Tucson, AZ 

•	 Agnes B. Lobscheid, PhD, Environmental Energy Technologies Division, Indoor Air Department, 

Lawrence Berkeley National Laboratory 

•	 P. Barry Ryan, PhD, Rollins School of Public Health, Emory University 

•	 Alan H. Stern, PhD, Independent Consultant 

•	 Nga L. Tran, PhD, Health Sciences Center for Chemical Regulation and Food Safety, Exponent, 

Washington, DC 

•	 Rosemary T. Zaleski, PhD, Occupational and Public Health Division, ExxonMobil Biomedical Sciences, 

Inc. 

Page Exposure Factors Handbook 

vi September 2011 
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Front Matter 

AUTHORS, CONTRIBUTORS, AND REVIEWERS (continued) 

ACKNOWLEDGMENTS 

The authors wish to acknowledge the important contributions of the following U.S. EPA individuals who 

conducted additional analyses for the revisions of this handbook: 

• David Hrdy, Office of Pesticide Programs 

• Henry Kahn, National Center for Environmental Assessment 

• David Miller, Office of Pesticide Programs 

• James Nguyen, Office of Pesticide Programs 

• Aaron Niman, Office of Pesticide Programs 

• Allison Nowotarski, Office of Pesticide Programs 

• Sheila Piper, Office of Pesticide Programs 

• Kristin Rury, Office of Pesticide Programs 

• Bernard Schneider, Office of Pesticide Programs 

• Nicolle Tulve, National Exposure Research Laboratory 

• Julie Van Alstine, Office of Pesticide Programs 

• Philip Villanueva, Office of Pesticide Programs 

In addition, the U.S. EPA, ORD, National Exposure Research Laboratory (NERL) made an important 

contribution to this handbook by conducting additional analyses of the National Human Activity Pattern Survey 

(NHAPS) data. U.S. EPA input to the NHAPS data analysis came from Karen A. Hammerstrom and Jacqueline 

Moya from NCEA-Washington Division, William C. Nelson from NERL-Research Triangle Park, and Stephen C. 

Hern, Joseph V. Behar (retired), and William H. Englemann from NERL-Las Vegas. 

The U.S. EPA Office of Water and Office of Pesticide Programs made important contributions by 

conducting an analysis of the U.S. Department of Agriculture (USDA) Continuing Survey of Food Intakes by 

Individual (CSFII) data in previous versions of the handbook. More recently, the Office of Pesticide Programs 

conducted an analysis of the National Health and Nutrition Examination Survey (NHANES) 2003−2006 to update 

the Food Commodity Intake Database (FCID) and food consumption chapters of this edition of the handbook. 

The authors also want to acknowledge the following individuals in NCEA: Terri Konoza for managing the 

document production activities and copy editing, Vicki Soto for copy editing, and Maureen Johnson for developing 

and managing the Web page. 

Exposure Factors Handbook Page 

September 2011 vii 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Front Matter 

EXECUTIVE SUMMARY 

Some of the steps for performing an exposure assessment are (1) identifying the source of the 

environmental contamination and the media that transports the contaminant; (2) determining the contaminant 

concentration; (3) determining the exposure scenarios, and pathways and routes of exposure; (4) determining the 

exposure factors related to human behaviors that define time, frequency, and duration of exposure; and 

(5) identifying the exposed population. Exposure factors are factors related to human behavior and characteristics 

that help determine an individual's exposure to an agent. This Exposure Factors Handbook has been prepared to 

provide information and recommendations on various factors used in assessing exposure to both adults and children. 

The purpose of the Exposure Factors Handbook is to (1) summarize data on human behaviors and characteristics 

that affect exposure to environmental contaminants, and (2) recommend values to use for these factors. This 

handbook provides nonchemical-specific data on the following exposure factors: 

• Ingestion of water and other selected liquids (see Chapter 3), 

• Non-dietary ingestion factors (see Chapter 4), 

• Ingestion of soil and dust (see Chapter 5), 

• Inhalation rates (see Chapter 6), 

• Dermal factors (see Chapter 7), 

• Body weight (see Chapter 8), 

• Intake of fruits and vegetables (see Chapter 9), 

• Intake of fish and shellfish (see Chapter 10), 

• Intake of meat, dairy products, and fats (see Chapter 11), 

• Intake of grain products (see Chapter 12), 

• Intake of home-produced food (see Chapter 13), 

• Total food intake (see Chapter 14), 

• Human milk intake (see Chapter 15), 

• Activity factors (see Chapter 16), 

• Consumer products (see Chapter 17), 

• Lifetime (see Chapter 18), and 

• Building characteristics (see Chapter 19). 

The handbook was first published in 1989 and was revised in 1997 (U.S. EPA, 1989, 1997). Recognizing 

that exposures among infants, toddlers, adolescents, and teenagers can vary significantly, the U.S. EPA published 

the Child-Specific Exposure Factors Handbook in 2002 (U.S. EPA, 2002) and its revision in 2008 (U.S. EPA, 

2008). The 2008 revision of the Child-Specific Exposure Factors Handbook as well as this 2011 edition of the 

Page Exposure Factors Handbook 

viii September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Front Matter 

Exposure Factors Handbook reflect the age categories recommended in the U.S. EPA Guidance on Selecting Age 

Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005). This 

2011 edition of the Exposure Factors Handbook also incorporates new factors and data provided in the 2008 ChildSpecific Exposure Factors Handbook (and other relevant information published through July 2011. The information 

presented in this 2011 edition of the Exposure Factors Handbook supersedes the 2008 Child-Specific Exposure 

Factors Handbook. 

The data presented in this handbook have been compiled from various sources, including government 

reports and information presented in the scientific literature. The data presented are the result of analyses by the 

individual study authors. However, in some cases, the U.S. EPA conducted additional analysis of published primary 

data to present results in a way that will be useful to exposure assessors and/or in a manner that is consistent with the 

recommended age groups. Studies presented in this handbook were chosen because they were seen as useful and 

appropriate for estimating exposure factors based on the following considerations: (1) soundness (adequacy of 

approach and minimal or defined bias); (2) applicability and utility (focus on the exposure factor of interest, 

representativeness of the population, currency of the information, and adequacy of the data collection period); 

(3) clarity and completeness (accessibility, reproducibility, and quality assurance); (4) variability and uncertainty 

(variability in the population and uncertainty in the results); and (5) evaluation and review (level of peer review and 

number and agreement of studies). Generally, studies were designated as “key” or “relevant” studies. Key studies 

were considered the most up-to-date and scientifically sound for deriving recommendations; while relevant studies 

provided applicable or pertinent data, but not necessarily the most important for a variety of reasons (e.g., data were 

outdated, limitations in study design). The recommended values for exposure factors are based on the results of key 

studies. The U.S. EPA also assigned confidence ratings of low, medium, or high to each recommended value based 

on the evaluation elements described above. These ratings are not intended to represent uncertainty analyses; rather, 

they represent the U.S. EPA’s judgment on the quality of the underlying data used to derive the recommendations. 

Key recommendations from the handbook are summarized in Table ES-1. Additional recommendations and 

detailed supporting information for these recommendations can be found in the individual chapters of this handbook. 

In providing recommendations for the various exposure factors, an attempt was made to present percentile values 

that are consistent with the exposure estimators defined in the Guidelines for Exposure Assessment (U.S. EPA, 

1992) (i.e., mean and upper percentile). However, this was not always possible because the data available were 

limited for some factors, or the authors of the study did not provide such information. As used throughout this 

handbook, the term “upper percentile” is intended to represent values in the upper tail (i.e., between 90th and 99.9th 

percentile) of the distribution of values for a particular exposure factor. The 95th percentile was used throughout the 

handbook to represent the upper tail because it is the middle of the range between 90th and 99th percentile. Other 

percentiles are presented, where available, in the tables at the end of each chapter. It should be noted that users of 

the handbook may use the exposure metric that is most appropriate for their particular situation. 

The recommendations provided in this handbook are not legally binding on any U.S. EPA program and 

should be interpreted as suggestions that program offices or individual exposure/risk assessors can consider and 

modify as needed based on their own evaluation of a given risk assessment situation. In certain cases, different 

Exposure Factors Handbook Page 

September 2011 ix 
 

Exposure Factors Handbook 

Front Matter 

values may be appropriate in consideration of policy, precedent, strategy, or other factors (e.g., more up-to-date data 

of better quality or more representative of the population of concern). 

Page Exposure Factors Handbook 

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Exposure Factors Handbook 

Front Matter 

REFERENCES FOR THE EXECUTIVE SUMMARY 

NCHS (National Center for Health Statistics). (1993) Joint policy on variance estimation and statistical reporting 

standards on NHANES III and CSFII reports: HNIS/NCHS Analytic Working Group recommendations. In: 

Analytic and reporting guidelines: the third National Health and Nutrition Examination Survey, NHANES 

III (1988-94). Centers for Disease Control and Prevention, Hyattsville, MD, pp. 39-45. Available online at 

http://www.cdc.gov/nchs/data/nhanes/nhanes3/nh3gui.pdf. 

U.S. EPA (Environmental Protection Agency). (1989) Exposure factors handbook. Exposure Assessment Group, 

Office of Research and Development, Washington, DC; EPA/600/8-89/043. Available online at 

http://rais.ornl.gov/documents/EFH_1989_EPA600889043.pdf. 

U.S. EPA (Environmental Protection Agency). (1992) Guidelines for exposure assessment. Risk Assessment Forum, 

Washington, DC; EPA/600/Z-92/001. Available online at http://cfpub.epa.gov/ncea/cfm/.cfm?deid=15263. 

U.S. EPA (Environmental Protection Agency). (1997) Exposure factors handbook. Office of Research and 

Development, Washington, DC; EPA/600/P-95/002Fa,b,c. Available online at 

http://www.epa.gov/ncea/pdfs/efh/efh-complete.pdf. 

U.S. EPA (Environmental Protection Agency). (2002) Child-specific exposure factors handbook. Interim final. 

National Center for Environmental Assessment, Washington, DC; EPA/P-00/002B. Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=55145. 

U.S. EPA (Environmental Protection Agency). (2005) Guidance on selecting age groups for monitoring and 

assessing childhood exposures to environmental contaminants. Risk Assessment Forum, Washington, DC; 

EPA/630/P-03/003F. Available online at http://www.epa.gov/raf/publications/pdfs/AGEGROUPS.PDF. 

U.S. EPA (Environmental Protection Agency) (2008) Child-specific exposure factors handbook. National Center for 

Environmental Assessment Washington, DC; EPA/600/R-06/096F. Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=199243. 

Exposure Factors Handbook Page 

September 2011 xi 
 

Table ES-1. Summary of Exposure Factor Recommendations 

Chapter 3 PER CAPITA INGESTION OF 

DRINKING WATER 

CONSUMERS-ONLY INGESTION OF 

DRINKING WATER 

Children 

mL/day 

Mean 

mL/kg-day 

95th Percentile 

mL/day mL/kg-day mL/day 

Mean 

mL/kg-day 

95th Percentile 

mL/day mL/kg-day 

Birth to 1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <18 years 

18 to <21 years 

Adults 

184 

227a 

362a 

360 

271 

317 

327 

414 

520 

573 

681 

52 

48 

52 

41 

23 

23 

18 

14 

10 

9 

9 

839a 232a 

896a 205a 

1,056 159 

1,055 126 

837 71 

877 60 

959 51 

1,316 43 

1,821 32 

1,783 28 

2,368 35 

470a 

552 

556 

467 

308 

356 

382 

511 

637 

702 

816 

137a 

119 

80 

53 

27 

26 

21 

17 

12 

10 

11 

858a 238a 

1,053a 285a 

1,171a 173a 

1,147 129 

893 75 

912 62 

999 52 

1,404 47 

1,976 35 

1,883 30 

2,818 36 

>21 years 

>65 years 

Pregnant women 

Lactating women 

1,043 

1,046 

819a 

1,379a 

13 

14 

13a 

21a 

2,958 40 

2,730 40 

2,503a 43a 

3,434a 55a 

1,227 

1,288 

872a 

1,665a 

16 

18 

14a 

26a 

3,092 42 

2,960 43 

2,589a 43a 

3,588a 55a 

a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical 

Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Chapter 3 INGESTION OF WATER WHILE SWIMMING 

Children 

Adults 

mL/eventa 

Mean 

mL/hour mL/event 

Upper Percentile 

mL/hour 

37 

16 

49 

21 

90b 

53 c 

120b 

71 c 

a 

b 

 c

Participants swam for 45 minutes. 

97th percentile 

Based on maximum value. 

Chapter 4 MOUTHING FREQUENCY AND DURATION 

Hand-to-Mouth Object-to-Mouth 

Indoor Frequency Outdoor Frequency Indoor Frequency Outdoor Frequency 

95 Mean th 

contacts/ Percentile 

hour contacts/ 

hour 

95th Mean Percentile 

contacts/ contacts/hour 

hour 

95th Mean Percentile 

contacts/ contacts/ 

hour hour 

95th Mean Percentile 

contacts/ contacts/ 

hour hour 

Birth to 1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

-

-

28 

19 

20 

13 

15 

7 

-

-

-

-

65 

52 

63 

37 

54 

21 

-

-

-

-

-

15 

14 

5 

9 

3 

-

-

-

-

-

47 

42 

20 

36 

12 

-

-

-

-

11 

20 

14 

9.9 

10 

1.1 

-

-

-

-

32 

38 

34 

24 

39 

3.2 

-

-

-

-

-

-

8.8 

8.1 

8.3 

1.9 

-

-

­

­

­

­

21 

40 

30 

9.1 

­

­

Object-to-Mouth 

Duration 

Mean minute/hour 95th Percentile minute/hour 

Birth to 1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

-

-

11 

9 

7 

10 

-

-

-

-

­

­

26 

19 

22 

11 

­

­

­

­

- No data. 

Exposure Factors Handbook 

Front Matter 

Page Exposure Factors Handbook 

xii September 2011 
Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Chapter 5 SOIL AND DUST INGESTION 

General 

Population
 

Central 

Tendency 

mg/day 

Soil Dust Soil + Dust 

High End
 

General 

Population 

Upper 

Percentile 

mg/day 

Soil-Pica 

mg/day 

Geophagy 

mg/day 

Central 

Tendency 

mg/day 

General 

Population 

Upper 

Percentile 

mg/day 

General 

Population 

Central 

Tendency 

mg/day 

General 

Population 

Upper 

Percentile 

mg/day 

6 weeks to <1 year 

1 to <6 years 

3 to <6 years 

6 to <21 years 

Adult 

30 

50 

-

50 

20 

-

-

200 

-

-

-

1,000 

-

1,000 

-

-

50,000 

-

50,000 

50,000 

30 

60 

-

60 

30 

-

-

100 

-

-

60 

100 

-

100 

50 

­

­

200 

­

­

- No data. 

Chapter 6 INHALATION 

Long-Term Inhalation Rates 

Mean 

m3/day 

95th Percentile 

m3/day 

Birth to 1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

Birth to <1year 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <31 years 

31 to <41 years 

41 to <51 years 

51 to <61 years 

61 to <71 years 

71 to <81 years 

≥81 years 

3.6 

3.5 

4.1 

5.4 

5.4 

8.0 

8.9 

10.1 

12.0 

15.2 

16.3 

15.7 

16.0 

16.0 

15.7 

14.2 

12.9 

12.2 

7.1 

5.8 

6.1 

8.0 

9.2 

12.8 

13.7 

13.8 

16.6 

21.9 

24.6 

21.3 

21.4 

21.2 

21.3 

18.1 

16.6 

15.7 

Short-Term Inhalation Rates, by Activity Level 

Sleep or Nap Sedentary/Passive Light Intensity Moderate Intensity High Intensity 

95 Mean th 

m3/ m3/

minute minute 

95th 95th 95 Mean Mean Mean th 

m3/ m3/ m3/ m3/ m3/ m3/ 

minute minute minute minute minute minute 

95 Mean th 

m3/ m3/ 

minute minute 

Birth to <1year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <31 years 

31 to <41 years 

41 to <51 years 

51 to <61 years 

61 to <71 years 

71 to <81 years 

≥81 years 

3.0E–03 

4.5E–03 

4.6E–03 

4.3E–03 

4.5E–03 

5.0E–03 

4.9E–03 

4.3E–03 

4.6E–03 

5.0E–03 

5.2E–03 

5.2E–03 

5.3E–03 

5.2E–03 

4.6E–03 

6.4E–03 

6.4E–03 

5.8E–03 

6.3E–03 

7.4E–03 

7.1E–03 

6.5E–03 

6.6E–03 

7.1E–03 

7.5E–03 

7.2E–03 

7.2E–03 

7.0E–03 

3.1E–03 

4.7E–03 

4.8E–03 

4.5E–03 

4.8E–03 

5.4E–03 

5.3E–03 

4.2E–03 

4.3E–03 

4.8E–03 

5.0E–03 

4.9E–03 

5.0E–03 

4.9E–03 

4.7E–03 

6.5E–03 

6.5E–03 

5.8E–03 

6.4E–03 

7.5E–03 

7.2E–03 

6.5E–03 

6.6E–03 

7.0E–03 

7.3E–03 

7.3E–03 

7.2E–03 

7.0E–03 

7.6E–03 

1.2E–02 

1.2E–02 

1.1E–02 

1.1E–02 

1.3E–02 

1.2E–02 

1.2E–02 

1.2E–02 

1.3E–02 

1.3E–02 

1.2E–02 

1.2E–02 

1.2E–02 

1.1E–02 

1.6E–02 

1.6E–02 

1.4E–02 

1.5E–02 

1.7E–02 

1.6E–02 

1.6E–02 

1.6E–02 

1.6E–02 

1.7E–02 

1.6E–02 

1.5E–02 

1.5E–02 

1.4E–02 

2.1E–02 

2.1E–02 

2.1E–02 

2.2E–02 

2.5E–02 

2.6E–02 

2.6E–02 

2.7E–02 

2.8E–02 

2.9E–02 

2.6E–02 

2.5E–02 

2.5E–02 

2.2E–02 

2.9E–02 

2.9E–02 

2.7E–02 

2.9E–02 

3.4E–02 

3.7E–02 

3.8E–02 

3.7E–02 

3.9E–02 

4.0E–02 

3.4E–02 

3.2E–02 

3.1E–02 

2.6E–02 

3.8E–02 

3.9E–02 

3.7E–02 

4.2E–02 

4.9E–02 

4.9E–02 

5.0E–02 

4.9E–02 

5.2E–02 

5.3E–02 

4.7E–02 

4.7E–02 

4.8E–02 

4.1E–02 

5.2E–02 

5.3E–02 

4.8E–02 

5.9E–02 

7.0E–02 

7.3E–02 

7.6E–02 

7.2E–02 

7.6E–02 

7.8E–02 

6.6E–02 

6.5E–02 

6.8E–02 

Exposure Factors Handbook 

Front Matter 

Exposure Factors Handbook Page 

September 2011 xiii 
 

Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Chapter 7 SURFACE AREA 

Total Surface Area 

Mean 95th Percentile 2 m 2 m

Birth to 1 month 0.29 0.34 

1 to <3 months 0.33 0.38 

3 to <6 months 0.38 0.44 

6 to <12 months 0.45 0.51 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

Adult Males 

0.53 

0.61 

0.76 

1.08 

1.59 

1.84 

0.61 

0.70 

0.95 

1.48 

2.06 

2.33 

21 to <30 years 

30 to <40 years 

40 to <50 years 

50 to <60 years 

60 to <70 years 

70 to <80 years 

>80 years 

Adult Females 

2.05 

2.10 

2.15 

2.11 

2.08 

2.05 

1.92 

2.52 

2.50 

2.56 

2.55 

2.46 

2.45 

2.22 

21 to <30 years 

30 to <40 years 

40 to <50 years 

50 to <60 years 

60 to <70 years 

70 to <80 years 

≥80 years 

1.81 

1.85 

1.88 

1.89 

1.88 

1.77 

1.69 

2.25 

2.31 

2.36 

2.38 

2.34 

2.13 

1.98 

Percent Surface Area of Body Parts 

Head Trunk Arms Hands Legs Feet 

Mean Percent of Total Surface Area 

Birth to 1 month 18.2 35.7 13.7 5.3 20.6 6.5 

1 to <3 months 18.2 35.7 13.7 5.3 20.6 6.5 

3 to <6 months 18.2 35.7 13.7 5.3 20.6 6.5 

6 to <12 months 18.2 35.7 13.7 5.3 20.6 6.5 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

Adult Males >21 

16.5 

8.4 

8.0 

6.1 

4.6 

4.1 

6.6 

35.5 

41.0 

41.2 

39.6 

39.6 

41.2 

40.1 

13.0 

14.4 

14.0 

14.0 

14.3 

14.6 

15.2 

5.7 

4.7 

4.9 

4.7 

4.5 

4.5 

5.2 

23.1 

25.3 

25.7 

28.8 

30.4 

29.5 

33.1 

6.3 

6.3 

6.4 

6.8 

6.6 

6.1 

6.7 

Adult Females >21 6.2 35.4 12.8 4.8 32.3 6.6 

Surface Area of Body Parts 

Head Trunk Arms Hands Legs Feet 

Mean 95th Mean 95th Mean 95th Mean 95th Mean 95th Mean 95th 

2 m 2 m 2 m 2 m 2 m 2 m 2 m 2 m 2 m 2 m 2 m 2 m 

Birth to 1 month 0.053 0.062 0.104 0.121 0.040 0.047 0.015 0.018 0.060 0.070 0.019 0.022 

1 to <3 months 0.060 0.069 0.118 0.136 0.045 0.052 0.017 0.020 0.068 0.078 0.021 0.025 

3 to <6 months 0.069 0.080 0.136 0.157 0.052 0.060 0.020 0.023 0.078 0.091 0.025 0.029 

6 to <12 months 0.082 0.093 0.161 0.182 0.062 0.070 0.024 0.027 0.093 0.105 0.029 0.033 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

Adult Males >21 

0.087 

0.051 

0.060 

0.066 

0.073 

0.076 

0.136 

0.101 

0.059 

0.076 

0.090 

0.095 

0.096 

0.154 

0.188 

0.250 

0.313 

0.428 

0.630 

0.759 

0.827 

0.217 

0.287 

0.391 

0.586 

0.816 

0.961 

1.10 

0.069 

0.088 

0.106 

0.151 

0.227 

0.269 

0.314 

0.079 

0.101 

0.133 

0.207 

0.295 

0.340 

0.399 

0.030 

0.028 

0.037 

0.051 

0.072 

0.083 

0.107 

0.035 

0.033 

0.046 

0.070 

0.093 

0.105 

0.131 

0.122 

0.154 

0.195 

0.311 

0.483 

0.543 

0.682 

0.141 

0.177 

0.244 

0.426 

0.626 

0.687 

0.847 

0.033 

0.038 

0.049 

0.073 

0.105 

0.112 

0.137 

0.038 

0.044 

0.061 

0.100 

0.136 

0.142 

0.161 

Adult Females >21 0.114 0.121 0.654 0.850 0.237 0.266 0.089 0.106 0.598 0.764 0.122 0.146 

Exposure Factors Handbook 

Front Matter 

Page Exposure Factors Handbook 

xiv September 2011 
Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Chapter 7	 MEAN SOLID ADEHERENCE TO SKIN (mg/cm2) 

Face Arms Hands Legs Feet 

Children 

 Residential (indoors)a - 0.0041 0.0011 0.0035 0.010 

 Daycare (indoors and outdoors)b - 0.024 0.099 0.020 0.071 

 Outdoor sportsc 0.012 0.011 0.11 0.031 - d Indoor sports - 0.0019 0.0063 0.0020 0.0022 

 Activities with soile 0.054 0.046 0.17 0.051 0.20 

 Playing in mud 

f - 11 47 23 15 

 Playing in sediment 

g 0.040 0.17 0.49 0.70 21 

Adults i Outdoor sports 0.0314 0.0872 0.1336 0.1223 -

 Activities with soilh  0.0240 0.0379 0.1595 0.0189 0.1393 

j Construction activities 0.0982 0.1859 0.2763 0.0660 - k Clamming 0.02 0.12 0.88 0.16 0.58 a Based on weighted average of geometric mean soil loadings for 2 groups of children (ages 3 to 13 years; N = 10) playing indoors. b Based on weighted average of geometric mean soil loadings for 4 groups of daycare children (ages 1 to 6.5 years; N =21) playing both 

indoors and outdoors. c Based on geometric mean soil loadings of 8 children (ages 13 to 15 years) playing soccer. d Based on geometric mean soil loadings of 6 children (ages >8 years) and 1 adult engaging in Tae Kwon Do. e Based on weighted average of geometric mean soil loadings for gardeners and archeologists (ages 16 to 35 years). f Based on weighted average of geometric mean soil loadings of 2 groups of children (age 9 to 14 years;N = 12) playing in mud. g Based on geometric mean soil loadings of 9 children (ages 7 to 12 years) playing in tidal flats. h Based on weighted average of geometric mean soil loadings of 3 groups of adults(ages 23 to 33 years) playing rugby and 2 groups of 

adults (ages 24 to 34) playing soccer. i	 Based on weighted average of geometric mean soil loadings for 69 gardeners, farmers, groundskeepers, landscapers, and archeologists 

(ages 16 to 64 years) for faces, arms and hands; 65 gardeners, farmers, groundskeepers, and archeologists (ages 16 to 64 years) for legs; 

and 36 gardeners, groundskeepers, and archeologists (ages 16 to 62) for feet. 

j	 Based on weighted average of geometric mean soil loadings for 27 construction workers, utility workers and equipment operators (ages 

21 to 54) for faces, arms, and hands; and based on geometric mean soil loadings for 8 construction workers (ages 21 to 30 years) for 

legs. k Based on geometric mean soil loadings of 18 adults (ages 33 to 63 years) clamming in tidal flats. 

- No data. 

Chapter 8	 BODY WEIGHT 

Mean 

Kg 

Birth to 1 month 4.8 

1 to <3 months 5.9 

3 to <6 months 7.4 

6 to <12 months 9.2 

1 to <2 years 11.4 

2 to <3 years 13.8 

3 to <6 years 18.6 

6 to <11 years 31.8 

11 to <16 years 56.8 

16 to <21 years 71.6 

Adults 80.0 

Exposure Factors Handbook 

Front Matter 

Exposure Factors Handbook Page 

September 2011 xv 
 

Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Chapter 9 FRUIT AND VEGETABLE INTAKE 

Mean 

g/kg-day 

Per Capita Consumers-Only 

95th Percentile 

g/kg-day 

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

Total Fruits 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

≥50 years 

6.2 

7.8 

7.8 

4.6 

2.3 

0.9 

0.9 

0.9 

1.4 

23.0a 

21.3a 

21.3a 

14.9 

8.7 

3.5 

3.5 

3.7 

4.4 

10.1 

8.1 

8.1 

4.7 

2.5 

1.1 

1.1 

1.1 

1.5 

25.8a 

21.4a 

21.4a 

15.1 

9.2 

3.8 

3.8 

3.8 

4.6 

Total Vegetables 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

≥50 years 

5.0 

6.7 

6.7 

5.4 

3.7 

2.3 

2.3 

2.5 

2.6 

16.2a 

15.6a 

15.6a 

13.4 

10.4 

5.5 

5.5 

5.9 

6.1 

6.8 

6.7 

6.7 

5.4 

3.7 

2.3 

2.3 

2.5 

2.6 

18.1a 

15.6a 

15.6a 

13.4 

10.4 

5.5 

5.5 

5.9 

6.1 a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Chapter 10 FISH INTAKE 

Mean 

g/kg-day 

Per Capita Consumers-Only 

95th Percentile 

g/kg-day 

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

General Population—Finfish 

All 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

Females 13 to 49 years 

>50 years 

0.16 

0.03 

0.22 

0.22 

0.19 

0.16 

0.10 

0.10 

0.15 

0.14 

0.20 

1.1 

0.0a 

1.2a 

1.2a 

1.4 

1.1 

0.7 

0.7 

1.0 

0.9 

1.2 

0.73 

1.3 

1.6 

1.6 

1.3 

1.1 

0.66 

0.66 

0.65 

0.62 

0.68 

2.2 

2.9a 

4.9a 

4.9a 

3.6a 

2.9a 

1.7 

1.7 

2.1 

1.8 

2.0 

General Population—Shellfish 

All 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21years 

21 to <50 years 

Females 13 to 49 years 

>50 years 

0.06 

0.00 

0.04 

0.04 

0.05 

0.05 

0.03 

0.03 

0.08 

0.06 

0.05 

0.4 

0.0a 

0.0a 

0.0a 

0.0 

0.2 

0.0 

0.0 

0.5 

0.3 

0.4 

0.57 

0.42 

0.94 

0.94 

1.0 

0.72 

0.61 

0.61 

0.63 

0.53 

0.41 

1.9 

2.3a 

3.5a 

3.5a 

2.9a 

2.0a 

1.9 

1.9 

2.2 

1.8 

1.2 

Exposure Factors Handbook 

Front Matter 

Page Exposure Factors Handbook 

xvi September 2011 
Table ES-1. Summary of Exposure Factor Recommendations (continued) 

General Population—Total Finfish and Shellfish 

All 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

Females 13 to 49 years 

>50 years 

0.22 

0.04 

0.26 

0.26 

0.24 

0.21 

0.13 

0.13 

0.23 

0.19 

0.25 

1.3 

0.0a 

1.6a 

1.6a 

1.6a 

1.4 

1.0 

1.0 

1.3 

1.2 

1.4 

0.78 

1.2 

1.5 

1.5 

1.3 

0.99 

0.69 

0.69 

0.76 

0.68 

0.71 

2.4 

2.9a 

5.9a 

5.9a 

3.6a 

2.7a 

1.8 

1.8 

2.5 

1.9 

2.1 a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
 

Recreational Population—Marine Fish—Atlantic
 

Mean g/day 95th Percentile g/day 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <18 years 

>18 years 

2.5 

2.5 

3.4 

2.8 

5.6 

8.8 

8.6 

13 

6.6 

18 

Recreational Population—Marine Fish—Gulf 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <18 years 

>18 years 

3.2 

3.3 

4.4 

3.5 

7.2 

13 

12 

18 

9.5 

26 

Recreational Population—Marine Fish—Pacific 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <18 years 

>18 years 

0.9 

0.9 

1.2 

1.0 

2.0 

3.3 

3.2 

4.8 

2.5 

6.8 

Recreational Population—Freshwater Fish—See Chapter 10
 

Native American Population—See Chapter 10
 

Other Populations—See Chapter 10
 

Chapter 11 MEATS, DAIRY PRODUCTS, AND FAT INTAKE 

Per Capita Consumers-Only 

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

Total Meats 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

≥50 years 

1.2 

4.0 

4.0 

3.9 

2.8 

2.0 

2.0 

1.8 

1.4 

5.4a 

10.0a 

10.0a 

8.5 

6.4 

4.7 

4.7 

4.1 

3.1 

2.7 

4.1 

4.1 

3.9 

2.8 

2.0 

2.0 

1.8 

1.4 

8.1a 

10.1a 

10.1a 

8.6 

6.4 

4.7 

4.7 

4.1 

3.1 

Total Dairy Products 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

≥50 years 

10.1 

43.2 

43.2 

24.0 

12.9 

5.5 

5.5 

3.5 

3.3 

43.2a 

94.7a 

94.7a 

51.1 

31.8 

16.4 

16.4 

10.3 

9.6 

11.7 

43.2 

43.2 

24.0 

12.9 

5.5 

5.5 

3.5 

3.3 

44.7a 

94.7a 

94.7a 

51.1 

31.8 

16.4 

16.4 

10.3 

9.6 

Exposure Factors Handbook 

Front Matter 

Exposure Factors Handbook Page 

September 2011 xvii 
 

Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Total Fats 

Birth to 1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <31 years 

31 to <41 years 

41 to <51 years 

51 to <61 years 

61 to <71 years 

71 to <81 years 

≥81 years 

5.2 

4.5 

4.1 

3.7 

4.0 

3.6 

3.4 

2.6 

1.6 

1.3 

1.2 

1.1 

1.0 

0.9 

0.9 

0.8 

0.9 

16 

12 

8.2 

7.0 

7.1 

6.4 

5.8 

4.2 

3.0 

2.7 

2.3 

2.1 

1.9 

1.7 

1.7 

1.5 

1.5 

7.8 

6.0 

4.4 

3.7 

4.0 

3.6 

3.4 

2.6 

1.6 

1.3 

1.2 

1.1 

1.0 

0.9 

0.9 

0.8 

0.9 

16 

12 

8.3 

7.0 

7.1 

6.4 

5.8 

4.2 

3.0 

2.7 

2.3 

2.1 

1.9 

1.7 

1.7 

1.5 

1.5 a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Chapter 12 GRAINS INTAKE 

Mean 

g/kg-day 

Per Capita Consumers-Only 

95th Percentile 

g/kg-day 

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

Birth to 1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

≥50 years 

3.1 

6.4 

6.4 

6.2 

4.4 

2.4 

2.4 

2.2 

1.7 

9.5a 

12.4a 

12.4a 

11.1 

8.2 

5.0 

5.0 

4.6 

3.5 

4.1 

6.4 

6.4 

6.2 

4.4 

2.4 

2.4 

2.2 

1.7 

10.3a 

12.4a 

12.4a 

11.1 

8.2 

5.0 

5.0 

4.6 

3.5 a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Chapter 13 HOME-PRODUCED FOOD INTAKE 

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

Consumer-Only Home-Produced Fruits, Unadjusteda 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

8.7 

4.1 

3.6 

1.9 

2.0 

2.7 

2.3 

60.6 

8.9 

15.8 

8.3 

6.8 

13.0 

8.7 

Consumer-Only Home-Produced Vegetables, Unadjusteda 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

5.2 

2.5 

2.0 

1.5 

1.5 

2.1 

2.5 

19.6 

7.7 

6.2 

6.0 

4.9 

6.9 

8.2 

Consumer-Only Home-Produced Meats, Unadjusteda 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

3.7 

3.6 

3.7 

1.7 

1.8 

1.7 

1.4 

10.0 

9.1 

14.0 

4.3 

6.2 

5.2 

3.5 

Exposure Factors Handbook 

Front Matter 

Page Exposure Factors Handbook 

xviii September 2011 
Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Consumer-Only Home-Caught Fish, Unadjusteda 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

-

-

2.8 

1.5 

1.9 

1.8 

1.2 

­

­

7.1 

4.7 

4.5 

4.4 

3.7 

Per Capita for Populations that Garden or (Farm) b Home-Produced Fruits b Home-Produced Vegetables

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

95th Mean Percentile 

g/kg-day g/kg-day 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

50+ years 

1.0 (1.4) 

1.0 (1.4) 

0.78 (1.0) 

0.40 (0.52) 

0.13 (0.17) 

0.13 (0.17) 

0.15 (0.20) 

0.24 (0.31) 

4.8 (9.1) 

4.8 (9.1) 

3.6 (6.8) 

1.9 (3.5) 

0.62 (1.2) 

0.62 (1.2) 

0.70 (1.3) 

1.1 (2.1) 

1.3 (2.7) 

1.3 (2.7) 

1.1 (2.3) 

0.80 (1.6) 

0.56 (1.1) 

0.56 (1.1) 

0.56 (1.1) 

0.60 (1.2) 

7.1 (14) 

7.1 (14) 

6.1 (12) 

4.2 (8.1) 

3.0 (5.7) 

3.0 (5.7) 

3.0 (5.7) 

3.2 (6.1) 

Per Capita for Populations that Farm or (Raise Animals) b Home-Produced Meats Home-Produced Dairy 

95th Mean Percentile 

g/kg-day g/kg-day 

95th Mean Percentile 

g/kg-day g/kg-day 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

50+ years 

1.4 (1.4) 

1.4 (1.4) 

1.4 (1.4) 

1.0 (1.0) 

0.71 (0.73) 

0.71 (0.73) 

0.65 (0.66) 

0.51 (0.52) 

5.8 (6.0) 

5.8 (6.0) 

5.8 (6.0) 

4.1 (4.2) 

3.0 (3.1) 

3.0 (3.1) 

2.7 (2.8) 

2.1 (2.2) 

11 (13) 

11 (13) 

6.7 (8.3) 

3.9 (4.8) 

1.6 (2.0) 

1.6 (2.0) 

0.95 (1.2) 

0.92 (1.1) 

76 (92) 

76 (92) 

48 (58) 

28 (34) 

12 (14) 

12 (14) 

6.9 (8.3) 

6.7 (8.0) a 

b 

-

Not adjusted to account for preparation and post cooking losses. 

Adjusted for preparation and post cooking losses. 

No data. 

Chapter 14 TOTAL PER CAPITA FOOD INTAKE 

Birth to 1 year 

1 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

≥50 years 

Mean 

g/kg-day 

95th Percentile 

g/kg-day 

91 

113 

79 

47 

28 

28 

29 

29 

208a 

185a 

137 

92 

56 

56 

63 

59 a Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Chapter 15 HUMAN MILK AND LIPID INTAKE 

Mean Upper Percentile 

mL/day mL/kg-day mL/day mL/kg-day 

Human Milk Intake 

Birth to 1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

510 

690 

770 

620 

150 

140 

110 

83 

950 

980 

1,000 

1,000 

220 

190 

150 

130 

Lipid Intake 

Birth to 1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

20 

27 

30 

25 

6.0 

5.5 

4.2 

3.3 

38 

40 

42 

42 

8.7 

8.0 

6.1 

5.2 

Exposure Factors Handbook 

Front Matter 

Exposure Factors Handbook Page 

September 2011 xix 
 

 

Exposure Factors Handbook 

Front Matter 

Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Chapter 16 ACTIVITY FACTORS 

Time Indoors (total) Time Outdoors (total) Time Indoors (at residence) 

minutes/day minutes/day minutes/day 

Mean 95th Percentile Mean 95th Percentile Mean 95th Percentile 

Birth to <1 month 1,440 - 0 - - -

1 to <3 months 1,432 - 8 - - -

3 to <6 months 1,414 - 26 - - -

6 to <12 months 1,301 - 139 - - -

Birth to <1 year - - - - 1,108 1,440 

1 to <2 years 1,353 - 36 - 1,065 1,440 

2 to <3 years 1,316 - 76 - 979 1,296 

3 to <6 years 1,278 - 107 - 957 1,355 

6 to <11 years 1,244 - 132 - 893 1,275 

11 to <16 years 1,260 - 100 - 889 1,315 

16 to <21 years 1,248 - 102 - 833 1,288 

18 to <64 years 1,159 - 281 - 948 1,428 

>64 years 1,142 - 298 - 1,175 1,440 

Showering 

minutes/day 

Bathing 

minutes/day 

Bathing/Showering 

minutes/day 

Mean 95th Percentile Mean 95th Percentile Mean 95th Percentile 

Birth to <1year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <64 years 

>64 years 

15 

20 

22 

17 

18 

18 

20 

-

-

-

-

44 

34 

41 

40 

45 

-

-

19 

23 

23 

24 

24 

25 

33 

-

-

30 

32 

45 

60 

46 

43 

60 

-

-

-

-

-

-

-

-

-

17 

17 

-

-

-

-

-

-

-

-

-

Playing on Sand/Gravel 

minutes/day 

Playing on Grass 

minutes/day 

Playing on Dirt 

minutes/day 

Mean 95th Percentile Mean 95th Percentile Mean 95th Percentile 

Birth to <1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <64 years 

>64 years 

18 

43 

53 

60 

67 

67 

83 

0 (median) 

0 (median) 

-

121 

121 

121 

121 

121 

-

121 

-

52 

68 

62 

79 

73 

75 

60 

60 (median) 

121 (median) 

-

121 

121 

121 

121 

121 

-

121 

-

33 

56 

47 

63 

63 

49 

30 

0 (median) 

0 (median) 

-

121 

121 

121 

121 

120 

-

120 

-

Swimming 

minutes/month 

Mean 95th Percentile 

Birth to <1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <64 years 

>64 years 

96 

105 

116 

137 

151 

139 

145 

45(median) 

40(median) 

-

-

181 

181 

181 

181 

181 

181 

181 

Page Exposure Factors Handbook 

xx September 2011 
Table ES-1. Summary of Exposure Factor Recommendations (continued) 

Occupational Mobility 

Median Tenure (years) 

Men 

Median Tenure (years) 

Women 

All ages, ≥16 years 

16 to 24 years 

25 to 29 years 

30 to 34 years 

35 to 39 years 

40 to 44 years 

45 to 49 years 

50 to 54 years 

55 to 59 years 

60 to 64 years 

65 to 69 years 

≥70 years 

7.9 

2.0 

4.6 

7.6 

10.4 

13.8 

17.5 

20.0 

21.9 

23.9 

26.9 

30.5 

5.4 

1.9 

4.1 

6.0 

7.0 

8.0 

10.0 

10.8 

12.4 

14.5 

15.6 

18.8 

Population Mobility 

All 

Residential Occupancy Period (years) Current Residence Time (years) 

95th Mean Percentile 95th Mean Percentile 

12 33 13 46 

- No data. 

Chapter 17 CONSUMER PRODUCTS - See Chapter 17 

Chapter 18 LIFE EXPECTANCY 

Years 

Total 

Males 

Females 

78 

75 

80 

Chapter 19 BUILDING CHARACTERISTICS 

Volume of Residence (m3) 

Mean 

Residential Buildings 

10th Percentile 

492 154 

Air Exchange Rate (air changes/hour) 0.45 0.18 

Non-Residential Buildings 

Volume of Non-residential Buildings (m3) 

Vacant 

Office 

Laboratory 

Non-refrigerated warehouse 

Food sales 

Public order and safety 

Outpatient healthcare 

Refrigerated warehouse 

Religious worship 

Public assembly 

Education 

Food service 

Inpatient healthcare 

Nursing 

Lodging 

Strip shopping mall 

Enclosed mall 

Retail other than mall 

Service 

Other 

All Buildings 

Mean (Standard Deviation) 10th Percentile 

4,789 

5,036 

24,681 

9,298 

1,889 

5,253 

3,537 

19,716 

3,443 

4,839 

8,694 

1,889 

82,034 

15,522 

11,559 

7,891 

287,978 

3,310 

2,213 

5,236 

5,575 

408 

510 

2,039 

1,019 

476 

816 

680 

1,133 

612 

595 

527 

442 

17,330 

1,546 

527 

1,359 

35,679 

510 

459 

425 

527 

Air Exchange Rate (air changes/hour) 1.5 (0.87) 

Range 0.3–4.1 

0.60 

Exposure Factors Handbook 

Front Matter 

Exposure Factors Handbook Page 

September 2011 xxi 
 

 

 

 

 

 

Exposure Factors Handbook 

Front Matter 

1.	 INTRODUCTION........................................................................................................................................1-3
 

1.1.	 BACKGROUND AND PURPOSE................................................................................................1-3
 

1.2.	 INTENDED AUDIENCE ..............................................................................................................1-3
 

1.3.	 SCOPE ...........................................................................................................................................1-3
 

1.4.	 UPDATES TO PREVIOUS VERSIONS OF THE HANDBOOK.................................................1-4
 

1.5.	 SELECTION OF STUDIES FOR THE HANDBOOK AND DATA PRESENTATION ...............1-4
 

1.5.1.	 General Assessment Factors ............................................................................................1-5
 

1.5.2.	 Selection Criteria .............................................................................................................1-5
 

1.6.	 APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
 

FACTORS......................................................................................................................................1-7
 

1.7.	 SUGGESTED REFERENCES FOR USE IN CONJUNCTION WITH THIS
 

HANDBOOK.................................................................................................................................1-9
 

1.8.	 THE USE OF AGE GROUPINGS WHEN ASSESSING EXPOSURE ......................................1-10
 

1.9.	 CONSIDERING LIFE STAGE WHEN CALCULATING EXPOSURE AND RISK .................1-11
 

1.10.	 FUNDAMENTAL PRINCIPLES OF EXPOSURE ASSESSMENT...........................................1-13
 

1.10.1.	 Exposure and Dose Equations .......................................................................................1-15
 

1.10.2.	 Use of Exposure Factors Data in Probabilistic Analyses...............................................1-17
 

1.11.	 AGGREGATE AND CUMULATIVE EXPOSURES..................................................................1-18
 

1.12.	 ORGANIZATION OF THE HANDBOOK .................................................................................1-19
 

1.13.	 REFERENCES FOR CHAPTER 1..............................................................................................1-20
 

APPENDIX 1A RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA AND 

DOSE RESPONSE INFORMATION FROM THE INTEGRATED RISK INFORMATION 

SYSTEM (IRIS)........................................................................................................................................1A-1 

Table 1-1. Availability of Various Exposure Metrics in Exposure Factors Data ..........................................1-27
 

Table 1-2. Criteria Used to Rate Confidence in Recommended Values........................................................1-28
 

Table 1-3. Age-Dependent Potency Adjustment Factor by Age Group for Mutagenic Carcinogens............1-29
 

Figure 1-1. Conceptual Drawing of Exposure and Dose Relationship (Zartarian et al., 2007). .....................1-13
 

Figure 1-2. Exposure-Dose-Effect Continuum ...............................................................................................1-30
 

Figure 1-3. Schematic Diagram of Exposure Pathways, Factors, and Routes. ...............................................1-31
 

Figure 1-4. Road Map to Exposure Factor Recommendations .......................................................................1-32
 

Page Exposure Factors Handbook 

xxii September 2011 
Exposure Factors Handbook 

Front Matter 

2. VARIABILITY AND UNCERTAINTY.......................................................................................................2-1
 

2.1. VARIABILITY VERSUS UNCERTAINTY..................................................................................2-1
 

2.2. TYPES OF VARIABILITY ...........................................................................................................2-2
 

2.3. ADDRESSING VARIABILITY ....................................................................................................2-2
 

2.4. TYPES OF UNCERTAINTY.........................................................................................................2-3
 

2.5. REDUCING UNCERTAINTY ......................................................................................................2-4
 

2.6. ANALYZING VARIABILITY AND UNCERTAINTY.................................................................2-4
 

2.7. LITERATURE REVIEW OF VARIABILITY AND UNCERTAINTY ANALYSIS .....................2-5
 

2.8. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSES ..................2-7
 

2.9. REFERENCES FOR CHAPTER 2................................................................................................2-8
 

Exposure Factors Handbook Page
 

September 2011 xxiii
 
 

 

 

 

 

 

Exposure Factors Handbook 

Front Matter 

3.	 INGESTION OF WATER AND OTHER SELECT LIQUIDS ....................................................................3-1
 

3.1.	 INTRODUCTION .........................................................................................................................3-1
 

3.2.	 RECOMMENDATIONS ...............................................................................................................3-2
 

3.2.1.	 Water Ingestion from Consumption of Water as a Beverage and From Food and 

Drink................................................................................................................................3-2
 

3.2.2.	 Pregnant and Lactating Women .......................................................................................3-2
 

3.2.3.	 Water Ingestion While Swimming or Diving...................................................................3-2
 

3.3.	 DRINKING WATER INGESTION STUDIES ..............................................................................3-9
 

3.3.1.	 Key Drinking Water Ingestion Study...............................................................................3-9
 

3.3.1.1. Kahn and Stralka (2008a)..................................................................................3-9
 

3.3.1.2. U.S. EPA Analysis of NHANES 2003–2006 Data ..........................................3-10
 

3.3.2.	 Relevant Drinking Water Ingestion Studies...................................................................3-11
 

3.3.2.1. Wolf (1958) .....................................................................................................3-11
 

3.3.2.2. National Research Council (1977) ..................................................................3-11
 

3.3.2.3. Hopkins and Ellis (1980).................................................................................3-12
 

3.3.2.4. Canadian Ministry of National Health and Welfare (1981).............................3-12
 

3.3.2.5. Gillies and Paulin (1983).................................................................................3-13
 

3.3.2.6. Pennington (1983) ...........................................................................................3-13
 

3.3.2.7. U.S. EPA (1984) ..............................................................................................3-14
 

3.3.2.8. Cantor et al. (1987)..........................................................................................3-14
 

3.3.2.9. Ershow and Cantor (1989)...............................................................................3-15
 

3.3.2.10.Roseberry and Burmaster (1992).....................................................................3-15
 

3.3.2.11.Levy et al. (1995) ............................................................................................3-16
 

3.3.2.12.USDA (1995)...................................................................................................3-16
 

3.3.2.13.U.S. EPA (1996) ..............................................................................................3-17
 

3.3.2.14.Heller et al. (2000)...........................................................................................3-17
 

3.3.2.15.Sichert-Hellert et al. (2001).............................................................................3-18
 

3.3.2.16.Sohn et al. (2001) ............................................................................................3-18
 

3.3.2.17.Hilbig et al. (2002) ..........................................................................................3-19
 

3.3.2.18.Marshall et al. (2003a).....................................................................................3-19
 

3.3.2.19.Marshall et al. (2003b) ....................................................................................3-20
 

3.3.2.20.Skinner et al. (2004)........................................................................................3-20
 

3.4.	 PREGNANT AND LACTATING WOMEN................................................................................3-21
 

3.4.1.	 Key Study on Pregnant and Lactating Women ..............................................................3-21
 

3.4.1.1. Kahn and Stralka (2008b)................................................................................3-21
 

3.4.2.	 Relevant Studies on Pregnant and Lactating Women ....................................................3-21
 

3.4.2.1. Ershow et al. (1991) ........................................................................................3-21
 

3.4.2.2. Forssen et al. (2007) ........................................................................................3-22
 

3.5.	 HIGH ACTIVITY LEVELS/HOT CLIMATES...........................................................................3-22
 

3.5.1.	 Relevant Studies on High Activity Levels/Hot Climates...............................................3-22
 

3.5.1.1. McNall and Schlegel (1968)............................................................................3-22
 

3.5.1.2. U.S. Army (1983) ............................................................................................3-23
 

3.6.	 WATER INGESTION WHILE SWIMMING AND DIVING .....................................................3-23
 

3.6.1.	 Key Study on Water Ingestion While Swimming ..........................................................3-23
 

3.6.1.1. Dufour et al. (2006).........................................................................................3-23
 

3.6.2.	 Relevant Studies on Water Ingestion While Swimming, Diving, or Engaging in 

Recreational Water Activities.........................................................................................3-24
 

3.6.2.1. Schijven and de Roda Husman (2006) ............................................................3-24
 

3.6.2.2. Schets et al. (2011) ..........................................................................................3-24
 

3.6.2.3. Dorevitch et al. (2011).....................................................................................3-25
 

3.7.	 REFERENCES FOR CHAPTER 3..............................................................................................3-25
 

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Front Matter 

Table 3-1. Recommended Values for Drinking Water Ingestion Rates ...........................................................3-3
 

Table 3-2. Confidence in Recommendations for Drinking Water Ingestion Rates..........................................3-4
 

Table 3-3. Recommended Values for Water Ingestion Rates of Community Water for Pregnant and
 

Lactating Women ...........................................................................................................................3-5
 

Table 3-4. Confidence in Recommendations for Water Ingestion for Pregnant/Lactating Women.................3-6
 

Table 3-5. Recommended Values for Water Ingestion While Swimming .......................................................3-7
 

Table 3-6. Confidence in Recommendations for Water Ingestion While Swimming......................................3-8
 

Table 3-7. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994-1996, 1998 CSFII: Community Water (mL/day) ................................................................3-28
 

Table 3-8. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 

1994-1996, 1998 CSFII: Bottled Water (mL/day)........................................................................3-29
 

Table 3-9. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994-1996, 1998 CSFII: Other Sources (mL/day).......................................................................3-30
 

Table 3-10. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994-1996, 1998 CSFII: All Sources (mL/day) ...........................................................................3-31
 

Table 3-11. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994-1996, 1998 CSFII: Community Water (mL/kg-day) ...........................................................3-32
 

Table 3-12. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994-1996, 1998 CSFII: Bottled Water (mL/kg-day) ..................................................................3-33
 

Table 3-13. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994-1996, 1998 CSFII: Other Sources (mL/kg-day)..................................................................3-34
 

Table 3-14. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994-1996, 1998 CSFII: All Sources (mL/kg-day)......................................................................3-35
 

Table 3-15. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994–1996, 1998 CSFII: Community Water (mL/day)................................................................3-36
 

Table 3-16. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994–1996, 1998 CSFII: Bottled Water (mL/day).......................................................................3-37
 

Table 3-17. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994–1996, 1998 CSFII: Other Sources (mL/day) ......................................................................3-38
 

Table 3-18. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

1994–1996, 1998 CSFII: All Sources (mL/day) ..........................................................................3-39
 

Table 3-19. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on 1994–1996,
 

1998 CSFII: Community Water (mL/kg-day) ..............................................................................3-40
 

Table 3-20. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on 1994–1996,
 

1998 CSFII: Bottled Water (mL/kg-day) .....................................................................................3-41
 

Table 3-21. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on 1994–1996,
 

1998 CSFII: Other Sources (mL/kg-day).....................................................................................3-42
 

Table 3-22. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on 1994–1996,
 

1998 CSFII: All Sources (mL/kg-day) .........................................................................................3-43
 

Table 3-23. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: Community Water (mL/day) ...................................................................3-44
 

Table 3-24. Per Capita Estimates of Combined Direct Water Ingestion Based on NHANES 2003–
 

2006: Bottled Water (mL/day) .....................................................................................................3-45
 

Table 3-25. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: Other Sources (mL/day)..........................................................................3-46
 

Table 3-26. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: All Sources (mL/day) ..............................................................................3-47
 

Table 3-27. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on 

NHANES 2003–2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and 

95th Percentiles: All Sources (mL/day).........................................................................................3-48
 

Table 3-28. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: Community Water (mL/kg-day)..............................................................3-49
 

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Front Matter 

Table 3-29. Per Capita Estimates of Combined Direct Water Ingestion Based on NHANES 2003– 

2006: Bottled Water (mL/kg-day) ................................................................................................3-50
 

Table 3-30. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: Other Sources (mL/kg-day) ....................................................................3-51
 

Table 3-31. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: All Sources (mL/kg-day).........................................................................3-52
 

Table 3-32. Per Capita Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and 

95th Percentiles: All Sources (mL/kg-day) ...................................................................................3-53
 

Table 3-33. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on 

NHANES 2003–2006: Community Water (mL/day) ...................................................................3-54
 

Table 3-34. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: Bottled Water (mL/day) ..........................................................................3-55
 

Table 3-35. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: Other Sources (mL/day)..........................................................................3-56
 

Table 3-36. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006: All Sources (mL/day) ..............................................................................3-57
 

Table 3-37. Consumer-Only Estimates of Combined Direct and Indirect Water Ingestion Based on
 

NHANES 2003–2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and 

95th Percentiles: All Sources (mL/day).........................................................................................3-58
 

Table 3-38. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
 

2003–2006: Community Water (mL/kg-day) ...............................................................................3-59
 

Table 3-39. Consumer-Only Estimates of Direct Water Ingestion Based on NHANES 2003–2006:
 

Bottled Water (mL/kg-day) ..........................................................................................................3-60
 

Table 3-40. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
 

2003–2006: Other Sources (mL/kg-day)......................................................................................3-61
 

Table 3-41. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
 

2003–2006: All Sources (mL/kg-day)..........................................................................................3-62
 

Table 3-42. Consumer-Only Estimates of Direct and Indirect Water Ingestion Based on NHANES
 

2003–2006, Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th 

Percentiles: All Sources (mL/kg-day) ..........................................................................................3-63
 

Table 3-43. Assumed Tap Water Content of Beverages in Great Britain ........................................................3-64
 

Table 3-44. Intake of Total Liquid, Total Tap Water, and Various Beverages (L/day) by the British
 

Population ....................................................................................................................................3-65
 

Table 3-45. Summary of Total Liquid and Total Tap Water Intake for Males and Females (L/day) in
 

Great Britain.................................................................................................................................3-66
 

Table 3-46. Daily Total Tap Water Intake Distribution for Canadians, by Age Group (approx. 0.20-L 

increments, both sexes, combined seasons) .................................................................................3-67
 

Table 3-47. Average Daily Tap Water Intake of Canadians (expressed as mL/kg body weight).....................3-68
 

Table 3-48. Average Daily Total Tap Water Intake of Canadians, by Age and Season (L/day) ......................3-68
 

Table 3-49. Average Daily Total Tap Water Intake of Canadians as a Function of Level of Physical
 

Activity at Work and in Spare Time (16 years and older, combined seasons, L/day) ..................3-69
 

Table 3-50. Average Daily Tap Water Intake by Canadians, Apportioned Among Various Beverages
 

(both sexes, by age, combined seasons, L/day)............................................................................3-69
 

Table 3-51. Intake Rates of Total Fluids and Total Tap Water by Age Group .................................................3-70
 

Table 3-52. Mean and Standard Error for the Daily Intake of Beverages and Tap Water by Age ...................3-70
 

Table 3-53. Average Total Tap Water Intake Rate by Sex, Age, and Geographic Area...................................3-71
 

Table 3-54. Frequency Distribution of Total Tap Water Intake Rates .............................................................3-71
 

Table 3-55. Total Tap Water Intake (mL/day) for Both Sexes Combined .......................................................3-72
 

Table 3-56. Total Tap Water Intake (mL/kg-day) for Both Sexes Combined..................................................3-73
 

Table 3-57. Summary of Tap Water Intake by Age .........................................................................................3-74
 

Table 3-58. Total Tap Water Intake (as % of total water intake) by Broad Age Category...............................3-74
 

Table 3-59. General Dietary Sources of Tap Water for Both Sexes ................................................................3-75
 

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Table 3-60. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Rates ......................3-76
 

Table 3-61. Estimated Quantiles and Means for Total Tap Water Intake Rates (mL/day)...............................3-76
 

Table 3-62 . Water Ingested (mL/day) From Water by Itself and Water Added to Other Beverages and
 

Foods............................................................................................................................................3-77
 

Table 3-63. Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data From 1989–1991 

(mL/day) ......................................................................................................................................3-78
 

Table 3-64. Number of Respondents That Consumed Tap Water at a Specified Daily Frequency .................3-79
 

Table 3-65. Number of Respondents That Consumed Juice Reconstituted With Tap Water at a 

Specified Daily Frequency...........................................................................................................3-80
 

Table 3-66. Mean (standard error) Water and Drink Consumption (mL/kg-day) by Race/Ethnicity ..............3-81
 

Table 3-67. Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and
 

Poverty Category .........................................................................................................................3-82
 

Table 3-68. Intake of Water From Various Sources in 2- to 13-Year-Old Participants of the DONALD
 

Study, 1985-1999 .........................................................................................................................3-83
 

Table 3-69. Mean (±standard error) Fluid Intake (mL/kg-day) by Children Aged 1 to 10 years,
 

NHANES III, 1988–1994 ............................................................................................................3-83
 

Table 3-70. Estimated Mean (±standard error) Amount of Total Fluid and Plain Water Intake Among 

Children Aged 1 to 10 Years by Age, Sex, Race/Ethnicity, Poverty Income Ratio, Region, 

and Urbanicity (NHANES III, 1988–1994) .................................................................................3-84
 

Table 3-71. Tap Water Intake in Breast-Fed and Formula-Fed Infants and Mixed-Fed Young Children 

at Different Age Points.................................................................................................................3-85
 

Table 3-72. Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes
 

(mL/day) for Children With Returned Questionnaires.................................................................3-86
 

Table 3-73. Mean (±standard deviation) Daily Beverage Intakes Reported on Beverage Frequency
 

Questionnaire and 3-Day Food and Beverage Diaries .................................................................3-87
 

Table 3-74. Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study)........3-88
 

Table 3-75. Per Capita Estimates of Direct and Indirect Water Intake From All Sources by Pregnant,
 

Lactating, and Childbearing Age Women (mL/kg-day) ...............................................................3-89
 

Table 3-76. Per Capita Estimates of Direct and Indirect Water Intake From All Sources by Pregnant,
 

Lactating, and Childbearing Age Women (mL/day) ....................................................................3-90
 

Table 3-77. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
 

Lactating, and Childbearing Age Women (mL/kg-day) ...............................................................3-90
 

Table 3-78. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
 

Lactating, and Childbearing Age Women (mL/day) ....................................................................3-91
 

Table 3-79. Estimates of Consumer-Only Direct and Indirect Water Intake from All Sources by
 

Pregnant, Lactating, and Childbearing Age Women (mL/kg-day) ...............................................3-91
 

Table 3-80. Estimates of Consumer-Only Direct and Indirect Water Intake From All Sources by
 

Pregnant, Lactating, and Childbearing Age Women (mL/day) ....................................................3-92
 

Table 3-81. Consumer-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
 

Lactating, and Childbearing Age Women (mL/kg-day) ...............................................................3-92
 

Table 3-82. Consumer-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant,
 

Lactating, and Childbearing Age Women (mL/day) ....................................................................3-93
 

Table 3-83. Total Fluid Intake of Women 15 to 49 Years Old.........................................................................3-93
 

Table 3-84. Total Tap Water Intake of Women 15 to 49 Years Old .................................................................3-94
 

Table 3-85. Total Fluid (mL/day) Derived from Various Dietary Sources by Women Aged 15 to 49 

Years.............................................................................................................................................3-94
 

Table 3-86. Total Tap Water and Bottled Water Intake by Pregnant Women (L/day) .....................................3-95
 

Table 3-87. Percentage of Mean Water Intake Consumed as Unfiltered and Filtered Tap Water by
 

Pregnant Women ..........................................................................................................................3-97
 

Table 3-88. Water Intake at Various Activity Levels (L/hour) ........................................................................3-99
 

Table 3-89. Planning Factors for Individual Tap Water Consumption ............................................................3-99
 

Table 3-90. Pool Water Ingestion by Swimmers ...........................................................................................3-100
 

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Table 3-91. Arithmetic Mean (maximum) Number of Dives per Diver and Volume of Water Ingested 

(mL/dive) ...................................................................................................................................3-100
 

Table 3-92. Exposure Parameters for Swimmers in Swimming Pools, Freshwater, and Seawater ...............3-101
 

Table 3-93. Estimated Water Ingestion During Water Recreation Activities (mL/hr)...................................3-101
 

Page Exposure Factors Handbook 

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Exposure Factors Handbook 

Front Matter 

4. NON-DIETARY INGESTION FACTORS ..................................................................................................4-1
 

4.1. INTRODUCTION .........................................................................................................................4-1
 

4.2. RECOMMENDATIONS ...............................................................................................................4-2
 

4.3. NON-DIETARY INGESTION—MOUTHING FREQUENCY STUDIES ...................................4-5
 

4.3.1. Key Studies of Mouthing Frequency ...............................................................................4-5
 

4.3.1.1. Zartarian et al. (1997a)/Zartarian et al. (1997b)/Zartarian et al. (1998) ............4-5
 

4.3.1.2. Reed et al. (1999) ..............................................................................................4-5
 

4.3.1.3. Freeman et al. (2001).........................................................................................4-6
 

4.3.1.4. Tulve et al. (2002) .............................................................................................4-6
 

4.3.1.5. AuYeung et al. (2004) .......................................................................................4-7
 

4.3.1.6. Black et al. (2005) .............................................................................................4-7
 

4.3.1.7. Xue et al. (2007)................................................................................................4-8
 

4.3.1.8. Beamer et al. (2008) ..........................................................................................4-9
 

4.3.1.9. Xue et al. (2010)................................................................................................4-9
 

4.3.2. Relevant Studies of Mouthing Frequency......................................................................4-10
 

4.3.2.1. Davis et al. (1995) ...........................................................................................4-10
 

4.3.2.2. Lew and Butterworth (1997) ...........................................................................4-11
 

4.3.2.3. Tudella et al. (2000).........................................................................................4-11
 

4.3.2.4. Ko et al. (2007)................................................................................................4-11
 

4.3.2.5. Nicas and Best (2008) .....................................................................................4-12
 

4.4. NON-DIETARY INGESTION—MOUTHING DURATION STUDIES ....................................4-12
 

4.4.1. Key Mouthing Duration Studies ....................................................................................4-12
 

4.4.1.1. Juberg et al. (2001)..........................................................................................4-12
 

4.4.1.2. Greene (2002)..................................................................................................4-13
 

4.4.1.3. Beamer et al. (2008) ........................................................................................4-14
 

4.4.2. Relevant Mouthing Duration Studies.............................................................................4-14
 

4.4.2.1. Barr et al. (1994) .............................................................................................4-14
 

4.4.2.2. Zartarian et al. (1997a)/Zartarian et al. (1997b)/Zartarian et al. (1998) ..........4-15
 

4.4.2.3. Groot et al. (1998) ...........................................................................................4-15
 

4.4.2.4. Smith and Norris (2003)/Norris and Smith (2002)..........................................4-16
 

4.4.2.5. AuYeung et al. (2004) .....................................................................................4-17
 

4.5. MOUTHING PREVALENCE STUDIES ....................................................................................4-17
 

4.5.1. Stanek et al. (1998)........................................................................................................4-17
 

4.5.2. Warren et al. (2000) .......................................................................................................4-18
 

4.6. REFERENCES FOR CHAPTER 4..............................................................................................4-18
 

Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration..................................4-3
 

Table 4-2. Confidence in Mouthing Frequency and Duration Recommendations ..........................................4-4
 

Table 4-3. New Jersey Children’s Mouthing Frequency (contacts/hour) From Video-Transcription............4-21
 

Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age ...................4-21
 

Table 4-5. Video-Transcription Median (Mean) Observed Mouthing in 19 Minnesota Children
 

(contacts/hour), by Age ................................................................................................................4-21
 

Table 4-6. Variability in Objects Mouthed by Washington State Children (contacts/hour)...........................4-22
 

Table 4-7. Indoor Mouthing Frequency (contacts per contacts/hour), Video-Transcription of 9 

Children by Age ...........................................................................................................................4-23
 

Table 4-8. Outdoor Mouthing Frequency (contacts per contacts/hour), Video-Transcription of 38 

Children, by Age ..........................................................................................................................4-23
 

Table 4-9. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD), by
 

Age...............................................................................................................................................4-24
 

Table 4-10. Indoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various
 

Studies, by Age ............................................................................................................................4-24
 

Table 4-11. Outdoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various
 

Studies, by Age ............................................................................................................................4-24
 

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Table 4-12. Object/Surface-to-Mouth Contact Frequency for Infants and Toddlers (events/hour) 

(N = 23)........................................................................................................................................4-25
 

Table 4-13. Distributions Mouthing Frequency and Duration for Non-Dietary Objects With
 

Significant Differences (p < 0.05) Between Infants and Toddlers ...............................................4-26
 

Table 4-14. Indoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various
 

Studies, by Age ............................................................................................................................4-27
 

Table 4-15. Outdoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various
 

Studies, by Age ............................................................................................................................4-27
 

Table 4-16. Survey-Reported Mouthing Behaviors for 92 Washington State Children ..................................4-28
 

Table 4-17. Number of Hand Contacts Observed in Adults During a Continuous 3-Hour Period.................4-28
 

Table 4-18. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and
 

Other Objects ...............................................................................................................................4-29
 

Table 4-19. Percent of Houston-Area and Chicago-Area Children Observed Mouthing, by Category
 

and Child’s Age............................................................................................................................4-29
 

Table 4-20. Estimates of Mouthing Time for Various Objects for Infants and Toddlers (minutes/hour),
 

by Age ..........................................................................................................................................4-30
 

Table 4-21. Object/Surface-to-Hands and Mouth Contact Duration for Infants and Toddlers
 

(minutes/hour) (N = 23) ...............................................................................................................4-31
 

Table 4-22. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without 

Pacifier (minutes/day), by Age.....................................................................................................4-31
 

Table 4-23. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys, and
 

Other Objects (hours:minutes:seconds) .......................................................................................4-31
 

Table 4-24. Outdoor Median Mouthing Duration (seconds/contact), Video-Transcription of 38 

Children, by Age ..........................................................................................................................4-31
 

Table 4-25. Indoor Mouthing Duration (minutes/hour), Video-Transcription of Nine Children With 

>15 Minutes in View Indoors.......................................................................................................4-31
 

Table 4-26. Outdoor Mouthing Duration (minutes/hour), Video-Transcription of 38 Children, by Age ........4-31
 

Table 4-27. Reported Daily Prevalence of Massachusetts Children’s Non-Food Mouthing/Ingestion
 

Behaviors .....................................................................................................................................4-31
 

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5. SOIL AND DUST INGESTION ..................................................................................................................5-1
 

5.1. INTRODUCTION .........................................................................................................................5-1
 

5.2. RECOMMENDATIONS ...............................................................................................................5-3
 

5.3. KEY AND RELEVANT STUDIES ...............................................................................................5-7
 

5.3.1. Methodologies Used in Key Studies................................................................................5-7
 

5.3.1.1. Tracer Element Methodology............................................................................5-7
 

5.3.1.2. Biokinetic Model Comparison Methodology ....................................................5-8
 

5.3.1.3. Activity Pattern Methodology ...........................................................................5-8
 

5.3.2. Key Studies of Primary Analysis .....................................................................................5-9
 

5.3.2.1. Vermeer and Frate (1979)..................................................................................5-9
 

5.3.2.2. Calabrese et al. (1989).......................................................................................5-9
 

5.3.2.3. Van Wïjnen et al. (1990)..................................................................................5-10
 

5.3.2.4. Davis et al. (1990) ...........................................................................................5-10
 

5.3.2.5. Calabrese et al. (1997a) ...................................................................................5-11
 

5.3.2.6. Stanek et al. (1998)..........................................................................................5-12
 

5.3.2.7. Davis and Mirick (2006) .................................................................................5-12
 

5.3.3. Key Studies of Secondary Analysis ...............................................................................5-13
 

5.3.3.1. Wong (1988) and Stanek (1993)......................................................................5-13
 

5.3.3.2. Calabrese and Stanek (1995) ...........................................................................5-14
 

5.3.3.3. Stanek and Calabrese (1995a) .........................................................................5-14
 

5.3.3.4. Hogan et al. (1998)..........................................................................................5-15

5.3.3.5. Özkaynak et al. (2010) ....................................................................................5-16
 

5.3.4. Relevant Studies of Primary Analysis............................................................................5-16
 

5.3.4.1. Dickins and Ford (1942)..................................................................................5-17
 

5.3.4.2. Ferguson and Keaton (1950) ...........................................................................5-17
 

5.3.4.3. Cooper (1957)..................................................................................................5-17
 

5.3.4.4. Barltrop (1966)................................................................................................5-17
 

5.3.4.5. Bruhn and Pangborn (1971) ............................................................................5-17
 

5.3.4.6. Robischon (1971) ............................................................................................5-18
 

5.3.4.7. Bronstein and Dollar (1974)............................................................................5-18
 

5.3.4.8. Hook (1978) ....................................................................................................5-18
 

5.3.4.9. Binder et al. (1986)..........................................................................................5-18
 

5.3.4.10.Clausing et al. (1987) ......................................................................................5-19
 

5.3.4.11.Calabrese et al. (1990).....................................................................................5-20
 

5.3.4.12.Cooksey (1995) ...............................................................................................5-20
 

5.3.4.13.Smulian et al. (1995) .......................................................................................5-20
 

5.3.4.14.Grigsby et al. (1999)........................................................................................5-21
 

5.3.4.15.Ward and Kutner (1999)..................................................................................5-21
 

5.3.4.16.Simpson et al. (2000).......................................................................................5-21
 

5.3.4.17.Obialo et al. (2001)..........................................................................................5-22
 

5.3.4.18.Klitzman et al. (2002)......................................................................................5-22
 

5.3.5. Relevant Studies of Secondary Analysis........................................................................5-22
 

5.3.5.1. Stanek and Calabrese (1995b) .........................................................................5-22
 

5.3.5.2. Calabrese and Stanek (1992b) .........................................................................5-23
 

5.3.5.3. Calabrese et al. (1996).....................................................................................5-23
 

5.3.5.4. Stanek et al. (1999)..........................................................................................5-23
 

5.3.5.5. Stanek and Calabrese (2000) ...........................................................................5-23
 

5.3.5.6. Stanek et al. (2001a)........................................................................................5-23
 

5.3.5.7. Stanek et al. (2001b)........................................................................................5-24
 

5.3.5.8. Von Lindern et al. (2003).................................................................................5-24
 

5.3.5.9. Gavrelis et al. (2011) .......................................................................................5-24
 

5.4. LIMITATIONS OF STUDY METHODOLOGIES .....................................................................5-25
 

5.4.1. Tracer Element Methodology ........................................................................................5-25
 

5.4.2. Biokinetic Model Comparison Methodology ................................................................5-28
 

5.4.3. Activity Pattern Methodology .......................................................................................5-28
 

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5.4.4. Key Studies: Representativeness of the U.S. Population...............................................5-29
 

5.5. SUMMARY OF SOIL AND DUST INGESTION ESTIMATES FROM KEY STUDIES..........5-31
 

5.6. DERIVATION OF RECOMMENDED SOIL AND DUST INGESTION VALUES ...................5-31
 

5.6.1. Central Tendency Soil and Dust Ingestion Recommendations ......................................5-31
 

5.6.2. Upper Percentile, Soil Pica, and Geophagy Recommendations.....................................5-33
 

5.7. REFERENCES FOR CHAPTER 5..............................................................................................5-34
 

Table 5-1. Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion (mg/day)..........................5-5
 

Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust ..................................................5-6
 

Table 5-3. Soil, Dust, and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study
 

Children .......................................................................................................................................5-39
 

Table 5-4. Amherst, Massachusetts Soil-Pica Child’s Daily Ingestion Estimates by Tracer and by
 

Week (mg/day).............................................................................................................................5-40
 

Table 5-5. Van Wïjnen et al. (1990) Limiting Tracer Method (LTM) Soil Ingestion Estimates for
 

Sample of Dutch Children............................................................................................................5-40
 

Table 5-6. Estimated Geometric Mean Limiting Tracer Method (LTM) Soil Ingestion Values of
 

Children Attending Daycare Centers According to Age, Weather Category, and Sampling 

Period...........................................................................................................................................5-41
 

Table 5-7. Estimated Soil Ingestion for Sample of Washington State Children............................................5-41
 

Table 5-8. Soil Ingestion Estimates for 64 Anaconda Children ....................................................................5-42
 

Table 5-9. Soil Ingestion Estimates for Massachusetts Children Displaying Soil Pica Behavior
 

(mg/day).......................................................................................................................................5-42
 

Table 5-10. Average Daily Soil and Dust Ingestion Estimate (mg/day)..........................................................5-43
 

Table 5-11. Mean and Median Soil Ingestion (mg/day) by Family Member ..................................................5-43
 

Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children....................................5-44
 

Table 5-13. Positive/Negative Error (bias) in Soil Ingestion Estimates in Calabrese et al. (1989)
 

Study: Effect on Mean Soil Ingestion Estimate (mg/day)............................................................5-44
 

Table 5-14. Predicted Soil and Dust Ingestion Rates for Children Age 3 to <6 Years (mg/day).....................5-45
 

Table 5-15. Estimated Daily Soil Ingestion for East Helena, Montana Children............................................5-45
 

Table 5-16. Estimated Soil Ingestion for Sample of Dutch Nursery School Children ....................................5-46
 

Table 5-17. Estimated Soil Ingestion for Sample of Dutch Hospitalized, Bedridden Children ......................5-46
 

Table 5-18. Items Ingested by Low-Income Mexican-Born Women Who Practiced Pica During
 

Pregnancy in the United States (N = 46)......................................................................................5-47
 

Table 5-19. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 Children
 

(mg/day).......................................................................................................................................5-47
 

Table 5-20. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64 

Subjects Projected Over 365 Days...............................................................................................5-48
 

Table 5-21. Prevalence of Non-Food Consumption by Substance for NHANES I and NHANES II .............5-48
 

Table 5-22. Summary of Estimates of Soil and Dust Ingestion by Adults and Children (0.5 to 14 years
 

old) From Key Studies (mg/day)..................................................................................................5-49
 

Table 5-23. Comparison of Hogan et al. (1998) Study Subjects’ Predicted Blood Lead Levels With
 

Actual Measured Blood Lead Levels, and Default Soil + Dust Intakes Used in IEUBK 

Modeling......................................................................................................................................5-49
 

Figure 5-1. Prevalence of Non-Food Substance Consumption by Age, NHANES I and NHANES II...........5-50
 

Figure 5-2. Prevalence of Non-Food Substance Consumption by Race, NHANES I and NHANES II .........5-51
 

Figure 5-3. Prevalence of Non-Food Substance Consumption by Income, NHANES I and NHANES
 

II...................................................................................................................................................5-52
 

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6. INHALATION RATES ................................................................................................................................6-1
 

6.1. INTRODUCTION .........................................................................................................................6-1
 

6.2. RECOMMENDATIONS ...............................................................................................................6-2
 

6.3. KEY INHALATION RATE STUDIES..........................................................................................6-7
 

6.3.1. Brochu et al. (2006a) .......................................................................................................6-7
 

6.3.2. Arcus-Arth and Blaisdell (2007)......................................................................................6-7
 

6.3.3. Stifelman (2007) ..............................................................................................................6-9
 

6.3.4. U.S. EPA (2009)...............................................................................................................6-9
 

6.3.5. Key Studies Combined ..................................................................................................6-10
 

6.4. RELEVANT INHALATION RATE STUDIES............................................................................6-10
 

6.4.1. International Commission on Radiological Protection (ICRP) (1981) ..........................6-10
 

6.4.2. U.S. EPA (1985).............................................................................................................6-11
 

6.4.3. Shamoo et al. (1990)......................................................................................................6-11
 

6.4.4. Shamoo et al. (1991)......................................................................................................6-12
 

6.4.5. Linn et al. (1992) ...........................................................................................................6-13
 

6.4.6. Shamoo et al. (1992)......................................................................................................6-14
 

6.4.7. Spier et al. (1992) ..........................................................................................................6-14
 

6.4.8. Adams (1993) ................................................................................................................6-15
 

6.4.9. Layton (1993) ................................................................................................................6-16
 

6.4.10. Linn et al. (1993) ...........................................................................................................6-17
 

6.4.11. Rusconi et al. (1994)......................................................................................................6-18
 

6.4.12. Price et al. (2003)...........................................................................................................6-19
 

6.4.13. Brochu et al. (2006b) .....................................................................................................6-19
 

6.4.14. Allan et al. (2009)..........................................................................................................6-20
 

6.5. REFERENCES FOR CHAPTER 6..............................................................................................6-21
 

Table 6-1. Recommended Long-Term Exposure Values for Inhalation (males and females combined).........6-1
 

Table 6-2. Recommended Short-Term Exposure Values for Inhalation (males and females combined).........6-4
 

Table 6-3. Confidence in Recommendations for Long- and Short-Term Inhalation Rates .............................6-6
 

Table 6-4. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3

/day) for 

Free-Living Normal-Weight Males and Females Aged 2.6 Months to 96 Years..........................6-24
 

Table 6-5. Mean and 95th Percentile Inhalation Rate Values (m3

/day) for Free-Living Normal-Weight
 

Males, Females, and Males and Females Combined....................................................................6-25
 

Table 6-6. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3

/day) for 

Free-Living Normal-Weight and Overweight/Obese Males and Females Aged 4 to 96
 

Years.............................................................................................................................................6-27
 

Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) per Unit of
 

Body Weight (m3

/kg-day) for Free-Living Normal-Weight Males and Females 

Aged 2.6 Months to 96 Years.......................................................................................................6-28
 

Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3

/kg-day) for 

Free-Living Normal-Weight and Overweight/Obese Males and Females Aged 4 to 96
 

Years.............................................................................................................................................6-29
 

Table 6-9. Physiological Daily Inhalation Rates (PDIRs) for Newborns Aged 1 Month or Less .................6-30
 

Table 6-10. Non-Normalized Daily Inhalation Rates (m3

/day) Derived Using Layton’s (1993) Method 

and CSFII Energy Intake Data .....................................................................................................6-31
 

Table 6-11. Mean and 95th Percentile Inhalation Rate Values (m3

/day) for Males and Females
 

Combined.....................................................................................................................................6-32
 

Table 6-12. Summary of Institute of Medicine (IOM) Energy Expenditure Recommendations for
 

Active and Very Active People With Equivalent Inhalation Rates...............................................6-33
 

Table 6-13. Mean Inhalation Rate Values (m3

/day) for Males, Females, and
 

Males and Females Combined .....................................................................................................6-34
 

Table 6-14. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category .................6-35
 

Table 6-15. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Category..............6-36
 

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Table 6-16. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males, Females, and 

Males and Females Combined .....................................................................................................6-37
 

Table 6-17. Descriptive Statistics for Average Ventilation Rate, Unadjusted for Body Weight, While
 

Performing Activities Within the Specified Activity Category, for Males by Age Category .......6-39
 

Table 6-18. Descriptive Statistics for Average Ventilation Rate, Adjusted for Body Weight, While
 

Performing Activities Within the Specified Activity Category, for Males by Age Category .......6-43
 

Table 6-19. Descriptive Statistics for Average Ventilation Rate, Unadjusted for Body Weight, While
 

Performing Activities Within the Specified Activity Category, for Females by Age 

Category.......................................................................................................................................6-47
 

Table 6-20. Descriptive Statistics for Average Ventilation Rate, Adjusted for Body Weight, While
 

Performing Activities Within the Specified Activity Category, for Females by Age 

Category.......................................................................................................................................6-48
 

Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
 

Within the Specified Activity Category, by Age for Males..........................................................6-48
 

Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities
 

Within the Specified Activity Category, by Age for Females ......................................................6-48
 

Table 6-23. Mean Inhalation Rate Values (m3

/day) From Key Studies for
 

Males and Females Combined .....................................................................................................6-48
 

Table 6-24. 95th Percentile Inhalation Rate Values (m3

/day) from Key Studies for 

Males and Females Combined .....................................................................................................6-48
 

Table 6-25. Concordance of Age Groupings Among Key Studies ..................................................................6-48
 

Table 6-26. Time Weighted Average of Daily Inhalation Rates (DIRs) Estimated From Daily
 

Activities......................................................................................................................................6-48
 

Table 6-27. Selected Inhalation Rate Values During Different Activity Levels Obtained From Various
 

Literature Sources ........................................................................................................................6-48
 

Table 6-28. Summary of Human Inhalation Rates by Activity Level (m3

/hour).............................................6-48
 

Table 6-29. Estimated Minute Ventilation Associated with Activity Level for Average Male Adult ..............6-48
 

Table 6-30. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for All
 

Age Groups ..................................................................................................................................6-48
 

Table 6-31. Summary of Daily Inhalation Rates (DIRs) Grouped by Age and Activity Level .......................6-48
 

Table 6-32. Distribution Pattern of Predicted Ventilation Rate (VR) and Equivalent Ventilation Rate
 

(EVR) for 20 Outdoor Workers....................................................................................................6-48
 

Table 6-33. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor
 

Workers........................................................................................................................................6-48
 

Table 6-34. Calibration and Field Protocols for Self-Monitoring of Activities
 

Grouped by Subject Panels ..........................................................................................................6-48
 

Table 6-35. Subject Panel Inhalation Rates by Mean Ventilation Rate (VR), Upper Percentiles, and
 

Self-Estimated Breathing Rates ...................................................................................................6-48
 

Table 6-36. Actual Inhalation Rates Measured at Four Ventilation Levels.....................................................6-48
 

Table 6-37. Distribution of Predicted Inhalation Rates by Location and Activity Levels for
 

Elementary and High School Students.........................................................................................6-48
 

Table 6-38. Average Hours Spent per Day in a Given Location and Activity Level for Elementary and
 

High School Students...................................................................................................................6-48
 

Table 6-39. Distribution Patterns of Daily Inhalation Rates (DIRs) for Elementary (EL) and High
 

School (HS) Students Grouped by Activity Level .......................................................................6-48
 

Table 6-40. Mean Minute Inhalation Rate (m3

/minute) by Group and Activity for
 

Laboratory Protocols....................................................................................................................6-48
 

Table 6-41. Mean Minute Inhalation Rate (m3

/minute) by Group and Activity for Field Protocols...............6-48
 

Table 6-42. Summary of Average Inhalation Rates (m3

/hour) by Age Group and Activity Levels for
 

Laboratory Protocols....................................................................................................................6-48
 

Table 6-43. Summary of Average Inhalation Rates (m3

/hour) by Age Group and Activity Levels in 

Field Protocols .............................................................................................................................6-48
 

Table 6-44. Comparisons of Estimated Basal Metabolic Rates (BMR) With Average Food-Energy 

Intakes (EFDs) for Individuals Sampled in the 1977−1978 NFCS..............................................6-48
 

Table 6-45. Daily Inhalation Rates (DIRs) Calculated From Food-Energy Intakes (EFDs) ...........................6-48
 

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Table 6-46. Statistics of the Age/Sex Cohorts Used to Develop Regression Equations for Predicting
 

Basal Metabolic Rates (BMR) .....................................................................................................6-48
 

Table 6-47. Daily Inhalation Rates (DIRs) Obtained From the Ratios of Total Energy
 

Expenditure to Basal Metabolic Rate (BMR) ..............................................................................6-48
 

Table 6-48. Daily Inhalation Rates (DIRs) Based on Time-Activity Survey ..................................................6-48
 

Table 6-49. Inhalation Rates for Short-Term Exposures .................................................................................6-48
 

Table 6-50. Distributions of Individual and Group Inhalation/Ventilation Rate (VR) for
 

Outdoor Workers..........................................................................................................................6-48
 

Table 6-51. Individual Mean Inhalation Rate (m3

/hour) by Self-Estimated Breathing Rate or Job
 

Activity Category for Outdoor Workers.......................................................................................6-48
 

Table 6-52. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in
 

618 Infants and Children Grouped in Classes of Age ..................................................................6-48
 

Table 6-53. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3

/day) Percentiles for
 

Free-Living Underweight Adolescents and Women Aged 11 to 55 Years
 

During Pregnancy and Postpartum Weeks ...................................................................................6-48
 

Table 6-54. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3

/day) Percentiles for
 

Free-Living Normal-Weight Adolescents and Women Aged 11 to 55 Years
 

During Pregnancy and Postpartum Weeks ...................................................................................6-48
 

Table 6-55. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3

/day) Percentiles for
 

Free-Living Overweight/Obese Adolescents and Women Aged 11 to 55 Years
 

During Pregnancy and Postpartum Weeks ...................................................................................6-48
 

Table 6-56. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3

/kg-day) Percentiles for
 

Free-Living Underweight Adolescents and Women Aged 11 to 55 Years
 

During Pregnancy and Postpartum Weeks ...................................................................................6-48
 

Table 6-57. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3

/kg-day) Percentiles for
 

Free-Living Normal-Weight and Women Aged 11 to 55 Years During Pregnancy and
 

Postpartum Weeks........................................................................................................................6-48
 

Table 6-58. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3

/kg-day) Percentiles for
 

Free-Living Overweight/Obese Adolescents and Women Aged 11 to 55 Years During 

Pregnancy and Postpartum Weeks ...............................................................................................6-48
 

Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Awake Subjects....... 6-48
 

Figure 6-2. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Asleep Subjects....... 6-48
 

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LIST OF TABLES .................................................................................................................................................... 7-iv
 

LIST OF FIGURES ....................................................................................................................................................7-v
 

7. DERMAL EXPOSURE FACTORS .............................................................................................................7-1
 

7.1. INTRODUCTION .........................................................................................................................7-1
 

7.2. RECOMMENDATIONS ...............................................................................................................7-2
 

7.2.1. Body Surface Area...........................................................................................................7-2
 

7.2.2. Adherence of Solids to Skin ............................................................................................7-3
 

7.2.3. Film Thickness of Liquids on Skin..................................................................................7-4
 

7.2.4. Residue Transfer ..............................................................................................................7-4
 

7.3. SURFACE AREA ........................................................................................................................7-13
 

7.3.1. Key Body Surface Area Studies.....................................................................................7-13
 

7.3.1.1. U.S. EPA (1985) ..............................................................................................7-13
 

7.3.1.2. Boniol et al. (2007)..........................................................................................7-13
 

7.3.1.3. U.S. EPA Analysis of NHANES 2005−2006 and 1999–2006 Data.................7-14
 

7.3.2. Relevant Body Surface Area Studies .............................................................................7-15
 

7.3.2.1. Murray and Burmaster (1992) .........................................................................7-15
 

7.3.2.2. Phillips et al. (1993) ........................................................................................7-15
 

7.3.2.3. Garlock et al. (1999)........................................................................................7-16
 

7.3.2.4. Wong et al. (2000) ...........................................................................................7-16
 

7.3.2.5. AuYeung et al. (2008) .....................................................................................7-16
 

7.4. ADHERENCE OF SOLIDS TO SKIN ........................................................................................7-17
 

7.4.1. Key Adherence of Solids to Skin Studies ......................................................................7-17
 

7.4.1.1. Kissel et al. (1996a).........................................................................................7-17
 

7.4.1.2. Holmes et al. (1999) ........................................................................................7-17
 

7.4.1.3. Shoaf et al. (2005a)..........................................................................................7-18
 

7.4.1.4. Shoaf et al. (2005b) .........................................................................................7-18
 

7.4.2. Relevant Adherence of Solids to Skin Studies...............................................................7-19
 

7.4.2.1. Harger (1979) ..................................................................................................7-19
 

7.4.2.2. Que Hee et al. (1985).......................................................................................7-19
 

7.4.2.3. Driver et al. (1989) ..........................................................................................7-19
 

7.4.2.4. Sedman (1989) ................................................................................................7-20
 

7.4.2.5. Finley et al. (1994) ..........................................................................................7-20
 

7.4.2.6. Kissel et al. (1996b).........................................................................................7-20
 

7.4.2.7. Holmes et al. (1996) ........................................................................................7-21
 

7.4.2.8. Kissel et al. (1998)...........................................................................................7-21
 

7.4.2.9. Rodes et al. (2001)...........................................................................................7-21
 

7.4.2.10.Edwards and Lioy (2001)................................................................................7-22
 

7.4.2.11.Choate et al. (2006) .........................................................................................7-22
 

7.4.2.12.Yamamoto et al. (2006) ...................................................................................7-23
 

7.4.2.13.Ferguson et al. (2008, 2009a, b, c) ..................................................................7-23
 

7.5. FILM THICKNESS OF LIQUIDS ON SKIN .............................................................................7-24
 

7.5.1. U.S. EPA (1987) and U.S. EPA (1992c).........................................................................7-24
 

7.6. RESIDUE TRANSFER ...............................................................................................................7-25
 

7.6.1. Residue Transfer Studies ...............................................................................................7-26
 

7.6.1.1. Ross et al. (1990).............................................................................................7-26
 

7.6.1.2. Ross et al. (1991).............................................................................................7-26
 

7.6.1.3. Formoli (1996) ................................................................................................7-26
 

7.6.1.4. Krieger et al. (2000) ........................................................................................7-27
 

7.6.1.5. Clothier (2000) ................................................................................................7-27
 

7.6.1.6. Bernard et al. (2001)........................................................................................7-28
 

7.6.1.7. Cohen-Hubal et al. (2005) ...............................................................................7-28
 

7.6.1.8. Cohen-Hubal et al. (2008) ...............................................................................7-28
 

7.6.1.9. Beamer et al. (2009) ........................................................................................7-29
 

7.7. OTHER FACTORS......................................................................................................................7-29
 

7.7.1. Frequency and Duration of Dermal (Hand) Contact......................................................7-29
 

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7.7.1.1. Zartarian et al. (1997)......................................................................................7-29
 

7.7.1.2. Reed et al. (1999) ............................................................................................7-30
 

7.7.1.3. Freeman et al. (2001).......................................................................................7-30
 

7.7.1.4. Freeman et al. (2005).......................................................................................7-30
 

7.7.1.5. AuYeung et al. (2006) .....................................................................................7-30
 

7.7.1.6. Ko et al. (2007)................................................................................................7-31
 

7.7.1.7. Beamer et al. (2008) ........................................................................................7-31
 

7.7.2. Thickness of the Skin.....................................................................................................7-32
 

7.8. REFERENCES FOR CHAPTER 7..............................................................................................7-32
 

APPENDIX 7A FORMULAS FOR TOTAL BODY SURFACE AREA..................................................................A-1
 

Table 7-1. Recommended Values for Total Body Surface Area, for Children (sexes combined) and 

Adults by Sex.................................................................................................................................7-5
 

Table 7-2. Recommended Values for Surface Area of Body Parts ..................................................................7-6
 

Table 7-3. Confidence in Recommendations for Body Surface Area..............................................................7-8
 

Table 7-4. Recommended Values for Mean Solids Adherence to Skin .........................................................7-10
 

Table 7-5. Confidence in Recommendations for Solids Adherence to Skin..................................................7-11
 

Table 7-6. Percentage of Total Body Surface Area by Body Part for Children (sexes combined) and
 

Adults by Sex...............................................................................................................................7-37
 

Table 7-7. Summary of Equation Parameters for Calculating Adult Body Surface Area..............................7-38
 

Table 7-8. Mean Proportion (%) of Children's Total Skin Surface Area, by Body Part ................................7-39
 

Table 7-9. Mean and Percentile Skin Surface Area (m2

) Derived From U.S. EPA Analysis of
 

NHANES 1999–2006 Males and Females Combined for Children <21 Years and 

NHANES 2005–2006 for Adults >21 Years.................................................................................7-40
 

Table 7-10. Mean and Percentile Skin Surface Area (m2

) Derived From U.S. EPA Analysis of
 

NHANES 1999–2006 for Children <21 Years and NHANES 2005–2006 for Adults >21 

Years, Males.................................................................................................................................7-41
 

Table 7-11. Mean and Percentile Skin Surface Area (m2

) Derived From U.S. EPA Analysis of
 

NHANES 1999–2006 for Children <21 Years and NHANES 2005–2006 for Adults >21 

Years, Females .............................................................................................................................7-42
 

Table 7-12. Surface Area of Adult Males (21 years and older) in Square Meters ...........................................7-43
 

Table 7-13. Surface Area of Adult Females (21 years and older) in Square Meters........................................7-44
 

Table 7-14. Statistical Results for Total Body Surface Area Distributions (m2

), for Adults............................7-45
 

Table 7-15. Descriptive Statistics for Surface Area/Body-Weight (SA/BW) Ratios (m2

/kg)..........................7-46
 

Table 7-16. Estimated Percent of Adult Skin Surface Exposed During Outdoor Activities............................7-47
 

Table 7-17. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities ..............................7-47
 

Table 7-18. Median per Contact Outdoor Fractional Surface Areas of the Hands, by Object, Both
 

Hands Combined..........................................................................................................................7-48
 

Table 7-19. Summary of Field Studies That Estimated Activity-Specific Adherence Rates...........................7-49
 

Table 7-20. Geometric Mean and Geometric Standard Deviations of Solids Adherence by Activity 

and Body Region..........................................................................................................................7-52
 

Table 7-21. Summary of Controlled Greenhouse Trials..................................................................................7-54
 

Table 7-22. Dermal Transfer Factors for Selected Contact Surface Types and Skin Wetness, Using
 

<80 μm Tagged ATD ....................................................................................................................7-54
 

Table 7-23. Comparison of Adherence (mg/cm2

) for Contact With Carpet and Aluminum Surfaces,
 

Averaged Across Pressure, Contact Time, Soil Type, and Soil Particle Size ...............................7-55
 

Table 7-24. Film Thickness Values of Selected Liquids Under Various Experimental Conditions
 

(10−3

cm) .......................................................................................................................................7-56
 

Table 7-25. Mean Transfer Efficiencies (%) ...................................................................................................7-57
 

Table 7-26. Transfer Efficiencies (%) for Dry, Water-Wetted, and Saliva-Wetted Palms and PUF
 

Roller ...........................................................................................................................................7-57
 

Table 7-27. Incremental and Overall Surface-to-Hand Transfer Efficiencies (%) ..........................................7-58
 

Table 7-28. Lognormal Distributions for Modeling Transfer Efficiencies (fraction)......................................7-59
 

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Table 7-29. Hand-to-Object/Surface Contact—Frequency (contacts/hour) ....................................................7-59
 

Table 7-30. Hand-to-Objects/Surfaces—Frequency (contacts/hour) ..............................................................7-60
 

Table 7-31. Median (mean ± SD) Hand Contact Frequency With Clothing, Surfaces, or Objects
 

(contacts/hour) .............................................................................................................................7-60
 

Table 7-32. Hand Contact With Objects/Surfaces—Frequency (contacts/hour) .............................................7-60
 

Table 7-33. Outdoor Hand Contact With Objects/Surfaces, Children 1 to 6 Years.........................................7-61
 

Table 7-34. Indoor Hand Contact With Objects/Surfaces—Frequency, Children 1 to 6 Years (median
 

contacts/hour)...............................................................................................................................7-62
 

Table 7-35. Outdoor Hand Contact With Surfaces—Frequency, Children 1 to 5 Years (contacts/hour).........7-62
 

Table 7-36. Hand Contact With Object/Surfaces, Infants and Toddlers..........................................................7-63
 

Figure 7-1. Frequency Distributions for the Surface Area of Men and Women. ............................................7-64
 

Figure 7-2. Skin Coverage as Determined by Fluorescence Versus Body Part for Adults Transplanting
 

Plants and Children Playing in Wet Soils.....................................................................................7-65
 

Figure 7-3. Gravimetric Loading Versus Body Part for Adults Transplanting Plants in Wet Soil and
 

Children Playing in Wet and Dry Soils ........................................................................................7-65
 

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8.	 BODY-WEIGHT STUDIES.........................................................................................................................8-1
 

8.1.	 INTRODUCTION .........................................................................................................................8-1
 

8.2.	 RECOMMENDATIONS ...............................................................................................................8-1
 

8.3.	 KEY BODY-WEIGHT STUDY ....................................................................................................8-4
 

8.3.1.	 U.S. EPA Analysis of NHANES 1999−2006 Data ..........................................................8-4
 

8.4.	 RELEVANT GENERAL POPULATION BODY-WEIGHT STUDIES ........................................8-4
 

8.4.1.	 National Center for Health Statistics (NCHS) (1987)......................................................8-4
 

8.4.2.	 Brainard and Burmaster (1992) .......................................................................................8-5
 

8.4.3.	 Burmaster and Crouch (1997)..........................................................................................8-5
 

8.4.4.	 U.S. EPA (2000)...............................................................................................................8-6
 

8.4.5.	 Kuczmarski et al. (2002)..................................................................................................8-6
 

8.4.6.	 U.S. EPA (2004)...............................................................................................................8-6
 

8.4.7.	 Ogden et al. (2004) ..........................................................................................................8-7
 

8.4.8.	 Freedman et al. (2006).....................................................................................................8-7
 

8.4.9.	 Martin et al. (2007)..........................................................................................................8-7
 

8.4.10.	 Portier et al. (2007)..........................................................................................................8-8
 

8.4.11.	 Kahn and Stralka (2008)..................................................................................................8-8
 

8.5.	 RELEVANT STUDIES—PREGNANT WOMEN BODY-WEIGHT STUDIES ..........................8-8
 

8.5.1.	 Carmichael et al. (1997)...................................................................................................8-8
 

8.5.2.	 U.S. EPA Analysis of 1999−2006 NHANES Data on Body Weight of Pregnant
	

Women.............................................................................................................................8-9
 

8.6.	 RELEVANT FETAL WEIGHT STUDIES ....................................................................................8-9
 

8.6.1.	 Brenner et al. (1976)........................................................................................................8-9
 

8.6.2.	 Doubilet et al. (1997).....................................................................................................8-10
 

8.7.	 REFERENCES FOR CHAPTER 8..............................................................................................8-10
 

Table 8-1. Recommended Values for Body Weight ................................................................................................. 8-2
 

Table 8-2. Confidence in Recommendations for Body Weight................................................................................ 8-3
 

Table 8-3. Mean and Percentile Body Weights (kg) Derived From NHANES (1999−2006) ................................ 8-12
 

Table 8-4. Mean and Percentile Body Weights (kg) for Males Derived From NHANES (1999−2006)................ 8-13
 

Table 8-5. Mean and Percentile Body Weights (kg) for Females Derived From NHANES (1999−2006) ............ 8-14
 

Table 8-6. Weight in Kilograms for Males 2 Months−21 Years of Age―Number Examined, Mean, and
	

Selected Percentiles, by Age Category: United States, 1976–1980 ..................................................... 8-15
 

Table 8-7. Weight in Kilograms for Females 6 Months−21 Years of Age―Number Examined, Mean, and
	

Selected Percentiles, by Age Category: United States, 1976−1980 ..................................................... 8-16
 

Table 8-8. Statistics for Probability Plot Regression Analyses: Female Body Weights 6 Months to 70 Years
 

of Age................................................................................................................................................... 8-17
 

Table 8-9. Statistics for Probability Plot Regression Analyses: Male Body Weights 6 Months to 70 Years of
 

Age....................................................................................................................................................... 8-18
 

Table 8-10. Body-Weight Estimates (kg) by Age and Sex, U.S. Population Derived from NHANES III
 

(1988−1994)......................................................................................................................................... 8-19
 

Table 8-11. Body-Weight Estimates (in kg) by Age, U.S. Population Derived from NHANES III (1988−1994).. 8-20
 

Table 8-12. Observed Mean, Standard Deviation, and Selected Percentiles for Weight (kg) by Sex and Age:
 

Birth to 36 Months............................................................................................................................... 8-21
 

Table 8-13. Estimated Distribution of Body Weight by Fine Age Categories All Individuals, Males and Females
 

Combined (kg) ..................................................................................................................................... 8-22
 

Table 8-14. Mean Body Weight (kg) by Age and Sex Across Multiple Surveys .................................................... 8-23
 

Table 8-15. Mean Height (cm) by Age and Sex Across Multiple Surveys ............................................................. 8-25
 

Table 8-16. Mean Body Mass Index (kg/m2

) by Age and Sex Across Multiple Surveys........................................ 8-27
 

Table 8-17. Sample Sizes by Age, Sex, Race, and Examination............................................................................. 8-29
 

Table 8-18. Mean BMI (kg/m2

) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex 

(ages 2 to 17)........................................................................................................................................ 8-30
 

Table 8-19. Mean Body Mass Index (kg/m2

) by Survey, Sex, Race/Ethnicity, and Age Group; Adults:
 

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United States ........................................................................................................................................ 8-31
 

Table 8-20. Prevalence of Overweight and Obesity Among Children.................................................................... 8-32
 

Table 8-21. Numbers of Live Births by Weight and Percentages of Live Births with Low and Very Low Birth 

Weights, by Race, and Hispanic Origin of Mother: United States, 2005 ............................................. 8-33
 

Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES II Data ................................................................................................................................. 8-34
 

Table 8-23. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES III Data................................................................................................................................ 8-36
 

Table 8-24. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES IV Data................................................................................................................................ 8-38
 

Table 8-25. Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessments .............. 8-40
 

Table 8-26. Estimated Percentile Distribution of Body Weight by Fine Age Categories........................................ 8-41
 

Table 8-27. Estimated Percentile Distribution of Body Weight by Fine Age Categories With Confidence
 

Interval................................................................................................................................................. 8-42
 

Table 8-28. Distribution of 1st Trimester Weight Gain and 2nd and 3rd Trimester Rates of Gain in Women With Good 

Pregnancy Outcomes ........................................................................................................................... 8-43
 

Table 8-29. Estimated Body Weights of Pregnant Women―NHANES (1999−2006) ........................................... 8-44
 

Table 8-30. Fetal Weight (g) Percentiles Throughout Pregnancy ........................................................................... 8-45
 

Table 8-31. Neonatal Weight by Gestational Age for Males and Females Combined ............................................ 8-46
 

Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months................................................... 8-47
 

Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months. .................................................. 8-48
 

Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months.............................................. 8-49
 

Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months. ............................................. 8-50
 

Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years. ...................................................... 8-51
 

Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years. ...................................................... 8-52
 

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9. INTAKE OF FRUITS AND VEGETABLES...............................................................................................9-1
 

9.1.	 INTRODUCTION .........................................................................................................................9-1
 

9.2.	 RECOMMENDATIONS ...............................................................................................................9-2
 

9.3.	 INTAKE STUDIES........................................................................................................................9-5
 

9.3.1.	 Key Fruits and Vegetables Intake Study ..........................................................................9-5
 

9.3.1.1.	 U.S. EPA Analysis of Consumption Data from 2003−2006 National
	

Health and Nutrition Examination Survey (NHANES).....................................9-5
 

9.3.2.	 Relevant Fruit and Vegetable Intake Studies ...................................................................9-7
 

9.3.2.1. U.S. Department of Agriculture (USDA) (1980, 1992, 1996a, b) .....................9-7
 

9.3.2.2. U.S. Department of Agriculture (USDA) (1999a).............................................9-7
 

9.3.2.3. U.S. Department of Agriculture (USDA) (1999b).............................................9-7
 

9.3.2.4. U.S. EPA Analysis of Continuing Survey of Food Intake Among 

Individuals (CSFII) 1994−1996, 1998 Based on U.S. Department of 

Agriculture (USDA) (2000) and U.S. EPA (2000) ............................................9-8
 

9.3.2.5. Smiciklas-Wright et al. (2002) ..........................................................................9-9
 

9.3.2.6. Vitolins et al. (2002)..........................................................................................9-9
 

9.3.2.7. Fox et al. (2004) ..............................................................................................9-10
 

9.3.2.8. Ponza et al. (2004)...........................................................................................9-11
 

9.3.2.9. Fox et al. (2006) ..............................................................................................9-11
 

9.3.2.10.Menella et al. (2006)........................................................................................9-11
 

9.4.	 CONVERSION BETWEEN WET- AND DRY-WEIGHT INTAKE RATES..............................9-12
 

9.5.	 REFERENCES FOR CHAPTER 9..............................................................................................9-12
 

Table 9-1. Recommended Values for Intake of Fruits and Vegetables, Edible Portion, Uncooked.................9-3
 

Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables...........................................9-4
 

Table 9-3. Per Capita Intake of Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible
 

portion, uncooked weight) ...........................................................................................................9-14
 

Table 9-4. Consumer-Only Intake of Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day,
 

edible portion, uncooked weight).................................................................................................9-15
 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kgday, edible portion, uncooked weight) .........................................................................................9-16
 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES
	

(g/kg-day, edible portion, uncooked weight)................................................................................9-24
 

Table 9-7. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age|
 

(1977−1978).................................................................................................................................9-31
 

Table 9-8. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age
 

(1987−1988, 1994, and 1995) ......................................................................................................9-32
 

Table 9-9. Per Capita Consumption of Fresh Fruits and Vegetables in 1997 ................................................9-33
 

Table 9-10. Mean Quantities of Vegetables Consumed Daily by Sex and Age, for Children, per Capita 

(g/day, as-consumed) ...................................................................................................................9-34
 

Table 9-11. Percentage of Individuals Consuming Vegetables, by Sex and Age, for Children (%) ................9-35
 

Table 9-12. Mean Quantities of Fruits Consumed Daily by Sex and Age, for Children, per Capita (g/day,
 

as-consumed) ...............................................................................................................................9-36
 

Table 9-13. Percentage of Individuals Consuming, Fruits by Sex and Age, for Children (%)........................9-37
 

Table 9-14. Per Capita Intake of Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible
 

portion, uncooked weight) ...........................................................................................................9-38
 

Table 9-15. Consumer-Only Intake of Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day,
 

edible portion, uncooked weight).................................................................................................9-40
 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII
	

(g/kg-day, edible portion, uncooked weight)................................................................................9-42
 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII
	

(g/kg-day, edible portion, uncooked weight)................................................................................9-51
 

Table 9-18. Per Capita Intake of Exposed Fruits Based on 1994−1996 CSFII (g/kg-day, as-consumed).......9-58
 

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Table 9-19. Per Capita Intake of Protected Fruits Based on 1994−1996 CSFII (g/kg-day, as-consumed)......9-59
 

Table 9-20. Per Capita Intake of Exposed Vegetables (g/kg-day, as-consumed).............................................9-60
 

Table 9-21. Per Capita Intake of Protected Vegetables Based on 1994−1996 CSFII (g/kg-day,
 

as-consumed) ...............................................................................................................................9-61
 

Table 9-22. Per Capita Intake of Root Vegetables Based on 1994−1996 CSFII (g/kg-day, as-consumed) .....9-62
 

Table 9-23. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and the 

Percentage of Individuals Consuming These Foods in Two Days ...............................................9-63
 

Table 9-24. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and
 

Percentage of Individuals Consuming These Foods in Two Days, by Food ................................9-64
 

Table 9-25. Consumption of Major Food Groups: Median Servings (and Ranges) by Demographic and 

Health Characteristics, for Older Adults ......................................................................................9-66
 

Table 9-26. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population ...............9-67
 

Table 9-27. Percentage of Infants and Toddlers Consuming Different Types of Vegetables...........................9-68
 

Table 9-28. Top Five Vegetables Consumed by Infants and Toddlers.............................................................9-69
 

Table 9-29. Percentage of Infants and Toddlers Consuming Different Types of Fruits...................................9-70
 

Table 9-30. Top Five Fruits Consumed by Infants and Toddlers.....................................................................9-71
 

Table 9-31. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants
 

(Percentages)................................................................................................................................9-72
 

Table 9-32. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC)
 

Participation Status ......................................................................................................................9-73
 

Table 9-33. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by
 

Infants From the 2002 Feeding Infants and Toddlers Study ........................................................9-74
 

Table 9-34. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by 

Toddlers From the 2002 Feeding Infants and Toddlers Study......................................................9-75
 

Table 9-35. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of
 

Fruits and Vegetables on a Given Day .........................................................................................9-76
 

Table 9-36. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants and Toddlers
 

per Age Group..............................................................................................................................9-77
 

Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible
 

Portions ........................................................................................................................................9-78
 

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10.	 INTAKE OF FISH AND SHELLFISH ......................................................................................................10-1
 

10.1.	 INTRODUCTION .......................................................................................................................10-1
 

10.2.	 RECOMMENDATIONS .............................................................................................................10-4
 

10.2.1.	 Recommendations—General Population.......................................................................10-4
 

10.2.2.	 Recommendations—Recreational Marine Anglers........................................................10-5
 

10.2.3.	 Recommendations—Recreational Freshwater Anglers..................................................10-5
 

10.2.4.	 Recommendations—Native American Populations.......................................................10-6
 

10.3.	 GENERAL POPULATION STUDIES ......................................................................................10-15
 

10.3.1.	 Key General Population Study ....................................................................................10-15
 

10.3.1.1.U.S. EPA Analysis of Consumption Data From 2003–2006 NHANES ........10-15
 

10.3.2.	 Relevant General Population Studies...........................................................................10-16
 

10.3.2.1.Javitz (1980)..................................................................................................10-16
 

10.3.2.2.Pao et al. (1982).............................................................................................10-17
 

10.3.2.3.USDA (1992a)...............................................................................................10-17
 

10.3.2.4.U.S. EPA (1996) ............................................................................................10-18
 

10.3.2.5.Stern et al. (1996)..........................................................................................10-18
 

10.3.2.6.U.S. EPA (2002) ............................................................................................10-19
 

10.3.2.7.Westat (2006).................................................................................................10-20
 

10.3.2.8.Moya et al. (2008) .........................................................................................10-21
 

10.3.2.9.Mahaffey et al. (2009)...................................................................................10-21
 

10.4.	 MARINE RECREATIONAL STUDIES....................................................................................10-21
 

10.4.1.	 Key Marine Recreational Study...................................................................................10-21
 

10.4.1.1.National Marine Fisheries Service (1986a, b, c, 1993)..................................10-21
 

10.4.2.	 Relevant Marine Recreational Studies.........................................................................10-23
 

10.4.2.1.Pierce et al. (1981).........................................................................................10-23
 

10.4.2.2.Puffer et al. (1981).........................................................................................10-24
 

10.4.2.3.Burger and Gochfeld (1991)..........................................................................10-25
 

10.4.2.4.Burger et al. (1992)........................................................................................10-26
 

10.4.2.5.Moya and Phillips (2001)..............................................................................10-26
 

10.4.2.6.KCA Research Division (1994).....................................................................10-27
 

10.4.2.7.Santa Monica Bay Restoration Project (SMBRP) (1994)..............................10-27
 

10.4.2.8.U.S. DHHS (1995) ........................................................................................10-28
 

10.4.2.9.Alcoa (1998)..................................................................................................10-29
 

10.4.2.10. Burger et al. (1998) ..................................................................................10-30
 

10.4.2.11. Chiang (1998) ..........................................................................................10-30
 

10.4.2.12. San Francisco Estuary Institute (SFEI) (2000).........................................10-31
 

10.4.2.13. Burger (2002a) .........................................................................................10-31
 

10.4.2.14. Mayfield et al. (2007)...............................................................................10-32
 

10.5.	 FRESHWATER RECREATIONAL STUDIES..........................................................................10-32
 

10.5.1.	 Fiore et al. (1989) ........................................................................................................10-32
 

10.5.2.	 West et al. (1989).........................................................................................................10-33
 

10.5.3.	 Chemrisk (1992) ..........................................................................................................10-35
 

10.5.4.	 Connelly et al. (1992) ..................................................................................................10-37
 

10.5.5.	 Hudson River Sloop Clearwater, Inc. (1993)...............................................................10-37
 

10.5.6.	 West et al. (1993).........................................................................................................10-38
 

10.5.7.	 Alabama Dept. of Environmental Management (ADEM) (1994)................................10-39
 

10.5.8.	 Connelly et al. (1996) ..................................................................................................10-39
 

10.5.9.	 Balcom et al. (1999) ....................................................................................................10-40
 

10.5.10. Burger et al. (1999)......................................................................................................10-41
 

10.5.11. Williams et al. (1999) ..................................................................................................10-42
 

10.5.12. Burger (2000)...............................................................................................................10-42
 

10.5.13. Williams et al. (2000) ..................................................................................................10-43
 

10.5.14. Benson et al. (2001).....................................................................................................10-43
 

10.5.15. Moya and Phillips (2001) ............................................................................................10-44
 

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10.5.16. Campbell et al. (2002) .................................................................................................10-44
 

10.5.17. Burger (2002b).............................................................................................................10-45
 

10.5.18. Mayfield et al. (2007) ..................................................................................................10-45
 

10.6. NATIVE AMERICAN STUDIES..............................................................................................10-46
 

10.6.1. Wolfe and Walker (1987).............................................................................................10-46
 

10.6.2. Columbia River Inter-Tribal Fish Commission (CRITFC) (1994) ..............................10-47
 

10.6.3. Peterson et al. (1994) ...................................................................................................10-48
 

10.6.4. Fitzgerald et al. (1995).................................................................................................10-49
 

10.6.5. Forti et al. (1995) .........................................................................................................10-50
 

10.6.6. Toy et al. (1996)...........................................................................................................10-51
 

10.6.7. Duncan (2000) .............................................................................................................10-52
 

10.6.8. Westat (2006)...............................................................................................................10-53
 

10.6.9. Polissar et al. (2006) ....................................................................................................10-53
 

10.7. OTHER POPULATION STUDIES ...........................................................................................10-54
 

10.7.1. U.S. EPA (1999)...........................................................................................................10-54
 

10.8. SERVING SIZE STUDIES........................................................................................................10-55
 

10.8.1. Pao et al. (1982)...........................................................................................................10-55
 

10.8.2. Smiciklas-Wright et al. (2002).....................................................................................10-56
 

10.9. OTHER FACTORS TO CONSIDER FOR FISH CONSUMPTION.........................................10-56
 

10.9.1. Conversion Between Wet and Dry Weight...................................................................10-56
 

10.9.2. Conversion Between Wet-Weight and Lipid-Weight Intake Rates ..............................10-57
 

10.10. REFERENCES FOR CHAPTER 10..........................................................................................10-57
 

APPENDIX 10A: RESOURCE UTILIZATION DISTRIBUTION .....................................................................10A-1
 

APPENDIX 10B: FISH PREPARATION AND COOKING METHODS............................................................10B-1
 

Table 10-1. Recommended Per Capita and Consumer-Only Values for Fish Intake (g/kg-day), 

Uncooked Fish Weight, by Age....................................................................................................10-7
 

Table 10-2. Confidence in Recommendations for General Population Fish Intake ........................................10-8
 

Table 10-3. Recommended Values for Recreational Marine Fish Intake ........................................................10-9
 

Table 10-4. Confidence in Recommendations for Recreational Marine Fish Intake.....................................10-10
 

Table 10-5. Summary of Relevant Studies on Freshwater Recreational Fish Intake.....................................10-11
 

Table 10-6. Summary of Relevant Studies on Native American Fish Intake ................................................10-13
 

Table 10-7. Per Capita Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight ......................10-62
 

Table 10-8. Consumer-Only Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight .............10-63
 

Table 10-9. Per Capita Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight ...................10-64
 

Table 10-10. Consumer-Only Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight ..........10-65
 

Table 10-11. Per Capita Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible Portion,
 

Uncooked Fish Weight...............................................................................................................10-66
 

Table 10-12. Consumer-Only Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible
 

Portion, Uncooked Fish Weight .................................................................................................10-67
 

Table 10-13. Total Fish Consumption, Consumers Only, by Demographic Variables ....................................10-68
 

Table 10-14. Percent Distribution of Total Fish Consumption for Females and Males by Age ......................10-70
 

Table 10-15. Mean Total Fish Consumption by Species.................................................................................10-71
 

Table 10-16. Best Fits of Lognormal Distributions Using the Non-Linear Optimization Method..................10-72
 

Table 10-17. Mean Fish Intake in a Day, by Sex and Age ..............................................................................10-72
 

Table 10-18. Percent of Respondents That Responded Yes, No, or Don’t Know to Eating Seafood in 1 

Month (including shellfish, eels, or squid).................................................................................10-73
 

Table 10-19. Number of Respondents Reporting Consumption of a Specified Number of Servings of
 

Seafood in 1 Month....................................................................................................................10-75
 

Table 10-20. Number of Respondents Reporting Monthly Consumption of Seafood That Was
 

Purchased or Caught by Someone They Knew ..........................................................................10-77
 

Table 10-21. Distribution of Fish Meals Reported by NJ Consumers During the Recall Period ....................10-78
 

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Table 10-22. Selected Species Among All Reported Meals by NJ Consumers During the Recall Period ......10-79
 

Table 10-23. Cumulative Probability Distribution of Average Daily Fish Consumption (g/day) ...................10-79
 

Table 10-24. Distribution of the Usual Frequency of Fish Consumption........................................................10-79
 

Table 10-25. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S.
 

Population, as Prepared..............................................................................................................10-80
 

Table 10-26. Daily Average Per Capita Estimates of Fish Consumption: U.S. Population—Mean
 

Consumption by Species Within Habitat, as Prepared ...............................................................10-81
 

Table 10-27. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S.
 

Population, Uncooked Fish Weight............................................................................................10-82
 

Table 10-28. Daily Average Per Capita Estimates of Fish Consumption U.S. Population—Mean
 

Consumption by Species Within Habitat, Uncooked Fish Weight .............................................10-83
 

Table 10-29. Per Capita Distributions of Fish (finfish and shellfish) Intake (g/day), as Prepared..................10-84
 

Table 10-30. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepared ...........10-86
 

Table 10-31. Per Capita Distribution of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish 

Weight ........................................................................................................................................10-88
 

Table 10-32. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish
 

Weight ........................................................................................................................................10-90
 

Table 10-33. Consumer-Only Distribution of Fish (finfish and shellfish) Intake (g/day), as Prepared...........10-92
 

Table 10-34. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), as
 

Prepared .....................................................................................................................................10-94
 

Table 10-35. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (g/day), Uncooked
 

Fish Weight ................................................................................................................................10-96
 

Table 10-36. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day),
 

Uncooked Fish Weight...............................................................................................................10-98
 

Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
 

Characteristics (g/kg-day, as-consumed)..................................................................................10-100
 

Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
 

Characteristics (g/kg-day, as-consumed)..................................................................................10-104
 

Table 10-39. Fish Consumption per kg Body Weight, All Respondents by State, Acquisition Method,
 

(g/kg-day, as-consumed) ..........................................................................................................10-108
 

Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method 

(g/kg-day, as-consumed) ..........................................................................................................10-111
 

Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic
 

Characteristics, Uncooked (g/kg-day)......................................................................................10-114
 

Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic
 

Characteristics, Uncooked (g/kg-day)......................................................................................10-118
 

Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition Method,
 

Uncooked (g/kg-day) ...............................................................................................................10-122
 

Table 10-44. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,
 

Uncooked (g/kg-day) ...............................................................................................................10-125
 

Table 10-45. Fish Consumption per kg Body Weight, All Respondents, by State, Subpopulation, and 

Sex (g/kg-day, as-consumed) ..................................................................................................10-128
 

Table 10-46. Fish Consumption per kg, Consumers Only, by State, Subpopulation, and Sex......................10-130
 

Table 10-47. Fish Consumption Among General Population in Four States, Consumers Only (g/kgday, as-consumed)....................................................................................................................10-133
 

Table 10-48. Estimated Number of Participants in Marine Recreational Fishing by State and Subregion ...10-135
 

Table 10-49. Estimated Weight of Fish Caught (catch Type A and B1) by Marine Recreational
 

Fishermen, by Wave and Subregion.........................................................................................10-136
 

Table 10-50. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status .....................10-137
 

Table 10-51. Estimated Weight of Fish Caught (Catch Type A and B1)by Marine Recreational
 

Fishermen, by Species Group and Subregion ..........................................................................10-138
 

Table 10-52. Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement
 

Bay, Washington ......................................................................................................................10-139
 

Table 10-53. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler
 

Populations Based on the Re-Analysis of the Puffer et al. (1981) and Pierce et al. (1981) 

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Data..........................................................................................................................................10-139
 

Table 10-54. Median Intake Rates Based on Demographic Data of Sport Fishermen and Their
 

Family/Living Group ...............................................................................................................10-140
 

Table 10-55. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed Sport 

Fishermen in the Metropolitan Los Angeles Area....................................................................10-140
 

Table 10-56. Catch Information for Primary Fish Species Kept by Sport Fishermen (N = 1,059) ...............10-141
 

Table 10-57. Fishing and Crabbing Behavior of Fishermen at Humacao, Puerto Rico.................................10-141
 

Table 10-58. Fish Consumption of Delaware Recreational Fishermen and Their Households.....................10-142
 

Table 10-59. Seafood Consumption Rates of All Fish by Ethnic and Income Groups of Santa Monica 

Bay...........................................................................................................................................10-143
 

Table 10-60. Means and Standard Deviations of Selected Characteristics by Population Groups in 

Everglades, Florida ..................................................................................................................10-143
 

Table 10-61. Grams per Day of Self-Caught Fish Consumed by Recreational Anglers—Alcoa/Lavaca 

Bay...........................................................................................................................................10-144
 

Table 10-62. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational
 

Anglers Lavaca Bay, Texas ......................................................................................................10-145
 

Table 10-63. Consumption Patterns of People Fishing and Crabbing in Barnegat Bay, New Jersey............10-146
 

Table 10-64. Fish Intake Rates of Members of the Laotian Community of West Contra Costa County,
 

California .................................................................................................................................10-146
 

Table 10-65. Consumption Rates (g/day) Among Recent Consumers by Demographic Factor....................10-147
 

Table 10-66. Mean + SD Consumption Rates for Individuals Who Fish or Crab in the Newark Bay
 

Area..........................................................................................................................................10-148
 

Table 10-67. Consumption Rates (g/day) for Marine Recreational Anglers in King County, WA...............10-148
 

Table 10-68. Percentile and Mean Intake Rates for Wisconsin Sport Anglers (all respondents) ..................10-149
 

Table 10-69. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households With
 

Recreational Fish Consumption ...............................................................................................10-149
 

Table 10-70. Comparison of 7-Day Recall and Estimated Seasonal Frequency for Fish Consumption .......10-150
 

Table 10-71. Distribution of Usual Fish Intake Among Survey Main Respondents Who Fished and
 

Consumed Recreationally Caught Fish....................................................................................10-150
 

Table 10-72. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the 1989–
 

1990 Ice Fishing or 1990 Open-Water Seasons .......................................................................10-151
 

Table 10-73. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day).............................10-152
 

Table 10-74. Total Consumption of Freshwater Fish Caught by All Survey Respondents During the
 

1990 Season .............................................................................................................................10-152
 

Table 10-75. Socio-Demographic Characteristics of Respondents ...............................................................10-153
 

Table 10-76. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport Anglers Fish 

Consumption Study, 1991–1992 ..............................................................................................10-154
 

Table 10-77. Mean Per Capita Freshwater Fish Intake of Alabama Anglers.................................................10-155
 

Table 10-78. Distribution of Fish Intake Rates (from all sources and from sport-caught sources) for
 

1992 Lake Ontario Anglers ......................................................................................................10-155
 

Table 10-79. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by SocioDemographic Characteristics ...................................................................................................10-156
 

Table 10-80. Seafood Consumption Rates of Nine Connecticut Population Groups ....................................10-156
 

Table 10-81. Fishing Patterns and Consumption Rates of People Fishing Along the Savannah River
 

(Mean ± SE).............................................................................................................................10-157
 

Table 10-82. Fish Consumption Rates for Indiana Anglers—Mail Survey (g/day) ......................................10-158
 

Table 10-83. Fish Consumption Rates for Indiana Anglers—On-Site Survey (g/day)..................................10-158
 

Table 10-84. Consumption of Sport-Caught and Purchased Fish by Minnesota and North Dakota 

Residents (g/day) .....................................................................................................................10-159
 

Table 10-85. Fishing Patterns and Consumption Rates of Anglers Along the Clinch River Arm of
 

Watts Bar Reservoir (Mean ± SE)............................................................................................10-161
 

Table 10-86. Daily Consumption of Wild-Caught Fish, Consumers Only (g/kg-day, as-consumed)............10-161
 

Table 10-87. Consumption Rates (g/day) for Freshwater Recreational Anglers in King County, WA..........10-162
 

Table 10-88. Number of Grams per Day of Fish Consumed by All Adult Respondents (consumers and 

non-consumers combined)—Throughout the Year ..................................................................10-162
 

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Table 10-89. Fish Intake Throughout the Year by Sex, Age, and Location by All Adult Respondents.........10-163
 

Table 10-90. Fish Consumption Rates Among Native American Children (age 5 years and under).............10-163
 

Table 10-91. Number of Fish Meals Eaten per Month and Fish Intake Among Native American
 

Children Who Consume Particular Species .............................................................................10-164
 

Table 10-92. Socio-Demographic Factors and Recent Fish Consumption....................................................10-164
 

Table 10-93. Number of Local Fish Meals Consumed per Year by Time Period for All Respondents .........10-165
 

Table 10-94. Mean Number of Local Fish Meals Consumed per Year by Time Period for All
 

Respondents and Consumers Only...........................................................................................10-165
 

Table 10-95. Mean Number of Local Fish Meals Consumed per Year by Time Period and Selected
 

Characteristics for All Respondents (Mohawk, N = 97; Control, N = 154) .............................10-166
 

Table 10-96. Fish Consumption Rates for Mohawk Native Americans (g/day)............................................10-166
 

Table 10-97. Percentiles and Mean of Adult Tribal Member Consumption Rates (g/kg-day) ......................10-167
 

Table 10-98. Median and Mean Consumption Rates by Sex (g/kg-day) Within Each Tribe.........................10-168
 

Table 10-99. Median Consumption Rate for Total Fish by Sex and Tribe (g/day)........................................10-168
 

Table 10-100. Percentiles of Adult Consumption Rates by Age (g/kg-day)....................................................10-169
 

Table 10-101. Median Consumption Rates by Income (g/kg-day) Within Each Tribe ...................................10-170
 

Table 10-102. Mean, 50th, and 90th Percentiles of Consumption Rates for Children Age Birth to 5 Years
 

(g/kg-day).................................................................................................................................10-171
 

Table 10-103. Adult Consumption Rate (g/kg-day): Individual Finfish and Shellfish and Fish Groups ........10-172
 

Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only.......................................................10-173
 

Table 10-105. Adult Consumption Rate (g/kg-day) by Sex ............................................................................10-176
 

Table 10-106. Adult Consumption Rate (g/kg-day) by Age............................................................................10-177
 

Table 10-107. Consumption Rates for Native American Children (g/kg-day), All Children (including 

non-consumers): Individual Finfish and Shellfish and Fish Groups ........................................10-179
 

Table 10-108. Consumption Rates for Native American Children (g/kg-day), Consumers Only:
 

Individual Finfish and Shellfish and Fish Groups....................................................................10-180
 

Table 10-109. Percentiles and Mean of Consumption Rates for Adult Consumers Only (g/kg-day)..............10-181
 

Table 10-110. Percentiles and Mean of Consumption Rates by Sex for Adult Consumers Only (g/kgday) ..........................................................................................................................................10-182
 

Table 10-111. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only—
 

Squaxin Island Tribe (g/kg-day)...............................................................................................10-184
 

Table 10-112. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only—Tulalip
 

Tribe (g/kg-day) .......................................................................................................................10-186
 

Table 10-113. Percentiles and Mean of Consumption Rates for Child Consumers Only (g/kg-day)..............10-187
 

Table 10-114. Percentiles and Mean of Consumption Rates by Sex for Child Consumers Only (g/kgday) ..........................................................................................................................................10-188
 

Table 10-115. Consumption Rates of API Community Members...................................................................10-189
 

Table 10-116. Demographic Characteristics of “Higher” and “Lower” Seafood Consumers.........................10-190
 

Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community
 

(g/kg-day).................................................................................................................................10-191
 

Table 10-118. Consumption Rates by Sex for All Asian and Pacific Islander Community ............................10-195
 

Table 10-119. Types of Seafood Consumed/Respondents Who Consumed (%).............................................10-196
 

Table 10-120. Mean, Median and 95th Percentile Fish Intake Rates for Different Groups (g/day) .................10-198
 

Table 10-121. Distribution of Quantity of Fish Consumed (in grams) per Eating Occasion, by Age and
 

Sex ...........................................................................................................................................10-199
 

Table 10-122. Distribution of Quantity of Canned Tuna Consumed (grams) per Eating Occasion, by Age 

and Sex.....................................................................................................................................10-200
 

Table 10-123. Distribution of Quantity of Other Finfish Consumed (grams) per Eating Occasion, by Age 

and Sex.....................................................................................................................................10-201
 

Table 10-124. Percentage of Individuals Using Various Cooking Methods at Specified Frequencies............10-202
 

Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species........................................10-203
 

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Figure 10-1. Locations of Freshwater Fish Consumption Surveys in the United States................................ 10-12
 

Figure 10-2. Species and Frequency of Meals Consumed by Geographic Residence. ................................ 10-208
 

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11. INTAKE OF MEATS, DAIRY PRODUCTS, AND FATS.........................................................................11-1
 

11.1. INTRODUCTION .......................................................................................................................11-1
 

11.2. RECOMMENDATIONS .............................................................................................................11-1
 

11.3. INTAKE OF MEAT AND DAIRY PRODUCTS........................................................................11-6
 

11.3.1. Key Meat and Dairy Intake Studies ...............................................................................11-6
 

11.3.1.1.U.S. EPA Analysis of Consumption Data From 2003−2006 National
	

Health and Nutrition Examination Survey (NHANES)...................................11-6
 

11.3.2. Relevant Meat and Dairy Intake Studies........................................................................11-7
 

11.3.2.1.USDA (1980, 1992, 1996a, b).........................................................................11-7
 

11.3.2.2.USDA (1999a).................................................................................................11-8
 

11.3.2.3.U.S. EPA Analysis of CSFII 1994−1996, 1998 Based on USDA (2000)
	

and U.S. EPA (2000)........................................................................................11-8
 

11.3.2.4.Smiciklas-Wright et al. (2002) ........................................................................11-9
 

11.3.2.5.Vitolins et al. (2002)......................................................................................11-10
 

11.3.2.6.Fox et al. (2004) ............................................................................................11-10
 

11.3.2.7.Ponza et al. (2004).........................................................................................11-11
 

11.3.2.8.Mennella et al. (2006)....................................................................................11-11
 

11.3.2.9.Fox et al. (2006) ............................................................................................11-11
 

11.4. INTAKE OF FAT .......................................................................................................................11-12
 

11.4.1. Key Fat Intake Study ...................................................................................................11-12
 

11.4.1.1.U.S. EPA (2007) ............................................................................................11-12
 

11.4.2. Relevant Fat Intake Studies .........................................................................................11-13
 

11.4.2.1.Cresanta et al. (1988)/Nicklas et al. (1993)/and Frank et al. (1986)..............11-13
 

11.5. CONVERSION BETWEEN WET- AND DRY-WEIGHT INTAKE RATES............................11-13
 

11.6. CONVERSION BETWEEN WET-WEIGHT AND LIPID-WEIGHT INTAKE RATES..........11-13
 

11.7. REFERENCES FOR CHAPTER 11..........................................................................................11-14
 

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12.	 INTAKE OF GRAIN PRODUCTS............................................................................................................12-1
 

12.1.	 INTRODUCTION .......................................................................................................................12-1
 

12.2.	 RECOMMENDATIONS .............................................................................................................12-1
 

12.3.	 INTAKE STUDIES......................................................................................................................12-4
 

12.3.1.	 Key Grain Intake Study .................................................................................................12-4
 

12.3.1.1.U.S. EPA Analysis of Consumption Data From 2003−2006 National
	

Health and Nutrition Examination Survey (NHANES)...................................12-4
 

12.3.2.	 Relevant Grain Intake Studies .......................................................................................12-5
 

12.3.2.1.USDA (1980, 1992, 1996a, b).........................................................................12-5
 

12.3.2.2.USDA (1999a).................................................................................................12-6
 

12.3.2.3.USDA (1999b).................................................................................................12-6
 

12.3.2.4.U.S. EPA Analysis of Continuing Survey of Food Intake by Individuals
 

(CSFII) 1994−1996, 1998 ...............................................................................12-7
 

12.3.2.5.Smiciklas-Wright et al. (2002) ........................................................................12-8
 

12.3.2.6.Vitolins et al. (2002)........................................................................................12-8
 

12.3.2.7.Fox et al. (2004) ..............................................................................................12-9
 

12.3.2.8.Ponza et al. (2004)...........................................................................................12-9
 

12.3.2.9.Fox et al. (2006) ............................................................................................12-10
 

12.3.2.10. Mennella et al. (2006) ..............................................................................12-10
 

12.4.	 CONVERSION BETWEEN WET- AND DRY-WEIGHT INTAKE RATES............................12-10
 

12.5.	 REFERENCES FOR CHAPTER 12..........................................................................................12-11
 

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13. INTAKE OF HOME-PRODUCED FOODS..............................................................................................13-1
 

13.1. INTRODUCTION .......................................................................................................................13-1
 

13.2. RECOMMENDATIONS .............................................................................................................13-1
 

13.3. KEY STUDY FOR INTAKE OF HOME-PRODUCED FOODS................................................13-5
 

13.3.1. U.S. EPA Analysis of NFCS 1987–1988; Moya and Phillips (2001).............................13-5
 

13.3.2. Phillips and Moya (2011)...............................................................................................13-9
 

13.4. RELEVANT STUDY FOR INTAKE OF HOME-PRODUCED FOODS .................................13-10
 

13.4.1. National Gardening Association (2009).......................................................................13-10
 

13.5. REFERENCES FOR CHAPTER 13..........................................................................................13-10
 

APPENDIX 13A FOOD CODES AND DEFINITIONS OF MAJOR FOOD GROUPS USED IN THE 

ANALYSIS .............................................................................................................................................13A-1 

APPENDIX 13B 1987−1988 NFCS FOOD CODES AND DEFINITIONS OF INDIVIDUAL FOOD 

ITEMS USED IN ESTIMATING THE FRACTION OF HOUSEHOLD FOOD INTAKE THAT IS 

HOME-PRODUCED ..............................................................................................................................13B-1 

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14.	 TOTAL FOOD INTAKE ...........................................................................................................................14-1
 

14.1.	 INTRODUCTION ......................................................................................................................14-1
 

14.2.	 RECOMMENDATIONS ............................................................................................................14-1
 

14.3.	 STUDIES OF TOTAL FOOD INTAKE .....................................................................................14-4
 

14.3.1.	 U.S. EPA Re−Analysis of 1994−1996, 1998 Continuing Survey of Food Intake
	

by Individuals (CSFII), Based on U.S. EPA (2007).......................................................14-4
 

14.3.2.	 U.S. EPA Analysis of National Health and Nutrition Examination Survey
 

(NHANES) 2003−2006 Data ........................................................................................14-5
 

14.4.	 REFERENCES FOR CHAPTER 14 ...........................................................................................14-6
 

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Exposure Factors Handbook 

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15. HUMAN MILK INTAKE ..........................................................................................................................15-1
 

15.1. INTRODUCTION .......................................................................................................................15-1
 

15.2. RECOMMENDATIONS .............................................................................................................15-1
 

15.2.1. Human Milk Intake........................................................................................................15-2
 

15.2.2. Lipid Content and Lipid Intake......................................................................................15-2
 

15.3. KEY STUDIES ON HUMAN MILK INTAKE...........................................................................15-9
 

15.3.1. Pao et al. (1980).............................................................................................................15-9
 

15.3.2. Dewey and Lönnerdal (1983) ........................................................................................15-9
 

15.3.3. Butte et al. (1984) ..........................................................................................................15-9
 

15.3.4. Neville et al. (1988) .....................................................................................................15-10
 

15.3.5. Dewey et al. (1991a, b)................................................................................................15-10
 

15.3.6. Butte et al. (2000) ........................................................................................................15-11
 

15.3.7. Arcus-Arth et al. (2005)...............................................................................................15-11
 

15.4. KEY STUDIES ON LIPID CONTENT AND LIPID INTAKE FROM HUMAN MILK .........15-12
 

15.4.1. Butte et al. (1984) ........................................................................................................15-12
 

15.4.2. Mitoulas et al. (2002)...................................................................................................15-13
 

15.4.3. Mitoulas et al. (2003)...................................................................................................15-13
 

15.4.4. Arcus-Arth et al. (2005)...............................................................................................15-14
 

15.4.5. Kent et al. (2006) .........................................................................................................15-14
 

15.5. RELEVANT STUDY ON LIPID INTAKE FROM HUMAN MILK ........................................15-14
 

15.5.1. Maxwell and Burmaster (1993) ...................................................................................15-14
 

15.6. OTHER FACTORS....................................................................................................................15-15
 

15.6.1. Population of Nursing Infants......................................................................................15-15
 

15.6.2. Intake Rates Based on Nutritional Status.....................................................................15-17
 

15.6.3. Frequency and Duration of Feeding ............................................................................15-18
 

15.7. REFERENCES FOR CHAPTER 15..........................................................................................15-18
 

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Exposure Factors Handbook 

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16.	 ACTIVITY FACTORS...............................................................................................................................16-1
 

16.1.	 INTRODUCTION .......................................................................................................................16-1
 

16.2.	 RECOMMENDATIONS .............................................................................................................16-1
 

16.2.1.	 Activity Patterns ............................................................................................................16-1
 

16.2.2.	 Occupational Mobility ...................................................................................................16-2
 

16.2.3.	 Population Mobility.......................................................................................................16-2
 

16.3.	 ACTIVITY PATTERNS.............................................................................................................16-10
 

16.3.1.	 Key Activity Pattern Studies........................................................................................16-10
 

16.3.1.1.Wiley et al. (1991).........................................................................................16-10
 

16.3.1.2.U.S. EPA (1996) ............................................................................................16-11
 

16.3.2.	 Relevant Activity Pattern Studies ................................................................................16-12
 

16.3.2.1.Hill (1985).....................................................................................................16-12
 

16.3.2.2.Timmer et al. (1985)......................................................................................16-13
 

16.3.2.3.Robinson and Thomas (1991.........................................................................16-14
 

16.3.2.4.Funk et al. (1998) ..........................................................................................16-14
 

16.3.2.5.Cohen Hubal et al. (2000) .............................................................................16-15
 

16.3.2.6.Wong et al. (2000).........................................................................................16-16
 

16.3.2.7.Graham and McCurdy (2004)........................................................................16-17
 

16.3.2.8.Juster et al. (2004) .........................................................................................16-17
 

16.3.2.9.Vandewater et al. (2004)................................................................................16-18
 

16.3.2.10. U.S. Department of Labor (2007) ............................................................16-18
 

16.3.2.11. Nader et al. (2008) ...................................................................................16-19
 

16.4.	 OCCUPATIONAL MOBILITY .................................................................................................16-19
 

16.4.1.	 Key Occupational Mobility Studies.............................................................................16-19
 

16.4.1.1.Carey (1988)..................................................................................................16-19
 

16.4.1.2.Carey (1990)..................................................................................................16-20
 

16.5.	 POPULATION MOBILITY.......................................................................................................16-20
 

16.5.1.	 Key Population Mobility Studies.................................................................................16-20
 

16.5.1.1.Johnson and Capel (1992) .............................................................................16-20
 

16.5.1.2.U.S. Census Bureau (2008a)..........................................................................16-21
 

16.5.2.	 Relevant Population Mobility Studies .........................................................................16-21
 

16.5.2.1.Israeli and Nelson (1992) ..............................................................................16-21
 

16.5.2.2.National Association of Realtors (NAR) (1993)............................................16-22
 

16.5.2.3.U.S. Census Bureau (2008b) .........................................................................16-22
 

16.6.	 REFERENCES FOR CHAPTER 16..........................................................................................16-22
 

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17. CONSUMER PRODUCTS........................................................................................................................17-1
 

17.1. INTRODUCTION .......................................................................................................................17-1
 

17.1.1. Background....................................................................................................................17-1
 

17.1.2. Additional Sources of Information ................................................................................17-1
 

17.2. RECOMMENDATIONS .............................................................................................................17-2
 

17.3. CONSUMER PRODUCTS USE STUDIES................................................................................17-2
 

17.3.1. CTFA (1983)..................................................................................................................17-2
 

17.3.2. Westat (1987a)...............................................................................................................17-2
 

17.3.3. Westat (1987b)...............................................................................................................17-3
 

17.3.4. Westat (1987c)...............................................................................................................17-4
 

17.3.5. Abt (1992)......................................................................................................................17-4
 

17.3.6. U.S. EPA (1996).............................................................................................................17-5
 

17.3.7. Bass et al. (2001) ...........................................................................................................17-5
 

17.3.8. Weegels and van Veen (2001)........................................................................................17-6
 

17.3.9. Loretz et al. (2005) ........................................................................................................17-6
 

17.3.10. Loretz et al. (2006) ........................................................................................................17-7
 

17.3.11. Hall et al. (2007)............................................................................................................17-7
 

17.3.12. Loretz et al. (2008) ........................................................................................................17-8
 

17.3.13. Sathyanarayana et al. (2008)..........................................................................................17-8
 

17.4. REFERENCES FOR CHAPTER 17............................................................................................17-8
 

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18. LIFETIME..................................................................................................................................................18-1
 

18.1. INTRODUCTION .......................................................................................................................18-1
 

18.2. RECOMMENDATIONS .............................................................................................................18-1
 

18.3. KEY LIFETIME STUDY ............................................................................................................18-3
 

18.3.1. Xu et al. (2010)..............................................................................................................18-3
 

18.4. RELEVANT LIFETIME STUDY................................................................................................18-3
 

18.4.1. U.S. Census Bureau (2008)............................................................................................18-3
 

18.5. REFERENCES FOR CHAPTER 18............................................................................................18-3
 

Table 18-1. Recommended Values for Expectation of Life at Birth: 2007......................................................18-1
 

Table 18-2. Confidence in Lifetime Expectancy Recommendations ..............................................................18-2
 

Table 18-3. Expectation of Life at Birth, 1970 to 2007 (years).......................................................................18-4
 

Table 18-4. Expectation of Life by Race, Sex, and Age: 2007........................................................................18-5
 

Table 18-5. Projected Life Expectancy at Birth by Sex, Race, and Hispanic Origin for the United
 

States: 2010 to 2050.....................................................................................................................18-6
 

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19.	 BUILDING CHARACTERISTICS ...........................................................................................................19-1
 

19.1.	 INTRODUCTION .......................................................................................................................19-1
 

19.2.	 RECOMMENDATIONS .............................................................................................................19-2
 

19.3.	 RESIDENTIAL BUILDING CHARACTERISTICS STUDIES .................................................19-9
 

19.3.1.	 Key Study of Volumes of Residences ............................................................................19-9
 

19.3.1.1.U.S. DOE (2008a) ...........................................................................................19-9
 

19.3.2.	 Relevant Studies of Volumes of Residences ..................................................................19-9
 

19.3.2.1.Versar (1990)...................................................................................................19-9
 

19.3.2.2.Murray (1996) .................................................................................................19-9
 

19.3.2.3.U.S. Census Bureau (2010) ...........................................................................19-10
 

19.3.3.	 Other Factors ...............................................................................................................19-10
 

19.3.3.1.Surface Area and Room Volumes..................................................................19-10
 

19.3.3.2.Products and Materials ..................................................................................19-10
 

19.3.3.3.Loading Ratios ..............................................................................................19-11
 

19.3.3.4.Mechanical System Configurations...............................................................19-11
 

19.3.3.5.Type of Foundation........................................................................................19-12
 

19.3.3.5.1. Lucas et al. (1992)....................................................................19-12
 

19.3.3.5.2. U.S. DOE (2008a)....................................................................19-13
 

19.4.	 NON-RESIDENTIAL BUILDING CHARACTERISTICS STUDIES .....................................19-13
 

19.4.1.	 U.S. DOE (2008b) .......................................................................................................19-13
 

19.5.	 TRANSPORT RATE STUDIES ................................................................................................19-14
 

19.5.1.	 Air Exchange Rates .....................................................................................................19-14
 

19.5.1.1.Key Study of Residential Air Exchange Rates ..............................................19-15
 

19.5.1.1.1. Koontz and Rector (1995)........................................................19-15
 

19.5.1.2.Relevant Studies of Residential Air Exchange Rates ....................................19-15
 

19.5.1.2.1. Nazaroff et al. (1988) ...............................................................19-15
 

19.5.1.2.2. Versar (1990)............................................................................19-15
 

19.5.1.2.3. Murray and Burmaster (1995)..................................................19-16
 

19.5.1.2.4. Diamond et al. (1996) ..............................................................19-16
 

19.5.1.2.5. Graham et al. (2004) ................................................................19-16
 

19.5.1.2.6. Price et al. (2006).....................................................................19-16
 

19.5.1.2.7. Yamamoto et al. (2010)............................................................19-17
 

19.5.1.3.Key Study of Non-Residential Air Exchange Rates......................................19-17
 

19.5.1.3.1. Turk et al. (1987)......................................................................19-17
 

19.5.2.	 Indoor Air Models........................................................................................................19-17
 

19.5.3.	 Infiltration Models .......................................................................................................19-18
 

19.5.4.	 Vapor Intrusion ............................................................................................................19-19
 

19.5.5.	 Deposition and Filtration .............................................................................................19-19
 

19.5.5.1.Deposition .....................................................................................................19-19
 

19.5.5.1.1. Thatcher and Layton (1995).....................................................19-20
 

19.5.5.1.2. Wallace (1996) .........................................................................19-20
 

19.5.5.1.3. Thatcher et al. (2002)...............................................................19-20
 

19.5.5.1.4. He et al. (2005) ........................................................................19-20
 

19.5.5.2.Filtration ........................................................................................................19-20
 

19.5.6.	 Interzonal Airflows ......................................................................................................19-20
 

19.5.7.	 House Dust and Soil Loadings.....................................................................................19-21
 

19.5.7.1.Roberts et al. (1991)......................................................................................19-21
 

19.5.7.2.Thatcher and Layton (1995)..........................................................................19-21
 

19.6.	 CHARACTERIZING INDOOR SOURCES .............................................................................19-21
 

19.6.1.	 Source Descriptions for Airborne Contaminants .........................................................19-22
 

19.6.2.	 Source Descriptions for Waterborne Contaminants.....................................................19-23
 

19.6.3.	 Soil and House Dust Sources.......................................................................................19-24
 

19.7.	 ADVANCED CONCEPTS ........................................................................................................19-24
 

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19.7.1. Uniform Mixing Assumption.......................................................................................19-24
 

19.7.2. Reversible Sinks ..........................................................................................................19-24
 

19.8. REFERENCES FOR CHAPTER 19..........................................................................................19-25
 

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ACRONYMS AND ABBREVIATIONS 

AAP = American Academy of Pediatrics 

ACH = Air Changes per Hour 

ADAFs = Age Dependent Adjustment Factors 

ADD = Average Daily Dose 

AF = Adherence Factor 

AHS = American Housing Survey 

AIR = Acid Insoluble Residue 

API = Asian and Pacific Islander 

ASHRAE = American Society of Heating, Refrigeration, and Air Conditioning Engineers 

ASTM = American Society for Testing and Materials 

ARS = Agricultural Research Service 

ASCII = American Standard Code for Information Interchange 

ATD = Arizona Test Dust 

ATSDR = Agency for Toxic Substances and Disease Registry 

ATUS = American Time Use Survey 

BI = Bootstrap Interval 

BMD = Benchmark Dose 

BMI = Body Mass Index 

BMR = Basal Metabolic Rate 

BTM = Best Tracer Method 

BW = Body Weight 

C = Concentration 

CATI = Computer-Assisted Telephone Interviewing 

CDC = Centers for Disease Control and Prevention 

CDFA = California Department of Food and Drugs 

CDS = Child Development Supplement 

CHAD = Consolidated Human Activity Database 

CI = Confidence Interval 

cm2 = Square Centimeter 

cm3 = Cubic Centimeter 

CNRC = Children’s Nutrition Research Center 

CRITFC = Columbia River Inter-Tribal Fish Commission 

CSFII = Continuing Survey of Food Intake by Individuals 

CT = Central Tendency 

CTFA = Cosmetic, Toiletry, and Fragrance Association 

CV = Coefficient of Variation 

DAF = Dosimetry Adjustment Factor 

DARLING = Davis Area Research on Lactation, Infant Nutrition and Growth 

DHHS = Department of Health and Human Services 

DIR = Daily Inhalation Rate 

DIY = Do-It-Yourself 

DK = Respondent Replied “Don’t Know” 

DLW = Doubly Labeled Water 

DOE = Department of Energy 

DONALD = Dortmund Nutritional and Anthropometric Longitudinally Designed 

E or EE = Energy Expenditure 

EBF = Exclusively Breastfed 

ECG = Energy Cost of Growth 

ED = Exposure Duration 

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ACRONYMS AND ABBREVIATIONS (continued) 

EFAST = Exposure and Fate Assessment Screening Tool 

EI = Energy Intake 

EPA = Environmental Protection Agency 

ERV = Energy Recovery Ventilator 

EVR = Equivalent Ventilation Rate 

F = Fahrenheit 

fB = Breathing Frequency 

FCID = Food Commodity Intake Database 

FITS = Feeding Infant and Toddler Study 

F/S = Food/Soil 

g = Gram 

GAF = General Assessment Factor 

GM = Geometric Mean 

GSD = Geometric Standard Deviation 

H = Oxygen Uptake Factor 

HEC = Human Equivalent Exposure Concentrations 

HR = Heart Rate 

HRV = Heat Recovery Ventilator 

USHUD = United States Department of Housing and Urban Development 

I = Tabulated Intake Rate 

IA = Adjusted Intake Rate 

I-BEAM = Indoor Air Quality Building and Assessment Model 

ICRP = International Commission on Radiological Protection 

IEUBK = Integrated Exposure and Uptake Biokinetic Model 

IFS = Iowa Fluoride Study 

IOM = Institute of Medicine 

IPCS = International Programme on Chemical Safety 

IR = Intake Rate/Inhalation Rate 

IRIS = Integrated Risk Information System 

IUR = Inhalation Unit Risk 

Kcal = Kilocalories 

KJ = Kilo Joules 

K-S = Kolmogorov-Smirnov 

kg = Kilogram 

L = Liter 

L1 = Cooking or Preparation Loss 

L2 = Post-cooking Loss 

LADD = Lifetime Average Daily Dose 

LCL = Lower Confidence Limit 

LTM = Limiting Tracer Method 

m2 = Square Meter 

m3 = Cubic Meter 

MCCEM = Multi-Chamber Concentration and Exposure Model 

MEC = Mobile Examination Center 

mg = Milligram 

MJ = Mega Joules 

mL = Milliliter 

METS = Metabolic Equivalents of Work 

MOA = Mode of Action 

MSA = Metropolitan Statistical Area 

MVPA = Moderate-to-Vigorous Physical Activity 

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ACRONYMS AND ABBREVIATIONS (continued) 

Nc = Weighted Number of Individuals Consuming Homegrown Food Item 

NT = Weighted Total Number of Individuals Surveyed 

NAS = National Academy of Sciences 

NCEA = National Center for Environmental Assessment 

NCHS = National Center for Health Statistics 

NERL = National Exposure Research Laboratory 

NFCS = Nationwide Food Consumption Survey 

NHANES = National Health and Nutrition Examination Survey 

NHAPS = National Human Activity Pattern Survey 

NHES = National Health Examination Survey 

NIS = National Immunization Survey 

NLO = Non-Linear Optimization 

NMFS = National Marine Fisheries Service 

NOAEL = No-Observed-Adverse-Effect-Level 

NOPES = Non-Occupational Pesticide Exposure Study 

NR = Not Reported 

NRC = National Research Council 

NS = No Statistical Difference 

OPP = Office of Pesticide Programs 

ORD = Office of Research and Development 

PBPK = Physiologically-Based Pharmacokinetic 

PC = Percent Consuming 

PDIR = Physiological Daily Inhalation Rate 

PFT = Perfluorocarbon Tracer 

PSID = Panel Study of Income Dynamics 

PTEAM = Particle Total Exposure Assessment Methodology 

RAGS = Risk Assessment Guidance for Superfund 

RDD = Random Digit Dial 

RECS = Residential Energy Conservation Survey 

RfD = Reference Dose 

RfC = Reference Concentration 

ROP = Residential Occupancy Period 

RTF = Ready to Feed 

SA = Surface Area 

SA/BW = Surface Area to Body Weight Ratio 

SAS = Statistical Analysis Software 

SCS = Soil Contact Survey 

SD = Standard Deviation 

SDA = Soaps and Detergent Association 

SE = Standard Error 

SEM = Standard Error of the Mean 

SES = Socioeconomic Status 

SHEDS = Stochastic Human Exposure and Dose Simulation Model 

SMBRP = Santa Monica Bay Restoration Project 

SMRB = Simmons Market Research Bureau 

SOCAL = Southern California 

SPS = Statistical Processing System 

t = Exposure Time 

TDEE = Total Daily Energy Expenditure 

TRF = Tuna Research Foundation 

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ACRONYMS AND ABBREVIATIONS (continued) 

UCL = Upper Confidence Limit 

USDA = United States Department of Agriculture 

USDL = United States Department of Labor 

VE = Volume of Air Breathed per Day 

VO2 = Oxygen Consumption Rate 

VOC = Volatile Organic Compounds 

VQ = Ventilatory Equivalent 

VR = Ventilation Rate 

VT = Tidal Volume 

WHO = World Health Organization 

WIC = USDA’s Women, Infants, and Children Program 

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Exposure Factors Handbook 

Chapter 1—Introduction 

1. INTRODUCTION 

1.1. BACKGROUND AND PURPOSE 

Some of the steps for performing an exposure 

assessment are (1) identifying the source of the 

environmental contamination and the media that 

transports the contaminant; (2) determining the 

contaminant concentration; (3) determining the 

exposure scenarios, and pathways and routes of 

exposure; (4) determining the exposure factors 

related to human behaviors that define time, 

frequency, and duration of exposure; and (5) 

identifying the exposed population. Exposure factors 

are factors related to human behavior and 

characteristics that help

determine an individual's 

exposure to an agent. The 

National Academy of

Sciences (NAS) report on 

Risk Assessment in the

Federal Government:

Managing the Process and subsequent publication of 

the U.S. Environmental Protection Agency’s (EPA) 

exposure guidelines in 1986 identified the need for 

summarizing exposure factors data necessary for 

characterizing some of the steps outlined above (U.S. 

EPA, 1987a; NRC, 1983). Around the same time, the 

U.S. EPA published a report entitled Development of 

Statistical Distributions or Ranges of Standard 

Factors Used in Exposure Assessment to support the 

1986 exposure guidelines and to promote consistency 

in U.S. EPA’s exposure assessment activities (U.S. 

EPA, 1985). The exposure assessment field continued 

to evolve and so did the 

need for more

comprehensive data on 

exposure factors. The

Exposure Factors

Handbook was first

published in 1989 and 

updated in 1997 in

response to this need (U.S. 

EPA, 1997a, 1989a). This 

current edition is the update of the 1997 handbook 

(U.S. EPA, 1997a), and it incorporates data from the 

Child-Specific Exposure Factors Handbook (U.S. 

EPA, 2008a) that was published in September 2008. 

The information presented in this handbook 

supersedes the Child-Specific Exposure Factors 

Handbook published in 2008 (U.S. EPA, 2008a). 

The purpose of the Exposure Factors Handbook 

is to (1) summarize data on human behavioral and 

physiological characteristics that affect exposure to 

environmental contaminants, and (2) provide 

exposure/risk assessors with recommended values for 

Exposure factors are factors related to 

human behavior and characteristics that help 

determine an individual's exposure to an 

agent. 

Purpose: 

(1) summarize data on human behavioral

and physiological characteristics 

(2) provide exposure/risk assessors with

recommended values for these factors 

these factors that can be used to assess exposure 

among both adults and children. 

1.2. INTENDED AUDIENCE 

The Exposure Factors Handbook is intended for 

use by exposure and risk assessors both within and 

outside the U.S. EPA as a reference tool and primary 

source of exposure factor information. It may be used 

by scientists, economists, and other interested parties 

as a source of data and/or U.S. EPA recommendations 

on numeric estimates for behavioral and 

physiological characteristics needed to estimate 

exposure to environmental agents. 

1.3. SCOPE 

This handbook incorporates 

the changes in risk assessment 

practices that were first presented 

in the U.S. EPA’s Cancer 

Guidelines, regarding the need to 

consider life stages rather than subpopulations (U.S. 

EPA, 2005c, e). A life stage “refers to a 

distinguishable time frame in an individual's life 

characterized by unique and relatively stable 

behavioral and/or physiological characteristics that 

are associated with development and growth” (U.S. 

EPA, 2005b). The handbook emphasizes a major 

recommendation in U.S. EPA’s Supplemental 

Guidance for Assessing Susceptibility from Early-Life 

Exposure to Carcinogens (U.S. EPA, 2005e) to sum 

exposures and risks across life stages rather than 

relying on the use of a lifetime average adult 

exposure to calculate risk. This 

handbook also uses updated 

information to incorporate any 

new exposure factors 

data/research that have become 

available since it was last revised 

in 1997 and is consistent with the 

U.S. EPA's new set of 

standardized childhood age 

groups (U.S. EPA, 2005b), which 

are recommended for use in exposure assessments. 

Available data through July 2011 are included in the 

handbook. 

The recommendations presented in this 

handbook are not legally binding on any U.S. EPA 

program and should be interpreted as suggestions that 

program offices or individual exposure assessors can 

consider and modify as needed. The 

recommendations provided in this handbook do not 

supersede standards or guidance established by 

U.S. EPA program offices, states, or other risk 

assessment organizations outside the Agency (e.g., 

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Exposure Factors Handbook 

Chapter 1—Introduction 

World Health Organization, National Research 

Council). Many of these factors are best quantified on 

a site- or situation-specific basis. The decision as to 

whether to use site-specific or national values for an 

assessment may depend on the quality of the 

competing data sets as well as on the purpose of the 

specific assessment. The handbook has strived to 

include full discussions of the issues that assessors 

should consider in deciding how to use these data and 

recommendations. 

This document does not include 

chemical-specific data or information on 

physiological parameters that may be needed for 

exposure assessments involving physiologically 

based pharmacokinetic (PBPK) modeling. 

Information on the application of PBPK models and 

supporting data are found in U.S. EPA (2006a) and 

Lipscomb (2006). 

1.4.	 UPDATES TO PREVIOUS VERSIONS 

OF THE HANDBOOK 

All chapters have been revised to include 

published literature up to July 2011. Some of the 

main revisions are highlighted below: 

 Added food and water intake data obtained 

from the National Health and Nutrition 

Examination Survey (NHANES) 2003–2006; 

 Added fat intake data and total 

food intake data; 

 Added new chapter on non-dietary factors; 

 Updated soil ingestion rates for 

children and adults; 

 Updated data on dermal exposure and added 

information on other factors such as film 

thickness of liquids to skin, transfer of 

residue, and skin thickness; 

 Updated fish intake rates for the general 

population using data obtained from 

NHANES 2003–2006; 

 Updated body-weight data with National 

Health and Nutrition Examination Survey 

1999–2006; 

 Added body-weight data for 

pregnant/lactating women and fetal weight; 

 Updated children’s factors with new 

recommended age groupings (U.S. EPA, 

2005b); 

 Updated life expectancy data with U.S. 

Census Bureau data 2006; 

 Updated data on human milk ingestion and 

prevalence of breast-feeding; and 

 Expanded residential characteristics chapter to 

include data from commercial buildings. 

1.5.	 SELECTION OF STUDIES FOR THE 

HANDBOOK AND DATA 

PRESENTATION 

Many scientific studies were reviewed for 

possible inclusion in this handbook. Although 

systematic literature searches were initially 

conducted for every chapter, much of the literature 

was identified through supplementary targeted 

searches and from personal communications with 

researchers in the various fields. Information in this 

handbook has been summarized from studies 

documented in the scientific literature and other 

publicly available sources. As such, this handbook is 

a compilation of data from a variety of different 

sources. Most of the data presented in this handbook 

are derived from studies that target (1) the general 

population (e.g., Center for Disease Control and 

Prevention [CDC] NHANES) or (2) a sample 

population from a specific area or group (e.g., fish 

consumption among Native American children). With 

very few exceptions, the data presented are the 

analyses of the individual study authors. Since the 

studies included in this handbook varied in terms of 

their objectives, design, scope, presentation of 

results, etc., the level of detail, statistics, and 

terminology may vary from study to study and from 

factor to factor. For example, some authors used 

geometric means to present their results, while others 

used arithmetic means or distributions. Authors have 

sometimes used different terms to describe the same 

racial/ethnic populations. Within the constraint of 

presenting the original material as accurately as 

possible, the U.S. EPA has made an effort to present 

discussions and results in a consistent manner and 

using consistent terminology. The strengths and 

limitations of each study are discussed to provide the 

reader with a better understanding of the uncertainties 

associated with the values derived from the study. 

If it is necessary to characterize a population that 

is not directly covered by the data in this handbook, 

the risk or exposure assessor may need to evaluate 

whether these data may be used as suitable 

substitutes for the population of interest or whether 

there is a need to seek additional population-specific 

data. If information is needed for identifying and 

enumerating populations who may be at risk for 

greater contaminant exposures or who exhibit a 

heightened sensitivity to particular chemicals, refer to 

Socio-demographic Data Used for Identifying 

Potentially Highly Exposed Populations (U.S. EPA, 

1999). 

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Studies were chosen that were seen as useful and 

appropriate for estimating exposure factors for both 

adults and children. In conjunction with the Guidance 

on Selecting Age Groups for Monitoring and 

Assessing Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005b), this handbook 

adopted the age group notation “X to <Y” (e.g., the 

age group 3 to <6 years is meant to span a 3-year 

time interval from a child’s 3rd birthday up until the 

day before his or her 6th birthday). Every attempt was 

made to present the data for the recommended age 

groups. In cases where age group categories from the 

study authors did not match exactly with the 

U.S. EPA recommended age groups, the 

recommendations were matched as closely as 

possible. In some cases, data were limited, and age 

groups were lumped into bigger age categories to 

obtain adequate sample size. It is also recognized that 

dose-response data may not be available for many of 

the recommended age groupings. However, a 

standard set of age groups can assist in data 

collection efforts and provide focus for future 

research to better assess all significant variations in 

life stage (U.S. EPA, 2005b). To this date, no specific 

guidance is available with regard to age groupings for 

presenting adult data. Therefore, adult data (i.e., 

>21 years old) are presented using the age groups 

defined by the authors of the individual studies. No 

attempt was made to reanalyze the data using a 

consistent set of age groups. Therefore, in cases 

where data were analyzed by the U.S. EPA, age 

categories were defined as finely as possible based on 

adequacy of sample size. It is recognized that adults’ 

activity patterns will vary with many factors 

including age, especially in the older adult 

population. 

Certain studies described in this handbook are 

designated as “key,” that is, the most up-to-date and 

scientifically sound for deriving recommendations for 

exposure factors. The recommended values for all 

exposure factors are based on the results of the key 

studies (see Section 1.6). Other studies are designated 

"relevant," meaning applicable or pertinent, but not 

necessarily the most important. As new data or 

analyses are published, “key” studies may be moved 

to the “relevant” category in future revisions because 

they are replaced by more up-to-date data or an 

analysis of improved quality. Studies may be 

classified as “relevant” for one or more of the 

following reasons: (1) they provide supporting data 

(e.g., older studies on food intake that may be useful 

for trend analysis); (2) they provide information 

related to the factor of interest (e.g., data on 

prevalence of breast-feeding); (3) the study design or 

approach makes the data less applicable to the 

population of interest (e.g., studies with small sample 

size, studies not conducted in the United States). 

It is important to note that studies were evaluated 

based on their ability to represent the population for 

which the study was designed. The users of the 

handbook will need to evaluate the studies’ 

applicability to their population of interest. 

1.5.1. General Assessment Factors 

The Agency recognizes the need to evaluate the 

quality and relevance of scientific and technical 

information used in support of Agency actions (U.S. 

EPA, 2006c, 2003d, 2002). When evaluating 

scientific and technical information, the U.S. EPA’s 

Science Policy Council recommends using five 

General Assessment Factors (GAFs): (1) soundness, 

(2) applicability and utility, (3) clarity and 

completeness, (4) uncertainty and variability, and (5) 

evaluation and review (U.S. EPA, 2003d). These 

GAFs were adapted and expanded to include specific 

considerations deemed to be important during 

evaluation of exposure factors data and were used to 

judge the quality of the underlying data used to 

derive recommendations. 

1.5.2. Selection Criteria 

The confidence ratings for the various exposure 

factor recommendations, and selection of the key 

studies that form the basis for these 

recommendations, were based on specific criteria 

within each of the five GAFs, as follows: 

1)	 Soundness: Scientific and technical 

procedures, measures, methods, or models 

employed to generate the information are 

reasonable for, and consistent with, the 

intended application. The soundness of the 

experimental procedures or approaches in the 

study designs of the available studies was 

evaluated according to the following: 

a) Adequacy of the Study Approach Used: 

In general, more confidence was placed 

on experimental procedures or approaches 

that more likely or closely captured the 

desired measurement. Direct exposure 

data collection techniques, such as direct 

observation, personal monitoring devices, 

or other known methods were preferred 

where available. If studies utilizing direct 

measurement were not available, studies 

were selected that relied on validated 

indirect measurement methods such as 

surrogate measures (such as heart rate for 

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inhalation rate), and use of questionnaires. 

If questionnaires or surveys were used, 

proper design and procedures include an 

adequate sample size for the population 

under consideration, a response rate large 

enough to avoid biases, and avoidance of 

bias in the design of the instrument and 

interpretation of the results. More 

confidence was placed in exposure factors 

that relied on studies that gave appropriate 

consideration to these study design issues. 

Studies were also deemed preferable if 

based on primary data, but studies based 

on secondary sources were also included 

where they offered an original analysis. In 

general, higher confidence was placed on 

exposure factors based on primary data. 

b)	 Minimal (or Defined) Bias in Study 

Design: Studies were sought that were 

designed with minimal bias, or at least if 

biases were suspected to be present, the 

direction of the bias (i.e., an overestimate 

or underestimate of the parameter) was 

either stated or apparent from the study 

design. More confidence was placed on 

exposure factors based on studies that 

minimized bias. 

2) Applicability and Utility: The information is 

relevant for the Agency’s intended use. The 

applicability and utility of the available 

studies were evaluated based on the following 

criteria: 

a) Focus on Exposure Factor of Interest: 

Studies were preferred that directly 

addressed the exposure factor of interest 

or addressed related factors that have 

significance for the factor under 

consideration. As an example of the latter 

case, a selected study contained useful 

ancillary information concerning fat 

content in fish, although it did not directly 

address fish consumption. 

b) Representativeness of the Population: 

More confidence was placed in studies 

that addressed the U.S. population. Data 

from populations outside the United 

States were sometimes included if 

behavioral patterns or other characteristics 

of exposure were similar. Studies seeking 

to characterize a particular region or 

demographic characteristic were selected, 

if appropriately representative of that 

population. In cases where data were 

limited, studies with limitations in this 

area were included, and limitations were 

noted in the handbook. Higher confidence 

ratings were given to exposure factors 

where the available data were 

representative of the population of 

interest. The risk or exposure assessor 

may need to evaluate whether these data 

may be used as suitable substitutes for 

their population of interest or whether 

there is a need to seek additional 

population-specific data. 

c)	 Currency of Information: More 

confidence was placed in studies that were 

sufficiently recent to represent current 

exposure conditions. This is an important 

consideration for those factors that change 

with time. Older data were evaluated and 

considered in instances where the 

variability of the exposure factor over 

time was determined to be insignificant or 

unimportant. In some cases, recent data 

were very limited. Therefore, the data 

provided in these instances were the only 

available data. Limitations on the age of 

the data were noted. Recent studies are 

more likely to use state-of-the-art 

methodologies that reflect advances in the 

exposure assessment field. Consequently, 

exposure factor recommendations based 

on current data were given higher 

confidence ratings than those based on 

older data, except in cases where the age 

of the data would not affect the 

recommended values. 

d)	 Adequacy of Data Collection Period: 

Because most users of the handbook are 

primarily addressing chronic exposures, 

studies were sought that utilized the most 

appropriate techniques for collecting data 

to characterize long-term behavior. Higher 

confidence ratings were given to exposure 

factor recommendations that were based 

on an adequate data collection period. 

3) Clarity and Completeness: The degree of 

clarity and completeness with which the data, 

assumptions, methods, quality assurance, 

sponsoring organizations and analyses 

employed to generate the information is 

documented. Clarity and completeness were 

evaluated based on the following criteria: 

a) Accessibility: Studies that the user could 

access in their entirety, if needed, were 

preferred. 

b) Reproducibility: Studies that contained 

sufficient information so that methods 

could be reproduced, or could be 

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evaluated, based on the details of the 

author’s work, were preferred. 

c)	 Quality Assurance: Studies with 

documented quality assurance/quality 

control measures were preferred. Higher 

confidence ratings were given to exposure 

factors that were based on studies where 

appropriate quality assurance/quality 

control measures were used. 

4) Variability and Uncertainty: The variability 

and uncertainty (quantitative and qualitative) 

in the information or the procedures, 

measures, methods, or models are evaluated 

and characterized. Variability arises from true 

heterogeneity across people, places, or time 

and can affect the precision of exposure 

estimates and the degree to which they can be 

generalized. The types of variability include 

spatial, temporal, and inter-individual. 

Uncertainty represents a lack of knowledge 

about factors affecting exposure or risk and 

can lead to inaccurate or biased estimates of 

exposure. Increasingly probabilistic methods 

are being utilized to analyze variability and 

uncertainty independently as well as 

simultaneously. It is sometimes challenging to 

distinguish between variability and parameter 

uncertainty in this context as both can involve 

the distributions of a random variable. The 

types of uncertainty include scenario, 

parameter, and model. More information on 

variability and uncertainty is provided in 

Chapter 2 of this handbook. The uncertainty 

and variability associated with the studies 

were evaluated based on the following 

criteria: 

a) Variability in the Population: Studies 

were sought that characterized any 

variability within populations. The 

variability associated with the 

recommended exposure factors is 

described in Section 1.6. Higher 

confidence ratings were given to exposure 

factors that were based on studies where 

variability was well characterized. 

b) Uncertainty: Studies were sought with 

minimal uncertainty in the data, which 

was judged by evaluating all the 

considerations listed above. Studies were 

preferred that identified uncertainties, 

such as those due to possible 

measurement error. Higher confidence 

ratings were given to exposure factors 

based on studies where uncertainty had 

been minimized. 

5)	 Evaluation and Review: The information or 

the procedures, measures, methods, or models 

are independently verified, validated, and peer 

reviewed. Relevant factors that were 

considered included: 

a) Peer Review: Studies selected were those 

from the peer-reviewed literature and final 

government reports. Unpublished and 

internal or interim reports were avoided, 

where possible. but were used in some 

cases to supplement information in 

published literature or government 

reports. 

b)	 Number and Agreement of Studies: 

Higher confidence was placed on 

recommendations where data were 

available from more than one key study, 

and there was good agreement between 

studies. 

1.6.	 APPROACH USED TO DEVELOP 

RECOMMENDATIONS FOR 

EXPOSURE FACTORS 

As discussed above, the U.S. EPA first reviewed 

the literature pertaining to a factor and determined 

key studies. These key studies were used to derive 

recommendations for the values of each factor. The 

recommended values were derived solely from the 

U.S. EPA’s interpretation of the available data. 

Different values may be appropriate for the user in 

consideration of policy, precedent, strategy, or other 

factors such as site-specific information. The 

U.S. EPA’s procedure for developing 

recommendations was as follows: 

1)	 Study Review and Evaluation: Key studies 

were evaluated in terms of both quality and 

relevance to specific populations (general 

U.S. population, age groups, sex, etc.). 

Section 1.5 describes the criteria for 

assessing the quality of studies. 

2)	 Selection of One versus Multiple Key 

Studies: If only one study was classified as 

key for a particular factor, the mean value 

from that study was selected as the 

recommended central value for that 

population. If multiple key studies with 

reasonably equal quality, relevance, and 

study design information were available, a 

weighted mean (if appropriate, considering 

sample size and other statistical factors) of 

the studies was chosen as the recommended 

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mean value. Recommendations for upper 

percentiles, when multiple studies were 

available, were calculated as the mid-point of 

the range of upper percentile values of the 

studies for each age group where data were 

available. It is recognized that the mid-point 

of the range of upper percentiles may not 

provide the best estimate, but in the absence 

of raw data, more sophisticated analysis 

could not be performed. 

3) Assessing Variability: The variability of the 

factor across the population is discussed. For 

recommended values, as well as for each of 

the studies on which the recommendations 

are based, variability was characterized in 

one or more of three ways: (1) as a table with 

various percentiles or ranges of values; (2) as 

analytical distributions with specified 

parameters; and/or (3) as a qualitative 

discussion. Analyses to fit standard or 

parametric distributions (e.g., normal, 

lognormal) to the exposure data have not 

been performed by the authors of this 

handbook, but have been reproduced as they 

were found in the literature. 

Recommendations on the use of these 

distributions were made where appropriate 

based on the adequacy of the supporting data. 

Table 1-1 presents the list of exposure factors 

and the way in which variability in the 

population has been characterized throughout 

this handbook (i.e., average, median, upper 

percentiles, multiple percentiles). 

In providing recommendations for the 

various exposure factors, an attempt was 

made to present percentile values that are 

consistent with the exposure estimators 

defined in Guidelines for Exposure 

Assessment (U.S. EPA, 1992c) (i.e., mean, 

50th, 90th, 95th, 98th, and 99.9th percentiles). 

However, this was not always possible, 

because the data available were limited for 

some factors, or the authors of the study did 

not provide such information. It is important 

to note, however, that these percentiles were 

discussed in the guidelines within the context 

of risk descriptors and not individual 

exposure factors. For example, the guidelines 

state that the assessor may derive a high-end 

estimate of exposure by using maximum or 

near maximum values for one or more 

sensitive exposure factors, leaving others at 

their mean value. The term “upper 

percentile” is used throughout this handbook, 

and it is intended to represent values in the 

upper tail (i.e., between 90th and 

99.9th percentiles) of the distribution of 

values for a particular exposure factor. Tables 

providing summaries of recommendations at 

the beginning of each chapter generally 

present a mean and an upper percentile value. 

The 95th percentile was used as the upper 

percentile in these tables, if available, 

because it is the middle of the range between 

the 90th and 99.9th percentiles. Other 

percentiles are presented, where available, in 

the tables at the end of the chapters. Users of 

the handbook should employ the exposure 

metric that is most appropriate for their 

particular situation. 

4)	 Assessing Uncertainty: Uncertainties are 

discussed in terms of data limitations, the 

range of circumstances over which the 

estimates were (or were not) applicable, 

possible biases in the values themselves, a 

statement about parameter uncertainties 

(measurement error, sampling error), and 

model or scenario uncertainties if models or 

scenarios were used to derive the 

recommended value. A more detailed 

discussion of variability and uncertainty for 

exposure factors is presented in Chapter 2 of 

this handbook. 

5)	 Assigning Confidence Ratings: Finally, the 

U.S. EPA assigned a confidence rating of low, 

medium, or high to each recommended value 

in each chapter. This qualitative rating is not 

intended to represent an uncertainty analysis; 

rather, it represents the U.S. EPA’s judgment 

on the quality of the underlying data used to 

derive the recommendation. This judgment 

was made using the GAFs described in 

Section 1.5. Table 1-2 provides an adaptation 

of the GAFs, as they pertain to the 

confidence ratings for the exposure factor 

recommendations. Clearly, there is a 

continuum from low to high, and judgment 

was used to assign a rating to each factor. It is 

important to note that these confidence 

ratings are based on the strengths and 

limitations of the underlying data and not on 

how these data may be used in a particular 

exposure assessment. 

The study elements listed in Table 1-2 do 

not have the same weight when arriving at 

the overall confidence rating for the various 

exposure factors. The relative weight of each 

of these elements for the various factors was 

subjective and based on the professional 

judgment of the authors of this handbook. 

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Also, the relative weights depend on the 

exposure factor of interest. For example, the 

adequacy of the data collection period may 

be more important when determining usual 

intake of foods in a population, but it is not as 

important for factors where long-term 

variability may be small, such as tap water 

intake. In the case of tap water intake, the 

currency of the data was a critical element in 

determining the final rating. In general, most 

studies ranked high with regard to “level of 

peer review,” “accessibility,” “focus on the 

factor of interest,” and “data pertinent to the 

United States” because the U.S. EPA 

specifically sought studies for the handbook 

that met these criteria. 

The confidence rating is also a reflection 

of the ease at which the exposure factor of 

interest could be measured. This is taken into 

consideration under the soundness criterion. 

For example, soil ingestion by children can 

be estimated by measuring, in feces, the 

levels of certain elements found in soil. Body 

weight, however, can be measured directly, 

and it is, therefore, a more reliable 

measurement than estimation of soil 

ingestion. The fact that soil ingestion is more 

difficult to measure than body weight is 

reflected in the overall confidence rating 

given to both of these factors. In general, the 

better the methodology used to measure the 

exposure factor, the higher the confidence in 

the value. 

Some exposure factors recommendations 

may have different confidence ratings 

depending on the population of interest. For 

example a lower confidence rating may be 

noted for some age groups for which sample 

sizes are small. As another example, a lower 

confidence rating was assigned to the 

recommendations as they would apply to 

long-term chronic exposures versus acute 

exposures because of the short-term nature of 

the data collection period. To the extent 

possible, these caveats were noted in the 

confidence rating tables. 

6)	 Recommendation Tables: The U.S. EPA 

developed a table at the beginning of each 

chapter that summarizes the recommended 

values for the relevant factor. Table ES-1 of 

the Executive Summary of this handbook 

summarizes the principal exposure factors 

addressed in this handbook and provides the 

confidence ratings for each exposure factor. 

1.7.	 SUGGESTED REFERENCES FOR USE 

IN CONJUNCTION WITH THIS 

HANDBOOK 

Many of the issues related to characterizing 

exposure from selected exposure pathways have been 

addressed in a number of existing U.S. EPA 

documents. Some of these provide guidance while 

others demonstrate various aspects of the exposure 

process. These include, but are not limited to, the 

following references listed in chronological order: 

 Methods for Assessing Exposure to 

Chemical Substances, Volumes 1–13 (U.S. 

EPA, 1983-1989); 

 Standard Scenarios for Estimating Exposure 

to Chemical Substances During Use of 

Consumer Products (U.S. EPA, 1986b, c); 

 Selection Criteria for Mathematical Models 

Used in Exposure Assessments: Surface 

Water Models (U.S. EPA, 1987b); 

 Selection Criteria for Mathematical Models 

Used in Exposure Assessments: 

Groundwater Models (U.S. EPA, 1988); 

 Risk Assessment Guidance for Superfund, 

Volume I, Part A, Human Health Evaluation 

Manual (U.S. EPA, 1989b); 

 Methodology for Assessing Health Risks 

Associated with Indirect Exposure to 

Combustor Emissions (U.S. EPA, 1990); 

 Risk Assessment Guidance for Superfund, 

Volume I, Part B, Development of 

Preliminary Remediation Goals (U.S. EPA, 

1991a); 

 Risk Assessment Guidance for Superfund, 

Volume I, Part C, Risk Evaluation of 

Remedial Alternatives (U.S. EPA, 1991b); 

 Guidelines for Exposure Assessment (U.S. 

EPA, 1992c); 

 Dermal Exposure Assessment: Principles 

and Applications (U.S. EPA, 1992a); 

 Soil Screening Guidance (U.S. EPA, 1996b); 

 Series 875 Occupational and Residential 

Exposure Test Guidelines—Final Guidelines 

—Group A—Application Exposure 

Monitoring Test Guidelines (U.S. EPA, 

1996a); 

 Series 875 Occupational and Residential 

Exposure Test Guidelines—Group B—Post 

Application Exposure Monitoring Test 

Guidelines (U.S. EPA, 1998); 

 Policy for Use of Probabilistic Analysis in 

Risk Assessment at the U.S. Environmental 

Protection Agency (U.S. EPA, 1997c); 

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 Guiding Principles for Monte Carlo 

Analysis (U.S. EPA, 1997b); 

 Sociodemographic Data for Identifying 

Potentially Highly Exposed Populations 

(U.S. EPA, 1999); 

 Options for Development of Parametric 

Probability Distributions for Exposure 

Factors (U.S. EPA, 2000a); 

 Risk Assessment Guidance for Superfund, 

Volume I, Part D, Standardized Planning, 

Reporting, and Review of Superfund Risk 

Assessments (U.S. EPA, 2001b); 

 Risk Assessment Guidance for Superfund 

Volume III, Part A, Process for Conducting 

Probabilistic Risk Assessments (U.S. EPA, 

2001c) 

 Framework for Cumulative Risk Assessment 

(U.S. EPA, 2003b); 

 Example Exposure Scenarios (U.S. EPA, 

2004a); 

 Exposure and Human Health Reassessment 

of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin 

(TCDD) and Related Compounds National 

Academy Sciences Review Draft (U.S. EPA, 

2003a); 

 Risk Assessment Guidance for Superfund, 

Volume I, Part E, Supplemental Guidance 

for Dermal Risk Assessment (U.S. EPA, 

2004b); 

 Cancer Guidelines for Carcinogen Risk 

Assessment (U.S. EPA, 2005c); 

 Supplemental Guidance for Assessing 

Susceptibility from Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005e); 

 Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants 

(U.S. EPA, 2005b); 

 Human Health Risk Assessment Protocol for 

Hazardous Waste Combustion Facilities 

(U.S. EPA, 2005d); 

 Aging and Toxic Response: Issues Relevant 

to Risk Assessment (U.S. EPA, 2005a); 

 A Framework for Assessing Health Risk of 

Environmental Exposures to Children (U.S. 

EPA, 2006b); 

 Dermal Exposure Assessment: A Summary 

of EPA Approaches (U.S. EPA, 2007b); 

 Child-Specific Exposure Factors Handbook 

(U.S. EPA, 2008a); 

 Concepts, Methods, and Data Sources For 

Cumulative Health Risk Assessment of 

Multiple Chemicals, Exposures and Effects: 

A Resource Document (U.S. EPA, 2007a); 

 Physiological Parameters Database for 

Older Adults (Beta 1.1) (U.S. EPA, 2008b); 

 Risk Assessment Guidance for Superfund 

Volume I: Human Health Evaluation 

Manual Part F, Supplemental Guidance for 

Inhalation Risk Assessment (U.S. EPA, 

2009b); 

 Draft Technical Guidelines Standard 

Operating Procedures for Residential 

Pesticide Exposure Assessment (U.S. EPA, 

2009a); 

 Stochastic Human Exposure and Dose 

Simulation (SHEDS)-Multimedia. Details of 

SHEDS-Multimedia Version 3: ORD/NERL’s 

Model to Estimate Aggregate and 

Cumulative Exposures to Chemicals (U.S. 

EPA, 2010); and 

 Recommended Use of Body Weight3/4 (BW3/4) 

as the Default Method in Derivation of the 

Oral Reference Dose (RfD) (U.S. EPA, 

2011). 

These documents may serve as valuable 

information resources to assist in the assessment of 

exposure. Refer to them for more detailed discussion. 

1.8. THE USE OF AGE GROUPINGS 

WHEN ASSESSING EXPOSURE 

When this handbook was published in 1997, no 

specific guidance existed with regard to which age 

groupings should be used when assessing children’s 

exposure. Age groupings varied from case to case and 

among Program Offices within the U.S. EPA. They 

depended on availability of data and were often based 

on professional judgment. More recently, the U.S. 

EPA has established a consistent set of age groupings 

and published guidance on this topic (U.S. EPA, 

2005b). This revision of the handbook attempts to 

present data in a manner consistent with the U.S. 

EPA’s recommended set of age groupings for 

children. The presentation of data for these fine age 

categories does not necessarily mean that every age 

category needs to be the subject of a particular 

assessment. It will depend on the objectives of the 

assessment and communications with toxicologists to 

identify the critical windows of susceptibility. 

The development of standardized age bins for 

children was the subject of discussion in a 2000 

workshop sponsored by the U.S. EPA Risk 

Assessment Forum. The workshop was titled Issues 

Associated with Considering Developmental Changes 

in Behavior and Anatomy When Assessing Exposure 

to Children (U.S. EPA, 2000b). The purpose of this 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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workshop was to gain insight and input into factors 

that need to be considered when developing 

standardized age bins and to identify future research 

necessary to accomplish these goals. 

Based upon consideration of the findings of the 

technical workshop, as well as analysis of available 

data, U.S. EPA developed guidance that established a 

set of recommended age groups for development of 

exposure factors for children entitled Guidance for 

Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005b). This revision of 

the handbook for individuals <21 years of age 

presents exposure factors data in a manner consistent 

with U.S. EPA’s recommended set of childhood age 

groupings. The recommended age groups (U.S. EPA, 

2005b) are as follows: 

Birth to <1 month
 

1 to <3 months
 

3 to <6 months
 

6 to <12 months
 

1 to <2 years
 

2 to <3 years
 

3 to <6 years
 

6 to <11 years
 

11 to <16 years
 

16 to <21 years
 

1.9.	 CONSIDERING LIFE STAGE WHEN 

CALCULATING EXPOSURE AND 

RISK 

In recent years, there has been an increased 

concern regarding the potential impact of 

environmental exposures to children and other 

susceptible populations such as older adults and 

pregnant/lactating women. As a result, the U.S. EPA 

and others have developed policy and guidance and 

undertaken research to better incorporate life stage 

data into human health risk assessment (Brown et al., 

2008). The Child-Specific Exposure Factors 

Handbook was published in 2008 to address the need 

to characterize children’s exposures at various life 

stages (U.S. EPA, 2008a). Children are of special 

concern because (1) they consume more of certain 

foods and water per unit of body weight than adults; 

(2) they have a higher ratio of body surface area to 

volume than adults; and (3) they experience 

important, rapid changes in behavior and physiology 

that may lead to differences in exposure (Moya et al., 

2004). Many studies have shown that young children 

can be exposed to various contaminants, including 

pesticides, during normal oral exploration of their 

environment (i.e., hand-to-mouth behavior) and by 

touching floors, surfaces, and objects such as toys 

(Garry, 2004; Eskenazi et al., 1999; Lewis et al., 

1999; Nishioka et al., 1999; Gurunathan et al., 1998). 

Dust and tracked-in soil accumulate in carpets, where 

young children spend a significant amount of time 

(Lewis et al., 1999). Children living in agricultural 

areas may experience higher exposures to pesticides 

than do other children (Curwin et al., 2007). They 

may play in nearby fields or be exposed via 

consumption of contaminated human milk from their 

farmworker mothers (Eskenazi et al., 1999). 

In terms of risk, children may also differ from 

adults in their vulnerability to environmental 

pollutants because of toxicodynamic differences (e.g., 

when exposures occur during periods of enhanced 

susceptibility) and/or toxicokinetic differences (i.e., 

differences in absorption, metabolism, and excretion) 

(U.S. EPA, 2000b). The immaturity of metabolic 

enzyme systems and clearance mechanisms in young 

children can result in longer half-lives of 

environmental contaminants (Clewell et al., 2004; 

Ginsberg et al., 2002). The cellular immaturity of 

children and the ongoing growth processes account 

for elevated risk (American Academy of Pediatrics, 

1997). Toxic chemicals in the environment can cause 

neurodevelopmental disabilities, and the developing 

brain can be particularly sensitive to environmental 

contaminants. For example, elevated blood lead 

levels and prenatal exposures to even relatively low 

levels of lead can result in behavior disorders and 

reductions of intellectual function in children 

(Landrigan et al., 2005). Exposure to high levels of 

methylmercury can result in developmental 

disabilities (e.g., intellectual deficiency, speech 

disorders, and sensory disturbances) among children 

(Myers and Davidson, 2000). Other authors have 

described the importance of exposure timing (i.e., 

pre-conceptional, prenatal, and postnatal) and how it 

affects the outcomes observed (Selevan et al., 2000). 

Exposures during these critical windows of 

development and age-specific behaviors and 

physiological factors can lead to differences in 

response (Makri et al., 2004). Fetal exposures can 

occur from the mobilization of chemicals of maternal 

body burden and transfer of those chemicals across 

the placenta (Makri et al., 2004). Absorption through 

the gastrointestinal tract is more efficient in neonates 

and infants, making ingestion exposures a significant 

route of exposure during the first year of age (Makri 

et al., 2004). 

It has also been suggested that higher levels of 

exposure to indoor air pollution and allergens among 

inner-city children compared to non-inner-city 

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children may explain the difference in asthma levels 

between these two groups (Breysse et al., 2005). With 

respect to contaminants that are carcinogenic via a 

mutagenic mode of action (MOA), the U.S. EPA has 

found that childhood is a particularly sensitive period 

of development in which cancer potencies per year of 

exposure can be an order of magnitude higher than 

during adulthood (U.S. EPA, 2005e). 

A framework for considering life stages in 

human health risk assessments was developed by the 

U.S. EPA in the report entitled A Framework for 

Assessing Health Risks of Environmental Exposures 

to Children (U.S. EPA, 2006b). Life stages are 

defined as “temporal stages (or intervals) of life that 

have distinct anatomical, physiological, behavioral, 

and/or functional characteristics that contribute to 

potential differences in environmental exposures” 

(Brown et al., 2008). One way to understand the 

differential exposures among life stages is to study 

the data using age binning or age groups as it is the 

recommendation for childhood exposures. Although 

the framework discusses the importance of 

incorporating life stages in the evaluation of risks to 

children, the approach can also be applied to other 

life stages that may have their own unique 

susceptibilities. For example, older individuals may 

experience differential exposures and risks to 

environmental contaminants due to biological 

changes that occur during aging, disease status, drug 

interactions, different exposure patterns, and 

activities. More information on the toxicokinetic and 

toxicodynamic impact of environmental agents in 

older adults can be found in U.S. EPA’s document 

entitled Aging and Toxic Response: Issues Relevant to 

Risk Assessment (U.S. EPA, 2005a). The need to 

better characterize differential exposures of the older 

adult population to environmental agents was 

recognized at the U.S. EPA’s workshop on the 

development of exposure factors for the aging (U.S. 

EPA, 2007c). A panel of experts in the fields of 

gerontology, physiology, exposure assessment, risk 

assessment, and behavioral science discussed existing 

data, data gaps, and current relevant research on the 

behavior and physiology of older adults, as well as 

practical considerations of the utility of developing 

an exposure factors handbook for the aging (U.S. 

EPA, 2007c). Pregnant and lactating women may also 

be a life stage of concern due to physiological 

changes during pregnancy and lactation. For 

example, lead is mobilized from the maternal 

skeleton during pregnancy and the postpartum period, 

increasing the chances for fetal lead exposure 

(Gulson et al., 1999). 

The U.S. EPA encourages the consideration of all 

life stages and endpoints to ensure that vulnerabilities 

during specific time periods are taken into account 

(Brown et al., 2008). Although the importance of 

assessing risks from environmental exposures to all 

susceptible populations is recognized, most of the 

guidance developed thus far relates to children. 

Furthermore, it is recognized that there is a lack of 

dose-response data to evaluate differential responses 

at various life stages (e.g., age groups, 

pregnant/lactating mothers, older populations). A key 

component of U.S. EPA’s Guidance on Selecting Age 

Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. 

EPA, 2005b) involves the need to sum age-specific 

exposures across time when assessing long-term 

exposure, as well as integrating these age-specific 

exposures with age-specific differences in toxic 

potency in those cases where information exists to 

describe such differences: an example is carcinogens 

that act via a mutagenic mode of action 

[Supplemental Guidance for Assessing Susceptibility 

from Early-Life Exposure to Carcinogens – (U.S. 

EPA, 2005e)]. When assessing chronic risks (i.e., 

exposures greater than 10% of human lifespan), 

rather than assuming a constant level of exposure for 

70 years (usually consistent with an adult level of 

exposure), the Agency is now recommending that 

assessors calculate chronic exposures by summing 

time-weighted exposures that occur at each life stage; 

this handbook provides data arrayed by childhood 

age in order to follow this new guidance (U.S. EPA, 

2005e). This approach is expected to increase the 

accuracy of risk assessments, because it will take into 

account life stage differences in exposure. Depending 

on whether body-weight-adjusted childhood 

exposures are either smaller or larger compared to 

those for adults, calculated risks could either decrease 

or increase when compared with the historical 

approach of assuming a lifetime of a constant adult 

level of exposure. 

The Supplemental Guidance report also 

recommended that in those cases where age-related 

differences in toxicity were also found to occur, 

differences in both toxicity and exposure would need 

to be integrated across all relevant age intervals (U.S. 

EPA, 2005e). This guidance describes such a case for 

carcinogens that act via a mutagenic mode of action, 

where age dependent adjustments factors (ADAFs) of 

10× and 3× are recommended for children ages birth 

to <2 years, and 2 to <16 years, respectively, when 

there is exposure during those years, and available 

data are insufficient to derive chemical-specific 

adjustment factors. 

Table 1-3, along with Chapter 6 of the 

Supplemental Guidance (U.S. EPA, 2005e) report, 

have been developed to help the reader understand 

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how to use the new sets of exposure and potency age 

groupings when calculating risk through the 

integration of life stage specific changes in exposure 

and potency for mutagenic carcinogens. 

Thus, Table 1-3 presents Lifetime Cancer Risk 

(for a population with average life expectancy of 70 

years) = ∑ (Exposure × Duration/70 years × Potency 

× ADAF) summed across all the age groups. This is a 

departure from the way cancer risks have historically 

been calculated based upon the premise that risk is 

proportional to the daily average of the long-term 

adult dose. 

1.10.	 FUNDAMENTAL PRINCIPLES OF 

EXPOSURE ASSESSMENT 

An exposure assessment is the “process of 

estimating or measuring the magnitude, frequency, 

and duration of exposure to an agent, along with the 

number and characteristics of the population 

exposed” (Zartarian et al., 2007). The definition of 

exposure as used by the International Program on 

Chemical Safety (WHO, 2001) is the “contact of an 

organism with a chemical or physical agent, 

quantified as the amount of chemical available at the 

exchange boundaries of the organism and available 

for absorption.” The term “agent” refers to a 

chemical, biological, or physical entity that contacts a 

target. The “target” refers to any physical, biological, 

or ecological object exposed to an agent. In the case 

of human exposures, the contact occurs with the 

visible exterior of a person (i.e., target) such as the 

skin, and openings such as the mouth, nostrils, and 

lesions. The process by which an agent crosses an 

outer exposure surface of a target without passing an 

absorption barrier (i.e., through ingestion or 

inhalation) is called an intake. The resulting dose is 

the intake dose. The intake dose is sometimes 

referred to in the literature as the administered dose 

or potential dose. 

The terms “exposure” and “dose” are very 

closely related and, therefore, are often confused 

(Zartarian et al., 2007). Dose is the amount of agent 

that enters a target in a specified period of time after 

crossing a contact boundary. An exposure does not 

necessarily leads to a dose. However, there can be no 

dose without a corresponding exposure (Zartarian et 

al., 2007). Figure 1-1 illustrates the relationship 

between exposure and dose. 

AGENT
 

EXPOSURE 

DOSE 

TARGET 

CONTACT BOUNDARY 

Figure 1-1. Conceptual Drawing of Exposure and 

Dose Relationship (Zartarian et al., 2007). 

In other words, the process of an agent entering 

the body can be described in two steps: contact 

(exposure) followed by entry (crossing the 

boundary). In the context of environmental risk 

assessment, risk to an individual or population can be 

represented as a continuum from the source through 

exposure to dose to effect as shown in Figure 1-2 

(Ott, 2007; WHO, 2006; U.S. EPA, 2003c). The 

process begins with a chemical or agent released 

from a source into the environment. Once in the 

environment, the agent can be transformed and 

transported through the environment via air, water, 

soil, dust, and diet (i.e., exposure pathway). Fate and 

transport mechanisms result in various chemical 

concentrations with which individuals may come in 

contact. Individuals encounter the agent either 

through inhalation, ingestion, or skin/eye contact 

(i.e., exposure route). The individual’s activity 

patterns as well as the concentration of the agent will 

determine the magnitude, frequency, and duration of 

the exposure. The exposure becomes an absorbed 

dose when the agent crosses an absorption barrier 

(e.g., skin, lungs, gut). Other terms used in the 

literature to refer to absorbed dose include internal 

dose, bioavailable dose, delivered dose, applied dose, 

active dose, and biologically effective dose (Zartarian 

et al., 2007). When an agent or its metabolites 

interact with a target tissue, it becomes a target tissue 

dose, which may lead to an adverse health outcome. 

The text under the boxes in Figure 1-2 indicates the 

specific information that may be needed to 

characterize each box. 

This approach has been used historically in 

exposure assessments and exposure modeling. It is 

usually referred to as source-to-dose approach. In 

recent years, person-oriented approaches and models 

have gained popularity. This approach is aimed at 

accounting for cumulative and aggregate exposures 

to individuals (Georgopoulos, 2008; Price et al., 

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2003a). The person-oriented approach can also take 

advantage of information about the individual’s 

susceptibility to environmental factors (e.g., genetic 

differences) (Georgopoulos, 2008). 

There are three approaches to calculate 

exposures: (1) the point-of-contact approach, (2) the 

scenario evaluation approach, and (3) the dose 

reconstruction approach (U.S. EPA, 1992c). The data 

presented in this handbook are generally useful for 

evaluating exposures using the scenario approach. 

There are advantages and disadvantages associated 

with each approach. Although it is not the purpose of 

this handbook to provide guidance on how to conduct 

an exposure assessment, a brief description of the 

approaches is provided below. 

The point-of-contact approach, or direct 

approach, involves measurements of chemical 

concentrations at the point where exposure occurs 

(i.e., at the interface between the person and the 

environment). This chemical concentration is coupled 

with information on the length of contact with each 

chemical to calculate exposure. The scenario 

evaluation approach, or the indirect approach, utilizes 

data on chemical concentration, frequency, and 

duration of exposure as well as information on the 

behaviors and characteristics of the exposed life 

stage. The third approach, dose reconstruction, allows 

exposure to be estimated from dose, which can be 

reconstructed through the measurement of 

biomarkers of exposure. A biomarker of exposure is a 

chemical, its metabolite, or the product of an 

interaction between a chemical and some target 

molecule or cell that is measured in a compartment in 

an organism (NRC, 2006). Biomonitoring is 

becoming a tool for identifying, controlling, and 

preventing human exposures to environmental 

chemicals (NRC, 2006). For example, blood lead 

concentrations and the associated health effects were 

used by the U.S. EPA in its efforts to reduce exposure 

to lead in gasoline. The Centers for Disease Control 

and Prevention conducts biomonitoring studies to 

help identify chemicals that are both present in the 

environment and in human tissues (NRC, 2006). 

Biomonitoring studies also assist public health 

officials in studying distributions of exposure in a 

population and how they change overtime. 

Biomonitoring data can be converted to exposure 

using pharmacokinetic modeling (NRC, 2006). 

Although biomonitoring can be a powerful tool, 

interpretation of the data is difficult. Unlike the other 

two approaches, biomonitoring provides information 

on internal doses integrated across environmental 

pathways and media. Interpretation of these data 

requires knowledge and understanding of how the 

chemicals are absorbed, excreted, and metabolized in 

the biological system, as well as the properties of the 

chemicals and their metabolites (NRC, 2006). The 

interpretation of biomarker data can be further 

improved by the development of other cellular and 

molecular approaches to include advances in 

genomics, proteomics, and other approaches that 

make use of molecular-environmental interactions 

(Lioy et al., 2005). Physiological parameters can also 

vary with life stage, age, sex, and other demographic 

information (Price et al., 2003b). Physiologic and 

metabolic factors and how they vary with life stage 

have been the subject of recent research. 

Pharmacokinetic models are frequently developed 

from data obtained from young adults. Therapeutic 

drugs have been used as surrogates to study 

pharmacokinetic differences in fetuses, children, and 

adults (Ginsberg et al., 2004). Specific considerations 

of susceptibilities for other populations (e.g., 

children, older adults) require knowledge of the 

physiological parameters that most influence the 

disposition of the chemicals in the body (Thompson 

et al., 2009). Physiological parameters include 

alveolar ventilation, cardiac output, organ and tissue 

weights and volumes, blood flows to organs and 

tissues, clearance parameters, and body composition 

(Thompson et al., 2009). Price et al. (2003b) 

developed a tool for capturing the correlation 

between organs and tissue and compartment volumes, 

blood flows, body weight, sex, and other 

demographic information. A database that records 

key, age-specific pharmacokinetic model inputs for 

healthy older adults and for older adults with 

conditions such as diabetes, chronic obstructive 

pulmonary disease, obesity, heart disease, and renal 

disease has been developed by the U.S. EPA 

(Thompson et al., 2009; U.S. EPA, 2008b). 

Computational exposure models can play an 

important role in estimating exposures to 

environmental chemicals (Sheldon and Cohen Hubal, 

2009). In general, these models combine 

measurements of the concentration of the chemical 

agent in the environment (e.g., air, water, soil, food) 

with information about the individual’s activity 

patterns to estimate exposure (WHO, 2005). Several 

models have been developed and may be used to 

support risk management decisions. For example, the 

U.S. EPA SHEDS model is a probabilistic model that 

simulates daily activities to predict distributions of 

daily exposures in a population (U.S. EPA, 2010). 

Other models such as the Modeling Environment for 

Total Risk Studies incorporates and expands the 

approach used by SHEDS and considers multiple 

routes of exposure (Georgopoulos and Lioy, 2006). 

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1.10.1. Exposure and Dose Equations 

Exposure can be quantified by multiplying the 

concentration of an agent times the duration of the 

contact. Exposure can be instantaneous when the 

contact between an agent and a target occurs at a 

single point in time and space (Zartarian et al., 2007). 

The summation of instantaneous exposures over the 

exposure duration is called the time-integrated 

exposure (Zartarian et al., 2007). Equation 1-1 shows 

the time-integrated exposure. 

t2 

E = ∫C(t)dt (Eqn. 1-1) 

t

1 

where: 

E = Time-integrated exposure 

(mass/volume), 

t2 – t1 = Exposure duration (ED) (time), 

and 

C = Exposure concentration as a 

function of time (mass/volume). 

Dividing the time-integrated exposure by the 

exposure duration, results in the time-averaged 

exposure (Zartarian et al., 2007). 

Dose can be classified as an intake dose or an 

absorbed dose (U.S. EPA, 1992c). Starting with a 

general integral equation for exposure, several dose 

equations can be derived depending upon boundary 

assumptions. One of the more useful of these derived 

equations is the average daily dose (ADD). The 

ADD, which is used for many non-cancer effects, 

averages exposures or doses over the period of time 

exposure occurred. The ADD can be calculated by 

averaging the intake dose over body weight and an 

averaging time as shown in Equations 1-2 and 1-3. 

Intake Dose ADD = (Eqn. 1-2) Body Weight x Averaging Time 

The exposure can be expressed as follows: 

Intake Dose = C × IR × ED (Eqn. 1-3) 

where: 

C = Concentration of the Agent 

(mass/volume), 

IR = Intake Rate (mass/time), and 

ED = Exposure Duration (time). 

Concentration of the agent is the mass of the 

agent in the medium (air, food, soil, etc.) per unit 

volume contacting the body and has units of 

mass/volume or mass/mass. 

The intake rate refers to the rates of inhalation, 

ingestion, and dermal contact, depending on the route 

of exposure. For ingestion, the intake rate is simply 

the amount of contaminated food ingested by an 

individual during some specific time period (units of 

mass/time). Much of this handbook is devoted to 

rates of ingestion for some broad classes of food. For 

inhalation, the intake rate is that at which 

contaminated air is inhaled. Factors presented in this 

handbook that affect dermal exposure are skin 

surface area and estimates of the amount of solids 

that adheres to the skin, film thickness of liquids to 

skin, transfer of residues, and skin thickness. It is 

important to note that there are other key factors in 

the calculation of dermal exposures that are not 

covered in this handbook (e.g., chemical-specific 

absorption factors). 

The exposure duration is the length of time of 

contact with an agent. For example, the length of 

time a person lives in an area, frequency of bathing, 

time spent indoors versus outdoors, and in various 

microenvironments, all affect the exposure duration. 

Chapter 16, Activity Factors, gives some examples of 

population behavior and macro and micro activities 

that may be useful for estimating exposure durations. 

When the above parameter values IR and ED 

remain constant over time, they are substituted 

directly into the dose equation. When they change 

with time, a summation approach is needed to 

calculate dose. In either case, the exposure duration is 

the length of time exposure occurs at the 

concentration and the intake rate specified by the 

other parameters in the equation. 

Note that the advent of childhood age groupings 

means that separate ADDs should be calculated for 

each age group considered. Chronic exposures can 

then be calculated by summing across each life 

stage-specific ADD. 

Cancer risks have traditionally been calculated in 

those cases where a linear non-threshold model is 

assumed, in terms of lifetime probabilities by 

utilizing dose values presented in terms of lifetime 

ADDs (LADDs). The LADD takes the form of 

Equation 1-2, with lifetime replacing averaging time. 

While the use of LADDs may be appropriate when 

developing screening-level estimates of cancer risk, 

the U.S. EPA recommends that risks should be 

calculated by integrating exposures or risks 

throughout all life stages (U.S. EPA, 1992c). 

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For some types of analyses, dose can be 

expressed as a total amount (with units of mass, e.g., 

mg) or as a dose rate in terms of mass/time (e.g., 

mg/day), or as a rate normalized to body mass (e.g., 

with units of mg of chemical per kg of body weight 

per day [mg/kg-day]). The LADD is usually 

expressed in terms of mg/kg-day or other 

mass/mass-time units. 

In most cases (inhalation and ingestion 

exposures), the dose-response parameters for 

carcinogenic risks have been adjusted for the 

difference in absorption across body barriers between 

humans and the experimental animals used to derive 

such parameters. Therefore, the exposure assessment 

in these cases is based on the intake dose, with no 

explicit correction for the fraction absorbed. 

However, the exposure assessor needs to make such 

an adjustment when calculating dermal exposure and 

in other specific cases when current information 

indicates that the human absorption factor used in the 

derivation of the dose-response factor is 

inappropriate. 

For carcinogens, the duration of a lifetime has 

traditionally been assigned the nominal value of 

70 years as a reasonable approximation. For dose 

estimates to be used for assessments other than 

carcinogenic risk, various averaging periods have 

been used. For acute exposures, the doses are usually 

averaged over a day or a single event. For nonchronic non-cancer effects, the time period used is 

the actual period of exposure (exposure duration). 

The objective in selecting the exposure averaging 

time is to express the dose in a way that can be 

combined with the dose-response relationship to 

calculate risk. 

The body weight to be used in Equation 1-2 

depends on the units of the exposure data presented 

in this handbook. For example, for food ingestion, the 

body weights of the surveyed populations were 

known in the USDA and NHANES surveys, and they 

were explicitly factored into the food intake data in 

order to calculate the intake as g/kg body weight-day. 

In this case, the body weight has already been 

included in the “intake rate” term in Equation 1-3, 

and the exposure assessor does not need to explicitly 

include body weight. 

The units of intake in this handbook for the 

incidental ingestion of soil and dust are not 

normalized to body weight. In this case, the exposure 

assessor will need to use (in Equation 1-2) the 

average weight of the exposed population during the 

time when the exposure actually occurs. When 

making body-weight assumptions, care must be taken 

that the values used for the population parameters in 

the dose-response analysis are consistent with the 

population parameters used in the exposure analysis. 

Intraspecies adjustments based on life stage can be 

made using a correction factor (CF) (U.S. EPA, 2011, 

2006b). Appendix 1A of this chapter discusses these 

adjustments in more detail. Some of the parameters 

(primarily concentrations) used in estimating 

exposure are exclusively site specific, and, therefore, 

default recommendations should not be used. It 

should be noted that body weight is correlated with 

food consumption rates, body surface area, and 

inhalation rates (for more information, see 

Chapters 6, 7, 9, 10, 11, 12, 13, and 14). 

The link between the intake rate value and the 

exposure duration value is a common source of 

confusion in defining exposure scenarios. It is 

important to define the duration estimate so that it is 

consistent with the intake rate: 

 The intake rate can be based on an 

individual event (e.g., serving size per 

event). The duration should be based on the 

number of events or, in this case, meals. 

 The intake rate also can be based on a 

long-term average, such as 10 g/day. In this 

case, the duration should be based on the 

total time interval over which the exposure 

occurs. 

The objective is to define the terms so that, when 

multiplied, they give the appropriate estimate of mass 

of agent contacted. This can be accomplished by 

basing the intake rate on either a long-term average 

(chronic exposure) or an event (acute exposure) 

basis, as long as the duration value is selected 

appropriately. 

Inhalation dosimetry is employed to derive the 

human equivalent exposure concentrations on which 

inhalation unit risks (IURs), and reference 

concentrations (RfCs), are based (U.S. EPA, 1994). 

U.S. EPA has traditionally approximated children’s 

respiratory exposure by using adult values, although 

a recent review (Ginsberg et al., 2005) concluded that 

there may be some cases where young children’s 

greater inhalation rate per body weight or pulmonary 

surface area as compared to adults can result in 

greater exposures than adults. The implications of 

this difference for inhalation dosimetry and children’s 

risk assessment were discussed at a peer involvement 

workshop hosted by the U.S. EPA in 2006 (Foos et 

al., 2008). 

Consideration of life stage-particular 

physiological characteristics in the dosimetry analysis 

may result in a refinement to the human equivalent 

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concentration (HEC) to ensure relevance in risk 

assessment across life stages, or might conceivably 

conclude with multiple HECs, and corresponding 

IUR values (e.g., separate for childhood and 

adulthood) (U.S. EPA, 2005e). The RfC 

methodology, which is described in Methods for 

Derivation of Inhalation Reference Concentrations 

and Applications of Inhalation Dosimetry (U.S. EPA, 

1994), allows the user to incorporate populationspecific assumptions into the models. Refer to U.S. 

EPA guidance (U.S. EPA, 1994) on how to make 

these adjustments. 

There are no specific exposure factor 

assumptions in the derivation of RfDs for susceptible 

populations. With regard to childhood exposures for a 

susceptible population, for example, the assessment 

of the potential for adverse health effects in infants 

and children is part of the overall hazard and doseresponse assessment for a chemical. Available data 

pertinent to children’s health risks are evaluated 

along with data on adults and the no-observedadverse-effect level (NOAEL) or benchmark dose 

(BMD) for the most sensitive critical effect(s), based 

on consideration of all health effects. By doing this, 

protection of the health of children will be considered 

along with that of other sensitive populations. In 

some cases, it is appropriate to evaluate the potential 

hazard to a susceptible population (e.g., children) 

separately from the assessment for the general 

population or other population groups. For more 

information regarding life stage-specific 

considerations for assessing children exposures, refer 

to the U.S. EPA report entitled Framework for 

Assessing Health Risk of Environmental Exposures to 

Children (U.S. EPA, 2006b). 

1.10.2.	 Use of Exposure Factors Data in 

Probabilistic Analyses 

Probabilistic risk assessment provides a range 

and likelihood estimate of risk rather than a single 

point estimate. It is a tool that can provide additional 

information to risk managers to improve decision 

making. Although this handbook is not intended to 

provide complete guidance on the use of Monte Carlo 

and other probabilistic analyses, some of the data in 

this handbook may be appropriate for use in 

probabilistic assessments. More detailed information 

on treating variability and uncertainty is discussed in 

Chapter 2 of this handbook. The use of Monte Carlo 

or other probabilistic analysis requires 

characterization of the variability of exposure factors 

and requires the selection of distributions or 

histograms for the input parameters of the dose 

equations presented in Section 1.10.1. The following 

suggestions are provided for consideration when 

using such techniques: 

•	 The exposure assessor should only consider 

using probabilistic analysis when there are 

credible distribution data (or ranges) for the 

factor under consideration. Even if these 

distributions are known, it may not be 

necessary to apply this technique. For 

example, if only average exposure values are 

needed, these can often be computed 

accurately by using average values for each of 

the input parameters unless a non-linear model 

is used. Generally, exposure assessments 

follow a tiered approach to ensure the efficient 

use of resources. They may start with very 

simple techniques and move to more 

sophisticated models. The level of assessment 

needed can be determined initially during the 

problem formulation. There is also a tradeoff 

between the level of sophistication and the 

need to make timely decisions (NRC, 2009). 

Probabilistic analysis may not be necessary 

when conducting assessments for the first tier, 

which is typically done for screening purposes, 

i.e., to determine if unimportant pathways can 

be eliminated. In this case, bounding estimates 

can be calculated using maximum or near 

maximum values for each of the input 

parameters. Alternatively, the assessor may use 

the maximum values for those parameters that 

have the greatest variance. 

•	 The selection of distributions can be highly 

site-specific and dependent on the purpose of 

the assessment. In some cases, the selection of 

distributions is driven by specific legislation. It 

will always involve some degree of judgment. 

Distributions derived from national data may 

not represent local conditions. Also, 

distributions may be representative of some 

age groups, but not representative when finer 

age categories are used. The assessor should 

evaluate the distributional data to ensure that it 

is representative of the population that needs 

to be characterized. In cases where 

site-specific data are available, the assessor 

may need to evaluate their quality and 

applicability. The assessor may decide to use 

distributional data drawn from the national or 

other surrogate population. In this case, it is 

important that the assessor address the extent 

to which local conditions may differ from the 

surrogate data. 

•	 It is also important to consider the 

independence/dependence of variables and 

data used in a simulation. For example, it may 

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be reasonable to assume that ingestion rate and 

contaminant concentration in foods are 

independent variables, but ingestion rate and 

body weight may or may not be independent. 

In addition to a qualitative statement of 

uncertainty, the representativeness assumption should 

be appropriately addressed as part of a sensitivity 

analysis. Distribution functions used in probabilistic 

analysis may be derived by fitting an appropriate 

function to empirical data. In doing this, it should be 

recognized that in the lower and upper tails of the 

distribution, the data are scarce, so that several 

functions, with radically different shapes in the 

extreme tails, may be consistent with the data. To 

avoid introducing errors into the analysis by the 

arbitrary choice of an inappropriate function, several 

techniques can be used. One technique is to avoid the 

problem by using the empirical data themselves 

rather than an analytic function. Another is to do 

separate analyses with several functions that have 

adequate fit but form upper and lower bounds to the 

empirical data. A third way is to use truncated 

analytical distributions. Judgment must be used in 

choosing the appropriate goodness-of-fit test. 

Information on the theoretical basis for fitting 

distributions can be found in a standard statistics text, 

[e.g., Gilbert (1987), among others]. Off-the-shelf 

computer software can be used to statistically 

determine the distributions that fit the data. Other 

software tools are available to identify outliers and 

for conducting Monte Carlo simulations. 

If only a range of values is known for 

an exposure factor, the assessor has several options. 

These options include: 

•	 keep that variable constant at its central value; 

•	 assume several values within the range of 

values for the exposure factor; 

•	 calculate a point estimate(s) instead of using 

probabilistic analysis; and 

•	 assume a distribution. (The rationale for the 

selection of a distribution should be discussed 

at length.) The effects of selecting a different, 

but equally probable distribution should be 

discussed. There are, however, cases where 

assuming a distribution may introduce 

considerable amount of uncertainty. These 

include: 

o	 data are missing or very limited for a key 

parameter; 

o	 data were collected over a short time 

period and may not represent long-term 

trends (the respondent’s usual behavior)— 

examples include food consumption 

surveys; activity pattern data; 

o	 data are not representative of the 

population of interest because sample size 

was small or the population studied was 

selected from a local area and was, 

therefore, not representative of the area of 

interest; for example, soil ingestion by 

children; and 

o	 ranges for a key variable are uncertain due 

to experimental error or other limitations 

in the study design or methodology; for 

example, soil ingestion by children. 

1.11.	 AGGREGATE AND CUMULATIVE 

EXPOSURES 

The U.S. EPA recognizes that individuals may be 

exposed to mixtures of chemicals both indoors and 

outdoors through more than one pathway. New 

directions in risk assessments in the U.S. EPA put 

more emphasis on total exposures via multiple 

pathways (U.S. EPA, 2007a, 2003c). Assessments 

that evaluate a single agent or stressor across multiple 

routes are not considered cumulative risk 

assessments. These are defined by the Food Quality 

Protection Act as aggregate risk assessments and can 

provide useful information to cumulative assessments 

(U.S. EPA, 2003c). Concepts and considerations to 

conduct aggregate risk assessments are provided in 

the U.S. EPA document entitled General Principles 

for Performing Aggregate Exposure and Risk 

Assessments (U.S. EPA, 2001a). 

Cumulative exposure is defined as the exposure 

to multiple agents or stressors via multiple routes. In 

the context of risk assessment, it means that risks 

from multiple routes and agents need to be combined, 

not necessarily added (U.S. EPA, 2003b). Analysis 

needs to be conducted on how the various agents and 

stressors interact (U.S. EPA, 2003b). 

In order to achieve effective risk assessment and 

risk management decisions, all media and routes of 

exposure should be assessed (NRC, 2009, 1991). 

Over the last several years, the U.S. EPA has 

developed a methodology for assessing risk from 

multiple chemicals (U.S. EPA, 2000c, 1986a). For 

more information, refer to the U.S. EPA’s Framework 

for Cumulative Risk Assessment (U.S. EPA, 2003b). 

The recent report by the NAS also recommends the 

development of approaches to incorporate the 

interactions between chemical and non-chemical 

stressors (NRC, 2009). 

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Chapter 1—Introduction 

1.12.	 ORGANIZATION OF THE 

HANDBOOK 

All the chapters of this handbook have been 

organized in a similar fashion. An introduction is 

provided that discusses some general background 

information about the exposure factor. This 

discussion is followed by the recommendations for 

that exposure factor including summary tables of the 

recommendations and confidence ratings. The goal of 

the summary tables is to present the data in a 

simplified fashion by providing mean and upper 

percentile estimates and referring the reader to more 

detailed tables with more percentile estimates or 

other demographic information (e.g., sex) at the end 

of the chapter. Because of the large number of tables 

in this handbook, tables that include information 

other than the recommendations and confidence 

ratings are presented at the end of each chapter, 

before the appendices, if any. Following the 

recommendations, the key studies are summarized. 

Relevant data on the exposure factor are also 

provided. These data are presented to provide the 

reader with added perspective on the current state-ofknowledge pertaining to the exposure factor of 

interest. Summaries of the key and relevant studies 

include discussions about their strengths and 

limitations. Note that because the studies often were 

performed for reasons unrelated to developing the 

factor of interest, the attributes that were 

characterized as limitations might not be limitations 

when viewed in the context of the study’s original 

purpose. 

The handbook is organized as follows: 

Chapter 1	 Introduction—includes discussions 

about general concepts in exposure 

assessments as well as the purpose, 

scope, and contents of the handbook. 

Chapter 2	 Variability and Uncertainty— 

provides a brief overview of the 

concepts of variability and 

uncertainty and directs the reader to 

other references for more in-depth 

information. 

Chapter 3	 Ingestion of Water and Other Select 

Liquids—provides information on 

drinking water consumption and data 

on intake of select liquids for the 

general population and various 

demographic groups; also provides 

data on intake of water while 

swimming. 

Chapter 4
 Non-dietary Ingestion—presents data 

on mouthing behavior necessary to 

estimate non-dietary exposures. 

Chapter 5
 Soil and Dust Ingestion—provides 

information on soil and dust 

ingestion for both adults and 

children. 

Chapter 6
 Inhalation Rates—presents data on 

average daily inhalation rates and 

activity-specific inhalation rates for 

the general population and various 

demographic groups. 

Chapter 7
 Dermal Exposure Factors—presents 

information on body surface area and 

solids adherence to the skin, as well 

as data on other 

non-chemical-specific factors that 

may affect dermal exposure. 

Chapter 8
 Body Weight—provides data on body 

weight for the general population and 

various demographic groups. 

Chapter 9
 Intake of Fruits and Vegetables— 

provides information on total fruit 

and vegetable consumption as well as 

intake of individual fruits and 

vegetables for the general population 

and various demographic groups. 

Chapter 10
 Intake of Fish and Shellfish— 

provides information on fish 

consumption for the general 

population, recreational freshwater 

and marine populations, and various 

demographic groups. 

Chapter 11
 Intake of Meats, Dairy Products, and 

Fats—provides information on meat, 

dairy products, and fats consumption 

for the general population and 

various demographic groups. 

Chapter 12
 Intake of Grain Products—provides 

information on grain consumption for 

the general population and various 

demographic groups. 

Chapter 13
 Intake of Home-produced Foods— 

provides information on 

home-produced food consumption 

for the general population and 

various demographic groups. 

Chapter 14
 Total Food Intake—provides 

information on total food 

consumption for the general 

population and various demographic 

groups; information on the 

composition of the diet is also 

provided. 

Exposure Factors Handbook Page
 

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Exposure Factors Handbook 

Chapter 1—Introduction 

Chapter 15 Human Milk Intake—presents data 

on human milk consumption for 

infants at various life stages. 

Chapter 16	 Activity Factors—presents data on 

activity patterns for the general 

population and various demographic 

groups. 

Chapter 17	 Consumer Products—provides 

information on frequency, duration, 

and amounts of consumer products 

used. 

Chapter 18	 Life Expectancy—presents data on 

the projected length of a lifetime, 

based on age and demographic 

factors. 

Chapter 19	 Building Characteristics—presents 

information on both residential and 

commercial building characteristics 

necessary to assess exposure to 

indoor air pollutants. 

Figure 1-3 provides a schematic diagram that 

shows the linkages of a select number of exposure 

pathways with the exposure factors presented in this 

handbook and the corresponding exposure routes. 

Figure 1-4 provides a roadmap to assist users of this 

handbook in locating recommended values and 

confidence ratings for the various exposure factors 

presented in these chapters. 

1.13.	 REFERENCES FOR CHAPTER 1 

American Academy of Pediatrics. (1997). Child 

health issues for the second session of the 

106th Congress. Washington, DC: 

Department of Federal Affairs. 

Breysse, PN; Buckley, TJ; Williams, D; Beck, CM; 

Jo, SJ; Merriman, B; Kanchanaraksa, S; 

Swartz, LJ; Callahan, KA; Butz, AM; Rand, 

CS; Diette, GB; Krishnan, JA; Moseley, 

AM; Curtin-Brosnan, J; Durkin, NB; 

Eggleston, PA. (2005). Indoor exposures to 

air pollutants and allergens in the homes of 

asthmatic children in inner-city Baltimore. 

Environ Res 98: 167-176. 

http://dx.doi.org/10.1016/j.envres.2004.07.0 

18. 

Brown, RC; Barone, S, Jr; Kimmel, CA. (2008). 

Children's health risk assessment: 

Incorporating a lifestage approach into the 

risk assessment process. Birth Defects Res B 

Dev Reprod Toxicol 83: 511-521. 

http://dx.doi.org/10.1002/bdrb.20172. 

Clewell, HJ; Gentry, PR; Covington, TR; 

Sarangapani, R; Teeguarden, JG. (2004). 

Evaluation of the potential impact of ageand gender-specific pharmacokinetic 

differences on tissue dosimetry. Toxicol Sci 

79: 381-393. 

http://dx.doi.org/10.1093/toxsci/kfh109. 

Curwin, BD; Hein, MJ; Sanderson, WT; Striley, C; 

Heederik, D; Kromhout, H; Reynolds, SJ; 

Alavanja, MC. (2007). Pesticide dose 

estimates for children of Iowa farmers and 

non-farmers. Environ Res 105: 307-315. 

http://dx.doi.org/10.1016/j.envres.2007.06.0 

01. 

Eskenazi, B; Bradman, A; Castorina, R. (1999). 

Exposures of children to organophosphate 

pesticides and their potential adverse health 

effects. Environ Health Perspect 3: 409-419. 

Foos, B; Marty, M; Schwartz, J; Bennett, W; Moya, 

J; Jarabek, AM; Salmon, AG. (2008). 

Focusing on children's inhalation dosimetry 

and health effects for risk assessment: An 

introduction. J Toxicol Environ Health A 71: 

149-165. 

http://dx.doi.org/10.1080/152873907015978 

71. 

Garry, VF. (2004). Pesticides and children. Toxicol 

Appl Pharmacol 198: 152-163. 

http://dx.doi.org/10.1016/j.taap.2003.11.027. 

Georgopoulos, PG. (2008). A multiscale approach for 

assessing the interactions of environmental 

and biological systems in a holistic health 

risk assessment framework. Water, Air, and 

Soil Pollution: Focus 8: 3-21. 

http://dx.doi.org/10.1007/s11267-007-9137­

7. 

Georgopoulos,	 PG; Lioy, PJ. (2006). From a 

theoretical framework of human exposure 

and dose assessment to computational 

system implementation: The Modeling 

ENvironment for TOtal Risk Studies 

(MENTOR). J Toxicol Environ Health B 

Crit Rev 9: 457-483. 

http://dx.doi.org/10.1080/109374006007559 

29. 

Gilbert, RO. (1987). Statistical methods for 

environmental pollution monitoring. New 

York, NY: Van Nostrand Reinhold. 

Ginsberg, G; Hattis, D; Miller, R; Sonawane, B. 

(2004). Pediatric pharmacokinetic data: 

Implications for environmental risk 

assessment for children. Pediatrics 113: 973­

983. 

Ginsberg, G; Hattis, D; Sonawane, B; Russ, A; 

Banati, P; Kozlak, M; Smolenski, S; Goble, 

R. (2002). Evaluation of child/adult 

Page Exposure Factors Handbook 

1-20 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

pharmacokinetic differences from a database 

derived from the therapeutic drug literature. 

Toxicol Sci 66: 185-200. 

Ginsberg, GL; Foos, BP; Firestone, MP. (2005). 

Review and analysis of inhalation dosimetry 

methods for application to children's risk 

assessment [Review]. J Toxicol Environ 

Health A 68: 573-615. 

http://dx.doi.org/10.1080/152873905909217 

93. 

Gulson, BL; Pounds, JG; Mushak, P; Thomas, BJ; 

Gray, B; Korsch, MJ. (1999). Estimation of 

cumulative lead releases (lead flux) from the 

maternal skeleton during pregnancy and 

lactation. J Lab Clin Med 134: 631-640. 

Gurunathan, S; Robson, M; Freeman, N; Buckley, B; 

Roy, A; Meyer, R; Bukowski, J; Lioy, PJ. 

(1998). Accumulation of chlorpyrifos on 

residential surfaces and toys accessible to 

children. Environ Health Perspect 106: 9-16. 

Landrigan, PJ; Sonawane, B; Butler, RN; Trasande, 

L; Callan, R; Droller, D. (2005). Early 

environmental origins of neurodegenerative 

disease in later life. Environ Health Perspect 

113: 1230-1233. 

http://dx.doi.org/10.1289/ehp.7571. 

Lewis, RG; Fortune, CR; Willis, RD; Camann, DE; 

Antley, JT. (1999). Distribution of pesticides 

and polycyclic aromatic hydrocarbons in 

house dust as a function of particle size. 

Environ Health Perspect 107: 721-726. 

Lioy, P; Leaderer, B; Graham, J; Lebret, E; Sheldon, 

L; Needham, L; Pellizzari, E; Lebowitz, M. 

(2005). The Major Themes from the Plenary 

Panel Session of the International Society of 

Exposure Analysis--2004 Annual Meeting 

on: The Application of Exposure 

Assessment to Environmental Health 

Science and Public Policy--What has been 

Accomplished and What Needs to Happen 

before Our 25th Anniversary in 2014. J 

Expo Anal Environ Epidemiol 15: 121. 

http://dx.doi.org/10.1038/sj.jea.7500417. 

Lipscomb, JC. (2006). Use of physiologically based 

pharmacokinetic models to quantify the 

impact of human age and interindividual 

differences in physiology and biochemistry 

pertinent to risk (Final Report). 

(EPA/600/R06/014A). Cincinnati, OH: U.S. 

Environmental Protection Agency. 

Makri, A; Goveia, M; Balbus, J; Parkin, R. (2004). 

Children's susceptibility to chemicals: A 

review by developmental stage [Review]. J 

Toxicol Environ Health B Crit Rev 7: 417­

435. 

http://dx.doi.org/10.1080/109374004905124 

65. 

Moya, J; Bearer, CF; Etzel, RA. (2004). Children's 

behavior and physiology and how it affects 

exposure to environmental contaminants. 

Pediatrics 113: 996-1006. 

Myers, GJ; Davidson, PW. (2000). Does 

methylmercury have a role in causing 

developmental disabilities in children? 

Environ Health Perspect 108: 413-420. 

Nishioka, MG; Burkholder, HM; Brinkman, MC; 

Lewis, RG. (1999). Distribution of 2,4­

dichlorophenoxyacetic acid in floor dust 

throughout homes following homeowner 

and commercial lawn applications: 

Quantitative effects of children, pets, and 

shoes. Environ Sci Technol 33: 1359-1365. 

NRC (National Research Council). (1983). Risk 

assessment in the federal government: 

Managing the process. Washington, DC: 

National Academies Press. 

http://www.nap.edu/openbook.php?record_i 

d=366&page=R1. 

NRC (National Research Council). (1991). Human 

exposure assessment for airborne pollutants: 

advances and opportunities. Washington, 

DC: National Academy of Sciences. 

http://books.nap.edu/openbook.php?record_i 

d=1544. 

NRC (National Research Council). (2006). Human 

biomonitoring for environmental chemicals. 

Washington, D.C.: The National Academies 

Press. 

http://www.nap.edu/catalog.php?record_id= 

11700. 

NRC (National Research Council). (2009). Science 

and decisions: Advancing risk assessment. 

Washington, DC: National Academies Press. 

http://www.nap.edu/catalog/12209.html. 

Ott, WR. (2007). Exposure analysis: A 

receptororiented science. In W Ott; AC 

Steinemann; LA Wallace (Eds.), Exposure 

analysis (pp. 3-32). Boca Raton, FL: CRC 

Press. 

Price, PS; Chaisson, CF; Koontz, M; Wilkes, C; 

Ryan, B; Macintosh, D; Georgopoulos, P. 

(2003a). Construction of a comprehensive 

chemical exposure framework using person 

oriented modeling. Annandale, VA: The 

LifeLine Group. 

http://www.thelifelinegroup.org/lifeline/doc 

uments/comprehensive_chemical_exposure_ 

framework.pdf. 

Price, PS; Conolly, RB; Chaisson, CF; Gross, EA; 

Young, JS; Mathis, ET; Tedder, DR. 

Exposure Factors Handbook Page
 

September 2011 1-21 
 

Exposure Factors Handbook 

Chapter 1—Introduction 

(2003b). Modeling interindividual variation 

in physiological factors used in PBPK 

models of humans. Crit Rev Toxicol 33: 

469-503. 

http://dx.doi.org/10.1080/104084403902423 

24. 

Selevan, SG; Kimmel, CA; Mendola, P. (2000). 

Identifying critical windows of exposure for 

children's health. Environ Health Perspect 

1083: 451-455. 

Sheldon, LS; Cohen Hubal, EA. (2009). Exposure as 

part of a systems approach for assessing 

risk. Environ Health Perspect 117: 119­

1194. 

http://dx.doi.org/10.1289/ehp.0800407. 

Thompson, CM; Johns, DO; Sonawane, B; Barton, 

HA; Hattis, D; Tardiff, R; Krishnan, K. 

(2009). Database for physiologically based 

pharmacokinetic (PBPK) modeling:

physiological data for healthy and healthimpaired elderly. J Toxicol Environ Health B 

Crit Rev 12: 1-24. 

http://dx.doi.org/10.1080/109374008025450 

60. 

U.S. EPA (U.S. Environmental Protection Agency). 

Methods for assessing exposure to chemical 

substances, volumes 113 (1983-1989). 

(EPA-560/5-85-001 to EPA-560/5-85-009, 

EPA-560/5-85-014 to EPA-560/5-85-017). 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1985). Development of statistical

distributions or ranges of standard factors 

used in exposure assessments.

(EPA600885010). 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB85242667. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1986a). Guidelines for the health risk 

assessment of chemical mixtures [EPA 

Report] (pp. 34014-34025). (EPA/630/R98/002). Washington, DC.

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=22567. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1986b). Standard scenarios for estimating 

exposure to chemical substances during use 

of consumer products: Volume I. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1986c). Standard scenarios for estimating 

exposure to chemical substances during use 

of consumer products: Volume II. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1987a). The risk assessment guidelines of 

1986 [EPA Report]. (EPA/600/8-87/045). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Health and 

Environmental Assessment. 

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=30001GOF.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1987b). Selection criteria for mathematical 

models used in exposure assessments: 

Surface water models. (EPA/600/8-87/042). 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1988). Selection criteria for mathematical 

models used in exposure assessments: 

Ground-water models. (EPA600888075). 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB88248752. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1989a). Exposure factors handbook. 

(EPA/600/8-89/043). Washington, DC: U.S. 

Environmental Protection Agency, Office of 

Health and Environmental Assessment. 

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=30001I91.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1989b). Risk assessment guidance for 

superfund: Volume 1: Human health 

evaluation manual (part A): Interim final 

[EPA Report]. (EPA/540/1-89/002). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Emergency and 

Remedial Response.

http://www.epa.gov/oswer/riskassessment/ra 

gsa/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1990). Methodology for assessing health 

risks associated with indirect exposure to 

combustor emissions. (EPA 600/6-90/003). 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1991a). Risk assessment guidance for 

superfund: Volume I - human health 

evaluation manual (part B, development of 

risk-based preliminary remediation goals): 

Interim [EPA Report]. (EPA/540/R-92/003). 

Washington, DC.

http://www.epa.gov/oswer/riskassessment/ra 

gsb/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1991b). Risk assessment guidance for 

superfund: Volume I - human health 

evaluation manual (part C, risk evaluation 

and remedial alternatives): Interim, 

appendix C: Short-term toxicity values (pp. 

49-56). (OSWER Dir 9285.7-01CFS). 

Washington, D.C.

Page Exposure Factors Handbook 

1-22 September 2011 
Exposure Factors Handbook 

Chapter 1—Introduction 

http://www.epa.gov/oswer/riskassessment/ra 

gsc/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992a). Dermal exposure assessment: 

Principles and applications (interim report). 

(EPA/600/8-91/011B). Washington, DC: 

U.S. Environmental Protection Agency, 

Office of Health and Environmental 

Assessment, Exposure Assessment Group. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=12188. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992b). EPA's approach for assessing the 

risks associated with chronic exposure to 

carcinogens: Background document 2. 

http://www.epa.gov/iris/carcino.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992c). Guidelines for exposure

assessment. (EPA/600/Z-92/001). 

Washington, DC: U.S. Environmental 

Protection Agency, Risk Assessment Forum. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=15263. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1993). Reference Dose (RfD): Description 

and Use in Health Risk Assessments 

Background Document 1A, March 15, 1993. 

Integrated Risk Information System. 

http://www.epa.gov/IRIS/rfd.htmgoo. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1994). Methods for derivation of inhalation 

reference concentrations and application of 

inhalation dosimetry. (EPA/600/8-90/066F). 

Research Triangle Park, NC: U.S. 

Environmental Protection Agency, Office of 

Research and Development, Office of 

Health and Environmental Assessment, 

Environmental Criteria and Assessment 

Office. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=71993. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1996a). Series 875 occupational and 

residential exposure test guidelines: Final 

guidelines. (EPA/712-C96/261). 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1996b). Soil screening guidance: Technical 

background document. (EPA/540/R95/128). 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1997a). Exposure factors handbook (final 

report). (EPA/600/P-95/002Fa-c). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Research and 

Development, National Center for

Environmental Assessment. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=12464. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1997b). Guiding principles for Monte Carlo 

analysis. (EPA/630/R-97/001). Washington, 

DC. 

http://www.epa.gov/raf/publications/guiding 

-monte-carlo-analysis.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1997c). Policy for use of probabilistic

analysis in risk assessment. Washington,

DC. 

http://www.epa.gov/OSA/spc/pdfs/probpol.p 

df. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1998). Series 875 - Occupational and

residential exposure test guidelines: Group 

B - Postapplication exposure monitoring test 

guidelines. Washington, DC: U.S.

Environmentla Protection Agency.

http://www.epa.gov/scipoly/sap/meetings/19 

98/march/front.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1999). Sociodemographic data used for

identifying potentially highly exposed

populations. (EPA/600/R-99/060). 

Washington, DC.

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=22562. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000a). Options for development of

parametric probability distributions for

exposure factors. (EPA/600/R-00/058). 

Washington, DC: U.S. Enivonmental

Protection Agency. 

http://www.epa.gov/ncea/pdfs/paramprob4ef 

/chap1.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000b). Summary report of the technical 

workshop on issues associated with

considering developmental changes in

behavior and anatomy when assessing

exposure to children. (EPA/630/R-00/005). 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000c). Supplementary guidance for

conducting health risk assessment of

chemical mixtures [EPA Report].

(EPA/630/R-00/002). 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=20533. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2001a). General principles for performing 

Exposure Factors Handbook Page
 

September 2011 1-23 
 

Exposure Factors Handbook 

Chapter 1—Introduction 

aggregate exposure and risk assessments. 

Washington, DC.

http://www.epa.gov/pesticides/trac/science/a 

ggregate.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2001b). Risk Assessment Guidance for 

Superfund (RAGS), Vol. I - Human health 

evaluation manual, Part D: Standardized 

planning, reporting and review of Superfund 

risk assessments. (OSWER9285747). 

Washington, DC.

http://www.epa.gov/oswer/riskassessment/ra 

gsd/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2001c). Risk assessment guidance for 

superfund: Volume III - part A, process for 

conducting probabilistic risk assessment. 

(EPA 540-R-02-002). Washington, DC: U.S. 

Environmental Protection Agency, Office of 

Solid Waste and Emergency Response. 

http://www.epa.gov/oswer/riskassessment/ra 

gs3adt/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2002). Overview of the EPA quality system 

for environmental data and technology. 

(EPA/240/R-02/003). 

http://www.epa.gov/QUALITY/qsdocs/overview-final.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2003a). Exposure and human health 

reassessment of 2,3,7,8 tetrachlorodibenzo-p 

dioxin (TCDD) and related compounds 

[NAS review draft]. (EPA/600/P-00/001). 

Washington, DC: U.S. Environmental 

Protection Agency, National Center for 

Environmental Assessment. 

http://www.epa.gov/nceawww1/pdfs/dioxin/ 

nas-review/. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2003b). Framework for cumulative risk 

assessment. (EPA/630/P-02/001F). 

Washington, DC: U.S. Environmental 

Protection Agency, Risk Assessment Forum. 

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=30004TJH.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2003c). Human health research strategy. 

(EPA/600/R-02/050). Washington, DC. 

http://www.epa.gov/ORD/htm/researchstrate 

gies.htm#rs01. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2003d). A summary of general assessment 

factors for evaluating the quality of 

scientific and technical information. 

Washington, DC.

http://www.epa.gov/spc/assess.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2004a). Example exposure scenarios. (EPA 

600/R03/036). Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=85843. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2004b). Risk Assessment Guidance for 

Superfund (RAGS), Volume I: Human 

health evaluation manual, (part E: 

Supplemental guidance for dermal risk 

assessment): Final. (EPA/540/R/99/005). 

Washington, DC.

http://www.epa.gov/oswer/riskassessment/ra 

gse/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005a). Aging and toxic response: Issues 

relevant to risk assessment. 

(EPA/600/P03/004A). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005b). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005c). Guidelines for carcinogen risk 

assessment. (EPA/630/P-03/001F). 

Washington, DC.

http://www.epa.gov/cancerguidelines/. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005d). Human health risk assessment 

protocol for hazardous waste combustion 

facilities. (EPA530-R-05-006). Washington, 

DC: US Environmental Protection Agency, 

Office of Solid Waste and Emergency 

Response (OSWER).

http://www.epa.gov/earth1r6/6pd/rcra_c/prot 

ocol/protocol.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005e). Supplemental guidance for 

assessing susceptibility from early-life 

exposure to carcinogens. (EPA/630/R03/003F). Washington, DC: U.S. 

Environmental Protection Agency, Risk 

Assessment Forum.

http://www.epa.gov/cancerguidelines/guideli 

nes-carcinogen-supplement.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2006a). Approaches for the application of 

physiologically based pharmacokinetic 

(PBPK) models and supporting data in risk 

Page Exposure Factors Handbook 

1-24 September 2011 
Exposure Factors Handbook 

Chapter 1—Introduction 

assessment (Final Report). (EPA/600/R05/043F). Washington, DC: U.S. 

Environmental Protection Agency, Office of 

Research and Development. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2006b). A framework for assessing health 

risk of environmental exposures to children. 

(EPA/600/R-05/093F). Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=158363. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2006c). Guidance on systematic planning 

using the data quality objectives process: 

EPA QA/G-4 [EPA Report]. (EPA/240/B06/001). Washington, DC.

http://www.epa.gov/QUALITY/qs-docs/g4­

final.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2007a). Concepts, methods, and data 

sources for cumulative health risk 

assessment of multiple chemicals, 

exposures, and effects: A resource document 

[EPA Report]. (EPA/600/R-06/013F). 

Cincinnati, OH.

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=190187. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2007b). Dermal exposure assessment: A 

summary of EPA approaches [EPA Report]. 

(EPA/600/R-07/040F). Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=183584. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2007c). Summary report of a Peer 

Involvement Workshop on the Development 

of an Exposure Factors Handbook for the 

Aging [EPA Report]. (EPA/600/R-07/061). 

Washington, DC.

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=171923. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2008a). Child-specific exposure factors 

handbook [EPA Report]. (EPA/600/R06/096F). Washington, DC.

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=199243. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2008b). Physiological parameters database 

for older adults (Beta 1.1) [Database]. 

Washington, DC. Retrieved from 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=201924 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009a). Draft technical guidelines: 

Standard operating procedures for 

residential pesticide exposure assessment: 

Submitted to the FIFRA Scientific Advisory 

Panel for review and comment, October 6-9, 

2009. http://www.biospotvictims.org/EPAHQ-OPP-2009-0516-0002.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009b). Risk assessment guidance for 

superfund volume I: Human health 

evaluation manual (Part F, supplemental 

guidance for inhalation risk assessment): 

Final. (EPA/540/-R-070/002). Washington, 

DC: U.S. Environmental Protection Agency, 

Office of Superfund Remediation and 

Technology Innovation.

http://www.epa.gov/oswer/riskassessment/ra 

gsf/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2010). SHEDS-multimedia: Details of 

SHEDS-multimedia version 3: ORD/NERLs 

model to estimate aggregate and cumulative 

exposures to chemicals. Research Triangle 

Park, NC.

http://www.epa.gov/heasd/products/sheds_m 

ultimedia/sheds_mm.html. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2011). Recommended use of body weight 

3/4 as the default method in derivation of the 

oral reference dose. (EPA/100/R11/0001). 

Washington, DC.

http://www.epa.gov/raf/publications/interspe 

cies-extrapolation.htm. 

WHO (World Health Organization). (2001). Glossary 

of exposure assessment-related terms: A 

compilation. Geneva, Switzerland. 

http://www.who.int/ipcs/publications/metho 

ds/harmonization/en/compilation_nov2001.p 

df. 

WHO	 (World Health Organization). (2005). 

Principles of characterizing and applying 

human exposure models. Geneva. 

http://whqlibdoc.who.int/publications/2005/ 

9241563117_eng.pdf. 

WHO	 (World Health Organization). (2006). 

Principles for evaluating health risks in 

children associated with exposure to 

chemicals [WHO EHC]. (Environmental 

Health Criteria 237). Geneva, Switzerland. 

http://www.who.int/ipcs/publications/ehc/eh 

c237.pdf. 

Zartarian, VG; Ott, WR; Duan, N. (2007). Basic 

concepts and definitions of exposure and 

dose. In WR Ott; AC Steinemann; LA 

Wallace (Eds.), Exposure analysis (pp. 33­

63). Boca Raton, FL: CRC Press. 

. 

Exposure Factors Handbook Page
 

September 2011 1-25 
 

Exposure Factors Handbook 

Chapter 1—Introduction 

Table 1-1. Availability of Various Exposure Metrics in Exposure Factors Data 

Exposure Factors Chapter Average Median Upper Percentile Multiple Percentiles 

Ingestion of water and other select liquids (Chapter 3) 3    

Non-dietary ingestion 4    

Soil and dust ingestion 5  a 

Inhalation rate 6    

Surface area 

Soil adherence 

7 

7 





  

Body weight 8    

Intake of fruits and vegetables 9    

Intake of fish and shellfish 10    

Intake of meats, dairy products, and fats 11    

Intake of grain products 12    

Intake of home produced foods 13    

Total food intake 14    

Human milk intake 15  

Total time indoors 16 

Total time outdoors 16 

Time showering 16    

Time bathing 16    

Time swimming 16    

Time playing on sand/gravel 16    

Time playing on grass 16    

Time playing on dirt 16    

Occupational mobility 16 

Population mobility 16    

Life expectancy 18 

Volume of residence or building 

Air exchange rates 

19 

19 





b 

b 

 = Data available. a Including soil pica and geophagy. b Lower percentile. 

Page Exposure Factors Handbook 

1-26 September 2011 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

Table 1-2. Criteria Used to Rate Confidence in Recommended Values 

General Assessment Factors Elements Increasing Confidence Elements Decreasing Confidence 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The studies used the best available 

methodology and capture the 

measurement of interest. 

As the sample size relative to that of 

the target population increases, there 

is greater assurance that the results 

are reflective of the target population. 

The response rate is greater than 80% 

for in-person interviews and 

telephone surveys, or greater than 

70% for mail surveys. 

The studies analyzed primary data. 

The study design minimizes 

measurement errors. 

There are serious limitations with the 

approach used; study design does not 

accurately capture the measurement of 

interest. 

Sample size too small to represent the 

population of interest. 

The response rate is less than 40%. 

The studies are based on secondary 

sources. 

Uncertainties with the data exist due to 

measurement error. 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The studies focused on the exposure 

factor of interest. 

The studies focused on the U.S. 

population. 

The studies represent current 

exposure conditions. 

The data collection period is 

sufficient to estimate long-term 

behaviors. 

The purpose of the studies was to 

characterize a related factor. 

Studies are not representative of the U.S. 

population. 

Studies may not be representative of 

current exposure conditions. 

Shorter data collection periods may not 

represent long-term exposures. 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The study data are publicly available. 

The results can be reproduced, or 

methodology can be followed and 

evaluated. 

The studies applied and documented 

quality assurance/quality control 

measures. 

Access to the primary data set was limited. 

The results cannot be reproduced, the 

methodology is hard to follow, and the 

author(s) cannot be located. 

Information on quality assurance/control 

was limited or absent. 

Exposure Factors Handbook Page
 

September 2011 1-27 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

Table 1-2. Criteria Used to Rate Confidence in Recommended Values (continued) 

General Assessment Factors Increasing Confidence Decreasing Confidence 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

The studies characterize variability in 

the population studied. 

The uncertainties are minimal and 

can be identified. Potential bias in the 

studies are stated or can be 

determined from the study design. 

The characterization of variability is 

limited. 

Estimates are highly uncertain and cannot 

be characterized. The study design 

introduces biases in the results. 

Evaluation and Review 

Peer Review 

Number and Agreement of 

Studies 

The studies received a high level of 

peer review (e.g., they are published 

in peer-reviewed journals). 

The number of studies is greater than 

three. The results of studies from 

different researchers are in 

agreement. 

The studies received limited peer review. 

The number of studies is one. The results 

of studies from different researchers are in 

disagreement. 

Table 1-3. Age-Dependent Potency Adjustment Factor by Age Group for Mutagenic Carcinogens 

Exposure Age Groupa Exposure Duration (year) Age-Dependent Potency Adjustment Factor 

Birth to <1 month 0.083 10× 

1 <3 months 0.167 10× 

3 <6 months 0.25 10× 

6 <12 months 0.5 10× 

1 to <2 years 1 10× 

2 to <3 years 1 3× 

3 to <6 years 3 3× 

6 to <11 years 5 3× 

11 to <16 years 5 3× 

16 to <21 years 5 1× 

≥21 years (21 to <70 years) 49 1× a U.S. EPA’s recommended childhood age groups (excluding ages >21 years). 

Page Exposure Factors Handbook 

1-28 September 2011 
SOURCE/STRESSOR 

FORMATION

SOURCE/STRESSOR 

FORMATION

TRANSPORT/ 

TRANSFORMATION

EXPOSURE

• Individual 

• Community 

• P ation

• Individual 

• Community 

• Population

DOSE DOSE

EARLY BIOLOGICAL 

EFFECT

EARLY BIOLOGICAL 

EFFECT

ALTERED STRUCTURE/ 

FUNCTION

ALTERED STRUCTURE/ 

FUNCTION

DISEASE DISEASE

ENVIRONMENTAL 

CHARACTERIZATION

ENVIRONMENTAL 

CHARACTERIZATION

 

 

 

 

 

 

 

 

 

 

 

SOURCE/STRESSOR 

FORMATION

TRANSPORT/ 

TRANSFORMATION

• Individual 

• Community 

• P ation

DOSE

EARLY BIOLOGICAL 

EFFECT

ALTERED STRUCTURE/ 

FUNCTION

DISEASE

ENVIRONMENTAL 

CHARACTERIZATION

 

 

 

 

 

 

 

 

 

 

 

Cancer 

Asthma

Physical Infertility etc. Microbial
 

Magnitude 

Duration 

Timing
 

ENVIRONMENTAL 

CHARACTERIZATION 

Edema 

Dispersion Arrhythmia 

Kinetics Enzymuria 

Thermodynamics Necrosis etc. 

Distributions 

Meteorology
 

Molecular
 

Biochemical
 

Cellular
 

Air Organ 

Water Organism 

Diet Absorbed Soil and Dust EXPOSURE Target 

Internal 

Pathway Biologically Effective 

Route 

Duration 

Frequency 

Magnitude 

Statistical Profile 

Reference Population 

Susceptible Individual 

Susceptible Populations 

Population Distributions 

Chemical

SOURCE/STRESSOR 

FORMATION 

Chemical 

TRANSPORT/
 

TRANSFORMATION
 

opul

• Individual 

• Community 

• Population 

DOSE 

EARLY BIOLOGICAL 

EFFECT 

ALTERED STRUCTURE/ 

FUNCTION 

DISEASE 

Activity 

Pattern

EXPOSURE

TRANSPORT/ 

TRANSFORMATION

Activity 

Pattern

Activity 

Pattern

EXPOSURE

Activity 

Pattern 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

Figure 1-2. Exposure-Dose-Effect Continuum. 

Source: Redrawn from U.S. EPA (2003c); WHO (2006); Ott (2007). 

The exposure-dose-effect continuum depicts the trajectory of an agent from its source to an effect. The 

agent can be transformed and transported through the environment via air, water, soil, dust, and diet. 

Individuals can become in contact with the agent through inhalation, ingestion, or skin/eye contact. The 

individual’s physiology, behavior, and activity patterns as well as the concentration of the agent will 

determine the magnitude, frequency, and duration of the exposure. The exposure becomes an absorbed dose 

once the agent crosses the absorption barrier (i.e., skin, lungs, eyes, gastrointestinal tract, placenta). 

Interactions of the chemical or its metabolites with a target tissue may lead to an adverse health outcome. 

The text under the boxes indicates the specific information that may be needed to characterize each step in 

the exposure-dose-effect continuum. 

Exposure Factors Handbook Page
 

September 2011 1-29 
Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 1-30 September 2011

Figure 1-3. Schematic Diagram of Exposure Pathways, Factors, and Routes. 
EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER 

RECOMMENDATIONS 

TABLE/RATINGS 

TABLE 

Ingestion 

Inhalation 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes)
 

Consumer Product Use
 

(All Routes) 

Building Characteristics 

Drinking Water Intake

Mouthing

Soil/Dust Intake

Fruit and Vegetable Intake

Fish and Shellfish Intake

Meat and Dairy Intake

Grain Intake

Home Produced Food Intake

Total Food Intake

Human Milk Intake

Time Swimming

Long Term

Inhalation Rate

Short Term

Body Surface Area

Adherence of Solids

Body Weight

Lifetime 

Activity Patterns

Occupational Mobility

Population Mobility

Frequency of Use

Amount Used

Duration

Air Exchange Rates

Building Volume

Adults

Children

Pregnant Women

Frequency

Duration

Adults

Children

Adults

Children

General Population

Marine Recreational

Freshwater Recreational

Native American Populations

Adults

Children

Adults

Children

Adults

Children

Adults

Children

Exclusively Breastfed Infants

Adults

Children

Adults

Children

Adults

Children

Adults

Children

Adults

Children

Adults

Children

Males

Females

Adults

Children

Adults

Adults

Children

General Population

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

3-1 / 3-2 

3 

3-1 / 3-4

3-1 / 3-6

4 4-1 / 4-2 

5 5-1 / 5-2 

9 9-1 / 9-2 

10-1 / 10-2

10-3 / 10-4 10 10-5

10-6

11 11-1 / 11-2 

12 12-1 / 12-2 

13 13-1 / 13-2 

14 14-1 / 14-2 

15 15-1 / 15-2

16 16-1 / 16-2 

6-1 / 16-3 

6 

6-2 / 6-3 

7-1, 7-2 / 7-3 

7 

7-4 / 7-5 

8 8-1 / 8-2 

18 18-1 / 18-2 

16-1 / 16-2 

16 16-3 / 16-4

16-5 / 16-6 

17 No Recommendations

19-1 / 19-2

19-3 / 19-4 19 19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing
 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake
 Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes)
 

Consumer Product Use
 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4

Figure 1-4. Road map to Exposure Factor Recommendations. 
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults 

Children 3 3-1 / 3-2 

Mouthing 

Pregnant Women 

Frequency

Duration 4 

3-3 / 3-4 

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency 

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings 

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
 
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults 

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults 

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
A

dults

3

3-1 / 3-2

Children3-1 / 3-4

Pregnant Women3-1 / 3-6

Frequency

44-1 / 4-2

Duration

Adults

55-1 / 5-2 Children Adults 9 9-1 / 9-2 Children Adults 11 11-1 / 11-2 Children Adults 12 12-1 / 12-2 Children Adults 13 13-1 / 13-2 Children Adults 14 14-1 / 14-2 Children Exclusively Breastfed Infants 15 15-1 / 15-2 Adults 16 16-1 / 16-2 Children

Inhalation Rate

Long Term

Adults

6

6-1 / 16-3 Children

Short Term

Adults

6-2 / 6-3 Children

BodySurface Area

Adults

7

7-1, 7-2 / 7-3 Children

Adherence of Solids

Adults

7-4 / 7-5 Children

Body Weight

Adults

88-1 / 8-2 Children

Lifetime

Males 18 18

-1 / 18-2

Females

Activity Patterns

Adults

16

16-1 / 16-2 Children

Occupational MobilityAdults 16-3 / 16-4

Population Mobility

Adults 16

-5 / 16-6 Children

Frequency of Use

Amount UsedGeneral Population 17No Recommendations

Duration

Air Exchange Rates

Residential Buildings

19

19-1 / 19-2

Commercial Buildings 19-3 / 19-4

Building Volume

Residential Buildings 19-1 / 19-2

Commercial Buildings 19-3 / 19-4

Meat and Dairy Intake 

Grain Intake 

Home Produced Food Intake 

Total Food Intake 

Human Milk Intake 

General Population 

10 

10-1 / 10-2 

Marine Recreational 10-3 / 10-4

Fish and Shellfish Intake 

Freshwater Recreational 10-5 

Native American Populations 10-6 

Time Swimming 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER 

RECOMMENDATIONS 

TABLE/RATINGS TABLE 

Ingestion 

Drinking Water Intake 

Mouthing Soil/Dust I

ntake 

Fruit and Vegetable Intake 

Inhalation 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Building Characteristics 
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults 

Children 11 

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults 

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults 

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults 

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants 

Adults

Children

15
 

16

15-1 / 15-2
 

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake 

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing 

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Fish and Shellfish Intake 

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5 Ingestion 

Meat and Dairy Intake 

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake 

Time Swimming 

Exclusively Breastfed Infants

Adults 

Children 

15

16
 

15-1 / 15-2

16-1 / 16-2
 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake

Time Swimming

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term 

Inhalation Rate 

Short Term 

Adults 

Children 

Adults 

Children 

6 

6-1 / 6-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake

Time Swimming

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area 

Adherence of Solids 

Adults 

Children 

Adults 

Children 

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake

Time Swimming

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) 

Human Characteristics 

Body Weight 

Lifetime 

Adults 

Children 

Males

Females

8 

18

8-1 / 8-2 

18-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake

Time Swimming

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) 

Human Characteristics 

Body Weight 

Lifetime 

Adults

Children

Males 

Females 

8 

18
 

8-1 / 8-2 

18-1 / 18-2
 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake

Time Swimming

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns 

Occupational Mobility 

Population Mobility 

Adults 

Children 

Adults 

Adults 

Children 

16 

16-1 / 16-2 

16-3 / 16-4 

16-5 / 16-6
 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake

Time Swimming

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use 

Amount Used 

Duration 

General Population 17 No Recommendations 

(All Routes) 

Building Characteristics 

Air Exchange Rates

Building Volume

Residential Buildings

Commercial Buildings

Residential Buildings

Commercial Buildings

19

19-1 / 19-2

19-3 / 19-4

19-1 / 19-2

19-3 / 19-4
RECOMMENDATIONS 

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION CHAPTER TABLE/RATINGS TABLE 

Drinking Water Intake

Adults

Children 3 

3-1 / 3-2 3-1 / 3-4

Mouthing

Pregnant Women

Frequency

Duration 4 

3-1 / 3-6

4-1 / 4-2 

Soil/Dust Intake Adults

Children 5 5-1 / 5-2 

Fruit and Vegetable Intake Adults

Children 9 9-1 / 9-2 

Ingestion Fish and Shellfish Intake

General Population

Marine Recreational

Freshwater Recreational 10

10-1 / 10-2

10-3 / 10-4

10-5

Meat and Dairy Intake

Native American Populations

Adults

Children 11

10-6

11-1 / 11-2 

Grain Intake Adults

Children 12 12

-1 / 12-2 

Home Produced Food Intake Adults

Children 13 13

-1 / 13-2 

Total Food Intake Adults

Children 14 14

-1 / 14-2 

Human Milk Intake

Time Swimming

Exclusively Breastfed Infants

Adults

Children

15

16

15-1 / 15-2

16-1 / 16-2 

Inhalation 

Long Term

Inhalation Rate

Short Term

Adults

Children

Adults

Children

6 

6-1 / 16-3 

6-2 / 6-3 

Dermal 

Body Surface Area

Adherence of Solids

Adults

Children

Adults

Children

7 

7-1, 7-2 / 7-3 

7-4 / 7-5 

(All Routes) Body Weight AdultsChildren 8 8-1 / 8-2 

Human Characteristics Lifetime Males

Females 18 18

-1 / 18-2 

(All Routes) 

Activity Factors 

Activity Patterns

Occupational Mobility

Population Mobility

Adults

Children

Adults

Adults

Children

16

16-1 / 16-2 

16-3 / 16-4

16-5 / 16-6 

(All Routes) 

Consumer Product Use 

Frequency of Use

Amount Used

Duration

General Population 17 No Recommendations

(All Routes) 

Building Characteristics 

Air Exchange Rates 

Building Volume 

Residential Buildings 

Commercial Buildings 

Residential Buildings 

Commercial Buildings 

19 

19-1 / 19-2
 

19-3 / 19-4
 

19-1 / 19-2
 

19-3 / 19-4
 
Exposure Factors Handbook 

Chapter 1—Introduction 

APPENDIX 1A 

RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA AND DOSE-RESPONSE
 

INFORMATION FROM THE INTEGRATED RISK INFORMATION SYSTEM (IRIS)
 

Exposure Factors Handbook Page
 

November 2011 1A-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

APPENDIX 1A—RISK CALCULATIONS 

USING EXPOSURE FACTORS HANDBOOK 

DATA AND DOSE-RESPONSE INFORMATION 

FROM THE INTEGRATED RISK 

INFORMATION SYSTEM (IRIS) 

1A-1. INTRODUCTION 

When estimating risk to a specific population 

from chemical exposure, whether it is the entire 

national population or some smaller population of 

interest, exposure data (either from this handbook or 

from other sources) must be combined with doseresponse information. The dose-response information 

typically comes from the Integrated Risk Information 

System (IRIS) database, which maintains a list of 

toxicity (i.e., dose-response) values for a number of 

chemical agents (www.epa.gov/iris). Care must be 

taken to ensure that population parameters from the 

dose-response assessment are consistent with the 

population parameters used in the exposure analysis. 

This appendix discusses procedures for ensuring this 

consistency. 

The U.S. EPA's approach to estimating risks 

associated with toxicity from non-cancer effects is 

fundamentally different from its approach to 

estimating risks associated with toxicity from 

carcinogenic effects. One difference is that different 

assumptions are made regarding the mode of action 

that is involved in the generation of these two types 

of effects. For non-cancer effects, the Agency 

assumes that these effects are produced through a 

non-linear (e.g., “threshold”) mode of action (i.e., 

there exists a dose below which effects do not occur) 

(U.S. EPA, 1993). For carcinogenic effects, deemed 

to operate through a mutagenic mode of action or for 

which the mode of action is unknown, the Agency 

assumes there is the absence of a “threshold” (i.e., 

there exists no level of exposure that does not pose a 

small, but finite, probability of generating a 

carcinogenic response). 

For carcinogens, quantitative estimates of risks 

for the oral route of exposure are generated using 

cancer slope factors. The cancer slope factor is an 

upper bound estimate of the increase in cancer risk 

per unit of dose and is typically expressed in units of 

(mg/kg-day)–1. Because dose-response assessment 

typically involves extrapolating from laboratory 

animals to humans, a human equivalent dose (HED) 

is calculated from the animal data in order to derive a 

cancer slope factor that is appropriately expressed in 

human equivalents. The Agency endorses a hierarchy 

of approaches to derive human equivalent oral 

exposures from data in laboratory animal species, 

with the preferred approach being physiologically 

based toxicokinetic (PBTK) modeling. In the absence 

of PBTK modeling, U.S. EPA advocates using body 

weight to the 3⁄4 power (BW3/4) as the default scaling 

factor for extrapolating toxicologically equivalent 

doses of orally administered agents from animals to 

humans (U.S. EPA, 2011). 

Application of the BW3/4 scaling factor is based 

on adult animal and human body weights to adjust for 

dosimetric differences (predominantly toxicokinetic) 

between adult animals and humans (U.S. EPA, 2011). 

The internal dosimetry of other life stages (e.g., 

children, pregnant or lactating mothers) may be 

different from that of an adult (U.S. EPA, 2011). In 

some cases where data are available on effects in 

infants or children, adult PBTK models (if available) 

could be parameterized in order to predict the dose 

metric in children, as described in U.S. EPA’s report, 

A Framework for Assessing Health Risk of 

Environmental Exposures to Children (U.S. EPA, 

2011, 2006b). However, more research is needed to 

develop models for children’s dosimetric adjustments 

across life stages and experimental animal species 

(U.S. EPA, 2006b). 

In Summary: 

• No correction factors are applied to RfDs 

and RfCs when combined with exposure 

information from specific populations of 

interest. 

• ADAFs are applied to oral slope factors, 

drinking water unit risks, and inhalation 

unit risks for chemicals with a mutagenic 

mode of action as in Table 1A-1. 

• Correction factors are applied to water 

unit risks for both body weight and water 

intake rate for specific populations of 

interest. 

For cancer data from chronic animal studies, no 

explicit lifetime adjustment is necessary when 

extrapolating to humans because the assumption is 

that events occurring in a lifetime animal bioassay 

will occur with equal probability in a human lifetime. 

For cancer data from human studies (either 

occupational or general population), the Agency 

typically makes no explicit assumptions regarding 

body weight or human lifetime. For both of these 

parameters, there is an implicit assumption that the 

exposed population of interest has the same 

characteristics as the population analyzed by the 

Agency in deriving its dose-response information. In 

the rare situation where this assumption is known to 

be violated, the Agency has made appropriate 

Page Exposure Factors Handbook 

1A-2 November 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

corrections so that the dose-response parameters are 

representative of the national average population. 

For carcinogens acting through a mutagenic 

MOA, where chemical-specific data concerning early 

life susceptibility are lacking, early life susceptibility 

should be assumed, and the following ADAFs should 

be applied to the oral cancer slope factor, drinking 

water unit risks, and inhalation unit risks as described 

in the Supplemental Guidance for Assessing 

Susceptibility from Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005e) and summarized in 

Section 1.9 of this handbook: 

 10-fold for exposures occurring before 2 

years of age; 

 3-fold for exposures occurring between the 

ages of 2 and 16 years of age; and 

 no adjustment for exposures occurring after 

16 years of age. 

In addition to cancer slope factors, dose-response 

measures for carcinogens are also expressed as 

increased cancer risk per unit concentration for 

estimating risks from exposure to substances found in 

air or water (U.S. EPA, 1992b). For exposure via 

inhalation, this dose-response value is referred to as 

an IUR and is typically expressed in units of 

(μg/m3

)

-1. For exposure via drinking water, this doseresponse value is termed the drinking water unit risk 

(U.S. EPA, 1992b). These unit risk estimates 

implicitly assume standard adult intake rates (i.e., 2 

L/day of drinking water; 20-m3

/day inhalation rate). 

It is generally not appropriate to adjust the inhalation 

unit risk for different body weights or inhalation rates 

because the amount of chemical that reaches the 

target site is not a simple function of two parameters 

(U.S. EPA, 2009b). For drinking water unit risks, 

however, it would be appropriate for risk assessors to 

replace the standard intake rates with values 

representative of the exposed population of interest, 

as described in Section 1A-2 and Table 1A-1 below 

(U.S. EPA, 2005e). 

As indicated above, for non-cancer effects, doseresponse assessment is based on a threshold 

hypothesis, which holds that there is a dose above 

which effects (or their precursors) begin to occur. The 

U.S. EPA defines the RfD as “an estimate of a daily 

oral exposure for a given duration to the human 

population (including susceptible subgroups) that is 

likely to be without an appreciable risk of adverse 

health effects over a lifetime. It is derived from a 

benchmark dose lower confidence limit (BMDL), a 

no-observed-adverse-effect level, a 

lowest-observed-adverse-effect level, or another 

suitable point of departure, with 

uncertainty/variability factors applied to reflect 

limitations of the data used.” The point of departure 

on which the RfD is based can come directly from 

animal dosing experiments or occasionally from 

human studies followed by application of uncertainty 

factors to reflect uncertainties such as extrapolating 

from subchronic to chronic exposure, extrapolating 

from animals to humans, and deficiencies in the 

toxicity database. Consistent with the derivation of 

oral cancer slope factors noted above, the U.S. EPA 

prefers the use of PBTK modeling to derive HEDs to 

extrapolate from data in laboratory animal species, 

but in the absence of a PBTK model, endorses the use 

of BW3/4 as the appropriate default scaling factor for 

use in calculating HEDs for use in derivation of the 

oral RfD (U.S. EPA, 2011). Body-weight scaling 

using children’s body weight may not be appropriate 

in the derivation of the RfD because RfDs are already 

intended to be protective of the entire population 

including susceptible populations such as children 

and other life stages (U.S. EPA, 2011). Uncertainty 

factors are used to account for intraspecies variation 

in susceptibility (U.S. EPA, 2011). As indicated 

above, body-weight scaling is meant to 

predominantly address toxicokinetic differences 

between animals and humans and can be viewed as a 

dosimetric adjustment factor (DAF). Data on 

toxicodynamic processes needed to assess the 

appropriateness of body-weight scaling for early life 

stages are not currently available (U.S. EPA, 2011). 

The procedure for deriving dose-response values 

for non-cancer effects resulting from the inhalation 

route of exposure (i.e., RfCs) differs from the 

procedure used for deriving dose-response values for 

non-cancer effects resulting from the oral route of 

exposure (i.e., RfDs). The difference lies primarily in 

the source of the DAFs that are employed. As with 

the RfD, the U.S. EPA prefers the application of 

PBTK modeling in order to extrapolate laboratory 

animal exposure concentrations to HECs for the 

derivation of an RfC. In the absence of a PBTK 

model, the U.S. EPA advocates the use of a default 

procedure for deriving HECs that involve application 

of DAFs. This procedure uses species-specific 

physiologic and anatomic factors relevant to the 

physical form of the pollutant (i.e., particulate or gas) 

and categorizes the pollutant with regard to whether 

it elicits a response either locally (i.e., within the 

respiratory tract) or remotely (i.e., extrarespiratory). 

These factors are combined in determining an 

appropriate DAF. The default dosimetric adjustments 

and physiological parameters used in RfC derivations 

assume an adult male with an air intake rate of 20 

Exposure Factors Handbook Page
 

November 2011 1A-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

m3/day and a body weight of 70 kg (U.S. EPA, 1994). 

Assumptions for extrathoracic, tracheobronchial, and 

pulmonary surface areas are also made based on an 

adult male (U.S. EPA, 1994). For gases, the 

parameters needed for deriving a DAF include 

species-to-species ratios of blood:gas partition 

coefficients. For particulates, the DAF is termed the 

regional deposition dose ratio and is derived from 

parameters that include region-specific surface areas, 

the ratio of animal-to-human minute volumes, and 

the ratio of animal-to-human regional fractional 

deposition. If DAFs are not available, simple 

ventilation rate adjustments can be made in 

generating HECs for use in derivation of the RfC 

(U.S. EPA, 2006b). Toxicity values (RfCs) derived 

using the default approach from the inhalation 

dosimetry methodology described in U.S. EPA (1994) 

are developed for the human population as a whole, 

including sensitive groups. Therefore, no quantitative 

adjustments of these toxicity values are needed to 

account for different ventilation rates or body weights 

of specific age groups (U.S. EPA, 2009b). 

1A-2. CORRECTIONS FOR DOSE-RESPONSE 

PARAMETERS 

The correction factors for the dose-response 

values tabulated in the IRIS database for non-cancer 

and carcinogenic effects are summarized in Table 1A1. Use of these correction factors is necessary to 

avoid introducing errors into the risk analysis. This 

table is applicable in most cases that will be 

encountered, but it is not applicable when (a) the 

effective dose has been derived with a PBTK model, 

and (b) the dose-response data have been derived 

from human data. In the former case, the population 

parameters need to be incorporated into the model. In 

the latter case, the correction factor for the 

dose-response parameter must be evaluated on a 

case-by case basis by examining the specific data and 

assumptions employed in the derivation of the 

parameter. 

It is important to note that the 2 L/day per capita 

water intake assumption is closer to a 90th percentile 

intake value than an average value. If an average 

measure of exposure in adults is of interest, the 

drinking water unit risk can be adjusted by 

multiplying it by 1.0/2 or 0.5, where 1.0 L/day is the 

average per capita water intake for adults ≥21 years 

old (see Chapter 3 of this handbook). If the 

population of interest is children, rather than adults, 

then a body-weight adjustment is also necessary. For 

example, the average water intake for children 3 to 

<6 years of age is 0.33 L/day (see Chapter 3 of this 

handbook), and the average body weight in this age 

group is 18.6 kg (see Chapter 8 of this handbook). 

The water unit risk then needs to be adjusted by 

multiplying it by an adjustment factor derived from 

these age-group-specific values and calculated using 

the formula from Table 1A-1 as follows: 

Water unit risk correction factor = 

0.33(L / day)  70(kg) 
  ×
 =
 0.6
 (Eqn. 1A-1)  

 

  2(L  / day)
 18.6(kg)

1A-3. REFERENCES FOR APPENDIX 1A 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992). EPA's approach for assessing the 

risks associated with chronic exposure to 

carcinogens: Background document 2. 

http://www.epa.gov/iris/carcino.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1993). Reference Dose (RfD): Description 

and Use in Health Risk Assessments 

Background Document 1A, March 15, 1993. 

Integrated Risk Information System. 

http://www.epa.gov/IRIS/rfd.htmgoo. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1994). Methods for derivation of inhalation 

reference concentrations and application of 

inhalation dosimetry. (EPA/600/8-90/066F). 

Research Triangle Park, NC: U.S. 

Environmental Protection Agency, Office of 

Research and Development, Office of 

Health and Environmental Assessment, 

Environmental Criteria and Assessment 

Office. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=71993. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Supplemental guidance for assessing 

susceptibility from early-life exposure to 

carcinogens. (EPA/630/R-03/003F). 

Washington, DC: U.S. Environmental 

Protection Agency, Risk Assessment Forum. 

http://www.epa.gov/cancerguidelines/guideli 

nes-carcinogen-supplement.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2006). A framework for assessing health 

risk of environmental exposures to children. 

(EPA/600/R-05/093F). Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=158363. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009). Risk assessment guidance for 

superfund volume I: Human health 

evaluation manual (Part F, supplemental 

Page Exposure Factors Handbook 

1A-4 November 2011 
 

 

Exposure Factors Handbook 

Chapter 1—Introduction 

guidance for inhalation risk assessment): 

Final. (EPA/540/-R-070/002). Washington, 

DC: U.S. Environmental Protection Agency, 

Office of Superfund Remediation and 

Technology Innovation. 

http://www.epa.gov/oswer/riskassessment/ra 

gsf/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2011). Recommended use of body weight 

3/4 as the default method in derivation of the 

oral reference dose. (EPA/100/R11/0001). 

Washington, DC. 

http://www.epa.gov/raf/publications/interspe 

cies-extrapolation.htm. 

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Exposure Factors Handbook 

Chapter 1—Introduction 

Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-Standard Populations 

IRIS Risk Measure [Units] Correction Factor (CF) for Modifying IRIS Risk Measuresa 

RfD No correction factor needed 

RfC No correction factor needed 

Oral Slope Factor [mg/(kg-day)]–1 No correction factor needed except for chemicals with mutagenic MOA. 

ADAFs are applied as follows: 

• 10-fold for exposure occurring before 2 years of age 

• 3-fold for exposure occurring between the ages of 2 and 16 

• no adjustment for exposures occurring after 16 years of age 

Drinking Water Unit Risk [μg/L]–1 [IW 

P

/2] × [70/(WP)] 

For chemicals with mutagenic MOA, ADAFs are applied as follows: 

• 10-fold for exposure occurring before 2 years of age 

• 3-fold for exposure occurring between the ages of 2 and 16 

• no adjustment for exposures occurring after 16 years of age 

Inhalation Unit Risk [μg/m3]

–1 No correction factor needed except for chemicals with mutagenic MOA. 

ADAFs are applied as follows: 

• 10-fold for exposure occurring before 2 years of age 

• 3-fold for exposure occurring between the ages of 2 and 16 

• no adjustment for exposures occurring after 16 years of age a Modified risk measure = (CF) × IRIS value. 

W = Body weight (kg) 

IW = Drinking water intake (liters per day) 

WP , IW 

P = Denote non-standard parameters from the actual population of interest 

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Exposure Factors Handbook 

Chapter 2—Variability and Uncertainty 

2. VARIABILITY AND UNCERTAINTY 

Accounting for variability and uncertainty is 

fundamental to exposure assessment and risk 

analysis. While more will be said about the 

distinction between variability and uncertainty in 

Section 2.1, it is useful at this point to motivate the 

treatment of variability and uncertainty in exposure 

assessment. Given that exposure and susceptibility to 

exposure is usually not uniform across a population, 

accounting for variability is the means by which a 

risk assessor properly accounts for risk to the 

population as a whole. However, a risk assessment 

usually involves uncertainties about the precision of a 

risk estimate. A heuristic distinction between 

variability and uncertainty is to consider uncertainty 

as a lack of knowledge about factors affecting 

exposure or risk, whereas variability arises from 

heterogeneity across people, places, or time. 

Properly addressing variability and uncertainty 

will increase the likelihood that results of an 

assessment or analysis will be used in an appropriate 

manner. Characterizing and communicating 

variability and uncertainty should be done throughout 

all the components of the risk assessment process 

(NRC, 1994). Thus, careful consideration of the 

variability and uncertainty associated with the 

exposure factors information used in an exposure 

assessment is of utmost importance. Proper 

characterization of variability and uncertainty will 

also support effective communication of risk 

estimates to risk managers and the public. 

This chapter provides an overview of variability 

and uncertainty in the context of exposure analysis 

and is not intended to present specific methodological 

guidance. It is intended to acquaint the exposure 

assessor with some of the fundamental concepts of 

variability and uncertainty as they relate to exposure 

assessment and the exposure factors presented in this 

handbook. It also provides summary descriptions of 

methods and considerations for evaluating and 

presenting the uncertainty associated with exposure 

estimates and a bibliography of references on a wide 

range of methodologies concerned with the 

application of variability and uncertainty analysis in 

exposure assessment. Subsequent sections in this 

chapter are devoted to the following topics: 

2.1	 Variability versus uncertainty; 

2.2	 Types of variability; 

2.3	 Addressing variability; 

2.4	 Types of uncertainty; 

2.5	 Reducing uncertainty; 

2.6	 Analyzing variability and uncertainty; 

2.7	 Literature review of variability and 

uncertainty analysis; 

2.8	 Presenting results of variability and
 

uncertainty analyses; and
 

2.9	 References. 

There are numerous ongoing efforts in the U.S. 

Environmental Protection Agency (EPA) and 

elsewhere to further improve the characterization of 

variability and uncertainty. The U.S. EPA’s Risk 

Assessment Forum has established guidelines for the 

use of probabilistic techniques (e.g., Monte Carlo 

analysis) to better assess and communicate risk (U.S. 

EPA, 1997a, b). The U.S. EPA’s Science Policy 

Council is developing white papers on the use of 

expert elicitation for characterizing uncertainty in 

risk assessments. Expert judgment has been used in 

the past by some regulatory agencies when limited 

data or knowledge results in large uncertainties 

(NRC, 2009). The International Program on 

Chemical Safety (IPCS) has developed guidance on 

characterizing and communicating uncertainty in 

exposure assessment (WHO, 2008). Suggestions for 

further reading on variability and uncertainty include 

Babendreier and Castleton (2005), U.S. EPA (2008), 

Saltelli and Annoni (2010), Bogen et al. (2009), and 

Refsgaard et al. (2007). 

2.1.	 VARIABILITY VERSUS UNCERTAINTY 

While some authors have treated variability as a 

specific type or component of uncertainty, the U.S. 

EPA (1995), following the NRC (1994) 

recommendation, has advised the risk assessor to 

distinguish between variability and uncertainty. 

Variability is a quantitative description of the range 

or spread of a set of values. Common measures 

include variance, standard deviation, and interquartile 

range. Variability arises from heterogeneity across 

individuals, places, or time. Uncertainty can be 

defined as a lack of precise knowledge, either 

qualitative or quantitative. In the context of exposure 

assessment, data uncertainty refers to the lack of 

knowledge about factors affecting exposure. 

The key difference between uncertainty and 

variability is that variability cannot be reduced, only 

better characterized (NRC, 2009). 

We will describe a brief example of human water 

consumption in relation to lead poisoning to help 

distinguish between variability and parameter 

uncertainty (a particular type of uncertainty). We 

might characterize the variability of water 

consumption across individuals by sampling from a 

population and measuring water consumption. From 

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this sample, we obtain useful statistics on the 

variability of water consumption, which we assume 

here represents the population of interest. There may 

be similar statistics on the variability in the 

concentration of lead in the water consumed. A risk 

model may include a factor (i.e., dose response, 

representing the absorption of lead from ingested 

water to blood). The dose response may be 

represented by a constant in a risk model. However, 

knowledge about the dose response may be uncertain, 

motivating an uncertainty analysis. Dose response 

values are often relatively uncertain compared to 

exposure parameters. Therefore, in the above 

example, a high uncertainty surrounds the absorption 

of lead, whereas there is less uncertainty associated 

with the parameters of water consumption (i.e., 

population mean and standard deviation). One 

challenge in modeling dose-response uncertainty is 

the lack of consensus on its treatment. 

Most of the data presented in this handbook 

concern variability. Factors contributing to variability 

in risk include variability in exposure potential (e.g., 

differing behavioral patterns, location), variability in 

susceptibility due to endogenous factors (e.g., age, 

sex, genetics, pre-existing disease), variability in 

susceptibility due to exogenous factors (e.g., 

exposures to other agents) (NRC, 2009). 

2.2. TYPES OF VARIABILITY 

Variability in exposure is dependent on 

contaminant concentrations as well as variability in 

human exposure factors. Human exposure factors 

may vary because of an individual’s location, specific 

exposure time, or behavior. However, even if all of 

those factors were constant across a set of 

individuals, there could still be variability in risk 

because of variability in susceptibilities. Variations in 

contaminant concentrations and human exposure 

factors are not necessarily independent. For example, 

contaminant concentrations and behavior might be 

correlated. 

A useful way to think about sources of variability 

is to consider these four broad categories: 

1) Spatial variability: variability across 

locations; 

2) Temporal variability: variability over time; 

3) Intra-individual variability: variability within 

an individual; and 

4) Inter-individual variability: variability across 

individuals. 

Spatial variability refers to differences that may 

occur because of location. For example, outdoor 

pollutant levels can be affected at the regional level 

by industrial activities and at the local level by 

activities of individuals. In general, higher exposures 

tend to be associated with closer proximity to a 

pollutant source, whether it is an industrial plant or 

related to a personal activity such as showering or 

gardening. Susceptibilities may vary across locations, 

for example, some areas have particularly high 

concentrations of a younger or older population. 

Temporal variability refers to variations over 

time, whether long- or short-term. Different seasons 

may cause varied exposure to pesticides, bacteria, or 

indoor air pollution, each of which might be 

considered an example of long-term variability. 

Examples of short-term variability are differences in 

industrial or personal activities on weekdays versus 

weekends or at different times of the day. 

Intra-individual variability is a function of 

fluctuations in an individual’s physiologic (e.g., body 

weight), or behavioral characteristics (e.g., ingestion 

rates or activity patterns). For example, patterns of 

food intake change from day to day and may do so 

significantly over a lifetime. Intra-individual 

variability may be associated with spatial or temporal 

variability. For example, because an individual’s 

dietary intake may reflect local food sources, intake 

patterns may change if place of residence changes. 

Also, physical activity may vary depending upon the 

season, life stage, or other factors associated with 

temporal variability. 

Inter-individual variability refers to variation 

across individuals. Three broad categories include the 

following: 

1) individual characteristics such as sex, age, race, 

height, or body weight (including any obesity), 

phenotypic genetic expression, and 

pathophysiological conditions; 

2) individual behaviors such as activity patterns, 

and ingestion rates; and 

3) susceptibilities due to such things as life stage 

or genetic predispositions. 

Inter-individual variability may also be 

related to spatial and temporal factors. 

2.3. ADDRESSING VARIABILITY 

In this handbook, variability is addressed by 

presenting data on the exposure factors in one of the 

following three ways: (1) as tables with percentiles or 

ranges of values for various age groups or other 

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populations, (2) as probability distributions with 

specified parameter estimates and related confidence 

intervals, or (3) as a qualitative discussion. One 

approach to exposure assessment is to assume a 

single value for a given exposure level, often the 

mean or median, in order to calculate a single point 

estimate of risk. Often however, individuals vary in 

their exposure, and an exposure assessment would be 

remiss to exclude other possible exposure levels. 

Thus, an exposure assessment often involves a 

quantification of the exposure at high levels of the 

exposure factor, i.e., 90th, 95th, and 99th percentiles, 

and not only the mean or median exposure. Where 

possible, confidence limits for estimated percentiles 

should be provided. The U.S. EPA’s approach to 

variability assessment is described in Risk Assessment 

Principles and Practices: Staff Paper (U.S. EPA, 

2004b). Accounting for variability in an exposure 

assessment may be limited to a deterministic model 

in which high-end values are used or may involve a 

probabilistic approach, e.g., Monte Carlo Analysis 

(U.S. EPA, 1997a). 

Populations are by nature heterogeneous. 

Characterizing the variability in the population can 

assist in focusing analysis on segments of the 

population that may be at higher risk from 

environmental exposure. Although population 

variability cannot be reduced, data variability can be 

lessened by disaggregating the population into 

segments with similar characteristics. 

Although much of this handbook is concerned 

with variability in exposure, it is critical to note that 

there are also important variations among individuals 

in a population with respect to susceptibility. As 

noted in NRC (2009), people differ in susceptibility 

to the toxic effects of a given chemical exposure 

because of such factors as genetics, lifestyle, 

predisposition to diseases and other medical 

conditions, and other chemical exposures that 

influence underlying toxic processes. Susceptibility is 

also a function of life stages, e.g., children may be at 

risk of high exposure relative to adults. Susceptibility 

factors are broadly considered to include any factor 

that increases (or decreases) the response of an 

individual to a dose relative to a typical individual in 

the population. The distribution of disease in a 

population can result not only from differences in 

susceptibility, but from differing exposures of 

individuals and target groups in a population. Taken 

together, variations in disease susceptibility and 

exposure potential give rise to potentially important 

variations in vulnerability to the effects of 

environmental chemicals (NRC, 2009). 

2.4. TYPES OF UNCERTAINTY 

Uncertainty in exposure analysis is related to the 

lack of knowledge concerning one or more 

components of the assessment process. The U.S. EPA 

(1992) has classified uncertainty in exposure 

assessment into three broad categories: (1) scenario 

uncertainty, (2) parameter uncertainty, and (3) model 

uncertainty. 

Scenario uncertainty 

Scenario uncertainty arises from descriptive 

errors, aggregation errors, errors in professional 

judgment, and incomplete analysis. Descriptive 

errors are errors in information that translate into 

errors in the development of exposure pathways, 

scenarios, exposed population, and exposure 

estimates. Aggregation errors occur as a result of 

lumping approximations. These include, for 

example, assuming a homogeneous population, and 

spatial and temporal assumptions. Uncertainty can 

also arise from errors in professional judgment. 

These errors affect how an exposure scenario is 

defined, the selection of exposure parameters, 

exposure routes and pathways, populations of 

concern, chemicals of concern, and the selection of 

appropriate models. An incomplete analysis can also 

be a source of uncertainty because important 

exposure scenarios and susceptible populations may 

be overlooked. 

Parameter uncertainty 

Risk assessments depict reality interpreted 

through mathematical representations that describe 

major processes and relationships. Process or 

mechanistic models use equations to describe the 

processes that an environmental agent undergoes in 

the environment in traveling from the source to the 

target organism. Mechanistic models have also been 

developed to represent the toxicokinetic and 

toxicodynamic processes that take place inside the 

organism, leading to the toxic endpoint. The specific 

parameters of the equations found in these models are 

factors that influence the release, transport, and 

transformation of the environmental agent, the 

exposure of the target organism to the agent, transport 

and metabolism of the agent in the body, and 

interactions on the cellular and molecular levels. 

Empirical models are also used to define 

relationships between two values, such as the dose 

and the response. Uncertainty in parameter estimates 

stem from a variety of sources, including the 

following: 

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a.	 Measurement errors: 

1.	 Random errors in analytical devices (e.g., 

imprecision of continuous monitors that 

measure stack emissions). 

2.	 Systemic bias (e.g., estimating inhalation 

from indoor ambient air without 

considering the effect of volatilization of 

contaminants from hot water during 

showers). 

b. Use of surrogate data for a parameter instead 

of direct analysis of it (e.g., use of standard 

emission factors for industrialized processes). 

c.	 Misclassification (e.g., incorrect assignment 

of exposures of subjects in historical 

epidemiologic studies due to faulty or 

ambiguous information). 

d. Random sampling error (e.g., variation in 

estimates due to who was randomly selected). 

e.	 Non-representativeness with regard to 

specified criteria (e.g., developing emission 

factors for dry cleaners based on a sample of 

“dirty” plants that do not represent the overall 

population of plants). 

Model uncertainty 

Model uncertainties arise because of gaps in the 

scientific theory that is required to make predictions 

on the basis of causal inferences. Common types of 

model uncertainties in various risk assessment-related 

activities include the following: 

a.	 Relationship errors (e.g., incorrectly inferring 

the basis of correlations between chemical 

structure and biological activity). 

b. Oversimplified representations of reality (e.g., 

representing a three-dimensional aquifer with 

a two-dimensional mathematical model). 

c.	 Incompleteness, i.e., exclusion of one or more 

relevant variables (e.g., relating asbestos to 

lung cancer without considering the effect of 

smoking on both those exposed to asbestos 

and those unexposed). 

d. Use of surrogate variables for ones that cannot 

be measured (e.g., using wind speed at the 

nearest airport as a proxy for wind speed at 

the facility site). 

e.	 Failure to account for correlations that cause 

seemingly unrelated events to occur more 

frequently than expected by chance (e.g., two 

separate components of a nuclear plant are 

both missing a particular washer because the 

same newly hired assembler put them 

together). 

f.	 Extent of (dis)aggregation used in the model 

(e.g., whether to break up the fat compartment 

into subcutaneous and abdominal fat in a 

physiologically based pharmacokinetic, or 

PBPK, model). 

Although difficult to quantify, model uncertainty 

is inherent in risk assessment that seeks to capture the 

complex processes impacting release, environmental 

fate and transport, exposure, and exposure response. 

2.5.	 REDUCING UNCERTAINTY 

Identification of the sources of uncertainty in an 

exposure assessment is the first step in determining 

how to reduce uncertainty. Because uncertainty in 

exposure assessments is fundamentally tied to a lack 

of knowledge concerning important exposure factors, 

strategies for reducing uncertainty often involve the 

application of more resources to gather either more or 

targeted data. Example strategies to reduce 

uncertainty include (1) collecting new data, 

(2) implementing an unbiased sample design, 

(3) identifying a more direct measurement method or 

a more appropriate target population, (4) using 

models to estimate missing values, (5) using 

surrogate data, (6) using default assumptions, 

(7) narrowing the scope of the assessment, and 

(8) obtaining expert elicitation. The best strategy 

likely depends on a combination of resource 

availability, time constraints, and the degree of 

confidence necessary in the results. 

2.6.	 ANALYZING VARIABILITY AND 

UNCERTAINTY 

There are different strategies available for 

addressing variability and uncertainty that vary in 

their level of sophistication. The level of effort 

required to conduct the analysis needs to be balanced 

against the need for transparency and timeliness. 

Exposure assessments are often developed in a 

tiered approach. The initial tier usually screens out 

the exposure scenarios or pathways that are not 

expected to pose much risk, to eliminate them from 

more detailed, resource-intensive review. Screeninglevel assessments typically examine exposures on the 

high end of the expected exposure distribution. 

Because screening-level analyses usually are 

included in the final exposure assessment, it may 

contain scenarios that differ in sophistication, data 

quality, and amenability to quantitative expressions 

of variability or uncertainty. Several approaches can 

be used to analyze uncertainty in parameter values. 

When uncertainty is high, for example, an assessor 

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may set order-of-magnitude bounding estimates of 

parameter ranges (e.g., from 0.1 to 10 liters for daily 

water intake). Another method may involve setting a 

range for each parameter as well as point estimates 

for certain parameters determined by available data 

or professional judgment. 

A sensitivity analysis can be used to determine 

which parameters and exposures have the most 

impact on an exposure assessment. General concepts 

in sensitivity analysis are described in Saltelli et al. 

(2008). The International Program on Chemical 

Safety proposes a four-tier approach for addressing 

uncertainty and variability (WHO, 2006). The four 

tiers are similar to those proposed in U.S. EPA (1992) 

and include the use of default assumptions; a 

qualitative, systematic identification and 

characterization of uncertainty; a qualitative 

evaluation of uncertainty using bounding estimates, 

interval analysis, and sensitivity analysis; and a more 

sophisticated one- or two-stage probabilistic analysis 

(WHO, 2006). 

Practical considerations regarding an uncertainty 

analysis include whether uncertainty would affect the 

results in a non-trivial way; an issue might be 

addressed by an initial sensitivity analysis in which a 

range of values are explored. An initial analysis of 

this sort might be facilitated by use of Microsoft 

Excel. Probabilistic risk analysis techniques are 

becoming more widely applied and are increasing in 

the level of sophistication. Bedford and Cooke (2001) 

describe in more detail the main tools and modeling 

techniques available for probabilistic risk analysis 

(Bedford and Cooke, 2001). If a probabilistic 

approach is pursued, another consideration is the 

choice of a software package. Popular software 

packages for Monte Carlo analysis range from the 

more general: Fortran, Mathematica, R, and SAS to 

the more specific: Crystal Ball, @Risk (Palisade 

Corporation), RISKMAN (PLG Inc.), and SimLab 

(Saltelli et al., 2004). 

Increasingly, probabilistic methods are being 

utilized to analyze variability and uncertainty 

independently as well as simultaneously. It is 

sometimes challenging to distinguish between 

variability and parameter uncertainty in this context 

as both can involve the distributions of a random 

variable. For instance, parameter uncertainty can be 

estimated by the standard error of a random variable 

(itself a function of variability). Note that in this case, 

increasing the sample size necessarily reduces the 

parameter uncertainty (i.e., standard error). 

More sophisticated techniques that attempt to 

simultaneously model both variability and 

uncertainty by sampling from their respective 

probability distributions are known as two-stage 

probabilistic analysis, or two-stage Monte Carlo 

analysis, which is discussed in great detail in Bogen 

and Spear (1987), Bogen (1990), Chapter 11 and 

Appendix I-3 of NRC (1994), and U.S. EPA (2001). 

These methods assume a probabilistic distribution for 

certain specified parameters. Random samples are 

drawn from each probabilistic distribution in a 

simulation and are used as input into a deterministic 

model. Analysis of the results from the simulations 

characterizes either the variability or uncertainty (or 

both) of the exposure assessment. 

Through the implementation of computationally 

efficient Markov Chain Monte Carlo algorithms like 

Metropolis-Hastings, Bayesian methods offer an 

alternative approach to uncertainty analysis that is 

attractive in part because of increasing usability of 

software. For more on Bayesian methods, see 

Gelman et al. (2003), Gilks et al. (1995), Robert and 

Casella (2004). 

The U.S. EPA has made significant efforts to use 

probabilistic techniques to characterize uncertainty. 

These efforts have resulted in documents such as the 

March 1997 Guiding Principles for Monte Carlo 

Analysis (U.S. EPA, 1997a), the May 1997 Policy 

Statement (U.S. EPA, 1997b), and the December 

2001 Superfund document Risk Assessment Guidance 

for Superfund: Volume III—Part A, Process for 

Conducting Probabilistic Risk Assessment (U.S. EPA, 

2001). 

2.7.	 LITERATURE REVIEW OF 

VARIABILITY AND UNCERTAINTY 

ANALYSIS 

There has been a great deal of recent scholarly 

research in the area of uncertainty with the 

widespread use of computer simulation. Some of this 

research also incorporates issues related to variability. 

The purpose of the literature review below is to give 

a brief description of notable developments. Section 

2.9 provides references for further research. 

Cox (1999) argues that, based on information 

theory, models with greater complexity lead to more 

certain risk estimates. This may only be true if there 

is some degree of certainty in the assumptions used 

by the model. Uncertainties associated with the 

model need to be evaluated (NRC, 2009). These 

methods were discussed in Bogen and Spear (1987), 

Cox and Baybutt (1981), Rish and Marnicio (1988), 

and U.S. EPA (1985). Seiler (1987) discussed the 

analysis of error propagation with respect to general 

mathematical formulations typically found in risk 

assessment, such as linear combinations, powers of 

one variable, and multiplicative normally distributed 

variables. Even for large and uncertain errors, the 

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formulations in Seiler (1987) are demonstrated to 

have practical value. Iman and Helton (1988) 

compared three methodologies for uncertainty and 

sensitivity analysis: (1) response surface analysis, (2) 

Latin hypercube sampling (with and without 

regression analysis), and (3) differential analysis. 

They found that Latin hypercube sampling with 

regression analysis had the best performance in terms 

of flexibility, estimate-ability, and ease of use. Saltelli 

(2002) and Frey (2002) offer views on the role of 

sensitivity analysis in risk assessment, and Frey and 

Patil (2002) compare methods for sensitivity analysis 

and recommend that two or more different sensitivity 

assessment methods should be used in order to obtain 

robust results. A Bayesian perspective on sensitivity 

analysis is described in Greenland (2001), who 

recommends that sensitivity analysis and Monte 

Carlo risk analysis should begin with specification of 

prior distributions, as in Bayesian analysis. Bayesian 

approaches to uncertainty analysis are described in 

Nayak and Kundu (2001). 

Price et al. (1999) review the history of the 

inter-individual variability factor, as well as the 

relative merits of the sensitive population conceptual 

model versus the finite sample size model in 

determining the magnitude of the variability factor. 

They found that both models represent different 

sources of uncertainty and that both should be 

considered when developing inter-individual 

uncertainty factors. Uncertainties related to interindividual and inter-species variability are treated in 

Hattis (1997) and Meek (2001), respectively. And 

Renwick (1999) demonstrates how inter-species and 

inter-individual uncertainty factors can be 

decomposed into kinetic and dynamic defaults by 

taking into account toxicodynamic and toxicokinetic 

differences. Burin and Saunders (1999) evaluate the 

robustness of the intra-species uncertainty factor and 

recommend intra-species uncertainty factoring in the 

range of 1-10. 

Based on Monte Carlo analysis, Shlyakhter 

(1994) recommends inflation of estimated 

uncertainties by default safety factors in order to 

account for unsuspected uncertainties. 

Jayjock (1997) defines uncertainty as either 

natural variability or lack of knowledge and also 

provides a demonstration of uncertainty and 

sensitivity analysis utilizing computer simulation. 

Additional approaches for coping with uncertainties 

in exposure modeling and monitoring are addressed 

by Nicas and Jayjock (2002). 

Distributional risk assessment should be 

employed when data are available that support its 

use. Fayerweather et al. (1999) describe distributional 

risk assessment, as well as its strengths and 

weaknesses. Exposure metrics for distributional risk 

assessment using log-normal distributions of time 

spent showering (Burmaster, 1998a), water intake 

(Burmaster, 1998c), and body weight (Burmaster, 

1998b; Burmaster and Crouch, 1997) have been 

developed. The lognormal distribution provides a 

succinct mathematical form that facilitates exposure 

and risk analyses. The fitted lognormal distribution is 

an approximation that should be carefully evaluated. 

One approach is to compare the lognormal 

distribution with other distributions (e.g., Weibull, 

Gamma). This is the approach used by Jacobs et al. 

(1998) and U.S. EPA (2002) in developing estimates 

of fish consumption and U.S. EPA (2004a) and Kahn 

and Stralka (2009) for estimates of water ingestion. 

These estimates were derived from the Continuing 

Survey of Food Intake by Individuals (CSFII), which 

was a Nationwide statistical survey of the population 

of the United States conducted by the U.S. 

Department of Agriculture. The CSFII collected 

extensive information on food and beverage intake 

from a sample that represented the population of the 

United States, and the sample weights provided with 

the data supported the estimation of empirical 

distributions of intakes for the entire population and 

various target populations such as intake distributions 

by various age categories. Kahn and Stralka (2008) 

used the CSFII data to estimate empirical 

distributions of water ingestion by pregnant and 

lactating women and compared the results to those 

presented by Burmaster (1998c). The comparison 

highlights the differences between the older data used 

by Burmaster and the CSFII and the differences 

between fitted approximate lognormal distributions 

and empirical distributions. The CSFII also collected 

data on body weight self-reported by respondents that 

supported the estimation of body-weight distributions 

by age categories, which are presented in Kahn and 

Stralka (2009). Detailed summary tables of results 

based on the CSFII data used by Kahn and Stralka 

(2009) are presented in Kahn (2008) personal 

communication (Kahn, 2008). 

When sensitivity analysis or uncertainty 

propagation analysis indicates that a parameter 

profoundly influences exposure estimates, the 

assessor should, if possible, develop a probabilistic 

description of its range. It is also possible to use 

estimates derived from a large-scale survey such as 

the CSFII as a basis for alternative parameter values 

that may be used in a sensitivity analysis. The CSFII 

provides the basis for an objective point of reference 

for food and beverage intake variables, which are 

critical components of many risk and exposure 

assessments. For example, an assumed value for a 

mean or upper percentile could be compared to a 

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suitable value from the CSFII to assess sensitivity. 

Deterministic and probabilistic approaches to risk 

assessment are reviewed for non-carcinogenic health 

effects in Kalbelah et al. (2003), with attention to 

quantifying sources of uncertainty. Kelly and 

Campbell (2000) review guidance for conducting 

Monte Carlo analysis and clarify the distinction 

between variability and uncertainty. This distinction 

is represented by two-stage Monte Carlo simulation, 

where a probability distribution represents variability 

in a population, while a separate distribution for 

uncertainty defines the degree of variation in the 

parameters of the population variability distribution. 

Another example of two-stage Monte Carlo 

simulation is given in Xue et al. (2006). Price et al. 

(1997) utilize a Monte Carlo approach to characterize 

uncertainties for a method aimed at estimating the 

probability of adverse, non-cancer health effects for 

exposures exceeding the reference dose. Their 

method relies on general toxicologic information for 

a compound, such as the no-observed-adverse-effectlevel dose (NOAEL). Semple et al. (2003) examine 

uncertainty arising in reconstructed exposure 

estimates using Monte Carlo methods. Uncertainty in 

PBPK models is discussed in Simon (1997) and Bois 

(2010). Slob and Pieters (1998) propose replacing 

uncertainty factors with probabilistic uncertainty 

distributions and discuss how uncertainties may be 

quantified for animal NOAELs and extrapolation 

factors. Zheng and Frey (2005) demonstrate the use 

of Monte Carlo methods for characterizing 

uncertainty and emphasize that uncertainty estimates 

will be biased if contributions from sampling error 

and measurement error are not accounted for 

separately. 

Distributional biometric data for probabilistic risk 

assessment are available for some exposure factors. 

Empirical distributions are provided in this handbook 

when available. If the data are unavailable or 

otherwise inadequate, expert judgment can be used to 

generate a subjective probabilistic representation. 

Such judgments should be developed in a consistent, 

well-documented manner. Morgan et al. (1990) and 

Rish (1988) describe techniques to solicit expert 

judgment, while Weiss (2001) demonstrates use of a 

Web-based survey. 

Standard statistical methods may be less 

cumbersome than a probabilistic approach and may 

be preferred, if there are enough data to justify their 

use and they are sufficient to support the 

environmental decision needed. Epidemiologic 

analyses may, for example, be used to estimate 

variability in human populations, as in Peretz et al. 

(1997), who describe variation in exposure time. 

Sources of variation and uncertainty may also be 

explored and quantified using a linear regression 

modeling framework, as in Robinson and Hurst 

(1997). A general framework for statistical 

assessment of uncertainty and variance is given for 

additive and multiplicative models in Rai et al. 

(1996) and Rai and Krewski (1998), respectively. 

Wallace and Williams (2005) describe a robust 

method for estimating long-term exposures based on 

short-term measurements. 

In addition to the use of defaults and quantitative 

analysis, exposure and risk assessors often rely on 

expert judgment when information is insufficient to 

establish uncertainty bounds (NRC, 2009). There are, 

however, some biases introduced during expert 

elicitation. Some of these include availability, 

anchoring and adjustment, representativeness, 

disqualification, belief in “law of small numbers,” 

and overconfidence (NRC, 2009). Availability refers 

to the tendency to assign greater probability to 

commonly encountered or frequently mentioned 

events (NRC, 2009). Anchoring and adjustment is the 

tendency to be over-influenced by the first 

information seen or provided (NRC, 2009). 

Representativeness is the tendency to judge an event 

by reference to another (NRC, 2009). 

Disqualification is the tendency to ignore data or 

evidence that contradicts strongly held convictions 

(NRC, 2009). The belief in the “law of small 

numbers” is to believe that small samples from a 

population are more representative than is justified 

(NRC, 2009). Overconfidence is the tendency of 

experts to belief that their answers are correct (NRC, 

2009). 

2.8.	 PRESENTING RESULTS OF 

VARIABILITY AND UNCERTAINTY 

ANALYSES 

The risk assessor is advised to distinguish 

between variability of exposure and associated 

uncertainties. A risk assessment should include three 

components involving elements of variability and 

uncertainty: (1) the estimated risk itself (X), (2) the 

level of confidence (Y) that the risk is no higher than 

X, and (3) the percent of the population (Z) that X is 

intended to apply to in a variable population (NRC, 

1994). This information will provide risk managers 

with a better understanding of how exposures are 

distributed over the population and of the certainty of 

the exposure assessment. 

Sometimes analyzing all exposure scenarios is 

unfeasible. At minimum, the assessor should describe 

the rationale for excluding reasonable exposure 

scenarios; characterize the uncertainty in these 

decisions as high, medium, or low; and state whether 

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they were based on data, analogy, or professional 

judgment. Where uncertainty is high, a sensitivity 

analysis can be used to estimate upper limits on 

exposure by way of a series of “what if” questions. 

Although assessors have historically used 

descriptors (e.g., high-end, worst case, average) to 

communicate risk variability, the 1992 Guidelines for 

Exposure Assessment (U.S. EPA, 1992) established 

quantitative definitions for these risk descriptors. The 

data presented in this handbook are one of the tools 

available to exposure assessors to construct the 

various risk descriptors. A thorough risk assessment 

should include particular assumptions about human 

behavior and biology that are a result of variability. A 

useful example is given in NRC (1994): 

“...a poor risk characterization for a 

hazardous air pollutant might say ‘The risk 

number R is a plausible upper bound.’” A 

better characterization would say, “The 

risk number R applies to a person of 

reasonably high-end behavior living at the 

fenceline 8 hours a day for 35 years.” 

In addition to presenting variability in exposure, 

frequently, exposure assessments include an 

uncertainty analysis. An exposure assessment will 

include assumptions about the contaminant, 

contaminant exposure routes and pathways, location, 

time, population characteristics, and susceptibilities. 

Each of these assumptions may be associated with 

uncertainties. Uncertainties may be presented using a 

variety of techniques, depending on the requirements 

of the assessment, the amount of data available, and 

the audience. Simple techniques include risk 

designations, i.e., high, medium, or low 

(un)certainties. Sophisticated techniques may include 

quantitative descriptions of the uncertainty analysis 

or graphical representations. 

The exposure assessor may need to make many 

decisions regarding the use of existing information in 

constructing scenarios and setting up the exposure 

equations. In presenting the scenario results, the 

assessor should strive for a balanced and impartial 

treatment of the evidence bearing on the conclusions 

with the key assumptions highlighted. For these key 

assumptions, one should cite data sources and explain 

any adjustments of the data. 

The exposure assessor should describe the 

rationale for any conceptual or mathematical models. 

This discussion should address their verification and 

validation status, how well they represent the 

situation being assessed (e.g., average versus 

high-end estimates), and any plausible alternatives in 

terms of their acceptance by the scientific 

community. 

To the extent possible, this handbook provides 

information that can be used in a risk assessment to 

characterize variability, and to some extent, 

uncertainty. In general, variability is addressed by 

providing probability distributions, where available, 

or qualitative discussions of the data sets used. 

Uncertainty is addressed by applying confidence 

ratings to the recommendations provided for the 

various factors, along with detailed discussions of 

any limitations of the data presented. 

2.9. REFERENCES FOR CHAPTER 2 

Babendreier, J; Castleton, K. (2005). Investigating 

uncertainty and sensitivity in integrated, 

multimedia environmental models: Tools for 

FRAMES-3MRA. Environ Modell Softw 

20: 1043-1055. 

http://dx.doi.org/10.1016/j.envsoft.2004.09. 

013. 

Bedford, T; Cooke, R. (2001). Probabilistic risk 

analysis: Foundations and methods. 

Cambridge, UK: Cambridge University 

Press. 

Bogen,	 KT. (1990). Uncertainty in environmental 

health risk assessment. New York, NY: 

Garlend Publishing. 

Bogen, KT; Cullen, AC; Frey, HC; Price, PS. (2009). 

Probabilistic exposure analysis for chemical 

risk characterization. Toxicol Sci 109: 4-17. 

http://dx.doi.org/10.1093/toxsci/kfp036. 

Bogen, KT; Spear, RC. (1987). Integrating 

uncertainty and interindividual variability in 

environmental risk assessment. Risk Anal 7: 

427-436. 

Bois, FY. (2010). Physiologically based modelling 

and prediction of drug interactions. Basic & 

Clinical Pharmacology & Toxicology Online 

Pharmacology Online 106: 154-161. 

http://dx.doi.org/10.1111/j.1742­

7843.2009.00488.x. 

Burin, GJ; Saunders, DR. (1999). Addressing human 

variability in risk assessment--the robustness 

of the intraspecies uncertainty factor. Regul 

Toxicol Pharmacol 30: 209-216. 

http://dx.doi.org/10.1006/rtph.1999.1351. 

Burmaster, DE. (1998a). A lognormal distribution for 

time spent showering. Risk Anal 18: 33-35. 

Burmaster, DE. (1998b). Lognormal distributions for 

skin area as a function of body weight. Risk 

Anal 18: 27-32. 

Burmaster, DE. (1998c). Lognormal distributions for 

Page Exposure Factors Handbook 

2-8 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 2—Variability and Uncertainty 

total water intake and tap water intake by 

pregnant and lactating women in the United 

States. Risk Anal 18: 215-219. 

Burmaster, DE; Crouch, EA. (1997). Lognormal 

distributions for body weight as a function 

of age for males and females in the United 

States, 1976-1980. Risk Anal 17: 499-505. 

Cox, DC; Baybutt, P. (1981). Methods for uncertainty 

analysis: A comparative survey. Risk Anal 1: 

251-258. http://dx.doi.org/10.1111/j.1539­

6924.1981.tb01425.x. 

Cox, LA. (1999). Internal dose, uncertainty analysis, 

and complexity of risk models. Environ Int 

25: 841-852. 

http://dx.doi.org/10.1016/S0160­

4120(99)00062-8. 

Fayerweather, WE; Collins, JJ; Schnatter, AR; 

Hearne, FT; Menning, RA; Reyner, DP. 

(1999). Quantifying uncertainty in a risk 

assessment using human data. Risk Anal 19: 

1077-1090. 

Frey, HC. (2002). Introduction to special section on 

sensitivity analysis and summary of 

NCSU/USDA workshop on sensitivity 

analysis. Risk Anal 22: 539-545. 

Frey, HC; Patil, SR. (2002). Identification and review 

of sensitivity analysis methods. Risk Anal 

22: 553-578. 

Gelman, A; Carlin, JB; Stern, HS; Rubin, DB. 

(2003). Bayesian data analysis (2nd ed.). 

Boca Raton, FL: Chapman and Hall/CRC 

Press. 

http://www.crcpress.com/product/isbn/9781 

584883883. 

Gilks, WR; Richardson, S; Spiegelhalter, DJ. (1995). 

Markov chain Monte Carlo in practice. Boca 

Raton, FL: Chapman & Hall/CRC Press. 

http://www.crcpress.com/product/isbn/9780 

412055515. 

Greenland,	 S. (2001). Sensitivity analysis, Monte 

Carlo risk analysis, and Bayesian 

uncertainty assessment. Risk Anal 21: 579­

583. 

Hattis, D. (1997). Human variability in susceptibility: 

How big, how often, for what responses to 

what agents? Environ Toxicol Pharmacol 4: 

195-208. 

Iman, RL; Helton, JC.	 (1988). An investigation of 

uncertainty and sensitivity analysis 

techniques for computer models. Risk Anal 

8: 71-90. 

Jacobs,	 HL; Kahn, HD; Stralka, KA; Phan, DB. 

(1998). Estimates of per capita fish 

consumption in the U.S. based on the 

continuing survey of food intake by 

individuals (CSFII). Risk Anal 18: 283-291. 

Jayjock, MA. (1997). Uncertainty analysis in the 

estimation of exposure. Am Ind Hyg Assoc J 

58: 380-382. 

http://dx.doi.org/10.1080/154281197910127 

66. 

Kahn, H. (2008). Letter from Henry Kahn to 

Jacqueline Moya, EPA, providing 

supplemental data to Estimated daily 

average per capita water ingestion by child 

and adult age categories based on USDA's 

1994-96 and 1998 continuing survey of food 

intakes by individuals (September 18, 2008). 

Available online at (accessed 

Kahn, H; Stralka, K. (2008). Estimates of Water 

Ingestion for Women in Pregnant, Lactating, 

and Non-Pregnant and Non-Lactating ChildBearing Age Groups Based on USDA's 

1994-96, 1998 Continuing Survey of Food 

Intake by Individuals. Hum Ecol Risk 

Assess 14: 1273-1290. 

http://dx.doi.org/10.1080/108070308024946 

18. 

Kahn, HD; Stralka, K. (2009). Estimated daily 

average per capita water ingestion by child 

and adult age categories based on USDA's 

1994-1996 and 1998 continuing survey of 

food intakes by individuals. J Expo Sci 

Environ Epidemiol 19: 396-404. 

http://dx.doi.org/10.1038/jes.2008.29. 

Kalberlah, F; Schneider, K; Schuhmacher-Wolz, U. 

(2003). Uncertainty in toxicological risk 

assessment for non-carcinogenic health 

effects. Regul Toxicol Pharmacol 37: 92­

104. 

Kelly, E; Campbell, K. (2000). Separating variability 

and uncertainty in environmental risk 

assessmentMaking choices. Hum Ecol Risk 

Assess 6: 1-13. 

http://dx.doi.org/10.1080/108070300911244 

19. 

Meek,	 M. (2001). Categorical default uncertainty 

factors-Interspecies variation and adequacy 

of database. Hum Ecol Risk Assess 7: 157­

163. 

Morgan, MG; Henrion, M; Small, M. (1990). 

Uncertainty: A guide to dealing with 

uncertainty in quantitative risk and policy 

analysis. Cambridge, UK: Cambridge 

University Press. 

Nayak, TK; Kundu, S. (2001). Calculating and 

describing uncertainty in risk assessment: 

the Bayesian approach. Hum Ecol Risk 

Assess 7: 307-328. 

Nicas, M; Jayjock, M. (2002). Uncertainty in 

Exposure Factors Handbook Page 

September 2011 2-9 
 

Exposure Factors Handbook 

Chapter 2—Variability and Uncertainty 

exposure estimates made by modeling 

versus monitoring. A I H A Journal 63: 275­

283. 

NRC (National Research Council). (1994). Science 

and judgment in risk assessment. 

Washington, DC: National Academy Press. 

http://www.nap.edu/openbook.php?isbn=03 

0904894X. 

NRC (National Research Council). (2009). Science 

and decisions: Advancing risk assessment. 

Washington, DC: National Academies Press. 

http://www.nap.edu/catalog/12209.html. 

Peretz, C; Goldberg, P; Kahan, E; Grady, S; Goren, 

A. (1997). The variability of exposure over 

time: A prospective longitudinal study. Ann 

Occup Hyg 41: 485-500. 

http://dx.doi.org/10.1016/S0003­

4878(97)00008-2. 

Price, PS; Keenan, RE; Schwab, B. (1999). Defining 

the interindividual (intraspecies) uncertainty 

factor. Hum Ecol Risk Assess 5: 1023-1033. 

http://dx.doi.org/10.1080/108070399912893 

10. 

Price, PS; Keenan, RE; Swartout, JC; Gillis, CA; 

Carlson-Lynch, H; Dourson, ML. (1997). An 

approach for modeling noncancer dose 

responses with an emphasis on uncertainty. 

Risk Anal 17: 427-437. 

Rai, S; Krewski, D; Bartlett, S. (1996). A general 

framework for the analysis of uncertainty 

and variability in risk assessment. Hum Ecol 

Risk Assess 2: 972-989. 

Rai, SN; Krewski, D. (1998). Uncertainty and 

variability analysis in multiplicative risk 

models. Risk Anal 18: 37-45. 

Refsgaard,	 JC; Van Der sluijs, JP; Højberg, AL; 

Vanrolleghem, PA. (2007). Uncertainty in 

the environmental modelling process A 

framework and guidance. Environ Modell 

Softw 22: 1543-1556. 

http://dx.doi.org/10.1016/j.envsoft.2007.02. 

004. 

Renwick, A. (1999). Subdivision of uncertainty 

factors to allow for toxicokinetics and 

toxicodynamics. Hum Ecol Risk Assess 5: 

1035-1050. 

Rish, WR. (1988). Approach to uncertainty in risk 

analysis. (ORNL/TM-10746). Oak Ridge, 

TN: Oak Ridge National Laboratory. 

Rish, WR; Marnicio, RJ. (1988). Review of studies 

related to uncertainty in risk analysis. 

(ORNL/TM 10776). Oak Ridge, TN: Oak 

Ridge National Laboratory. 

Robert, CP; Casella, G. (2004). Monte Carlo 

statistical methods. New York, NY: Springer. 

Robinson, RB; Hurst, BT. (1997). Statistical 

quantification of the sources of variance in 

uncertainty analyses. Risk Anal 17: 447-453. 

Saltelli, A. (2002). Sensitivity analysis for importance 

assessment. Risk Anal 22: 579-590. 

Saltelli, A; Annoni, P. (2010). How to avoid a 

perfunctory sensitivity analysis. Environ 

Modell Softw 25: 1508-1517. 

http://dx.doi.org/10.1016/j.envsoft.2010.04. 

012. 

Saltelli, A; Ratto, M; Andres, T; Campolongo, F; 

Cariboni, J; Gatelli, D; Saisana, M; 

Tarantola, S. (2008). Global sensitivity 

analysis: The primer. West Sussex, UK: John 

Wiley & Sons. 

Saltelli, A; Tarantola, S; Campolongo, F; Ratto, M. 

(2004). Sensitivity analysis in practice: A 

guide to assessing scientific models. West 

Sussex, UK: John Wiley & Sons. 

Seiler, FA. (1987). Error propagation for large errors. 

Risk Anal 7: 509-518. 

Semple, SE; Proud, LA; Cherrie, JW. (2003). Use of 

Monte Carlo simulation to investigate 

uncertainty in exposure modeling. Scand J 

Work Environ Health 29: 347-353. 

Shlyakhter, AI. (1994). An improved framework for 

uncertainty analysis: accounting for 

unsuspected errors. Risk Anal 14: 441-447. 

Simon, TW. (1997). Combining physiologically 

based pharmacokinetic modeling with 

Monte Carlo simulation to derive an acute 

inhalation guidance value for 

trichloroethylene. Regul Toxicol Pharmacol 

26: 257-270. 

http://dx.doi.org/10.1006/rtph.1997.1168. 

Slob,	 W; Pieters, MN. (1998). A probabilistic 

approach for deriving acceptable human 

intake limits and human health risks from 

toxicological studies: general framework. 

Risk Anal 18: 787-798. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1985). Methodology for characterization of 

uncertainty in exposure assessments. 

(EPA600885009). 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB85240455. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992). Guidelines for exposure assessment. 

(EPA/600/Z-92/001). Washington, DC: U.S. 

Environmental Protection Agency, Risk 

Assessment Forum.

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=15263. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1995). Guidance for risk characterization. 

Page Exposure Factors Handbook 

2-10 September 2011 
Exposure Factors Handbook 

Chapter 2—Variability and Uncertainty 

Washington, DC.

http://www.epa.gov/spc/pdfs/rcguide.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1997a). Guiding principles for Monte Carlo 

analysis. (EPA/630/R-97/001). Washington, 

DC. 

http://www.epa.gov/raf/publications/guiding 

-monte-carlo-analysis.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1997b). Policy for use of probabilistic 

analysis in risk assessment. Washington, 

DC. 

http://www.epa.gov/OSA/spc/pdfs/probpol.p 

df. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2001). Risk assessment guidance for 

superfund: Volume III - part A, process for 

conducting probabilistic risk assessment. 

(EPA 540-R-02-002). Washington, DC: U.S. 

Environmental Protection Agency, Office of 

Solid Waste and Emergency Response. 

http://www.epa.gov/oswer/riskassessment/ra 

gs3adt/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2002). Estimated per capita fish 

consumption in the United States. 

(EPA/821/C-02/003). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2004a). Estimated per capita water 

ingestion and body weight in the United 

States: An update. (EPA-822/R-00-001). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Water, Office 

of Science and Technology. 

http://water.epa.gov/action/advisories/drinki 

ng/upload/2005_05_06_criteria_drinking_pe 

rcapita_2004.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2004b). An examination of EPA risk 

assessment principles and practices. 

(EPA/100/B-04/001). Washington, DC: U.S. 

Environmental Protection Agency, Office of 

the Science Advisor. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2008). Uncertainty and variability in 

physiologically based pharmacokinetic 

models: Key issues and case studies [EPA 

Report]. (EPA/600/R-08/090). Washington, 

DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=198846. 

Wallace,	 L; Williams, R. (2005). Validation of a 

method for estimating long-term exposures 

based on short-term measurements. Risk 

Anal 25: 687-694. 

http://dx.doi.org/10.1111/j.1539­

6924.2005.00605.x. 

Weiss, B. (2001). A Web-based survey method for 

evaluating different components of 

uncertainty in relative health risk judgments. 

Neurotoxicology 22: 707-721. 

WHO (World Health Organization). (2006). Draft 

guidance on characterizing and 

communicating uncertainty in exposure 

assessment. Geneva, Switzerland. 

http://www.who.int/ipcs/methods/harmoniza 

tion/areas/exposure_assessment/en/index.ht 

ml. 

WHO	 (World Health Organization). (2008). 

Uncertainty and data quality in exposure 

assessment. Geneva.

http://www.who.int/ipcs/publications/metho 

ds/harmonization/exposure_assessment.pdf. 

Xue, J; Zartarian, VG; Ozkaynak, H; Dang, W; Glen, 

G; Smith, L; Stallings, C. (2006). A 

probabilistic arsenic exposure assessment 

for children who contact chromated copper 

arsenate (CCA)-treated playsets and decks, 

Part 2: Sensitivity and uncertainty analyses. 

Risk Anal 26: 533-541. 

http://dx.doi.org/10.1111/j.1539­

6924.2006.00748.x. 

Zheng, JY; Frey, HC. (2005). Quantitative analysis of 

variability and uncertainty with known 

measurement error: Methodology and case 

study. Risk Anal 25: 663-675. 

http://dx.doi.org/10.1111/j.1539­

6924.2005.00620.x. 

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Chapter 3—Ingestion of Water and Other Select Liquids 

3.	 INGESTION OF WATER AND OTHER 

SELECT LIQUIDS 

3.1. INTRODUCTION 

Water ingestion is another pathway of exposure 

to environmental chemicals. Contamination of water 

may occur at the water supply source (ground water 

or surface water); during treatment (for example, 

toxic by-products may be formed during 

chlorination); or post-treatment (such as leaching of 

lead or other materials from plumbing systems). 

People may be exposed to contaminants in water 

when consuming water directly as a beverage, 

indirectly from foods and drinks made with water, or 

incidentally while swimming. Estimating the 

magnitude of the potential dose of toxics from water 

ingestion requires information on the quantity of 

water consumed. The purpose of this section is to 

describe key and relevant published studies that 

provide information on water ingestion for various 

populations and to provide recommended ingestion 

rate values for use in exposure assessments. The 

studies described in this section provide information 

on ingestion of water consumed as a beverage, 

ingestion of other select liquids, and ingestion of 

water while swimming. Historically, the U.S. 

Environmental Protection Agency (EPA) has assumed 

a drinking water ingestion rate of 2 L/day for adults 

and 1 L/day for infants and children under 10 years 

of age (U.S. EPA, 2000). This rate includes water 

consumed in the form of juices and other beverages 

containing tap water. The National Research Council 

(NRC, 1977) estimated that daily consumption of 

water may vary with levels of physical activity and 

fluctuations in temperature and humidity. It is 

reasonable to assume that people engaging in 

physically-demanding activities or living in warmer 

regions may have higher levels of water ingestion. 

However, there is limited information on the effects 

of activity level and climatic conditions on water 

ingestion. 

The U.S. EPA selected the analysis by Kahn and 

Stralka (2009) and Kahn (2008) of the (USDA’s) 

1994–1996, 1998 Continuing Survey of Food Intake 

by Individuals (CSFII) as a key study of drinking 

water ingestion for the general population of children 

<3 years of age. U.S. EPA’s 2010 analysis of 

2003-2006 data from the National Health and 

Nutrition Examination Survey (NHANES) was 

selected as a key study of drinking water ingestion 

for the general population of individuals ≥3 years of 

age. Although NHANES 2003–2006 contains the 

most up-to-date information on water intake rates, 

estimates for children <3 years of age obtained from 

the NHANES survey are less reliable due to sample 

size limitations. Kahn and Stralka (2008) was 

selected as a key study of drinking water ingestion 

for pregnant and lactating women. Kahn and Stralka 

(2008) used data from U.S. Department of 

Agriculture’s (USDA’s) 1994–1996, 1998 Continuing 

Survey of Food Intake by Individuals (CSFII). The 

2010 U.S. EPA analysis of NHANES data and the 

analyses by Kahn (2008) and Kahn and Stralka 

(2009; 2008) generated ingestion rates for direct and 

indirect ingestion of water. Direct ingestion is defined 

as direct consumption of water as a beverage, while 

indirect ingestion includes water added during food 

preparation but not water intrinsic to purchased foods 

(i.e., water that is naturally contained in foods) (Kahn 

and Stralka, 2009; Kahn and Stralka, 2008). Data for 

consumption of water from various sources (i.e., the 

community water supply, bottled water, and other 

sources) are also presented. It is noted that the type of 

water people are drinking has changed in the last 

decade, as evidenced by the increase in bottled water 

consumption. However, the majority of the U.S. 

population consumes water from public (i.e., 

community) water distribution systems; about 15% of 

the U.S. population obtains their water from private 

(i.e., household) wells, cisterns, or springs (U.S. EPA, 

2002). Regardless of the source of the water, the 

physiological need for water should be the same 

among populations using community or private water 

systems. For the purposes of exposure assessments 

involving site-specific contaminated drinking water, 

ingestion rates based on the community supply are 

most appropriate. Given the assumption that bottled 

water, and purchased foods and beverages that 

contain water are widely distributed and less likely to 

contain source-specific water, the use of total water 

ingestion rates may overestimate the potential 

exposure to toxic substances present only in local 

water supplies; therefore, tap water ingestion of 

community water, rather than total water ingestion, is 

emphasized in this section. 

The key studies on water ingestion for the 

general population (CSFII and NHANES) and the 

population of pregnant/lactating women (CSFII) are 

both based on short-term survey data (2 days). 

Although short-term data may be suitable for 

obtaining mean or median ingestion values that are 

representative of both short- and long-term ingestion 

distributions, upper- and lower-percentile values may 

be different for short-term and long-term data. It 

should also be noted that most currently available 

water ingestion surveys are based on respondent 

recall. This may be a source of uncertainty in the 

estimated ingestion rates because of the subjective 

nature of this type of survey technique. Percentile 

distributions for water ingestion are presented in this 

Exposure Factors Handbook Page 

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Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

handbook, where sufficient data are available. Data 

are not provided for the location of water 

consumption (i.e., home, school, daycare center, etc.). 

Limited information was available regarding 

incidental ingestion of water while swimming. A 

recent pilot study (Dufour et al., 2006) has provided 

some quantitative experimental data on water 

ingestion among swimmers. These data are provided 

in this chapter. 

Section 3.2 provides the recommendations and 

confidence ratings for water ingestion among the 

general population and pregnant and lactating 

women, and among swimmers. Section 3.2.1 

provides the key studies for general water ingestion 

rates, Section 3.4.1 provides ingestion rates for 

pregnant and lactating women, and Section 3.6.1 

provides ingestion rates for swimming. For water 

ingestion at high activity levels or hot climates, no 

recommendations are provided, but Section 3.5 

includes relevant studies. Relevant studies on all 

subcategories of water ingestion are also presented to 

provide the reader with added perspective on the 

current state-of-knowledge pertaining to ingestion of 

water and select liquids. 

3.2. RECOMMENDATIONS 

3.2.1. Water Ingestion From Consumption of 

Water as a Beverage and From Food and 

Drink 

The recommended water ingestion from the 

consumption of water as a beverage and from foods 

and drinks are based on Kahn and Stralka (2009) and 

Kahn (2008) for children <3 years of age and on U.S. 

EPA’s 2010 analysis of NHANES data from 2003– 

2006 for individuals ≥3 years of age. Table 3-1 

presents a summary of the recommended values for 

direct and indirect ingestion of community water. Per 

capita mean and 95th percentile values range from 

184 mL/day to 1,046 mL/day and 837 mL/day to 

2,958 mL/day, respectively, depending on the age 

group. Consumer-only mean and 95th percentile 

values range from 308 mL/day to 1,288 mL/day and 

858 mL/day to 3,092 mL/day, respectively, 

depending on the age group. Per capita intake rates 

represent intake that has been averaged over the 

entire population (including those individuals that 

reported no intake). In general, per capita intake rates 

are appropriate for use in exposure assessments for 

which average daily dose estimates are of interest 

because they represent both individuals who drank 

water during the survey period and individuals who 

may drink water at some time but did not consume it 

during the survey period. Consumer-only intake rates 

represent the quantity of water consumed only by 

individuals who reported water intake during the 

survey period. Table 3-2 presents a characterization 

of the overall confidence in the accuracy and 

appropriateness of the recommendations for drinking 

water intake. 

3.2.2.	 Pregnant and Lactating Women 

Based upon the results of Kahn and Stralka 

(2008), per capita mean and 95th percentile values for 

ingestion of drinking water among pregnant women 

were 819 mL/day and 2,503 mL/day, respectively. 

The per capita mean and 95th percentile values for 

lactating women were 1,379 mL/day and 

3,434 mL/day, respectively. Table 3-3 presents a 

summary of the recommended values for water 

ingestion rates. Table 3-4 presents the confidence 

ratings for these recommendations. 

3.2.3.	 Water Ingestion While Swimming or 

Diving 

Based on the results of the Dufour et al. (2006) 

study, mean water ingestion rates of 49 mL/hour for 

children under 18 years of age and 21 mL/hour for 

adults are recommended for exposure scenarios 

involving swimming activities. Although these 

estimates were derived from swimming pool 

experiments, Dufour et al. (2006) noted that 

swimming behavior of recreational pool swimmers 

may be similar to freshwater swimmers. Estimates 

may be different for salt water swimmers and 

competitive swimmers. The recommended upper 

percentile water ingestion rate for swimming 

activities among children is based on the 

97th percentile value of 120 mL/hour 

(90 mL/0.75 hour) from Dufour et al. (2006). 

Because the data set for adults is limited, the 

maximum value observed in the Dufour et al. (2006) 

study is used as an upper percentile value for adults: 

71 mL/hour (53 mL/0.75 hour). Table 3-5 presents a 

summary of the recommended values for water 

ingestion rates. Table 3-6 presents the confidence 

ratings for these recommendations. Data on the 

amount of time spent swimming can be found in 

Chapter 16 (see Table 16-1) of this handbook. 

Page Exposure Factors Handbook 

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Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-1. Recommended Values for Drinking Water Ingestion Ratesa 

Age Group 

Mean 95th Percentile 

mL/day mL/kg-day mL/day mL/kg-day Multiple Percentiles 

Per Capitab 

Birth to <1 monthc 184 52 839d 232d 

See Table 3-7 and Table 3-11 

for children <3 years old and 

Table 3-23 and Table 3-28 for 

individuals >3 years old. 

1 to <3 monthsc 227 48 896d 205d 

3 to <6 monthsc 362 52 1,056 159 

6 to <12 monthsc 360 41 1,055 126 

1 to <2 yearsc 271 23 837 71 

2 to <3 yearsc 317 23 877 60 

3 to <6 years 327 18 959 51 

6 to <11 years 414 14 1,316 43 

11 to <16 years 520 10 1,821 32 

16 to <18 years 573 9 1,783 28 

18 to <21 years 681 9 2,368 35 

≥21 years 1,043 13 2,958 40 

>65 years 1,046 14 2,730 40 

All agese 869 14 2,717 42 

Consumers Onlyf 

Birth to <1 monthc 470d 137d 858d 238d 

See Table 3-15 and Table 3-19 

for children <3 years old and 

Table 3-33 and Table 3-38 for 

individuals >3 years old. 

1 to <3 monthsc 552 119 1,053d 285d 

3 to <6 monthsc 556 80 1,171d 173d 

6 to <12 monthsc 467 53 1,147 129 

1 to <2 yearsc 308 27 893 75 

2 to <3 yearsc 356 26 912 62 

3 to <6 years 382 21 999 52 

6 to <11 years 511 17 1,404 47 

11 to <16 years 637 12 1,976 35 

16 to <18 years 702 10 1,883 30 

18 to <21 years 816 11 2,818 36 

≥21 years 1,227 16 3,092 42 

>65 years 1,288 18 2,960 43 

All agese 1,033 16 2,881 44 

a Ingestion rates for combined direct and indirect water from community water supply. b Per capita intake rates are generated by averaging consumer-only intakes over the entire population (including 

those individuals that reported no intake). c Based on Kahn and Stralka (2009) and Kahn (2008). d Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation 

and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working 

Group Recommendations (NCHS, 1993). e Based on U.S. EPA analysis of NHANES 2003–2006 data. f Consumer-only intake represents the quantity of water consumed only by individuals that reported consuming 

water during the survey period. 

Source: Kahn and Stralka (2009); Kahn (2008); U.S. EPA analysis of NHANES 2003–2006 data. 

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Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-2. Confidence in Recommendations for Drinking Water Ingestion Rates 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The survey methodology and data analysis were adequate. 

The surveys sampled approximately 20,000 individuals 

(CSFII) and 18,000 (NHANES) individuals; sample size 

varied with age. 

No physical measurements were taken. The method relied 

on recent recall of standardized volumes of drinking water 

containers. 

Medium to High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key studies were directly relevant to water ingestion. 

The data were demographically representative (based on 

stratified random sample). Sample sizes for some age 

groups were limited. 

Data were collected between 1994 and 1998 for CSFII 

and between 2003 and 2006 for NHANES. 

Data were collected for 2 non-consecutive days. 

However, long-term variability may be small. Use of a 

short-term average as a chronic ingestion measure can be 

assumed. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The CSFII and NHANES data are publicly available. 

The methodology was clearly presented; enough 

information was included to reproduce the results. 

CSFII and NHANES data collection follow strict QA/QC 

procedures. Quality control of the secondary data analysis 

was not well described. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were developed. 

Except for data collection based on recall, sources of 

uncertainty were minimal. 

High 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The CSFII and NHANES surveys received a high level of 

peer review. The CSFII data were published in the peerreviewed literature. The U.S. EPA analysis of NHANES 

has not been peer-reviewed outside the Agency. 

There were two key studies for drinking water ingestion 

among the general population. 

Medium 

Overall Rating Medium to High, 

Low for footnote 

“d” on Table 3-1 

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c 

Table 3-3. Recommended Values for Water Ingestion Rates of Community Water 

for Pregnant and Lactating Womena 

Per Capitab 

Mean 95th Percentile 

Group mL/day mL/kg-day mL/day mL/kg-day 

Pregnant women 819c 13c 2,503c 43c 

Lactating women 1,379c 21c 3,434c 55c 

Consumers Onlyd 

Mean 95th Percentile 

Group mL/day mL/kg-day mL/day mL/kg-day 

Pregnant women 872c 14c 2,589c 43c 

Lactating women 1,665c 26c 3,588c 55c 

a	 Ingestion rates for combined direct and indirect water from community water 

supply. b Per capita intake rates are generated by averaging consumer-only intakes over 

the entire population (including those individuals that reported no intake). 

Estimates are less statistically reliable based on guidance published in the Joint Policy 

on Variance Estimation and Statistical Reporting Standards on NHANES III and 

CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 

1993). d	 Consumer-only intake represents the quantity of water consumed only by 

individuals that reported consuming water during the survey period. 

Source:	 Kahn and Stralka (2008). 

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Chapter 3—Ingestion of Water and Other Select Liquids 

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Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-4. Confidence in Recommendations for Water Ingestion for Pregnant/Lactating Women 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The survey methodology and data analysis were 

adequate. The sample size was small, approximately 

99 pregnant and lactating women. 

No physical measurements were taken. The method 

relied on recent recall of standardized volumes of 

drinking water containers. 

Low 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key study was directly relevant to water ingestion. 

The data were demographically representative (based 

on stratified random sample). 

Data were collected between 1994 and 1998. 

Data were collected for 2 non-consecutive days. 

However, long-term variability may be small. Use of a 

short-term average as a chronic ingestion measure can 

be assumed. 

Low to Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The CSFII data are publicly available. The Kahn and 

Stralka (2008) analysis of the CSFII 1994–1996, 1998 

data was published in a peer-reviewed journal. 

The methodology was clearly presented; enough 

information was included to reproduce the results. 

Quality assurance of the CSFII data was good; quality 

control of the secondary data analysis was not well 

described. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were given in a separate document 

(Kahn, 2008). 

Except for data collection based on recall, sources of 

uncertainty were minimal. 

Low 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The USDA CSFII survey received a high level of peer 

review. The Kahn and Stralka (2008) study was 

published in a peer-reviewed journal. 

There was one key study for pregnant/lactating 

women water ingestion. 

Medium 

Overall Rating Low 

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 c 

Table 3-5. Recommended Values for Water Ingestion
 

While Swimming
 

Mean Upper Percentile Age Group mL/eventa mL/hour mL/eventa mL/hour 

Children 37 49 90b 120b 

Adults 16 21 53c 71c 

a Participants swam for 45 minutes. b 97th percentile. 

Based on maximum value. 

Source:	 Dufour et al. (2006). 

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Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-6. Confidence in Recommendations for Water Ingestion While Swimming 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The approach appears to be appropriate given that 

cyanuric acid (a tracer used in treated pool water) is not 

metabolized, but the sample size was small (41 children 

and 12 adults). The Dufour et al. (2006) study analyzed 

primary data on water ingestion during swimming. 

Data were collected over a period of 45 minutes; this may 

not accurately reflect the time spent by a recreational 

swimmer. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key study was directly relevant to water ingestion 

while swimming. 

The sample was not representative of the U.S. population. 

Data cannot be divided into by age categories. 

It appears that the study was conducted in 2005. 

Data were collected over a period of 45 minutes. 

Low to Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The Dufour et al. (2006) study was published in a peerreviewed journal. 

The methodology was clearly presented; enough 

information was included to reproduce the results. 

Quality assurance methods were not described in the 

study. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were not available. Data were not 

broken out by age groups. 

There were multiple sources of uncertainty (e.g., sample 

population may not reflect swimming practices for all 

swimmers, rates based on swimming duration of 

45 minutes, differences by age group not defined). 

Low 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

Dufour et al. (2006) was published in a peer-reviewed 

journal. 

There was one key study for ingestion of water when 

swimming. 

Medium 

Overall Rating Low 

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Chapter 3—Ingestion of Water and Other Select Liquids 

3.3.	 DRINKING WATER INGESTION 

STUDIES 

3.3.1. Key Drinking Water Ingestion Study 

3.3.1.1.	 Kahn and Stralka (2009)—Estimated 

Daily Average Per Capita Water 

Ingestion by Child and Adult Age 

Categories Based on USDA’s 1994–1996 

and 1998 Continuing Survey of Food 

Intakes by Individuals and Supplemental 

Data, Kahn (2008) 

Kahn and Stralka (2009) analyzed the combined 

1994–1996 and 1998 CSFII data sets to examine 

water ingestion rates of more than 20,000 individuals 

surveyed, including approximately 10,000 under age 

21 and 9,000 under age 11. USDA surveyed 

households in the United States and District of 

Columbia and collected food and beverage recall data 

as part of the CSFII (USDA, 2000). Data were 

collected by an in-home interviewer. The Day 2 

interview was conducted 3 to 10 days later and on a 

different day of the week. Each individual in the 

survey was assigned a sample weight based on his or 

her demographic data. These weights were taken into 

account when calculating mean and percentile water 

ingestion rates from various sources. Kahn and 

Stralka (2009) derived mean and percentile estimates 

of daily average water ingestion for the following age 

categories: <1 month, 1 to <3 months, 3 to 

<6 months, 6 to <12 months, 1 to <2 years of age, 2 

to <3 years, 3 to <6 years, 6 to <11 years, 11 to 

<16 years, 16 to <18 years, 18 to <21 years of age, 

21 years and older, 65 years and older, and all ages. 

The increased sample size for children younger than 

11 years of age (from 4,339 in the initial 1994–1996 

survey to 9,643 children in the combined 1994–1996, 

1998 survey) enabled water ingestion estimates to be 

categorized into the finer age categories 

recommended by U.S. EPA (2005). Consumer-only 

and per capita water ingestion estimates were 

reported in the Kahn and Stralka (2009) study for two 

water source categories: all sources and community 

water. “All sources” included water from all supply 

sources such as community water supply (i.e., tap 

water), bottled water, other sources, and missing 

sources. “Community water” included tap water from 

a community or municipal water supply. Other 

sources included wells, springs, and cisterns; missing 

sources represented water sources that the survey 

respondent was unable to identify. The water 

ingestion estimates included both water ingested 

directly as a beverage (direct water) and water added 

to foods and beverages during final preparation at 

home or by local food service establishments such as 

school cafeterias and restaurants (indirect water). 

Commercial water added by a manufacturer (i.e., 

water contained in soda or beer) and intrinsic water in 

foods and liquids (i.e., milk and natural undiluted 

juice) were not included in the estimates. Kahn and 

Stralka (2009) only reported the mean and 90th and 

95th percentile estimates of per capita and 

consumer-only ingestion. The full distributions of 

ingestion estimates were provided by the author 

(Kahn, 2008). Table 3-7 to Table 3-22 presents full 

distributions for the various water source categories 

(community water, bottled water, other sources, and 

all sources). Table 3-7 to Table 3-10 provide per 

capita ingestion estimates of total water (combined 

direct and indirect water) in mL/day for the various 

water source categories (i.e., community, bottled, 

other, and all sources). Table 3-11 to Table 3-14 

present the same information as Table 3-7 to 

Table 3-10 but in units of mL/kg-day. Table 3-15 to 

Table 3-18 provide consumer-only combined direct 

and indirect water ingestion estimates in mL/day for 

the various source categories. Table 3-19 to 

Table 3-22 present the same information as Table 

3-15 to Table 3-18 but in units of mL/kg-day. 

Estimates that do not meet the minimum sample size 

requirements as described in the Joint Policy on 

Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII 

Reports: NHIS/NCHS Analytical Working Group 

Recommendations (NCHS, 1993) are flagged in the 

tables. 

The CSFII 1994–1996, 1998 data have both 

strengths and limitations with regard to estimating 

water ingestion. These are discussed in detail in 

U.S. EPA (2004) and Kahn and Stralka (2009). The 

principal advantages of this survey are that (1) it was 

designed to be representative of the United States 

population, including children and low income 

groups, (2) sample weights were provided that 

facilitated proper analysis of the data and accounted 

for non-response; and (3) the number of individuals 

sampled (more than 20,000) is sufficient to allow 

categorization within narrowly defined age 

categories. One limitation of this survey is that data 

were collected for only 2 days. As discussed in 

Section 3.3.1.2 with regard to U.S. EPA’s analysis of 

NHANES data, short-term data may not accurately 

reflect long-term intake patterns, especially at the 

extremes (i.e., tails) of the distribution of water 

intake. This study is considered key because the 

sample size for children less than 3 years of age are 

larger than in the most up-to-date information from 

NHANES 2003–2006 (see Section 3.3.1.2). 

Therefore, recommendations for these age groups are 

based on this analysis. 

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Chapter 3—Ingestion of Water and Other Select Liquids 

3.3.1.2.	 U.S. EPA Analysis of NHANES 2003– 

2006 Data 

In 2010, U.S. EPA analyzed the combined 

2003-2004 and 2005–2006 NHANES data sets to 

examine water ingestion rates for the general 

population. The 2003–2006 data set included 

information on more than 18,000 individuals 

surveyed, including approximately 10,000 under age 

21 and 5,000 under age 11. The U.S. Centers for 

Disease Control and Prevention surveyed households 

across the United States and collected food and 

beverage recall data as part of the NHANES. The 

first dietary recall interview was conducted in-person 

in a Mobile Examination Center, and the second was 

collected by telephone 3 to 10 days later on a 

different day of the week. Each individual in the 

survey was assigned a sample weight based on his or 

her demographic data. These weights were taken into 

account when calculating mean and percentile water 

ingestion rates from various sources. 

In 2010, U.S. EPA, Office of Pesticide Programs 

used NHANES 2003–2006 data to update the Food 

Commodity Intake Database (FCID) that was 

developed in earlier analyses of data from the 

USDA’s CSFII (U.S. EPA, 2000; USDA, 2000). In 

FCID, NHANES data on the foods people reported 

eating were converted to the quantities of agricultural 

commodities eaten, including water that was added in 

the preparation of foods and beverages. FCID was 

used in the U.S. EPA analysis to derive estimates of 

water that was ingested from the consumption of 

foods and beverages. 

U.S. EPA derived mean and percentile estimates 

of daily average water ingestion for the following age 

categories: Birth to <1 month, 1 to <3 months, 3 to 

<6 months, 6 to <12 months, 1 to <2 years of age, 

2 to <3 years, 3 to <6 years, 6 to <11 years, 11 to 

<16 years, 16 to <18 years, and 18 to <21 years of 

age, 21 years and older, 65 years and older, and all 

ages. 

Consumer-only and per capita water ingestion 

estimates were generated for four water source 

categories: community water, bottled water, other 

sources, and all sources. Consumer-only intake 

represents the quantity of water consumed by 

individuals during the survey period. These data are 

generated by averaging intake across only the 

individuals in the survey who reported consumption 

of water. Per capita intake rates are generated by 

averaging consumer-only intakes over the entire 

population (including those individuals that reported 

no intake). In general, per capita intake rates are 

appropriate for use in exposure assessments for 

which average dose estimates are of interest because 

they represent both individuals who drank water 

during the survey period and individuals who may 

drink water at some time but did not consume it 

during the survey period. “All sources” included 

water from all supply sources such as community 

water supply (i.e., tap water), bottled water, other 

sources, and missing/unknown sources. “Community 

water” included tap water from a community or 

municipal water supply. “Other sources” included 

wells, springs, cisterns, other non-specified sources, 

and missing/unknown sources that the survey 

respondent was unable to identify. The water 

ingestion estimates included both water ingested 

directly as a beverage (direct water) and water added 

to foods and beverages during final preparation at 

home or by local food service establishments such as 

school cafeterias and restaurants (indirect water). 

Commercial water added by a manufacturer (i.e., 

water contained in soda or beer) and intrinsic water in 

foods and liquids (i.e., milk and natural undiluted 

juice) were not included in the estimates. NHANES 

water consumption respondent data were averaged 

over both days of dietary data when they were 

available; otherwise, 1-day data were used. Intake 

rate distributions were provided in units of mL/day 

and mL/kg-day. The body weights of survey 

participants were used in developing intake rate 

estimates in units of mL/kg-day. 

Table 3-23 to Table 3-42 present full 

distributions for the various water source categories 

(community water, bottled water, other sources, and 

all sources). Table 3-23 to Table 3-26 provide per 

capita ingestion estimates of total water (combined 

direct and indirect water) in mL/day for the various 

water source categories (i.e., community, bottled, 

other, and all sources). Table 3-27 presents the 90% 

confidence intervals (CIs) around the estimated 

means and the 90% bootstrap intervals (BIs) around 

the 90th and 95th percentiles of total water ingestion 

from all water sources. Table 3-28 to Table 3-32 

present the same information as Table 3-23 to 

Table 3-27 but in units of mL/kg-day. Table 3-33 to 

Table 3-36 provide consumer-only combined direct 

and indirect water ingestion estimates in mL/day for 

the various source categories. Table 3-37 presents 

confidence and bootstrap intervals for total water 

ingestion estimates by consumers only from all 

sources. Table 3-38 to Table 3-42 present the same 

information as Table 3-33 to Table 3-37 but in units 

of mL/kg-day. Estimates that do not meet the 

minimum sample size as described in the Joint Policy 

on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII 

Reports: NHIS/NCHS Analytical Working Group 

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Recommendations (NCHS, 1993), are flagged in the 

tables. The design effect used to determine the 

minimum required sample size was domain specific 

(i.e., calculated separately for various age groups). 

The data show that the total quantity of water 

ingested from all sources per unit mass of body 

weight was at a maximum in the first half year of life 

and decreased with increasing age. When indexed to 

body weight, the per capita ingestion rate of water 

from all sources combined for children under 

6 months of age was approximately 2.5 times higher 

than that of adults ≥21 years (see Table 3-31), and 

consumers younger than 6 months of age ingested 

approximately 3.5 times the amount of water (all 

sources combined) as adults (see Table 3-41). The 

pattern of decreasing water ingestion per unit of body 

weight was also observed in consumer-only estimates 

of community water (see Table 3-38), and other 

sources (see Table 3-40). However, this trend was not 

observed in per capita estimates of community water, 

bottled water, and other sources due to the lack of 

available responses under these age and water source 

categories. 

It should be noted that per capita estimates of 

water intake from all sources using the NHANES 

2003–2006 data are higher than estimates derived 

previously from CSFII 1994–1996, 1998 for adults 

(see Section 3.3.1.1). Among adults, total per-capita 

water consumption increased by 234 mL, or 16%. 

Per-capita bottled water consumption among adults 

nearly doubled, from 189 to 375 mL/day. Among 

infants, there appear to be erratic changes in water 

consumption patterns. In particular, ingestion rate 

estimates of bottled water for children <12 months 

old are considerably less when compared to values 

obtained from CSFII. This is due to the fact that 

NHANES does not allow for the allocation of any 

bottled water consumed indirectly in the preparation 

of foods and beverages. This may have an impact on 

the bottled water consumption for infants whose 

formula is prepared with bottled water. Among older 

children and adolescents, overall water consumption 

increased by 0% to 10%, and bottled water 

consumption increased 25% to 211%. Almost none of 

the NHANES—CSFII differences are statistically 

significant, except for all adults and all respondents, 

which have very large sample sizes. 

The advantages of U.S. EPA’s analysis of the 

2003–2006 NHANES surveys are (1) that the surveys 

were designed to obtain statistically valid sample of 

the civilian non-institutionalized U.S. population 

(i.e., the sampling frame was organized using 2000 

U.S. population census estimates); (2) NHANES 

oversampled low income persons, adolescents 

12-19 years, persons 60 years and older, Blacks, and 

Mexican Americans; (3) several sets of sampling 

weights were available for use with the intake data to 

facilitate proper analysis of the data; (4) the sample 

size was sufficient to allow categorization within 

narrowly defined age categories, and the large sample 

provided useful information on the overall 

distribution of ingestion by the population and should 

adequately reflect the range among respondent 

variability; (5) the survey was conducted over 

2 non-consecutive days, which improved the variance 

over consecutive days of consumption; and (6) the 

most current data set was used. One limitation of the 

data is that the data were collected over only 2 days 

and do not necessarily represent “usual” intake. 

“Usual dietary intake” refers to the long-term average 

of daily intakes by an individual. Thus, water 

ingestion estimates based on short-term data may 

differ from long-term rates, especially at the tails of 

the distribution. There are, however, several 

limitations associated with these data. Water intake 

estimates for children under 3 years of age are less 

statistically reliable due to sample size. In addition, 

NHANES does not allow for the allocation of 

indirect water intake in the estimation of bottled 

water consumption. Another limitation of these data 

is that the survey design, while being well-tailored 

for the overall population of the United States and 

conducted throughout the year to account for 

seasonal variation, is of limited utility for assessing 

small and potentially at-risk populations based on 

ethnicity, medical status, geography/climate, or other 

factors such as activity level. 

3.3.2.	 Relevant Drinking Water Ingestion 

Studies 

3.3.2.1.	 Wolf (1958)—Body Water Content 

Wolf (1958) provided information on the water 

content of human bodies. Wolf (1958) stated that a 

newborn baby is about 77% water while an adult 

male is about 60% water by weight. An adult male 

gains and loses about 2,750 mL of water each day. 

Water intake in dissimilar mammals varies according 

to 0.88 power of body weight. 

3.3.2.2.	 National Research Council (1977)— 

Drinking Water and Health 

NRC (1977) calculated the average per capita 

water (liquid) consumption per day to be 1.63 L. This 

figure was based on a survey of the following 

literature sources: Starling (1941); Bourne and 

Kidder (1953); Walker et al. (1957); Wolf (1958); 

Guyton (1968); McNall and Schlegel (1968); Randall 

(1973); NRC (1974); and Pike and Brown (1975), as 

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cited in NRC (1977). Although the calculated average 

intake rate was 1.63 L/day, NRC (1977) adopted a 

larger rate (2 L/day) to represent the intake of the 

majority of water consumers. This value is relatively 

consistent with the total tap water intakes rate 

estimated from the key study presented previously. 

However, the use of the term "liquid" was not clearly 

defined in this study, and it is not known whether the 

populations surveyed are representative of the adult 

U.S. population. Consequently, the results of this 

study are of limited use in recommending total tap 

water intake rates, and this study is not considered a 

key study. 

3.3.2.3.	 Hopkins and Ellis (1980)—Drinking 

Water Consumption in Great Britain 

A study conducted in Great Britain over a 

6-week period during September and October 1978, 

estimated the drinking water consumption rates of 

3,564 individuals from 1,320 households in England, 

Scotland, and Wales (Hopkins and Ellis, 1980). The 

participants were selected randomly and were asked 

to complete a questionnaire and a diary indicating the 

type and quantity of beverages consumed over a 

1-week period. Total liquid intake included total tap 

water taken at home and away from home; purchased 

alcoholic beverages; and non-tap water-based drinks. 

Total tap water included water content of tea, coffee, 

and other hot water drinks; homemade alcoholic 

beverages; and tap water consumed directly as a 

beverage. Table 3-43 presents the assumed tap water 

contents for these beverages. Based on responses 

from 3,564 participants, the mean intake rates and 

frequency distribution data for various beverage 

categories were estimated by Hopkins and Ellis 

(1980). Table 3-44 lists these data. The mean per 

capita total liquid intake rate for all individuals 

surveyed was 1.59 L/day, and the mean per capita 

total tap water intake rate was 0.96 L/day, with a 

90th percentile value of about 1.57 L/day. Liquid 

intake rates were also estimated for males and 

females in various age groups. Table 3-45 

summarizes the total liquid and total tap water intake 

rates for 1,758 males and 1,800 females grouped into 

six age categories (Hopkins and Ellis, 1980). The 

mean and 90th percentile total tap water intake values 

for adults over age 18 years are, respectively, 

1.07 L/day and 1.87 L/day, as determined by pooling 

data for males and females for the three adult age 

ranges in Table 3-45. This calculation assumes, as 

does Table 3-44 and Table 3-45, that the underlying 

distribution is normal and not lognormal. 

The advantage of these data is that the responses 

were not generated on a recall basis but by recording 

daily intake in diaries. The latter approach may result 

in more accurate responses being generated. Diaries 

were maintained for 1 week, which is longer than 

other surveys (e.g., CSFII). The use of total liquid 

and total tap water was well defined in this study. 

Also, these data were based on the population of 

Great Britain and not the United States. Drinking 

patterns may differ among these populations as a 

result of varying weather conditions and 

socioeconomic factors. For these reasons, this study 

is not considered a key study in this document. 

3.3.2.4.	 Canadian Ministry of National Health 

and Welfare (1981)—Tap Water 

Consumption in Canada 

In a study conducted by the Canadian Ministry 

of National Health and Welfare, 970 individuals from 

295 households were surveyed to determine the per 

capita total tap water intake rates for various age/sex 

groups during winter and summer seasons (Canadian 

Ministry of National Health and Welfare, 1981). 

Intake rate was also evaluated as a function of 

physical activity. The population that was surveyed 

matched the Canadian 1976 census with respect to 

the proportion in different age, regional, community 

size, and dwelling type groups. Participants 

monitored water intake for a 2-day period 

(1 weekday, and 1 weekend day) in both late summer 

of 1977 and winter of 1978. All 970 individuals 

participated in both the summer and winter surveys. 

The amount of tap water consumed was estimated 

based on the respondents' identification of the type 

and size of beverage container used, compared to 

standard-sized vessels. The survey questionnaires 

included a pictorial guide to help participants in 

classifying the sizes of the vessels. For example, a 

small glass of water was assumed to be equivalent to 

4.0 ounces of water, and a large glass was assumed to 

contain 9.0 ounces of water. The study also accounted 

for water derived from ice cubes and popsicles, and 

water in soups, infant formula, and juices. The survey 

did not attempt to differentiate between tap water 

consumed at home and tap water consumed away 

from home. The survey also did not attempt to 

estimate intake rates for fluids other than tap water. 

Consequently, no intake rates for total fluids were 

reported. 

Table 3-46 presents daily consumption 

distribution patterns for various age groups. For 

adults (over 18 years of age) only, the average total 

tap water intake rate was 1.38 L/day, and the 

90th percentile rate was 2.41 L/day as determined by 

graphical interpolation. These data follow a 

lognormal distribution. Table 3-47 presents the intake 

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Chapter 3—Ingestion of Water and Other Select Liquids 

data for males, females, and both sexes combined as 

a function of age and expressed in units of mL/kg 

body weight. The tap water survey did not include 

body weights of the participants, but the body-weight 

information was taken from a Canadian health survey 

dated 1981; it averaged 65.1 kg for males and 55.6 kg 

for females. Table 3-48 presents intake rates for 

specific age groups and seasons. The average daily 

total tap water intake rate for all ages and seasons 

combined was 1.34 L/day, and the 90th percentile rate 

was 2.36 L/day. The summer intake rates are nearly 

the same as the winter intake rates. The authors 

speculate that the reason for the small seasonal 

variation is that in Canada, even in the summer, the 

ambient temperature seldom exceeded 20°C, and 

marked increase in water consumption with high 

activity levels has been observed in other studies only 

when the ambient temperature has been higher than 

20°C. Table 3-49 presents average daily total tap 

water intake rates as a function of the level of 

physical activity, as estimated subjectively. Table 

3-50 presents the amounts of tap water consumed that 

are derived from various foods and beverages. Note 

that the consumption of direct “raw” tap water is 

almost constant across all age groups from schoolage children through the oldest ages. The increase in 

total tap water consumption beyond school age is due 

to coffee and tea consumption. 

This survey may be more representative of total 

tap water consumption than some other less 

comprehensive surveys because it included data for 

some tap water-containing items not covered by other 

studies (i.e., ice cubes, popsicles, and infant formula). 

One potential source of error in the study is that 

estimated intake rates were based on identification of 

standard vessel sizes; the accuracy of this type of 

survey data is not known. The cooler climate of 

Canada may have reduced the importance of large tap 

water intakes resulting from high activity levels, 

therefore making the study less applicable to the 

United States. The authors were not able to explain 

the surprisingly large variations between regional tap 

water intakes; the largest regional difference was 

between Ontario (1.18 L/day) and Quebec 

(1.55 L/day). 

3.3.2.5.	 Gillies and Paulin (1983)—Variability of 

Mineral Intakes From Drinking Water 

Gillies and Paulin (1983) conducted a study to 

evaluate variability of mineral intake from drinking 

water. A study population of 109 adults (75 females; 

34 males) ranging in age from 16 to 80 years (mean 

age = 44 years) in New Zealand was asked to collect 

duplicate samples of water consumed directly from 

the tap or used in beverage preparation during a 

24-hour period. Participants were asked to collect the 

samples on a day when all of the water consumed 

would be from their own home. Individuals were 

selected based on their willingness to participate and 

their ability to comprehend the collection procedures. 

The mean total tap water intake rate for this 

population was 1.25 (±0.39) L/day, and the 

90th percentile rate was 1.90 L/day. The median total 

tap water intake rate (1.26 L/day) was very similar to 

the mean intake rate. The reported range was 0.26 to 

2.80 L/day. 

The advantage of these data is that they were 

generated using duplicate sampling techniques. 

Because this approach is more objective than recall 

methods, it may result in more accurate responses. 

However, these data are based on a short-term survey 

that may not be representative of long-term behavior, 

the population surveyed is small, and the procedures 

for selecting the survey population were not designed 

to be representative of the New Zealand population, 

and the results may not be applicable to the United 

States. For these reasons, the study is not regarded as 

a key study in this document. 

3.3.2.6.	 Pennington (1983)—Revision of the 

Total Diet Study Food List and Diets 

Based on data from the U.S. Food and Drug 

Administration's Total Diet Study, Pennington (1983) 

reported average intake rates for various foods and 

beverages for five age groups of the population. The 

Total Diet Study is conducted annually to monitor the 

nutrient and contaminant content of the U.S. food 

supply and to evaluate trends in consumption. 

Representative diets were developed based on 

24-hour recall and 2-day diary data from the 

1977-1978 USDA Nationwide Food Consumption 

Survey (NFCS) and 24-hour recall data from the 

Second National Health and Nutrition Examination 

Survey (NHANES II). The numbers of participants in 

NFCS and NHANES II were approximately 30,000 

and 20,000, respectively. The diets were developed to 

"approximate 90% or more of the weight of the foods 

usually consumed" (Pennington, 1983). The source of 

water (bottled water as distinguished from tap water) 

was not stated in the Pennington study. For the 

purposes of this report, the consumption rates for the 

food categories defined by Pennington (1983) were 

used to calculate total fluid and total water intake 

rates for five age groups. Total water includes water, 

tea, coffee, soft drinks, and soups and frozen juices 

that are reconstituted with water. Reconstituted soups 

were assumed to be composed of 50% water, and 

juices were assumed to contain 75% water. Total 

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fluids include total water in addition to milk, 

ready-to-use infant formula, milk-based soups, 

carbonated soft drinks, alcoholic beverages, and 

canned fruit juices. Table 3-51 presents these intake 

rates. Based on the average intake rates for total 

water for the two adult age groups, 1.04 and 

1.26 L/day, the average adult intake rate is about 

1.15 L/day. These rates should be more representative 

of the amount of source-specific water consumed 

than are total fluid intake rates. Because this study 

was designed to measure food intake, and it used 

both USDA 1978 data and NHANES II data, there 

was not necessarily a systematic attempt to define tap 

water intake per se, as distinguished from bottled 

water. For this reason, it is not considered a key tap 

water study in this document. 

3.3.2.7.	 U.S. EPA (1984)—An Estimation of the 

Daily Average Food Intake by Age and 

Sex for Use in Assessing the 

Radionuclide Intake of the General 

Population 

Using data collected by USDA in the 1977–1978 

NFCS, U.S. EPA (1984) determined daily food and 

beverage intake levels by age to be used in assessing 

radionuclide intake through food consumption. Tap 

water, water-based drinks, and soups were identified 

subcategories of the total beverage category. Table 

3-52 presents daily intake rates for tap water, waterbased drinks, soup, and total beverages. As seen in 

Table 3-52, mean tap water intake for different adult 

age groups (age 20 years and older) ranged from 0.62 

to 0.76 L/day, water-based drinks intake ranged from 

0.34 to 0.69 L/day, soup intake ranged from 0.04 to 

0.06 L/day, and mean total beverage intake levels 

ranged from 1.48 to 1.73 L/day. Total tap water 

intake rates were estimated by combining the average 

daily intakes of tap water, water-based drinks, and 

soups for each age group. For adults (ages 20 years 

and older), mean total tap water intake rates range 

from 1.04 to 1.47 L/day, and for children (ages <1 to 

19 years), mean intake rates range from 0.19 to 0.90 

L/day. The total tap water intake rates, derived by 

combining data on tap water, water-based drinks, and 

soup should be more representative of source-specific 

drinking water intake than the total beverage intake 

rates reported in this study. The chief limitation of the 

study is that the data were collected in 1978 and do 

not reflect the expected increase in the U.S. 

consumption of soft drinks and bottled water or 

changes in the diet within the last three decades. 

Since the data were collected for only a 3-day period, 

the extrapolation to chronic intake is uncertain. Also, 

these intake rates do not include reconstituted infant 

formula. 

3.3.2.8.	 Cantor et al. (1987)—Bladder Cancer, 

Drinking Water Source, and Tap Water 

Consumption 

The National Cancer Institute, in a 

population-based, case control study investigating the 

possible relationship between bladder cancer and 

drinking water, interviewed approximately 

8,000 adult White individuals, 21 to 84 years of age 

(2,805 cases and 5,258 controls) in their homes, using 

a standardized questionnaire (Cantor et al., 1987). 

The cases and controls resided in one of five 

metropolitan areas (Atlanta, Detroit, New Orleans, 

San Francisco, and Seattle) and five States 

(Connecticut, Iowa, New Jersey, New Mexico, and 

Utah). The individuals interviewed were asked to 

recall the level of intake of tap water and other 

beverages in a typical week during the winter prior to 

the interview. Total beverage intake was divided into 

the following two components: (1) beverages derived 

from tap water; and (2) beverages from other sources. 

Tap water used in cooking foods and in ice cubes was 

apparently not considered. Participants also supplied 

information on the primary source of the water 

consumed (i.e., private well, community supply, 

bottled water, etc.). The control population was 

randomly selected from the general population and 

frequency matched to the bladder cancer case 

population in terms of age, sex, and geographic 

location of residence. The case population consisted 

of Whites only and had no people under the age of 

21 years; 57% were over the age of 65 years. The 

fluid intake rates for the bladder cancer cases were 

not used because their participation in the study was 

based on selection factors that could bias the intake 

estimates for the general population. Based on 

responses from 5,258 White controls (3,892 males; 

1,366 females), average tap water intake rates for a 

"typical" week were compiled by sex, age group, and 

geographic region. Table 3-53 lists these rates. The 

average total fluid intake rate was 2.01 L/day for men 

of which 70% (1.4 L/day) was derived from tap 

water, and 1.72 L/day for women of which 79% 

(1.35 L/day) was derived from tap water. Table 3-54 

presents frequency distribution data for the 

5,228 controls, for which the authors had information 

on both tap water consumption and cigarette smoking 

habits. These data follow a lognormal distribution 

having an average value of 1.30 L/day and an upper 

90th percentile value of approximately 2.40 L/day. 

These values were determined by graphically 

interpolating the data of Table 3-54 after plotting it 

on log probability graph paper. These values 

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represent the usual level of intake for this population 

of adults in the winter. Limitations associated with 

this data set are that the population surveyed was 

older than the general population and consisted 

exclusively of Whites. Also, the intake data are based 

on recall of behavior during the winter only. 

Extrapolation of the data to other seasons is difficult. 

The authors presented data on person-years of 

residence with various types of water supply sources 

(municipal versus private, chlorinated versus nonchlorinated, and surface versus well water). 

Unfortunately, these data cannot be used to draw 

conclusions about the national average apportionment 

of surface versus groundwater since a large fraction 

(24%) of municipal water intake in this survey could 

not be specifically attributed to either ground or 

surface water. 

3.3.2.9.	 Ershow and Cantor (1989)—Total Water 

and Tap Water Intake in the U.S.: 

Population-Based Estimates of Quantities 

and Sources 

Ershow and Cantor (1989) estimated water 

intake rates based on data collected by the USDA 

1977–1978 NFCS. The survey was conducted 

through interviews and diary entries. Daily intake 

rates for tap water and total water were calculated for 

various age groups for males, females, and both sexes 

combined. Tap water was defined as "all water from 

the household tap consumed directly as a beverage or 

used to prepare foods and beverages." Total water 

was defined as tap water plus "water intrinsic to 

foods and beverages" (i.e., water contained in 

purchased food and beverages). The authors showed 

that the age, sex, and racial distribution of the 

surveyed population closely matched the estimated 

1977 U.S. population. 

Table 3-55 presents daily total tap water intake 

rates, expressed as mL/day by age group. These data 

follow a lognormal distribution. Table 3-56 presents 

the same data, expressed as mL per kg body weight 

per day. Table 3-57 presents a summary of these 

tables, showing the mean, the 10th and 90th percentile 

intakes, expressed as both mL/day and mL/kg-day as 

a function of age. This shows that the mean and 

90th percentile intake rates for adults (ages 20 to 65+) 

are approximately 1,410 mL/day and 2,280 mL/day, 

and for all ages, the mean and 90th percentile intake 

rates are 1,193 mL/day and 2,092 mL/day. Note that 

older adults have greater intakes than do adults 

between age 20 and 64, an observation bearing on the 

interpretation of the Cantor et al. (1987) study, which 

surveyed a population that was older than the 

national average (see Section 3.3.2.8). 

Ershow and Cantor (1989) also measured total 

water intake for the same age groups and concluded 

that it averaged 2,070 mL/day for all groups 

combined and that tap water intake (1,190 mL/day) is 

55% of the total water intake. (Table 3-58 presents 

the detailed intake data for various age groups). 

Ershow and Cantor (1989) also concluded that, for all 

age groups combined, the proportion of tap water 

consumed as drinking water, or used to prepare foods 

and beverages is 54, 10, and 36%, respectively. 

(Table 3-59 presents the detailed data on proportion 

of tap water consumed for various age groups). 

Ershow and Cantor (1989) also observed that males 

of all age groups had higher total water and tap water 

consumption rates than females; the variation of each 

from the combined-sexes mean was about 8%. 

With respect to region of the country, the 

northeast states had slightly lower average tap water 

intake (1,200 mL/day) than the three other regions 

(which were approximately equal at 1,400 mL/day). 

This survey has an adequately large size 

(26,446 individuals), and it is a representative sample 

of the U.S. population with respect to age distribution 

and residential location. The data are more than 

20 years old and may not be entirely representative of 

current patterns of water intake, but, in general, the 

rates are similar to those presented in the key 

drinking water study in this chapter. 

3.3.2.10.	 Roseberry and Burmaster (1992)— 

Lognormal Distributions for Water 

Intake 

Roseberry and Burmaster (1992) fit lognormal 

distributions to the water intake data population-wide 

distributions for total fluid and total tap water intake 

based on proportions of the population in each age 

group. Their publication shows the data and the fitted 

lognormal distributions graphically. The mean was 

estimated as the zero intercept, and the standard 

deviation (SD) was estimated as the slope of the bestfit line for the natural logarithm of the intake rates 

plotted against their corresponding z-scores 

(Roseberry and Burmaster, 1992). Least squares 

techniques were used to estimate the best-fit straight 

lines for the transformed data. Table 3-60 presents 

summary statistics for the best-fit lognormal 

distribution. In this table, the simulated balanced 

population represents an adjustment to account for 

the difference in the age distribution of the U.S. 

population in 1988 from the age distribution in 1978 

when Ershow and Cantor (1989) collected their data. 

Table 3-61 summarizes the quantiles and means of 

tap water intake as estimated from the best-fit 

distributions. The mean total tap water intake rates 

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for the two adult populations (ages 20 to 65 years, 

and 65+ years) were estimated to be 1.27 and 

1.34 L/day. 

These intake rates were based on the data 

originally presented by Ershow and Cantor (1989). 

Consequently, the same advantages and 

disadvantages associated with the Ershow and Cantor 

(1989) study apply to this data set. 

3.3.2.11.	 Levy et al. (1995)—Infant Fluoride 

Intake From Drinking Water Added to 

Formula, Beverages, and Food 

Levy et al. (1995) conducted a study to 

determine fluoride intake by infants through drinking 

water and other beverages prepared with water and 

baby foods. The study was longitudinal and covered 

the ages from birth to 9 months old. A total of 

192 mothers, recruited from the post partum wards of 

two hospitals in Iowa City, completed mail 

questionnaires and 3-day beverage and food diaries 

for their infants at ages 6 weeks, and 3, 6, and 

9 months (Levy et al., 1995). The questionnaire 

addressed feeding habits, water sources and 

ingestion, and the use of dietary fluoride supplements 

during the preceding week (Levy et al., 1995). Data 

on the quantity of water consumed by itself or as an 

additive to infant formula, other beverages, or foods 

were obtained. In addition, the questionnaire 

addressed the infants’ ingestion of cows’ milk, breast 

milk, ready-to-feed (RTF) infant products (formula, 

juices, beverages, baby food), and table foods. 

Mothers were contacted for any clarifications of 

missing data and discrepancies (Levy et al., 1995). 

Levy et al. (1995) assessed non-response bias and 

found no significant differences in the reported 

number of adults or children in the family, water 

sources, or family income at 3, 6, or 9 months. Table 

3-62 provides the range of water ingestion from 

water by itself and from addition to selected foods 

and beverages. The percentage of infants ingesting 

water by itself increased from 28% at 6 weeks to 

66% at 9 months, respectively, and the mean intake 

increased slightly over this time frame. During this 

time frame, the largest proportion of the infants’ 

water ingestion (i.e., 36% at 9 months to 48% at 

6 months) came from the addition of water to 

formula. Levy et al. (1995) noted that 32% of the 

infants at age 6 weeks and 23% of the infants at age 

3 months did not receive any water from any of the 

sources studied. Levy et al. (1995) also noted that the 

proportion of children ingesting some water from all 

sources gradually increased with age. 

The advantages of this study are that it provides 

information on water ingestion of infants starting at 

6 weeks old, and the data are for water only and for 

water added to beverages and foods. The limitations 

of the study are that the sample size was small for 

each age group, it captured information from a select 

geographical location, and data were collected 

through self-reporting. The authors noted, however, 

that the 3-day diary has been shown to be a valid 

assessment tool. Levy et al. (1995) also stated that 

(1) for each time period, the ages of the infants varied 

by a few days to a few weeks, and are, therefore, not 

exact and could, at early ages, have an effect on 

age-specific intake patterns, and (2) the same number 

of infants were not available at each of the four time 

periods. 

3.3.2.12.	 USDA (1995)—Food and Nutrient 

Intakes by Individuals in the United 

States, 1 Day, 1989–1991 

USDA (1995) collected data on the quantity of 

"plain drinking water" and various other beverages 

consumed by individuals in one day during 1989 

through 1991. The data were collected as part of 

USDA's CSFII. The data used to estimate mean per 

capita intake rates combined 1-day dietary recall data 

from three survey years: 1989, 1990, and 1991 during 

which 15,128 individuals supplied 1-day intake data. 

Individuals from all income levels in the 

48 conterminous states and Washington D.C. were 

included in the sample. A complex 3-stage sampling 

design was employed, and the overall response rate 

for the study was 58%. To minimize the biasing 

effects of the low response rate and adjust for the 

seasonality, a series of weighting factors was 

incorporated into the data analysis. Table 3-63 

presents the intake rates based on this study. Table 

3-63 includes data for (a) "plain drinking water," 

which might be assumed to mean tap water directly 

consumed rather than bottled water; (b) coffee and 

tea, which might be assumed to be constituted from 

tap water; (c) fruit drinks and ades, which might be 

assumed to be reconstituted from tap water rather 

than canned products; and (d) the total of the three 

sources. With these assumptions, the mean per capita 

total intake of water is estimated to be 1,416 mL/day 

for adult males (i.e., 20 years of age and older), 1,288 

mL/day for adult females (i.e., 20 years of age and 

older), and 1,150 mL/day for all ages and both sexes 

combined. Although these assumptions appear 

reasonable, a close reading of the definitions used by 

USDA (1995) reveals that the word “tap water” does 

not occur, and this uncertainty prevents the use of this 

study as a key study of tap water intake. 

The advantages of using these data are that 

(1) the survey had a large sample size; and (2) the 

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authors attempted to represent the general U.S. 

population by oversampling low-income groups and 

by weighting the data to compensate for low response 

rates. The disadvantages are that (1) the word “tap 

water” was not defined, and the assumptions that 

must be used in order to compare the data with the 

other tap water studies might not be valid; (2) the 

data collection period reflects only a 1-day intake 

period and may not reflect long-term drinking water 

intake patterns; (3) data on the percentiles of the 

distribution of intakes were not given; and (4) the 

data are almost 20 years old and may not be entirely 

representative of current intake patterns. 

3.3.2.13.	 U.S. EPA (1996)—Descriptive Statistics 

From a Detailed Analysis of the National 

Human Activity Pattern Survey (NHAPS) 

Responses 

The U.S. EPA collected information on the 

number of glasses of drinking water and juice 

reconstituted with tap water consumed by the general 

population as part of the National Human Activity 

Pattern Survey (NHAPS) (U.S. EPA, 1996). NHAPS 

was conducted between October 1992 and September 

1994. Over 9,000 individuals in the 48 contiguous 

United States provided data on the duration and 

frequency of selected activities and the time spent in 

selected microenvironments via 24-hour diaries. Over 

4,000 NHAPS respondents also provided information 

on the number of 8-ounce glasses of water and the 

number of 8-ounce glasses of juice reconstituted with 

water that they drank during the 24-hour survey 

period (see Table 3-64 and Table 3-65). The median 

number of glasses of tap water consumed was 1–2, 

and the median number of glasses of juice with tap 

water consumed was 1–2. 

For both individuals who drank tap water and 

individuals who drank juices reconstituted with tap 

water, the number of glasses consumed in a day 

ranged from 1 to 20 glasses. The highest percentage 

of the population (37.1%) who drank tap water, 

consumed in the range of 3–5 glasses a day, and the 

highest percentage of the population (51.5%) who 

consumed juice reconstituted with tap water 

consumed 1–2 glasses in a day. Based on the 

assumption that each glass contained 8 ounces of 

water (226.4 mL), the total volume of tap water and 

juice with tap water consumed would range from 

0.23 L/day (1 glass) to 4.5 L/day (20 glasses) for 

respondents who drank tap water. Using the same 

assumption, the volume of tap water consumed for 

the population who consumed 3–5 glasses would be 

0.68 L/day to 1.13 L/day, and the volume of juice 

with tap water consumed for the population who 

consumed 1–2 glasses would be 0.23–0.46 L/day. 

Assuming that the average individual consumes 

3-5 glasses of tap water plus 1–2 glasses of juice with 

tap water, the range of total tap water intake for this 

individual would range from 0.9 L/day to 1.64 L/day. 

These values are consistent with the average intake 

rates observed in other studies. 

The advantages of NHAPS are that the data were 

collected for a large number of individuals and that 

the data are representative of the U.S. population. 

However, evaluation of drinking water intake rates 

was not the primary purpose of the study, and the 

data do not reflect the total volume of tap water 

consumed. In addition, using the assumptions 

described above, the estimated drinking water intake 

rates from this study are within the same ranges 

observed for other drinking water studies. 

3.3.2.14.	 Heller et al. (2000)—Water Consumption 

and Nursing Characteristics of Infants by 

Race and Ethnicity 

Heller et al. (2000) analyzed data from the 

1994-1996 CSFII to evaluate racial/ethnic differences 

in the ingestion rates of water in children younger 

than 2 years old. Using data from 946 children in this 

age group, the mean amounts of water consumed 

from eight sources were determined for various 

racial/ethnic groups, including Black non-Hispanic, 

White non-Hispanic, Hispanic, and “other” (Asian, 

Pacific Islander, American Indian, Alaskan Native, 

and other non-specified racial/ethnic groups). The 

sources analyzed included (1) plain tap water, 

(2) milk and milk drinks, (3) reconstituted powdered 

or liquid infant formula made from drinking water, 

(4) ready-to-feed and other infant formula, (5) baby 

food, (6) carbonated beverages, (7) fruit and 

vegetable juices and other non-carbonated drinks, and 

(8) other foods and beverages. In addition, Heller et 

al. (2000) calculated mean plain water and total water 

ingestion rates for children by age, sex, region, 

urbanicity, and poverty category. Ages were defined 

as less than 12 months and 12 to 24 months. Regions 

were categorized as Northeast, Midwest, South, and 

West. The states represented by each of these regions 

were not reported in Heller et al. (2000). However, it 

is likely that these regions were defined in the same 

way as in Sohn et al. (2001). See Section 3.3.2.16 for 

a discussion on the Sohn et al. (2001) study. 

Urbanicity of the residence was defined as urban (i.e., 

being in a Metropolitan Statistical Area [MSA], 

suburban [outside of an MSA], or rural [being in a 

non-MSA]). Poverty category was derived from the 

poverty income ratio. In this study, a poverty income 

ratio was calculated by dividing the family’s annual 

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income by the federal poverty threshold for that size 

household. The poverty categories used were 0–1.30, 

1.31 to 3.50, and greater than 3.50 times the federal 

poverty level (Heller et al., 2000). 

Table 3-66 provides water ingestion estimates for 

the eight water sources evaluated, for each of the 

race/ethnic groups. Heller et al. (2000) reported that 

Black non-Hispanic children had the highest mean 

plain tap water intake (21 mL/kg-day), and White 

non-Hispanic children had the lowest mean plain tap 

water intake (13 mL/kg-day). The only statistically 

significant difference between the racial/ethnic 

groups was found to be in plain tap water 

consumption and total water consumption. 

Reconstituted baby formula made up the highest 

proportion of total water intake for all race/ethnic 

groups. Table 3-67 presents tap water and total water 

ingestion by age, sex, region, urbanicity, and poverty 

category. On average, children younger than 

12 months of age consumed less plain tap water 

(11 mL/kg-day) than children aged 12–24 months 

(18 mL/kg-day). There were no significant 

differences in plain tap water consumption by sex, 

region, or urbanicity. Heller et al. (2000) reported a 

significant association between higher income and 

lower plain tap water consumption. For total water 

consumption, ingestion per kg body weight was 

lower for the 12–24 month-old children than for 

those younger than 12 months of age. Urban children 

consumed more plain tap water and total water than 

suburban and rural children. In addition, plain tap 

water and total water ingestion was found to decrease 

with increasing poverty category (i.e., higher wealth). 

A major strength of the Heller et al. (2000) study 

is that it provides information on tap water and total 

water consumption by race, age, sex, region, 

urbanicity, and family income. The weaknesses in the 

CSFII data set have been discussed under Kahn and 

Stralka (2009) and U.S. EPA (2004) and include 

surveying participants for only 2 days. 

3.3.2.15.	 Sichert-Hellert et al. (2001)—FifteenYear Trends in Water Intake in German 

Children and Adolescents: Results of the 

DONALD Study 

Water and beverage consumption was evaluated 

by Sichert-Hellert et al. (2001) using 3-day dietary 

records of 733 children, ages 2 to 13 years, enrolled 

in the Dortmund Nutritional and Anthropometric 

Longitudinally Designed Study (DONALD study). 

The DONALD study is a cohort study, conducted in 

Germany, that collects data on diet, metabolism, 

growth, and development from healthy subjects 

between infancy and adulthood (Sichert-Hellert et al., 

2001). Beginning in 1985, approximately 40 to 

50 infants were enrolled in the study annually. 

Mothers of the participants were recruited in hospital 

maternity wards. Older children and parents of 

younger children were asked to keep dietary records 

for 3 days by recording and weighing (to the nearest 

1 gram) all foods and fluids, including water, 

consumed. 

Sichert-Hellert et al. (2001) evaluated 

3,736 dietary records from 733 subjects (354 males 

and 379 females) collected between 1985 and 1999. 

Total water ingestion was defined as the sum of water 

content from food (intrinsic water), beverages, and 

oxidation. Beverages included milk, mineral water, 

tap water, juice, soft drinks, and coffee and tea. Table 

3-68 presents the mean water ingestion rates for these 

different sources, as well as mean total water 

ingestion rates for three age ranges of children (aged 

2 to 3 years, aged 4 to 8 years, and aged 9 to 

13 years). According to Sichert-Hellert et al. (2001), 

mean total water ingestion increased with age from 

1,114 mL/day in the 2- to 3-year-old subjects to 1,891 

and 1,676 mL/day in 9- to 13-year-old boys and girls, 

respectively. However, mean total water intake per 

body weight decreased with age. Sichert-Hellert et al. 

(2001) observed that the most important source of 

total water ingestion was mineral water for all 

children, except the 2- to 3-year-olds. For these 

children, the most important source of total water 

ingestion was milk. 

One of the limitations of this study is that it 

evaluated water and beverage consumption in 

German children and, as such, it may not be 

representative of consumption patterns of U.S. 

children. 

3.3.2.16.	 Sohn et al. (2001)—Fluid Consumption 

Related to Climate Among Children in 

the United States 

Sohn et al. (2001) investigated the relationship 

between fluid consumption among children aged 1 to 

10 years and local climate using data from the third 

National Health and Nutrition Examination Survey 

(NHANES III, 1988–1994). Children aged 1 to 

10 years who completed the 24-hour dietary 

interview (or proxy interview for the younger 

children) during the NHANES III survey were 

selected for the analysis. Breast-fed children were 

excluded from the analysis. Among 8,613 children 

who were surveyed, 688 (18%) were excluded due to 

incomplete data. A total of 7,925 eligible children 

remained. Since data for climatic conditions were not 

collected in the NHANES III survey, the mean daily 

maximum temperature from 1961 to 1990, averaged 

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for the month during which the NHANES III survey 

was conducted, was obtained for each survey location 

from the U.S. Local Climate Historical Database. Of 

the 7,925 eligible children with complete dietary 

data, temperature information was derived for only 

3,869 children (48.8%) since detailed information on 

survey location, in terms of county and state, was 

released only for counties with a population of more 

than a half million. 

Sohn et al. (2001) calculated the total amount of 

fluid intake for each child by adding the fluid intake 

from plain drinking water and the fluid intake from 

foods and beverages other than plain drinking water 

provided by NHANES III. Sohn et al. (2001) 

identified major fluid sources as milk (and milk 

drinks), juice (fruit and vegetable juices and other 

non-carbonated drinks), carbonated drinks, and plain 

water. Fluid intake from sources other than these 

major sources was grouped into other foods and 

beverages. Other foods and beverages included 

bottled water, coffee, tea, baby food, soup, 

water-based beverages, and water used for dilution of 

food. Table 3-69 presents mean fluid ingestion rates 

of selected fluids for the total sample population and 

for the subsets of the sample population with and 

without temperature information. The estimated mean 

total fluid and plain water ingestion rates for the 

3,869 children for whom temperature information 

was obtained are presented in Table 3-70 according to 

age (years), sex, race/ethnicity, poverty/income ratio, 

region, and urbanicity. Poverty/income ratio was 

defined as the ratio of the reported family income to 

the federal poverty level. The following categories 

were assigned low socioeconomic status (SES) = 

0.000 to 1.300 times the poverty/income ratio; 

medium SES = 1.301 to 3.500 times the 

poverty/income level; and high SES = 3.501 or 

greater times the poverty/income level. Regions were 

as Northeast, Midwest, South, and West, as defined 

by the U.S. Census (see Table 3-70). Sohn et al. 

(2001) did not find a significant association between 

mean daily maximum temperature and total fluid or 

plain water ingestion, either before or after 

controlling for sex, age, SES, and race or ethnicity. 

However, significant associations between fluid 

ingestion and age, sex, socioeconomic status, and 

race and ethnicity were reported. 

The main strength of the Sohn et al. (2001) study 

is the evaluation of water intake as it relates to 

weather data. The main limitations of this study were 

that northeast and western regions were overrepresented since temperature data were only 

available for counties with populations in excess of a 

half million. In addition, Whites were underrepresented compared to other racial or ethnic 

groups. Other limitations include lack of data for 

children from extremely cold or hot weather 

conditions. 

3.3.2.17.	 Hilbig et al. (2002)—Measured 

Consumption of Tap Water in German 

Infants and Young Children as 

Background for Potential Health Risk 

Assessment: Data of the DONALD Study 

Hilbig et al. (2002) estimated tap water ingestion 

rates based on 3-day dietary records of 504 German 

children aged 3, 6, 9, 12, 18, 24, and 36 months. The 

data were collected between 1990 and 1998 as part of 

the DONALD study. Details of data collection for the 

DONALD study have been provided previously 

under the Sichert-Hellert et al. (2001) study in 

Section 3.3.2.15 of this handbook. Tap water 

ingestion rates were calculated for three subgroups of 

children: (1) breast-fed infants ≤12 months of age 

(exclusive and partial breast-fed infants), 

(2) formula-fed infants ≤12 months of age (no human 

milk, but including weaning food), and (3) mixed-fed 

young children aged 18 to 36 months. Hilbig et al. 

(2002) defined “total tap water from household” as 

water from the tap consumed as a beverage or used in 

food preparation. “Tap water from food 

manufacturing” was defined as water used in 

industrial production of foods, and “Total Tap Water” 

was defined as tap water consumed from both the 

household and that used in manufacturing. 

Table 3-71 summarizes total tap water ingestion 

(in mL/day and mL/kg-day) and tap water ingestion 

from household and manufacturing sources (in 

mL/kg-day) for breast-fed, formula-fed, and 

mixed-fed children. Mean total tap water intake was 

higher in formula-fed infants (53 mL/kg-day) than in 

breast-fed infants (17 g/kg-day) and mixed-fed young 

children (19 g/kg-day). Tap water from household 

sources constituted 66 to 97% of total tap water 

ingestion in the different age groups. 

The major limitation of this study is that the 

study sample consists of families from an upper 

social background in Germany (Hilbig et al., 2002). 

Because the study was conducted in Germany, the 

data may not be directly applicable to the U.S. 

population. 

3.3.2.18.	 Marshall et al. (2003b)—Patterns of 

Beverage Consumption During the 

Transition Stage of Infant Nutrition 

Marshall et al. (2003b) investigated beverage 

ingestion during the transition stage of infant 

nutrition. Mean ingestion of infant formula, cows’ 

milk, combined juice and juice drinks, water, and 

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other beverages was estimated using a frequency 

questionnaire. A total of 701 children, aged 6 months 

through 24 months, participated in the Iowa Fluoride 

Study (IFS). Mothers of newborns were recruited 

from 1992 through 1995. The parents were sent 

questionnaires when the children were 6, 9, 12, 16, 

20, and 24 months old. Of the 701 children, 470 

returned all six questionnaires, 162 returned five, 58 

returned four, and 11 returned three, with the 

minimum criteria being three questionnaires to be 

included in the data set (Marshall et al., 2003b). The 

questionnaire was designed to assess the type and 

quantity of the beverages consumed during the 

previous week. The validity of the questionnaire was 

assessed using a 3-day food diary for reference 

(Marshall et al., 2003b). Table 3-72 presents the 

percentage of subjects consuming beverages and 

mean daily beverage ingestion for children with 

returned questionnaires. Human milk ingestion was 

not quantified, but the percent of children consuming 

human milk was provided at each age category (see 

Table 3-72). Juice (100%) and juice drinks were not 

distinguished separately but categorized as juice and 

juice drinks. Water used to dilute beverages beyond 

normal dilution and water consumed alone were 

combined. Based on Table 3-72, 97% of the children 

consumed human milk, formula, or cows’ milk 

throughout the study period, and the percentage of 

infants consuming human milk decreased with age, 

while the percent consuming water increased 

(Marshall et al., 2003b). Marshall et al. (2003b) 

observed that, in general, lower family incomes were 

associated with less breast-feeding and increased 

ingestion of other beverages. 

The advantage of this study is that it provides 

mean ingestion data for various beverages. 

Limitations of the study are that it is based on 

samples gathered in one geographical area and may 

not be reflective of the general population. The 

authors also noted the following limitations: the 

parents were not asked to differentiate between 100% 

juice and juice drinks; the data are parent-reported 

and could reflect perceptions of appropriate ingestion 

instead of actual ingestion, and a substantial number 

of the infants from well educated, economically 

secure households dropped out during the initial 

phase. 

3.3.2.19.	 Marshall et al. (2003a)—Relative 

Validation of a Beverage Frequency 

Questionnaire in Children Aged 

6 Months Through 5 Years Using 3-Day 

Food and Beverage Diaries 

Marshall et al. (2003a) conducted a study based 

on data taken from 700 children in the IFS. This 

study compared estimated beverage ingestion rates 

reported in questionnaires for the preceding week and 

diaries for the following week. Packets were sent 

periodically (every 4 to 6 months) to parents of 

children aged 6 weeks through 5 years of age. This 

study analyzed data from children, aged 6 and 

12 months, and 2 and 5 years of age. Beverages were 

categorized as human milk, infant formula, cows’ 

milk, juice and juice drinks, carbonated and 

rehydration beverages, prepared drinks (from 

powder) and water. The beverage questionnaire was 

completed by parents and summarized the average 

amount of each beverage consumed per day by their 

children. The data collection for the diaries 

maintained by parents included 1 weekend day and 

2 weekdays and included detailed information about 

beverages consumed. Table 3-73 presents the mean 

ingestion rates of all beverages for children aged 6 

and 12 months and 3 and 5 years. Marshall et al. 

(2003a) concluded that estimates of beverage 

ingestion derived from quantitative questionnaires are 

similar to those derived from diaries. They found that 

it is particularly useful to estimate ingestion of 

beverages consumed frequently using quantitative 

questionnaires. 

The advantage of this study is that the survey 

was conducted in two different forms (questionnaire 

and diary), and that diaries for recording beverage 

ingestion were maintained by parents for 3 days. The 

main limitation is the lack of information regarding 

whether the diaries were populated on consecutive or 

non-consecutive days. The IFS survey participants 

may not be representative of the general population 

of the United States since participants were primarily 

White, and from affluent and well-educated families 

in one geographic region of the country. 

3.3.2.20.	 Skinner et al. (2004)—Transition in 

Infants’ and Toddlers’ Beverage Patterns 

Skinner et al. (2004) investigated the pattern of 

beverage consumption by infants and children 

participating in the Feeding Infants and Toddlers 

Study (FITS) sponsored by Gerber Products 

Company. The FITS is a cross-sectional study 

designed to collect and analyze data on feeding 

practices, food consumption, and usual nutrient 

intake of U.S. infants and toddlers (Devaney et al., 

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Chapter 3—Ingestion of Water and Other Select Liquids 

2004). It included a stratified random sample of 

3,022 infants and toddlers between 4 and 24 months 

of age. Parents or primary caregivers of sampled 

infants and toddlers completed a single 24-hour 

dietary recall of all foods and beverages consumed by 

the child on the previous day by telephone interview. 

All recalls were completed between March and July 

2002. Detailed information on data collection, 

coding, and analyses related to FITS is provided in 

Devaney et al. (2004). 

Beverages consumed by FITS participants were 

identified as total milks (i.e., human milk, infant 

formulas, cows’ milk, soy milk, goats’ milk), 100% 

juices, fruit drinks, carbonated beverages, water, and 

“other” drinks (i.e., tea, cocoa, dry milk mixtures, 

and electrolyte replacement beverages). There were 

six age groupings in the FITS study: 4 to 6, 7 to 8, 9 

to 11, 12 to 14, 15 to 18, and 19 to 24 months. 

Skinner et al. (2004) calculated the percentage of 

children in each age group consuming any amount in 

a beverage category and the mean amounts 

consumed. Table 3-74 provides the mean beverage 

consumption rates in mL/day for the six age 

categories. Skinner et al. (2004) found that some 

form of milk beverage was consumed by almost all 

children at each age; however, total milk ingestion 

decreased with increasing age. Water consumption 

also doubled with age, from 163 mL/day in children 

aged 4 to 6 months old to 337 mL/day in children 

aged 19 to 24 months old. The percentages of 

children consuming water increased from 34% at 4 to 

6 months of age to 77% at 19 to 24 months of age. 

A major strength of the Skinner et al. (2004) 

study is the large sample size (3,022 children). 

However, beverage ingestion estimates are based on 

1 day of dietary recall data and human milk quantity 

derived from studies that weighed infants before and 

after each feeding to determine the quantity of human 

milk consumed (Devaney et al., 2004); therefore, 

estimates of total milk ingestion may not be accurate. 

3.4. PREGNANT AND LACTATING WOMEN 

3.4.1.	 Key Study on Pregnant and Lactating 

Women 

3.4.1.1.	 Kahn and Stralka (2008)—Estimates of 

Water Ingestion for Women in Pregnant, 

Lactating and Non-Pregnant and 

Non-Lactating Child Bearing Age 

Groups Based on USDA’s 1994–1996, 

1998 CSFII 

The combined 1994–1996 and 1998 CSFII data 

sets were analyzed to examine the ingestion of water 

by various segments of the U.S. population as 

described in Section 3.3.1.1. Kahn and Stralka (2008) 

provided water intake data for pregnant, lactating, 

and child-bearing age women. Mean and upper 

percentile distribution data were provided. Lactating 

women had an estimated per capita mean community 

water ingestion of 1.38 L/day, the highest water 

ingestion rates of any identified subpopulation. The 

mean consumer-only population was 1.67 L/day. 

Table 3-75 through Table 3-82 provide estimated 

drinking water intakes for pregnant and lactating 

women, and non-pregnant, non-lactating women aged 

15–44 years old. The same advantages and 

disadvantages discussed in Section 3.3.1.1 apply to 

these data. 

3.4.2. Relevant Studies on Pregnant and 

Lactating Women 

3.4.2.1. Ershow et al. (1991)—Intake of Tap 

Water and Total Water by Pregnant and 

Lactating Women 

Ershow et al. (1991) used data from the 

1977-1978 USDA NFCS to estimate total fluid and 

total tap water intake among pregnant and lactating 

women (ages 15–49 years). Data for 188 pregnant 

women, 77 lactating women, and 

6,201 non-pregnant, non-lactating control women 

were evaluated. The participants were interviewed 

based on 24-hour recall and then asked to record a 

food diary for the next 2 days. "Tap water" included 

tap water consumed directly as a beverage and tap 

water used to prepare food and tap water-based 

beverages. "Total water" was defined as all water 

from tap water and non-tap water sources, including 

water contained in food. Table 3-83 and Table 3-84 

present estimated total fluid and total tap water intake 

rates for the three groups, respectively. Lactating 

women had the highest mean total fluid intake rate 

(2.24 L/day) compared with both pregnant women 

(2.08 L/day) and control women (1.94 L/day). 

Lactating women also had a higher mean total tap 

water intake rate (1.31 L/day) than pregnant women 

(1.19 L/day) and control women (1.16 L/day). The 

tap water distributions are neither normal nor 

lognormal, but lactating women had a higher mean 

tap water intake than controls and pregnant women. 

Ershow et al. (1991) also reported that rural women 

(N = 1,885) consumed more total water (1.99 L/day) 

and tap water (1.24 L/day) than urban/suburban 

women (N = 4,581, 1.93 and 1.13 L/day, 

respectively). Total water and tap water intake rates 

were lowest in the northeastern region of the United 

States (1.82 and 1.03 L/day) and highest in the 

western region of the United States (2.06 L/day and 

1.21 L/day). Mean intake per unit body weight was 

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Chapter 3—Ingestion of Water and Other Select Liquids 

highest among lactating women for both total fluid 

and total tap water intake. Total tap water intake 

accounted for over 50% of mean total fluid in all 

three groups of women (see Table 3-84). Drinking 

water accounted for the largest single proportion of 

the total fluid intake for control (30%), pregnant 

(34%), and lactating women (30%) (see Table 3-85). 

All other beverages combined accounted for 

approximately 46%, 43%, and 45% of the total water 

intake for control, pregnant, and lactating women, 

respectively. Food accounted for the remaining 

portion of total water intake. 

The same advantages and limitations associated 

with the Ershow and Cantor (1989) data also apply to 

these data sets (see Section 3.3.2.9). A further 

advantage of this study is that it provides information 

on estimates of total water and tap water intake rates 

for pregnant and lactating women. This topic has 

rarely been addressed in the literature. 

3.4.2.2.	 Forssen et al. (2007)—Predictors of Use 

and Consumption of Public Drinking 

Water Among Pregnant Women 

Forssen et al. (2007) evaluated the demographic 

and behavioral characteristics that would be 

important in predicting water consumption among 

pregnant women in the United States. Data were 

collected through telephone interviews with 

2,297 pregnant women in three geographical areas in 

the southern United States. Women 18 years old and 

≤12 weeks pregnant were recruited from the local 

communities and from both private and public 

prenatal care facilities in the southern United States. 

Variables studied included demographic, health status 

and history (e.g., diabetes, pregnancy history), 

behavioral (e.g., exercise, smoking, caffeine 

consumption), and some physiological characteristics 

(e.g., pre-pregnancy weight). Daily amount of water 

ingestion was estimated based on cup sizes defined in 

the interview. Water consumption was reported as 

cold tap water (filtered and unfiltered) and bottled 

water. Other behavioral information on water use 

such as showering and bathing habits, use of 

swimming pools, hot tubs, and Jacuzzis was 

collected. The overall mean tap water ingested was 

1.7 L/day (percentiles: 25th = 0.5 L/day, 

50th = 1.4 L/day, 75th = 2.4 L/day, and 

90th = 3.8 L/day). The overall mean bottled water 

ingested was 0.6 L/day (percentiles: 25th = 0.1 L/day, 

50th = 0.2 L/day, 75th = 0.6 L/day, and 

90th = 1.8 L/day). Table 3-86 presents water ingestion 

by the different variables studied, and Table 3-87 

presents the percentage of ingested tap water that is 

filtered and unfiltered by various variables. The 

advantage of this study is that it investigated water 

consumption in relation to multiple variables. 

However, the study population was not random and 

not representative of the entire United States. There 

are also limitations associated with recall bias. 

3.5. HIGH ACTIVITY LEVELS/HOT 

CLIMATES 

3.5.1. Relevant Studies on High Activity 

Levels/Hot Climates 

3.5.1.1.	 McNall and Schlegel (1968)—Practical 

Thermal Environmental Limits for 

Young Adult Males Working in Hot, 

Humid Environments 

McNall and Schlegel (1968) conducted a study 

that evaluated the physiological tolerance of adult 

males working under varying degrees of physical 

activity. Subjects were required to operate 

pedal-driven propeller fans for 8-hour work cycles 

under varying environmental conditions. The activity 

pattern for each individual was cycled as 15 minutes 

of pedaling and 15 minutes of rest for each 8-hour 

period. Two groups of eight subjects each were used. 

Work rates were divided into three categories as 

follows: high activity level (0.15 horsepower [hp] per 

person), medium activity level (0.1 hp per person), 

and low activity level (0.05 hp per person). Evidence 

of physical stress (i.e., increased body temperature, 

blood pressure, etc.) was recorded, and individuals 

were eliminated from further testing if certain stress 

criteria were met. The amount of water consumed by 

the test subjects during the work cycles was also 

recorded. Water was provided to the individuals on 

request. 

Table 3-88 presents the water intake rates 

obtained at the three different activity levels and the 

various environmental temperatures. The data 

presented are for test subjects with continuous data 

only (i.e., those test subjects who were not eliminated 

at any stage of the study as a result of stress 

conditions). Water intake was the highest at all 

activity levels when environmental temperatures 

were increased. The highest intake rate was observed 

at the low activity level at 100o

F (0.65 L/hour); 

however, there were no data for higher activity levels 

at 100o

F. It should be noted that this study estimated 

intake on an hourly basis during various levels of 

physical activity. These hourly intake rates cannot be 

converted to daily intake rates by multiplying by 

24 hours/day because they are only representative of 

intake during the specified activity levels, and the 

intake rates for the rest of the day are not known. 

Therefore, comparison of intake rate values from this 

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study cannot be made with values from the 

previously described studies on drinking water 

intake. 

3.5.1.2.	 U.S. Army (1983)—Water Consumption 

Planning Factors Study 

The U.S. Army has developed water 

consumption planning factors to enable them to 

transport an adequate amount of water to soldiers in 

the field under various conditions (U.S. Army, 1983). 

Both climate and activity levels were used to 

determine the appropriate water consumption needs. 

Consumption factors have been established for the 

following uses: (1) drinking, (2) heat treatment, 

(3) personal hygiene, (4) centralized hygiene, 

(5) food preparation, (6) laundry, (7) medical 

treatment, (8) vehicle and aircraft maintenance, 

(9) graves registration, and (10) construction. Only 

personal drinking water consumption factors are 

described here. Drinking water consumption planning 

factors are based on the estimated amount of water 

needed to replace fluids lost by urination, 

perspiration, and respiration. It assumes that water 

lost to urinary output averages 1 quart/day 

(0.9 L/day), and perspiration losses range from 

almost nothing in a controlled environment to 

1.5 quarts/day (1.4 L/day) in a very hot climate where 

individuals are performing strenuous work. Water 

losses to respiration are typically very low except in 

extreme cold where water losses can range from 1 to 

3 quarts/day (0.9 to 2.8 L/day). This occurs when the 

humidity of inhaled air is near zero, but expired air is 

98% saturated at body temperature (U.S. Army, 

1983). 

Drinking water is defined by the U.S. Army 

(1983) as "all fluids consumed by individuals to 

satisfy body needs for internal water." This includes 

soups, hot and cold drinks, and tap water. Planning 

factors have been established for hot, temperate, and 

cold climates based on the following mixture of 

activities among the workforce: 15% of the force 

performing light work, 65% of the force performing 

medium work, and 20% of the force performing 

heavy work. Hot climates are defined as tropical and 

arid areas where the temperature is greater than 80°F. 

Temperate climates are defined as areas where the 

mean daily temperature ranges from 32°F to 80°F. 

Cold regions are areas where the mean daily 

temperature is less than 32°F. Table 3-89 presents 

drinking water consumption factors for these three 

climates. These factors are based on research on 

individuals and small unit training exercises. The 

estimates are assumed to be conservative because 

they are rounded up to account for the subjective 

nature of the activity mix and minor water losses that 

are not considered (U.S. Army, 1983). 

The advantage of using these data is that they 

provide a conservative estimate of drinking water 

intake among individuals performing at various 

levels of physical activity in hot, temperate, and cold 

climates. However, the planning factors described 

here are based on assumptions about water loss from 

urination, perspiration, and respiration, and are not 

based on survey data or actual measurements. 

3.6.	 WATER INGESTION WHILE 

SWIMMING AND DIVING 

3.6.1.	 Key Study on Water Ingestion While 

Swimming 

3.6.1.1.	 Dufour et al. (2006)—Water Ingestion 

During Swimming Activities in a Pool: A 

Pilot Study 

Dufour et al. (2006) estimated the amount of 

water ingested while swimming, using cyanuric acid 

as an indicator of pool water ingestion exposure. 

Cyanuric acid is a breakdown product of 

chloroisocyanates, which are commonly used as 

disinfectant stabilizers in recreational water 

treatment. Because ingested cyanuric acid passes 

through the body unmetabolized, the volume of water 

ingested can be estimated based on the amount of 

cyanuric acid measured in the pool water and in the 

urine of swimmers, as follows: 

Vpool water ingested = Vurine × CAurine/CApool (Eqn. 3-1) 

where: 

Vpool water ingested = volume of pool water 

ingested (mL), 

Vurine = volume of urine collected 

over a 24-hour period 

(mL), 

CAurine = concentration of cyanuric 

acid in urine (mg/L), and 

CApool = concentration of cyanuric 

acid in pool water (mg/L). 

According to Dufour et al. (2006), dermal 

absorption of cyanuric acid has been shown to be 

negligible. Thus, the concentration in urine is 

assumed to represent the amount ingested. Dufour et 

al. (2006) estimated pool water intake among 

53 swimmers that participated in a pilot study at an 

outdoor swimming pool treated with 

chloroisocyanate. This pilot study population 

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included 12 adults (4 males and 8 females) and 

41 children under 18 years of age (20 males and 

21 females). The study participants were asked not to 

swim for 24 hours before or after a 45-minute period 

of active swimming in the pool. Pool water samples 

were collected prior to the start of swimming 

activities, and swimmers’ urine was collected for 

24 hours after the swimming event ended. The pool 

water and urine sample were analyzed for cyanuric 

acid. 

Table 3-90 presents the results of this pilot study. 

The mean volumes of water ingested over a 

45-minute period were 16 mL for adults and 37 mL 

for children. The maximum volume of water ingested 

by adults was 53 mL, and by children, was 

154 mL/45 minutes, as found in the 

recommendations table for water ingestion while 

swimming (see Table 3-5). The 97th percentile 

volume of water ingested by children was 

approximately 90 mL/45 minutes (see Table 3-5). 

The advantage of this study is that it is one of the 

first attempts to measure water ingested while 

swimming. However, the number of study 

participants was low, and data cannot be broken out 

by the recommended age categories. As noted by 

Dufour et al. (2006), swimming behavior of pool 

swimmers may be similar to freshwater swimmers 

but may differ from salt water swimmers. 

Based on the results of the Dufour et al. (2006) 

study, the recommended mean water ingestion rates 

for exposure scenarios involving swimming activities 

are 21 mL/hour for adults and 49 mL/hour for 

children under 18 years of age. Because the data set 

is limited, upper percentile water ingestion rates for 

swimming are based on the 97th percentile value for 

children and the maximum value for adults from the 

Dufour et al. (2006) study. These values are 

71 mL/hour for adults and 120 mL/hour for children 

(see Table 3-5). Also, competitive swimmers may 

swallow more water than the recreational swimmers 

observed in this study (Dufour et al., 2006). 

3.6.2.	 Relevant Studies on Water Ingestion 

While Swimming, Diving, or Engaging in 

Recreational Water Activities 

3.6.2.1.	 Schijven and de Roda Husman (2006)— 

A Survey of Diving Behavior and 

Accidental Occupational and Sport 

Divers to Assess the Risk of Infection 

With Waterborne Pathogenic 

Microorganisms 

Schijven and de Roda Husman (2006) estimated 

the amount of water ingested by occupational and 

sports divers in The Netherlands. Questionnaires 

were used to obtain information on the number of 

dives for various types of water bodies, and the 

approximate volume of water ingested per dive. 

Estimates of the amount of water ingested were made 

by comparing intake to common volumes (i.e., a few 

drops = 2.75 mL; shot glass = 25 mL; coffee 

cup = 100 mL; soda glass = 190 mL). The study was 

conducted among occupational divers in 2002 and 

among sports divers in 2003 and included responses 

from more than 500 divers. Table 3-91 provides the 

results of this study. On average, occupational divers 

ingested 9.8 mL/dive marine water and 5.7 mL/dive 

freshwater. Sports divers wearing an ordinary diving 

mask ingested 9.0 mL/dive marine water and 

13 mL/dive fresh recreational water. Sports divers 

who wore full face masks ingested less water. The 

main limitation of this study is that no measurements 

were taken. It relies on estimates of the perceived 

amount of water ingested by the divers. 

3.6.2.2.	 Schets et al. (2011)—Exposure 

Assessment for Swimmers in Bathing 

Waters and Swimming Pools 

Schets et al. (2011) collected exposure data for 

swimmers in freshwater, seawater, and swimming 

pools in 2007 and 2009. Information on the 

frequency, duration, and amount of water swallowed 

were collected via questionnaires administered to 

nearly 10,000 people in The Netherlands. Individuals 

15 years of age and older were considered to be 

adults and answered questions for themselves, and a 

parent answered the questions for their eldest child 

under 15 years of age. Survey participants estimated 

the amount of water that they swallowed while 

swimming by responding in one of four ways: 

(1) none or only a few drops; (2) one or two 

mouthfuls; (3) three to five mouthfuls; or (4) six to 

eight mouthfuls. Schets et al. (2011) conducted a 

series of experiments to measure the amount of water 

that corresponded to a mouthful of water and 

converted the data in the four response categories to 

volumes of water ingested. Monte Carlo analyses 

were used to combine the distribution of volume (i.e., 

mouthful) measurements with the distribution of 

responses in the four response categories to generate 

distributions of the amount of water swallowed per 

event for adult men and women, and children less 

than 15 year of age. Table 3-92 presents the means 

and 95% confidence intervals for the duration of 

swimming and amount of water ingested during 

swimming. Frequency data were also provided by 

Schets et al. (2011), but these data are not presented 

here because they are for the population of The 

Netherlands and may not be representative of 

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Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

swimming frequency in the U.S. According to Schets 

et al. (2011), the mean volume of water ingested by 

children (<15 years) during an average swimming 

pool event lasting 81 minutes was 51 mL or 

0.63 mL/min (38 mL/hour). The values for children 

were slightly lower for swimming in freshwater and 

seawater. For adults, the mean volume of water 

ingested ranged from 0.5 to 0.6 mL/min (30 to 

36 mL/hour) for men and 0.3 to 0.4 mL/min (20 to 

26 mL/hour) for women (see Table 3-92). 

The advantages of this study are that it is based 

on a relatively large sample size and that data are 

provided for various types of swimming 

environments (i.e., pools, freshwater, and seawater). 

However, the data were collected from a population 

in The Netherlands and may not be entirely 

representative of the United States. While the 

ingestion data are based primarily on self-reported 

estimates, the mean values reported in this study are 

similar to those based on measurements of cyanuric 

acid in the urine of swimmers as reported by Dufour 

et al. (2006). 

3.6.2.3.	 Dorevitch et al. (2011)—Water Ingestion 

During Water Recreation 

Dorevitch et al. (2011) estimated the volumes of 

water ingested during “limited contact water 

recreation activities.” These activities included such 

as canoeing, fishing, kayaking, motor boating, 

rowing, wading and splashing, and walking. Full 

contact scenarios (i.e., swimming and immersion) 

were also evaluated. Dorevitch et al. (2011) estimated 

water intake among individuals greater than 6 years 

of age using two different methods in studies 

conducted in 2009. In the first surface water study, 

self-reported estimates of ingestion were obtained via 

interview from 2,705 individuals after they engaged 

in recreation activities in Chicago area surface 

waters. A total of 2,705 participants reported whether 

they swallowed no water, a drop or two, a teaspoon, 

or one or more mouthfuls of water during one of the 

five limited contact recreational activities (i.e., 

canoeing, fishing, kayaking, motor boating, and 

rowing). A second study was conducted in swimming 

pools where 662 participants engaged in limited 

contact scenarios (i.e., canoeing, simulated fishing, 

kayaking, motor boating, rowing, wading/splashing, 

and walking), as well as full contact activities such as 

swimming and immersion. Participants were 

interviewed after performing their water activity and 

reported on their estimated water ingestion. In 

addition, 24-hour urine samples were collected for 

analysis of cyanuric acid, a tracer of swimming pool 

water. Translation factors for each of the reported 

categories of ingestion (e.g., none, drop/teaspoon, 

mouthful) were developed using the results of the 

urine analyses. These translation factors were used to 

estimate the volume of water ingested for the various 

water activities evaluated in this study (Dorevitch et 

al., 2011). Table 3-93 presents the estimated volumes 

of water ingested for the limited and full contact 

scenarios. Swimmers had the highest estimated water 

intake (mean = 10 mL/hr; 95% upper confidence 

limit = 35 mL/hr) among the activities evaluated. 

The advantage of this study is that it provides 

information on the estimated volume of water 

ingested during both limited and full contact 

recreational activities. However, the data are based on 

self-reporting, and data are not provided for 

individual age groups of the population. 

3.7. REFERENCES FOR CHAPTER 3 

Bourne, GH; Kidder, GW (Eds.). (1953). 

Biochemistry and physiology of nutrition, 

v.1. New York, NY: Academic Press. 

Canadian Ministry of National Health and Welfare. 

(1981). Tap water consumption in Canada. 

(Document Number 82-EHD-80). Ottawa, 

Canada: Public Affairs Directorate, 

Department of National Health and Welfare. 

Cantor, KP; Hoover, R; Hartge, P; Mason, TJ; 

Silverman, DT; Altman, R; Austin, DF; 

Child, MA; Key, CR; Marrett, LD; Al, E. 

(1987). Bladder cancer, drinking water 

source, and tap water consumption: A casecontrol study. J Natl Cancer Inst 79: 1269­

1279. 

Devaney, B; Kalb, L; Briefel, R; Zavitsky-Novak, T; 

Clusen, N; Ziegler, P. (2004). Feeding 

infants and toddlers study: overview of the 

study design. J Am Diet Assoc 104: s8-13. 

http://dx.doi.org/10.1016/j.jada.2003.10.023. 

Dorevitch, S; Panthi, S; Huang, Y; Li, H; Michalek, 

AM; Pratap, P; Wroblewski, M; Liu, L; 

Scheff, PA; Li, A. (2011). Water ingestion 

during water recreation. Water Res 45: 

2020-2028. 

http://dx.doi.org/10.1016/j.watres.2010.12.0 

06. 

Dufour,	 AP; Evans, O; Behymer, TD; Cantú, R. 

(2006). Water ingestion during swimming 

activities in a pool: a pilot study. J Water 

Health 4: 425-430. 

Ershow, AB; Cantor, KP.	 (1989). Total Water and 

Tapwater Intake in the United States: 

Population-Based Estimates of Quantities 

and Sources. Ershow, AB; Cantor, KP. 

Exposure Factors Handbook Page
 

September 2011 3-25 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Ershow, AG; Brown, LM; Cantor, KP. (1991). Intake 

of tapwater and total water by pregnant and 

lactating women. Am J Public Health 81: 

328-334. 

FASEB/LSRO (Federation of American Societies for 

Experimental Biology, Life Sciences 

Research Office). (1995). Third report on 

nutrition monitoring in the United States: 

Volume 1. Washington, DC: Interagency 

Board for Nutrition Monitoring and Related 

Research. 

Forssén, UM; Herring, AH; Savitz, DA; 

Nieuwenhuijsen, MJ; Murphy, PA; Singer, 

PC; Wright, JM. (2007). Predictors of use 

and consumption of public drinking water 

among pregnant women. J Expo Sci Environ 

Epidemiol 17: 159-169. 

http://dx.doi.org/10.1038/sj.jes.7500488. 

Gillies, ME; Paulin, HV. (1983). Variability of 

mineral intakes from drinking water: a 

possible explanation for the controversy 

over the relationship of water quality to 

cardiovascular disease. Int J Epidemiol 12: 

45-50. 

Guyton, AC. (1968). Textbook of medical physiology 

(3rd ed.). Philadelphia, PA: W.B. Saunders 

Co. 

Heller, KE; Sohn, W; Burt, BA; Feigal, RJ. (2000). 

Water consumption and nursing 

characteristics of infants by race and 

ethnicity. J Public Health Dent 60: 140-146. 

Hilbig, A; Kersting, M; Sichert-Hellert, W. (2002). 

Measured consumption of tap water in 

German infants and young children as 

background for potential health risk 

assessments: data of the DONALD Study. 

Food Addit Contam 19: 829-836. 

http://dx.doi.org/10.1080/026520302101518 

59. 

Hopkins, SM; Ellis, JC. (1980). Drinking water 

consumption in Great Britain: a survey of 

drinking habits with special reference to tapwater-based beverages. (Technical Report 

137). Wiltshire, Great Britain: Water 

Research Centre. 

Kahn, H. (2008). Letter from Henry Kahn to 

Jacqueline Moya, EPA, providing 

supplemental data to Estimated daily 

average per capita water ingestion by child 

and adult age categories based on USDA's 

1994-96 and 1998 continuing survey of food 

intakes by individuals (September 18, 2008). 

Available online at (accessed 

Kahn, H; Stralka, K. (2008). Estimates of Water 

Ingestion for Women in Pregnant, Lactating, 

and Non-Pregnant and Non-Lactating ChildBearing Age Groups Based on USDA's 

1994-96, 1998 Continuing Survey of Food 

Intake by Individuals. Hum Ecol Risk 

Assess 14: 1273-1290. 

http://dx.doi.org/10.1080/108070308024946 

18. 

Kahn, HD; Stralka, K. (2009). Estimated daily 

average per capita water ingestion by child 

and adult age categories based on USDA's 

1994-1996 and 1998 continuing survey of 

food intakes by individuals. J Expo Sci 

Environ Epidemiol 19: 396-404. 

http://dx.doi.org/10.1038/jes.2008.29. 

Levy, SM; Kohout, FJ; Guha-Chowdhury, N; Kiritsy, 

MC; Heilman, JR; Wefel, JS. (1995). 

Infants' fluoride intake from drinking water 

alone, and from water added to formula, 

beverages, and food. J Dent Res 74: 1399­

1407. 

Marshall, TA; Eichenberger Gilmore, JM; Broffitt, B; 

Levy, SM; Stumbo, PJ. (2003a). Relative 

validation of a beverage frequency 

questionnaire in children ages 6 months 

through 5 years using 3-day food and 

beverage diaries. J Am Diet Assoc 103: 714­

720; discussion 720. 

http://dx.doi.org/10.1053/jada.2003.50137. 

Marshall, TA; Levy, SM; Broffitt, B; EichenbergerGilmore, JM; Stumbo, PJ. (2003b). Patterns 

of beverage consumption during the 

transition stage of infant nutrition. J Am Diet 

Assoc 103: 1350-1353. 

McNall, PE; Schlegel, JC. (1968). Practical thermal 

environmental limits for young adult males 

working in hot, humid environments. In 

ASHRAE Transactions 74: American 

Society of Heating, Refrigerating and Air 

Conditioning Engineers. 

NCHS (National Center for Health Statistics). (1993). 

Joint policy on variance estimation and 

statistical reporting standards on NHANES 

III and CSFII reports: HNIS/NCHS Analytic 

Working Group recommendations. 

Riverdale, MD: Human Nutrition 

Information Service (HNIS)/Analytic 

Working Group. Agricultural Research 

Service, Survey Systems/Food Consumption 

Laboratory. 

NRC (National Research Council). (1974).
 

Recommended dietary allowances.
 

NRC (National Research Council). (1977). Drinking
 

water and health. Washington, DC.
 

Page Exposure Factors Handbook 

3-26 September 2011 
Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-27 

Pennington, JAT. (1983). Revision of the total diet 

study food list and diets. J Am Diet Assoc 

82: 166-173. 

Pike, RL; Brown, M. (1975). Minerals and water in 

nutrition—an integrated approach (2nd ed.). 

New York, NY: John Wiley & Sons. 

Randall, HT. (1973). Water, electrolytes and acid base 

balance. In Modern nutrition in health and 

disease. Philadelphia, PA: Lea and Febiger. 

Roseberry, AM; Burmaster, DE. (1992). Lognormal 

distributions for water intake by children 

and adults. Risk Anal 12: 99-104. 

Schets, FM; Schijven, JF; de Roda Husman, AM. 

(2011). Exposure assessment for swimmers 

in bathing waters and swimming pools. 

Water Res 45: 2392-2400. 

http://dx.doi.org/10.1016/j.watres.2011.01.0 

25. 

Schijven, J; de Roda Husman, AM. (2006). A survey 

of diving behaviour and accidental water 

ingestion among Dutch occupational and 

sport divers to assess the risk of infection 

with waterborne pathogenic

microorganisms. Environ Health Perspect 

114: 712-717. 

Sichert-Hellert, W; Kersting, M; Manz, F. (2001). 

Fifteen year trends in water intake in 

German children and adolescents: results of 

the DONALD Study. Dortmund Nutritional 

and Anthropometric Longitudinally

Designed Study. Acta Paediatr 90: 732-737. 

Skinner, JD; Ziegler, P; Ponza, M. (2004). Transitions 

in infants' and toddlers' beverage patterns. J 

Am Diet Assoc 104: s45-s50. 

http://dx.doi.org/10.1016/j.jada.2003.10.027. 

Sohn, W; Heller, KE; Burt, BA. (2001). Fluid 

consumption related to climate among 

children in the United States. J Public Health 

Dent 61: 99-106. 

Starling, EH. (1941). Starling’s principles of human 

physiology. In th (Ed.), (Evans, CL ed.). 

London, England: Churchill. 

U.S. Army.	 (1983). Water consumption planning 

factors study. Fort Lee, VA: Directorate of 

Combat Developments, U.S. Army 

Quartermaster School. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1984). An estimation of the daily average 

food intake by age and sex for use in 

assessing the radionuclide intake of 

individuals in the general population. (EPA520/1-84-021). 

U.S. EPA (U.S. Environmental Protection Agency). 

(1996). Descriptive statistics from a detailed 

analysis of the National Human Activity 

Pattern Survey (NHAPS) responses. 

(EPA/600/R-96/148). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000). Methodology for deriving ambient 

water quality criteria for the protection of 

human health (2000) [EPA Report]. (EPA822-B-00-004). Washington, DC. 

http://water.epa.gov/scitech/swguidance/stan 

dards/criteria/health/methodology/index.cfm 

. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2002). Drinking water from household 

wells. (EPA/816/K-02/003). Washington, 

DC: U.S. Environmental Protection Agency; 

Office of Water. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2004). Estimated per capita water ingestion 

and body weight in the United States: An 

update. (EPA-822/R-00-001). Washington, 

DC: U.S. Environmental Protection Agency, 

Office of Water, Office of Science and 

Technology. 

http://water.epa.gov/action/advisories/drinki 

ng/upload/2005_05_06_criteria_drinking_pe 

rcapita_2004.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

USDA (U.S. Department of Agriculture). (1995). 

Food and nutrient intakes by individuals in 

the United States, 1 day, 1989–91. 

Washington, DC.

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/csfii8991_rep_91-2.pdf. 

USDA (U.S. Department of Agriculture). (2000). 

1994-1996, 1998 continuing survey of food 

intakes by individuals (CSFII). Beltsville, 

MD: Agricultural Research Service, 

Beltsville Human Nutrition Research Center. 

Walker, BS; Boyd, WC; Asimov, I. (1957). 

Biochemistry and human metabolism (2nd 

ed.). Baltimore, MD: Williams and Wilkins, 

Co. 

Wolf, AV. (1958). Body water content. Sci Am 199: 

125-126. 
 

 

 

 

 

 

 

 

 

 

 

 

Table 3-7. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Community Water (mL/day) 

Age Sample 

Size Mean Percentile 

10 25 50 75 90 95 99 

Birth to <1 month 91 184 - - - 322 687* 839* 860* 

1 to <3 months 253 227 - - - 456 804 896* 1,165* 

3 to <6 months 428 362 - - 148 695 928 1,056 1,424* 

6 to <12 months 714 360 - 17 218 628 885 1,055 1,511* 

1 to <2 years 1,040 271 - 60 188 402 624 837 1,215* 

2 to <3 years 1,056 317 - 78 246 479 683 877 1,364* 

3 to <6 years 4,391 380 4 98 291 547 834 1,078 1,654 

6 to <11 years 1,670 447 22 133 350 648 980 1,235 1,870* 

11 to <16 years 1,005 606 30 182 459 831 1,387 1,727 2,568* 

16 to <18 years 363 731 16 194 490 961 1,562 1,983* 3,720* 

18 to <21 years 389 826 24 236 628 1,119 1,770 2,540* 3,889* 

>21 years 9,207 1,104 69 422 928 1,530 2,230 2,811 4,523 

>65 yearsc 2,170 1,127 16 545 1,067 1,601 2,139 3,551 3,661 

All ages 20,607 926 30 263 710 1,311 2,014 2,544 4,242 a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. c U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (FASEB/LSRO, 1995). 

Source: Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-28 September 2011 
 

 

 

 

 

 

 

 

 

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Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-8. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Bottled Water (mL/day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 91 104 - - - 18 437* 556* 1,007* 

1 to <3 months 253 106 - - - - 541 771* 1,056* 

3 to <6 months 428 120 - - - - 572 774 1,443* 

6 to <12 months 714 120 - - - 53 506 761 1,284* 

1 to <2 years 1,040 59 - - - - 212 350 801* 

2 to <3 years 1,056 76 - - - - 280 494 1,001* 

3 to <6 years 4,391 84 - - - - 325 531 1,031* 

6 to <11 years 1,670 84 - - - - 330 532 1,079* 

11 to <16 years 1,005 111 - - - - 382 709 1,431* 

16 to <18 years 363 109 - - - - 426 680* 1,605* 

18 to <21 years 389 185 - - - - 514 1,141* 2,364* 

>21 years 9,207 189 - - - - 754 1,183 2,129 

>65 yearsc 2,170 136 - - - - 591 1,038 1,957 

All ages 20,607 163 - - - - 592 1,059 2,007 a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook Page
 

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c 

Table 3-9. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Other Sources (mL/day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 91 13 - - - - - - 393* 

1 to <3 months 253 35 - - - - - 367* 687* 

3 to <6 months 428 45 - - - - - 365 938* 

6 to <12 months 714 45 - - - - 31 406 963* 

1 to <2 years 1,040 22 - - - - - 118 482* 

2 to <3 years 1,056 39 - - - - 52 344 718* 

3 to <6 years 4,391 43 - - - - 58 343 830 

6 to <11 years 1,670 61 - - - - 181 468 1,047* 

11 to <16 years 1,005 102 - - - - 344 786 1,698* 

16 to <18 years 363 97 - - - - 295 740* 1,760* 

18 to <21 years 389 47 - - - - - 246* 1,047* 

>21 years 9,207 156 - - - - 541 1,257 2,381 

>65 yearsc 2,170 171 - - - - 697 1,416 2,269 

All ages 20,607 128 - - - - 345 1,008 2,151 a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

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c 

Table 3-10. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: All Sources (mL/day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 91 301 - - 135 542 846* 877* 1,088* 

1 to <3 months 253 368 - - 267 694 889 1,020* 1,265* 

3 to <6 months 428 528 - 89 549 812 1,025 1,303 1,509* 

6 to <12 months 714 530 37 181 505 771 1,029 1,278 1,690* 

1 to <2 years 1,040 358 68 147 287 477 735 961 1,281* 

2 to <3 years 1,056 437 104 211 372 588 825 999 1,662* 

3 to <6 years 4,391 514 126 251 438 681 980 1,200 1,794 

6 to <11 years 1,670 600 169 304 503 803 1,130 1,409 2,167* 

11 to <16 years 1,005 834 224 401 663 1,099 1,649 1,960 3,179* 

16 to <18 years 363 964 236 387 742 1,273 1,842 2,344* 3,854* 

18 to <21 years 389 1,075 189 406 803 1,394 2,117 2,985* 4,955* 

>21 years 9,207 1,466 500 828 1,278 1,871 2,553 3,195 5,174 

>65 yearsc 2,170 1,451 651 935 1,344 1,832 2,323 2,708 3,747 

All ages 20,607 1,233 285 573 1,038 1,633 2,341 2,908 4,805 a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-31 
 

 

 

 

 

c 

Table 3-11. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Community Water (mL/kg-day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 88 52 - - - 101 196* 232* 253* 

1 to <3 months 245 48 - - - 91 151 205* 310* 

3 to <6 months 411 52 - - 20 98 135 159 216* 

6 to <12 months 678 41 - 2 24 71 102 126 185* 

1 to <2 years 1,002 23 - 5 17 34 53 71 106* 

2 to <3 years 994 23 - 6 17 33 50 60 113* 

3 to <6 years 4,112 22 - 6 17 31 48 61 93 

6 to <11 years 1,553 16 1 5 12 22 34 43 71* 

11 to <16 years 975 12 1 4 9 16 25 34 54* 

16 to <18 years 360 11 - 3 8 15 23 31* 55* 

18 to <21 years 383 12 1 4 10 16 17 35* 63* 

>21 years 9,049 15 1 6 12 21 31 39 62 

>65 yearsc 2,139 16 - 7 15 23 31 37 52 

All ages 19,850 16 1 5 12 21 32 43 75 a Includes all participants whether or not they ingested any water from the source during survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-32 September 2011 
 

 

 

 

c 

Table 3-12. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Bottled Water (mL/kg-day) 

Sample	 Percentile 

Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 88 33 - - - 6 131* 243* 324* 

1 to <3 months 245 22 - - - - 97 161* 242* 

3 to <6 months 411 16 - - - - 74 117 193* 

6 to <12 months 678 13 - - - 4 52 87 139* 

1 to <2 years 1,002 5 - - - - 18 28 67* 

2 to <3 years 994 5 - - - - 19 35 84* 

3 to <6 years 4,112 5 - - - - 18 30 59 

6 to <11 years 1,553 3 - - - - 10 18 41* 

11 to <16 years 975 2 - - - - 8 14 26* 

16 to <18 years 360 2 - - - - 6 10* 27* 

18 to <21 years 383 3 - - - - 8 19* 34* 

>21 years 9.049 3 - - - - 10 17 32 

>65 yearsc 2,139 2 - - - - 9 15 27 

All ages 19,850 3 - - - - 10 18 39 a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-33 
 

 

 

 

 

c 

Table 3-13. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Other Sources (mL/kg-day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 88 4 - - - - - - 122* 

1 to <3 months 245 7 - - - - - 52* 148* 

3 to <6 months 411 7 - - - - - 55 155* 

6 to <12 months 678 5 - - - - 3 35 95* 

1 to <2 years 1,002 2 - - - - - 11 45* 

2 to <3 years 994 3 - - - - 4 23 61* 

3 to <6 years 4,112 2 - - - - 3 19 48 

6 to <11 years 1,553 2 - - - - 7 16 36* 

11 to <16 years 975 2 - - - - 7 14 34* 

16 to <18 years 360 2 - - - - 5 11* 27* 

18 to <21 years 383 1 - - - - - 4* 14* 

>21 years 9,049 2 - - - - 7 17 33 

>65 yearsc 2,139 2 - - - - 10 20 35 

All ages 19,850 2 - - - - 6 16 35 a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-34 September 2011 
 

 

 

 

c 

Table 3-14. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: All Sources (mL/kg-day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 88 89 - - 21 168 235* 269* 338* 

1 to <3 months 245 77 - - 46 134 173 246* 336* 

3 to <6 months 411 75 - 9 73 118 156 186 225* 

6 to <12 months 678 59 4 20 53 86 118 148 194* 

1 to <2 years 1,002 31 6 13 24 39 63 85 122* 

2 to <3 years 994 31 7 15 26 41 59 73 130* 

3 to <6 years 4,112 29 7 14 25 38 56 69 102 

6 to <11 years 1,553 21 6 10 18 27 39 50 76* 

11 to <16 years 975 16 4 8 13 20 31 39 60* 

16 to <18 years 360 15 4 6 12 18 28 37* 59* 

18 to <21 years 383 16 3 6 12 21 32 41* 73* 

>21 years 9,049 20 7 11 17 26 36 44 68 

>65 yearsc 2,139 21 9 13 19 27 34 39 54 

All ages 20,850 21 6 10 17 26 38 50 87 a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- = Zero. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-35 
 

 

 

 

Table 3-15. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Community Water (mL/day) 

Age Sample 

Size Mean Percentile 

10 25 50 75 90 95 99 

Birth to <1 month 40 470* 32* 215* 482* 692* 849* 858* 919* 

1 to <3 months 114 552 67* 339 533 801 943* 1,053* 1,264* 

3 to <6 months 281 556 44 180 561 837 1,021 1,171* 1,440* 

6 to <12 months 562 467 44 105 426 710 971 1,147 1,586* 

1 to <2 years 916 308 43 107 229 428 674 893 1,248* 

2 to <3 years 934 356 49 126 281 510 700 912 1,388* 

3 to <6 years 3,960 417 57 146 336 581 867 1,099 1,684 

6 to <11 years 1,555 480 74 177 373 682 994 1,251 2,024* 

11 to <16 years 937 652 106 236 487 873 1,432 1,744 2,589* 

16 to <18 years 341 792 106 266 591 987 1,647 2,002* 3,804* 

18 to <21 years 364 895 114 295 674 1,174 1,860 2,565* 3,917* 

>21 years 8,505 1,183 208 529 1,006 1,582 2,289 2,848 4,665 

>65 yearsc 1,958 1,242 310 704 1,149 1,657 2,190 2,604 3,668 

All ages 18,509 1,000 127 355 786 1,375 2,069 2,601 4,274 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. c U.S. EPA (2004). 

* The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (FASEB/LSRO, 1995). 

Source: Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-36 September 2011 
 

 

 

 

 

c 

Table 3-16. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Bottled Water (mL/day) 

Sample	 Percentile Age	 Mean size 10 25 50 75 90 95 99 

Birth to <1 month 25 - - - - - - - ­

1 to <3 months 64 450* 31* 62* 329* 743* 886* 1,045* 1,562* 

3 to <6 months 103 507 48* 88 493 747 1,041* 1,436* 1,506* 

6 to <12 months 200 425 47 114 353 630 945* 1,103* 1,413* 

1 to <2 years 229 262 45 88 188 324 600 709* 1,083* 

2 to <3 years 232 352 57 116 241 471 736 977* 1,665* 

3 to <6 years 1,021 380 72 149 291 502 796 958 1,635* 

6 to <11 years 332 430 88 168 350 557 850 1,081* 1,823* 

11 to <16 years 192 570 116* 229 414 719 1,162* 1,447* 2,705* 

16 to <18 years 63 615* 85* 198* 446* 779* 1,365* 1,613* 2,639* 

18 to <21 years 97 769 118* 236 439 943 1,788* 2,343* 3,957* 

>21 years 1,893 831 167 354 650 1,071 1,773 2,093 3,505 

>65 yearsc 302 910 234 465 785 1,182 1,766 2,074 2,548 

All ages 4,451 736 118 266 532 975 1,567 1,964 3,312 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- Insufficient sample size to estimate mean and percentiles. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-37 
 

 

 

 

 

 

 

 

 

 

c 

Table 3-17. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: Other Sources (mL/day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 3 - - - - - - - ­

1 to <3 months 19 - - - - - - - ­

3 to <6 months 38 562* 59* 179* 412* 739* 983* 1,205* 2,264* 

6 to <12 months 73 407* 31* 121* 300* 563* 961* 1,032* 1,144* 

1 to <2 years 98 262 18* 65 143 371 602* 899* 1,204* 

2 to <3 years 129 354 56* 134 318 472 704* 851* 1,334* 

3 to <6 years 533 396 59 148 314 546 796 1,019 1,543* 

6 to <11 years 219 448 89 177 347 682 931 1,090* 1,596* 

11 to <16 years 151 687 171* 296 482 947 1,356* 1,839* 2,891* 

16 to <18 years 53 657* 152* 231* 398* 823* 1,628* 1,887* 2,635* 

18 to <21 years 33 569* 103* 142* 371* 806* 1,160* 1,959* 1,962* 

>21 years 1,386 1,137 236 503 976 1,533 2,161 2,739 4,673 

>65 yearsc 323 1,259 360 680 1,188 1,660 2,136 2,470 3,707* 

All ages 2,735 963 148 347 741 1,344 1,970 2,468 3,814 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- Insufficient sample size to estimate means and percentiles. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-38 September 2011 
 

 

 

 

 

 

 

 

 

c 

Table 3-18. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on 

1994–1996, 1998 CSFII: All Sources (mL/day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 58 511* 51* 266* 520* 713* 858* 986* 1,274* 

1 to <3 months 178 555 68* 275 545 801 946* 1,072* 1,470* 

3 to <6 months 363 629 69 384 612 851 1,064 1,330* 1,522* 

6 to <12 months 667 567 90 250 551 784 1,050 1,303 1,692* 

1 to <2 years 1,017 366 84 159 294 481 735 978 1,281* 

2 to <3 years 1,051 439 105 213 375 589 825 1,001 1,663* 

3 to <6 years 4,350 518 134 255 442 682 980 1,206 1,796 

6 to <11 years 1,659 603 177 310 506 805 1,131 1,409 2,168* 

11 to <16 years 1,000 837 229 404 665 1,105 1,649 1,961 3,184* 

16 to <18 years 357 983 252 395 754 1,276 1,865 2,346* 3,866* 

18 to <21 years 383 1,094 219 424 823 1,397 2,144 3,002* 4,967* 

>21 years 9,178 1,472 506 829 1,282 1,877 2,559 3,195 5,175 

>65 yearsc 2,167 1,453 651 939 1,345 1,833 2,324 2,708 3,750 

All ages 20,261 1,242 296 585 1,047 1,642 2,345 2,923 4,808 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-39 
 

 

 

 

 

 

 

 

 

 

c 

Table 3-19. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on 1994–1996, 

1998 CSFII: Community Water (mL/kg-day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 37 137* 11* 65* 138* 197* 235* 238* 263* 

1 to <3 months 108 119 12* 71 107 151 228* 285* 345* 

3 to <6 months 269 80 7 27 77 118 148 173* 222* 

6 to <12 months 534 53 5 12 47 81 112 129 186* 

1 to <2 years 880 27 4 9 20 36 56 75 109* 

2 to <3 years 879 26 4 9 21 36 52 62 121* 

3 to <6 years 3,703 24 3 8 19 33 49 65 97 

6 to <11 years 1,439 17 3 6 13 23 35 45 72* 

11 to <16 years 911 13 2 5 10 17 26 34 54* 

16 to <18 years 339 12 1 4 9 16 24 32* 58* 

18 to <21 years 361 13 2 5 10 17 29 35* 63* 

>21 years 8,355 16 3 7 13 22 32 39 63 

>65 yearsc 1,927 18 5 10 16 24 32 37 53 

All ages 17,815 17 3 7 13 22 33 44 77 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-40 September 2011 
 

 

 

 

 

 

 

 

 

 

99 

c 

Table 3-20. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on 1994–1996, 

1998 CSFII: Bottled Water (mL/kg-day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 

Birth to <1 month 25 - - - - - - - ­

1 to <3 months 64 92* 7* 12* 76* 151* 164* 220* 411* 

3 to <6 months 95 72 6* 15 69 100 149* 184* 213* 

6 to <12 months 185 47 5* 11 34 73 104* 120* 166* 

1 to <2 years 216 22 5 8 16 27 49 66* 103* 

2 to <3 years 211 25 4 8 17 35 54 81* 91* 

3 to <6 years 946 21 4 8 16 29 45 57 90* 

6 to <11 years 295 15 3 5 11 19 30 42* 69* 

11 to <16 years 180 11 2* 4 8 14 24* 27* 44* 

16 to <18 years 63 10* 1* 3* 7* 11* 23* 27* 37* 

18 to <21 years 93 11 2* 3 6 14 27* 30* 54* 

>21 years 1,861 12 2 5 9 16 25 31 45 

>65 yearsc 297 13 3 7 12 17 26 30 42* 

All ages 4,234 13 2 5 9 17 27 36 72 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- Insufficient sample size to estimate means and percentiles. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-41 
 

 

 

 

 

 

 

 

 

 

 

c 

Table 3-21. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on 1994–1996, 

1998 CSFII: Other Sources (mL/kg-day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 3 - - - - - - - ­

1 to <3 months 19 - - - - - - - ­

3 to <6 months 38 80* 10* 23* 59* 106* 170* 200* 246* 

6 to <12 months 68 44* 4* 10* 33* 65* 95* 106* 147* 

1 to <2 years 95 23 1* 5 13 28 46* 84* 125* 

2 to <3 years 124 26 4* 10 21 34 55* 66* 114* 

3 to <6 years 505 22 3 8 17 30 46 56 79* 

6 to <11 years 208 16 3 6 12 23 32 39* 62* 

11 to <16 years 148 13 3* 6 9 18 27* 36* 56* 

16 to <18 years 52 10* 2* 4* 7* 12* 24* 29* 43* 

18 to <21 years 33 8* 1* 2* 6* 10* 16* 27* 31* 

>21 years 1,365 15 3 6 13 21 30 39 58 

>65 yearsc 322 18 5 9 16 24 31 37 50* 

All ages 2,657 16 3 6 12 21 32 41 67 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

- Indicates insufficient sample size to estimate distribution percentiles. 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-42 September 2011 
 

 

 

 

 

 

 

 

c 

Table 3-22. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on 1994–1996, 

1998 CSFII: All Sources (mL/kg-day) 

Sample	 Percentile Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 55 153* 13* 83* 142* 208* 269* 273* 400* 

1 to <3 months 172 116 12* 50 107 161 216* 291* 361* 

3 to <6 months 346 90 9 52 86 125 161 195* 233* 

6 to <12 months 631 63 10 27 58 88 120 152 198* 

1 to <2 years 980 31 7 14 25 40 64 86 122* 

2 to <3 years 989 31 7 15 27 41 59 73 130* 

3 to <6 years 4,072 29 7 15 25 38 56 70 102* 

6 to <11 years 1,542 21 6 10 18 27 39 50 76* 

11 to <16 years 970 16 4 8 13 20 31 39 60* 

16 to <18 years 354 15 4 7 12 18 29 37* 60* 

18 to <21 years 378 16 3 6 12 21 32 41* 73* 

>21 years 9,020 20 7 11 17 26 36 44 68 

>65 yearsc 2,136 21 9 13 19 27 34 39 54 

All ages 19,509 21 6 11 17 26 38 50 87 a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

U.S. EPA (2004). 

* The sample size does not meet minimum requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source:	 Kahn (2008) (Based on 1994–1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-43 
 

 

 

 

 

Table 3-23. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: Community Water (mL/day)
 

Percentile Sample Age	 Mean Size 10	 25 50 75 90 95 99 

Birth to <1 month 88 239* - - 78* 473* 693* 851* 956* 

1 to <3 months 143 282* - - 41* 524* 784* 962* 1,102* 

3 to <6 months 244 373* - - 378* 630* 794* 925* 1,192* 

6 to <12 months 466 303 - 46 199 520 757* 866* 1,150* 

1 to <2 years 611 223 - 27 134 310 577* 760* 1,206* 

2 to <3 years 571 265 - 39 160 387 657* 861* 1,354* 

3 to <6 years 1,091 327 - 67 245 465 746 959 1,570* 

6 to <11 years 1,601 414 - 64 297 598 1,000 1,316 2,056* 

11 to <16 years 2,396 520 - 60 329 688 1,338 1,821 2,953 

16 to <18 years 1,087 573 - 59 375 865 1,378 1,783 3,053 

18 to <21 years 1,245 681 - 88 355 872 1,808 2,368 3,911 

≥21 years 8,673 1,043 - 227 787 1,577 2,414 2,958 4,405 

≥65 years 2,287 1,046 - 279 886 1,587 2,272 2,730 4,123 

All ages 18,216 869 - 134 560 1,299 2,170 2,717 4,123 

a	 Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-44 September 2011 
 

 

Table 3-24. Per Capitaa Estimates of Combined Directb Water Ingestion Based on NHANES 

2003–2006: Bottled Water (mL/day) 

Percentile Sample Age	 Mean Size 10	 25 50 75 90 95 99 

Birth to <1 month 88 6* - - - - 8* 28* 59* 

1 to <3 months 143 21* - - - - 46* 122* 336* 

3 to <6 months 244 12* - - - - 27* 77* 184* 

6 to <12 months 466 34 - - - 26 118* 187* 422* 

1 to <2 years 611 65 - - - 82 230* 342* 586* 

2 to <3 years 571 95 - - - 81 303* 575* 1,136* 

3 to <6 years 1,091 108 - - - 118 355 526 883* 

6 to <11 years 1,601 138 - - - 172 444 696 1,138* 

11 to <16 years 2,396 202 - - - 259 612 938 1,630 

16 to <18 years 1,087 339 - - - 428 1,063 1,545 2,772 

18 to <21 years 1,245 391 - - - 497 1,174 1,697 2,966 

≥21 years 8,673 375 - - - 518 1,199 1,718 3,004 

≥65 years 2,287 152 - - - 9 533 948 2,288 

All ages 18,216 321 - - - 399 1,065 1,502 2,811 

a	 Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water, defined as water 

added in the preparation of food or beverages, was not accounted for in the estimation of bottled 

water intake. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-45 
 

 

 

 

Table 3-25. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: Other Sources (mL/day)
 

Age Sample 

Size Mean 

10 25 50 

Percentile 

75 90 95 99 

Birth to <1 month 88 51* - - - 92* 166* 229* 265* 

1 to <3 months 143 82* - - - 146* 243* 276* 544* 

3 to <6 months 244 141* - - 75* 211* 274* 329* 1,045* 

6 to <12 months 466 124 - - 15 173 297* 770* 1,078* 

1 to <2 years 611 82 - - 5 50 271* 479* 867* 

2 to <3 years 571 74 - - - 45 232* 459* 935* 

3 to <6 years 1,091 62 - - - 38 179 433 883* 

6 to <11 years 1,601 108 - - - 66 386 659 1,112* 

11 to <16 years 2,396 163 - - - 94 495 1,030 2,242 

16 to <18 years 1,087 201 - - - 105 603 1,231 2,581 

18 to <21 years 1,245 167 - - - 72 432 1,154 2,474 

≥21 years 8,673 282 - - - 151 972 1,831 3,289 

≥65 years 2,287 301 - - - 186 1,248 1,765 2,645 

All ages 18,216 237 - - - 123 747 1,480 3,095 

a	 Includes all participants whether or not they ingested any water from the source during survey 

period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-46 September 2011 
 

 

 

Table 3-26. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: All Sources (mL/day) 

Percentile Sample Age	 Mean Size 10	 25 50 75 90 95 99 

Birth to <1 month 88 295* - - 104* 504* 852* 954* 1,043* 

1 to <3 months 143 385* - - 169* 732* 1,049* 1,084* 1,265* 

3 to <6 months 244 527* - 24* 567* 889* 1,045* 1,192* 1,390* 

6 to <12 months 466 461 50 124 379 761 995* 1,126* 1,521* 

1 to <2 years 611 370 65 172 297 493 762* 912* 1,414* 

2 to <3 years 571 435 88 190 340 585 920* 1,086* 1,447* 

3 to <6 years 1,091 498 115 249 432 659 925 1,181 1,787* 

6 to <11 years 1,601 660 144 335 573 870 1,184 1,567 2,302* 

11 to <16 years 2,396 885 178 375 687 1,147 1,821 2,595 3,499 

16 to <18 years 1,087 1,113 239 441 951 1,512 2,289 2,652 3,781 

18 to <21 years 1,245 1,240 163 496 945 1,740 2,569 3,346 4,955 

≥21 years 8,673 1,700 491 922 1,509 2,257 3,085 3,727 5,252 

≥65 years 2,287 1,498 566 896 1,359 1,922 2,582 3,063 4,126 

All ages 18,216 1,426 281 607 1,201 1,967 2,836 3,412 4,943 

a	 Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-47 
 

 

Table 3-27. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on NHANES 2003–2006,
 

Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/day)
 

Mean	 90th percentile 95th percentile 

Sample 90% CI 90% BI	 90% BI Age Size Lower Upper Lower Upper	 Lower Upper Estimate	 Estimate Estimate 

Bound Bound Bound Bound	 Bound Bound 

Birth to <1 month 88 295* 208* 382* 852* 635* 941* 954* 759* 1,037* 

1 to <3 months 143 385* 325* 444* 1,049* 929* 1,074* 1,084* 1,036* 1,099* 

3 to <6 months 244 527* 466* 588* 1,045* 1,023* 1,126* 1,190* 1,088* 1,250* 

6 to <12 months 466 461 417 506 995* 903* 1,057* 1,126* 1,056* 1,212* 

1 to <2 years 611 370 339 401 762* 673* 835* 912* 838* 1,084* 

2 to <3 years 571 435 397 472 920* 836* 987* 1,086* 973* 1,235* 

3 to <6 years 1,091 498 470 526 925 888 1,009 1,181 1,068 1,250 

6 to <11 years 1,601 660 617 703 1,184 1,117 1,294 1,567 1,411 1,810 

11 to <16 years 2,396 885 818 952 1,821 1,678 2,114 2,595 2,280 2,807 

16 to <18 years 1,087 1,113 1,027 1,199 2,289 2,055 2,412 2,652 2,502 2,868 

18 to <21 years 1,245 1,240 1,128 1,352 2,569 2,377 2,991 3,346 3,044 3,740 

≥21 years 8,673 1,700 1,641 1,759 3,085 3,027 3,147 3,727 3,586 3,858 

≥65 years 2,287 1,498 1,442 1,555 2,582 2,470 2,671 3,063 2,961 3,328 

All ages 18,216 1,426 1,377 1,474 2,836 2,781 2,896 3,412 3,352 3,499 a	 Includes all participants whether or not they ingested any water from the source during survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of food or 

beverages. Does not include indirect consumption of bottled water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
 

CI = Confidence Interval.
 

BI = Bootstrap Interval.
 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Chapter 3—Water Ingestion 

Exposure Factors Handbook 

Page Child-Specific Exposure Factors Handbook 3-48 September 2011 
 

 

 

Table 3-28. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: Community Water (mL/kg-day) 

Sample Percentile 

Age	 Mean Size 10	 25 50 75 90 95 99 

Birth to <1 month 88 52* - - 16* 94* 144* 169* 210* 

1 to <3 months 143 49* - - 5* 92* 134* 164* 200* 

3 to <6 months 244 52* - - 53* 85* 116* 132* 177* 

6 to <12 months 466 34 - 5 21 56 85* 103* 133* 

1 to <2 years 611 20 - 2 12 28 53* 67* 115* 

2 to <3 years 571 19 - 3 12 27 48* 61* 102* 

3 to <6 years 1,091 18 - 4 13 27 41 51 81* 

6 to <11 years 1,601 14 - 2 9 20 32 43 75* 

11 to <16 years 2,396 10 - 1 6 13 23 32 61 

16 to <18 years 1,087 9 - 1 6 12 20 28 44 

18 to <21 years 1,245 9 - 1 5 13 23 35 53 

≥21 years 8,673 13 - 3 10 20 32 40 61 

≥65 years 2,287 14 - 4 12 21 32 40 59 

All ages 18,216 14 - 2 9.4 19 32 42 72 

a Includes all participants whether or not they ingested any water from the source during survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-49 
 

 

 

Table 3-29. Per Capitaa Estimates of Combined Directb Water Ingestion Based on NHANES 

2003–2006: Bottled Water (mL/kg-day) 

Age Sample 

Size Mean 

10 25 50 

Percentile 

75 90 95 99 

Birth to <1 month 88 1* - - - - 1* 7* 18* 

1 to <3 months 143 4* - - - - 8* 19* 60* 

3 to <6 months 244 2* - - - - 4* 11* 24* 

6 to <12 months 466 4 - - - 3 13* 22* 42* 

1 to <2 years 611 6 - - - 7 20* 30* 49* 

2 to <3 years 571 7 - - - 6 21* 40* 77* 

3 to <6 years 1,091 6 - - - 7 19 31 53* 

6 to <11 years 1,601 4 - - - 5 13 24 38* 

11 to <16 years 2,396 4 - - - 5 11 17 25 

16 to <18 years 1,087 5 - - - 6 16 24 42 

18 to <21 years 1,245 5 - - - 7 17 24 45 

≥21 years 8,673 5 - - - 7 15 22 39 

≥65 years 2,287 2 - - - 0 7 13 29 

All ages 18,216 5 - - - 6 15 22 40 

a	 Includes all participants whether or not they ingested any water from the source during survey 

period. b	 Direct water is defined as water ingested directly as a beverage; indirect water, defined as water 

added in the preparation of food or beverages, was not accounted for in the estimation of bottled 

water intake. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3— Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-50 September 2011 
 

 

 

Table 3-30. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: Other Sources (mL/kg-day) 

Percentile Sample Age	 Mean Size 10	 25 50 75 90 95 99 

Birth to <1 month 88 11* - - - 22* 34* 45* 53* 

1 to <3 months 143 14* - - - 30* 39* 49* 81* 

3 to <6 months 244 20* - - 9* 29* 44* 60* 142* 

6 to <12 months 466 14 - - 2 18 35* 74* 137* 

1 to <2 years 611 7 - - 1 5 24* 43* 75* 

2 to <3 years 571 6 - - - 3 17* 34* 69* 

3 to <6 years 1,091 3 - - - 2 11 22 47* 

6 to <11 years 1,601 4 - - - 2 13 23 42* 

11 to <16 years 2,396 3 - - - 2 9 16 35 

16 to <18 years 1,087 3 - - - 1 9 19 32 

18 to <21 years 1,245 2 - - - 1 5 15 34 

≥21 years 8,673 4 - - - 2 12 23 45 

≥65 years 2,287 4 - - - 3 17 23 37 

All ages 18,216 4 - - - 2 12 23 45 

a Includes all participants whether or not they ingested any water from the source during survey 

period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-51 
 

 

 

 

Table 3-31. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: All Sources (mL/kg-day)
 

Age Sample 

Size Mean 

10 25 50 

Percentile 

75 90 95 99 

Birth to <1 month 88 65* - - 19* 120* 173* 195* 247* 

1 to <3 months 143 67* - - 29* 123* 180* 194* 230* 

3 to <6 months 244 74* - 4* 72* 116* 153* 179* 228* 

6 to <12 months 466 52 6 14 42 84 113* 137* 181* 

1 to <2 years 611 33 6 15 26 44 68* 80* 122* 

2 to <3 years 571 32 6 15 25 42 67* 78* 123* 

3 to <6 years 1,091 27 7 13 23 36 52 63 96* 

6 to <11 years 1,601 22 5 11 18 28 42 52 78* 

11 to <16 years 2,396 16 3 7 13 20 33 44 66 

16 to <18 years 1,087 16 4 7 14 22 33 43 58 

18 to <21 years 1,245 17 2 6 13 23 36 44 82 

≥21 years 8,673 22 6 11 19 29 41 50 70 

≥65 years 2,287 20 7 11 18 26 36 45 61 

All ages 18,216 22 5 11 18 29 43 53 84 

a	 Includes all participants whether or not they ingested any water from the source during survey 

period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

- = Zero. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3— Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-52 September 2011 
 

Table 3-32. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion Based on NHANES 2003–2006, 

Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/kg-day) 

Mean 90th percentile 95th percentile 

Sample 90% CI 90% BI 90% BI Age Size Lower Upper Lower Upper Lower Upper Estimate Estimate Estimate Bound Bound Bound Bound Bound Bound 

Birth to <1 month 88 65* 45* 84* 173* 128* 195* 195* 168* 216* 

1 to <3 months 143 67* 55* 78* 180* 152* 193* 194* 164* 204* 

3 to <6 months 244 74* 65* 82* 153* 140* 178* 179* 157* 195* 

6 to <12 months 466 52 47 57 113* 105* 124* 137* 123* 145* 

1 to <2 years 611 33 30 36 68* 62* 73* 80* 73* 96* 

2 to <3 years 571 32 29 35 67* 59* 72* 78* 71* 91* 

3 to <6 years 1,091 27 25 29 52 47 54 63 57 68 

6 to <11 years 1,601 22 20 23 42 39 46 52 49 55 

11 to <16 years 2,396 16 15 17 33 30 37 44 38 53 

16 to <18 years 1,087 16 15 18 33 29 35 43 36 45 

18 to <21 years 1,245 17 15 19 36 33 39 44 41 47 

≥21 years 8,673 22 21 23 41 40 42 50 48 51 

≥65 years 2,287 20 20 21 36 34 38 45 42 46
 

All ages 18,216 22 21 23 43 42 44 53 51 54
 a Includes all participants whether or not they ingested any water from the source during survey period.
 b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of food or
 

beverages. Does not include indirect consumption of bottled water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
 

CI = Confidence Interval.
 

BI = Bootstrap Interval.
 

Source: U.S. EPA analysis of NHANES 2003–2006 data. 

Child-Specific Exposure Factors Handbook ChildChapter 3—Water Ingestion 

-Specific Exposure Factors Handbook Page 

September 2011 3-53 
 

 

 

Table 3-33. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on
 

NHANES 2003–2006: Community Water (mL/day)
 

Age Sample 

size Mean 

10 25 50 

Percentile 

75 90 95 99 

Birth to <1 month 51 409* 72* 172* 399* 492* 851* 852* 990* 

1 to <3 months 85 531* 103* 341* 513* 745* 957* 1,019* 1,197* 

3 to <6 months 192 520* 89* 312* 530* 739* 880* 929* 1,248* 

6 to <12 months 416 356 43* 94 270 551 772* 948* 1,161* 

1 to <2 years 534 277 36* 88 199 377 627* 781* 1,277* 

2 to <3 years 508 321 43* 105 227 448 722* 911* 1,374* 

3 to <6 years 985 382 53 137 316 515 778 999 1,592* 

6 to <11 years 1,410 511 79 178 413 690 1,072 1,404 2,099* 

11 to <16 years 2,113 637 77 192 436 808 1,535 1,976 3,147 

16 to <18 years 944 702 97 236 515 966 1,571 1,883 3,467 

18 to <21 years 1,086 816 88 216 503 1,065 1,921 2,818 4,106 

≥21 years 7,616 1,227 192 469 991 1,741 2,546 3,092 4,576 

≥65 years 1,974 1,288 325 628 1,137 1,760 2,395 2,960 4,137 

All ages 15,940 1,033 124 333 743 1,474 2,318 2,881 4,312 

a	 Excludes individuals who did not ingest water from the source during the survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-54 September 2011 
 

 

Table 3-34. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: Bottled Water (mL/day) 

Sample	 Percentile 

Age	 Mean size 10	 25 50 75 90 95 99 

Birth to <1 month 11 55* 15* 20* 27* 46* 59* 190* 275* 

1 to <3 months 28 135* 13* 31* 58* 145* 309* 347* 377* 

3 to <6 months 65 69* 10* 15* 35* 84* 156* 202* 479* 

6 to <12 months 190 111* 13* 30* 58* 147* 261* 359* 627* 

1 to <2 years 247 193* 43* 73* 126* 277* 385* 474* 682* 

2 to <3 years 220 276* 38* 74* 155* 333* 681* 1,000* 1,315* 

3 to <6 years 430 297 72 118 207 389 615 825* 1,305* 

6 to <11 years 661 350 81 118 236 445 740 898* 1,934* 

11 to <16 years 1,171 477 116 215 333 595 1,000 1,297 1,990 

16 to <18 years 549 726 151 252 467 893 1,609 2,121 3,096* 

18 to <21 years 662 783 178 255 497 1,019 1,698 2,324 3,824 

≥21 years 3,836 840 162 281 637 1,137 1,777 2,363 3,665 

≥65 years 7,442 749 100 178 409 824 1,346 1,940 2,717 

All ages 8,070 738 118 237 500 999 1,640 2,133 3,601 

a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water, defined as water 

added in the preparation of food or beverages, was not accounted for in the estimation of bottled 

water intake. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993) . 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-55 
 

 

 

Table 3-35. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on
 

NHANES 2003–2006: Other Sources (mL/day)
 

Age Sample 

Size Mean 

10 25 50 

Percentile 

75 90 95 99 

Birth to <1 month 41 121* 25* 59* 112* 166* 234* 246* 269* 

1 to <3 months 67 187* 33* 120* 177* 236* 278* 400* 612* 

3 to <6 months 160 237* 42* 130* 194* 265* 325* 730* 1,184* 

6 to <12 months 287 223* 15* 46* 139* 235* 736* 877* 1,203* 

1 to <2 years 312 155 9* 20 47 196 474* 628* 1,047* 

2 to <3 years 256 163* 9* 19* 50* 214* 482* 798* 1,070* 

3 to <6 years 449 155 9 22 57 178 485 631* 999* 

6 to <11 years 609 270 16 40 124 386 814 1,065* 1,183* 

11 to <16 years 1,116 367 15 44 131 451 1,044 1,467 2,376 

16 to <18 years 467 457 12 49 133 530 1,368 2,159 3,122* 

18 to <21 years 572 417 17 50 106 432 1,505 2,131 2,831* 

≥21 years 3,555 672 32 80 216 926 1,980 2,774 4,285 

≥65 years 834 816 64 143 546 1,319 1,923 2,309 3,283* 

All ages 7,891 559 22 62 179 689 1,731 2,381 3,798 

a	 Excludes individuals who did not ingest water from the source during the survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993) . 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-56 September 2011 
 

 

 

Table 3-36. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on 

NHANES 2003–2006: All Sources (mL/day) 

Sample Percentile 

Age	 Mean Size 10 25 50 75 90 95 99 

Birth to <1 month 54 481* 74* 217* 473* 658* 921* 996* 1,165* 

1 to <3 months 92 665* 103* 457* 704* 1,014* 1,076* 1,099* 1,328* 

3 to <6 months 209 660* 55* 379* 685* 965* 1,101* 1,215* 1,450* 

6 to <12 months 453 477 64* 152 393 765 1,021* 1,128* 1,526* 

1 to <2 years 596 378 78* 173 300 497 772* 914* 1,421* 

2 to <3 years 560 441 95* 203 341 589 920* 1,087* 1,450* 

3 to <6 years 1,077 506 130 259 437 665 933 1,182 1,787* 

6 to <11 years 1,580 666 155 348 574 875 1,186 1,585 2,305* 

11 to <16 years 2,362 898 217 385 689 1,149 1,829 2,600 3,499 

16 to <18 years 1,059 1,138 259 499 973 1,519 2,298 2,672 3,788 

18 to <21 years 1,210 1,277 250 528 986 1,754 2,617 3,358 4,964 

≥21 years 8,608 1,712 509 934 1,516 2,258 3,091 3,733 5,253 

≥65 years 2,281 1,503 573 898 1,361 1,925 2,585 3,066 4,126 

All ages 17,860 1,444 304 623 1,218 1,981 2,842 3,422 4,960 

a	 Excludes individuals who did not ingest water from the source during the survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993) . 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-57 
 

 

 

Table 3-37. Consumer-Onlya Estimates of Combined Direct and Indirectb Water Ingestion Based on NHANES 2003–2006,
 

Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/day)
 

Mean	 90th percentile 95th percentile 

Sample 90% CI	 90% BI 90% BI Age Size 

Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper 

Bound Bound	 Bound Bound Bound Bound 

Birth to <1 month 54 481* 396* 566* 921* 715* 993* 996* 853* 1,041* 

1 to <3 months 92 665* 626* 704* 1,076* 1,030* 1,097* 1,099* 1,073* 1,215* 

3 to <6 months 209 660* 596* 724* 1,101* 1,032* 1,189* 1,215* 1,137* 1,256* 

6 to <12 months 453 477 432 523 1,021* 906* 1,057* 1,128* 1,057* 1,238* 

1 to <2 years 596 378 347 409 772* 674* 838* 914* 837* 1,086* 

2 to <3 years 560 441 403 479 920* 837* 994* 1,087* 970* 1,242* 

3 to <6 years 1,077 506 479 534 933 898 1,017 1,182 1,078 1,253 

6 to <11 years 1,580 666 624 708 1,186 1,114 1,300 1,585 1,414 1,812 

11 to <16 years 2,362 898 832 963 1,829 1,700 2,169 2,600 2,322 2,805 

16 to <18 years 1,059 1,138 1,052 1,224 2,298 2,052 2,421 2,672 2,514 2,888 

18 to <21 years 1,210 1,277 1,164 1,389 2,617 2,389 3,030 3,358 3,059 3,790 

≥21 years 8,608 1,712 1,654 1,771 3,091 3,034 3,149 3,733 3,585 3,861 

≥65 years 2,281 1,503 1,446 1,560 2,585 2,471 2,688 3,066 2,961 3,316 

All ages 17,860 1,444 1,395 1,492 2,842 2,796 2,917 3,422 3,363 3,510 a	 Excludes individuals who did not ingest water from the source during the survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of 

food or beverages. Does not include indirect consumption of bottled water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical 

Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 

1993). 

CI = Confidence Interval.
 

BI = Bootstrap Interval.
 

Source: U.S. EPA analysis of NHANES 2003–2006 data. 

Child-Specific Exposure Factors Handbook 

Chapter 3—Water Ingestion 

Page Exposure Factors Handbook 3-58 September 2011 
 

 

Table 3-38. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on NHANES 

2003–2006: Community Water (mL/kg-day) 

Percentile Sample Age	 Mean Size 10	 25 50 75 90 95 99 

Birth to <1 month 51 90* 13* 40* 89* 120* 167* 172* 228* 

1 to <3 months 85 93* 17* 62* 91* 118* 163* 186* 210* 

3 to <6 months 192 73* 10* 45* 74* 100* 128* 140* 191* 

6 to <12 months 416 40 5* 10 30 64 87* 104* 135* 

1 to <2 years 534 25 3* 8 17 31 56* 71* 117* 

2 to <3 years 508 23 3* 8 16 33 52* 62* 108* 

3 to <6 years 985 21 3 8 17 29 43 52 83* 

6 to <11 years 1,410 17 2 6 13 23 35 47 78* 

11 to <16 years 2,113 12 1 4 8 15 26 35 62 

16 to <18 years 944 10 1 4 8 15 23 30 47 

18 to <21 years 1,086 11 1 3 7 15 26 36 58 

≥21 years 7,616 16 2 6 12 22 34 42 64 

≥65 years 1,974 18 4 8 15 23 34 43 60 

All ages 15,940 16 2 6 12 22 35 44 76 

a Excludes individuals who did not ingest water from the source during the survey period. b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-59 
 

 

 

Table 3-39. Consumer-Onlya Estimates of Directb Water Ingestion Based on NHANES 2003–2006:
 

Bottled Water (mL/kg-day)
 

Age Sample 

Size Mean 

10 25 50 

Percentile 

75 90 95 99 

Birth to <1 month 11 12* 3* 6* 7* 8* 17* 38* 58* 

1 to <3 months 28 24* 2* 6* 9* 23* 55* 63* 68* 

3 to <6 months 65 10* 2* 2* 5* 11* 21* 27* 81* 

6 to <12 months 190 12* 2* 4* 7* 16* 29* 36* 63* 

1 to <2 years 247 17* 4* 7* 13* 23* 35* 44* 62* 

2 to <3 years 220 20* 3* 5* 11* 23* 48* 68* 111* 

3 to <6 years 430 16 4 7 11 20 34 47* 67* 

6 to <11 years 661 11 2 4 7 13 26 31* 60* 

11 to <16 years 1,171 9 2 4 6 11 19 23 35 

16 to <18 years 549 11 2 4 7 14 24 34 58* 

18 to <21 years 662 11 3 4 7 14 24 33 52 

≥21 years 3,836 11 2 3 8 14 23 29 51 

≥65 years 7,442 11 1 2 6 11 18 28 41 

All ages 8,070 11 2 4 8 14 24 31 54 

a	 Excludes individuals who did not ingest water from the source during the survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water, defined as water 

added in the preparation of food or beverages, was not accounted for in the estimation of bottled 

water intake. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-60 September 2011 
 

 

 

Table 3-40. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on NHANES 

2003–2006: Other Sources (mL/kg-day) 

Percentile Sample Age	 Mean Size 10	 25 50 75 90 95 99 

Birth to <1 month 41 26* 4* 13* 26* 33* 47* 51* 55* 

1 to <3 months 67 31* 5* 22* 32* 37* 49* 69* 87* 

3 to <6 months 160 33* 5* 17* 27* 36* 51* 113* 179* 

6 to <12 months 287 25* 2* 5* 16* 28* 69* 98* 142* 

1 to <2 years 312 14 1* 2 4 17 43* 54* 97* 

2 to <3 years 256 12* 1* 1* 4* 15* 35* 62* 75* 

3 to <6 years 449 8 0 1 3 11 24 28* 54* 

6 to <11 years 609 9 1 1 4 13 23 33* 45* 

11 to <16 years 1,116 6 0 1 2 8 18 23 41 

16 to <18 years 467 6 0 1 2 6 21 27 42* 

18 to <21 years 572 6 0 1 2 5 20 28 42* 

≥21 years 3,555 9 0 1 3 11 25 35 53 

≥65 years 834 11 1 2 7 18 25 33 42* 

All ages 7,891 9 0 1 3 11 25 35 55 

a	 Excludes individuals who did not ingest water from the source during the survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-61 
 

 

 

Table 3-41. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on NHANES 

2003–2006: All Sources (mL/kg-day) 

Age Sample 

Size Mean 

10 25 50 

Percentile 

75 90 95 99 

Birth to <1 month 54 105* 15* 46* 120* 141* 189* 211* 255* 

1 to <3 months 92 115* 18* 71* 119* 160* 193* 201* 241* 

3 to <6 months 209 92* 8* 50* 95* 132* 163* 186* 238* 

6 to <12 months 453 54 7* 16 44 84 114* 137* 183* 

1 to <2 years 596 34 7* 15 26 44 68* 82* 122* 

2 to <3 years 560 32 7* 15 25 43 67* 78* 123* 

3 to <6 years 1,077 27 7 14 24 37 52 63 96* 

6 to <11 years 1,580 22 5 11 18 28 42 52 78* 

11 to <16 years 2,362 16 4 7 13 20 33 44 66 

16 to <18 years 1,059 17 4 7 14 22 33 44 59 

18 to <21 years 1,210 18 3 7 14 23 36 45 83 

≥21 years 8,608 22 6 12 19 29 41 50 70 

≥65 years 2,281 20 7 12 18 26 36 45 61 

All ages 17,860 22 6 11 19 29 43 53 84 

a	 Excludes individuals who did not ingest water from the source during the survey period. b	 Direct water is defined as water ingested directly as a beverage; indirect water is defined as water 

added in the preparation of food or beverages. Does not include indirect consumption of bottled 

water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS 

Analytical Working Group Recommendations (NCHS, 1993). 

Source:	 U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-62 September 2011 
 

 

Table 3-42. Consumer-Onlya Estimates of Direct and Indirectb Water Ingestion Based on NHANES 2003–2006, 

Mean Confidence Intervals and Bootstrap Intervals for 90th and 95th Percentiles: All Sources (mL/kg-day) 

Mean 90th percentile 95th percentile 

Sample 90% CI 90% BI 90% BI Age Size Lower Upper Lower Upper Lower Upper Estimate Estimate Estimate 

Bound Bound Bound Bound Bound Bound 

Birth to <1 month 54 105* 86* 125* 189* 160* 211* 211* 174* 238* 

1 to <3 months 92 115* 106* 125* 193* 164* 199* 201* 188* 222* 

3 to <6 months 209 92* 84* 101* 163* 143* 179* 186* 171* 201* 

6 to <12 months 453 54 49 59 114* 105* 126* 137* 124* 146* 

1 to <2 years 596 34 31 37 68* 62* 74* 82* 74* 100* 

2 to <3 years 560 32 29 35 67* 60* 72* 78* 72* 92* 

3 to <6 years 1,077 27 26 29 52 48 54 63 57 70 

6 to <11 years 1,580 22 21 24 42 39 46 52 49 55 

11 to <16 years 2,362 16 15 18 33 30 37 44 39 53 

16 to <18 years 1,059 17 16 18 33 29 35 44 36 45 

18 to <21 years 1,210 18 16 19 36 33 39 45 42 48 

≥21 years 8,608 22 21 23 41 40 43 50 48 51 

≥65 years 2,281 20 20 21 36 34 39 45 42 47
 

All ages 17,860 22 22 23 43 42 44 53 52 54
 a Excludes individuals who did not ingest water from the source during the survey period.
 b Direct water is defined as water ingested directly as a beverage; indirect water is defined as water added in the preparation of food or
 

beverages. Does not include indirect consumption of bottled water. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993).
 

CI = Confidence Interval.
 

BI = Bootstrap Interval.
 

Source: U.S. EPA analysis of NHANES 2003–2006 data. 

Exposure Factors Handbook Chapter 3—Water Ingestion Exposure Factors Handbook 

Page 

September 2011 3-63 
 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-43. Assumed Tap Water Content of Beverages in Great Britain 

Beverage % Tap Water 

Cold Water 

Home-made Beer/Cider/Lager 

Home-made Wine 

Other Hot Water Drinks 

Ground/Instant Coffee:a 

Black 

White 

Half Milk 

All Milk 

Tea 

Hot Milk 

Cocoa/Other Hot Milk Drinks 

Water-based Fruit Drink 

Fizzy Drinks 

Fruit Juice Type 1b 

Fruit Juice Type 2b 

Milk 

Mineral Waterc 

Bought cider/beer/lager 

Bought Wine 

100 

100 

100 

100 

100 

80 

50 

0 

80 

0 

0 

75 

0 

0 

75 

0 

0 

0 

0 a Black—coffee with all water, milk not added; White—coffee with 80% 

water, 20% milk; Half Milk—coffee with 50% water, 50% milk; All Milk— 

coffee with all milk, water not added. b Fruit juice: individuals were asked in the questionnaire if they consumed 

ready-made fruit juice (Type 1 above), or the variety that is diluted (Type 2). c Information on volume of mineral water consumed was obtained only as 

"number of bottles per week." A bottle was estimated at 500 mL, and the 

volume was split so that 2/7 was assumed to be consumed on weekends, and 

5/7 during the week. 

Source: Hopkins and Ellis (1980). 

Page Exposure Factors Handbook 

3-64 September2011 
 

Table 3-44. Intake of Total Liquid, Total Tap Water, and Various Beverages (L/day) by the British Population 

All Individuals 

Beverage Approx. 95% 

Confidence 

Mean Approx. Std. Interval for 10 and 90 1 and 99 

Intake Error of Mean Mean Percentiles Percentiles 

Total Liquid 1.589 0.0203 1.547–1.629 0.77–2.57 0.34–4.50 

Total Liquid 1.104 0.0143 1.075–1.133 0.49–1.79 0.23–3.10 Home 

Total Liquid 0.484 0.0152 0.454–0.514 0.00–1.15 0.00–2.89 Away 

Total Tap Water 0.955 0.0129 0.929–0.981 0.39–1.57 0.10–2.60 

Total Tap Water 0.754 0.0116 0.731–0.777 0.26–1.31 0.02–2.30 Home 

Total Tap Water 0.201 0.0056 0.190–0.212 0.00–0.49 0.00–0.96 Away 

Tea 0.584 0.0122 0.560–0.608 0.01–1.19 0.00–2.03 

Coffee 0.19 0.0059 0.178–0.202 0.00–0.56 0.00–1.27 

Other Hot 0.011 0.0015 0.008–0.014 0.00–0.00 0.00–0.25 Water Drinks 

Cold Water 0.103 0.0049 0.093–0.113 0.00–0.31 0.00–0.85 

Fruit Drinks 0.057 0.0027 0.052–0.062 0.00–0.19 0.00–0.49 

Non-Tap Water 0.427 0.0058 0.415–0.439 0.20–0.70 0.06–1.27 

Home-brew 0.01 0.0017 0.007–0.013 0.00–0.00 0.00–0.20 

Bought 

Alcoholic 0.206 0.0123 0.181–0.231 0.00–0.68 0.00–2.33 

Beverages 

Consumers Onlya 

Approx. 95% 

Percentage of Approx. Confidence Mean Total Number of Std. Error of Interval for Intake Individuals Mean Mean 

100 1.589 0.0203 1.547–1.629 

100 1.104 0.0143 1.075–1.133 

89.9 0.539 0.0163 0.506–0.572 

99.8 0.958 0.0129 0.932–0.984 

99.4 0.759 0.0116 0.736–0.782 

79.6 0.253 0.0063 0.240–0.266 

90.9 0.643 0.0125 0.618–0.668 

63 0.302 0.0105 0.281–0.323 

9.2 0.12 0.0133 0.093–0.147 

51 0.203 0.0083 0.186–0.220 

46.2 0.123 0.0049 0.113–0.133 

99.8 0.428 0.0058 0.416–0.440 

7 0.138 0.0209 0.096–0.180 

43.5 0.474 0.025 0.424–0.524 

a “Consumers only” is defined as only those individuals who reported consuming the beverage during the survey period. 

Source: Hopkins and Ellis (1980). 

Chapter 3—Exposure Factors Handbook 

Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page September 2011 3-65 
 

 

Table 3-45. Summary of Total Liquid and Total Tap Water Intake for Males and Females (L/day) in Great Britain 

Number Mean Intake Approx. Std. Error of Approx 95% Confidence 10 and 90 Percentiles 

Beverage Age Mean Interval for Mean 

Group 

(years) Male Female Male Female Male Female Male Female Male Female 

1 to 4 88 75 0.853 0.888 0.0557 0.066 0.742–0.964 0.756–1.020 0.38–1.51 0.39–1.48 

5 to 11 249 201 0.986 0.902 0.0296 0.0306 0.917–1.045 0.841–0.963 0.54–1.48 0.51–1.39 

12 to 17 180 169 1.401 1.198 0.0619 0.0429 1.277–1.525 1.112–1.284 0.75–2.27 0.65–1.74 Total Liquid
 

Intake
 18 to 30 333 350 2.184 1.547 0.0691 0.0392 2.046–2.322 1.469–1.625 1.12–3.49 0.93–2.30 

31 to 54 512 551 2.112 1.601 0.0526 0.0215 2.007–2.217 1.558–1.694 1.15–3.27 0.95–2.36 

>55 396 454 1.83 1.482 0.0498 0.0356 1.730–1.930 1.411–1.553 1.03–2.77 0.84–2.17 

1 to 4 88 75 0.477 0.464 0.0403 0.0453 0.396–0.558 0.373–0.555 0.17–0.85 0.15–0.89 

5 to 11 249 201 0.55 0.533 0.0223 0.0239 0.505–0.595 0.485–0.581 0.22–0.90 0.22–0.93 

Total Tap 

W 12 to 17 180 169 0.805 0.725 0.0372 0.0328 0.731–0.8790 0.659–0.791 0.29–1.35 0.31–1.16 ater Intake 

18 to 30 333 350 1.006 0.991 0.0363 0.0304 0.933–1.079 0.930–1.052 0.45–1.62 0.50–1.55 

31 to 54 512 551 1.201 1.091 0.0309 0.024 1.139–1.263 1.043–1.139 0.64–1.88 0.62–1.68 

>55 396 454 1.133 1.027 0.0347 0.0273 1.064–1.202 0.972–1.082 0.62–1.72 0.54–1.57 

Source: Hopkins and Ellis (1980). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 3-66 September 2011
Table 3-46. Daily Total Tap Water Intake Distribution for Canadians, by Age Group 

(approx. 0.20-L increments, both sexes, combined seasons) 

Age Group (years) 

Amount Consumeda 

5 and Under 6 to 17 18 and Over L/day 

% Number % Number % Number 

0.00–0.21 11.1 9 2.8 7 0.5 3 

0.22–0.43 17.3 14 10.0 25 1.9 12 

0.44–0.65 24.8 20 13.2 33 5.9 38 

0.66–0.86 9.9 8 13.6 34 8.5 54 

0.87–1.07 11.1 9 14.4 36 13.1 84 

1.08–1.29 11.1 9 14.8 37 14.8 94 

1.30–1.50 4.9 4 9.6 24 15.3 98 

1.51–1.71 6.2 5 6.8 17 12.1 77 

1.72–1.93 1.2 1 2.4 6 6.9 44 

1.94–2.14 1.2 1 1.2 3 5.6 36 

2.15–2.36 1.2 1 4.0 10 3.4 22 

2.37–2.57 - 0 0.4 1 3.1 20 

2.58–2.79 - 0 2.4 6 2.7 17 

2.80–3.00 - 0 2.4 6 1.4 9 

3.01–3.21 - 0 0.4 1 1.1 7 

3.22–3.43 - 0 - 0 0.9 6 

3.44–3.64 - 0 - 0 0.8 5 

3.65–3.86 - 0 - 0 - 0 

>3.86 - 0 1.6 4 2.0 13 

TOTAL 100.0 81 100.0 250 100.0 639 

a Includes tap water and foods and beverages derived from tap water. 

Source: Canadian Ministry of National Health and Welfare (1981). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-67 
 

Table 3-47. Average Daily Tap Water Intake of Canadians 

(expressed as mL/kg body weight) 

Age Group Average Daily Intake (mL/kg) 

(years) Females Males Both Sexes 

<3 53 35 45 

3 to 5 49 48 48 

6 to 17 24 27 26 

18 to 34 23 19 21 

35 to 54 25 19 22 

>55 24 21 22 

Total Population 24 21 22 

Source: Canadian Ministry of National Health and Welfare (1981). 

 

 

 

 

Table 3-48. Average Daily Total Tap Water Intake of Canadians, by Age and Season (L/day)a 

Age (years) 

<3 3 to 5 6 to 17 18 to 34 35 to 54 ≥55 All Ages 

Average 

Summer 0.57 0.86 1.14 1.33 1.52 1.53 1.31 

Winter 0.66 0.88 1.13 1.42 1.59 1.62 1.37 

Summer/Winter 0.61 0.87 1.14 1.38 1.55 1.57 1.34 

90th Percentile 

Summer/Winter 1.5 1.5 2.21 2.57 2.57 2.29 2.36 

a Includes tap water and foods and beverages derived from tap water. 

Source: Canadian Ministry of National Health and Welfare (1981). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-68 September 2011 
 

 

Table 3-49. Average Daily Total Tap Water Intake of Canadians as a Function of
 

Level of Physical Activity at Work and in Spare Time
 

(16 years and older, combined seasons, L/day)
 

Work Spare Time 

Activity Consumptionb Number of Respondents Consumptionb Number of Respondents 

Levela L/day L/day 

Extremely Active 1.72 99 1.57 52 

Very Active 1.47 244 1.51 151 

Somewhat Active 1.47 217 1.44 302 

Not Very Active 1.27 67 1.52 131 

Not At All Active 1.3 16 1.35 26 

Did Not State 1.3 45 1.31 26 

TOTAL 688 688 

a The levels of physical activity listed here were not defined any further by the survey report, and 

categorization of activity level by survey participants is assumed to be subjective. b Includes tap water and foods and beverages derived from tap water. 

Source: Canadian Ministry of National Health and Welfare (1981). 

Table 3-50. Average Daily Tap Water Intake by Canadians, Apportioned Among Various Beverages 

(both sexes, by age, combined seasons, L/day)a 

Age Group (years) 

<3 3 to 5 6 to 17 18 to 34 35 to 54 >55 

Total Number in Group 34 47 250 232 254 153 

Water 0.14 0.31 0.42 0.39 0.38 0.38 

Ice/Mix 0.01 0.01 0.02 0.04 0.03 0.02 

Tea * 0.01 0.05 0.21 0.31 0.42 

Coffee 0.01 * 0.06 0.37 0.5 0.42 

"Other Type of Drink" 0.21 0.34 0.34 0.2 0.14 0.11 

Reconstituted Milk 0.1 0.08 0.12 0.05 0.04 0.08 

Soup 0.04 0.08 0.07 0.06 0.08 0.11 

Homemade Beer/Wine * * 0.02 0.04 0.07 0.03 

Homemade Popsicles 0.01 0.03 0.03 0.01 * * 

Baby Formula, etc. 0.09 * * * * * 

TOTAL 0.61 0.86 1.14 1.38 1.55 1.57 

a Includes tap water and foods and beverages derived from tap water. 

* Less than 0.01 L/day. 

Source: Canadian Ministry of National Health and Welfare (1981). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-69 
 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-51. Intake Rates of Total Fluids and Total Tap Water by 

Age Group 

Average Daily Consumption Rate (L/day) 

Age Group Total Fluidsa Total Tap Waterb 

6 to 11 months 

2 years 

14 to 16 years 

25 to 30 years 

60 to 65 years 

0.80 

0.99 

1.47 

1.76 

1.63 

0.20 

0.50 

0.72 

1.04 

1.26 

a Includes milk, "ready-to-use" formula, milk-based soup, 

carbonated soda, alcoholic beverages, canned juices, water, 

coffee, tea, reconstituted juices, and reconstituted soups. Does 

not include reconstituted infant formula. 

b Includes water, coffee, tea, reconstituted juices, and 

reconstituted soups. 

Source:Derived from Pennington (1983) 

Table 3-52. Mean and Standard Error for the Daily Intake of Beverages and Tap Water by Age 

Age (years) Tap Water Intake 

(mL) 

Water-Based 

Drinks (mL)a 

Soups 

(mL) 

Total Beverage Intakeb 

(mL) 

All ages 

<1 

1 to 4 

5 to 9 

10 to 14 

15 to 19 

20 to 24 

25 to 29 

30 to 39 

40 to 59 

>60 

662.5 ± 9.9 

170.7 ± 64.5 

434.6 ± 31.4 

521.0 ± 26.4 

620.2 ± 24.7 

664.7 ± 26.0 

656.4 ± 33.9 

619.8 ± 34.6 

636.5 ± 27.2 

735.3 ± 21.1 

762.5 ± 23.7 

457.1 ± 6.7 

8.3 ± 43.7 

97.9 ± 21.5 

116.5 ± 18.0 

140.0 ± 16.9 

201.5 ± 17.7 

343.1 ± 23.1 

441.6 ± 23.6 

601.0 ± 18.6 

686.5 ± 14.4 

561.1 ± 16.2 

45.9 ± 1.2 

10.1 ± 7.9 

43.8 ± 3.9 

36.6 ± 3.2 

35.4 ± 3.0 

34.8 ± 3.2 

38.9 ± 4.2 

41.3 ± 4.2 

40.6 ± 3.3 

51.6 ± 2.6 

59.4 ± 2.9 

1,434.0 ± 13.7 

307.0 ± 89.2 

743.0 ± 43.5 

861.0 ± 36.5 

1,025.0 ± 34.2 

1,241.0 ± 35.9 

1,484.0 ± 46.9 

1,531.0 ± 48.0 

1,642.0 ± 37.7 

1,732.0 ± 29.3 

1,547.0 ± 32.8 

a Includes water-based drinks such as coffee, etc. Reconstituted infant formula does not appear to be 

included in this group. b Includes tap water and water-based drinks such as coffee, tea, soups, and other drinks such as soft drinks, 

fruitades, and alcoholic drinks. 

Source: U.S. EPA (1984). 

Page Exposure Factors Handbook 

3-70 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-53. Average Total Tap Water Intake Rate by 

Sex, Age, and Geographic Area 

Group/Subgroup Number of 

Respondents 

Average Total 

Tap Water 

Intake,a,b 

L/day 

Total group 

Sex 

Males 

Females 

Age, years 

21 to 44 

45 to 64 

65 to 84 

Geographic area 

Atlanta 

Connecticut 

Detroit 

Iowa 

New Jersey 

New Mexico 

New Orleans 

San Francisco 

Seattle 

Utah 

5,258 

3,892 

1,366 

291 

1,991 

2,976 

207 

844 

429 

743 

1,542 

165 

112 

621 

316 

279 

1.39 

1.40 

1.35 

1.30 

1.48 

1.33 

1.39 

1.37 

1.33 

1.61 

1.27 

1.49 

1.61 

1.36 

1.44 

1.35 

a Standard deviations not reported in Cantor et al. 

(1987). b Total tap water defined as all water and 

beverages derived from tap water. 

Source: Cantor et al. (1987). 

Table 3-54. Frequency Distribution of Total 

Tap Water Intake Ratesa 

Consumption 

Rate (L/day) Frequencyb (%) Cumulative Frequencyb (%) 

≤0.80 

0.81–1.12 

1.13–1.44 

1.45–1.95 

≥1.96 

20.6 

21.3 

20.5 

19.5 

18.1 

20.6 

41.9 

62.4 

81.9 

100.0 

a Represents consumption of tap water and 

beverages derived from tap water in a 

"typical" winter week. b Extracted from Table 3 in the article by 

Cantor et al. (1987). 

Source: Cantor et al. (1987). 

Exposure Factors Handbook Page
 

September 2011 3-71 
Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 3-72 September 2011 

 

 

 

 

 

 

 

 

 

 

 

Table 3-55. Total Tap Water Intake (mL/day) for Both Sexes Combineda 

Age (years) Number of 

Observations Mean SD SE of Mean 

Percentile Distribution 

1 5 10 25 50 75 90 95 99 

<0.5 182 272 247 18 * 0 0 80 240 332 640 800 * 

0.5 to 0.9 221 328 265 18 * 0 0 117 268 480 688 764 * 

1 to 3 1,498 646 390 10 33 169 240 374 567 820 1,162 1,419 1,899 

4 to 6 1,702 742 406 10 68 204 303 459 660 972 1,302 1,520 1,932 

7 to 10 2,405 787 417 9 68 241 318 484 731 1,016 1,338 1,556 1,998 

11 to 14 2,803 925 521 10 76 244 360 561 838 1,196 1,621 1,924 2,503 

15 to 19 2,998 999 593 11 55 239 348 587 897 1,294 1,763 2,134 2,871 

20 to 44 7,171 1,255 709 8 105 337 483 766 1,144 1,610 2,121 2,559 3,634 

45 to 64 4,560 1,546 723 11 335 591 745 1,057 1,439 1,898 2,451 2,870 3,994 

65 to 74 1,663 1,500 660 16 301 611 766 1,044 1,394 1,873 2,333 2,693 3,479 

>75 878 1,381 600 20 279 568 728 961 1,302 1,706 2,170 2,476 3,087 

Infants (ages <1) 

Children (ages 1 to 10) 

Teens (ages 11 to 19) 

Adults (ages 20 to 64) 

Adults (ages >65) 

All 

403 

5,605 

5,801 

11,731 

2,541 

26,081 

302 

736 

965 

1,366 

1,459 

1,193 

258 

410 

562 

728 

643 

702 

13 

5 

7 

7 

13 

4 

0 

56 

67 

148 

299 

80 

0 

192 

240 

416 

598 

286 

0 

286 

353 

559 

751 

423 

113 

442 

574 

870 

1,019 

690 

240 

665 

867 

1,252 

1,367 

1,081 

424 

960 

1,246 

1,737 

1,806 

1,561 

649 

1,294 

1,701 

2,268 

2,287 

2,092 

775 

1,516 

2,026 

2,707 

2,636 

2,477 

1,102 

1,954 

2,748 

3,780 

3,338 

3,415 

a Total tap water is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages." 

* Value not reported due to insufficient number of observations. 

SD = Standard deviation. 

SE = Standard error. 

Source: Ershow and Cantor (1989). 
 

 

99 

Table 3-56. Total Tap Water Intake (mL/kg-day) for Both Sexes Combineda 

Number of 

Observations Percentile Distribution 

Actual Weighted SE of 1 5 10 25 50 75 90 95 

Age (years) Count Count Mean SD Mean 

<0.5 182 201.2 52.4 53.2 3.9 * 0 0 14.8 37.8 66.1 128.3 155.6 * 

0.5 to 0.9 221 243.2 36.2 29.2 2 * 0 0 15.3 32.2 48.1 69.4 102.9 * 

1 to 3 1,498 1,687.7 46.8 28.1 0.7 2.7 11.8 17.8 27.2 41.4 60.4 82.1 101.6 140.6 

4 to 6 1,702 1,923.9 37.9 21.8 0.5 3.4 10.3 14.9 21.9 33.3 48.7 69.3 81.1 103.4 

7 to 10 2,405 2,742.4 26.9 15.3 0.3 2.2 7.4 10.3 16 24 35.5 47.3 55.2 70.5 

11 to 14 2,803 3,146.9 20.2 11.6 0.2 1.5 4.9 7.5 11.9 18.1 26.2 35.7 41.9 55 

15 to 19 2,998 3,677.9 16.4 9.6 0.2 1 3.9 5.7 9.6 14.8 21.5 29 35 46.3 

20 to 44 7,171 13,444.5 18.6 10.7 0.1 1.6 4.9 7.1 11.2 16.8 23.7 32.2 38.4 53.4 

45 to 64 4,560 8,300.4 22 10.8 0.2 4.4 8 10.3 14.7 20.2 27.2 35.5 42.1 57.8 

65 to 74 1,663 2,740.2 21.9 9.9 0.2 4.6 8.7 10.9 15.1 20.2 27.2 35.2 40.6 51.6 

>75 878 1,401.8 21.6 9.5 0.3 3.8 8.8 10.7 15 20.5 27.1 33.9 38.6 47.2 

Infants (ages <1) 403 444.3 43.5 42.5 2.1 0 0 0 15.3 35.3 54.7 101.8 126.5 220.5 

Children (ages 1 to 10) 5,605 6,354.1 35.5 22.9 0.3 2.7 8.3 12.5 19.6 30.5 46.0 64.4 79.4 113.9 

Teens (ages 11 to 19) 5,801 6,824.9 18.2 10.8 0.1 1.2 4.3 6.5 10.6 16.3 23.6 32.3 38.9 52.6 

Adults (ages 20 to 64) 11,731 21,744.9 19.9 10.8 0.1 2.2 5.9 8.0 12.4 18.2 25.3 33.7 40.0 54.8 

Adults (ages >65) 2,541 4,142.0 21.8 9.8 0.2 4.5 8.7 10.9 15.0 20.3 27.1 34.7 40.0 51.3 

All 26,081 39,510.2 22.6 15.4 0.1 1.7 5.8 8.2 13.0 19.4 28.0 39.8 50.0 79.8 

a Total tap water is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages." 

* Value not reported due to insufficient number of observations.
 

SD = Standard deviation.
 

SE = Standard error.
 

Source: Ershow and Cantor (1989). 

Chapter 3—Exposure Factors Handbook 

Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page September 2011 3-73 
 

 

Table 3-57. Summary of Tap Water Intake by Age 

Intake (mL/day) Intake (mL/kg-day) Age Group 10th 10th Mean –90th Percentiles Mean –90th Percentiles 

Infants (<1 year) 302 0–649 43.5 0–100 

Children (1 to 10 years) 736 286–1,294 35.5 12.5–64.4 

Teens (11 to 19 years) 965 353–1,701 18.2 6.5–32.3 

Adults (20 to 64 years) 1,366 559–2,268 19.9 8.0–33.7 

Adults (>65 years) 1,459 751–2,287 21.8 10.9–34.7 

All ages 1,193 423–2,092 22.6 8.2–39.8 

Source: Ershow and Cantor (1989). 

 

 

 

Table 3-58. Total Tap Water Intake (as % of total water intake) by Broad Age Categorya,b 

Age (years) Mean 

Percentile Distribution 

1 5 10 25 50 75 90 95 99 

<1 26 0 0 0 12 22 37 55 62 82 

1 to 10 45 6 19 24 34 45 57 67 72 81 

11 to 19 47 6 18 24 35 47 59 69 74 83 

20 to 64 59 12 27 35 49 61 72 79 83 90 

>65 65 25 41 47 58 67 74 81 84 90 

a Does not include pregnant women, lactating women, or breast-fed children. b Total tap water is defined as "all water from the household tap consumed directly as a beverage or used to 

prepare foods and beverages." 

0 = Less than 0.5%. 

Source: Ershow and Cantor (1989). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-74 September 2011 
Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

 

 

 

Table 3-59. General Dietary Sources of Tap Water for Both Sexesa,b 

Age 

(years) 

Source 

% of Tap Water 

Mean 

Standard 

Deviation 5 25 50 75 95 99 

<1 Foodc 

Drinking Water 

Other Beverages 

All Sources 

11 

69 

20 

100 

24 

37 

33 

0 

0 

0 

0 

39 

0 

0 

87 

0 

10 

100 

22 

70 

100 

100 

100 

100 

100 

1 to 10 Foodc 

Drinking Water 

Other Beverages 

All Sources 

15 

65 

20 

100 

16 

25 

21 

0 

0 

0 

5 

52 

0 

10 

70 

15 

19 

84 

32 

44 

96 

63 

100 

100 

93 

11 to 19 Foodc 

Drinking Water 

Other Beverages 

All Sources 

13 

65 

22 

100 

15 

25 

23 

0 

0 

0 

3 

52 

0 

8 

70 

16 

17 

85 

34 

38 

98 

68 

100 

100 

96 

20 to 64 Foodc 

Drinking Water 

Other Beverages 

All Sources 

8 

47 

45 

100 

10 

26 

26 

0 

0 

0 

2 

29 

25 

5 

48 

44 

11 

67 

63 

25 

91 

91 

49 

100 

100 

>65 Foodc 

Drinking Water 

Other Beverages 

All Sources 

8 

50 

42 

100 

9 

23 

23 

0 

0 

3 

2 

36 

27 

5 

52 

40 

11 

66 

57 

23 

87 

85 

38 

99 

100 

All Foodc 

Drinking Water 

Other Beverages 

All Sources 

10 

54 

36 

100 

13 

27 

27 

0 

0 

0 

2 

36 

14 

6 

56 

34 

13 

75 

55 

31 

95 

87 

64 

100 

100 

a Does not include pregnant women, lactating women, or breast-fed children. b Individual values may not add to totals due to rounding. c Food category includes soups. 

0 = Less than 0.5%. 

Source: Ershow and Cantor (1989). 

Exposure Factors Handbook Page
 

September 2011 3-75 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 3-60. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake 

Ratesa 

Group In Total Fluid Intake Rate 

(Age in Years) μ σ R2 

<1 6.979 0.291 0.996 

1 to <11 7.182 0.340 0.953 

11 to <20 7.490 0.347 0.966 

20 to <65 7.563 0.400 0.977 

> 65 7.583 0.360 0.988 

All ages 7.487 0.405 0.984 

Simulated balanced population 7.492 0.407 1.000 

Group In Total Fluid Intake Rate 

(Age in Years) μ σ R2 

<1 5.587 0.615 0.970 

1 to <11 6.429 0.498 0.984 

11 to <20 6.667 0.535 0.986 

20 to <65 7.023 0.489 0.956 

> 65 7.088 0.476 0.978 

All ages 6.870 0.530 0.978 

Simulated balanced population 6.864 0.575 0.995 a	 These values (mL/day) were used in the following equations to estimate the quantiles and 

averages for total tap water intake shown in Table 3-61. 

97.5 percentile intake rate = exp [μ + (1.96 × σ)]
	

75 percentile intake rate = exp [μ + (0.6745 × σ)]
	

50 percentile intake rate = exp [μ]
 

25 percentile intake rate = exp [μ – (0.6745 × σ)]
	

2.5 percentile intake rate = exp [μ – (1.96 × σ)]
	

Mean intake rate – exp [μ + 0.5 × σ2

)]
 

Source:	 Roseberry and Burmaster (1992). 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-61. Estimated Quantiles and Means for Total Tap Water Intake Rates (mL/day)a 

Age Group 

(years) 

Percentile Arithmetic 

Average 2.5 25 50 75 97.5 

<1 

1 to <11 

11 to <20 

20 to <65 

> 65 

All ages 

Simulated Balanced Population 

80 

233 

275 

430 

471 

341 

310 

176 

443 

548 

807 

869 

674 

649 

267 

620 

786 

1,122 

1,198 

963 

957 

404 

867 

1,128 

1,561 

1,651 

1,377 

1,411 

891 

1,644 

2,243 

2,926 

3,044 

2,721 

2,954 

323 

701 

907 

1,265 

1,341 

1,108 

1,129 

a Total tap water is defined as "all water from the household tap consumed directly as a beverage or used to 

prepare foods and beverages." 

Source: Roseberry and Burmaster (1992). 

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3-76 September 2011 
 

 

 

 

 

 

 

 

 

Chapter 3—Water IngestionExposure Factors Handbook

Table 3-62 . Water Ingested (mL/day)a From Water by Itself and Water Added to Other Beverages and Foods 

Category 6 Weeks (N = 124) 3 Months (N = 120) 6 Months (N = 99) 9 Months (N = 77) 

Water by Itself Range

Per capita meanb ± SD 

Consumer-only meanc 

Percent consumingd 

0–355 

30 ± 89 

89 

28 

0–355 

30 ± 59 

89 

24 

0–266 

30 ± 59 

118 

42 

0–473 

89 ± 89 

118 

66 

Water Added to Formula- Powdered Concentrate Range

Per capita mean ± SD

Consumer-only mean

Percent consuming 

0–1,242

177 ± 296 

473 

39 

0–1,242

266 ± 384 

621 

42 

0–1,124

266 ± 355 

562 

48 

0–1,064

207 ± 325 

562 

36 

Liquid Concentrate Range

Per capita mean ± SD

Consumer-only mean Percent consuming 

0–621 

89 ± 148 

355 

23 

0–680 

237 ± 207 

384 

30 

0–710 

148 ± 207 

414 

35 

0–532 

59 ± 148 

325 

21 

All Concentrated Formula Range

Per capita mean ± SD

Consumer-only mean

Percent consuming 

0–1,242

266 ± 296 

444 

60 

0–1,242

384 ± 355 

562 

68 

0–1,123

414 ± 325 

532 

81 

0–1,064

266 ± 296 

503 

56 

Water Added to Juices 

and Other Beverages 

Range

Per capita mean ± SD

Consumer-only mean

Percent consuming 

0–118 

<30 ± 30 

89 

3 

0–710 

30 ± 89 

207 

9 

0–473 

30 ± 89 

148 

18 

0–887 

59 ± 148 

207 

32 

Water Added to Powdered 

Baby Foods and Cereals 

Range

Per capita mean ± SD

Consumer-only mean

Percent consuming 

0–30 

<30 ± 30 

30 

2 

0–177 

<30 ± 30 

59 

17 

0–266 

59 ± 59 

89 

64 

0–177 

30 ± 59 

89 

43 

Water Added to Other Foods 

(Soups, Jell-o, Puddings) 

Range

Per capita mean ± SD

Consumer-only mean

Percent consuming 

---

0 

0–118 

30 ± 30 

89 

2 

0–118 

<30 ± 30 

59 

8 

0–355 

30 ± 59 

118 

29 

ALL SOURCES OF WATER Range

Per capita mean ± SD

Consumer-only mean

Percent consuming 

0–1,242

296 ± 325 

414 

68 

0–1,419

414 ± 414 

562 

77 

0–1,123

473 ± 325 

503 

94 

0–1,745

444 ± 355 

473 

97 

a Converted from ounces/day; 1 fluid ounce = 29.57 mL. b Mean intake among entire sample. c Mean intake for only those ingesting water from the particular category. d Percentage of infants receiving water from that individual source. 

N = Number of observations. 

SD = Standard deviation. 

- Indicates there is insufficient sample size to estimate means. 

Source: Levy et al. (1995). 

Exposure Factors Handbook PageSeptember 2011 3-77
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-63. Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data From 1989–1991 

(mL/day) 

Sex and Age 

(years) 

Plain Drinking 

Water Coffee Tea Fruit Drinks and Adesa Total 

Males and Females: 

<1 

1 to 2 

3 to 5 

<5 

194 

333 

409 

359 

0 

<0.5 

2 

1 

<0.5 

9 

26 

17 

17 

85 

100 

86 

211.5 

427.5 

537 

463 

Males: 

6 to 11 

12 to 19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 69 

70 to 79 

>80 

>20 

537 

725 

842 

793 

745 

755 

946 

824 

747 

809 

2 

12 

168 

407 

534 

551 

506 

430 

326 

408 

44 

95 

136 

136 

149 

168 

115 

115 

165 

139 

114 

104 

101 

50 

53 

51 

34 

45 

57 

60 

697 

936 

1,247 

1,386 

1,481 

1,525 

1,601 

1,414 

1,295 

1,416 

Females: 

6 to 11 

12 to 19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 69 

70 to 79 

>80 

>20 

476 

604 

739 

732 

781 

819 

829 

772 

856 

774 

1 

21 

154 

317 

412 

438 

429 

324 

275 

327 

40 

87 

120 

136 

174 

137 

124 

161 

149 

141 

86 

87 

61 

59 

36 

37 

36 

34 

28 

46 

603 

799 

1,074 

1,244 

1,403 

1,431 

1,418 

1,291 

1,308 

1,288 

All individuals 711 260 114 65 1,150 

a Includes regular and low calorie fruit drinks, punches, and ades, including those made from powdered mix 

and frozen concentrate. Excludes fruit juices and carbonated drinks. 

Source: USDA (1995). 

Page Exposure Factors Handbook 

3-78 September 2011 
Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 3-64. Number of Respondents That Consumed Tap Water at a Specified Daily Frequency 

Number of Glasses in a Day
 

Population Group Total N None
 1–2 3–5 6–9 10–19 20+ DK 

Overall 4,663 1,334 1,225 1,253 500 151 31 138 

Sex 

Male 2,163 604 582 569 216 87 25 65 

Female 2,498 728 643 684 284 64 6 73 

Refused 2 2 - - - - - -

Age (years) 

1 to 4 263 114 96 40 7 1 0 5 

5 to 11 348 90 127 86 15 7 2 20 

12 to 17 326 86 109 88 22 7 - 11 

18 to 64 2,972 908 751 769 334 115 26 54 

>64 670 117 127 243 112 20 2 42 

Race 

White 3,774 1,048 1,024 1,026 416 123 25 92 

Black 463 147 113 129 38 9 1 21 

Asian 77 25 18 23 6 1 - 4 

Some Others 96 36 18 22 6 7 2 5 

Hispanic 193 63 42 40 28 10 2 7 

Refused 60 15 10 13 6 1 1 9 

Hispanic 

No 4,244 1,202 1,134 1,162 451 129 26 116 

Yes 347 116 80 73 41 18 4 13 

DK 26 5 6 7 4 3 - 1 

Refused 46 11 5 11 4 1 1 8 

Employment 

Full-time 2,017 637 525 497 218 72 18 40 

Part-time 379 90 94 120 50 13 7 5 

Not Employed 1,309 313 275 413 188 49 3 54 

Refused 32 6 4 11 1 2 1 4 

Education 

<High School 399 89 95 118 51 14 2 28 

High School Graduate 1,253 364 315 330 132 52 13 37 

<College 895 258 197 275 118 31 5 9 

College Graduate 650 195 157 181 82 19 4 6 

Post Graduate 445 127 109 113 62 16 3 12 

Census Region 

Northeast 1,048 351 262 266 95 32 7 28 

Midwest 1,036 243 285 308 127 26 9 33 

South 1,601 450 437 408 165 62 11 57 

West 978 290 241 271 113 31 4 20 

Day of Week 

Weekday 3,156 864 840 862 334 96 27 106 

Weekend 1,507 470 385 391 166 55 4 32 

Season 

Winter 1,264 398 321 336 128 45 5 26 

Spring 1,181 337 282 339 127 33 10 40 

Summer 1,275 352 323 344 155 41 9 40 

Fall 943 247 299 234 90 32 7 32 

Asthma 

No 4,287 1,232 1,137 1,155 459 134 29 115 

Yes 341 96 83 91 40 16 1 13 

DK 35 6 5 7 1 1 1 10 

Angina 

No 4,500 1,308 1,195 1,206 470 143 29 123 

Yes 125 18 25 40 27 6 1 6 

DK 38 8 5 7 3 2 1 9 

Bronchitis/Emphysema 

No 4,424 1,280 1,161 1,189 474 142 29 124 

Yes 203 48 55 58 24 9 1 5 

DK 36 6 9 6 2 - 1 9 

- = Missing data.
 

DK = Don't know.
 

N = Sample size.
 

Refused = Respondent refused to answer.
 

Source: U.S. EPA (1996).
 

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3-80 September 2011 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-65. Number of Respondents That Consumed Juice Reconstituted with Tap Water at a Specified 

Daily Frequency 

Number of Glasses in a Day 

Population Group Total N 

None 1–2 3–5 6–9 10–19 20+ DK 

Overall 4,663 1,877 1,418 933 241 73 21 66 

Sex 

Male 2,163 897 590 451 124 35 17 33 

Female 2,498 980 826 482 117 38 4 33 

Refused 2 - 2 - - - - -

Age (years) 

1 to 4 263 126 71 48 11 4 1 2 

5 to 11 348 123 140 58 12 2 1 11 

12 to 17 326 112 118 63 18 7 1 4 

18 to 64 2,972 1,277 817 614 155 46 16 30 

>64 670 206 252 133 43 12 2 14 

Race 

White 3,774 1,479 1,168 774 216 57 16 44 

Black 463 200 142 83 15 9 1 7 

Asian 77 33 27 15 1 - - 0 

Some Others 96 46 19 24 2 1 3 1 

Hispanic 193 95 51 30 5 5 1 5 

Refused 60 24 11 7 2 1 - 9 

Hispanic 

No 4,244 1,681 1,318 863 226 64 17 49 

Yes 347 165 87 61 14 7 4 7 

DK 26 11 6 5 - 1 - 3 

Refused 46 20 7 4 1 1 - 7 

Employment 

Full-time 2,017 871 559 412 103 32 9 20 

Part-time 379 156 102 88 19 7 2 5 

Not Employed 1,309 479 426 265 75 20 7 21 

Refused 32 15 4 4 2 1 - 3 

Education 

<High School 399 146 131 82 25 7 2 4 

High School Graduate 1,253 520 355 254 68 21 7 17 

<College 895 367 253 192 47 18 5 11 

College Graduate 650 274 201 125 31 7 1 5 

Post Graduate 445 182 130 92 26 5 3 4 

Census Region 

Northeast 1,048 440 297 220 51 13 4 15 

Midwest 1,036 396 337 200 63 17 4 14 

South 1,601 593 516 332 84 26 10 28 

West 978 448 268 181 43 17 3 9 

Day of Week 

Weekday 3,156 1,261 969 616 162 51 11 46 

Weekend 1,507 616 449 307 79 22 10 20 

Season 

Winter 1,264 529 382 245 66 23 4 10 

Spring 1,181 473 382 215 54 19 8 17 

Summer 1,275 490 389 263 68 18 6 28 

Fall 943 385 265 210 53 13 3 11 

Asthma 

No 4,287 1,734 1,313 853 216 69 20 55 

Yes 341 130 102 74 25 3 1 5 

DK 35 13 3 6 - 1 - 6 

Angina 

No 4,500 1,834 1,362 900 231 67 20 59 

Yes 125 31 53 25 7 5 1 1 

DK 38 12 3 8 3 1 - 6 

Bronchitis/Emphysema 

No 4,424 1,782 1,361 882 230 65 21 57 

Yes 203 84 53 44 10 6 - 3 

DK 36 11 4 7 1 2 - 6 

- = Missing data. 

DK = Don't know. 

N = Sample size. 

Refused = Respondent refused to answer. 

Source: U.S. EPA (1996). 
 

 

 

 

 

 

 

Exposure Factors Handbook Chapter 3—Water IngestionExposure Factors Handbook

Page

September 2011 3-81

Table 3-66. Mean (standard error) Water and Drink Consumption (mL/kg-day) by Race/Ethnicity 

Race/Ethnic 

Group N Plain 

Tap Water 

Milk and 

Milk 

Drinks 

Reconstituted 

Formula 

RTF 

Formula 

Baby 

Food 

Juices and 

Carbonated 

Drinks 

NonCarbonated 

Drinks 

Other Totala 

Black nonHispanic 121 21 

(1.7) 

24 

(4.6) 

35 

(6.0) 

4 

(2.0) 

8 

(1.6) 

2 

(0.7) 

14 

(1.3) 

21 

(1.7) 

White nonHispanic 620 13 

(0.8) 

23 

(1.2) 

29 

(2.7) 

8 

(1.5) 

10 

(1.2) 

1 

(0.2) 

11 

(0.7) 

18 

(0.8) 

Hispanic 146 15 

(1.2) 

23 

(2.4) 

38 

(7.3) 

12 

(4.0) 

10 

(1.4) 

1 

(0.3) 

10 

(1.6) 

16 

(1.4) 

Other 59 21 

(2.4) 

19 

(3.7) 

31 

(9.1) 

19 

(11.2) 

7 

(4.0) 

1 

(0.5) 

8 

(2.0) 

19 

(3.2) 

129 

(5.7) 

113 

(2.6) 

123 

(5.2) 

124 

(10.6) 

a Totals may be slightly different from the sums of all categories due to rounding. 

N = Number of observations. 

RTF = Ready-to-feed. 

Note: Standard error shown in parentheses. 

Source: Heller et al. (2000). 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-67. Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and 

Poverty Category 

Plain Tap Water 

(mL/kg-day) 

Total Water 

(mL/kg-day) 

Variable N Mean SE Mean SE 

Age 

<12 months 

12 to 24 months 

296 

650 

11 

18 

1.0 

0.8 

130 

108 

4.6 

1.7 

Sex 

Male 

Female 

475 

471 

15 

15 

1.0 

0.8 

116 

119 

4.1 

3.2 

Region 

Northeast 

Midwest 

South 

West 

175 

197 

352 

222 

13 

14 

15 

17 

1.4 

1.0 

1.3 

1.1 

121 

120 

113 

119 

6.3 

3.1 

3.7 

4.6 

Urbanicity 

Urban 

Suburban 

Rural 

305 

446 

195 

16 

13 

15 

1.5 

0.9 

1.2 

123 

117 

109 

3.5 

3.1 

3.9 

Poverty categorya 

0–1.30 

1.31–3.50 

>3.50 

289 

424 

233 

19 

14 

12 

1.5 

1.0 

1.3 

128 

117 

109 

2.6 

4.2 

3.5 

Total 946 15 0.6 118 2.3 

a Poverty category represents family’s annual incomes of 0–1.30, 1.31–3.50, and greater than 3.50 

times the federal poverty level. 

N = Number of observations. 

SE = Standard error. 

Source: Heller et al. (2000). 

Page Exposure Factors Handbook 

3-82 September 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-68. Intake of Water From Various Sources in 2- to 13-Year-Old Participants of the DONALD 

Study, 1985-1999 

Water Intake Source 

Boys and Girls 

2 to 3 years 

N = 858b 

Boys and Girls 

4 to 8 years 

N = 1,795b 

Boys 

9 to 13 years 

N = 541b 

Girls 

9 to 13 years 

N = 542b 

Mean 

Water in Food (mL/day)a 365 (33)c 487 (36) 673 (36) 634 (38) 

Beverages (mL/day)a 614 (55) 693 (51) 969 (51) 823 (49) 

Milk (mL/day)a 191 (17) 177 (13) 203 (11) 144 (9) 

Mineral water (mL/day)a 130 (12) 179 (13) 282 (15) 242 (15) 

Tap water (mL/day)a 45 (4) 36 (3) 62 (3) 56 (3) 

Juice (mL/day)a 114 (10) 122 (0) 133 (7) 138 (8) 

Soft drinks (mL/day)a 57 (5) 111 (8) 203 (11) 155 (9) 

Coffee/tea (mL/day)a 77 (7) 69 (5) 87 (4) 87 (5) 

Mean ± SD 

Total water intakea,d (mL/day) 1,114 ± 289 1,363 ± 333 1,891 ± 428 1,676 ± 386 

Total water intakea,d (mL/kg-day) 78 ± 22 61 ± 13 49 ± 11 43 ± 10 

Total water intakea,d (mL/kcal-day) 1.1 ± 0.3 0.9 ± 0.2 1.0 ± 0.2 1.0 ± 0.2 

a Converted from g/day, g/kg-day, or g/kcal-day; 1 g = 1 mL. b N = Number of records. c Percent of total water shown in parentheses. d Total water = water in food + beverages + oxidation. 

SD = Standard deviation. 

Source: Sichert-Hellert et al. (2001). 

Table 3-69. Mean (±standard error) Fluid Intake (mL/kg-day) by Children Aged 1 to 10 Years, 

NHANES III, 1988–1994 

Total Sample 

(N = 7,925) 

Sample with 

Temperature Information 

(N = 3,869) 

Sample without 

Temperature Information 

(N = 4,056) 

Total fluid 84 ± 1.0 84 ± 1.0 85 ± 1.4 

Plain water 27 ± 0.8 27 ± 1.0 26 ± 1.1 

Milk 18 ± 0.3 18 ± 0.6 18 ± 0.4 

Carbonated drinks 6 ± 0.2 5 ± 0.3 6 ± 0.3 

Juice 12 ± 0.3 11 ± 0.6 12 ± 0.4 

N = Number of observations. 

Source: Sohn et al. (2001). 

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September 2011 3-83 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

c 

Table 3-70. Estimated Mean (±standard error) Amount of Total Fluid and Plain Water Intake 

Among Childrena Aged 1 to 10 Years by Age, Sex, Race/Ethnicity, Poverty Income Ratio, Region, 

and Urbanicity (NHANES III, 1988–1994) 

N Total Fluid Plain Water 

mL/day mL/kg-day mL/day mL/kg-day 

Age (years) 

1 578 1,393 ± 31 124 ± 2.9 298 ± 19 26 ± 1.8 

2 579 1,446 ± 31 107 ± 2.3 430 ± 26 32 ± 1.9 

3 502 1,548 ± 75 100 ± 4.6 482 ± 27 31 ± 1.8 

4 511 1,601 ± 41 91 ± 2.8 517 ± 23 29 ± 1.3 

5 465 1,670 ± 54 84 ± 2.3 525 ± 36 26 ± 1.7 

6 255 1,855 ± 125 81 ± 4.9 718 ± 118 31 ± 4.7 

7 235 1,808 ± 66 71 ± 2.3 674 ± 46 26 ± 1.9 

8 247 1,792 ± 37 61 ± 1.8 626 ± 37 21 ± 1.2 

9 254 2,113 ± 78 65 ± 2.1 878 ± 59 26 ± 1.4 

10 243 2,051 ± 97 58 ± 2.4 867 ± 74 24 ± 2.0 

Sex 

Male 1,974 1,802 ± 30 86 ± 1.8 636 ± 32 29 ± 1.3 

Female 1,895 1,664 ± 24 81 ± 1.5 579 ± 26 26 ± 1.0 

Race/ethnicity 

White 736 1,653 ± 26 79 ± 1.8 552 ± 34 24 ± 0.3 

Black 1,122 1,859 ± 42 88 ± 1.8 795 ± 36 36 ± 1.5 

Mexican American 1,728 1,817 ± 25 89 ± 1.7 633 ± 23 29 ± 1.1 

Other 283 1,813 ± 47 90 ± 4.2 565 ± 39 26 ± 1.7 

Poverty/income ratiob 

Low 1,868 1,828 ± 32 93 ± 2.6 662 ± 27 32 ± 1.3 

Medium 1,204 1,690 ± 31 80 ± 1.6 604 ± 35 26 ± 1.4 

High 379 1,668 ± 54 76 ± 2.5 533 ± 41 22 ± 1.7 

Regionc,d 

Northeast 679 1,735 ± 31 87 ± 2.3 568 ± 52 26 ± 2.1 

Midwest 699 1,734 ± 45 84 ± 1.5 640 ± 54 29 ± 1.8 

South 869 1,739 ± 31 83 ± 2.2 613 ± 24 28 ± 1.3 

West 1,622 737 ± 25 81 ± 1.7 624 ± 44 27 ± 1.9 

Urban/rurald 

Urban 3,358 1,736 ± 18 84 ± 1.0 609 ± 29 27 ± 1.1 

Rural 511 1,737 ± 19 84 ± 4.3 608 ± 20 28 ± 1.2 

Total 3,869 1,737 ± 15 84 ± 1.1 609 ± 24 27 ± 1.0
 a Children for whom temperature data were obtained.
 b Based on ratio of household income to federal poverty threshold. Low: <1.300; medium: 1.301–3.500;
 

high: >3.501.
 

All variables except for Region and Urban/rural showed statistically significant differences for both total 

fluid and plain water intake by Bonferroni multiple comparison method.
 d	 Northeast = Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, 

Rhode Island, Vermont; 

Midwest = Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, 

South Dakota, Wisconsin; 

South = Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, 

Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West 

Virginia; 

West = Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, 

Utah, Washington, Wyoming. 

N	 = Number of observations. 

Source:	 Sohn et al. (2001). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-84 September 2011 
 

 

 

 

 

 

 

 

 

Table 3-71. Tap Water Intake in Breast-Fed and Formula-Fed Infants and Mixed-Fed Young Children at Different Age Points 

Tap Water Intakeb (mL/day) Tap Water Intakeb (mL/kg-day) 

Na Age Total Total From Householdc From Manufacturingd 

Mean SD Median p95 Max Mean SD Median p95 Max %e Mean SD %f Mean SD %f
 

Breast-fed
 

1 year, total 300 130 180 50 525 1,172
 17 24** 6 65 150 17 15 23** 85 2.4 4.7** 15
 

3 months 111 67 167 0 493 746
 10 25** 0 74 125 10 10 25** 97 0.3 1.9** 3
 

6 months 124 136 150 68 479 634
 18 20** 8 5`8 85 18 14 19** 79 3.8 6.3* 21
 

9 months 47 254 218 207 656 1,172
 30 27** 23 77 150 28 26 27** 87 3.7 3.4 13
 

12 months 18 144 170 85 649 649
 15 18** 9 66 66 19 13 18** 86 2.2 2.1 14
 

Formula-fed
 

1 year, total 758 441 244 440 828 1,603
 53 33 49 115 200 51 49 33 92 4.0 8.0 8
 

3 months 78 662 154 673 874 994
 107 23 107 147 159 93 103 28 97 3.4 17.9 3
 

6 months 141 500 178 519 757 888
 63 23 65 99 109 64 59 25 92 4.8 8.0 8
 

9 months 242 434 236 406 839 1,579
 49 27 45 94 200 50 44 27 91 4.5 6.3 9
 

12 months 297 360 256 335 789 1,603
 37 26 32 83 175 39 33 25 91 3.3 3.7 9
 

Mixed-fed
 

1 to 3 years, total 904 241 243 175 676 2,441
 19 20 14 56 203 24 15 20 78 3.9 5.5 22
 

18 months 277 280 264 205 828 1,881
 25 23 18 70 183 28 22 23 88 3.0 4.1 12
 

24 months 292 232 263 158 630 2,441
 18 21 12 49 203 23 15 21 80 3.7 5.0 20
 

36 months 335 217 199 164 578 1,544
 14 13 11 36 103 22 9 12 66 4.9 6.6 34
 a Numbers of 3-day diet records.
 b Total tap water = tap water from the household and tap water from food manufacturing. Converted from g/day and g/kg-day; 1 g = 1 mL.
 c Tap water from household = tap water from the household tap consumed directly as a beverage or used to prepare foods and beverages.
 d Tap water from food = manufacturing tap water from the industrial food production used for the preparation of foods (bread, butter/margarine, tinned 

fruit, vegetables and legumes, ready to serve meals, commercial weaning food) and mixed beverages (lemonade, soft drinks).
 e Mean as a percentage of total water.
 f Mean as a percentage of total tap water.
 

* Significantly different from formula-fed infants, p < 0.05.
 

** Significantly different from formula-fed infants, p < 0.0001.
 

SD = Standard Deviation.
 

p95 = 95th percentile.
 

Source: Hilbig et al. (2002). 

Chapter 3—Exposure Factors Handbook 

Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page September 2011 3-85 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 3-86 September 2011 

Table 3-72. Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes (mL/day) for Children With 

Returned Questionnaires 

Age at Questionnaire 

Actual Age (Months) 

Nb 

6 Months 

6.29 ± 0.35 

677 

9 Months 

9.28 ± 0.35 

681 

12 Months 

12.36 ± 0.46 

659 

16 Months 

16.31 ± 0.49 

641 

20 Months 

20.46 ± 0.57 

632 

24 Months 

24.41 ± 0.53 

605 

6 to 24 Monthsa 

-

585c 

Human Milkd 30 19 11 5 3 0 -

Infant Formulae 

%d 

mL/dayf 

68 

798 ± 234 

69 

615 ± 328 

29 

160 ± 275 

4 

12 ± 77 

2 

9 ± 83 

0 

-

67g 

207 ± 112 

Cows’ Milke 

%d 

mL/dayf 

5 

30 ± 145 

25 

136 ± 278 

79 

470 ± 310 

91 

467 ± 251 

93 

402 ± 237 

97 

358 ± 225 

67g 

355 ± 163 

Formula and Cows’ Milke 

%d 

mL/dayf 

70 

828 ± 186 

81 

751 ± 213 

88 

630 ± 245 

92 

479 ± 248 

94 

411 ± 237 

98 

358 ± 228 

67g 

562 ± 154 

Juice and Juice Drinks 

%d 

mL/dayf 

55 

65 ± 95 

73 

103 ± 112 

89 

169 ± 151 

94 

228 ± 166 

95 

269 ± 189 

93 

228 ± 172 

99h 

183 ± 103 

Water 

%d 

mL/dayf 

36 

27 ± 47 

59 

53 ± 71 

75 

92 ± 109 

87 

124 ± 118 

90 

142 ± 127 

94 

145 ± 148 

99h 

109 ± 74 

Other Beveragesi 

%d 

mL/dayf 

1 

3 ± 18 

9 

6 ± 27 

23 

27 ± 71 

42 

53 ± 109 

62 

83 ± 121 

86 

89 ± 133 

80h 

44 ± 59 

Total Beverages mL/daye,f,j 934 ± 219 917 ± 245 926 ± 293 887 ± 310 908 ± 310 819 ± 299 920 ± 207 

a Cumulative number of children and percentage of children consuming beverage and beverage intakes for the 6- through 24-month period. b Number of children with returned questionnaires at each time period. c Number of children with cumulative intakes for 6- through 24-month period. d Percentage of children consuming beverage. e Children are not included when consuming human milk. f Mean standard deviation of beverage intake. Converted from ounces/day; 1 fluid ounce = 29.57 mL. g Percentage of children consuming beverage during 6- through 24-month period. Children who consumed human milk are not included. h Percentage of children consuming beverage during 6- through 24-month period. i Other beverages include non-juice beverages (e.g., carbonated beverages, Kool-Aid). 

j Total beverages includes all beverages except human milk. 

- Indicates there are insufficient data. 

Source: Marshall et al. (2003b). 
 

 

 

 

 

 

 

 

 

 

 

mL/daya %b mL/daya %b mL/daya %b mL/daya %b 

Human milk 204 ± 373 195 ± 358 28.0 9 ± 21 56 ± 225 12.6 NAc NA - NA NA -

Infant formula 609 ± 387 603 ± 364 85.8 180 ± 290 139 ± 251 37.0 NA NA - NA NA -

Cows’ milk 24 ± 124 24 ± 124 6.7 429 ± 349 408 ± 331 90.4 316 ± 216 358 ± 216 100 319 ± 198 325 ± 177 98.2 

Juice/juice drinks 56 ± 124 33 ± 59 57.5 151 ± 136 106 ± 101 92.2 192 ± 169 198 ± 169 96.9 189 ± 169 180 ± 163 95.5 

Liquid soft drinks 6 ± 68 0 ± 0 1.3 9 ± 30 3 ± 15 20.9 62 ± 71 74 ± 101 74.2 74 ± 95 101 ± 121 82.1 

Powdered soft 

drinks 0 ± 18 0 ± 0 0.4 12 ± 47 3 ± 18 10.5 62 ± 115 47 ± 101 51.2 74 ± 124 47 ± 95 52.7 

Water 44 ± 80 30 ± 53 61.7 127 ± 136 80 ± 109 84.9 177 ± 204 136 ± 177 95.3 240 ± 242 169 ± 183 99.1 

Total 940 ± 319 896 ± 195 100 905 ± 387 804 ± 284 100 795 ± 355 816 ± 299 100 896 ± 399 819 ± 302 100 

Table 3-73. Mean (±standard deviation) Daily Beverage Intakes Reported on Beverage Frequency Questionnaire and 3-Day Food 

and Beverage Diaries 

Age 

6 months (N = 240) 12 months (N = 192) 3 years (N = 129) 5 years (N = 112) 

Beverage Questionnaire Diary Questionnaire Diary Questionnaire Diary Questionnaire Diary 

a Mean standard deviation of all subjects. Converted from ounces/day; 1 fluid ounce = 29.57 mL.
 b Percent of subjects consuming beverage on either questionnaire or diary.
 c NA = not applicable.
 

N = Number of observations.
 

- Indicates there are insufficient data to calculate percentage.
 

Source: Marshall et al. (2003a). 

Chapter 3—Exposure Factors Handbook 

Ingestion of Water and Other Select Liquids 

SeptemberExposure Factors Handbook 

 2011 3-87 

Page 
c 

Table 3-74. Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study) 

Age (months) 

4 to 6 Months (N = 862) 7 to 8 Months (N = 483) 9 to 11 Months (N = 679) 12 to 14 Months (N = 374) 15 to 18 Months (N = 308) 19 to 24 Months (N = 316) 

Beverage 

Category Consumers 

%a 

Mean ± SD 

mL/dayb 

Consumers 

%a 

Mean ± SD 

mL/dayb 

Consumers 

%a 

Mean ± SD 

mL/dayb 

Consumers 

%a 

Mean ± SD 

mL/dayb 

Consumers 

%a 

Mean ± SD 

mL/dayb 

Consumers 

%a 

Mean ± SD 

mL/dayb 

Total Milks

c 100 778 ± 257 100 692 ± 257 99.7 659 ± 284 98.2 618 ± 293 94.2 580 ± 305 93.4 532 ± 281 

100% Juiced 21.3 121 ± 89 45.6 145 ± 109 55.3 160 ± 127 56.2 186 ± 145 57.8 275 ± 189 61.6 281 ± 189 

Fruit Drinks

e 1.6 101 ± 77 7.1 98 ± 77 12.4 157 ± 139 29.1 231 ± 186 38.6 260 ± 231 42.6 305 ± 308 

Carbonated 0.1 86 ± 0 1.1 6 ± 9 1.7 89 ± 92 4.5 115 ± 83 11.2 157 ± 106 11.9 163 ± 172 

Water 33.7 163 ± 231 56.1 174 ± 219 66.9 210 ± 234 72.2 302 ± 316 74.0 313 ± 260 77.0 337 ± 245 

Otherf 1.4 201 ± 192 2.2 201 ± 219 3.5 169 ± 166 6.6 251 ± 378 12.2 198 ± 231 11.2 166 ± 248 

Total 100 863 ± 254 100 866 ± 310 100 911 ± 361 100 1,017 ± 399 100 1,079 ± 399 100 1,097 ± 482 

beverages 

a	 Weighted percentages, adjusted for over sampling, non-response, and under-representation of some racial and ethnic groups. b	 Amounts consumed only by those children who had a beverage from this beverage category. Converted from ounces/day; 1 fluid ounce = 29.57 mL. 

Includes human milk, infant formula, cows’ milk, soy milk, and goats’ milk. d	 Fruit or vegetable juices with no added sweeteners. e	 Includes beverages with less than 100% juice and often with added sweeteners; some were fortified with one or more nutrients. f	 “Other” beverages category included tea, cocoa, and similar dry milk beverages, and electrolyte replacement beverages for infants. 

N	 = Number of observations. 

SD	 = Standard Deviation. 

Source:	 Skinner et al. (2004). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 3-88 September 2011 
Table 3-75. Per Capita Estimates of Direct and Indirect Water Intake From All Sources by Pregnant, 

Lactating, and Childbearing Age Women (mL/kg-day) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI 

Women Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
 

Categories Size Bound Bound Bound Bound Bound Bound
 

Pregnant 69 21* 19* 22* 39* 33* 46* 44* 38* 46* 

Lactating 40 21* 15* 28* 53* 44* 55* 55* 52* 57* 

Non-pregnant, 

Non-lactating 2,166 19 19 20 35 35 36 36 46 

Ages 15 to 44 

years 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates 

may involve aggregation of variance estimation units when data are too sparse to support estimation of the 

variance; all estimates exclude commercial and biological water. 

90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile 

estimates using bootstrap method with 1,000 replications. 

* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as 

described in the Third Report on Nutrition Monitoring in the United States, 1994–1996 (FASEB/LSRO, 

1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

47 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-89 
 

 

 

 

Table 3-76. Per Capita Estimates of Direct and Indirect Water Intake From All Sources by Pregnant, 

Lactating, and Childbearing Age Women (mL/day) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI 

Women Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
 

Categories Size Bound Bound Bound Bound Bound Bound
 

Pregnant 70 1,318* 1,199* 1,436* 2,336* 1,851* 3,690* 2,674* 2,167* 3,690* 

Lactating 41 1,806* 1,374* 2,238* 3,021* 2,722* 3,794* 3,767* 3,452* 3,803* 

Non-pregnant, 2,221 1,243 1,193 1,292 2,336 2,222 2,488 2,937 2,774 3,211 

Non-lactating 

Aged 15 to 44 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may involve aggregation of 

variance estimation units when data are too sparse to support estimation of the variance; all estimates exclude commercial and 

biological water. 

90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile estimates using bootstrap 

method with 1,000 replications. 

*	 The sample size does not meet minimum reporting requirements to make statistically reliable estimates as described in the Third 

Report on Nutrition Monitoring in the United States, 1994–1996 (FASEB/LSRO, 1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

 

 

 

Table 3-77. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant,
 

Lactating, and Childbearing Age Women (mL/kg-day)
 

Mean	 90th Percentile 95th Percentile 

90% CI 90% BI	 90% BI 

Women Categories Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper 

Size Bound Bound Bound Bound Bound Bound 

Pregnant 69 13* 11* 14* 31* 28* 46* 43* 33* 46* 

Lactating 40 21* 15* 28* 53* 44* 55* 55* 52* 57* 

Non-pregnant, 

Non-lactating 2,166 14 14 15 31 30 32 38 36 39 

Ages 15 to 44 years 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may involve 

aggregation of variance estimation units when data are too sparse to support estimation of the variance; all estimates exclude 

commercial and biological water. 

90% CI = 90% confidence intervals for estimated means; 90% B.I. = 90% Bootstrap intervals for percentile estimates using 

bootstrap method with 1,000 replications. 

*	 The sample size does not meet minimum reporting requirements to make statistically reliable estimates as described in the Third 

Report on Nutrition Monitoring in the United States, 1994–1996 (FASEB/LSRO, 1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-90 September 2011 
Table 3-78. Per Capita Estimated Direct and Indirect Community Water Ingestion by Pregnant, 

Lactating, and Childbearing Age Women (mL/day) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI 

Women Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
 

Categories Size Bound Bound Bound Bound Bound Bound
 

Pregnant 70 819* 669* 969* 1,815* 1,479* 2,808* 2,503* 2,167* 3,690* 

Lactating 41 1,379* 1,021* 1,737* 2,872* 2,722* 3,452* 3,434* 2,987* 3,803* 

Non-pregnant, 

Non-lactating 

Ages 15 to 44 

2,221 916 882 951 1,953 1,854 2,065 2,575 2,403 2,908 

years 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates 

may involve aggregation of variance estimation units when data are too sparse to support estimation of the 

variance; all estimates exclude commercial and biological water. 

90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile 

estimates using bootstrap method with 1,000 replications. 

* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as 

described in the Third Report on Nutrition Monitoring in the United States, 1994–1996 (FASEB/LSRO, 

1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

Table 3-79. Estimates of Consumers-Only Direct and Indirect Water Intake From All Sources by Pregnant, 

Lactating, and Childbearing Age Women (mL/kg-day) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI 

Women Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
 

Categories Size Bound Bound Bound Bound Bound Bound
 

Pregnant 69 21* 19* 22* 39* 33* 46* 44* 38* 46* 

Lactating 40 28* 19* 38* 53* 44* 57* 57* 52* 58* 

Non-pregnant, 

Non-lactating 2,149 19 19 20 35 34 37 46 42 

Ages 15 to 44 

years 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may 

involve aggregation of variance estimation units when data are too sparse to support estimation of the variance; 

all estimates exclude commercial and biological water. 

90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile 

estimates using bootstrap method with 1,000 replications. 

* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as 

described in the Third Report on Nutrition Monitoring in the United States, 1994–1996 (FASEB/LSRO, 1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

48 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-91 
 

Table 3-80. Estimates of Consumers-Only Direct and Indirect Water Intake From All Sources by Pregnant, 

Lactating, and Childbearing Age Women (mL/day) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI 

Women Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
 

Categories Size Bound Bound Bound Bound Bound Bound
 

Pregnant 70 1,318* 1,199* 1,436* 2,336* 1,851* 3,690* 2,674* 2,167* 3,690* 

Lactating 41 1,806* 1,374* 2,238* 3,021* 2,722* 3,794* 3,767* 3,452* 3,803* 

Non-pregnant, 

Non-lactating 

Ages 15 to 44 

2,203 1,252 1,202 1,303 2,338 2,256 2,404 2,941 2,834 3,179 

years 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates may 

involve aggregation of variance estimation units when data are too sparse to support estimation of the variance; all 

estimates exclude commercial and biological water. 

90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile 

estimates using bootstrap method with 1,000 replications. 

* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as 

described in the Third Report on Nutrition Monitoring in the United States, 1994–1996 (FASEB/LSRO, 1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

Table 3-81. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant, 

Lactating, and Childbearing Age Women (mL/kg-day) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI 

Women Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper
 

Categories Size Bound Bound Bound Bound Bound Bound
 

Pregnant 65 14* 12* 15* 33* 29* 46* 43* 33* 46* 

Lactating 33 26* 18* 18* 54* 44* 55* 55* 53* 57* 

Non-pregnant, 

Non-lactating 2,028 15 14 16 32 31 33 38 36 42 

Ages 15 to 44 

years 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval estimates 

may involve aggregation of variance estimation units when data are too sparse to support estimation of the 

variance; all estimates exclude commercial and biological water. 

90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for percentile 

estimates using bootstrap method with 1,000 replications. 

* The sample size does not meet minimum reporting requirements to make statistically reliable estimates as 

described in the Third Report on Nutrition Monitoring in the United States, 1994–1996 (FASEB/LSRO, 

1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-92 September 2011 
Table 3-82. Consumers-Only Estimated Direct and Indirect Community Water Ingestion by Pregnant, 

Lactating, and Childbearing Age Women (mL/day) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI 

Women Sample Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper 

Categories Size Bound Bound Bound Bound Bound Bound 

Pregnant 65 872* 728* 1,016* 1,844* 1,776* 3,690* 2,589* 2,167* 3,690* 

Lactating 34 1,665* 1,181* 2,148* 2,959* 2,722* 3,452* 3,588* 2,987* 4,026* 

Non-pregnant, 

Non-lactating 2,077 976 937 1,014 2,013 1,893 2,065 2,614 2,475 2,873 

Ages 15 to 44 

years 

NOTE:	 Source of data: 1994–1996, 1998 USDA CSFII; estimates are based on 2-day averages; interval 

estimates may involve aggregation of variance estimation units when data are too sparse to support 

estimation of the variance; all estimates exclude commercial and biological water. 

90% CI = 90% confidence intervals for estimated means; 90% BI = 90% Bootstrap intervals for 

percentile estimates using bootstrap method with 1,000 replications. 

* The sample size does not meet minimum reporting requirements to make statistically reliable 

estimates as described in the Third Report on Nutrition Monitoring in the United States, 1994–1996 

(FASEB/LSRO, 1995). 

Source:	 Kahn and Stralka (2008) (Based on CSFII 1994–1996 and 1998). 

 

 

 

 

 

 

 

 

Table 3-83. Total Fluid Intake of Women 15 to 49 Years Old 

Reproductive 

Statusa Mean 

Standard 

Deviation 

Percentile Distribution 

5 10 25 50 75 90 95 

mL/day 

Control 

Pregnant 

Lactating 

1,940 

2,076 

2,242 

686 

743 

658 

995 

1,085 

1,185 

1,172 

1,236 

1,434 

1,467 

1,553 

1,833 

1,835 

1,928 

2,164 

2,305 

2,444 

2,658 

2,831 

3,028 

3,169 

3,186 

3,475 

3,353 

mL/kg-day 

Control 

Pregnant 

Lactating 

32.3 

32.1 

37.0 

12.3 

11.8 

11.6 

15.8 

16.4 

19.6 

18.5 

17.8 

21.8 

23.8 

17.8 

21.8 

30.5 

30.5 

35.1 

38.7 

40.4 

45.0 

48.4 

48.9 

53.7 

55.4 

53.5 

59.2 

a Number of observations: non-pregnant, non-lactating controls (N = 6,201); pregnant (N = 188); lactating 

(N = 77). 

Source: Ershow et al. (1991). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-93 
Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-94 September 2011 

Table 3-84. Total Tap Water Intake of Women 15 to 49 Years Old 

Reproductive Statusa Mean Standard 

Deviation 

Percentile Distribution 

5 10 25 50 75 90 95 

mL/day 

 Control 

 Pregnant 

 Lactating 

mL/kg-day 

 Control 

 Pregnant 

 Lactating 

1,157 

1,189 

1,310 

19.1 

18.3 

21.4 

635 

699 

591 

10.8 

10.4 

9.8 

310 

274 

430 

5.2 

4.9 

7.4 

453 

419 

612 

7.5 

5.9 

9.8 

709 

713 

855 

11.7 

10.7 

14.8 

1,065 

1,063 

1,330 

17.3 

16.4 

20.5 

1,503 

1,501 

1,693 

24.4 

23.8 

26.8 

1,983 

2,191 

1,945 

33.1 

34.5 

35.1 

2,310 

2,424 

2,191 

39.1 

39.6 

37.4 

Fraction of daily fluid intake that is tap water (%) 

 Control 57.2 18.0 

 Pregnant 54.1 18.2 

 Lactating 57.0 15.8 

24.6 

21.2 

27.4 

32.2 

27.9 

38.0 

45.9 

42.9 

49.5 

59.0 

54.8 

58.1 

70.7 

67.6 

65.9 

79.0 

76.6 

76.4 

83.2 

83.2 

80.5 a 

Source: 

Number of observations: non-pregnant, non-lactating controls (N = 6,201); pregnant (N = 188); lactating (N = 77). 

Ershow et al. (1991). 

 

 

 

Table 3-85. Total Fluid (mL/day) Derived from Various Dietary Sources by Women Aged 15 to 49 Yearsa 

Control Women Pregnant Women Lactating Women 

Sources Percentile Percentile Percentile 

Meanb 50 95 Meanb 50 95 Meanb 50 95 

Drinking Water 583 480 1,440 695 640 1,760 677 560 1,600 

Milk and Milk Drinks 162 107 523 308 273 749 306 285 820 

Other Dairy Products 23 8 93 24 9 93 36 27 113 

Meats, Poultry, Fish, Eggs 126 114 263 121 104 252 133 117 256 

Legumes, Nuts, and Seeds 13 0 77 18 0 88 15 0 72 

Grains and Grain Products 90 65 257 98 69 246 119 82 387 

Citrus and Non-citrus Fruit Juices 57 0 234 69 0 280 64 0 219 

Fruits, Potatoes, Vegetables, Tomatoes 198 171 459 212 185 486 245 197 582 

Fats, Oils, Dressings, Sugars, Sweets 9 3 41 9 3 40 10 6 50 

Tea 148 0 630 132 0 617 253 77 848 

Coffee and Coffee Substitutes 291 159 1,045 197 0 955 205 80 955 

Carbonated Soft Drinksc 174 110 590 130 73 464 117 57 440 

Non-carbonated Soft Drinksc 38 0 222 48 0 257 38 0 222 

Beer 17 0 110 7 0 0 17 0 147 

Wine Spirits, Liqueurs, Mixed Drinks 10 0 66 5 0 25 6 0 59 

All Sources 1,940 NA NA 2,076 NA NA 2,242 NA NA 

a Number of observations: non-pregnant, non-lactating controls (N = 6,201); pregnant (N = 188); lactating (N = 77). 

b Individual means may not add to all-sources total due to rounding. 

Includes regular, low-calorie, and non-calorie soft drinks. 

NA: Not appropriate to sum the columns for the 50th and 95th percentiles of intake. 

Source: Ershow et al. (1991). 

c 
Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook 

September 2011 

Page 

3-95 

 

Table 3-86. Total Tap Water and Bottled Water Intake by Pregnant Women (L/day) 

Variables 

Cold Tap Water Bottled Water 

N Mean (SD) N Mean (SD) 

Demographics 

Home 2,293 1.3 (1.2) a a 

Work 2,295 0.4 (0.6) a a 

Total 2,293 1.7 (1.4) 2,284 0.6 (0.9) 

Geographic Region 

Site 1 1,019 1.8 (1.4) 1,016 0.5 (0.9) 

Site 2 864 1.9 (1.4) 862 0.4 (0.7) 

Site 3 410 1.1 (1.3) 406 1.1 (1.2) 

Season 

Winter 587 1.6 (1.3) 584 0.6 (1.0) 

Spring 622 1.7 (1.4) 622 0.6 (1.0) 

Summer 566 1.8 (1.6) 560 0.6 (0.9) 

Fall 518 1.8 (1.5) 518 0.5 (0.9) 

Age at LMPb 

17 to 25 852 1.6 (1.4) 848 0.6 (1.0) 

26 to 30 714 1.8 (1.5) 710 0.6 (1.0) 

31 to 35 539 1.7 (1.3) 538 0.5 (0.8) 

≥36 188 1.8 (1.4) 188 0.5 (0.9) 

Education 

≤High school 691 1.5 (1.5) 687 0.6 (1.0) 

Some college 498 1.7 (1.5) 496 0.6 (1.0) 

≥4-year college 1,103 1.8 (1.3) 1,100 0.5 (0.9) 

Race/ethnicity 

White, non-Hispanic 1,276 1.8 (1.4) 1,273 0.5 (0.9) 

Black, non-Hispanic 727 1.6 (1.5) 722 0.6 (0.9) 

Hispanic, any race 204 1.1 (1.3) 202 1.1 (1.2) 

Other 84 1.9 (1.5) 85 0.5 (0.9) 

Marital Status 

Single, never married 719 1.6 (1.5) 713 0.6 (1.0) 

Married 1,497 1.8 (1.4) 1,494 0.5 (0.9) 

Other 76 1.7 (1.9) 76 0.5 (0.9) 

Annual Income ($) 

≤40,000 967 1.6 (1.5) 962 0.6 (1.0) 

40,000–80,000 730 1.8 (1.4) 730 0.5 (0.9) 

>80,000 501 1.7 (1.3) 499 0.5 (0.9) 

Employment 

No 681 1.7 (1.5) 679 0.5 (0.9) 

Yes 1,611 1.7 (1.4) 1,604 0.6 (0.9) 

BMI 

Low 268 1.6 (1.3) 267 0.6 (1.0) 

Normal 1,128 1.7 (1.4) 1,123 0.5 (0.9) 

Overweight 288 1.7 (1.5) 288 0.6 (0.9) 

Obese 542 1.8 (1.6) 540 0.6 (1.0) 
 

Table 3-86. Total Tap Water and Bottled Water Intake by Pregnant Women 

(L/day) (continued) 

Cold Tap Water Bottled Water Variables N Mean (SD) N Mean (SD) 

Diabetes 

No diabetes 2,221 1.7 (1.4) 2,213 0.6 (0.9) 

Regular diabetes 17 2.6 (2.1) 17 0.4 (0.8) 

Gestational diabetes 55 1.6 (1.6) 54 0.6 (1.0) 

Nausea during pregnancy 

No 387 1.6 (1.4) 385 0.6 (1.0) 

Yes 1,904 1.7 (1.4) 1,897 0.6 (0.9) 

Pregnancy history 

No prior pregnancy 691 1.7 (1.4) 685 0.6 (1.0) 

Prior pregnancy with no SABc 1,064 1.7 (1.4) 1,063 0.5 (0.9) 

Prior pregnancy with SAB 538 1.8 (1.5) 536 0.6 (1.0) 

Caffeine 

0 mg/day 578 1.8 (1.5) 577 0.6 (1.0) 

1–150 mg/day 522 1.6 (1.3) 522 0.5 (0.8) 

151–300 mg/day 433 1.6 (1.4) 433 0.6 (0.9) 

>300 mg/day 760 1.7 (1.5) 752 0.6 (1.0) 

Vitamin use 

No 180 1.4 (1.4) 176 0.5 (0.8) 

Yes 2,113 1.7 (1.4) 2,108 0.6 (0.9) 

Smoking 

Non-smoker 2,164 1.7 (1.4) 2,155 0.6 (0.9) 

<10 cigarettes/day 84 1.8 (1.5) 84 0.8 (1.3) 

≥10 cigarettes/day 45 1.8 (1.6) 45 0.4(0.7) 

Alcohol use 

No 2,257 1.7 (1.4) 2,247 0.6 (0.9) 

Yes 36 1.6 (1.2) 37 0.6 (0.8) 

Recreational exercise 

No 1,061 1.5 (1.4) 1,054 0.6 (0.9) 

Yes 1,232 1.8 (1.4) 1,230 0.6 (1.0) 

Illicit drug use 

No 2,024 1.7 (1.4) 2,017 0.6 (0.9) 

Yes 268 1.7 (1.5) 266 0.6 (1.0) 

a 

b 

c 

N 

SD 

Data are not reported in the source document. 

LMP = Age of Last Menstrual Period. 

SAB = Spontaneous abortion. 

= Number of observations. 

= Standard deviation. 

Source: Forssen et al. (2007). 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Page Exposure Factors Handbook 

3-96 September 2011 
Exposure Factors Handbook 

September 2011 

Page 

3-97 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-87. Percentage of Mean Water Intake Consumed as Unfiltered and Filtered Tap Water by Pregnant 

Variables 

N 

Total 2,280 

Geographic Region 

Site 1 1,014 

Site 2 860 

Site 3 406 

Season 

Winter 583 

Spring 621 

Summer 559 

Fall 517 

Age at LMPa 

≤25 845 

26–30 709 

31–35 538 

≥36 188 

Education 

≤High school 685 

Some college 495 

≥4-year college 1,099 

Race/ethnicity 

White, non-Hispanic 1,272 

Black, non-Hispanic 720 

Hispanic, any race 202 

Other 84 

Marital Status 

Single, never married 711 

Married 1,492 

Other 76 

Annual Income ($) 

≤40,000 960 

40,000–80,000 728 

>80,000 499 

Employment 

No 678 

Yes 1,601 

BMI 

Low 266 

Normal 1,121 

Women 

Cold Unfiltered Tap Water 

% 

52 

46 

67 

37 

52 

53 

50 

54 

55 

49 

51 

53 

56 

53 

49 

50 

60 

37 

48 

57 

50 

57 

56 

51 

45 

52 

52 

50 

51 

Cold Filtered Tap 

Water 

% 

19 

28 

13 

10 

19 

19 

20 

19 

11 

22 

27 

22 

8 

16 

27 

26 

9 

9 

27 

9 

25 

9 

11 

24 

29 

21 

19 

21 

22 

Bottled Water 

% 

28 

26 

19 

53 

29 

28 

29 

26 

33 

28 

22 

25 

34 

30 

23 

23 

30 

54 

25 

33 

25 

34 

33 

24 

25 

27 

29 

29 

27 
 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-87. Percentage of Mean Water Intake Consumed as Unfiltered and Filtered Tap Water 

by Pregnant Women (continued) 

Cold Unfiltered Tap Water Cold Filtered Tap Bottled Water 

Variables Water 

N % % % 

Overweight 287 53 18 28 

Obese 540 56 14 29 

Diabetes 

No diabetes 2,209 52 19 28 

Regular diabetes 17 69 15 16 

Gestational diabetes 54 50 22 27 

Nausea during pregnancy 

No 385 54 18 28 

Yes 1,893 52 20 28 

Pregnancy history 

No prior pregnancy 685 48 21 31 

Prior pregnancy with no SABb 1,060 54 18 27 

Prior pregnancy with SAB 535 53 20 26 

Caffeine 

0 mg/day 577 50 22 27 

1–150 mg/day 520 53 17 29 

151–300 mg/day 432 52 17 30 

>300 mg/day 751 53 19 27 

Vitamin use 

No 176 57 8 34 

Yes 2,104 52 20 28 

Smoking 

Non-smoker 2,151 51 20 28 

<10 cigarettes/day 84 60 10 28 

≥10 cigarettes/day 45 66 7 22 

Alcohol use 

No 2,244 52 19 28 

Yes 36 58 19 23 

Recreational exercise 

No 1,053 54 14 31 

Yes 1,227 51 24 26 

Illicit drug use 

No 2,013 51 20 28 

Yes 266 56 12 31 

a LMP = Age of Last Menstrual Period. b SAB = spontaneous abortion. 

BMI = body mass index. 

Source: Forssen et al. (2007). 

Page Exposure Factors Handbook 

3-98 September 2011 
c 

Table 3-88. Water Intake at Various Activity Levels (L/hour)

a 

Room Temperature

b (°F) Activity Level 

High (0.15 hp/man)c Medium (0.10 hp/man)

c Low (0.05 hp/man)c 

Nd Intake N Intake N Intake 

100 - - - - 15 0.653 

(0.75) 

95 18 0.540 12 0.345 6 0.50 

(0.31) (0.59) (0.31) 

90 7 0.286 7 0.385 16 0.23 

(0.26) (0.26) (0.20) 

85 7 0.218 16 0.213 - ­

(0.36) (0.20) 

80 16 0.222 - - - ­

(0.14) 

a Data expressed as mean intake with standard deviation in parentheses. b Humidity = 80%; air velocity = 60 ft/minute. 

The symbol "hp" refers to horsepower. d Number of subjects with continuous data. 

- Data not reported in the source document. 

Source: McNall and Schlegel (1968). 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-89. Planning Factors for Individual Tap Water Consumption 

Environmental Condition Recommended Planning Factor 

(gal/day)a 

Recommended Planning Factor 

(L/day)a,b 

Hot 

Temperate 

Cold 

3.0c 

1.5d 

2.0e 

11.4 

5.7 

7.6 

a Based on a mix of activities among the workforce as follows: 15% light work; 65% medium work; 20% heavy 

work. These factors apply to the conventional battlefield where no nuclear, biological, or chemical weapons 

are used. b Converted from gal/day to L/day. c This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day-man for urination plus 6 

quarts/12-hours light work/man, 9 quarts/12-hours moderate work/man, and 12 quarts/12-hours heavy 

work/man. d This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day/man for urination plus 1 

quart/12-hours light work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/12-hours heavy 

work/man. e This assumes 1 quart/12-hour rest period/man for perspiration losses, 1 quart/day/man for urination, and 2 

quarts/day/man for respiration losses plus 1 quart/12-hours light work/man, 3 quarts/12-hours moderate 

work/man, and 6 quarts/6-hours heavy work/man. 

Source: U.S. Army (1983). 

Exposure Factors Handbook Page
 

September 2011 3-99 
 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Table 3-90. Pool Water Ingestion by Swimmers 

Study Group Number of 

Participants 

Average Water Ingestion Rate 

(mL/45-minute interval) 

Average Water Ingestion Rate 

(mL/hour)a 

Children <18 years old 

Males <18 years old 

Females <18 years old 

41 

20 

21 

37 

45 

30 

49 

60 

43 

Adults (>18 years) 

Men 

Women 

12 

4 

8 

16 

22 

12 

21 

29 

16 

a Converted from mL/45-minute interval. 

Source: Dufour et al. (2006). 

Table 3-91. Arithmetic Mean (maximum) Number of Dives per Diver and Volume of Water Ingested 

(mL/dive) 

Divers and Locations % of Divers # of Dives Volume of Water Ingested 

(mL) 

Occupational Divers (N = 35) 

Open sea 

Coastal water, USD <1 km 

Coastal water, USD >1 km 

Coastal water, USD unknown 

Open sea and coastal combined 

Freshwater, USD <1 km 

Freshwater, USD >1 km 

Freshwater, no USD 

Freshwater, USD unknown 

All freshwater combined 

57 

23 

20 

51 

-

37 

37 

37 

77 

-

24 (151) 

3.2 (36) 

1.8 (16) 

16 (200) 

-

8.3 (76) 

16 (200) 

16 (200) 

45 (200) 

-

8.7 (25) 

9.7 (25) 

8.3 (25) 

12 (100) 

9.8 (100) 

5.5 (25) 

5.5 (25) 

4.8 (25) 

6.0 (25) 

5.7 (25) 

Sports Divers—ordinary mask (N = 482) 

Open sea 

Coastal water 

Open sea and coastal combined 

Fresh recreational water 

Canals and rivers 

City canals 

Canals, rivers, city canals combined 

Swimming pools 

26 

78 

-

85 

11 

1.5 

-

65 

2.1 (120) 

14 (114) 

-

22 (159) 

0.65 (62) 

0.031 (4) 

-

17 (134) 

7.7 (100) 

9.9 (190) 

9.0 (190) 

13 (190) 

3.4 (100) 

2.8 (100) 

3.2 (100) 

20 (190) 

Sports Divers—full face mask (N = 482) 

Open sea 

Coastal water 

Fresh recreational water 

Canals and rivers 

City canals 

All surface water combined 

Swimming pools 

0.21 

1.0 

27 

1.2 

0.41 

-

2.3 

0.012 (6) 

0.10 (34) 

0.44 (80) 

0.098 (13) 

0.010 (3) 

-

0.21 (40) 

0.43 (2.8) 

1.3 (15) 

1.3 (15) 

0.47 (2.8) 

0.31 (2.8) 

0.81 (25) 

13 (190) 

N = Number of divers. 

USD = Upstream sewage discharge. 

Source: Schijven and de Roda Husman (2006). 

Page Exposure Factors Handbook 

3-100 September 2011 
Table 3-92. Exposure Parameters for Swimmers in Swimming Pools, Freshwater, and Seawater 

Adults Children <15 years Parameter Men Women 

Mean 95% UCI Mean 95% UCI Mean 95% UCI 

Swimming Duration (min) 

Swimming Pool 

Freshwater 

Seawater 

Volume Water Swallowed (mL) 

Swimming Pool 

Freshwater 

Seawater 

UCL = Upper confidence interval. 

Source: Schets et al. (2011). 

68 180 67 170 81 200 

54 200 54 220 79 270 

45 160 41 180 65 240 

34 170 23 110 51 200 

27 140 18 86 37 170 

27 140 18 90 31 140 

 

 

 

 

 

 

 

 

 

Table 3-93. Estimated Water Ingestion During Water Recreation Activities (mL/hr) 

Surface Water Study Swimming Pool Study 

Activity N Median Mean UCL N Median Mean UCL 

Limited Contact Scenarios 

Boating 316 2.1 3.7 11.2 0 - - -

Canoeing 766 76 

no capsize 2.2 3.8 11.4 2.1 3.6 11.0 

with capsize 3.6 6.0 19.9 3.9 6.6 22.4 

all activities 2.3 3.9 11.8 2.6 4.4 14.1 

Fishing 600 2.0 3.6 10.8 121 2.0 3.5 10.6 

Kayaking 801 104 

no capsize 2.2 3.8 11.4 2.1 3.6 10.9 

with capsize 2.9 5.0 16.5 4.8 7.9 26.8 

all activities 2.3 3.8 11.6 3.1 5.2 17.0 

Rowing 222 0 

no capsize 2.3 3.9 11.8 - - -

with capsize 2.0 3.5 10.6 - - -

all activities 2.3 3.9 11.8 - - -

Wading/splashing 0 - - - 112 2.2 3.7 1.0 

Walking 0 - - - 23 2.0 3.5 1.0 

Full Contact Scenarios 

Immersion 0 - - - 112 3.2 5.1 15.3 

Swimming 0 - - - 114 6.0 10.0 34.8 

TOTAL 2,705 662 

N = Number of participants.
 

UCL = Upper confidence limit (i.e. mean +1.96 × standard deviation).
 

- = No data.
 

Source: Dorevitch et al. (2011).
 

Exposure Factors Handbook 

Chapter 3—Ingestion of Water and Other Select Liquids 

Exposure Factors Handbook Page
 

September 2011 3-101 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

4. NON-DIETARY INGESTION FACTORS 

4.1. INTRODUCTION 

Adults and children have the potential for 

exposure to toxic substances through non-dietary 

ingestion pathways other than soil and dust ingestion 

(e.g., ingesting pesticide residues that have been 

transferred from treated surfaces to the hands or 

objects that are mouthed). Adults mouth objects such 

as cigarettes, pens and pencils, or their hands. Young 

children mouth objects, surfaces, or their fingers as 

they explore their environment. Mouthing behavior 

includes all activities in which objects, including 

fingers, are touched by the mouth or put into the 

mouth—except for eating and drinking—and 

includes licking, sucking, chewing, and biting (Groot 

et al., 1998). In addition, the sequence of events can 

be important, such as when a hand-washing occurs 

relative to contact with soil and hand-to-mouth 

contact. Videotaped observations of children’s 

mouthing behavior demonstrate the intermittent 

nature of hand-to-mouth and object-to-mouth 

behaviors in terms of the number of contacts 

recorded per unit of time (Ko et al., 2007). 

Adult and children’s mouthing behavior can 

potentially result in ingestion of toxic substances 

(Lepow et al., 1975). Only one study was located that 

provided data on mouthing frequency or duration for 

adults, but Cannella et al. (2006) indicated that adults 

with developmental disabilities frequently exhibit 

excessive hand-mouthing behavior. In a large 

non-random sample of children born in Iowa, parents 

reported non-nutritive sucking behaviors to be very 

common in infancy, and to continue for a substantial 

proportion of children up to the 3rd and 4th birthdays 

(Warren et al., 2000). Hand-to-mouth behavior has 

been observed in both preterm and full-term infants 

(Takaya et al., 2003; Blass et al., 1989; Rochat et al., 

1988). Infants are born with a sucking reflex for 

breast-feeding, and within a few months, they begin 

to use sucking or mouthing as a means to explore 

their surroundings. Sucking also becomes a means of 

comfort when a child is tired or upset. In addition, 

teething normally causes substantial mouthing 

behavior (i.e., sucking or chewing) to alleviate 

discomfort in the gums (Groot et al., 1998). 

There are three general approaches to gather data 

on children’s mouthing behavior: real-time hand 

recording, in which trained observers manually 

record information (Davis et al., 1995); videotranscription, in which trained videographers tape a 

child’s activities and subsequently extract the 

pertinent data manually or with computer software 

(Black et al., 2005; Zartarian et al., 1998, 1997a; 

Zartarian et al., 1997b); and questionnaire, or survey 

response, techniques (Stanek et al., 1998). With realtime hand recording, observations made by trained 

professionals—rather than parents—may offer the 

advantage of consistency in interpreting visible 

behaviors and may be less subjective than 

observations made by someone who maintains a 

caregiving relationship to the child. On the other 

hand, young children’s behavior may be influenced 

by the presence of unfamiliar people (Davis et al., 

1995). Groot et al. (1998) indicated that parent 

observers perceived that deviating from their usual 

care giving behavior by observing and recording 

mouthing behavior appeared to have influenced their 

children’s behavior. With video-transcription 

methodology, an assumption is made that the 

presence of the videographer or camera does not 

influence the child’s behavior. This assumption may 

result in minimal biases introduced when filming 

newborns, or when the camera and videographer are 

not visible to the child. However, if the children 

being studied are older than newborns and can see the 

camera or videographer, biases may be introduced. 

Ferguson et al. (2006) described apprehension caused 

by videotaping as well as situations where a child’s 

awareness of the videotaping crew caused “playacting” to occur, or parents indicated that the child 

was behaving differently during the taping session, 

although children tend to ignore the presence of the 

camera after some time has passed. Another possible 

source of measurement error may be introduced when 

children’s movements or positions cause their 

mouthing not to be captured by the camera. Data 

transcription errors can bias results in either the 

negative or positive direction. Finally, measurement 

error can occur if situations arise in which caregivers 

are absent during videotaping and researchers must 

stop videotaping and intervene to prevent risky 

behaviors (Zartarian et al., 1995). Meanwhile, survey 

response studies rely on responses to questions about 

a child’s mouthing behavior posed to parents or 

caregivers. Measurement errors from these studies 

could occur for a number of different reasons, 

including language/dialect differences between 

interviewers and respondents, question wording 

problems and lack of definitions for terms used in 

questions, differences in respondents’ interpretation 

of questions, and recall/memory effects. 

Some researchers express mouthing behavior as 

the frequency of occurrence (e.g., contacts per hour 

or contacts per minute). Others describe the duration 

of specific mouthing events, expressed in units of 

seconds or minutes. This chapter does not address 

issues related to contaminant transfer from thumbs, 

fingers, or objects or surfaces, into the mouth, and 

subsequent ingestion. Examples of how to use 

Exposure Factors Handbook Page 

September 2011 4-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

mouthing frequency and duration data can be found 

in a U.S. Environmental Protection Agency 

(U.S. EPA) Office of Pesticide Programs guidance 

document for conducting residential exposure 

assessments (U.S. EPA, 2009). This guidance 

document provides a standard method for estimating 

potential dose among toddlers from incidental 

ingestion of pesticide residues from previously 

treated turf. This scenario assumes that pesticide 

residues are transferred to the skin of toddlers playing 

on treated yards and are subsequently ingested as a 

result of hand-to-mouth transfer. A second scenario 

assumes that pesticide residues are transferred to a 

child’s toy and are subsequently ingested as a result 

of object-to-mouth transfer. Neither scenario includes 

residues ingested as a result of soil ingestion. 

The recommendations for mouthing frequency 

and duration for children only are provided in the 

next section, along with a summary of the confidence 

ratings for these recommendations. The 

recommended values for children are based on key 

studies identified by the U.S. EPA for this factor. 

Although some studies in Sections 4.3.1 and 4.4.1 are 

classified as key, they were not directly used to 

provide the recommendations. They are included as 

key because they were used by Xue et al. (2007) or 

Xue et al. (2010) in meta-analyses, which are the 

primary sources of the recommendations provided in 

this chapter for hand-to-mouth and object-to-mouth 

frequency, respectively. Following the 

recommendations, key and relevant studies on 

mouthing frequency (see Section 4.3) and duration 

(see Section 4.4) are summarized and the 

methodologies used in the key and relevant studies 

are described. Information on the prevalence of 

mouthing behavior is presented in Section 4.5. 

4.2. RECOMMENDATIONS 

The key studies described in Section 4.3 and 

Section 4.4 were used to develop recommended 

values for mouthing frequency and duration, 

respectively, among children. Only one relevant study 

was located that provided data on mouthing 

frequency or duration for adults. The recommended 

hand-to-mouth frequencies are based on data from 

Xue et al. (2007). Xue et al. (2007) conducted a 

secondary analysis of data from several of the studies 

summarized in this chapter, as well as data from 

unpublished studies. Xue et al. (2007) provided data 

for the age groups in U.S. EPA’s Guidance on 

Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005) and categorized the 

data according to indoor and outdoor contacts. The 

recommendations for frequency of object-to-mouth 

contact are based on data from Xue et al. (2010). Xue 

et al. (2010) conducted a secondary analysis of data 

from several of the studies summarized in this 

chapter, as well as data from an unpublished study. 

Recommendations for duration of object-to-mouth 

contacts are based on data from Juberg et al. (2001), 

Greene (2002), and Beamer et al. (2008). 

Recommendations on duration of object-to-mouth 

contacts pre-dated the U.S. EPA’s (2005) guidance on 

age groups. For cases in which age groups of children 

in the key studies did not correspond exactly to 

U.S. EPA’s recommended age groups, the closest age 

group was used. 

Table 4-1 shows recommended mouthing 

frequencies, expressed in units of contacts per hour, 

between either any part of the hand (including fingers 

and thumbs) and the mouth or between an object or 

surface and the mouth. Recommendations for handto-mouth duration are not provided since the 

algorithm to estimate exposures from this pathway is 

not time dependent. Table 4-2 presents the confidence 

ratings for the recommended values. The overall 

confidence rating is low for both frequency and 

duration of hand-to-mouth and object-to-mouth 

contact. 

Page Exposure Factors Handbook 

4-2 September 2011 
 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-1. Summary of Recommended Values for Mouthing Frequency and Duration 

Age Group 

Hand-to-Mouth 

Indoor Frequency (contacts/hour) Outdoor Frequency (contacts/hour) Source 

Mean 95th percentile Mean 95th percentile 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

-

-

28 

19 

20 

13 

15 

7 

-

-

-

-

65 

52 

63 

37 

54 

21 

-

-

-

-

-

15 

14 

5 

9 

3 

-

-

-

-

-

47 

42 

20 

36 

12 

-

-

Xue et al. (2007) 

Object-to-Mouth 

Indoor Frequency (contacts/hour) Outdoor Frequency (contacts/hour) 

Mean 95th percentile Mean 95th percentile 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

-

-

11 

20 

14 

9.9 

10 

1.1 

-

-

-

-

32 

38 

34 

24 

39 

3.2 

-

-

-

-

-

-

8.8 

8.1 

8.3 

1.9 

-

-

-

-

-

-

21 

40 

30 

9.1 

-

-

Xue et al. (2010) 

Mean Duration (minutes/hour) 95th percentile Duration (minutes/hour) 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

-

-

11a 

9c 

7e 

10f 

-

-

-

-

-

-

26b 

19d 

22e 

11g 

-

-

-

-

Juberg et al. (2001); Greene 

(2002); Beamer et al. (2008) 

a Mean calculated from Juberg et al. (2001) (0 to 18 months) and Greene (2002) (3 to 12 months). b Calculated 95th percentile from Greene (2002) (3 to 12 months). c Mean calculated from Juberg et al. (2001) (0 to 18 months), Greene (2002) (3 to 12 months), and Beamer et al. (2008) (6 to 13 

months). d Calculated 95th percentile from Greene (2002) (3 to 12 months) and Beamer et al. (2008) (6 to 13 months). e Mean and 95th percentile from Greene (2002) (12 to 24 months). f Mean calculated from Juberg et al. (2001) (19 to 36 months), Greene (2002) (24 to 36 months), and Beamer et al. (2008) (20 to 

26 months). g Calculated 95th percentile from Greene (2002) (24 to 36 months) and Beamer et al. (2008) (20 to 26 months). 

- = No data. 

Exposure Factors Handbook Page 

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Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-2. Confidence in Mouthing Frequency and Duration Recommendations 

General Assessment Factor Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The approaches for data collection and analysis used were adequate for 

providing estimates of children’s mouthing frequencies and durations. 

Sample sizes were very small relative to the population of interest. Xue et 

al. (2007) and (2010) meta-analysis of secondary data was considered to be 

of suitable utility for the purposes for developing recommendations. 

Bias in either direction likely exists in both frequency and duration 

estimates; the magnitude of bias is unknown. 

Low 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

Key studies for older children focused on mouthing behavior while the 

infant studies were designed to research developmental issues. 

Most key studies were of samples of U.S. children, but, due to the small 

sample sizes and small number of locations under study, the study subjects 

may not be representative of the overall U.S. child population. 

The studies were conducted over a wide range of dates. However, the 

currency of the data is not expected to affect mouthing behavior 

recommendations. 

Extremely short data collection periods may not represent behaviors over 

longer time periods. 

Low 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The journal articles are in the public domain, but, in many cases, primary 

data were unavailable. 

Data collection methodologies were capable of providing results that were 

reproducible within a certain range. 

Several of the key studies applied and documented quality assurance/quality 

control measures. 

Low 

Variability and Uncertainty 

Variability in Population 

Description of Uncertainty 

The key studies characterized inter-individual variability to a limited extent, 

and they did not characterize intra-individual variability over diurnal or 

longer term time frames. 

The study authors typically did not attempt to quantify uncertainties 

inherent in data collection methodology (such as the influence of observers 

on behavior), although some described these uncertainties qualitatively. The 

study authors typically did attempt to quantify uncertainties in data analysis 

methodologies (if video-transcription methods were used). Uncertainties 

arising from short data collection periods typically were unaddressed either 

qualitatively or quantitatively. 

Low 

Evaluation and Review 

Peer Review 

Number and Agreement of 

Studies 

All key studies appear in peer-review journals. 

Several key studies were available for both frequency and duration, but data 

were not available for all age groups. The results of studies from different 

researchers are generally in agreement. 

Medium 

Overall rating Low 

Page Exposure Factors Handbook 

4-4 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

4.3.	 NON-DIETARY INGESTION— 

MOUTHING FREQUENCY STUDIES 

4.3.1. Key Studies of Mouthing Frequency 

4.3.1.1.	 Zartarian et al. (1997b)—Quantifying 

Videotaped Activity Patterns: Video 

Translation Software and Training 

Technologies/Zartarian et al. (1997a)— 

Quantified Dermal Activity Data From a 

Four-Child Pilot Field Study/Zartarian et 

al. (1998)—Quantified Mouthing Activity 

Data From a Four-Child Pilot Field Study 

Zartarian et al. (1998, 1997a; 1997b) conducted a 

pilot study of the video-transcription methodology to 

investigate the applicability of using videotaping for 

gathering information related to children’s activities, 

dermal exposures, and mouthing behaviors. The 

researchers had conducted studies using the real-time 

hand recording methodology. These studies 

demonstrated poor inter-observer reliability and 

observer fatigue when working for long periods of 

time. This prompted the investigation into using 

videotaping with transcription of the children’s 

activities at a point in time after the videotaped 

observations occurred. 

Four Mexican American farm worker children in 

the Salinas Valley of California each were videotaped 

with a hand-held video camera during their waking 

hours, excluding time spent in the bathroom, over 

one day in September 1993. The boys were 2 years 

10 months old and 3 years 9 months old; the girls 

were 2 years and 5 months old, and 4 years and 2 

months old. Time of videotaping was 6.0 hours for 

the younger girl, 6.6 hours for the older girl, 8.4 

hours for the younger boy and 10.1 hours for the 

older boy. The videotaping gathered information on 

detailed micro-activity patterns of children to be used 

to evaluate software for videotaped activities and 

translation training methods. The researchers reported 

measures taken to assess inter-observer reliability and 

several problems with the video-transcription 

process. 

The hourly data showed that non-dietary object 

mouthing occurred in 30 of the 31 hours of tape time, 

with one child eating during the hour in which no 

non-dietary object mouthing occurred. Mean objectto-mouth contacts for the four children were reported 

to be 11 contacts per hour (median = 9 contacts per 

hour), with an average per child range of 1 to 

29 contacts per hour (Zartarian et al., 1998). Objects 

mouthed included bedding/towels, clothes, dirt, 

grass/vegetation, hard surfaces, hard toys, paper/card, 

plush toy, and skin (Zartarian et al., 1998). Average 

hand-to-mouth contacts for the four children were 

13 contacts per hour [averaging the sum of left hand 

and right hand-to-mouth contacts and averaging 

across children, from Zartarian et al. (1997a)], with 

the average per child ranging from 9 to 19 contacts 

per hour. 

This study’s primary purpose was to develop and 

evaluate the video-transcription methodology; a 

secondary purpose was collection of mouthing 

behavior data. The sample of children studied was 

very small and not likely to be representative of the 

national population. As with other video-transcription 

studies, the presence of non-family-member 

videographers and a video camera may have 

influenced the children’s behavior. 

4.3.1.2.	 Reed et al. (1999)—Quantification of 

Children’s Hand and Mouthing Activities 

Through a Videotaping Methodology 

In this study, Reed et al. (1999) used a videotranscription methodology to quantify the frequency 

and type of children’s hand and mouth contacts, as 

well as a survey response methodology, and 

compared the videotaped behaviors with parents’ 

perceptions of those behaviors. Twenty children ages 

3 to 6 years old selected randomly at a daycare center 

in New Brunswick, NJ, and 10 children ages 2 to 5 

years old at residences in Newark and Jersey City, NJ 

who were not selected randomly, were studied (sex 

not specified). For the video-transcription 

methodology, inter-observer reliability tests were 

performed during observer training and at four points 

during the two years of the study. The researchers 

compared the results of videotaping the ten children 

in the residences with their parents’ reports of the 

children’s daily activities. Mouthing behaviors 

studied included hand-to-mouth and hand bringing 

object-to-mouth. 

Table 4-3 presents the video-transcription 

mouthing contact frequency results. The authors 

analyzed parents’ responses on frequencies of their 

children’s mouthing behaviors and compared those 

responses with the children’s videotaped behaviors, 

which revealed certain discrepancies: Parents’ 

reported hand-to-mouth contact of “almost never” 

corresponded to overall somewhat lower videotaped 

hand-to-mouth frequencies than those of children 

whose parents reported “sometimes,” but there was 

little correspondence between parents’ reports of 

object-to-mouth frequency and videotaped behavior. 

The advantages of this study were that it 

compared the results of video-transcription with the 

survey response methodology results and that it 

described quality assurance steps taken to assure 

reliability of transcribed videotape data. However, 

only a small number of children were studied, some 

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were not selected for observation randomly, and the 

sample of children studied may not be representative 

of either the locations studied or the national 

population. Because of the children’s ages, the 

presence of unfamiliar persons following the children 

with a video camera may influence the videotranscription results. The parents’ survey responses 

also may be influenced by recall/memory effects and 

other limitations of survey methodologies. 

4.3.1.3.	 Freeman et al. (2001)—Quantitative 

Analysis of Children’s Micro-Activity 

Patterns: The Minnesota Children’s 

Pesticide Exposure Study 

Freeman et al. (2001) conducted a survey 

response and video-transcription study of some of the 

respondents in a phased study of children’s pesticide 

exposures in the summer and early fall of 1997. A 

probability-based sample of 168 families with 

children ages 3 to <14 years old in urban 

(Minneapolis/St. Paul) and non-urban (Rice and 

Goodhue Counties) areas of Minnesota answered 

questions about children’s mouthing of paint chips, 

food-eating without utensils, eating of food dropped 

on the floor, mouthing of non-food items, and 

mouthing of thumbs and fingers. For the survey 

response portion of the study, parents provided the 

responses for children ages 3 and 4 years and 

collaborated with or assisted older children with their 

responses. Of the 168 families responding to the 

survey, 102 were available, selected, and agreed to 

measurements of pesticide exposure. Of these 

102 families, 19 agreed to videotaping of the study 

children’s activities for a period of 4 consecutive 

hours. 

Based on the survey responses for 168 children, 

the 3-year olds had significantly more positive 

responses for all reported behavior compared to the 

other age groups. The authors stated that they did not 

know whether parent reporting of 3-year olds’ 

behavior influenced the responses given. Table 4-4 

shows the percentage of children, grouped by age, 

who were reported to exhibit non-food related 

mouthing behaviors. Table 4-5 presents the mean and 

median number of mouthing contacts by age for the 

19 videotaped children. Among the four age 

categories of these children, object-to-mouth 

activities were significantly greater for the 3- and 

4-year olds than any other age group, with a median 

of 3 and a mean of 6 contacts per hour (p = 0.002, 

Kruskal Wallis test comparison across four age 

groups). Hand-to-mouth contacts had a median of 3.5 

and mean of 4 contacts per hour for the three 3- and 

4-year olds observed, median of 2.5 and mean of 

8 contacts per hour for the seven 5- and 6-year olds 

observed, median of 3 and mean of 5 contacts per 

hour for the four 7- and 8-year olds observed, and 

median of 2 and mean of 4 for the five 10-, 11-, and 

12-year olds observed. Sex differences were observed 

for some of the activities, with boys spending 

significantly more time outdoors than girls. Hand-tomouth and object-to-mouth activities were less 

frequent outdoors than indoors for both boys and 

girls. 

For the 19 children in the video-transcription 

portion of the study, inter-observer reliability checks 

and quality control checks were performed on 

randomly sampled tapes. For four children’s tapes, 

comparison of the manual video-transcription with a 

computerized transcription method (Zartarian et al., 

1995) also was performed; no significant differences 

were found in the frequency of events recorded using 

the two techniques. The frequency of six behaviors 

(hand-to-mouth, hand-to-object, object-to-mouth, 

hand-to-smooth surface, hand-to-textured surface, 

and hand-to-clothing) was recorded. The amount of 

time each child spent indoors, outdoors, and in 

contact with soil or grass, as well as whether the child 

was barefoot was also recorded. For the four children 

whose tapes were analyzed with the computerized 

transcription method, which calculates event 

durations, the authors stated that most hand-to-mouth 

and object-to-mouth activities were observed during 

periods of lower physical activity, such as television 

viewing. 

An advantage to this study is that it included 

results from two separate methodologies, and 

included quality assurance steps taken to assure 

reliability of transcribed videotape data. However, the 

children in this study may not be representative of all 

children in the United States. Variation in who 

provided the survey responses (sometimes parents 

only, sometimes children with parents) may have 

influenced the responses given. Children studied 

using the video-transcription methodology were not 

chosen randomly from the survey response group. 

The presence of unfamiliar persons following the 

children with a video camera may have influenced 

the video-transcription methodology results. 

4.3.1.4.	 Tulve et al. (2002)—Frequency of 

Mouthing Behavior in Young Children 

Tulve et al. (2002) coded the unpublished Davis 

et al. (1995) data for location (indoor and outdoor) 

and activity type (quiet or active) and analyzed the 

subset of the data that consisted of indoor mouthing 

behavior during quiet activity (72 children, ranging in 

age from 11 to 60 months). A total of one hundred 

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eighty-six 15-minute observation periods were 

included in the study, with the number of observation 

periods per child ranging from 1 to 6. Tulve et al. 

(2002) used the Davis et al. (1995) data from which 

the children were selected randomly based on date of 

birth through a combination of birth certificate 

records and random digit dialing of residential 

telephone numbers. 

Results of the data analyses indicated that there 

was no association between mouthing frequency and 

sex, but a clear association between mouthing 

frequency and age was observed. The analysis 

indicated that children ≤24 months had the highest 

frequency of mouthing behavior (81 events/hour) and 

that children >24 months had the lowest 

(42 events/hour) (see Table 4-6). Both groups of 

children were observed to mouth toys and hands 

more frequently than household surfaces or body 

parts other than hands. 

An advantage of this study is that the randomized 

design may mean that the children studied were 

relatively representative of young children living in 

the study area, although they may not be 

representative of the U.S. population. Due to the ages 

of the children studied, the observers’ use of 

headphones and manual recording of mouthing 

behavior on observation sheets may have influenced 

the children’s behavior. 

4.3.1.5.	 AuYeung et al. (2004)—Young Children’s 

Mouthing Behavior: An Observational 

Study via Videotaping in a Primarily 

Outdoor Residential Setting 

AuYeung et al. (2004) used a video-transcription 

methodology to study a group of 38 children 

(20 females and 18 males; ages 1 to 6 years), 37 of 

whom were selected randomly via a telephone 

screening survey of a 300 to 400 square mile portion 

of the San Francisco, CA peninsula, along with one 

child selected by convenience because of time 

constraints. Families who lived in a residence with a 

lawn and whose annual income was >$35,000 were 

asked to participate. Videotaping took place between 

August 1998 and May 1999 for approximately two 

hours per child. Videotaping by one researcher was 

supplemented with field notes taken by a second 

researcher who also was present during taping. Most 

of the videotaping took place during outdoor play, 

however, data were included for several children (one 

child <2 years old and eight children >2 years old) 

who had more than 15 minutes of indoor play during 

their videotaping sessions. 

The videotapes were translated into American 

Standard Code for Information Interchange (ASCII) 

computer files using Virtual Timing DeviceTM 

software described in Zartarian et al. (1997b). Both 

frequency and duration (see Section 4.4.2.5 of this 

chapter) were analyzed. Between 5% and 10% of the 

data files translated were randomly chosen for quality 

control checks for inter-observer agreement. 

Ferguson et al. (2006) described quality control 

aspects of the study in detail. 

For analysis, the mouthing contacts were divided 

into indoor and outdoor locations and 

16 object/surface categories. Mouthing frequency 

was analyzed by age and sex separately and in 

combination. Mouthing contacts were defined as 

contact with the lips, inside of the mouth, and/or the 

tongue; dietary contacts were ignored. Table 4-7 

shows mouthing frequencies for indoor locations. For 

the one child observed that was ≤24 months of age, 

the total mouthing frequency was 84.8 contacts/hour; 

for children >24 months, the median indoor mouthing 

frequency was 19.5 contacts/hour. Outdoor median 

mouthing frequencies (see Table 4-8) were very 

similar for children ≤24 months of age 

(13.9 contacts/hour) and >24 months 

(14.6 contacts/hour). 

Non-parametric tests, such as the Wilcoxon rank 

sum test, were used for the data analyses. Both age 

and sex were found to be associated with differences 

in mouthing behavior. Girls had significantly higher 

frequencies of mouthing contacts with the hands and 

non-dietary objects than boys (p = 0.01 and p = 

0.008, respectively). 

This study provides distributions of outdoor 

mouthing frequencies with a variety of objects and 

surfaces. Although indoor mouthing data also were 

included in this study, the results were based on a 

small number of children (N = 9) and a limited 

amount of indoor play. The sample of children may 

be representative of certain socioeconomic strata in 

the study area, but it is not likely to be representative 

of the national population. Because of the children’s 

ages, the presence of unfamiliar persons following 

the children with a video camera may have 

influenced the video-transcription methodology 

results. 

4.3.1.6.	 Black et al. (2005)—Children’s Mouthing 

and Food-Handling Behavior in an 

Agricultural Community on the 

U.S./Mexico Border 

Black et al. (2005) studied mouthing behavior of 

children in a Mexican-American community along 

the Rio Grande River in Texas, during the spring and 

summer of 2000, using a survey response and a 

video-transcription methodology. A companion study 

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of this community (Shalat et al., 2003) identified 

870 occupied households during the April 2000 U.S. 

Census and contacted 643 of these via in-person 

interview to determine the presence of children under 

the age of 3 years. Of the 643 contacted, 91 had at 

least one child under the age of 3 years (Shalat et al., 

2003). Of these 91 households, the mouthing and 

food-handling behavior of 52 children (26 boys and 

26 girls) from 29 homes was videotaped, and the 

children’s parents answered questions about 

children’s hygiene, mouthing and food-handling 

activities (Black et al., 2005). The study was of 

children ages 7 to 53 months, grouped into four age 

categories: infants (7 to 12 months), 1-year olds (13 

to 24 months), 2-year olds (25 to 36 months), and 

preschoolers (37 to 53 months). 

The survey asked questions about children’s ages, 

sexes, reported hand-washing, mouthing and foodhandling behavior (N = 52), and activities (N = 49). 

Parental reports of thumb/finger placement in the 

mouth showed decreases with age. The researchers 

attempted to videotape each child for 4 hours. The 

children were followed by the videographers through 

the house and yard, except for times when they were 

napping or using the bathroom. Virtual Timing 

DeviceTM software, mentioned earlier, was used to 

analyze the videotapes. 

Based on the results of videotaping, most of the 

children (49 of 52) spent the majority of their time 

indoors. Of the 39 children who spent time both 

indoors and outdoors, all three behaviors 

(hand-to-mouth, object-to-mouth and food handling) 

were more frequent and longer while the child was 

indoors. Hand-to-mouth activity was recorded during 

videotaping for all but one child, a 30 month old girl. 

For the four age groups, the mean hourly hand-tomouth frequency ranged from 11.9 (2-year olds) to 

22.1 (preschoolers), and the mean hourly 

object-to-mouth frequency ranged from 7.8 

(2-year olds) to 24.4 (infants). No significant linear 

trends were seen with age or sex for hand-to-mouth 

hourly frequency. A significant linear trend was 

observed for hourly object-to-mouth frequency, 

which decreased as age increased (adjusted 

R2 = 0.179; p = 0.003). Table 4-9 shows the results of 

this study. 

Because parental survey reports were not strongly 

correlated with videotaped hand or object mouthing, 

the authors suggested that future research might 

include alternative methods of asking about mouthing 

behavior to improve the correlation of questionnaire 

data with videotaped observations. 

One advantage of this study is that it compared 

survey responses with videotaped information on 

mouthing behavior. A limitation is that the sample 

was fairly small and was from a limited area (midRio Grande Valley) and is not likely to be 

representative of the national population. Because of 

the children’s ages, the presence of unfamiliar 

persons following the children with a video camera 

may have influenced the video-transcription 

methodology results. 

4.3.1.7.	 Xue et al. (2007)—A Meta-Analysis of 

Children’s Hand-to-Mouth Frequency 

Data for Estimating Non-Dietary Ingestion 

Exposure 

Xue et al. (2007) gathered hand-to-mouth 

frequency data from nine available studies 

representing 429 subjects and more than 2,000 hours 

of behavior observation (Beamer et al., 2008; Black 

et al., 2005; Hore, 2003; Greene, 2002; Tulve et al., 

2002; Freeman et al., 2001; Leckie et al., 2000; Reed 

et al., 1999; Zartarian et al., 1998). Two of these 

studies [i.e., Leckie et al. (2000); Hore (2003)] are 

unpublished data sets and are not summarized in this 

chapter. The remaining seven studies are summarized 

elsewhere in this chapter. Xue et al. (2007) conducted 

a meta-analysis to study differences in hand-to-mouth 

behavior. The purpose of the analysis was to 

1.	 examine differences across studies by age 

[using the new U.S. EPA recommended age 

groupings (U.S. EPA, 2005)], sex, and 

indoor/outdoor location; 

2.	 fit variability distributions to the available 

hand-to-mouth frequency data for use in onedimensional Monte Carlo exposure 

assessments; 

3.	 fit uncertainty distributions to the available 

hand-to-mouth frequency data for use in twodimensional Monte Carlo exposure 

assessments; and 

4.	 assess hand-to-mouth frequency data needs 

using the new U.S. EPA recommended age 

groupings (U.S. EPA, 2005). 

The data were sorted into age groupings. Visual 

inspection of the data and statistical methods (i.e., 

method of moments and maximum likelihood 

estimation) were used, and goodness-of-fit tests were 

applied to verify the selection among lognormal, 

Weibull, and normal distributions (Xue et al., 2007). 

Analyses to study inter- and intra-individual 

variability of indoor and outdoor hand-to-mouth 

frequency were conducted. It was found that age and 

location (indoor vs. outdoor) were important factors 

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contributing to hand-to-mouth frequency, but study 

and sex were not (Xue et al., 2007). Distributions of 

hand-to-mouth frequencies were developed for both 

indoor and outdoor activities. Table 4-10 presents 

distributions for indoor settings while Table 4-11 

presents distributions for outdoor settings. Hand-tomouth frequencies decreased for both indoor and 

outdoor activity as age increased, and they were 

higher indoors than outdoors for all age groups (Xue 

et al., 2007). 

A strength of this study is that it is the first effort 

to fit hand-to-mouth distributions of children in 

different locations while using U.S. EPA’s 

recommended age groups. Limitations of the studies 

used in this meta-analysis apply to the results from 

the meta-analysis as well; the uncertainty analysis in 

this study does not account for uncertainties arising 

out of differences in approaches used in the various 

studies used in the meta-analysis. 

4.3.1.8.	 Beamer et al. (2008)—Quantified Activity 

Pattern Data From 6 to 27-Month-Old 

Farm Worker Children for Use in 

Exposure Assessment 

Beamer et al. (2008) conducted a follow-up to the 

pilot study performed by Zartarian et al. (1998, 

1997a; 1997b), described in Sections 4.3.1.1 and 

4.4.2.2. For this study, a convenience sample of 23 

children residing in the farm worker community of 

Salinas Valley, CA, was enrolled. Participants were 6­

to 13-month-old infants or 20- to 26-month-old 

toddlers. Two researchers videotaped each child’s 

activities for a minimum of 4 hours and kept a 

detailed written log of locations visited and objects 

and surfaces contacted by the child. A questionnaire 

was administered to an adult in the household to 

acquire demographic data, housing and cleaning 

characteristics, eating patterns, and other information 

pertinent to the child’s potential pesticide exposure. 

Table 4-12 presents the distribution of 

object/surface contact frequency for infants and 

toddlers in events/hour. The mean hand-to-mouth 

frequency was 18.4 events/hour. The mean mouthing 

frequency of non-dietary objects was 

29.2 events/hour. Table 4-13 presents the 

distributions for the mouthing frequency and duration 

of non-dietary objects, and it highlights the 

differences between infants and toddlers. Toddlers 

had higher mouthing frequencies with non-dietary 

items associated with pica (i.e., paper) while infants 

had higher mouthing frequencies with other 

non-dietary objects. In addition, boys had higher 

mouthing frequencies than girls. The advantage of 

this study is that it included both infants and toddlers. 

Differences between the two age groups, as well as 

sex differences, could be observed. As with other 

video-transcription studies, the presence of 

non-family-member videographers and a video 

camera may have influenced the children’s behavior. 

4.3.1.9.	 Xue et al. (2010)—A Meta-Analysis of 

Children’s Object-to-Mouth Frequency 

Data for Estimating Non-Dietary Ingestion 

Exposure 

Xue et al. (2010) gathered object-to-mouth 

frequency data from 7 available studies representing 

438 subjects and approximately 1,500 hours of 

behavior observation. The studies used in this 

analysis included six published studies that were also 

individually summarized in this chapter (Beamer et 

al., 2008; AuYeung et al., 2004; Greene, 2002; Tulve 

et al., 2002; Freeman et al., 2001; Reed et al., 1999) 

as well as one unpublished data set (Hore, 2003). 

These data were used to conduct a meta-analysis to 

study differences in object-to-mouth behavior. The 

purpose of the analysis was to 

1.	 “examine differences across studies by age 

[using the new U.S. EPA recommended age 

groupings (U.S. EPA, 2005)], sex, and 

indoor/outdoor location; 

2.	 fit variability distributions to the available 

object to-mouth frequency data for use in one 

dimensional Monte Carlo exposure 

assessments; 

3.	 fit uncertainty distributions to the available 

object-to-mouth frequency data for use in two 

dimensional Monte Carlo exposure 

assessments; and 

4.	 assess object-to-mouth frequency data needs 

using the new U.S. EPA recommended age 

groupings (U.S. EPA, 2005).” 

 

 

 

 

 

 

 

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Chapter 4—Non-Dietary Ingestion Factors 

The data were sorted into age groupings. Visual 

inspection of the data and statistical methods (i.e., 

method of moments and maximum likelihood 

estimation) were used, and goodness-of-fit tests were 

applied to verify the selection among lognormal, 

Weibull, and normal distributions (Xue et al., 2010). 

Analyses to study inter- and intra-individual 

variability of indoor and outdoor object-to-mouth 

frequency were conducted. It was found that age, 

location (indoor vs. outdoor), and study were 

important factors contributing to object-to-mouth 

frequency, but study and sex were not (Xue et al., 

2010). Distributions of object-to-mouth frequencies 

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were developed for both indoor and outdoor 

activities. Table 4-14 presents distributions for indoor 

settings while Table 4-15 presents distributions for 

outdoor settings. Object-to-mouth frequencies 

decreased for both indoor and outdoor activity as age 

increased (i.e., after age 6 to <12 months for indoor 

activity; and after 3 to <6 years for outdoor activity), 

and were higher indoors than outdoors for all age 

groups (Xue et al., 2010). 

A strength of this study is that it is the first effort 

to fit object-to-mouth distributions of children in 

different locations while using U.S. EPA’s 

recommended age groups. Limitations of the studies 

used in this meta-analysis apply to the results from 

the meta-analysis as well; the uncertainty analysis in 

this study does not account for uncertainties arising 

out of differences in approaches used in the various 

studies used in the meta-analysis. 

4.3.2. Relevant Studies of Mouthing Frequency 

4.3.2.1. Davis et al. (1995)—Soil Ingestion in 

Children With Pica: Final Report 

In 1992, under a Cooperative Agreement with 

U.S. EPA, the Fred Hutchinson Cancer Research 

Center conducted a survey response and real-time 

hand recording study of mouthing behavior data. The 

study included 92 children (46 males, 46 females) 

ranging in age from 12 months to <60 months, from 

Richland, Kennewick, and Pasco, WA. The children 

were selected randomly based on date of birth 

through a combination of birth certificate records and 

random digit dialing of residential telephone 

numbers. For each child, data were collected in one 

7-day period during January to April, 1992. 

Eligibility included residence within the city limits, 

residence duration >1 month, and at least one parent 

or guardian who spoke English. Most of the adults 

who responded to the survey reported their marital 

status as being married (90%), their race as 

Caucasian (89%), their household income in the 

>$30,000 range (56%), or their housing status as 

single-family home occupants (69%). 

The survey asked questions about thumbsucking and frequency questions about pacifier use, 

placing fingers, hands and feet in the mouth, and 

mouthing of furniture, railings, window sills, floor, 

dirt, sand, grass, rocks, mud, clothes, toys, crayons, 

pens, and other items. Table 4-16 shows the survey 

responses for the 92 study children. For most of the 

children in the study, the mouthing behavior real-time 

hand recording data were collected simultaneously by 

parents and by trained observers who described and 

quantified the mouthing behavior of the children in 

their home environment. The observers recorded 

mouth and tongue contacts with hands, other body 

parts, natural objects, surfaces, and toys every 

15 seconds during 15-minute observation periods 

spread over 4 days. Parents and trained observers 

wore headphones that indicated elapsed time (Davis 

et al., 1995). If all attempted observation periods 

were successful, each child would have a total of 

sixteen 15-minute observation periods with sixty 

15-second intervals per 15-minute observation 

period, or nine hundred sixty 15-second intervals in 

all. The number of successful intervals of observation 

ranged from 0 to 840 per child. Comparisons of the 

inter-observer reliability between the trained 

observers and parents showed 

“a high degree of correlation between the 

overall degree of both mouth and tongue 

activity recorded by parents and observers. 

For total mouth activity, there was a 

significant correlation between the rankings 

obtained according to parents and observers, 

and parents were able to identify the same 

individuals as observers as being most and 

least oral in 60% of the cases” (Davis et al., 

1995). 

One advantage of this study is the simultaneous 

observations by both, parents and trained observers, 

that allow comparisons regarding the consistency of 

the recorded observations. The random nature in 

which the population was selected may provide a 

representative population of the study area, within 

certain limitations, but not of the national population. 

In addition, this study was considered relevant 

because the data were not analyzed for deriving 

estimates of mouthing contact. These data were 

analyzed by Tulve et al. (2002) (see Section 4.3.1.4). 

Simultaneous collection of food, medication, fecal, 

and urine samples that occurred as part of the overall 

study (not described in this summary) may have 

contributed a degree of deviation from normal 

routines within the households during the 7 days of 

data collection and may have influenced children’s 

usual behaviors. Wearing of headphones by parents 

and trained observers during mouthing observations, 

presence of non-family-member observers, and 

parents’ roles as observers as well as caregivers also 

may have influenced the results; the authors state 

“Having the child play naturally while being 

observed was challenging. Usually the first day of 

observation was the most difficult in this respect, and 

by the third or fourth day of observation the child 

generally paid little attention to the observers.” 

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4.3.2.2.	 Lew and Butterworth (1997)—The 

Development of Hand-Mouth Coordination 

in 2- to 5-Month-Old Infants: Similarities 

With Reaching and Grasping 

Lew and Butterworth (1997) studied 14 infants 

(10 males, 4 females; mostly first-borns) in Stirling, 

United Kingdom, in 1990 using a video-transcription 

methodology. Attempts were made to study each 

infant within 1 week of the infant’s 2-, 3-, 4-, and 

5-month birthdays. After becoming accustomed to the 

testing laboratory, and with their mothers present, 

infants were placed in semi-reclining seats and filmed 

during an experimental protocol in which researchers 

placed various objects into the infants’ hands. Infants 

were observed for two baseline periods of 2 minutes 

each. The researchers coded all contacts to the face 

and mouth that occurred during baseline periods 

(prior to and after the object handling period) as well 

as contacts occurring during the object handling 

period. Hand-to-mouth contacts included contacts 

that landed directly in or on the mouth as well as 

those in which the hand landed on the face first and 

then moved to the mouth. The researchers assessed 

inter-observer agreement using a rater not involved 

with the study, for a random proportion 

(approximately 10%) of the movements documented 

during the object handling period, and reported interobserver agreement of 0.90 using Cohen’s kappa for 

the location of contacts. The frequency of contacts 

ranged between zero and one contact per minute. 

The advantages of this study were that use of 

video cameras could be expected to have minimal 

effect on infant behavior for infants of these ages, and 

the researchers performed tests of inter-observer 

reliability. A disadvantage is that the study included 

baseline observation periods of only 2 minutes’ 

duration, during which spontaneous hand-to-mouth 

movements could be observed. The extent to which 

these infants’ behavior is representative of other 

infants of these ages is unknown. 

4.3.2.3.	 Tudella et al. (2000)—The Effect of OralGustatory, Tactile-Bucal, and TactileManual Stimulation on the Behavior of the 

Hands in Newborns 

Tudella et al. (2000) studied the frequency of 

hand-to-mouth contact, as well as other behaviors, in 

24 full-term Brazilian newborns (10 to 14 days old) 

using a video-transcription methodology. Infants 

were in an alert state, in their homes in silent and 

previously heated rooms in a supine position and had 

been fed between 1 and 1 1/2 hours before testing. 

Infants were studied for a 4-minute baseline period 

without stimuli before experimental stimuli were 

administered. Results from the four-minute baseline 

period, without stimuli, indicated that the mean 

frequency of hand-to-mouth contact (defined as right 

hand or left hand touching the lips or entering the 

buccal cavity, either with or without rhythmic jaw 

movements) was almost 3 right hand contacts and 

slightly more than 1.5 left hand contacts, for a total 

hand-to-mouth contact frequency of about 4 contacts 

in the 4-minute period. The researchers performed 

inter-observer reliability tests on the videotape data 

and reported an inter-coder Index of Concordance of 

93%. 

The advantages of this study were that use of 

video cameras could be expected to have virtually no 

effect on newborns’ behavior, and inter-observer 

reliability tests were performed. However, the study 

data may not represent newborn hand-to-mouth 

contact during non-alert periods such as sleep. The 

extent to which these infants’ behavior is 

representative of other full-term 10- to 14-day-old 

infants’ behavior is unknown. 

4.3.2.4.	 Ko et al. (2007)—Relationships of Video 

Assessments of Touching and Mouthing 

Behaviors During Outdoor Play in Urban 

Residential Yards to Parental Perceptions 

of Child Behaviors and Blood Lead Levels 

Ko et al. (2007) compared parent survey 

responses with results from a video-transcription 

study of children’s mouthing behavior in outdoor 

settings, as part of a study of relationships between 

children’s mouthing behavior and other variables 

with blood lead levels. A convenience sample of 

37 children (51% males, 49% females) 14 to 

69 months old was recruited via an urban health 

center and direct contacts in the surrounding area, 

apparently in Chicago, IL. Participating children 

were primarily Hispanic (89%). The mouth area was 

defined as within 1 inch of the mouth, including the 

lips. Items passing beyond the lips were defined as in 

the mouth. Placement of an object or food item in the 

mouth along with part of the hand was counted as 

both hand and food or hand and object in mouth. 

Mouthing behaviors included hand-to-mouth area 

both with and without food, hand-in-mouth with or 

without food, and object-in-mouth including food, 

drinks, toys, or other objects. 

Survey responses for the 37 children who also 

were videotaped included parents reporting children’s 

inserting hand, toys, or objects in mouth when 

playing outside, and inserting dirt, stones, or sticks in 

mouth. Video-transcription results of outdoor play for 

these 37 children indicated 0 to 27 hand-in-mouth 

and 3 to 69 object-in-mouth touches per hour for the 

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13 children reported to frequently insert hand, toys, 

or objects in mouth when playing outside; 0 to 67 

hand-in-mouth, and 7 to 40 object-in-mouth touches 

per hour for the 10 children reported to “sometimes” 

perform this behavior; 0 to 30 hand-in-mouth and 

0 to 125 object in mouth touches per hour for the 

12 children reported to “hardly ever” perform this 

behavior, and 1 to 8 hand-in-mouth and 3 to 6 objectin-mouth touches per hour for the 2 children reported 

to “never” perform this behavior. 

Videotaping was attempted for 2 hours per child 

over two or more play sessions, with videographers 

trying to avoid interacting with the children. Children 

played with their usual toys and partners, and no 

instructions were given to parents regarding their 

supervision of the children’s play. The authors stated 

that during some portion of the videotape time, 

children’s hands and mouths were out of camera 

view. Videotape transcription was performed 

manually, according to a modified version of the 

protocol used in the Reed et al. (1999) study. 

Inter-observer reliability between three 

video-transcribers was checked with seven 30-minute 

video segments. 

One strength of this study is its comparison of 

survey responses with results from the videotranscription methodology. A limitation is that the 

non-randomly selected sample of children studied is 

unlikely to be representative of the national 

population. Comparing results from this study with 

results from other video-transcription studies may be 

problematic because of inclusion of food handling 

with hand-to-mouth and object-to-mouth frequency 

counts. Due to the children’s ages, their behavior may 

have differed from normal patterns because of the 

presence of strangers who videotaped them. 

4.3.2.5.	 Nicas and Best (2008)—A Study 

Quantifying the Hand-to-Face Contact 

Rate and Its Potential Application to 

Predicting Respiratory Tract Infection 

Nicas and Best (2008) conducted an observational 

study on adults (five women and five men; ages not 

specified), in which individuals were videotaped 

while performing office-type work for a 3-hour 

period. The videotapes were viewed by the 

investigators, who counted the number of 

hand-to-face touches the subjects made while they 

worked on a laptop computer, read, or wrote. 

Following the observations, the sample mean and 

standard deviation were computed for the number of 

times each subject touched his or her eyes, nostrils, 

and lips. For the three combinations of touch 

frequencies (i.e., lips-eyes, lips-nostrils, 

eyes-nostrils), Spearman rank correlation coefficients 

were computed and tests of the hypothesis that the 

rank correlation coefficients exceeded zero were 

performed. 

Table 4-17 shows the frequency of hand-to-face 

contacts with the eyes, nostrils, and lips of the 

subjects, and the sum of these counts. There was 

considerable inter-individual variability among the 

subjects. During the 3-hour continuous study period, 

the total number of hand contacts with the eyes, lips 

and nostrils ranged from 3 to 104 for individual 

subjects, with a mean of 47. The mean per hour 

contact rate was 15.7. There was a positive 

correlation between the number of hand contacts with 

lips and eyes and with lips and nostrils (subjects who 

touched their lips frequently also touched their eyes 

and nostrils frequently). The Spearman rank 

correlation coefficients for contacts between different 

facial targets were 0.76 for the lips and eyes; 0.66 for 

the lips and nostrils, and 0.44 for the eyes and 

nostrils. 

The study’s primary purpose was to quantify 

hand-to-face contacts in order to determine the 

application of this contact rate in predicting 

respiratory tract infection. The authors developed an 

algebraic model for estimating the dose of pathogens 

transferred to target facial membranes during a 

defined exposure period. The advantage of this study 

is that it determined the frequency of hand-to-face 

contacts for adults. A limitation of the study is that 

there were very few subjects (five women and five 

men) who may not have been representative of the 

U.S. population. In addition, as with other videotranscription studies, the presence of videographers 

and a video camera may have influenced the subjects’ 

behaviors. 

4.4.	 NON-DIETARY INGESTION— 

MOUTHING DURATION STUDIES 

4.4.1. Key Mouthing Duration Studies 

4.4.1.1.	 Juberg et al. (2001)—An Observational 

Study of Object Mouthing Behavior by 

Young Children 

Juberg et al. (2001) studied 385 children ages 0 to 

36 months in western New York State, with parents 

collecting real-time hand-recording mouthing 

behavior data, primarily in the children’s own home 

environments. The study consisted of an initial pilot 

study conducted in February 1998, a second phase 

conducted in April 1998, and a third phase conducted 

at an unspecified later time. The study’s sample was 

drawn from families identified in a child play 

research center database or whose children attended a 

child care facility in the same general area; some 

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geographic variation within the local area was 

obtained by selecting families with different zip 

codes in the different study phases. The pilot phase 

had 30 children who participated out of 150 surveys 

distributed; the second phase had 187 children out of 

approximately 300 surveys distributed, and the third 

phase had 168 participants out of 300 surveys 

distributed. 

Parents were asked to observe their child’s 

mouthing of objects only; hand-to-mouth behavior 

was not included. Data were collected on a single day 

(pilot and second phases) or 5 days (third phase); 

parents recorded the insertion of objects into the 

mouth by noting the “time in” and “time out” and the 

researchers summed the recorded data to tabulate 

total times spent mouthing the various objects during 

the days of observation. Thus, the study data were 

presented as minutes per day of object mouthing 

time. Mouthed items were classified as pacifiers, 

teethers, plastic toys, or other objects. 

Table 4-18 shows the results of the combined 

pilot and second phase data. For both age groups, 

mouthing time for pacifiers greatly exceeded 

mouthing time for non-pacifiers, with the difference 

more acute for the older age group than for the 

younger age group. Histograms of the observed data 

show a peak in the low end of the distribution (0 to 

100 minutes per day) and a rapid decline at longer 

durations. 

A third phase of the study focused on children 

between the ages of 3 and 18 months and included 

only non-pacifier objects. Subjects were observed for 

5 non-consecutive days over a 2-month period. A 

total of 168 participants returned surveys for at least 

one day, providing a total of 793 person-days of data. 

The data yielded a mean non-pacifier object 

mouthing duration of 36 minutes per day; the mean 

was the same when calculated on the basis of 

793 person-days of data as on the basis of 168 daily 

average mouthing times. 

One advantage of this study is the large sample 

size (385 children); however, the children apparently 

were not selected randomly, although some effort was 

made to obtain local geographic variation among 

study participants. There is no description of the 

socioeconomic status or racial and ethnic identities of 

the study participants. The authors do not describe 

the methodology parents used to record mouthing 

event durations (e.g., using stopwatches, analog or 

digital clocks, or guesses). The authors stated that 

using mouthing event duration units of minutes rather 

than seconds may have yielded observations rounded 

to the nearest minute. 

4.4.1.2.	 Greene (2002)—A Mouthing Observation 

Study of Children Under Six Years of Age 

The U.S. Consumer Product Safety Commission 

conducted a survey response and real-time hand 

recording study between December 1999 and 

February 2001 to quantify the cumulative time per 

day that young children spend awake, not eating, and 

mouthing objects. “Mouthing” was defined as 

children sucking, chewing, or otherwise putting an 

object on their lips or into their mouth. Participants 

were recruited via a random digit dialing telephone 

survey in urban and nearby rural areas of Houston, 

TX and Chicago, IL. Of the 115,289 households 

surveyed, 1,745 households had a child under the age 

of 6 years and were willing to participate. In the 

initial phase of the study, 491 children ages 3 to 

81 months participated. Parents were instructed to 

use watches with second hands or to count seconds to 

estimate mouthing event durations. Parents also were 

to record mouthing frequency and types of objects 

mouthed. Parents collected data in four separate, nonconsecutive 15-minute observation periods. Initially, 

parents were called back by the researchers and asked 

to provide their data over the telephone. Of the 

491 children, 43 children (8.8%) had at least one 

15-minute observation period with mouthing event 

durations recorded as exceeding 15 minutes. Due to 

this data quality problem, the researchers excluded 

the parent observation data from further analysis. 

In a second phase, trained observers used 

stopwatches to record the mouthing behaviors and 

mouthing event durations of the subset of 109 of 

these children ages 3 to 36 months and an additional 

60 children (total in second phase, 169), on 2 hours 

of each of 2 days. The observations were done at 

different times of the day at the child’s home and/or 

child care facility. Table 4-19 shows the prevalence of 

observed mouthing among the 169 children in the 

second phase. All children were observed to mouth 

during the 4 hours of observation time; 99% mouthed 

parts of their anatomy. Pacifiers were mouthed by 

27% in an age-declining pattern ranging from 47% of 

children less than 12 months old to 10% of the 2- to 

<3-year olds. 

Table 4-20 provides the average mouthing time 

by object category and age in minutes per hour. The 

average mouthing time for all objects ranged from 

5.3 to 10.5 minutes per hour, with the highest 

mouthing time corresponding to children <1 year of 

age and the lowest to the 2 to <3 years of age 

category. Among the objects mouthed, pacifiers 

represented about one third of the total mouthing 

time, with 3.4 minutes per hour for the youngest 

children, 2.6 minutes per hour for the children 

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between 1 and 2 years and 1.8 minutes per hour for 

children 2 to <3 years old. The next largest single 

item category was anatomy. In this category, children 

under 1 year of age spent 2.4 minutes per hour 

mouthing fingers and thumbs; this behavior declined 

with age to 1.2 minutes per hour for children 2 to <3 

years old. 

Of the 169 children in the second phase, data 

were usable on the time awake and not eating (or 

“exposure time”) for only 109; data for the remaining 

60 children were missing. Thus, in order to develop 

extrapolated estimates of daily mouthing time for the 

109 children, from the 2 hours of observation per day 

for two days, the researchers developed a statistical 

model that accounted for the children’s demographic 

characteristics, that estimated exposure times for the 

60 children with missing data, and then computed 

statistics for the extrapolated daily mouthing times 

for all 169 children, using a “bootstrap” procedure. 

Using this method, the estimated mean daily 

mouthing time of objects other than pacifiers ranged 

from 37 minutes/day to 70 minutes/day with the 

lowest number corresponding to the 2 to <3-year-old 

children and the largest number corresponding to the 

3 to <12-month-old children. 

The 551 child participants were 55% males, 

45% females. The study’s sample was drawn in an 

attempt to duplicate the overall U.S. demographic 

characteristics with respect to race, ethnicity, 

socioeconomic status and urban/suburban/rural 

settings. The sample families’ reported annual 

incomes were generally higher than those of the 

overall U.S. population. 

This study’s strength was that it consisted of a 

randomly selected sample of children from both 

urban and non-urban areas in two different 

geographic areas within the United States. However, 

the observers’ presence and use of a stopwatch to 

time mouthing durations may have affected the 

children’s behavior. 

4.4.1.3.	 Beamer et al. (2008)—Quantified Activity 

Pattern Data From 6- to 27-Month-Old 

Farm Worker Children for Use in 

Exposure Assessment 

Beamer et al. (2008) conducted a follow-up to the 

pilot study performed by Zartarian et al. (1998, 

1997a; 1997b), described in Sections 4.3.1.1 and 

4.4.2.2. For this study, a convenience sample of 23 

children residing in the farm worker community of 

Salinas Valley, CA was enrolled. Participants were 6­

to 13-month-old infants or 20- to 26-month-old 

toddlers. Two researchers videotaped each child’s 

activities for a minimum of 4 hours, and kept a 

detailed written log of locations visited and objects 

and surfaces contacted by the child. A questionnaire 

was administered to an adult in the household to 

acquire demographic data, housing and cleaning 

characteristics, eating patterns, and other information 

pertinent to the child’s potential pesticide exposure. 

Table 4-21 presents the object/surface hourly 

contact duration in minutes/hour. The mean hourly 

mouthing duration for hands and non-dietary objects 

was 1.4 and 3.5 minutes/hour, respectively. Infants 

had higher hourly mouthing duration with toys and 

all non-dietary objects than toddlers. Girls had higher 

contact durations than boys. 

The advantage of this study is that it included 

both infants and toddlers. Differences between the 

two age groups, as well as sex differences, could be 

observed. As with other video-transcription studies, 

the presence of non-family-member videographers 

and a video camera may have influenced the 

children’s behavior. 

4.4.2. Relevant Mouthing Duration Studies 

4.4.2.1.	 Barr et al. (1994)—Effects of Intra-Oral 

Sucrose on Crying, Mouthing, and HandMouth Contact in Newborn and Six-WeekOld Infants 

Barr et al. (1994) studied hand-to-mouth contact, 

as well as other behaviors, in 15 newborn 

(eight males, seven females) and fifteen 5- to 7-week 

old (eight males, seven females) full-term Canadian 

infants using a video-transcription methodology. The 

newborns were 2- to 3-days old, were in a quiet, 

temperature-controlled room at the hospital, were in a 

supine position and had been fed between 2 1/2 and 

3 1/2 hours before testing. Barr et al. (1994) analyzed 

a 1-minute baseline period, with no experimental 

stimuli, immediately before a sustained crying 

episode lasting 15 seconds. For the newborns, 

reported durations of hand-to-mouth contact during 

10-second intervals of the 1-minute baseline period 

were in the range of 0 to 2%. The 5- to 7-week old 

infants apparently were studied at primary care 

pediatric facilities when they were in bassinets 

inclined at an angle of 10 degrees. For these slightly 

older infants, the baseline periods analyzed were less 

than 20 seconds in length, but Barr et al. (1994) 

reported similarly low mean percentages of the 

10-second intervals (approximately 1% of the time 

with hand-to-mouth contact). Hand-to-mouth contact 

was defined as “any part of the hand touching the lips 

and/or the inside of the mouth.” The researchers 

performed inter-observer reliability tests on the 

videotape data and reported a mean inter-observer 

reliability of 0.78 by Cohen’s kappa. 

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The advantages of this study were that use of 

video cameras could be expected to have virtually no 

effect on newborns’ or five to seven week old infants’ 

behavior, and that inter-observer reliability tests were 

performed. The study data did not represent newborn 

or 5- to 7-week-old infant hand-to-mouth contact 

during periods in which infants of these ages were in 

a sleeping or other non-alert state, and data may only 

represent behavior immediately prior to a state of 

distress (sustained crying episode). The extent to 

which these infants’ behavior is representative of 

other full-term infants of these ages is unknown. 

4.4.2.2.	 Zartarian et al. (1997b)—Quantifying 

Videotaped Activity Patterns: Video 

Translation Software and Training 

Technologies/Zartarian et al. (1997a)— 

Quantified Dermal Activity Data From a 

Four-Child Pilot Field Study/Zartarian et 

al. (1998)—Quantified Mouthing Activity 

Data From a Four-Child Pilot Field Study 

As described in Section 4.3.1.1, Zartarian et al. 

(1998, 1997a; 1997b) conducted a pilot study of the 

video-transcription methodology to investigate the 

applicability of using videotaping for gathering 

information related to children’s activities, dermal 

exposures and mouthing behaviors. The researchers 

had conducted studies using the real-time hand 

recording methodology. These studies demonstrated 

poor inter-observer reliability and observer fatigue 

when attempted for long periods of time. This 

prompted the investigation into using videotaping 

with transcription of the children’s activities at a 

point in time after the videotaped observations 

occurred. 

Four Mexican-American farm worker children in 

the Salinas Valley of California each were videotaped 

with a hand-held videocamera during their waking 

hours, excluding time spent in the bathroom, over 

1 day in September 1993. The boys were 2 years 

10 months old and 3 years 9 months old; the girls 

were 2 years 5 months old and 4 years 2 months old. 

Time of videotaping was 6.0 hours for the younger 

girl, 6.6 hours for the older girl, 8.4 hours for the 

younger boy and 10.1 hours for the older boy. The 

videotaping gathered information on detailed 

micro-activity patterns of children to be used to 

evaluate software for videotaped activities and 

translation training methods. 

The four children mouthed non-dietary objects an 

average of 4.35% (range 1.41 to 7.67%) of the total 

observation time, excluding the time during which 

the children were out of the camera’s view (Zartarian 

et al., 1998). Objects mouthed included 

bedding/towels, clothes, dirt, grass/vegetation, hard 

surfaces, hard toys, paper/card, plush toy, and skin 

(Zartarian et al., 1998). Frequency distributions for 

the four children’s non-dietary object contact 

durations were reported to be similar in shape. 

Reported hand-to-mouth contact presumably is a 

subset of the object-to-mouth contacts described in 

Zartarian et al. (1997b), and is described in Zartarian 

et al. (1997a). The four children mouthed their hands 

an average of 2.35% (range 1.0 to 4.4%) of 

observation time (Zartarian et al., 1997a). The 

researchers reported measures taken to assess 

inter-observer reliability and several problems with 

the video-transcription process. 

This study’s primary purpose was to develop and 

evaluate the video-transcription methodology; a 

secondary purpose was collection of mouthing 

behavior data. The sample of children studied was 

very small and not likely to be representative of the 

national population. Thus, U.S. EPA did not judge it 

to be suitable for consideration as a key study of 

children’s mouthing behavior. As with other videotranscription studies, the presence of non-family 

member videographers and a video camera may have 

influenced the children’s behavior. 

4.4.2.3.	 Groot et al. (1998)—Mouthing Behavior of 

Young Children: An Observational Study 

In this study, Groot et al. (1998) examined the 

mouthing behavior of 42 Dutch children (21 boys and 

21 girls) between the ages of 3 and 36 months in late 

July and August 1998. Parent observations were 

made of children in 36 families. Parents were asked 

to observe their children 10 times per day for 

15-minute intervals (i.e., 150 minutes total per day) 

for two days and measure mouthing times with a 

stopwatch. In this study, mouthing was defined as “all 

activities in which objects are touched by mouth or 

put into the mouth except for eating and drinking. 

This term includes licking as well as sucking, 

chewing and biting.” 

For the study, a distinction was made between 

toys meant for mouthing (e.g., pacifiers, teething 

rings) and those not meant for mouthing. Inter- and 

intra-observer reliability was measured by trained 

observers who co-observed a portion of observation 

periods in three families and who co-observed and 

repeatedly observed some video transcriptions made 

of one child. Another quality assurance procedure 

performed for the extrapolated total mouthing time 

data was to select 12 times per hour randomly during 

the entire waking period of four children during 

1 day, in which the researchers recorded activities 

and total mouthing times. 

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Although the sample size was relatively small, the 

results provided estimates of mouthing times, other 

than pacifier use, during 1 day. The results were 

extrapolated to the entire day based on the 

150 minutes of observation per day, and the mean 

value for each child for the 2 days of observations 

was interpreted as the estimate for that child. Table 

4-22 shows summary statistics. The standard 

deviation in all four age categories except the 3- to 

6-month old children exceeded the estimated mean. 

The 3 to 6 month children (N = 5) were estimated to 

have mean non-pacifier mouthing durations of 

36.9 minutes per day, with toys as the most 

frequently mouthed product category, while the 6 to 

12 month children (N = 14) were estimated to have 

44 minutes per day (fingers most frequently 

mouthed). The 12- to 18-month olds’ (N = 12) 

estimated mean non-pacifier mouthing time was 

16.4 minutes per day, with fingers most frequently 

mouthed, and 18- to 36-month olds’ (N = 11) 

estimated mean non-pacifier mouthing time was 

9.3 minutes per day (fingers most frequently 

mouthed). 

One strength of this study is that the researchers 

recognized that observing children might affect their 

behavior and emphasized to the parents the 

importance of making observations under conditions 

that were as normal as possible. In spite of these 

efforts, many parents perceived that their children’s 

behavior was affected by being observed and that 

observation interfered with caregiving 

responsibilities such as comforting children when 

they were upset. Other limitations included a small 

sample size that was not representative of the Dutch 

population and that also may not be representative of 

U.S. children. Technical problems with the 

stopwatches affected at least 14 of 36 parents’ data. 

4.4.2.4.	 Smith and Norris (2003)—Reducing the 

Risk of Choking Hazards: Mouthing 

Behavior of Children Aged 1 Month to 

5 Years/Norris and Smith (2002)— 

Research Into the Mouthing Behavior of 

Children up to 5 Years Old 

Smith and Norris (2003) conducted a real-time 

hand recording study of mouthing behavior among 

236 children (111 males, 125 females) in the United 

Kingdom (exact locations not specified) who were 

from 1 month to 5 years old. Children were observed 

at home by parents, who used stopwatches to record 

the time that mouthing began, the type of mouthing, 

the type of object being mouthed, and the time that 

mouthing ceased. Children were observed for a total 

of 5 hours over a 2-week period; the observation time 

consisted of twenty 15-minute periods spread over 

different times and days during the child’s waking 

hours. Parents also recorded the times each child was 

awake and not eating meals so that the researchers 

could extrapolate estimates of total daily mouthing 

time from the shorter observation periods. Mouthing 

was defined as licking/lip touching, sucking/trying to 

bite and biting or chewing, with a description of each 

category, together with pictures, given to parents as 

guidance for what to record. 

Table 4-23 shows the results of the study. While 

no overall pattern could be found in the different age 

groups tested, a Kruskal-Wallis test on the data for all 

items mouthed indicated that there was a significant 

difference between the age groups. Across all age 

groups and types of items, licking and sucking 

accounted for 64% of all mouthing behavior. 

Pacifiers and fingers exhibited less variety on 

mouthing behavior (principally sucking), while other 

items had a higher frequency of licking, biting, or 

other mouthing. 

The researchers randomly selected 25 of the 

236 children for a single 15-minute observation of 

each child (total observation time across all children: 

375 minutes), to compare the mouthing frequency 

and duration data obtained according to the real-time 

hand recording and the video-transcription 

methodologies, as well as the reliability of parent 

observations versus those made by trained 

professionals. For this group of 25 children, the total 

number of mouthing behavior events recorded by 

video (160) exceeded those recorded by parents (114) 

and trained observers (110). Similarly, the total 

duration recorded by video (24 minutes and 15 

seconds) exceeded that recorded by observers 

(parents and trained observers both recorded identical 

totals of 19 minutes and 44 seconds). The mean and 

standard deviation of observed mouthing time were 

both lower when recorded by video versus real-time 

hand recording. The maximum observed mouthing 

time also was lower (6 minutes and 7 seconds by 

video vs. 9 minutes and 43 seconds for both parents 

and trained observers). 

The strengths of this study were its comparison of 

three types of observation (i.e., parents, trained 

observers, and videotaping), and its detailed reporting 

of mouthing behaviors by type, object/item mouthed, 

and age group. However, the children studied may 

not be representative of U.S. children. In addition, the 

study design or approach made the data less 

applicable for exposure assessment purposes 

(e.g., data on mouthing behavior that was intended to 

be used in reducing the risk of choking hazards). 

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4.4.2.5.	 AuYeung et al. (2004)—Young Children’s 

Mouthing Behavior: An Observational 

Study via Videotaping in a Primarily 

Outdoor Residential Setting 

As described in Section 4.3.1.5, AuYeung et al. 

(2004) used a video-transcription methodology to 

study a group of 38 children (20 females and 

18 males; ages 1 to 6 years), 37 of whom were 

selected randomly via a telephone screening survey 

of a 300- to 400-square-mile portion of the San 

Francisco, CA peninsula, along with one child 

selected by convenience because of time constraints. 

Families who lived in a residence with a lawn and 

whose annual income was >$35,000 were asked to 

participate. Videotaping took place between August 

1998 and May 1999 for approximately 2 hours per 

child. Videotaping by one researcher was 

supplemented with field notes taken by a second 

researcher who was also present during taping. Most 

of the videotaping took place during outdoor play, 

however, data were included for several children (one 

child <2 years old and 8 children >2 years old) who 

had more than 15 minutes of indoor play during their 

videotaping sessions. 

The videotapes were translated into ASCII 

computer files using VirtualTimingDeviceTM software 

described in Zartarian et al. (1997b). Both frequency 

(see Section 4.3.1.5 of this chapter) and duration 

were analyzed. Between 5 and 10% of the translated 

data files were randomly chosen for quality control 

checks for inter-observer agreement. Ferguson et al. 

(2006) described quality control aspects of the study 

in detail. 

For analysis, the mouthing contacts were divided 

into indoor and outdoor locations and 

16 object/surface categories. Mouthing durations 

were analyzed by age and sex separately and in 

combination. Mouthing contacts were defined as 

contact with the lips, inside of the mouth, and/or the 

tongue; dietary contacts were ignored. Table 4-24 

shows mouthing durations (outdoor locations). For 

the children in all age groups, the median duration of 

each mouthing contact was 1 to 2 seconds, 

confirming the observations of other researchers that 

children’s mouthing contacts are of very short 

duration. For the one child observed that was 

≤24 months, the total indoor mouthing duration was 

11.1 minutes/hour; for children >24 months, the 

median indoor mouthing duration was 

0.9 minutes/hour (see Table 4-25). For outdoor 

environments, median contact durations for these age 

groups decreased to 0.8 and 0.6 minutes/hour, 

respectively (see Table 4-26). 

Non-parametric tests, such as the Wilcoxon rank 

sum test, were used for the data analyses. Both age 

and sex were found to be associated with differences 

in mouthing behavior. Girls’ hand-to-mouth contact 

durations were significantly shorter than for boys (p 

= 0.04). 

This study provides distributions of outdoor 

mouthing durations with various objects and surfaces. 

Although indoor mouthing data were also included in 

this study, the results were based on a small number 

of children (N = 9) and a limited amount of indoor 

play. The sample of children may be representative of 

certain socioeconomic strata in the study area, but is 

not likely to be representative of the national 

population. Because of the children’s ages, the 

presence of unfamiliar persons following the children 

with a video camera may have influenced the 

video-transcription methodology results. 

4.5. MOUTHING PREVALENCE STUDIES 

4.5.1. Stanek et al. (1998)—Prevalence of Soil 

Mouthing/Ingestion Among Healthy 

Children Aged 1 to 6 

Stanek et al. (1998) characterized the prevalence 

of mouthing behavior among healthy children based 

on a survey response study of parents or guardians of 

533 children (289 females, 244 males) ages 1 to 

6 years old. Study participants were attendees at 

scheduled well-child visits at three clinics in western 

Massachusetts in August through October, 1992. 

Participants were questioned about the frequency of 

28 mouthing behaviors of the children over the 

preceding month in addition to exposure time 

(e.g., time outdoors, play in sand or dirt) and 

children’s characteristics (e.g., teething). 

Table 4-27 presents the prevalence of reported 

non-food ingestion/mouthing behaviors by child’s 

age as the percentage of children whose parents 

reported the behavior in the preceding month. The 

table includes a column of data for the 3 to <6 year 

age category; this column was calculated by 

U.S. EPA as a weighted mean value of the individual 

data for 3-, 4-, and 5-year olds in order to conform to 

the standardized age categories used in this 

handbook. Among all the age groups, 1-year olds had 

the highest reported daily sucking of fingers/thumb; 

the proportion dropped for 2-year olds, but rose 

slightly for 3- and 4-year olds and declined again 

after age 4. A similar pattern was reported for more 

than weekly finger/thumb sucking, while more than 

monthly finger/thumb sucking showed a very slight 

increase for 6-year olds. Reported pacifier use was 

highest for 1-year olds and declined with age for 

daily and more than weekly use; for more than 

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Chapter 4—Non-Dietary Ingestion Factors 

monthly use of a pacifier several 6-year olds were 

reported to use pacifiers, which altered the 

age-declining pattern for the daily and more than 

weekly reported pacifier use. A pattern similar to 

pacifier use existed with reported mouthing of 

teething toys, with highest reported use for 1-year 

olds, a decline with age until age 6 when reported use 

for daily, more than weekly, and more than monthly 

use of teething toys increased. 

The authors developed an outdoor mouthing rate 

for each child as the sum of rates for responses to 

four questions on mouthing specific outdoor objects. 

Survey responses were converted to mouthing rates 

per week, using values of 0, 0.25, 1, and 7 for 

responses of never, monthly, weekly, and daily 

ingestion. Reported outdoor soil mouthing behavior 

prevalence was found to be higher than reported 

indoor dust mouthing prevalence, but both behaviors 

had the highest reported prevalence among 1-year old 

children and decreased for children 2 years and older. 

The investigators conducted principal component 

analyses on responses to four questions relating to 

ingestion/mouthing of outdoor objects in an attempt 

to characterize variability. Outdoor 

ingestion/mouthing rates constructed from the survey 

responses were that children 1-year old were reported 

to mouth or ingest outdoor objects 4.73 times per 

week while 2- to 6-year olds were reported to mouth 

or ingest outdoor objects 0.44 times per week. The 

authors developed regression models to identify 

factors related to high outdoor mouthing rates. The 

authors found that children who were reported to play 

in sand or dirt had higher outdoor object 

ingestion/mouthing rates. 

A strength of this study is that it was a large 

sample obtained in an area with urban and semiurban residents within various socioeconomic 

categories and with varying racial and ethnic 

identities. However, difficulties with parents’ recall of 

past events may have caused either over-estimates or 

under-estimates of the behaviors studied. 

4.5.2. Warren et al. (2000)—Non-Nutritive 

Sucking Behaviors in Preschool Children: 

A Longitudinal Study 

Warren et al. (2000) conducted a survey 

response study of a non-random cohort of children 

born in certain Iowa hospitals from early 1992 to 

early 1995 as part of a study of children’s fluoride 

exposure. For this longitudinal study of children’s 

non-nutritive sucking behaviors, 1,374 mothers were 

recruited at the time of their newborns’ birth, and 

more than 600 were active in the study until the 

children were at least 3 years old. Survey questions 

on non-nutritive sucking behaviors were administered 

to the mothers when the children were 6 weeks, and 

3, 6, 9, 12, 16, and 24 months old, and then yearly 

after age 24 months. Questions were posed regarding 

the child’s sucking behavior during the previous 3 to 

12 months. 

The authors reported that nearly all children 

sucked non-nutritive items, including pacifiers, 

thumbs or other fingers, and/or other objects, at some 

point in their early years. The parent-reported sucking 

behavior prevalence peaked at 91% for 3 month old 

children. At 2 years of age, a majority (53%) retained 

a sucking habit, while 29% retained the habit at age 

3 years and 21% at age 4 years. Parent-reported 

pacifier use was 28% for 1-year olds, 25% for 2-year 

olds, and 10% for 3-year olds. The authors cautioned 

against generalizing the results to other children 

because of study design limitations. 

Strengths of this study were its longitudinal 

design and the large sample size. A limitation is that 

the non-random selection of original study 

participants and the self-selected nature of the cohort 

of survey respondents who participated over time 

means that the results may not be representative of 

other U.S. children of these ages. 

4.6. REFERENCES FOR CHAPTER 4 

AuYeung, W; Canales, R; Beamer, P; Ferguson, AC; 

Leckie, JO. (2004). Young children’s 

mouthing behavior: An observational study 

via videotaping in a primarily outdoor 

residential setting. J Child Health 2: 271­

295. 

Barr, RG; Quek, VSH; Cousineau, D; Oberlander, 

TF; Brian, JA; Young, SN. (1994). Effects of 

intra-oral sucrose on crying, mouthing and 

hand-mouth contact in newborn and sixweek-old infants. Dev Med Child Neurol 36: 

608-618. 

Beamer, P; Key, ME; Ferguson, AC; Canales, RA; 

Auyeung, W; Leckie, JO. (2008). Quantified 

activity pattern data from 6 to 27-month-old 

farmworker children for use in exposure 

assessment. Environ Res 108: 239-246. 

http://dx.doi.org/10.1016/j.envres.2008.07.0 

07. 

Black, K; Shalat, SL; Freeman, NCG; Jimenez, M; 

Donnelly, KC; Calvin, JA. (2005). 

Children's mouthing and food-handling 

behavior in an agricultural community on 

the US/Mexico border. J Expo Anal Environ 

Epidemiol 15: 244-251. 

http://dx.doi.org/10.1038/sj.jea.7500398. 

Page Exposure Factors Handbook 

4-18 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Blass, EM; Fillion, TJ; Rochat, P; Hoffmeyer, LB; 

Metzger, MA. (1989). Sensorimotor and 

motivational determinants of hand-mouth 

coordination in 1-3-day-old human infants. 

Dev Psychol 25: 963-975. 

http://dx.doi.org/10.1037//0012­

1649.25.6.963. 

Cannella, HI; O'Reilly, MF; Lancioni, GE. (2006). 

Treatment of hand mouthing in individuals 

with severe to profound developmental 

disabilities: A review of the literature. Res 

Dev Disabil 27: 529-544. 

http://dx.doi.org/10.1016/j.ridd.2005.06.004. 

Davis, S; Myers, PA; Kohler, E; Wiggins, C. (1995). 

Soil ingestion in children with pica: Final 

report. (U.S. EPA Cooperative Agreement 

CR 816334-01). Seattle, WA: Fred 

Hutchison Cancer Research Center. 

Ferguson, AC; Canales, RA; Beamer, P; Auyeung, 

W; Key, M; Munninghoff, A; Lee, KT; 

Robertson, A; Leckie, JO. (2006). Video 

methods in the quantification of children's 

exposures. J Expo Sci Environ Epidemiol 

16: 287-298. 

http://dx.doi.org/10.1038/sj.jea.7500459. 

Freeman, NCG; Jimenez, M; Reed, KJ; Gurunathan, 

S; Edwards, RD; Roy, A; Adgate, JL; 

Pellizzari, ED; Quackenboss, J; Sexton, K; 

Lioy, PJ. (2001). Quantitative analysis of 

children's microactivity patterns: the 

Minnesota children's pesticide exposure 

study. J Expo Sci Environ Epidemiol 11: 

501-509. 

Greene, MA.	 (2002). Mouthing times for children 

from the observational study. Bethesda, MD: 

U.S. Consumer Product Safety Commission. 

Groot, ME; Lekkerkerk, MC; Steenbekkers, LPA. 

(1998). Mouthing behavior of young 

children: An observational study. 

Wageningen, the Netherlands: Agricultural 

University. 

Hore, P. (2003) Pesticide accumulation patterns for 

child accessible surfaces and objects and 

urinary excretion by children for two weeks 

after a professional crack and crevice 

application. (Doctoral Dissertation). Rutgers 

University and the University of Medicine 

and Dentistry of New Jersey, Newark, NJ. 

Juberg, DR; Alfano, K; Coughlin, RJ; Thompson, 

KM. (2001). An observational study of 

object mouthing behavior by young 

children. Pediatrics 107: 135-142. 

Ko, S; Schaefer, PD; Vicario, CM; Binns, HJ; Safer 

Yards, P. (2007). Relationships of video 

assessments of touching and mouthing 

behaviors during outdoor play in urban 

residential yards to parental perceptions of 

child behaviors and blood lead levels. J 

Expo Sci Environ Epidemiol 17: 47-57. 

http://dx.doi.org/10.1038/sj.jes.7500519. 

Leckie, JO; Naylor, KA; Canales, RA; Ferguson, AC; 

Cabrera, NL; Hurtado, AL; Lee, K; Lin, AY; 

Ramirez, JD; VM, V. (2000). Quantifying 

children’s microlevel activity data from 

existing videotapes. (Reference No. 

U2F112OT-RT. 2000). Washington, DC: 

U.S. Environmental Protection Agency. 

Lepow, ML; Bruckman, L; Gillette, M; Markowitz, 

S; Robino, R; Kapish, J. (1975). 

Investigations into sources of lead in the 

environment of urban children. Environ Res 

10: 415-426. 

Lew, AR; Butterworth, G. (1997). The development 

of hand-mouth coordination in 2-to 5­

month-old infants: Similarities with reaching 

and grasping. Infant Behav Dev 20: 59-69. 

Nicas, M; Best, D. (2008). A study quantifying the 

hand-to-face contact rate and its potential 

application to predicting respiratory tract 

infection. Journal of Occupational and 

Environmental Hygiene (Online) 5: 347­

352. 

http://dx.doi.org/10.1080/154596208020038 

96. 

Norris, B; Smith, S. (2002). Research into the 

mouthing behaviour of children up to 5 

years old. London, England: Consumer and 

Competition Policy Directorate, Department 

of Trade and Industry. 

Reed, KJ; Jimenez, M; Freeman, NC; Lioy, PJ. 

(1999). Quantification of children's hand 

and mouthing activities through a 

videotaping methodology. J Expo Anal 

Environ Epidemiol 9: 513-520. 

Rochat, P; Blass, EM; Hoffmeyer, LB. (1988). 

Oropharyngeal control of hand^mouth 

coordination in newborn infants. Dev 

Psychol 24: 459-463. 

http://dx.doi.org/10.1037//0012­

1649.24.4.459. 

Shalat, SL; Donnelly, KC; Freeman, NCG; Calvin, 

JA; Ramesh, S; Jimenez, M; Black, K; 

Coutinho, C; Needham, LL; Barr, DB; 

Ramirez, J. (2003). Nondietary ingestion of 

pesticides by children in an agricultural 

community on the US/Mexico border: 

preliminary results. J Expo Sci Environ 

Epidemiol 13: 42-50. 

http://dx.doi.org/10.1038/sj.jea.7500249. 

Exposure Factors Handbook Page
 

September 2011 4-19 
 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Page Exposure Factors Handbook 

4-20 September 2011 

Smith, SA; Norris, B. (2003). Reducing the risk of 

choking hazards: mouthing behaviour of 

children aged 1 month to 5 years. Inj Contr 

Saf Promot 10: 145-154. 

http://dx.doi.org/10.1076/icsp.10.3.145.1456 

2. 

Stanek, EJ, III; Calabrese, EJ; Mundt, K; Pekow, P; 

Yeatts, KB. (1998). Prevalence of soil 

mouthing/ingestion among healthy children 

aged 1 to 6. Journal of Soil Contamination 

7: 227-242. 

Takaya, R; Yukuo, K; Bos, AF; Einspieler, C. (2003). 

Preterm to early postterm changes in the 

development of hand-mouth contact and 

other motor patterns. Early Hum Dev 75 

Suppl: S193-S202. 

Tudella, E; Oishi, J; Puglia Bergamasco, NH. (2000). 

The effect of oral-gustatory, tactile-bucal, 

and tactile-manual stimulation on the 

behavior of the hands in newborns. Dev 

Psychobiol 37: 82-89. 

http://dx.doi.org/10.1002/1098­

2302(200009)37:2<82::AIDDEV3>3.0.CO;2-B. 

Tulve, NS; Suggs, JC; Mccurdy, T; Cohen Hubal, 

EA; Moya, J. (2002). Frequency of 

mouthing behavior in young children. J 

Expo Anal Environ Epidemiol 12: 259-264. 

http://dx.doi.org/10.1038/sj.jea.7500225. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009). Draft technical guidelines: Standard 

operating procedures for residential 

pesticide exposure assessment: Submitted to 

the FIFRA Scientific Advisory Panel for 

review and comment, October 6-9, 2009. 

http://www.biospotvictims.org/EPA-HQOPP-2009-0516-0002.pdf. 

Warren, JJ; Levy, SM; Nowak, AJ; Tang, S. (2000). 

Non-nutritive sucking behaviors in 

preschool children: a longitudinal study. 

Pediatr Dent 22: 187-191. 

Xue, J; Zartarian, V; Moya, J; Freeman, N; Beamer, 

P; Black, K; Tulve, N; Shalat, S. (2007). A 

meta-analysis of children's hand-to-mouth 

frequency data for estimating nondietary 

ingestion exposure. Risk Anal 27: 411-420. 

http://dx.doi.org/10.1111/j.1539­

6924.2007.00893.x. 

Xue, J; Zartarian, V; Tulve, N; Moya, J; Freeman, N; 

Auyeung, W; Beamer, P. (2010). A metaanalysis of children's object-to-mouth 

frequency data for estimating non-dietary 

ingestion exposure. J Expo Sci Environ 

Epidemiol 20: 536-545. 

http://dx.doi.org/10.1038/jes.2009.42. 

Zartarian, VG; Ferguson, AC; Leckie, JO. (1997a). 

Quantified dermal activity data from a fourchild pilot field study. J Expo Anal Environ 

Epidemiol 7: 543-552. 

Zartarian, VG; Ferguson, AC; Leckie, JO. (1998). 

Quantified mouthing activity data from a 

four-child pilot field study. J Expo Anal 

Environ Epidemiol 8: 543–553. 

Zartarian, VG; Ferguson, AC; Ong, CG; Leckie, JO. 

(1997b). Quantifying videotaped activity 

patterns: video translation software and 

training methodologies. J Expo Anal 

Environ Epidemiol 7: 535-542. 

Zartarian, VG; Streicker, J; Rivera, A; Cornejo, CS; 

Molina, S; Valadez, OF; Leckie, JO. (1995). 

A pilot study to collect micro-activity data 

of two- to four-year-old farm labor children 

in Salinas Valley, California. J Expo Anal 

Environ Epidemiol 5: 21-34. 
Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-3. New Jersey Children’s Mouthing Frequency (contacts/hour) From Video-Transcription 

Category Minimum Mean Median 90th Percentile Maximum 

Hand to mouth 0.4 9.5 8.5 20.1 25.7 

Object to mouth 0 16.3 3.6 77.1 86.2 

Source: Reed et al. (1999). 

Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age 

Age Group (years) Thumbs/Fingers in Mouth Toes in Mouth Non-Food Items in Mouth 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

71 

63 

33 

30 

28 

33 

43 

38 

33 

33 

29 

0 

-

-

-

-

-

-

-

-

71 

31 

20 

29 

28 

40 

38 

38 

48 

17 

- = No data. 

Source: Freeman et al. (2001). 

Table 4-5. Video-Transcription Median (Mean) Observed Mouthing in 19 Minnesota Children 

(contacts/hour), by Age 

Age Group (years) N Object-to-Moutha Hand-to-Mouth 

3 to 4 

5 to 6 

7 to 8 

10 to 12 

3 

7 

4 

5 

3 (6) 

0 (1) 

0 (1) 

0 (1) 

3.5 (4) 

2.5 (8) 

3 (5) 

2 (4) a Kruskal Wallis test comparison across four age groups, p = 0.002. 

N = Number of observations. 

Source: Freeman et al. (2001). 

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c 

Table 4-6. Variability in Objects Mouthed by Washington State Children (contacts/hour) 

All Subjects ≤24 Months >24 Months 

Variable 

Na Meanb Median 95% CIc Na Meanb Median 95% CIc Na Meanb Median 95% CIc 

Mouth to body 186 8 2 2−3 69 10 4 3−6 117 7 1 0.8−1.3 

Mouth to hand 186 16 11 9−14 69 18 12 9−16 117 16 9 7−12 

Mouth to 186 4 1 0.8−1.2 69 7 5 3−8 117 2 1 0.9−1.1 

surface 

Mouth to toy 186 27 18 14−23 69 45 39 31−48 117 17 9 7−12 

Total events 186 56 44 36−52 69 81 73 60−88 117 42 31 25−39 

a Number of observations. b Arithmetic mean. 

The 95% confidence intervals (CI) apply to median. Values were calculated in logs and converted to original units. 

Source: Tulve et al. (2002). 

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Chapter 4—Non-Dietary Ingestion Factors 

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Chapter 4—Non-Dietary Ingestion Factors 

Table 4-7. Indoor Mouthing Frequency (contacts per contacts/hour), Video-Transcription of 9 Children, by 

Age 

Age Group N Statistic Hand Total Non-Dietarya 

13 to 84 months 9 Mean 

Median 

Range 

20.5 

14.8 

2.5−70.4 

29.6 

22.1 

3.2−82.2 

≤24 months 1 - 73.5 84.8 

>24 months 8 Mean 

Median 

Range 

13.9 

13.3 

2.2−34.1 

22.7 

19.5 

2.8−51.3 a Object/surface categories mouthed indoors included: clothes/towels, hands, metal, paper/wrapper, plastic, skin, toys, 

and wood. 

N = Number of subjects. 

Source: AuYeung et al. (2004). 

Table 4-8. Outdoor Mouthing Frequency (contacts per contacts/hour), Video-Transcription of 38 Children, by 

Age 

Age Group N Statistic Hand Total Non-Dietarya 

13 to 84 months 38 Mean 

5th percentile 

25th percentile 

50th percentile 

75th percentile 

95th percentile 

99th percentile 

11.7 

0.4 

4.4 

8.4 

14.8 

31.5 

47.6 

18.3 

0.8 

9.2 

14.5 

22.4 

51.7 

56.6 

≤24 months 8 Mean 

Median 

Range 

13.0 

7.0 

1.3−47.7 

20.4 

13.9 

6.2−56.4 

>24 months 30 Mean 

5th percentile 

25th percentile 

50th percentile 

75th percentile 

95th percentile 

99th percentile 

11.3 

0.2 

4.7 

8.6 

14.8 

27.7 

39.5 

17.7 

0.6 

7.6 

14.6 

22.4 

43.8 

53.0 a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric, hands, metal, non-dietary water, 

paper/wrapper, plastic, skin, toys, vegetation/grass, and wood. 

N = Number of subjects. 

Source: AuYeung et al. (2004). 

Exposure Factors Handbook Page
 

September 2011 4-23 
 

Table 4-9. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD), by Age 

Hand-to-Mouth Object-to-Mouth 

Age N (contact/hour) (contact/hour) 

Median (Mean ± SD) Frequency Median (Mean ± SD) Frequency 

7 to 12 months 13 14 (19.8 ± 14.5) 18.1 (24.4 ± 11.6) 

13 to 24 months 12 13.3 (15.8 ± 8.7) 8.4 (9.8 ± 6.3) 

25 to 36 months 18 9.9 (11.9 ± 9.3) 5.5 (7.8 ± 5.8) 

37 to 53 months 9 19.4 (22.1 ± 22.1) 8.4 (10.1 ± 12.4) 

N = Number of subjects. 

SD = Standard deviation. 

Source: Black et al. (2005). 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-10. Indoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various Studies, 

by Age 

Age Group Weibull 

Scale Parameter 

Weibull 

Shape 

Parameter 

Chi-Square N Mean SD 

Percentile 

5 25 50 75 95 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

1.28 

1.02 

0.91 

0.76 

0.75 

1.36 

30.19 

19.01 

18.79 

11.04 

12.59 

7.34 

fail 

pass 

fail 

fail 

pass 

pass 

23 

119 

245 

161 

169 

14 

28.0 

18.9 

19.6 

12.7 

14.7 

6.7 

21.7 

17.4 

19.6 

14.2 

18.4 

5.5 

3.0 

1.0 

0.1 

0.1 

0.1 

1.7 

8.0 

6.6 

6.0 

2.9 

3.7 

2.4 

23.0 

14.0 

14.0 

9.0 

9.0 

5.7 

48.0 

26.4 

27.0 

17.0 

20.0 

10.2 

65.0 

52.0 

63.0 

37.0 

54.0 

20.6 

N = Number of subjects. 

SD = Standard deviation. 

Source: Xue et al. (2007). 

Table 4-11. Outdoor Hand-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various Studies, 

by Age 

Age Group Weibull Scale 

Parameter 

Weibull Shape 

Parameter Chi-Square N Mean SD Percentile 

5 25 50 75 95 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

1.39 

0.98 

0.56 

0.55 

0.49 

15.98 

13.76 

3.41 

5.53 

1.47 

pass 

pass 

fail 

fail 

fail 

10 

32 

46 

55 

15 

14.5 

13.9 

5.3 

8.5 

2.9 

12.3 

13.6 

8.1 

10.7 

4.3 

2.4 

1.1 

0.1 

0.1 

0.1 

7.6 

4.2 

0.1 

0.1 

0.1 

11.6 

8.0 

2.6 

5.6 

0.5 

16.0 

19.2 

7.0 

11.0 

4.7 

46.7 

42.2 

20.0 

36.0 

11.9 

N = Number of subjects. 

SD = Standard deviation. 

Source: Xue et al. (2007). 

Page Exposure Factors Handbook 

4-24 September 2011 
Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-12. Object/Surface-to-Mouth Contact Frequency for Infants and Toddlers (events/hour) (N = 23) 

Percentiles
 

Object/Surface Range Mean 5th 50th 95th 25th 75th 99th 

Animal - - - - - - - ­

Body 0.0−5.0 1.5 0.0 0.4 0.8 2.4 4.0 4.8 

Clothes/towel 0.3−13.6 5.4 1.1 2.6 3.6 6.9 13.2 13.5 

Fabric 0.0−5.7 1.1 0.0 0.0 0.3 2.2 3.3 5.2 

Floor 0.0−1.3 0.2 0.0 0.0 0.0 0.4 1.0 1.2 

Food 2.3−68.3 28.9 11.1 17.8 28.2 34.8 53.7 65.2 

Footwear 0.0−8.9 0.7 0.0 0.0 0.0 0.0 5.7 8.3 

Hand/mouth 2.0−62.1 18.4 6.6 10.0 15.2 22.8 44.7 58.6 

Metal 0.0−2.1 0.3 0.0 0.0 0.0 0.1 1.3 1.9 

Non-dietary - - - - - - - ­

water 

Paper/wrapper 0.0−13.6 2.1 0.0 0.3 0.8 2.1 7.2 12.2 

Plastic 0.0−14.3 2.0 0.0 0.4 1.4 2.3 5.1 12.3 

Rock/brick - - - - - - - ­

Toy 0.3−48.4 14.7 1.9 6.8 12.5 20.6 34.9 45.6 

Vegetation 0.0−18.2 0.8 0.0 0.0 0.0 0.0 0.0 14.2 

Wood 0.0−3.9 0.5 0.0 0.0 0.0 0.5 1.8 3.4 

Non-dietary 6.2−82.3 29.2 8.1 15.9 27.2 38.0 64.0 78.8 

objecta 

All 24.4−145.9 76.5 28.7 58.7 77.4 94.5 123.1 141.2 

objects/surfaces 

a All object designations except for food and hand/mouth represent non-dietary objects. 

- No mouth contact with these objects/surfaces occurred. 

Source: Beamer et al. (2008). 

Exposure Factors Handbook Page
 

September 2011 4-25 
 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Page Exposure Factors Handbook 4-26 September 2011 

Table 4-13. Distributions Mouthing Frequency and Duration for Non-Dietary Objects With Significant Differences (p < 0.05) 

Between Infants and Toddlers 

Object/Surface Infant (6 to 13 months) Mouthing Frequency (contacts/hour) Infant (6 to 13 months) Mouthing Duration (minutes/hour) 

N Range Mean 5th 25th 50th 75th 95th 99th Range Mean 5th 25th 50th 75th 95th 99th 

Clothes/towel 

Paper/wrapper 

Toy 

Non-dietary 

object/surface 

13 

13 

13 

13 

2−13.3 

0.0−7.2 

6.5−48.4 

14−82.3 

6.8 

1.1 

21.1 

37.8 

2.7 

0.0 

7.3 

20.0 

4.8 

0.2 

14.4 

28.3 

6.3 

0.7 

20.2 

35.2 

7.2 

0.8 

25.5 

38.6 

12.7 

4.3 

40.8 

72.8 

12.1 

6.6 

46.9 

64.0 

-

0.0−0.7 

0.7−17.9 

1.1−18.4 

-

0.1 

3.6 

4.5 

-

0.0 

0.8 

1.2 

-

0.0 

1.2 

2.2 

-

0.0 

1.7 

2.8 

-

0.1 

2.8 

4.1 

-

0.4 

11.6 

12.6 

-

0.6 

16.6 

17.2 

Toddler (20−26 months) Mouthing Frequency (contacts/hour) Toddler (20−26 months) Mouthing Duration (minutes/hour) 

N Range Mean 5th 25th 50th 75th 95th 99th Range Mean 5th 25th 50th 75th 95th 99th 

Clothes/towel 

Paper/wrapper 

Toy 

Other non-dietary 

object/surfacea 

10 

10 

10 

10 

0.3−13.6 

0.3−12.6 

0.3−13.6 

6.2−41.2 

3.5 

6.3 

3.5 

18.0 

0.6 

1.0 

0.6 

7.0 

2.0 

2.8 

2.0 

9.4 

2.6 

5.4 

2.6 

15.9 

3.6 

9.6 

3.6 

22.0 

9.1 

12.5 

9.1 

35.2 

12.7 

12.6 

12.7 

40.5 

-

0.0−0.8 

0.0−6.8 

0.3−6.9 

-

0.2 

1.5 

2.1 

-

0.0 

0.1 

0.4 

-

0.0 

0.2 

0.7 

-

0.1 

0.5 

1.3 

-

0.2 

0.7 

1.8 

-

0.6 

6.1 

6.3 

-

0.7 

6.6 

6.7 

a Excludes “clothes/towel,” “paper/wrapper,” and “toys;” includes all other non-dietary objects/surfaces shown in Table 4-12. 

- No significant difference between infants and toddlers for this object/surface category. 

Source: Beamer et al. (2008) supplemental data. 
 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-14. Indoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various Studies, 

by Age 

Age Group Weibull 

Scale Parameter 

Weibull 

Shape 

Parameter 

Chi-Square N Mean SD 

5th 25th 

Percentile 

50th 75th 95th 

3 to <6 months 9.83 0.74 pass 19 11.2 10.0 0.1 1.7 9.3 17.3 31.8 

6 to <12 months 22.72 1.66 pass 82 20.3 12.5 3.3 11.3 19.0 28.0 37.9 

1 to <2 years 15.54 1.39 pass 137 14.2 10.2 2.0 6.5 12.3 19.0 34.0 

2 to <3 years 10.75 1.36 pass 95 9.9 7.0 1.7 4.2 8.7 14.5 24.4 

3 to <6 years 6.90 0.58 pass 167 10.1 14.8 0.1 1.0 5.0 13.0 39.0 

6 to <11 years 1.04 0.85 pass 14 1.1 1.1 0.1 0.1 0.9 1.985 3.2 

N = Number of subjects. 

SD = Standard deviation. 

Source: Xue et al. (2010). 

Table 4-15. Outdoor Object-to-Mouth Frequency (contacts/hour) Weibull Distributions From Various 

Studies, by Age 

Age Group 

(years) 

Weibull Scale 

Parameter 

Weibull Shape 

Parameter Chi-Square N Mean SD Percentile 

5th 25th 50th 75th 95th 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

8.58 

6.15 

5.38 

1.10 

0.93 

0.64 

0.55 

0.55 

pass 

pass 

pass 

fail 

21 

29 

53 

29 

8.8 

8.1 

8.3 

1.9 

8.8 

10.5 

12.4 

2.8 

0.1 

0.1 

0.1 

0.1 

3.8 

1.5 

0.1 

0.1 

6.0 

4.6 

5.0 

0.8 

10.8 

11.0 

10.6 

2.0 

21.3 

40.0 

30.3 

9.1 

N = Number of subjects. 

SD = Standard deviation. 

Source: Xue et al. (2010). 

Exposure Factors Handbook Page
 

September 2011 4-27 
 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-16. Survey-Reported Mouthing Behaviors for 92 Washington State Children 

Behavior Never Seldom Occasionally Frequently Always Unknown 

N % N % N % N % N % N % 

Hand/foot in mouth 4 4 27 30 23 25 31 34 4 4 3 3 

Pacifier 74 81 6 7 2 2 9 10 1 1 0 0 

Mouth on object 14 15 30 33 25 27 19 21 1 1 3 3 

Non-food in mouth 5 5 25 27 33 36 24 26 5 5 0 0 

Eat dirt/sand 37 40 39 43 11 12 4 4 1 1 0 0 

N = Number of subjects. 

Source: Davis et al. (1995). 

Table 4-17. Number of Hand Contacts Observed in Adults During a Continuous 

3-Hour Period 

Subject Eye Lip Nostril Total 

1 0 0 3 3 

2 4 2 1 7 

3 2 12 4 18 

4 1 1 20 22 

5 10 22 15 47 

6 13 33 8 54 

7 17 15 27 59 

8 6 31 28 65 

9 9 52 30 91 

10 12 72 20 104 

Mean 7.4 24 16 47 

Standard 

Deviation 5.7 24 11 35 

Source: Nicas and Best (2008). 

Page Exposure Factors Handbook 

4-28 September 2011 
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-18. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and Other 

Objects 

Age 0 to 18 Months Age 19 to 36 Months 

Object Type All Children Only Children Who 

Mouthed Objecta All Children Only Children Who Mouthed Objecta 

Minutes/Day Minutes/Day Minutes/Day Minutes/Day 

Pacifier 

Teether 

Plastic toy 

Other objects 

108 (N = 107) 

6 (N = 107) 

17 (N = 107) 

9 (N = 107) 

221 (N = 52) 

20 (N = 34) 

28 (N = 66) 

22 (N = 46) 

126 (N = 110) 

0 (N = 110) 

2 (N = 110) 

2 (N = 110) 

462 (N = 52) 

30 (N = 1) 

11 (N = 21) 

15 (N = 18) a Refers to means calculated for the subset of the sample children who mouthed the object stated (zeroes are eliminated 

from the calculation of the mean). 

N = Number of children. 

Source: Juberg et al. (2001). 

Table 4-19. Percent of Houston-Area and Chicago-Area Children Observed Mouthing, by Category and 

Child’s Age 

Object Category All Ages <1 Year 1 to 2 Years 2 to 3 Years 

All objects 

Pacifier 

Non-pacifier 

Soft plastic food content item 

Anatomy 

Non-soft plastic toy, teether, and rattle 

Other items 

100 

27 

100 

28 

99 

91 

98 

100 

43 

100 

13 

100 

94 

98 

100 

27 

100 

30 

97 

91 

97 

100 

10 

100 

41 

100 

86 

98 

Source: Greene (2002). 

Exposure Factors Handbook Page
 

September 2011 4-29 
 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-20. Estimates of Mouthing Time for Various Objects for Infants and Toddlers (minutes/hour), by Age 

Age Group Mean (SD) Median 95th Percentile 99th Percentile 

All Itemsa 

3 to <12 months 

12 to <24 months 

24 to <36 months 

10.5 (7.3) 

7.3 (6.8) 

5.3 (8.2) 

9.6 

5.5 

2.4 

26.2 

22.0 

15.6 

39.8 

28.8 

47.8 

Non-Pacifierb 

3 to <12 months 

12 to <24 months 

24 to <36 months 

7.1 (3.6) 

4.7 (3.7) 

3.5 (3.6) 

6.9 

3.6 

2.3 

13.1 

12.8 

12.8 

14.4 

18.9 

15.6 

All Soft Plastic Itemc 

3 to <12 months 

12 to <24 months 

24 to <36 months 

0.5 (0.6) 

0.4 (0.4) 

0.4 (0.6) 

0.1 

0.2 

0.1 

1.8 

1.3 

1.6 

2.5 

1.9 

2.9 

Soft Plastic Item Not Food Contact 

3 to <12 months 

12 to <24 months 

24 to <36 months 

0.4 (0.6) 

0.3 (0.4) 

0.2 (0.4) 

0.1 

0.1 

0.0 

1.8 

1.1 

1.3 

2.0 

1.5 

1.8 

Soft Plastic Toy, Teether, and Rattle 

3 to <12 months 

12 to <24 months 

24 to <36 months 

0.3 (0.5) 

0.2 (0.3) 

0.1 (0.2) 

0.1 

0.0 

0.0 

1.8 

0.9 

0.2 

2.0 

1.3 

1.6 

Soft Plastic Toy 

3 to <12 months 

12 to <24 months 

24 to <36 months 

0.1 (0.3) 

0.2 (0.3) 

0.1 (0.2) 

0.0 

0.0 

0.0 

0.7 

0.9 

0.2 

1.1 

1.3 

1.6 

Soft Plastic Teether and Rattle 

3 to <12 months 

12 to <24 months 

24 to <36 months 

0.2 (0.4) 

0.0 (0.1) 

0.0 (0.1) 

0.0 

0.0 

0.0 

1.0 

0.1 

0.0 

2.0 

0.6 

1.0 

Other Soft Plastic Item 

3 to <12 months 

12 to <24 months 

24 to <36 months 

0.1 (0.2) 

0.1 (0.1) 

0.1 (0.3) 

0.0 

0.0 

0.0 

0.8 

0.4 

0.5 

1.0 

0.6 

1.4 

Soft Plastic Food Contact Item 

3 to <12 months 

12 to <24 months 

24 to <36 months 

0.0 (0.2) 

0.1 (0.2) 

0.2 (0.4) 

0.0 

0.0 

0.0 

0.3 

0.7 

1.2 

0.9 

1.2 

1.9 

Anatomy 

3 to <12 months 

12 to <24 months 

24 to <36 months 

2.4 (2.8) 

1.7 (2.7) 

1.2 (2.3) 

1.5 

0.8 

0.4 

10.1 

8.3 

5.1 

12.2 

14.8 

13.6 

Page Exposure Factors Handbook 

4-30 September 2011 
 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-20. Estimates of Mouthing Time for Various Objects for Infants and Toddlers (minutes/hour), by Age 

(continued) 

Age Group Mean (SD) Median 95th Percentile 99th Percentile 

Non-Soft Plastic Toy, Teether, and Rattle 

3 to <12 months 

12 to <24 months 

24 to <36 months 

1.8 (1.8) 

0.6 (0.8) 

0.2 (0.4) 

1.3 

0.3 

0.1 

6.5 

1.8 

0.9 

7.7 

4.6 

2.3 

Other Item 

3 to <12 months 

12 to <24 months 

24 to <36 months 

2.5 (2.1) 

2.1 (2.0) 

1.7 (2.6) 

2.1 

1.4 

0.7 

7.8 

6.6 

7.1 

8.1 

9.0 

14.3 

Pacifier 

3 to <12 months 

12 to <24 months 

24 to <36 months 

3.4 (6.9) 

2.6 (6.5) 

1.8 (7.9) 

0.0 

0.0 

0.0 

19.5 

19.9 

4.8 

37.3 

28.6 

46.3 a Object category “all items” is subdivided into pacifiers and non-pacifiers. b Object category “non-pacifiers” is subdivided into all soft plastic items, anatomy ( which includes hair, skin, fingers 

and hands), non-soft plastic toys/teethers/rattles, and other items. c Object category “all soft plastic items” is subdivided into food contact items, non-food contact items (toys, teethers, 

and rattles) and other soft plastic. 

SD = Standard deviation. 

Source: Greene (2002). 

Exposure Factors Handbook Page
 

September 2011 4-31 
 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-21. Object/Surface-to-Hands and Mouth Contact Duration for Infants and Toddlers (minutes/hour) 

(N = 23) 

Percentiles Object/Surface Range Mean 5th 25th 50th 75th 95th 99th 

Animal - - - - - - - ­

Body 0.0−0.3 0.1 0.0 0.0 0.0 0.1 0.3 0.3 

Clothe/towel 0.0−0.9 0.3 0.0 0.1 0.2 0.4 0.7 0.9 

Fabric 0.0−0.2 0.0 0.0 0.0 0.0 0.1 0.2 0.2 

Floor 0.0−0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.1 

Food 0.3−15.0 4.7 0.4 1.8 3.8 6.6 10.9 14.1 

Footwear 0.0−1.4 0.1 0.0 0.0 0.0 0.0 0.3 1.1 

Hand/mouth 0.2−5.4 1.4 0.4 0.5 1.2 1.8 3.7 5.0 

Metal 0.0−0.2 0.0 0.0 0.0 0.0 0.0 0.1 0.2 

Non-dietary water - - - - - - - ­

Paper/wrapper 0.0−0.8 0.1 0.0 0.0 0.0 0.1 0.7 0.8 

Plastic 0.0−0.6 0.1 0.0 0.0 0.1 0.1 0.5 0.6 

Rock/brick - - - - - - - ­

Toys 0.0−17.9 2.7 0.1 0.6 1.2 2.8 7.4 15.6 

Vegetation 0.0−0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 

Wood 0.0−0.3 0.0 0.0 0.0 0.0 0.0 0.2 0.3 

Non-dietary objecta 0.3−18.4 3.5 0.5 1.2 2.2 3.9 8.5 16.3 

All objects/surfaces 2.2−33.6 9.6 2.4 5.1 8.8 12.0 17.1 30.0 a All object designations except for food and hand/mouth represent non-dietary objects. 

- No mouth contact with these objects/surfaces occurred. 

Source: Beamer et al. (2008). 

Page Exposure Factors Handbook 

4-32 September 2011 
 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-22. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without Pacifier 

(minutes/day), by Age 

Age Group N Mean SD Minimum Maximum 

3 to 6 months 

6 to 12 months 

12 to 18 months 

18 to 36 months 

5 

14 

12 

11 

36.9 

44 

16.4 

9.3 

19.1 

44.7 

18.2 

9.8 

14.5 

2.4 

0 

0 

67 

171.5 

53.2 

30.9 

Note: The object most mouthed in all age groups was the fingers, except for the 6 to 12 month group, which mostly mouthed 

toys. 

N = Number of children. 

SD = Standard deviation. 

Source: Groot et al. (1998). 

Exposure Factors Handbook Page
 

September 2011 4-33 
 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Page Exposure Factors Handbook 4-34 September 2011 

Table 4-23. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys, and Other Objects 

(hours:minutes:seconds) 

Item 

Mouthed 

Age Group 

1 to 3 

months 

3 to 6 

months 

6 to 9 

months 

9 to 12 

months 

12 to 15 

months 

15 to 18 

months 

18 to 21 

Months 

21 to 24 

months 

2 

years 

3 

years 

4 

years 

5 

years 

N = 9 14 15 17 16 14 16 12 39 31 29 24 

Dummy (pacifier) 0:47:13 0:27:45 0:14:36 0:41:39 1:00:15 0:25:22 1:09:02 0:25:12 0:32:55 0:48:42 0:16:40 0:00:20 

Finger 0:18:22 0:49:03 0:16:54 0:14:07 0:08:24 0:10:07 0:18:40 0:35:34 0:29:43 0:34:42 0:19:26 0:44:06 

Toy 0:00:14 0:28:20 0:39:10 0:23:04 0:15:18 0:16:34 0:11:07 0:15:46 0:12:23 0:11:37 0:03:11 0:01:53 

Other object 0:05:14 0:12:29 0:24:30 0:16:25 0:12:02 0:23:01 0:19:49 0:12:53 0:21:46 0:15:16 0:10:44 0:10:00 

Not recorded 0:00:45 0:00:24 0:00:00 0:00:01 0:00:02 0:00:08 0:00:11 0:14:13 0:02:40 0:00:01 0:00:05 0:02:58 

Total (all objects) 1:11:48 1:57:41 1:35:11 1:35:16 1:36:01 0:15:13 1:58:49 1:43:39 1:39:27 1:50:19 0:50:05 0:59:17 

N = Number of children in sample. 

Source: Smith and Norris (2003). 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-24. Outdoor Median Mouthing Duration (seconds/contact), Video-Transcription of 38 Children, 

by Age 

Age Group N Statistic Hand Total Non-Dietarya 

13 to 84 months 38 

Mean 

5th percentile 

25th percentile 

50th percentile 

75th percentile 

95th percentile 

99th percentile 

3.5 

0 

1 

1 

2 

12 

41.6 

3.4 

0 

1 

1 

3 

11 

40 

≤24 months 8 

Mean 

Median 

Range 

9 

3 

0 to 136 

7 

2 

0 to 136 

>24 months 30 

Mean 

5th percentile 

25th percentile 

50th percentile 

75th percentile 

95th percentile 

99th percentile 

2 

0 

1 

1 

2 

5 

17.4 

2.4 

0 

1 

1 

2 

7 

24.6 a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric, hands, metal, non-dietary water, 

paper/wrapper, plastic, skin, toys, vegetation/grass, and wood. 

N = Number of subjects. 

Source: AuYeung et al. (2004). 

Table 4-25. Indoor Mouthing Duration (minutes/hour), Video-Transcription of Nine Children With 

>15 Minutes in View Indoors 

Age Group N Statistic Hand Total Non-Dietarya 

13 to 84 months 9 

Mean 

Median 

Range 

1.8 

0.7 

0−10.7 

2.3 

0.9 

0−11.1 

≤24 months 1 Observation 10.7 11.1 

>24 months 8 

Mean 

Median 

Range 

0.7 

0.7 

0−1.9 

1.2 

0.9 

0−3.7 a Object/surface categories mouthed indoors included: clothes/towels, hands, metal, paper/wrapper, plastic, skin, toys, 

and wood. 

N = Number of subjects. 

Source: AuYeung et al. (2004). 

Exposure Factors Handbook Page
 

September 2011 4-35 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Table 4-26. Outdoor Mouthing Duration (minutes/hour), Video-Transcription of 38 Children, by Age 

Age Group N Statistic Hand Total Non-Dietarya 

13 to 84 months 38 

Mean 

5th percentile 

25th percentile 

50th percentile 

75th percentile 

95th percentile 

99th percentile 

Range 

0.9 

0 

0.1 

0.2 

0.6 

2.6 

11.2 

0−15.5 

1.2 

0 

0.2 

0.6 

1.2 

2.9 

11.5 

0−15.8 

≤24 months 8 

Mean 

5th percentile 

25th percentile 

50th percentile 

75th percentile 

95th percentile 

99th percentile 

Range 

2.7 

0 

0.2 

0.4 

1.5 

11.5 

14.7 

0−15.5 

3.1 

0.2 

0.2 

0.8 

3.1 

11.7 

15 

0.2−15.8 

>24 months 30 

Mean 

5th percentile 

25th percentile 

Median 

75th percentile 

95th percentile 

99th percentile 

Range 

0.4 

0 

0.1 

0.2 

0.4 

1.2 

2.2 

0−2.4 

0.7 

0 

0.2 

0.6 

1 

2.1 

2.5 

0−2.6 a Object/surface categories mouthed outdoors included: animal, clothes/towels, fabric, hands, metal, non-dietary water, 

paper/wrapper, plastic, skin, toys, vegetation/grass, and wood. 

N = Number of subjects. 

Source: AuYeung et al. (2004). 

Page Exposure Factors Handbook 

4-36 September 2011 
Table 4-27. Reported Daily Prevalence of Massachusetts Children’s Non-Food Mouthing/Ingestion 

Behaviors
 

Percent of Children Reported to Mouth/Ingest Daily Object or Substance Mouthed 1 Year 2 Years 3 to <6 Years

a 6 Years All Years or Ingested N = 171 N = 70 N = 265 N = 22 N = 528 

Grass, leaf, flower 16 0 1 0 6
 

Twig, stick, woodchip 12 0 0 0 4
 

Teething toy 44 6 2 9 17
 

Other toy 63 27 12 5 30
 

Blanket, cloth 29 11 10 5 16
 

Shoes, Footwear 20 1 0 0 7
 

Clothing 25 7 9 14 14
 

Crib, chair, furniture 13 3 1 0 5
 

Paper, cardboard, tissue 28 9 5 5 13
 

Crayon, pencil, eraser 19 17 5 18 12
 

Toothpaste 52 87 89 82 77
 

Soap, detergent, shampoo 15 14 2 0 8
 

Plastic, plastic wrap 7 4 1 0 3
 

Cigarette butt, tobacco 4 0 1 0 2
 

Suck finger/thumb 44 21 24 14 30
 

Suck feet or toe 8 1 0 0 3
 

Bite nail 2 7 10 14 7
 

Use pacifier 20 6 2 0 9
 a	 Weighted mean of 3-, 4-, and 5-year-olds’ data calculated by U.S. EPA to conform to standardized age categories 

used in this handbook. 

Source:	 Stanek et al. (1998). 

Exposure Factors Handbook 

Chapter 4—Non-Dietary Ingestion Factors 

Exposure Factors Handbook Page
 

September 2011 4-37 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

5. SOIL AND DUST INGESTION 

5.1. INTRODUCTION 

The ingestion of soil and dust is a potential route 

of exposure for both adults and children to 

environmental chemicals. Children, in particular, may 

ingest significant quantities of soil due to their 

tendency to play on the floor indoors and on the 

ground outdoors and their tendency to mouth objects 

or their hands. Children may ingest soil and dust 

through deliberate hand-to-mouth movements, or 

unintentionally by eating food that has dropped on 

the floor. Adults may also ingest soil or dust particles 

that adhere to food, cigarettes, or their hands. Thus, 

understanding soil and dust ingestion patterns is an 

important part of estimating overall exposures to 

environmental chemicals. 

At this point in time, knowledge of soil and dust 

ingestion patterns within the United States is 

somewhat limited. Only a few researchers have 

attempted to quantify soil and dust ingestion patterns 

in U.S. adults or children. 

This chapter explains the concepts of soil 

ingestion, soil pica, and geophagy, defines these 

terms for the purpose of this handbook’s exposure 

factors, and presents available data from the literature 

on the amount of soil and dust ingested. 

The Centers for Disease Control and Prevention's 

Agency for Toxic Substances and Disease Registry 

(ATSDR) held a workshop in June 2000 in which a 

panel of soil ingestion experts developed definitions 

for soil ingestion, soil-pica, and geophagy, to 

distinguish aspects of soil ingestion patterns that are 

important from a research perspective (ATSDR, 

2001). This chapter uses the definitions that are based 

on those developed by participants in that workshop: 

Soil ingestion is the consumption of soil. This 

may result from various behaviors including, 

but not limited to, mouthing, contacting dirty 

hands, eating dropped food, or consuming soil 

directly. 

Soil-pica is the recurrent ingestion of unusually 

high amounts of soil (i.e., on the order of 

1,000−5,000 mg/day or more). 

Geophagy is the intentional ingestion of earths 

and is usually associated with cultural 

practices. 

Some studies are of a behavior known as “pica,” 

and the subset of “pica” that consists of ingesting 

soil. A general definition of the concept of pica is that 

of ingesting non-food substances, or ingesting large 

quantities of certain particular foods. Definitions of 

pica often include references to recurring or repeated 

ingestion of these substances. Soil-pica is specific to 

ingesting materials that are defined as soil, such as 

clays, yard soil, and flower-pot soil. Although soilpica is a fairly common behavior among children, 

information about the prevalence of pica behavior is 

limited. Gavrelis et al. (2011) reported that the 

prevalence of non-food substance consumption varies 

by age, race, and income level. The behavior was 

most prevalent among children 1 to <3 years 

(Gavrelis et al., 2011). Geophagy, on the other hand, 

is an extremely rare behavior, especially among 

children, as is soil-pica among adults. One distinction 

between geophagy and soil-pica that may have public 

health implications is the fact that surface soils 

generally are not the main source of geophagy 

materials. Instead, geophagy is typically the 

consumption of clay from known, uncontaminated 

sources, whereas soil-pica involves the consumption 

of surface soils, usually the top 2−3 inches (ATSDR, 

2001). 

Researchers in many different disciplines have 

hypothesized motivations for human soil-pica or 

geophagy behavior, including alleviating nutritional 

deficiencies, a desire to remove toxins or selfmedicate, and other physiological or cultural 

influences (Danford, 1982). Bruhn and Pangborn 

(1971) and Harris and Harper (1997) suggest a 

religious context for certain geophagy or soil 

ingestion practices. Geophagy is characterized as an 

intentional behavior, whereas soil-pica should not be 

limited to intentional soil ingestion, primarily 

because children can consume large amounts of soil 

from their typical behaviors and because 

differentiating intentional and unintentional behavior 

in young children is difficult (ATSDR, 2001). Some 

researchers have investigated populations that may be 

more likely than others to exhibit soil-pica or 

geophagy behavior on a recurring basis. These 

populations might include pregnant women who 

exhibit soil-pica behavior (Simpson et al., 2000), 

adults and children who practice geophagy (Vermeer 

and Frate, 1979), institutionalized children (Wong, 

1988), and children with developmental delays 

(Danford, 1983), autism (Kinnell, 1985), or celiac 

disease (Korman, 1990). However, identifying 

specific soil-pica and geophagy populations remains 

difficult due to limited research on this topic. It has 

been estimated that 33% of children ingest more than 

10 grams of soil 1 or 2 days a year (ATSDR, 2001). 

No information was located regarding the prevalence 

of geophagy behavior. 

Because some soil and dust ingestion may be a 

result of hand-to-mouth behavior, soil properties may 

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Chapter 5—Soil and Dust Ingestion 

be important. For example, soil particle size, organic 

matter content, moisture content, and other soil 

properties may affect the adherence of soil to the 

skin. Soil particle sizes range from 50−2,000 μm for 

sand, 2−50 μm for silt, and are <2 μm for clay 

(USDA, 1999), while typical atmospheric dust 

particle sizes are in the range of 0.001−30 μm (Mody 

and Jakhete, 1987). Studies on particle size have 

indicated that finer soil particles (generally <63 μm 

in diameter) tend to be adhered more efficiently to 

human hands, whereas adhered soil fractions are 

independent of organic matter content or soil origin 

(Choate et al., 2006; Yamamoto et al., 2006). More 

large particle soil fractions have been shown to 

adhere to the skin for soils with higher moisture 

content (Choate et al., 2006). 

In this handbook, soil, indoor settled dust and 

outdoor settled dust are defined generally as the 

following: 

Soil. Particles of unconsolidated mineral and/or 

organic matter from the earth’s surface that 

are located outdoors, or are used indoors to 

support plant growth. It includes particles that 

have settled onto outdoor objects and surfaces 

(outdoor settled dust). 

Indoor Settled Dust. Particles in building 

interiors that have settled onto objects, 

surfaces, floors, and carpeting. These particles 

may include soil particles that have been 

tracked or blown into the indoor environment 

from outdoors as well as organic matter. 

Outdoor Settled Dust. Particles that have settled 

onto outdoor objects and surfaces due to either 

wet or dry deposition. Note that it may not be 

possible to distinguish between soil and 

outdoor settled dust, since outdoor settled dust 

generally would be present on the uppermost 

surface layer of soil. 

For the purposes of this handbook, soil ingestion 

includes both soil and outdoor settled dust, and dust 

ingestion includes indoor settled dust only. 

There are several methodologies represented in 

the literature related to soil and dust ingestion. Two 

methodologies combine biomarker measurements 

with measurements of the biomarker substance’s 

presence in environmental media. An additional 

methodology offers modeled estimates of soil/dust 

ingestion from activity pattern data from 

observational studies (e.g., videography) or from the 

responses to survey questionnaires about children’s 

activities, behaviors, and locations. 

The first of the biomarker methodologies 

measures quantities of specific elements present in 

feces, urine, food and medications, yard soil, house 

dust, and sometimes also community soil and dust, 

and combines this information using certain 

assumptions about the elements’ behavior in the 

gastrointestinal tract to produce estimates of soil and 

dust quantities ingested (Davis et al., 1990). In this 

chapter, this methodology is referred to as the “tracer 

element” methodology. The second biomarker 

methodology compares results from a biokinetic 

model of lead exposure and uptake that predict blood 

lead levels, with biomarker measurements of lead in 

blood (Von Lindern et al., 2003). The model 

predictions are made using assumptions about 

ingested soil and dust quantities that are based, in 

part, on results from early versions of the first 

methodology. Therefore, the comparison with actual 

measured blood lead levels serves to confirm, to 

some extent, the assumptions about ingested soil and 

dust quantities used in the biokinetic model. In this 

chapter, this methodology is referred to as the 

“biokinetic model comparison” methodology. Lead 

isotope ratios have also been used as a biomarker to 

study sources of lead exposures in children. This 

technique involves measurements of different lead 

isotopes in blood and/or urine, food, water, and house 

dust and compares the ratio of different lead isotopes 

to infer sources of lead exposure that may include 

dust or other environmental exposures (Manton et al., 

2000). However, application of lead isotope ratios to 

derive estimates of dust ingestion by children has not 

been attempted. Therefore, it is not discussed any 

further in this chapter. 

The third, “activity pattern” methodology, 

combines information from hand-to-mouth and 

object-to-mouth behaviors with microenvironment 

data (i.e., time spent at different locations) to derive 

estimates of soil and dust ingestion. Behavioral 

information often comes from data obtained using 

videography techniques or from responses to survey 

questions obtained from adults, caregivers, and/or 

children. Surveys often include questions about handto-mouth and object-to-mouth behaviors, soil and 

dust ingestion behaviors, frequency, and sometimes 

quantity (Barltrop, 1966). 

Although not directly evaluated in this chapter, a 

fourth methodology uses assumptions regarding 

ingested quantities of soil and dust that are based on a 

general knowledge of human behavior, and 

potentially supplemented or informed by data from 

other methodologies (Wong et al., 2000; Kissel et al., 

1998; Hawley, 1985). 

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The recommendations for soil, dust, and soil + 

dust ingestion rates are provided in the next section, 

along with a summary of the confidence ratings for 

these recommendations. The recommended values 

are based on key studies identified by the U.S. 

Environmental Protection Agency (U.S. EPA) for this 

factor. Following the recommendations, a description 

of the three methodologies used to estimate soil and 

dust ingestion is provided, followed by a summary of 

key and relevant studies. Because strengths and 

limitations of each one of the key and relevant studies 

relate to the strengths and limitations inherent of the 

methodologies themselves, they are discussed at the 

end of the key and relevant studies. 

5.2. RECOMMENDATIONS 

The key studies described in Section 5.3 were 

used to recommend values for soil and dust ingestion 

for adults and children. Table 5-1 shows the central 

tendency recommendations for daily ingestion of soil, 

dust, or soil + dust, in mg/day. It also shows the high 

end recommendations for daily ingestion of soil, in 

mg/day. The high end recommendations are 

subdivided into a general population soil ingestion 

rate, an ingestion rate for “soil-pica,” and an estimate 

for individuals who exhibit “geophagy.” The soil pica 

and geophagy recommendations are likely to 

represent an acute high soil ingestion episode or 

behaviors at an unknown point on the high end of the 

distribution of soil ingestion. Published estimates 

from the key studies have been rounded to one 

significant figure. 

The soil ingestion recommendations in Table 5-1 

are intended to represent ingestion of a combination 

of soil and outdoor settled dust, without 

distinguishing between these two sources. The source 

of the soil in these recommendations could be 

outdoor soil, indoor containerized soil used to 

support growth of indoor plants, or a combination of 

both outdoor soil and containerized indoor soil. The 

inhalation and subsequent swallowing of soil 

particles is accounted for in these recommended 

values, therefore, this pathway does not need to be 

considered separately. These recommendations are 

called “soil.” The dust ingestion recommendations in 

Table 5-1 include soil tracked into the indoor setting, 

indoor settled dust, and air-suspended particulate 

matter that is inhaled and swallowed. Central 

tendency “dust” recommendations are provided, in 

the event that assessors need recommendations for an 

indoor or inside a transportation vehicle scenario in 

which dust, but not outdoor soil, is the exposure 

medium of concern. The soil + dust recommendations 

would include soil, either from outdoor or 

containerized indoor sources, dust that is a 

combination of outdoor settled dust, indoor settled 

dust, and air-suspended particulate matter that is 

inhaled, subsequently trapped in mucous and moved 

from the respiratory system to the gastrointestinal 

tract, and a soil-origin material located on indoor 

floor surfaces that was tracked indoors by building 

occupants. Soil and dust recommendations exclude 

the soil or dust’s moisture content. In other words, 

recommended values represent mass of ingested soil 

or dust that is represented on a dry-weight basis. 

Studies estimating adult soil ingestion are 

extremely limited, and only two of these are 

considered to be key studies [i.e., Vermeer and Frate 

(1979); Davis and Mirick (2006)]. In the Davis and 

Mirick (2006) study, soil ingestion for adults and 

children in the same family was calculated using a 

mass-balance approach. The adult data were seen to 

be more variable than for the children in the study, 

possibly indicating an important occupational 

contribution of soil ingestion in some of the adults. 

For the aluminum and silicon tracers, soil ingestion 

rates ranged from 23−92 mg/day (mean), 

0−23 mg/day (median), and 138−814 mg/day 

(maximum), with an overall mean value of 

52 mg/day for the adults in the study. Based on this 

value, the recommended mean value from the Davis 

and Mirick (2006) study is estimated to be 50 mg/day 

for adult soil and dust ingestion (see Table 5-1). 

There are no available studies estimating the 

ingestion of dust by adults, therefore, the assumption 

used by U.S. EPA’s Integrated Exposure and Uptake 

Biokinetic (IEUBK) model for lead in children (i.e., 

45% soil, 55% dust contribution) was used to derive 

estimates for soil and dust using the soil + dust value 

derived from Davis and Mirick (2006). Rounded to 

one significant figure, these estimates are 20 mg/day 

and 30 mg/day for soil and dust respectively. 

The key studies pre-dated the age groups 

recommended for children by U.S. EPA (2005) and 

were performed on groups of children of varying 

ages. As a result, central tendency recommendations 

can be used for the life stage categories of 6 to 

<12 months, 1 to <2 years, 2 to <3 years, 3 to 

<6 years, and part of the 6 to <11 years categories. 

Upper percentile recommendations can be used for 

the life stage categories of 1 to <2 years, 2 to 

<3 years, 3 to <6 years, 6 to <11 years, and part or all 

of the 11 to <16 years category. 

The recommended central tendency soil + dust 

ingestion estimate for infants from 6 weeks up to 

their first birthday is 60 mg/day (Hogan et al., 1998; 

van Wijnen et al., 1990). If an estimate is needed for 

soil only, from soil derived from outdoor or indoor 

sources, or both outdoor and indoor sources, the 

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Chapter 5—Soil and Dust Ingestion 

recommendation is 30 mg/day (van Wijnen et al., 

1990). If an estimate for indoor dust only is needed, 

that would include a certain quantity of tracked-in 

soil from outside, the recommendation is 30 mg/day 

(Hogan et al., 1998). This dust ingestion value is 

based on the 30 mg/day value for soil ingestion for 

this age group (van Wijnen et al., 1990), and the 

assumption that the soil and dust inhalation values 

will be comparable, as were the Hogan et al. (1998) 

values for the 1 to <6 year age group. The confidence 

rating for this recommendation is low due to the 

small numbers of study subjects in the IEUBK model 

study on which the recommendation is in part based 

and the inferences needed to develop a quantitative 

estimate. Examples of these inferences include: an 

assumption that the relative proportions of soil and 

dust ingested by 6 week to <12 month old children 

are the same as those ingested by older children 

[45% soil, 55% dust, based on U.S. EPA (1994a)], 

and the assumption that pre-natal or non-soil, nondust sources of lead exposure do not dominate these 

children’s blood lead levels. 

When assessing risks for individuals who are not 

expected to exhibit soil-pica or geophagy behavior, 

the recommended central tendency soil + dust 

ingestion estimate is 100 mg/day for children ages 1 

to <21 years (Hogan et al., 1998). If an estimate for 

soil only is needed, for exposure to soil such as 

manufactured topsoil or potted-plant soil that could 

occur in either an indoor or outdoor setting, or when 

the risk assessment is not considering children's 

ingestion of indoor dust (in an indoor setting) as well, 

the recommendation is 50 mg/day (Hogan et al., 

1998). If an estimate for indoor dust only is needed, 

the recommendation is 60 mg/day (Hogan et al., 

1998). Although these quantities add up to 

110 mg/day, the sum is rounded to one significant 

figure. Although there were no tracer element studies 

or biokinetic model comparison studies performed 

for children 6 to <21 years, as a group, their mean or 

central tendency soil ingestion would not be zero. In 

the absence of data that can be used to develop 

specific central tendency soil and dust ingestion 

recommendations for children aged 6 to <11 years, 11 

to <16 years and 16 to <21 years, U.S. EPA 

recommends using the same central tendency soil and 

dust ingestion rates that are recommended for 

children in the 1 to <6 year old age range. 

No key studies are available estimating soil-pica 

behavior in children less than 12 months of age or in 

adults, therefore, no recommended values are 

provided for these age groups. The upper percentile 

recommendation for soil and dust ingestion among 

the general population of children 3 to <6 years old is 

200 mg/day and it is based on the 95th percentile 

value obtained from modeling efforts from Özkaynak 

et al. (2011) and from 95th percentile estimates 

derived by Stanek and Calabrese (1995b). When 

assessing risks for children who may exhibit soil-pica 

behavior, or a group of children that includes 

individual children who may exhibit soil-pica 

behavior, the soil-pica ingestion estimate in the 

literature for children up to age 14 ranges from 400 to 

41,000 mg/day (Stanek et al., 1998; Calabrese et al., 

1997b; Calabrese et al., 1997a; Calabrese and Stanek, 

1993; Calabrese et al., 1991; Barnes, 1990; Calabrese 

et al., 1989; Wong, 1988; Vermeer and Frate, 1979). 

Due to the definition of soil-pica used in this chapter, 

that sets a lower bound on the quantity referred to as 

“soil-pica” at 1,000 mg/day (ATSDR, 2001), and due 

to the significant number of observations in the U.S. 

tracer element studies that are at or exceed that 

quantity, the recommended soil-pica ingestion rate is 

1,000 mg/day. It should be noted, however, that this 

value may be more appropriate for acute exposures. 

Currently, no data are available for soil-pica behavior 

for children ages 6 to <21 years. Because pica 

behavior may occur among some children ages ~1 to 

21 years old (Hyman et al., 1990), it is prudent to 

assume that, for some children, soil-pica behavior 

may occur at any age up to 21 years. 

The recommended geophagy soil estimate is 

50,000 mg/day (50 grams) for both adults and 

children (Vermeer and Frate, 1979). It is important to 

note that this value may be more representative of 

acute exposures. Risk assessors should use this value 

for soil ingestion in areas where residents are known 

to exhibit geophagy behaviors. 

Table 5-2 shows the confidence ratings for these 

recommendations. Section 5.4 gives a more detailed 

explanation of the basis for the confidence ratings. 

An important factor to consider when using these 

recommendations is that they are limited to estimates 

of soil and dust quantities ingested. The scope of this 

chapter is limited to quantities of soil and dust taken 

into the gastrointestinal tract, and does not extend to 

issues regarding bioavailability of environmental 

contaminants present in that soil and dust. 

Information from other sources is needed to address 

bioavailability. In addition, as more information 

becomes available regarding gastrointestinal 

absorption of environmental contaminants, 

adjustments to the soil and dust ingestion exposure 

equations may need to be made, to better represent 

the direction of movement of those contaminants 

within the gastrointestinal tract. 

To place these recommendations into context, it is 

useful to compare these soil ingestion rates to 

common measurements. The central tendency 

recommendation of 50 mg/day or 0.050 g/day, dryPage Exposure Factors Handbook 

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Chapter 5—Soil and Dust Ingestion 

weight basis, would be equivalent to approximately 

1/6 of an aspirin tablet per day because the average 

aspirin tablet is approximately 325 mg. The 50 g/day 

ingestion rate recommended to represent geophagy 

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behavior would be roughly equivalent to 150 aspirin 

tablets per day. 

 

 

 

 

Table 5-1. Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion (mg/day) 

Age Group 

Soila Dustb Soil + Dust 

General 

Population 

Central Tendency c 

High End 

General 

Population 

Central 

Tendency g 

General 

Population 

Upper 

Percentile h 

General 

Population 

Central 

Tendency c 

General 

Population 

Upper 

Percentile h 

General 

Population 

Upper 

Percentile d 

Soil-Picae Geophagy f 

6 weeks to <1 year 30 30 60 

1 to <6 years 50 1,000 50,000 60 100i 

3 to <6 years 200 100 200 

6 to <21 years 50 1,000 50,000 60 100i 

Adult 20j 50,000 30j 50 a Includes soil and outdoor settled dust. b Includes indoor settled dust only. c Davis and Mirick (2006); Hogan et al. (1998); Davis et al. (1990); van Wïjnen et al. (1990); Calabrese and Stanek 

(1995). d Özkaynak et al. (2011); Stanek and Calabrese (1995b); rounded to one significant figure. e ATSDR (2001); Stanek et al. (1998); Calabrese et al. (1997b; 1997a; 1991; 1989); Calabrese and Stanek (1993); Barnes 

(1990); Wong (1988); Vermeer and Frate (1979). f Vermeer and Frate (1979). g Hogan et al. (1998). h Özkaynak et al. (2011); rounded to one significant figure. i Total soil and dust ingestion rate is 110 mg/day; rounded to one significant figure it is 100 mg/day. 

j Estimates of soil and dust were derived from the soil + dust and assuming 45% soil and 55% dust. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Chapter 5—Soil and Dust Ingestion 

Table 5-2. Confidence in Recommendations for Ingestion of Soil and Dust 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The methodologies have significant limitations. The studies did not capture all of the 

information needed (quantities ingested, frequency of high soil ingestion episodes, 

prevalence of high soil ingestion). Six of the 12 key studies were of census or 

randomized design. Sample selection may have introduced some bias in the results (i.e., 

children near smelter or Superfund sites, volunteers in nursery schools). The total 

number of adults and children in key studies were 122 and 1,203 (859 U.S. children, 

292 Dutch, and 52 Jamaican children), respectively, while the target population 

currently numbers more than 74 million (U.S. Department of Commerce, 2008). 

Modeled estimates were based on 1,000 simulated individuals. The response rates for 

in-person interviews and telephone surveys were often not stated in published articles. 

Primary data were collected for 381 U.S. children and 292 Dutch children; secondary 

data for 478 U.S. children and 52 Jamaican children. Two key studies provided data for 

adults. 

Numerous sources of measurement error exist in the tracer element studies. Biokinetic 

model comparison studies may contain less measurement error than tracer element 

studies. Survey response study may contain measurement error. Some input variables 

for the modeled estimates are uncertain. 

Low 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

Eleven of the 12 key studies focused on the soil exposure factor, with no or less focus 

on the dust exposure factor. The biokinetic model comparison study did not focus 

exclusively on soil and dust exposure factors. 

The study samples may not be representative of the United States in terms of race, 

ethnicity, socioeconomics, and geographical location; studies focused on specific areas. 

Studies results are likely to represent current conditions. 

Tracer element studies’ data collection periods may not represent long-term behaviors. 

Biokinetic model comparison and survey response studies do represent longer term 

behaviors. Data used in modeled simulation estimates may not represent long-term 

behaviors. 

Low 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

Observations for individual children are available for only three of the 12 key studies. 

For the methodologies used by more than one research group, reproducible results were 

obtained in some instances. Some methodologies have been used by only one research 

group and have not been reproduced by others. 

For some studies, information on quality assurance/quality control was limited or 

absent. 

Low 

Variability and Uncertainty 

Variability in Population 

Minimal Uncertainty 

Tracer element and activity pattern methodology studies characterized variability among 

study sample members; biokinetic model comparison and survey response studies did 

not. Day-to-day and seasonal variability was not very well characterized. Numerous 

factors that may influence variability have not been explored in detail. 

Estimates are highly uncertain. Tracer element studies’ design appears to introduce 

biases in the results. Modeled estimates may be sensitive to input variables. 

Low 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

All key studies appeared in peer-review journals. 

12 key studies. Some key studies are reanalysis of previously published data. 

Researchers using similar methodologies obtained generally similar results; somewhat 

general agreement between researchers using different methodologies. 

Medium 

Overall Rating Low 

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Chapter 5—Soil and Dust Ingestion 

5.3. KEY AND RELEVANT STUDIES 

The key tracer element, biokinetic model 

comparison, and survey response studies are 

summarized in the following sections. Certain studies 

were considered “key” and were used as a basis for 

developing the recommendations, using judgment 

about the study’s design features, applicability, and 

utility of the data to U.S. soil and dust ingestion rates, 

clarity and completeness, and characterization of 

uncertainty and variability in ingestion estimates. 

Because the studies often were performed for reasons 

unrelated to developing soil and dust ingestion 

recommendations, their attributes that were 

characterized as “limitations” in this chapter might 

not be limitations when viewed in the context of the 

study’s original purpose. However, when studies are 

used for developing a soil or dust ingestion 

recommendation, U.S. EPA has categorized some 

studies’ design or implementation as preferable to 

others. In general, U.S. EPA chose studies designed 

either with a census or randomized sample approach 

over studies that used a convenience sample, or other 

non-randomized approach, as well as studies that 

more clearly explained various factors in the study’s 

implementation that affect interpretation of the 

results. However, in some cases, studies that used a 

non-randomized design contain information that is 

useful for developing exposure factor 

recommendations (for example, if they are the only 

studies of children in a particular age category), and 

thus may have been designated as “key” studies. 

Other studies were considered “relevant” but not 

“key” because they provide useful information for 

evaluating the reasonableness of the data in the key 

studies, but in U.S. EPA’s judgment they did not meet 

the same level of soundness, applicability and utility, 

clarity and completeness, and characterization of 

uncertainty and variability that the key studies did. In 

addition, studies that did not contain information that 

can be used to develop a specific recommendation for 

mg/day soil and dust ingestion were classified as 

relevant rather than key. 

Some studies are re-analyses of previously 

published data. For this reason, the sections that 

follow are organized into key and relevant studies of 

primary analysis (that is, studies in which researchers 

have developed primary data pertaining to soil and 

dust ingestion) and key and relevant studies of 

secondary analysis (that is, studies in which 

researchers have interpreted previously published 

results, or data that were originally collected for a 

different purpose). 

5.3.1. Methodologies Used in Key Studies 

5.3.1.1. Tracer Element Methodology 

The tracer element methodology attempts to 

quantify the amounts of soil ingested by analyzing 

samples of soil and dust from residences and/or 

children’s play areas, and feces or urine. The soil, 

dust, fecal, and urine samples are analyzed for the 

presence and quantity of tracer elements—typically, 

aluminum, silicon, titanium, and other elements. A 

key underlying assumption is that these elements are 

not metabolized into other substances in the body or 

absorbed from the gastrointestinal tract in significant 

quantities, and thus their presence in feces and urine 

can be used to estimate the quantity of soil ingested 

by mouth. Although they are sometimes called mass 

balance studies, none of the studies attempt to 

quantify amounts excreted in perspiration, tears, 

glandular secretions, or shed skin, hair or finger- and 

toenails, nor do they account for tracer element 

exposure via the dermal or inhalation into the lung 

routes, and thus they are not a complete “mass 

balance” methodology. Early studies using this 

methodology did not always account for the 

contribution of tracer elements from non-soil 

substances (food, medications, and non-food sources 

such as toothpaste) that might be swallowed. U.S. 

studies using this methodology in or after the mid to 

late 1980s account for, or attempt to account for, 

tracer element contributions from these non-soil 

sources. Some study authors adjust their soil 

ingestion estimate results to account for the potential 

contribution of tracer elements found in household 

dust as well as soil. 

The general algorithm that is used to calculate the 

quantity of soil or dust estimated to have been 

ingested is as follows: the quantity of a given tracer 

element, in milligrams, present in the feces and urine, 

minus the quantity of that tracer element, in 

milligrams, present in the food and medicine, the 

result of which is divided by the tracer element’s soil 

or dust concentration, in milligrams of tracer per 

gram of soil or dust, to yield an estimate of ingested 

soil, in grams. 

The U.S. tracer element researchers have all 

assumed a certain offset, or lag time between 

ingestion of food, medication, and soil, and the 

resulting fecal and urinary output. The lag times used 

are typically 24 or 28 hours; thus, these researchers 

subtract the previous day’s food and medication 

tracer element quantity ingested from the current 

day’s fecal and urinary tracer element quantity that 

was excreted. When compositing food, medication, 

fecal and urine samples across the entire study 

period, daily estimates can be obtained by dividing 

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the total estimated soil ingestion by the number of 

days in which fecal and/or urine samples were 

collected. A variation of the algorithm that provides 

slightly higher estimates of soil ingestion is to divide 

the total estimated soil ingestion by the number of 

days on which feces were produced, which by 

definition would be equal to or less than the total 

number of days of the study period’s fecal sample 

collection. 

Substituting tracer element dust concentrations 

for tracer element soil concentrations yields a dust 

ingestion estimate. Because the actual non-food, nonmedication quantity ingested is a combination of soil 

and dust, the unknown true soil and dust ingestion is 

likely to be somewhere between the estimates that are 

based on soil concentrations and estimates that are 

based on dust concentrations. Tracer element 

researchers have described ingestion estimates for 

soil that actually represent a combination of soil and 

dust, but were calculated based on tracer element 

concentrations in soil. Similarly, they have described 

ingestion estimates for dust that are actually for a 

combination of soil and dust, but were calculated 

based on tracer element concentrations in dust. Other 

variations on these general soil and dust ingestion 

algorithms have been published, in attempts to 

account for time spent indoors, time spent away from 

the house, etc. that could be expected to influence the 

relative proportion of soil versus dust. 

Each individual’s soil and dust ingestion can be 

represented as an unknown constant in a set of 

simultaneous equations of soil or dust ingestion 

represented by different tracer elements. To date, only 

two of the U.S. research teams (Barnes, 1990; 

Lásztity et al., 1989) have published estimates 

calculated for pairs of tracer elements using 

simultaneous equations. 

The U.S. tracer element studies have been 

performed for only short-duration study periods, and 

only for 33 adults (Davis and Mirick, 2006) and 

241 children [101 in Davis et al. (1990), 12 of whom 

were studied again in Davis and Mirick (2006); 64 in 

Calabrese et al. (1989) and Barnes (1990); 64 in 

Calabrese et al. (1997b); and 12 in Calabrese et al. 

(1997a)]. They provide information on quantities of 

soil and dust ingested for the studied groups for short 

time periods, but provide limited information on 

overall prevalence of soil ingestion by U.S. adults 

and children, and limited information on the 

frequency of higher soil ingestion episodes. 

The tracer element studies appear to contain 

numerous sources of error that influence the 

estimates upward and downward. Sometimes the 

error sources cause individual soil or dust ingestion 

estimates to be negative, which is not physically 

possible. In some studies, for some of the tracers, so 

many individual “mass balance” soil ingestion 

estimates were negative that median or mean 

estimates based on that tracer were negative. For soil 

and dust ingestion estimates based on each particular 

tracer, or averaged across tracers, the net impact of 

these competing upward and downward sources of 

error is unclear. 

5.3.1.2.	 Biokinetic Model Comparison 

Methodology 

The Biokinetic Model Comparison methodology 

compares direct measurements of a biomarker, such 

as blood or urine levels of a toxicant, with predictions 

from a biokinetic model of oral, dermal and 

inhalation exposure routes with air, food, water, soil, 

and dust toxicant sources. An example is to compare 

measured children’s blood lead levels with 

predictions from the IEUBK model. Where 

environmental contamination of lead in soil, dust, and 

drinking water has been measured and those 

measurements can be used as model inputs for the 

children in a specific community, the model’s 

assumed soil and dust ingestion values can be 

confirmed or refuted by comparing the model’s 

predictions of blood lead levels with those children’s 

measured blood lead levels. It should be noted, 

however, that such confirmation of the predicted 

blood lead levels would be confirmation of the net 

impact of all model inputs, and not just soil and dust 

ingestions. Under the assumption that the actual 

measured blood lead levels of various groups of 

children studied have minimal error, and those 

measured blood lead levels roughly match biokinetic 

model predictions for those groups of children, then 

the model’s default assumptions may be roughly 

accurate for the central tendency, or typical, children 

in an assessed group of children. The model’s default 

assumptions likely are not as useful for predicting 

outcomes for highly exposed children. 

5.3.1.3.	 Activity Pattern Methodology 

The activity pattern methodology includes 

observational studies as well as surveys of adults, 

children’s caretakers, or children themselves, via 

in-person or mailed questionnaires that ask about 

mouthing behavior and ingestion of various non-food 

items and time spent in various microenvironments. 

There are three general approaches to gather data on 

children’s mouthing behavior: real-time hand 

recording, in which trained observers manually 

record information (Davis et al., 1995); 

video-transcription, in which trained videographers 

tape a child’s activities and subsequently extract the 

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pertinent data manually or with computer software 

(Black et al., 2005); and questionnaire, or survey 

response, techniques (Stanek et al., 1998). 

The activity-pattern methodology combines 

information on hand-to-mouth and object-to-mouth 

activities (microactivities) and time spent at various 

locations (microenvironments) with assumptions 

about transfer parameters (e.g., soil-to-skin 

adherence, saliva removal efficiency) and other 

exposure factors (e.g., frequency of hand washing) to 

derive estimates of soil and dust ingestion. This 

methodology has been used in U.S. EPA's Stochastic 

Human Exposure and Dose Simulation (SHEDS) 

model. The SHEDS model is a probabilistic model 

that can simulate cumulative (multiple chemicals) or 

aggregate (single chemical) residential exposures for 

a population of interest over time via multiple routes 

of exposure for different types of chemicals and 

scenarios, including those involving soil ingestion 

(U.S. EPA, 2010). 

One of the limitations of this approach includes 

the availability and quality of the input variables. 

Özkaynak et al. (2011) found that the model is most 

sensitive to dust loadings on carpets and hard floor 

surfaces, soil-to-skin adherence factors, hand 

mouthing frequency, and hand washing frequency 

(Ozkaynak et al., 2011). 

5.3.2. Key Studies of Primary Analysis 

5.3.2.1.	 Vermeer and Frate (1979)—Geophagia in 

Rural Mississippi: Environmental and 

Cultural Contexts and Nutritional 

Implications 

Vermeer and Frate (1979) performed a survey 

response study in Holmes County, Mississippi in the 

1970s (date unspecified). Questions about geophagy 

(defined as regular consumption of clay over a period 

of weeks) were asked of household members 

(N = 229 in 50 households; 56 were women, 33 were 

men, and 140 were children or adolescents) of a 

subset of a random sample of nutrition survey 

respondents. Caregiver responses to questions about 

115 children under 13 indicate that geophagy was 

likely to be practiced by a minimum of 18 (16%) of 

these children; however, 16 of these 18 children were 

1 to 4 years old, and only 2 of the 18 were older than 

4 years. Of the 56 women, 32 (57%) reported eating 

clay. There was no reported geophagy among 33 men 

or 25 adolescent study subjects questioned. 

In a separately administered survey, geophagy 

and pica data were obtained from 142 pregnant 

women over a period of 10 months. Geophagy was 

reported by 40 of these women (28%), and an 

additional 27 respondents (19%) reported other pica 

behavior, including the consumption of laundry 

starch, dry powdered milk, and baking soda. 

The average daily amount of clay consumed was 

reported to be about 50 grams, for the adult and child 

respondents who acknowledged practicing geophagy. 

Quantities were usually described as either portions 

or multiples of the amount that could be held in a 

single, cupped hand. Clays for consumption were 

generally obtained from the B soil horizon, or subsoil 

rather than an uppermost layer, at a depth of 50 to 

130 centimeters. 

5.3.2.2.	 Calabrese et al. (1989)—How Much Soil 

Do Young Children Ingest: An 

Epidemiologic Study/Barnes 

(1990)―Childhood Soil Ingestion: How 

Much Dirt Do Kids Eat?/Calabrese et al. 

(1991)—Evidence of Soil-Pica Behavior 

and Quantification of Soil Ingested 

Calabrese et al. (1989) and Barnes (1990) studied 

soil ingestion among children using eight tracer 

elements—aluminum, barium, manganese, silicon, 

titanium, vanadium, yttrium, and zirconium. A 

non-random sample of 30 male and 34 female 1, 2, 

and 3-year-olds from the greater Amherst, 

Massachusetts area were studied, presumably in 

1987. The children were predominantly from 

two-parent households where the parents were highly 

educated. The study was conducted over a period of 

8 days spread over 2 weeks. During each week, 

duplicate samples of food, beverages, medicines, and 

vitamins were collected on Monday through 

Wednesday, while excreta, excluding wipes and toilet 

paper, were collected for four 24-hour cycles running 

from Monday/Tuesday through Thursday/Friday. Soil 

and dust samples were also collected from the child’s 

home and play area. Study participants were supplied 

with toothpaste, baby cornstarch, diaper rash cream, 

and soap with low levels of most of the tracer 

elements. 

Table 5-3 shows the published mean soil 

ingestion estimates ranging from −294 mg/day based 

on manganese to 459 mg/day based on vanadium, 

median soil ingestion estimates ranging from 

−261 mg/day based on manganese to 96 mg/day 

based on vanadium, and 95th percentile estimates 

ranged from 106 mg/day based on yttrium to 

1,903 mg/day based on vanadium. Maximum daily 

soil ingestion estimates ranged from 1,391 mg/day 

based on zirconium to 7,281 mg/day based on 

manganese. Dust ingestions calculated using tracer 

concentrations in dust were often, but not always, 

higher than soil ingestions calculated using tracer 

concentrations in soil. 

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Data for the uppermost 23 subject-weeks (the 

highest soil ingestion estimates, averaged over the 

4 days of excreta collection during each of the 

2 weeks) were published in Calabrese et al. (1991). 

One child’s soil-pica behavior was estimated in 

Barnes (1990) using both the subtraction/division 

algorithm and the simultaneous equations method. 

On two particular days during the second week of the 

study period, the child’s aluminum-based soil 

ingestion estimates were 19 g/day (18,700 mg/day) 

and 36 g/day (35,600 mg/day), silicon-based soil 

ingestion estimates were 20 g/day (20,000 mg/day) 

and 24 g/day (24,000), and simultaneous-equation 

soil ingestion estimates were 20 g/day 

(20,100 mg/day) and 23 g/day (23,100 mg/day) 

(Barnes, 1990). By tracer, averaged across the entire 

week, this child’s estimates ranged from 

approximately 10 to 14 g/day during the second week 

of observation [Calabrese et al. (1991), shown in 

Table 5-4], and averaged 6 g/day across the entire 

study period. Additional information about this 

child’s apparent ingestion of soil versus dust during 

the study period was published in Calabrese and 

Stanek (1992b). 

5.3.2.3.	 Van Wïjnen et al. (1990)—Estimated Soil 

Ingestion by Children 

In a tracer element study by van Wïjnen et al. 

(1990), soil ingestion among Dutch children ranging 

in age from 1 to 5 years was evaluated using a tracer 

element methodology. Van Wïjnen et al. (1990) 

measured three tracers (titanium, aluminum, and acid 

insoluble residue [AIR]) in soil and feces. The 

authors estimated soil ingestion based on an 

assumption called the Limiting Tracer Method 

(LTM), which assumed that soil ingestion could not 

be higher than the lowest value of the three tracers. 

LTM values represented soil ingestion estimates that 

were not corrected for dietary intake. 

An average daily feces dry weight of 15 grams 

was assumed. A total of 292 children attending 

daycare centers were studied during the first of two 

sampling periods and 187 children were studied in 

the second sampling period; 162 of these children 

were studied during both periods (i.e., at the 

beginning and near the end of the summer of 1986). 

A total of 78 children were studied at campgrounds. 

The authors reported geometric mean LTM values 

because soil ingestion rates were found to be skewed 

and the log-transformed data were approximately 

normally distributed. Geometric mean LTM values 

were estimated to be 111 mg/day for children in 

daycare centers and 174 mg/day for children 

vacationing at campgrounds (see Table 5-5). For the 

162 daycare center children studied during both 

sampling periods the arithmetic mean LTM was 

162 mg/day, and the median was 114 mg/day. 

Fifteen hospitalized children were studied and 

used as a control group. These children’s LTM soil 

ingestion estimates were 74 (geometric mean), 

93 (mean), and 110 (median) mg/day. The authors 

assumed the hospitalized children’s soil ingestion 

estimates represented dietary intake of tracer 

elements, and used rounded 95% confidence limits 

on the arithmetic mean, 70 to 120 mg/day, to correct 

the daycare and campground children’s LTM 

estimates for dietary intake of tracers. Corrected soil 

ingestion rates were 69 mg/day (162 mg/day minus 

93 mg/day) for daycare children and 120 mg/day 

(213 mg/day minus 93 mg/day) for campers. 

Corrected geometric mean soil ingestion was 

estimated to range from 0 to 90 mg/day, with a 

90th percentile value of up to 190 mg/day for the 

various age categories within the daycare group and 

30 to 200 mg/day, with a 90th percentile value of up 

to 300 mg/day for the various age categories within 

the camping group. 

AIR was the limiting tracer in about 80%of the 

samples. Among children attending daycare centers, 

soil ingestion was also found to be higher when the 

weather was good (i.e., <2 days/week precipitation) 

than when the weather was bad (i.e., >4 days/week 

precipitation (see Table 5-6). 

5.3.2.4.	 Davis et al. (1990)—Quantitative Estimates 

of Soil Ingestion in Normal Children 

Between the Ages of 2 and 7 Years: 

Population-Based Estimates Using 

Aluminum, Silicon, and Titanium as Soil 

Tracer Elements 

Davis et al. (1990) used a tracer element 

technique to estimate soil ingestion among children. 

In this study, 104 children between the ages of 2 and 

7 years were randomly selected from a three-city area 

in southeastern Washington State. Soil and dust 

ingestion was evaluated by analyzing soil and house 

dust, feces, urine, and duplicate food, dietary 

supplement, medication and mouthwash samples for 

aluminum, silicon, and titanium. Data were collected 

for 101 of the 104 children during July, August, or 

September, 1987. In each family, data were collected 

over a 7-day period, with 4 days of excreta sample 

collection. Participants were supplied with toothpaste 

with known tracer element content. In addition, 

information on dietary habits and demographics was 

collected in an attempt to identify behavioral and 

demographic characteristics that influence soil 

ingestion rates among children. The amount of soil 

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Chapter 5—Soil and Dust Ingestion 

ingested on a daily basis was estimated using 

Equation 5-1: 

(((DW f + DW p ) × E f ) + 2Eu ) − (DW fd × E fd ) S =	 (Eqn. 5-1) i,e Esoil 

where: 

Si,e	 =soil ingested for child i based on 

tracer e (grams); 

DWf	 =feces dry weight (grams); 

DWp	 =feces dry weight on toilet paper 

(grams); 

Ef	 =tracer concentration in feces 

(μg/g); 

Eu	 =tracer amount in urine (μg); 

DWfd	 =food dry weight (grams); 

Efd	 =tracer concentration in food 

(μg/g); and 

Esoil	 =tracer concentration in soil (μg/g). 

The soil ingestion rates were corrected by adding 

the amount of tracer in vitamins and medications to 

the amount of tracer in food, and adjusting the food, 

fecal and urine sample weights to account for missing 

samples. Food, fecal and urine samples were 

composited over a 4-day period, and estimates for 

daily soil ingestion were obtained by dividing the 

4-day composited tracer quantities by 4. 

Soil ingestion rates were highly variable, 

especially those based on titanium. Mean daily soil 

ingestion estimates were 38.9 mg/day for aluminum, 

82.4 mg/day for silicon and 245.5 mg/day for 

titanium (see Table 5-7). Median values were 

25 mg/day for aluminum, 59 mg/day for silicon, and 

81 mg/day for titanium. The investigators also 

evaluated the extent to which differences in tracer 

concentrations in house dust and yard soil impacted 

estimated soil ingestion rates. The value used in the 

denominator of the soil ingestion estimate equation 

was recalculated to represent a weighted average of 

the tracer concentration in yard soil and house dust 

based on the proportion of time the child spent 

indoors and outdoors, using an assumption that the 

likelihood of ingesting soil outdoors was the same as 

that of ingesting dust indoors. The adjusted mean 

soil/dust ingestion rates were 64.5 mg/day for 

aluminum, 160.0 mg/day for silicon, and 

268.4 mg/day for titanium. Adjusted median soil/dust 

ingestion rates were: 51.8 mg/day for aluminum, 

112.4 mg/day for silicon, and 116.6 mg/day for 

titanium. The authors investigated whether nine 

behavioral and demographic factors could be used to 

predict soil ingestion, and found family income less 

than $15,000/year and swallowing toothpaste to be 

significant predictors with silicon-based estimates; 

residing in one of the three cities to be a significant 

predictor with aluminum-based estimates, and 

washing the face before eating significant for 

titanium-based estimates. 

5.3.2.5.	 Calabrese et al. (1997b)—Soil Ingestion 

Estimates for Children Residing on a 

Superfund Site 

Calabrese et al. (1997b) estimated soil ingestion 

rates for children residing on a Superfund site using a 

methodology in which eight tracer elements were 

analyzed. The methodology used in this study is 

similar to that employed in Calabrese et al. (1989), 

except that rather than using barium, manganese, and 

vanadium as three of the eight tracers, the researchers 

replaced them with cerium, lanthanum, and 

neodymium. A total of 64 children ages 1−3 years (36 

male, 28 female) were selected for this study of the 

Anaconda, Montana area. The study was conducted 

for seven consecutive days during September or 

September and October, apparently in 1992, shortly 

after soil was removed and replaced in some 

residential yards in the area. Duplicate samples of 

meals, beverages, and over-the-counter medicines 

and vitamins were collected over the 7 day period, 

along with fecal samples. In addition, soil and dust 

samples were collected from the children’s home and 

play areas. Toothpaste containing non-detectable 

levels of the tracer elements, with the exception of 

silica, was provided to all of the children. Infants 

were provided with baby cornstarch, diaper rash 

cream, and soap, which were found to contain low 

levels of tracer elements. 

Because of the high degree of intertracer 

variability, Calabrese et al. (1997b) also derived 

estimates based on the “Best Tracer Methodology” 

(BTM). This BTM uses food/soil tracer concentration 

ratios in order to correct for errors caused by 

misalignment of tracer input and outputs, ingestion of 

non-food sources, and non-soil sources (Stanek and 

Calabrese, 1995b). A low food/soil ratio is desired 

because it minimizes transit time errors. The BTM 

did not use the results from Ce, La, and Nd despite 

these tracers having low food/soil ratios because the 

soil concentrations for these elements were found to 

be affected by particle size and more susceptible to 

source errors. Calabrese et al. (1997b) noted that 

estimates based on Al, Si, and Y in this study may 

result in lower soil ingestion estimates than the true 

value because the apparent residual negative errors 

found for these three tracers for a large majority of 

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subjects. It was noted that soil ingestion estimates for 

this population may be lower than estimates found by 

previous studies in the literature because of families’ 

awareness of contamination from the Superfund site, 

which may have resulted in altered behavior. 

Soil ingestion estimates were also examined 

based on various demographic characteristics. There 

were no statistically significant differences in soil 

ingestion based on age, sex, birth order, or house yard 

characteristics (Calabrese et al., 1997b). Although not 

statistically significant, soil ingestion rates were 

generally higher for females, children with lower 

birth number, children with parents employed as 

laborers, or in service profession, homemakers, or 

unemployed and for children with pets (Calabrese et 

al., 1997b). 

Table 5-8 shows the estimated soil and dust 

ingestion by each tracer element and by the BTM. 

Based on the BTM, the mean soil and dust ingestion 

rates were 65.5 mg/day and 127.2 mg/day, 

respectively. 

5.3.2.6.	 Stanek et al. (1998)—Prevalence of Soil 

Mouthing/Ingestion Among Healthy 

Children Aged One to Six/Calabrese et al. 

(1997a)—Soil Ingestion Rates in Children 

Identified by Parental Observation as 

Likely High Soil Ingesters 

Stanek et al. (1998) conducted a survey response 

study using in-person interviews of parents of 

children attending well visits at three western 

Massachusetts medical clinics in August, September, 

and October of 1992. Of 528 children ages 1 to 7 

with completed interviews, parents reported daily 

mouthing or ingestion of sand and stones in 6%, daily 

mouthing or ingestion of soil and dirt in 4%, and 

daily mouthing or ingestion of dust, lint and dustballs 

in 1%. Parents reported more than weekly mouthing 

or ingestion of sand and stones in 16%, more than 

weekly mouthing or ingestion of soil and dirt in 10%, 

and more than weekly mouthing or ingestion of dust, 

lint and dustballs in 3%. Parents reported more than 

monthly mouthing or ingestion of sand and stones in 

27%, more than monthly mouthing or ingestion of 

soil and dirt in 18%, and more than monthly 

mouthing or ingestion of dust, lint, and dustballs in 

6%. 

Calabrese and colleagues performed a follow-up 

tracer element study (Calabrese et al., 1997a) for a 

subset (N = 12) of the Stanek et al. (1998) children 

whose caregivers had reported daily sand/soil 

ingestion (N = 17). The time frame of the follow-up 

tracer study relative to the original survey response 

study was not stated; the study duration was 7 days. 

Of the 12 children in Calabrese et al. (1997a), one 

exhibited behavior that the authors believed was 

clearly soil pica; Table 5-9 shows estimated soil 

ingestion rates for this child during the study period. 

Estimates ranged from –10 mg/day to 7,253 mg/day 

depending on the tracer. Table 5-10 presents the 

estimated average daily soil ingestion estimates for 

the 12 children studied. Estimates calculated based 

on soil tracer element concentrations only ranged 

from –15 to +1,783 mg/day based on aluminum, 

−46 to +931 mg/day based on silicon, and –47 

to +3,581 mg/day based on titanium. Estimated 

average daily dust ingestion estimates ranged from 

−39 to +2,652 mg/day based on aluminum, –351 

to +3,145 mg/day based on silicon, and –98 

to +3,632 mg/day based on titanium. Calabrese et al. 

(1997a) question the validity of retrospective 

caregiver reports of soil pica on the basis of the tracer 

element results. 

5.3.2.7.	 Davis and Mirick (2006)—Soil Ingestion in 

Children and Adults in the Same Family 

Davis and Mirick (2006) calculated soil ingestion 

for children and adults in the same family using a 

tracer element approach. Data were collected in 1988, 

one year after the Davis et al. (1990) study was 

conducted. Samples were collected and prepared for 

laboratory analysis and then stored for a 2-year 

period prior to tracer element quantification with 

laboratory analysis. Analytical recovery values for 

spiked samples were within the quality control limits 

of ±25%. The 20 families in this study were a nonrandom subset of the 104 families who participated in 

the soil ingestion study by Davis et al. (1990). Data 

collection issues resulted in sufficiently complete 

data for only 19 of the 20 families consisting of a 

child participant from the Davis et al. (1990) study 

ages 3 to 7, inclusive, and a female and male parent 

or guardian living in the same house. Duplicate 

samples of all food and medication items consumed, 

and all feces excreted, were collected for 

11 consecutive days. Urine samples were collected 

twice daily for 9 of the 11 days; for the remaining 

2 days, attempts were made to collect full 24-hour 

urine specimens. Soil and house dust samples were 

also collected. Only 12 children had sufficiently 

complete data for use in the soil and dust ingestion 

estimates. 

Tracer elements for this study included aluminum, 

silicon, and titanium. Toothpaste was supplied for use 

by study participants. In addition, parents completed 

a daily diary of activities for themselves and the 

participant child for 4 consecutive days during the 

study period. 

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Table 5-11 shows soil ingestion rates for all three 

family member participants. The mean and median 

estimates for children for all three tracers ranged 

from 36.7 to 206.9 mg/day and 26.4 to 46.7 mg/day, 

respectively, and fall within the range of those 

reported by Davis et al. (1990). Adult soil ingestion 

estimates ranged from 23.2 to 624.9 mg/day for mean 

values and from 0 to 259.5 mg/day for median 

values. Adult soil ingestion estimates were more 

variable than those of children in the study regardless 

of the tracer. The authors believed that this higher 

variability may have indicated an important 

occupational contribution of soil ingestion in some, 

but not all, of the adults. Similar to previous studies, 

the soil ingestion estimates were the highest for 

titanium. Although toothpaste is a known source of 

titanium, the titanium content of the toothpaste used 

by study participants was not determined. 

Only three of a number of behaviors examined for 

their relationship to soil ingestion were found to be 

associated with increased soil ingestion in this study: 

 reported eating of dirt (for children); 

 occupational contact with soil (for adults); and 

 hand washing before meals (for both children 

and adults). 

Several typical childhood behaviors, however, 

including thumb-sucking, furniture licking, and 

carrying around a blanket or toy were not associated 

with increased soil ingestion for the participating 

children. Among both parents and children, neither 

nail-biting nor eating unwashed fruits or vegetables 

was correlated with increased soil ingestion. 

However, because the study design required an equal 

amount of any food consumed to be included in the 

sample for analysis, eating unwashed fruits or 

vegetables would not have contributed to an increase 

in soil ingestion. Although eating unwashed fruits or 

vegetables was not associated with soil ingestion in 

either children or adults in this study, the authors 

noted that it is a behavior that could lead to soil 

ingestion. When investigating correlations within the 

same family, a child’s soil ingestion was not found to 

be associated with either parent’s soil ingestion, nor 

did the mother and father’s soil ingestion appear to be 

correlated. 

5.3.3. Key Studies of Secondary Analysis 

5.3.3.1.	 Wong (1988)—The Role of Environmental 

and Host Behavioral Factors in 

Determining Exposure to Infection With 

Ascaris lumbricoides and Trichuris 

Trichiura/Calabrese and Stanek 

(1993)―Soil Pica: Not a Rare Event 

Calabrese and Stanek (1993) reviewed a tracer 

element study that was conducted by Wong (1988) to 

estimate the amount of soil ingested by two groups of 

children. Wong (1988) studied a total of 52 children 

in two government institutions in Jamaica. The 

younger group included 24 children with an average 

age of 3.1 years (range of 0.3 to 7.5 years). The older 

group included 28 children with an average age of 

7.2 years (range of 1.8 to 14 years). One fecal sample 

was collected each month from each subject over the 

4-month study period. The amount of silicon in dry 

feces was measured to estimate soil ingestion. 

An unspecified number of daily fecal samples 

were collected from a hospital control group of 

30 children with an average age of 4.8 years (range of 

0.3 to 12 years). Dry feces were observed to contain 

1.45% silicon, or 14.5 mg Si per gram of dry feces. 

This quantity was used to correct measured fecal 

silicon from dietary sources. Fecal silicon quantities 

greater than 1.45% in the 52 studied children were 

interpreted as originating from soil ingestion. 

For the 28 children in the older group, soil 

ingestion was estimated to be 58 mg/day, based on 

the mean minus one outlier, and 1,520 mg/day, based 

on the mean of all the children. The outlier was a 

child with an estimated average soil ingestion rate of 

41 g/day over the 4 months. 

Estimates of soil ingestion were higher in the 

younger group of 24 children. The mean soil 

ingestion of all the children was 470 ± 370 mg/day. 

Due to some sample losses, of the 24 children 

studied, only 15 had samples for each of the 4 months 

of the study. Over the entire 4-month study period, 9 

of 84 samples (or 10.5%) yielded soil ingestion 

estimates in excess of 1 g/day. 

Of the 52 children studied, 6 had one-day 

estimates of more than 1,000 mg/day. Table 5-12 

shows the estimated soil ingestion for these six 

children. The article describes 5 of 24 (or 20.8%) in 

the younger group of children as having 

a >1,000 mg/day estimate on at least one of the four 

study days; in the older group one child is described 

in this manner. A high degree of daily variability in 

soil ingestion was observed among these six children; 

three showed soil-pica behavior on 2, 3, and 4 days, 

respectively, with the most consistent (4 out of 

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4 days) soil-pica child having the highest estimated 

soil ingestion, 3.8 to 60.7 g/day. 

5.3.3.2.	 Calabrese and Stanek (1995)—Resolving 

Intertracer Inconsistencies in Soil 

Ingestion Estimation 

Calabrese and Stanek (1995) explored sources 

and magnitude of positive and negative errors in soil 

ingestion estimates for children on a subject-week 

and trace element basis. Calabrese and Stanek (1995) 

identified possible sources of positive errors as 

follows: 

 Ingestion of high levels of tracers before the 

start of the study and low ingestion during the 

study period; and 

 Ingestion of element tracers from a non-food 

or non-soil source during the study period. 

Possible sources of negative bias were identified 

as follows: 

 Ingestion of tracers in food that are not 

captured in the fecal sample either due to slow 

lag time or not having a fecal sample available 

on the final study day; and 

 Sample measurement errors that result in 

diminished detection of fecal tracers, but not 

in soil tracer levels. 

The authors developed an approach that attempted 

to reduce the magnitude of error in the individual 

trace element ingestion estimates. Results from a 

previous study conducted by Calabrese et al. (1989) 

were used to quantify these errors based on the 

following criteria: (1) a lag period of 28 hours was 

assumed for the passage of tracers ingested in food to 

the feces (this value was applied to all subject-day 

estimates); (2) a daily soil ingestion rate was 

estimated for each tracer for each 24-hour day a fecal 

sample was obtained; (3) the median tracer-based soil 

ingestion rate for each subject-day was determined; 

and (4) negative errors due to missing fecal samples 

at the end of the study period were also determined. 

Also, upper- and lower-bound estimates were 

determined based on criteria formed using an 

assumption of the magnitude of the relative standard 

deviation presented in another study conducted by 

Stanek and Calabrese (1995a). Daily soil ingestion 

rates for tracers that fell beyond the upper and lower 

ranges were excluded from subsequent calculations, 

and the median soil ingestion rates of the remaining 

tracer elements were considered the best estimate for 

that particular day. The magnitude of positive or 

negative error for a specific tracer per day was 

derived by determining the difference between the 

value for the tracer and the median value. 

Table 5-13 presents the estimated magnitude of 

positive and negative error for six tracer elements in 

the children's study [conducted by Calabrese et al. 

(1989)]. The original non-negative mean soil 

ingestion rates (see Table 5-3) ranged from a low of 

21 mg/day based on zirconium to a high of 

459 mg/day based on vanadium. The adjusted mean 

soil ingestion rate after correcting for negative and 

positive errors ranged from 97 mg/day based on 

yttrium to 208 mg/day based on titanium. Calabrese 

and Stanek (1995) concluded that correcting for 

errors at the individual level for each tracer element 

provides more reliable estimates of soil ingestion. 

5.3.3.3.	 Stanek and Calabrese (1995b)—Soil 

Ingestion Estimates for Use in Site 

Evaluations Based on the Best Tracer 

Method 

Stanek and Calabrese (1995b) recalculated soil 

ingestion rates for adults and children from two 

previous studies, using data for eight tracers from 

Calabrese et al. (1989) and three tracers from Davis 

et al. (1990). Recalculations were performed using 

the BTM. This method selected the “best” tracer(s), 

by dividing the total amount of tracer in a particular 

child’s duplicate food sample by tracer concentration 

in that child’s soil sample to yield a food/soil (F/S) 

ratio. The F/S ratio was small when the tracer 

concentration in food was low compared to the tracer 

concentration in soil. Small F/S ratios were desirable 

because they lessened the impact of transit time error 

(the error that occurs when fecal output does not 

reflect food ingestion, due to fluctuation in 

gastrointestinal transit time) in the soil ingestion 

calculation. 

For adults, Stanek and Calabrese (1995b) used 

data for eight tracers from the Calabrese et al. (1989) 

study to estimate soil ingestion by the BTM. The 

lowest F/S ratios were Zr and Al and the element 

with the highest F/S ratio was Mn. For soil ingestion 

estimates based on the median of the lowest four F/S 

ratios, the tracers contributing most often to the soil 

ingestion estimates were Al, Si, Ti, Y, V, and Zr. 

Using the median of the soil ingestion rates based on 

the best four tracer elements, the average adult soil 

ingestion rate was estimated to be 64 mg/day with a 

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median of 87 mg/day. The 95th percentile soil 

ingestion estimate was 142 mg/day. These estimates 

are based on 18 subject weeks for the six adult 

volunteers described in Calabrese et al. (1989). 

The BTM used a ranking scheme of F/S ratios to 

determine the best tracers for use in the ingestion rate 

calculation. To reduce the impact of biases that may 

occur as a result of sources of fecal tracers other than 

food or soil, the median of soil ingestion estimates 

based on the four lowest F/S ratios was used to 

represent soil ingestion. 

Using the lowest four F/S ratios for each 

individual, calculated on a per-week (“subject-week”) 

basis, the median of the soil ingestion estimates from 

the Calabrese et al. (1989) study most often included 

aluminum, silicon, titanium, yttrium, and zirconium. 

Based on the median of soil ingestion estimates from 

the best four tracers, the mean soil ingestion rate for 

children was 132 mg/day and the median was 

33 mg/day. The 95th percentile value was 154 mg/day. 

For the 101 children in the Davis et al. (1990) study, 

the mean soil ingestion rate was 69 mg/day and the 

median soil ingestion rate was 44 mg/day. The 

95th percentile estimate was 246 mg/day. These data 

are based on the three tracers (i.e., aluminum, silicon, 

and titanium) from the Davis et al. (1990) study. 

When the results for the 128 subject-weeks in 

Calabrese et al. (1989) and 101 children in Davis et 

al. (1990) were combined, soil ingestion for children 

was estimated to be 104 mg/day (mean); 37 mg/day 

(median); and 217 mg/day (95th percentile), using the 

BTM. 

5.3.3.4.	 Hogan et al. (1998)—Integrated Exposure 

Uptake Biokinetic Model for Lead in 

Children: Empirical Comparisons With 

Epidemiologic Data 

Hogan et al. (1998) used the biokinetic model 

comparison methodology to review the measured 

blood lead levels of 478 children. These children 

were a subset of the entire population of children 

living in three historic lead smelting communities 

(Palmerton, Pennsylvania; Madison County, Illinois; 

and southeastern Kansas/southwestern Missouri), 

whose environmental lead exposures (soil and dust 

lead levels) had been studied as part of public health 

evaluations in these communities. The study 

populations were, in general, random samples of 

children 6 months to 7 years of age. Children who 

had lived in their residence for less than 3 months or 

those reported by their parents to be away from home 

more than 10 hours per week (>20 hours/week for the 

Pennsylvania data set) were excluded due to lack of 

information regarding lead exposure at the secondary 

location. The nature of the soil and dust exposures for 

the residential study population were typical, with the 

sample size considered sufficiently large to ensure 

that a wide enough range of children’s behavior 

would be spanned by the data. Comparisons were 

made for a number of exposure factors, including 

age, location, time spent away from home, time spent 

outside, and whether or not children took food 

outside to eat. 

The IEUBK model is a biokinetic model for 

predicting children’s blood lead levels that uses 

measurements of lead content in house dust, soil, 

drinking water, food, and air, and child-specific 

estimates of intake for each exposure medium (dust, 

soil, drinking water, food and air). Model users can 

also use default assumptions for the lead contents and 

intake rates for each exposure medium when they do 

not have specific information for each child. 

Hogan et al. (1998) compared children’s 

measured blood lead levels with biokinetic model 

predictions (IEUBK version 0.99d) of blood lead 

levels, using the children’s measured drinking water, 

soil, and dust lead contamination levels together with 

default IEUBK model inputs for soil and dust 

ingestion, relative proportions of soil and dust 

ingestion, lead bioavailability from soil and dust, and 

other model parameters. Thus, the default soil and 

dust ingestion rates in the model, and other default 

assumptions in the model, were tested by comparing 

measured blood lead levels with the model’s 

predictions for those children’s blood lead levels. 

Most IEUBK model kinetic and intake parameters 

were drawn independently from published literature 

(White et al., 1998; U.S. EPA, 1994b). Elimination 

parameters in particular had relatively less literature 

to draw upon (few data in children) and were fixed 

through a calibration exercise using a data set with 

children's blood lead levels paired with measured 

environmental lead exposures in and around their 

homes, while holding the other model parameters 

constant. 

For Palmerton, Pennsylvania (N = 34), the 

community-wide geometric mean measured blood 

lead levels (6.8 μg/dL) were slightly over-predicted 

by the model (7.5 μg/dL); for southeastern 

Kansas/southwestern Missouri (N = 111), the blood 

lead levels (5.2 μg/dL) were slightly under-predicted 

(4.6 μg/dL), and for Madison County, Illinois 

(N = 333), the geometric mean measured blood lead 

levels matched the model predictions (5.9 μg/dL 

measured and predicted), with very slight differences 

in the 95% confidence interval. Although there may 

be uncertainty in these estimates, these results 

suggest that the default soil and dust ingestion rates 

used in this version of the IEUBK model 

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(approximately 50 mg/day soil and 60 mg/day dust 

for a total soil + dust ingestion of 110 mg/day, 

averaged over children ages 1 through 6) may be 

roughly accurate in representing the central tendency 

soil and dust ingestion rates of residence-dwelling 

children in the three locations studied. 

5.3.3.5.	 Özkaynak et al. (2011)—Modeled 

Estimates of Soil and Dust Ingestion Rates 

for Children 

Özkaynak et al. (2011) developed soil and dust 

ingestion rates for children 3 to <6 years of age using 

U.S. EPA’s SHEDS model for multimedia pollutants 

(SHEDS-Multimedia). The authors had two main 

objectives for this research: (1) to demonstrate an 

application of the SHEDS model while identifying 

and quantifying the key factors contributing to the 

predicted variability and uncertainty in the soil and 

dust ingestion exposure estimates, and (2) to compare 

the modeled results to existing tracer-element field 

measurements. The SHEDS model is a physically 

based probabilistic exposure model, which combines 

diary information on sequential time spent in 

different locations and activities drawn from 

U.S. EPA’s Consolidated Human Activity Database 

(CHAD), with micro-activity data (e.g., hand-tomouth frequency, hand-to-surface frequency), 

surface/object soil or dust loadings, and other 

exposure factors (e.g., soil-to-skin adherence, saliva 

removal efficiency). The SHEDS model generates 

simulated individuals, who are then followed through 

time, generally up to one year. The model computes 

changes to their exposure at the diary event level. 

For this study, an indirect modeling approach 

was used, in which soil and dust were assumed to 

first adhere to the hands, and remain until washed off 

or ingested by mouthing. The object-to-mouth 

pathway for soil/dust ingestion was also addressed. 

For this application of the SHEDS model, however, 

other avenues of soil/dust ingestion were not 

considered. Outdoor matter was designated as “soil” 

and indoor matter as “dust.” Estimates for the 

distributions of exposure factors such as activity, time 

outdoors, environmental concentrations, soil-skin and 

dust-skin transfer, hand washing frequency and 

efficiency, hand-mouthing frequency, area of object 

or hand mouthed, mouthing removal rates, and other 

variables were obtained from the literature. These 

input variables were used in this SHEDS model 

application to generate estimates of soil and dust 

ingestion rates for a simulated population of 1,000. 

Both sensitivity and uncertainty analyses were 

conducted. Based on the sensitivity analysis, the 

model results are the most sensitive to dust loadings 

on carpet and hard floor surfaces; soil-skin adherence 

factor; hand mouthing frequency, and; mean number 

of hand washes per day. Based on 200 uncertainty 

simulations that were conducted, the modeling 

uncertainties were seen to be asymmetrically 

distributed around the 50th (median) or the central 

variability distribution. 

Table 5-14 shows the predicted soil- and 

dust-ingestion rates. Mean total soil and dust 

ingestion was predicted to be 68 mg/day, with 

approximately 60% originating from soil ingestion, 

30% from dust on hands, and 10% from dust on 

objects. Hand-to-mouth soil and dust ingestion was 

found to be the most important pathway, followed by 

hand-to-mouth dust ingestion, then object-to-mouth 

dust ingestion. The authors noted that these modeled 

estimates were found to be consistent with other 

soil/dust ingestion values in the literature, but slightly 

lower than the central tendency value of 100 mg/day 

recommended in U.S. EPA’s Child-Specific Exposure 

Factors Handbook (U.S. EPA, 2008). 

The advantages of this study include the fact that 

the SHEDS methodology can be applied to specific 

study populations of interest, a wide range of input 

parameters can be applied, and a full range of 

distributions can be generated. The primary limitation 

of this study is the lack of data for some of the input 

variables. Data needs include additional information 

on the activities and environments of children in 

younger age groups, including children with high 

hand-to-mouth, object-to-mouth, and pica behaviors, 

and information on skin adherence and dust loadings 

on indoor objects and floors. In addition, other age 

groups of interest were not included because of lack 

of data for some of the input variables. 

5.3.4. Relevant Studies of Primary Analysis 

The following studies are classified as relevant 

rather than key. The tracer element studies described 

in this section are not designated as key because the 

methodology to account for non-soil tracer exposures 

was not as well-developed as the methodology in the 

U.S. tracer element studies described in 

Sections 5.3.2 and 5.3.3, or because they do not 

provide a quantitative estimate of soil ingestion. 

However, the method of Clausing et al. (1987) was 

used in developing biokinetic model default soil and 

dust ingestion rates (U.S. EPA, 1994a) used in the 

Hogan et al. (1998) study, which was designated as 

key. In the survey response studies, in most cases the 

studies were of a non-randomized design, insufficient 

information was provided to determine important 

details regarding study design, or no data were 

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provided to allow quantitative estimates of soil and/or 

dust ingestion rates. 

5.3.4.1.	 Dickins and Ford (1942)—Geophagy (Dirt 

Eating) Among Mississippi Negro School 

Children 

Dickens and Ford conducted a survey response 

study of rural Black school children (4th grade and 

above) in Oktibbeha County, Mississippi in 

September 1941. A total of 52 of 207 children (18 of 

69 boys and 34 of 138 girls) studied gave positive 

responses to questions administered in a test-taking 

format regarding having eaten dirt in the previous 10 

to 16 days. The authors stated that the study sample 

likely was more representative of the higher 

socioeconomic levels in the community, because 

older children from lower socioeconomic levels 

sometimes left school in order to work, and because 

children in the lower grades, who were more 

socioeconomically representative of the overall 

community, were excluded from the study. Clay was 

identified as the predominant type of soil eaten. 

5.3.4.2.	 Ferguson and Keaton (1950)—Studies of 

the Diets of Pregnant Women in 

Mississippi: II Diet Patterns 

Ferguson and Keaton (1950) conducted a survey 

response study of a group of 361 pregnant women 

receiving health care at the Mississippi State Board 

of Health, who were interviewed regarding their diet, 

including the consumption of clay or starch. All of 

the women were from the lowest economic and 

educational level in the area, and 92% were Black. Of 

the Black women, 27% reported clay-eating and 

41% starch-eating. In the group of White women, 7 

and 10% reporting clay- and starch-eating, 

respectively. The amount of starch eaten ranged from 

2−3 small lumps to 3 boxes (24 ounces) per day. The 

amount of clay eaten ranged from one tablespoon to 

one cup per day. 

5.3.4.3.	 Cooper (1957)—Pica: A Survey of the 

Historical Literature as Well as Reports 

From the Fields of Veterinary Medicine 

and Anthropology, the Present Study of 

Pica in Young Children, and a Discussion 

of Its Pediatric and Psychological 

Implications 

Cooper (1957) conducted a non-randomized 

survey response study in the 1950s of children age 

7 months or older referred to a Baltimore, Maryland 

mental hygiene clinic. For 86 out of 784 children 

studied, parents or caretakers gave positive responses 

to the question, “Does your child have a habit, or did 

he ever have a habit, of eating dirt, plaster, ashes, 

etc.?” and identified dirt, or dirt combined with other 

substances, as the substance ingested. Cooper (1957) 

described a pattern of pica behavior, including 

ingesting substances other than soil, being most 

common between ages 2 and 4 or 5 years, with one of 

the 86 children ingesting clay at age 10 years and 

9 months. 

5.3.4.4.	 Barltrop (1966)—The Prevalence of Pica 

Barltrop (1966) conducted a randomized survey 

response study of children born in Boston, 

Massachusetts between 1958 and 1962, inclusive, 

whose parents resided in Boston and who were 

neither illegitimate nor adopted. A stratified random 

subsample of 500 of these children was contacted for 

in-person caregiver interviews, in which a total of 

186 families (37%) participated. A separate stratified 

subsample of 1,000 children was selected for a 

mailed survey, in which 277 (28%) of the families 

participated. Interview-obtained data regarding 

care-giver reports of pica (in this study is defined as 

placing non-food items in the mouth and swallowing 

them) behavior in all children ages 1 to 6 years in the 

186 families (N = 439) indicated 19 had ingested dirt 

(defined as yard dirt, house dust, plant-pot soil, 

pebbles, ashes, cigarette ash, glass fragments, lint, 

and hair combings) in the preceding 14 days. It does 

not appear that these data were corrected for unequal 

selection probability in the stratified random sample, 

nor were they corrected for non-response bias. 

Interviews were conducted in the March/April time 

frame, presumably in 1964. Mail-survey obtained 

data regarding caregiver reports of pica in the 

preceding 14 days indicated that 39 of 277 children 

had ingested dirt, presumably using the same 

definition as above. Barltrop (1966) mentions several 

possible limitations of the study, including nonparticipation bias and respondents’ memory, or recall, 

effects. 

5.3.4.5.	 Bruhn and Pangborn (1971)—Reported 

Incidence of Pica Among Migrant Families 

Bruhn and Pangborn (1971) conducted a survey 

among 91 low income families of migrant 

agricultural workers in California in May through 

August 1969. Families were of Mexican descent in 

two labor camps (Madison camp, 10 miles west of 

Woodland, and Davis camp, 10 miles east of Davis) 

and were “Anglo” families at the Harney Lane camp 

17 miles north of Stockton. Participation was 34 of 

50 families at the Madison camp, 31 of 50 families at 

the Davis camp, and 26 of 26 families at the Harney 

Lane camp. Respondents for the studied families 

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(primarily wives) gave positive responses to openended questions such as “Do you know of anyone 

who eats dirt or laundry starch?” Bruhn and 

Pangborn (1971) apparently asked a modified version 

of this question pertaining to the respondents’ own or 

relatives’ families. They reported 18% (12 of 65) of 

Mexican families’ respondents as giving positive 

responses for consumption of “dirt” among children 

within the Mexican respondents’ own or relatives’ 

families. They reported 42% (11 of 26) of “Anglo” 

families’ respondents as giving positive responses for 

consumption of “dirt” among children within the 

Anglo respondents’ own or relatives’ families. 

5.3.4.6.	 Robischon (1971)—Pica Practice and 

Other Hand-Mouth Behavior and 

Children’s Developmental Level 

A survey response sample of 19- to 24-month old 

children examined at an urban well-child clinic in the 

late 1960s or 1970 in an unspecified location 

indicated that 48 of the 130 children whose 

caregivers were interviewed, exhibited pica behavior 

(defined as “ate non-edibles more than once a 

week”). The specific substances eaten were reported 

for 30 of the 48 children. All except 2 of the 30 

children habitually ate more than one non-edible 

substance. The soil and dust-like substances reported 

as eaten by these 30 children were: ashes (17), 

“earth” (5), dust (3), fuzz from rugs (2), clay (1), and 

pebbles/stones (1). Caregivers for some of the study 

subjects (between 0 and 52 of the 130 subjects, exact 

number not specified) reported that the children “ate 

non-edibles less than once a week.” 

5.3.4.7.	 Bronstein and Dollar (1974)—Pica in 

Pregnancy 

The frequency and effects of pica behavior was 

investigated by Bronstein and Dollar (1974) in 

410 pregnant, low-income women from both urban 

(N = 201) and rural (N = 209) areas in Georgia. The 

women selected were part of the Nutrition 

Demonstration Project, a study investigating the 

effect of nutrition on the outcome of the pregnancy, 

conducted at the Eugene Talmadge Memorial 

Hospital and University Hospital in Augusta, 

Georgia. During their initial prenatal visit, each 

patient was interviewed by a nutrition counselor who 

questioned her food frequency, social and dietary 

history, and the presence of pica. Patients were 

categorized by age, parity, and place of residence 

(rural or urban). 

Of the 410 women interviewed, 65 (16%) stated 

that they practiced pica. A variety of substances were 

ingested, with laundry starch being the most 

common. There was no significant difference in the 

practice of pica between rural and urban women, 

although older rural women (20−35 years) showed a 

greater tendency to practice pica than younger rural 

or urban women (<20 years). The number of previous 

pregnancies did not influence the practice of pica. 

The authors noted that the frequency of pica among 

rural patients had declined from a previous study 

conducted 8 years earlier, and attributed the reduction 

to a program of intensified nutrition education and 

counseling provided in the area. No specific 

information on the amount of pica substances 

ingested was provided by this study, and the data are 

more than 30 years old. 

5.3.4.8.	 Hook (1978)—Dietary Cravings and 

Aversions During Pregnancy 

Hook (1978) conducted interviews of 250 women 

who had each delivered a live infant at two New York 

hospitals; the interviews took place in 1975. The 

mothers were first asked about any differences in 

consumption of seven beverages during their 

pregnancy, and the reasons for any changes. They 

were then asked, without mentioning specific items, 

about any cravings or aversions for other foods or 

non-food items that may have developed at any time 

during their pregnancy. 

Non-food items reportedly ingested during 

pregnancy were ice, reported by three women, and 

chalk from a river clay bank, reported by one woman. 

In addition, one woman reported an aversion to 

non-food items (specific non-food item not reported). 

No quantity data were provided by this study. 

5.3.4.9.	 Binder et al. (1986)—Estimating Soil 

Ingestion: The Use of Tracer Elements in 

Estimating the Amount of Soil Ingested by 

Young Children 

Binder et al. (1986) used a tracer technique 

modified from a method previously used to measure 

soil ingestion among grazing animals to study the 

ingestion of soil among children 1 to 3 years of age 

who wore diapers. The children were studied during 

the summer of 1984 as part of a larger study of 

residents living near a lead smelter in East Helena, 

Montana. Soiled diapers were collected over a 3-day 

period from 65 children (42 males and 23 females), 

and composited samples of soil were obtained from 

the children's yards. Both excreta and soil samples 

were analyzed for aluminum, silicon, and titanium. 

These elements were found in soil but were thought 

to be poorly absorbed in the gut and to have been 

present in the diet only in limited quantities. Excreta 

measurements were obtained for 59 of the children. 

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Soil ingestion by each child was estimated on the 

basis of each of the three tracer elements using a 

standard assumed fecal dry weight of 15 g/day, and 

the following equation (5-2): 

fi ,e × Fi Ti,e = (Eqn. 5-2) 

Si,e 

where: 

Ti,e = estimated soil ingestion for child i 

based on element e (g/day), 

fi,e = concentration of element e in fecal 

sample of child i (mg/g), 

Fi = fecal dry weight (g/day), and 

Si,e = concentration of element e in child i's 

yard soil (mg/g). 

The analysis assumed that (1) the tracer elements 

were neither lost nor introduced during sample 

processing; (2) the soil ingested by children 

originates primarily from their own yards; and 

(3) that absorption of the tracer elements by children 

occurred in only small amounts. The study did not 

distinguish between ingestion of soil and house dust, 

nor did it account for the presence of the tracer 

elements in ingested foods or medicines. 

The arithmetic mean quantity of soil ingested by 

the children in the Binder et al. (1986) study was 

estimated to be 181 mg/day (range 25 to 1,324) based 

on the aluminum tracer; 184 mg/day (range 31 to 

799) based on the silicon tracer; and 1,834 mg/day 

(range 4 to 17,076) based on the titanium tracer (see 

Table 5-15). The overall mean soil ingestion estimate, 

based on the minimum of the three individual tracer 

estimates for each child, was 108 mg/day (range 4 to 

708). The median values were 121 mg/day, 

136 mg/day, and 618 mg/day for aluminum, silicon, 

and titanium, respectively. The 95th percentile values 

for aluminum, silicon, and titanium were 584 mg/day, 

578 mg/day, and 9,590 mg/day, respectively. The 95th 

percentile value based on the minimum of the three 

individual tracer estimates for each child was 

386 mg/day. 

The authors were not able to explain the 

difference between the results for titanium and for the 

other two elements, but they speculated that 

unrecognized sources of titanium in the diet or in the 

laboratory processing of stool samples may have 

accounted for the increased levels. The frequency 

distribution graph of soil ingestion estimates based on 

titanium shows that a group of 21 children had 

particularly high titanium values 

(i.e., >1,000 mg/day). The remainder of the children 

showed titanium ingestion estimates at lower levels, 

with a distribution more comparable to that of the 

other elements. 

5.3.4.10.Clausing et al. (1987)—A Method for 

Estimating Soil Ingestion by Children 

Clausing et al. (1987) conducted a soil ingestion 

study with Dutch children using a tracer element 

methodology. Clausing et al. (1987) measured 

aluminum, titanium, and acid-insoluble residue 

contents of fecal samples from children aged 2 to 

4 years attending a nursery school, and for samples of 

playground dirt at that school. Over a 5-day period, 

27 daily fecal samples were obtained for 18 children. 

Using the average soil concentrations present at the 

school, and assuming a standard fecal dry weight of 

10 g/day, soil ingestion was estimated for each tracer. 

Six hospitalized, bedridden children served as a 

control group, representing children who had very 

limited access to soil; eight daily fecal samples were 

collected from the hospitalized children. 

Without correcting for the tracer element 

contribution from background sources, represented 

by the hospitalized children’s soil ingestion estimates, 

the aluminum-based soil ingestion estimates for the 

school children in this study ranged from 23 to 

979 mg/day, the AIR-based estimates ranged from 48 

to 362 mg/day, and the titanium-based estimates 

ranged from 64 to 11,620 mg/day. As in the Binder et 

al. (1986) study, a fraction of the children (6/18) 

showed titanium values above 1,000 mg/day, with 

most of the remaining children showing substantially 

lower values. Calculating an arithmetic mean 

quantity of soil ingested based on each fecal sample 

yielded 230 mg/day for aluminum; 129 mg/day for 

AIR, and 1,430 mg/day for titanium (see Table 5-16). 

Based on the LTM and averaging across each fecal 

sample, the arithmetic mean soil ingestion was 

estimated to be 105 mg/day with a population 

standard deviation of 67 mg/day (range 23 to 

362 mg/day); geometric mean soil ingestion was 

estimated to be 90 mg/day. Use of the LTM assumed 

that "the maximum amount of soil ingested 

corresponded with the lowest estimate from the three 

tracers" (Clausing et al., 1987). 

The hospitalized children’s arithmetic mean 

aluminum-based soil ingestion estimate was 

56 mg/day; titanium-based estimates included 

estimates for three of the six children that exceeded 

1,000 mg/day, with the remaining three children in 

the range of 28 to 58 mg/day (see Table 5-17). AIR 

measurements were not reported for the hospitalized 

children. Using the LTM method, the mean soil 

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ingestion rate was estimated to be 49 mg/day with a 

population standard deviation of 22 mg/day (range 26 

to 84 mg/day). The geometric mean soil ingestion 

rate was 45 mg/day. The hospitalized children’s data 

suggested a major non-soil source of titanium for 

some children and a background non-soil source of 

aluminum. However, conditions specific to 

hospitalization (e.g., medications) were not 

considered. 

Clausing et al. (1987) estimated that the average 

soil ingestion of the nursery school children was 

56 mg/day, after subtracting the mean LTM soil 

ingestion for the hospitalized children (49 mg/day) 

from the nursery school children’s mean LTM soil 

ingestion (105 mg/day), to account for background 

tracer intake from dietary and other non-soil sources. 

5.3.4.11.Calabrese et al. (1990)—Preliminary Adult 

Soil Ingestion Estimates: Results of a Pilot 

Study 

Calabrese et al. (1990) studied six adults to 

evaluate the extent to which they ingest soil. This 

adult study was originally part of the children soil 

ingestion study (Calabrese et al., 1989) and was used 

to validate part of the analytical methodology used in 

the children’s study. The participants were six healthy 

adults, three males and three females, 25−41 years 

old. Each volunteer ingested one empty gelatin 

capsule at breakfast and one at dinner Monday, 

Tuesday, and Wednesday during the first week of the 

study. During the second week, they ingested 

50 milligrams of sterilized soil within a gelatin 

capsule at breakfast and at dinner (a total of 

100 milligrams of sterilized soil per day) for 3 days. 

For the third week, the participants ingested 

250 milligrams of sterilized soil in a gelatin capsule 

at breakfast and at dinner (a total of 500 milligrams 

of soil per day) during the 3 days. Duplicate meal 

samples (food and beverage) were collected from the 

six adults. The sample included all foods ingested 

from breakfast Monday, through the evening meal 

Wednesday during each of the 3 weeks. In addition, 

all medications and vitamins ingested by the adults 

were collected. Total excretory output was collected 

from Monday noon through Friday midnight over 

3 consecutive weeks. 

Data obtained from the first week, when empty 

gelatin capsules were ingested, were used to estimate 

soil intake by adults. On the basis of recovery values, 

Al, Si, Y, and Zr were considered the most valid 

tracers. The mean values for these four tracers were: 

Al, 110 milligrams; Si, 30 milligrams; Y, 

63 milligrams; and Zr, 134 mg. A limitation of this 

study is the small sample size. 

5.3.4.12.Cooksey (1995)—Pica and Olfactory 

Craving of Pregnancy: How Deep Are the 

Secrets? 

Postpartum interviews were conducted between 

1992 and 1994 of 300 women at a mid-western 

hospital, to document their experiences of pica 

behavior. The majority of women were Black and 

low-income, and ranged in age from 13 to 42 years. 

In addition to questions regarding nutrition, each 

woman was asked if during her pregnancy she 

experienced a craving to eat ice or other things that 

are not food. 

Of the 300 women, 194 (65%) described 

ingesting one or more pica substances during their 

pregnancy, and the majority (78%) ate ice/freezer 

frost alone or in addition to other pica substances. 

Reported quantities of items ingested on a daily basis 

were three to four 8-pound bags of ice, two to three 

boxes of cornstarch, two cans of baking powder, one 

cereal bowl of dirt, five quarts of freezer frost, and 

one large can of powdered cleanser. 

5.3.4.13.Smulian et al. (1995)—Pica in a Rural 

Obstetric Population 

In 1992, Smulian et al. (1995) conducted a survey 

response study of pica in a convenience sample of 

125 pregnant women in Muscogee County, Georgia, 

who ranged in age from 12 to 37 years. Of these, 73 

were Black, 47 were White, 4 were Hispanic, and 1 

was Asian. Interviews were conducted at the time of 

the first prenatal visit, using non-directive 

questionnaires to obtain information regarding 

substances ingested as well as patterns of pica 

behavior and influences on pica behavior. Only 

women ingesting non-food items were considered to 

have pica. Ingestion of ice was included as a pica 

behavior only if the ice was reported to be ingested 

multiple times per day, if the ice was purchased 

solely for ingestion, or if the ice was obtained from 

an unusual source such as freezer frost. 

The overall prevalence of pica behavior in this 

study was 14.4% (18 of 125 women), and was 

highest among Black women (17.8%). There was no 

significant difference between groups with respect to 

age, race, weight, or gestational age at the time of 

enrollment in the study. The most common form of 

pica was ice eating (pagophagia), reported by 44.4% 

of the patients. Nine of the women reported 

information on the frequency and amount of the 

substances they were ingesting. Of these women, 

66.7% reported daily consumption and 33.3% 

reported pica behavior three times per week. Soap, 

paint chips, or burnt matches were reportedly 

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ingested 3 days per week. One patient ate ice 

60 times per week. Women who ate dirt or clay 

reported ingesting 0.5−1 pound per week. The largest 

amount of ice consumed was five pounds per day. 

5.3.4.14.Grigsby et al. (1999)—Chalk Eating in 

Middle Georgia: A Culture-Bound 

Syndrome of Pica? 

Grigsby et al. (1999) investigated the ingestion of 

kaolin, also known as white dirt, chalk, or white clay, 

in the central Georgia Piedmont area as a 

culture-bound syndrome. A total of 21 individuals 

who consumed kaolin at the time or had a history of 

consuming kaolin were interviewed, using a 

seven-item, one-page interview protocol. All of those 

interviewed were Black, ranging in age from 28 to 

88 years (mean age of 46.5 years), and all were 

female except for one. 

Reasons for eating kaolin included liking the 

taste, being pregnant, craving it, and to gain weight. 

Eight respondents indicated that they obtained the 

kaolin from others, five reported getting it directly 

from the earth, four purchased it from a store, and 

two obtained it from a kaolin pit mine. The majority 

of the respondents reported that they liked the taste 

and feel of the kaolin as they ate it. Only three 

individuals reported knowing either males or White 

persons who consumed kaolin. Most individuals were 

not forthcoming in discussing their ingestion of 

kaolin and recognized that their behavior was 

unusual. 

The study suggests that kaolin-eating is primarily 

practiced by Black women who were introduced to 

the behavior by family members or friends, during 

childhood or pregnancy. The authors concluded that 

kaolin ingestion is a culturally-transmitted form of 

pica, not associated with any other psychopathology. 

Although information on kaolin eating habits and 

attitudes were provided by this study, no quantitative 

information on consumption was included, and the 

sample population was small and non-random. 

5.3.4.15.Ward and Kutner (1999)—Reported Pica 

Behavior in a Sample of Incident Dialysis 

Patients 

Structured interviews were conducted with a 

sample of 226 dialysis patients in the metropolitan 

Atlanta, Georgia area from September 1996 to 

September 1997. Interviewers were trained in 

nutrition data collection methods, and patients also 

received a 3-day diet diary that they were asked to 

complete and return by mail. If a subject reported a 

strong past or current food or non-food craving, a 

separate form was used to collect information to 

determine if this was a pica behavior. 

Pica behavior was reported by 37 of the dialysis 

patients studied (16%), and most of these patients (31 

of 37) reported that they were currently practicing 

some form of pica behavior. The patients’ race and 

sex were significantly associated with pica behavior, 

with Black patients and women making up 86% and 

84% of those reporting pica, respectively. Those 

reporting pica behavior were also younger than the 

remainder of the sample, and approximately 2 

described a persistent craving for ice. Other pica 

items reportedly consumed included starch, dirt, 

flour, or aspirin. 

5.3.4.16.Simpson et al. (2000)—Pica During 

Pregnancy in Low-Income Women Born in 

Mexico 

Simpson et al. (2000) interviewed 

225 Mexican-born women, aged 18−42 years (mean 

age of 25 years), using a questionnaire administered 

in Spanish. Subjects were recruited by approaching 

women in medical facilities that served low-income 

populations in the cities of Ensenada, Mexico 

(N = 75), and Santa Ana, Bakersfield, and East Los 

Angeles, California (N = 150). Criteria for 

participation were that the women had to be 

Mexican-born, speak Spanish as their primary 

language, and be pregnant or have been pregnant 

within the past year. Only data for U.S. women are 

included in this handbook. 

Pica behavior was reported in 31% of the women 

interviewed in the United States. Table 5-18 shows 

the items ingested and the number of women 

reporting the pica behavior. Of the items ingested, 

only ice was said to be routinely eaten outside of 

pregnancy, and was only reported by U.S. women, 

probably because none of the low-income women 

interviewed in Mexico owned a refrigerator. 

Removing the 12 women who reported eating only 

ice from the survey lowers the percentage of U.S. 

women who reported pica behavior to 23%. Women 

said they engaged in pica behavior because of the 

taste, smell, or texture of the items, for medicinal 

purposes, or because of advice from someone, and 

one woman reported eating clay for religious reasons. 

Magnesium carbonate, a pica item not found to be 

previously reported in the literature, was reportedly 

consumed by 17% of women. The amount of 

magnesium carbonate ingested ranged from a quarter 

of a block to five blocks per day; the blocks were 

approximately the size of a 35-mm film box. No 

specific quantity information on the amounts of pica 

substances ingested was provided in the study. 

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5.3.4.17.Obialo et al. (2001)—Clay Pica Has No 

Hematologic or Metabolic Correlate to 

Chronic Hemodialysis Patients 

A total of 138 dialysis patients at the Morehouse 

School of Medicine, Atlanta, Georgia, were 

interviewed about their unusual cravings or food 

habits. The patients were Black and ranged in age 

from 37 to 78 years. 

Thirty of the patients (22%) reported some form 

of pica behavior, while 13 patients (9.4%) reported 

clay pica. The patients with clay pica reported daily 

consumption of 225−450 grams of clay. 

5.3.4.18.Klitzman et al. (2002)—Lead Poisoning 

Among Pregnant Women in New York 

City: Risk Factors and Screening Practices 

Klitzman et al. (2002) interviewed 33 pregnant 

women whose blood lead levels were >20 μg/dL as 

reported to the New York City Department of Health 

between 1996 and 1999. The median age of the 

women was 24 years (range of 15 to 43 years), and 

the majority were foreign born. The women were 

interviewed regarding their work, reproductive and 

lead exposure history. A home visit was also 

conducted and included a visual inspection and a 

colorimetric swab test; consumable items suspected 

to contain lead were sent to a laboratory for analysis. 

There were 13 women (39%) who reported pica 

behavior during their current pregnancies. Of these, 

10 reported eating soil, dirt or clay, 2 reported 

pulverizing and eating pottery, and 1 reported eating 

soap. One of the women reported eating 

approximately one quart of dirt daily from her 

backyard for the past three months. No other quantity 

data were reported. 

5.3.5. Relevant Studies of Secondary Analysis 

The secondary analysis literature on soil and dust 

ingestion rates gives important insights into 

methodological strengths and limitations. The tracer 

element studies described in this section are grouped 

to some extent according to methodological issues 

associated with the tracer element methodology. 

These methodological issues include attempting to 

determine the origins of apparent positive and 

negative bias in the methodologies, including: food 

input/fecal output misalignment; missed fecal 

samples; assumptions about children’s fecal weights; 

particle sizes of, and relative contributions of soils 

and dusts to total soil and dust ingestion; and 

attempts to identify a “best” tracer element or 

combination of tracer elements. Potential error from 

using short-term studies’ estimates for long term soil 

and dust ingestion behavior estimates is also 

discussed. 

5.3.5.1.	 Stanek and Calabrese (1995a)—Daily 

Estimates of Soil Ingestion in Children 

Stanek and Calabrese (1995a) presented a 

methodology that links the physical passage of food 

and fecal samples to construct daily soil ingestion 

estimates from daily food and fecal trace-element 

concentrations. Soil ingestion data for children 

obtained from the Amherst study (Calabrese et al., 

1989) were reanalyzed by Stanek and Calabrese 

(1995a). A lag period of 28 hours between food 

intake and fecal output was assumed for all 

respondents. Day 1 for the food sample corresponded 

to the 24-hour period from midnight on Sunday to 

midnight on Monday of a study week; day 1 of the 

fecal sample corresponded to the 24-hour period from 

noon on Monday to noon on Tuesday. Based on these 

definitions, the food soil equivalent was subtracted 

from the fecal soil equivalent to obtain an estimate of 

soil ingestion for a trace element. A daily overall 

ingestion estimate was constructed for each child as 

the median of trace element values remaining after 

tracers falling outside of a defined range around the 

overall median were excluded. 

Table 5-19 presents adjusted estimates, modified 

according to the input/output misalignment 

correction, of mean daily soil ingestion per child 

(mg/day) for the 64 study participants. The approach 

adopted in this paper led to changes in ingestion 

estimates from those presented in Calabrese et al. 

(1989). 

Estimates of children’s soil ingestion projected 

over a period of 365 days were derived by fitting 

lognormal distributions to the overall daily soil 

ingestion estimates using estimates modified 

according to the input/output misalignment correction 

(see Table 5-20). The estimated median value of the 

64 respondents' daily soil ingestion averaged over a 

year was 75 mg/day, while the 95th percentile was 

1,751 mg/day. In developing the 365-day soil 

ingestion estimates, data that were obtained over a 

short period of time (as is the case with all available 

soil ingestion studies) were extrapolated over a year. 

The 2-week study period may not reflect variability 

in tracer element ingestion over a year. While Stanek 

and Calabrese (1995a) attempted to address this 

through modeling of the long term ingestion, new 

uncertainties were introduced through the parametric 

modeling of the limited subject day data. 

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5.3.5.2.	 Calabrese and Stanek (1992a)—What 

Proportion of Household Dust is Derived 

From Outdoor Soil? 

Calabrese and Stanek (1992a) estimated the 

amount of outdoor soil in indoor dust using statistical 

modeling. The model used soil and dust data from the 

60 households that participated in the Calabrese et al. 

(1989) study, by preparing scatter plots of each 

tracer’s concentration in soil versus dust. Correlation 

analysis of the scatter plots was performed. The 

scatter plots showed little evidence of a consistent 

relationship between outdoor soil and indoor dust 

concentrations. The model estimated the proportion 

of outdoor soil in indoor dust using the simplifying 

assumption that the following variables were 

constants in all houses: the amount of dust produced 

every day from both indoor and outdoor sources; the 

proportion of indoor dust due to outdoor soil; and the 

concentration of the tracer element in dust produced 

from indoor sources. Using these assumptions, the 

model predicted that 31.3% by weight of indoor dust 

came from outdoor soil. This model was then used to 

adjust the soil ingestion estimates from Calabrese et 

al. (1989). 

5.3.5.3.	 Calabrese et al. (1996)—Methodology to 

Estimate the Amount and Particle Size of 

Soil Ingested by Children: Implications for 

Exposure Assessment at Waste Sites 

Calabrese et al. (1996) examined the hypothesis 

that one cause of the variation between tracers seen in 

soil ingestion studies could be related to differences 

in soil tracer concentrations by particle size. This 

study, published prior to the Calabrese et al. (1997b) 

primary analysis study results, used laboratory 

analytical results for the Anaconda, Montana soil’s 

tracer concentration after it had been sieved to a 

particle size of <250 μm in diameter [it was sieved 

to <2 mm soil particle size in Calabrese et al. 

(1997b)]. The smaller particle size was examined 

based on the assumption that children principally 

ingest soil of small particle size adhering to fingertips 

and under fingernails. For five of the tracers used in 

the original study (aluminum, silicon, titanium, 

yttrium, and zirconium), soil concentration was not 

changed by particle size. However, the soil 

concentrations of three tracers (lanthanum, cerium, 

and neodymium) were increased 2- to 4-fold at the 

smaller soil particle size. Soil ingestion estimates for 

these three tracers were decreased by approximately 

60% at the 95th percentile compared to the Calabrese 

et al. (1997b) results. 

5.3.5.4.	 Stanek et al. (1999)—Soil Ingestion 

Estimates for Children in Anaconda Using 

Trace Element Concentrations in Different 

Particle Size Fractions 

Stanek et al. (1999) extended the findings from 

Calabrese et al. (1996) by quantifying trace element 

concentrations in soil based on sieving to particle 

sizes of 100−250 μm and to particle sizes of 53 to 

<100 μm. The earlier study (Calabrese et al., 1996) 

used particle sizes of 0−2 μm and 1−250 μm. This 

study used the data from soil concentrations from the 

Anaconda, Montana site reported by Calabrese et al. 

(1997b). Results of the study indicated that soil 

concentrations of aluminum, silicon, and titanium did 

not increase at the two finer particle size ranges 

measured. However, soil concentrations of cerium, 

lanthanum, and neodymium increased by a factor of 

2.5 to 4.0 in the 100−250 μm particle size range 

when compared with the 0−2 μm particle size range. 

There was not a significant increase in concentration 

in the 53−100 μm particle size range. 

5.3.5.5.	 Stanek and Calabrese (2000)—Daily Soil 

Ingestion Estimates for Children at a 

Superfund Site 

Stanek and Calabrese (2000) reanalyzed the soil 

ingestion data from the Anaconda study. The authors 

assumed a lognormal distribution for the soil 

ingestion estimates in the Anaconda study to predict 

average soil ingestion for children over a longer time 

period. Using “best linear unbiased predictors,” the 

authors predicted 95th percentile soil ingestion values 

over time periods of 7 days, 30 days, 90 days, and 

365 days. The 95th percentile soil ingestion values 

were predicted to be 133 mg/day over 7 days, 

112 mg/day over 30 days, 108 mg/day over 90 days, 

and 106 mg/day over 365 days. Based on this 

analysis, estimates of the distribution of longer term 

average soil ingestion are expected to be narrower, 

with the 95th percentile estimates being as much as 

25% lower (Stanek and Calabrese, 2000). 

5.3.5.6.	 Stanek et al. (2001a)—Biasing Factors for 

Simple Soil Ingestion Estimates in Mass 

Balance Studies of Soil Ingestion 

In order to identify and evaluate biasing factors 

for soil ingestion estimates, the authors developed a 

simulation model based on data from previous soil 

ingestion studies. The soil ingestion data used in this 

model were taken from Calabrese et al. (1989) (the 

Amherst study); Davis et al. (1990) (southeastern 

Washington State); Calabrese et al. (1997b) (the 

Anaconda study); and Calabrese et al. (1997a) 

(soil-pica in Massachusetts), and relied only on the 

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aluminum and silicon trace element estimates 

provided in these studies. 

Of the biasing factors explored, the impact of 

study duration was the most striking, with a positive 

bias of more than 100% for 95th percentile estimates 

in a 4-day tracer element study. A smaller bias was 

observed for the impact of absorption of trace 

elements from food. Although the trace elements 

selected for use in these studies are believed to have 

low absorption, whatever amount is not accounted for 

will result in an underestimation of the soil ingestion 

distribution. In these simulations, the absorption of 

trace elements from food of up to 30% was shown to 

negatively bias the estimated soil ingestion 

distribution by less than 20 mg/day. No biasing effect 

was found for misidentifying play areas for soil 

sampling (i.e., ingested soil from a yard other than 

the subject’s yard). 

5.3.5.7.	 Stanek et al. (2001b)—Soil Ingestion 

Distributions for Monte Carlo Risk 

Assessment in Children 

Stanek et al. (2001b) developed “best linear 

unbiased predictors” to reduce the biasing effect of 

short-term soil ingestion estimates. This study 

estimated the long-term average soil ingestion 

distribution using daily soil ingestion estimates from 

children who participated in the Anaconda, Montana 

study. In this long-term (annual) distribution, the soil 

ingestion estimates were: mean 31, median 24, 

75th percentile 42, 90th percentile 75, and 

95th percentile 91 mg/day. 

5.3.5.8.	 Von Lindern et al. (2003)—Assessing 

Remedial Effectiveness Through the Blood 

Lead: Soil/Dust Lead Relationship at the 

Bunker Hill Superfund Site in the Silver 

Valley of Idaho 

Similar to Hogan et al. (1998), von Lindern et al. 

(2003) used the IEUBK model to predict blood lead 

levels in a non-random sample of several hundred 

children ages 0−9 years in an area of northern Idaho 

from 1989−1998 during community-wide soil 

remediation. Von Lindern et al. (2003) used the 

IEUBK default soil and dust ingestion rates together 

with observed house dust/soil lead levels (and 

imputed values based on community soil and dust 

lead levels, when observations were missing). The 

authors compared the predicted blood lead levels 

with observed blood lead levels and found that the 

default IEUBK soil and dust ingestion rates and lead 

bioavailability value over-predicted blood lead levels, 

with the over-prediction decreasing as the community 

soil remediation progressed. The authors stated that 

the over-prediction may have been caused either by a 

default soil and dust ingestion that was too high, a 

default bioavailability value for lead that was too 

high, or some combination of the two. They also 

noted under-predictions for some children, for whom 

follow up interviews revealed exposures to lead 

sources not accounted for by the model, and noted 

that the study sample included many children with a 

short residence time within the community. 

Von Lindern et al. (2003) developed a statistical 

model that apportioned the contributions of 

community soils, yard soils of the residence, and 

house dust to lead intake; the models’ results 

suggested that community soils contributed more 

(50%) than neighborhood soils (28%) or yard soils 

(22%) to soil found in house dust of the studied 

children. 

5.3.5.9.	 Gavrelis et al. (2011)—An Analysis of the 

Proportion of the U.S. Population That 

Ingests Soil or Other Non-Food Substances 

Gavrelis et al. (2011) evaluated the prevalence of 

the U.S. population that ingests non-food substances 

such as soil, clay, starch, paint, or plaster. Data were 

compiled from the National Health and Nutrition 

Examination Survey (NHANES) collected from 

1971−1975 (NHANES I) and 1976−1980 

(NHANES II), which represent a complex, stratified, 

multistage, probability-cluster design and include 

nationwide probability samples of approximately 

21,000 and 25,000 study participants, respectively. 

NHANES I surveyed people aged 1 to 74 years and 

NHANES II surveyed those 6 months to 74 years. 

The study population included women of 

childbearing age, people with low income status, the 

elderly, and preschool children, who represented an 

oversampling of specific groups in the population 

that were believed to have high risks for malnutrition. 

The survey questions were demographic, 

socioeconomic, dietary, and health-related queries, 

and included specific questions regarding soil and 

non-food substance ingestion. Survey questions for 

children under 12 years asked whether they 

consumed non-food substances including dirt or clay, 

starch, paint or plaster, and other materials 

(NHANES I) or about consumption of clay, starch, 

paint or plaster, dirt, and other materials 

(NHANES II). For participants over 12 years of age, 

the survey questions asked only about consumption 

of dirt or clay, starch, and other materials 

(NHANES I) or about non-food substances including 

clay, starch, and other materials (NHANES II). Age 

groupings used in this analysis vary slightly from the 

age group categories established by U.S. EPA and 

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described in Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

Other demographic parameters included sex 

(including pregnant and non-pregnant females); race 

(White, Black, and other); geography (urban and 

rural, with “urban” defined as populations >2,500); 

income level (ranging from $0−$9,999 up 

to >$20,000, or not stated); and highest grade head of 

household (population under 18 years) or respondent 

(population >18 years) attended. For statistical 

analysis, frequency estimates were generated for the 

proportion of the total U.S. population that reported 

consumption of dirt, clay, starch, paint or plaster, or 

other materials “considered unusual” using the 

appropriate NCHS sampling weights and responses 

to the relevant questions in NHANES I and II. 

NHANES I and II were evaluated separately, because 

the data sets did not provide components of the 

weight variable separately (i.e., probability of 

selection, non-response adjustment weight, and 

post-stratification weight). 

Although the overall prevalence estimates were 

higher in NHANES I compared with NHANES II, 

similar patterns were generally observed across 

substance types and demographic groups studied. For 

NHANES I, the estimated prevalence of all non-food 

substance consumption in the United States for all 

ages combined was 2.5% (95% Confidence Interval 

[CI]: 2.2−2.9%), whereas for NHANES II, the 

estimated prevalence of all non-food substance 

consumption in the United States for all ages 

combined was 1.1% (95% CI: 1.0−1.2%). Table 5-21 

provides the prevalence estimates by type of 

substance consumed for all ages combined. By type 

of substance, the estimated prevalence was greatest 

for dirt and clay consumption and lowest for starch. 

Figure 5-1, Figure 5-2, and Figure 5-3, respectively, 

show the prevalence of non-food substance 

consumption by age, race, and income. The most 

notable differences were seen across age, race (Black 

versus White), and income groups. For both 

NHANES I and II, prevalence for the ingestion of all 

non-food substances decreased with increasing age, 

was higher among Blacks (5.7%; 95% CI: 4.4−7.0%) 

as compared to Whites (2.1%; 95% CI: 1.8−2.5%), 

and was inversely related to income level, with 

prevalence of non-food consumption decreasing as 

household income increased. The estimated 

prevalence of all non-food substances for the 1 to 

<3 year age category was at least twice that of the 

next oldest category (3 to <6 years). Prevalence 

estimates were 22.7% (95% CI: 20.1–25.3%) for the 

1 to <3 year age group based on NHANES I and 

12% based on NHANES II. In contrast, prevalence 

estimates for the >21 year age group was 0.7% 

(95% CI: 0.5–1.0%) and 0.4% (95% CI: 0.3–0.5%) 

for NHANES I and NHANES II, respectively. Other 

differences related to geography (i.e., urban and 

rural), highest grade level of the household head, and 

sex were less remarkable. For NHANES I, for 

example, the estimated prevalence of non-food 

substance consumption was only slightly higher 

among females (2.9%; CI: 2.3−3.5%) compared to 

males (2.1%; CI: 1.8−2.5%) of all ages. For pregnant 

females, prevalence estimates (2.5%; 

95% CI: 0.0−5.6%) for those 12 years and over were 

more than twice those for non-pregnant females 

(1.0%; 95% CI: 0.7−1.4%). 

5.4.	 LIMITATIONS OF STUDY 

METHODOLOGIES 

The three types of information needed to provide 

recommendations to exposure assessors on soil and 

dust ingestion rates among U.S. children include 

quantities of soil and dust ingested, frequency of high 

soil and dust ingestion episodes, and prevalence of 

high soil and dust ingesters. The methodologies 

provide different types of information: the tracer 

element, biokinetic model comparison, and activity 

pattern methodologies provide information on 

quantities of soil and dust ingested; the tracer element 

methodology provides limited evidence of the 

frequency of high soil ingestion episodes; the survey 

response methodology can shed light on prevalence 

of high soil ingesters and frequency of high soil 

ingestion episodes. The methodologies used to 

estimate soil and dust ingestion rates and prevalence 

of soil and dust ingestion behaviors have certain 

limitations, when used for the purpose of developing 

recommended soil and dust ingestion rates. These 

limitations may not have excluded specific studies 

from use in the development of recommended 

ingestion rates, but have been noted throughout this 

handbook. This section describes some of the known 

limitations, presents an evaluation of the current state 

of the science for U.S. children’s soil and dust 

ingestion rates, and describes how the limitations 

affect the confidence ratings given to the 

recommendations. 

5.4.1. Tracer Element Methodology 

This section describes some previously identified 

limitations of the tracer element methodology as it 

has been implemented by U.S. researchers, as well as 

additional potential limitations that have not been 

explored. Some of these same limitations would also 

apply to the Dutch and Jamaican studies that used a 

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control group of hospitalized children to account for 

dietary and pharmaceutical tracer intakes. 

Binder et al. (1986) described some of the major 

and obvious limitations of the early U.S. tracer 

element methodology as follows: 

[T]he algorithm assumes that children ingest 

predominantly soil from their own yards and 

that concentrations of elements in composite 

soil samples from front and back yards are 

representative of overall concentrations in the 

yards....children probably eat a combination of 

soil and dust; the algorithm used does not 

distinguish between soil and dust 

ingestion....fecal sample weights...were much 

lower than expected...the assumption that 

aluminum, silicon and titanium are not 

absorbed is not entirely true....dietary intake of 

aluminum, silicon and titanium is not 

negligible when compared with the potential 

intake of these elements from soil....Before 

accepting these estimates as true values of soil 

ingestion in toddlers, we need a better 

understanding of the metabolisms of 

aluminum, silicon and titanium in children, 

and the validity of the assumptions we made 

in our calculations should be explored further. 

The subsequent U.S. tracer element studies 

(Davis and Mirick, 2006; Calabrese et al., 1997b; 

Barnes, 1990; Davis et al., 1990; Calabrese et al., 

1989) made some progress in addressing some of the 

Binder et al. (1986) study’s stated limitations. 

Regarding the issue of non-yard 

(community-wide) soil as a source of ingested soil, 

one study (Barnes, 1990; Calabrese et al., 1989) 

addressed this issue to some extent, by including 

samples of children’s daycare center soil in the 

analysis. Calabrese et al. (1997b) attempted to 

address the issue by excluding children in daycare 

from the study sample frame. Homogeneity of 

community soils’ tracer element content would play a 

role in whether this issue is an important biasing 

factor for the tracer element studies’ estimates. Davis 

et al. (1990) evaluated community soils’ aluminum, 

silicon, and titanium content and found little variation 

among 101 yards throughout the three-city area. 

Stanek et al. (2001a) concluded that there was 

“minimal impact” on estimates of soil ingestion due 

to mis-specifying a child’s play area. 

Regarding the issue of soil and dust both 

contributing to measured tracer element quantities in 

excreta samples, the key U.S. tracer element studies 

all attempted to address the issue by including 

samples of household dust in the analysis, and in 

some cases estimates are presented in the published 

articles that adjust soil ingestion estimates on the 

basis of the measured tracer elements found in the 

household dust. The relationship between soil 

ingestion rates and indoor settled dust ingestion rates 

has been evaluated in some of the secondary studies 

(Calabrese and Stanek, 1992a). An issue similar to 

the community-wide soil exposures in the previous 

paragraph could also exist with community-wide 

indoor dust exposures (such as dust found in schools 

and community buildings occupied by study subjects 

during or prior to the study period). A portion of the 

community-wide indoor dust exposures (due to 

occupying daycare facilities) was addressed in the 

Calabrese et al. (1989) and Barnes (1990) studies, but 

not in the other three key tracer element studies. In 

addition, if the key studies’ vacuum cleaner collection 

method for household and daycare indoor settled dust 

samples influenced tracer element composition of 

indoor settled dust samples, the dust sample 

collection method would be another area of 

uncertainty with the key studies’ indoor dust related 

estimates. The survey response studies suggest that 

some young children may prefer ingesting dust to 

ingesting soil. The existing literature on soil versus 

dust sources of children’s lead exposure may provide 

useful information that has not yet been compiled for 

use in soil and dust ingestion recommendations. 

Regarding the issue of fecal sample weights and 

the related issue of missing fecal and urine samples, 

the key tracer element studies have varying strengths 

and limitations. The Calabrese et al. (1989) article 

stated that wipes and toilet paper were not collected 

by the researchers, and thus underestimates of fecal 

quantities may have occurred. Calabrese et al. (1989) 

stated that cotton cloth diapers were supplied for use 

during the study; commodes apparently were used to 

collect both feces and urine for those children who 

were not using diapers. Barnes (1990) described 

cellulose and polyester disposable diapers with 

significant variability in silicon and titanium content 

and suggested that children’s urine was not included 

in the analysis. Thus, it is unclear to what extent 

complete fecal and urine output was obtained, for 

each study subject. The Calabrese et al. (1997b) study 

did not describe missing fecal samples and did not 

state whether urinary tracer element quantities were 

used in the soil and dust ingestion estimates, but 

stated that wipes and toilet paper were not collected. 

Missing fecal samples may have resulted in negative 

bias in the estimates from both of these studies. Davis 

et al. (1990) and Davis and Mirick (2006) were 

limited to children who no longer wore diapers. 

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Missed fecal sample adjustments might affect those 

studies’ estimates in either a positive or negative 

direction, due to the assumptions the authors made 

regarding the quantities of feces and urine in missed 

samples. Adjustments for missing fecal and urine 

samples could introduce errors sufficient to cause 

negative estimates if missed samples were heavier 

than the collected samples used in the soil and dust 

ingestion estimate calculations. 

Regarding the issue of dietary intake, the key U.S. 

tracer element studies have all addressed dietary (and 

non-dietary, non-soil) intake by subtracting calculated 

estimates of these sources of tracer elements from 

excreta tracer element quantities, or by providing 

study subjects with personal hygiene products that 

were low in tracer element content. Applying the 

food and non-dietary, non-soil corrections required 

subtracting the tracer element contributions from 

these non-soil sources from the measured fecal/urine 

tracer element quantities. To perform this correction 

required assumptions to be made regarding the 

gastrointestinal transit time, or the time lag between 

inputs (food, non-dietary non-soil, and soil) and 

outputs (fecal and urine). The gastrointestinal transit 

time assumption introduced a new potential source of 

bias that some authors (Stanek and Calabrese, 1995a) 

called input/output misalignment or transit time error. 

Stanek and Calabrese (1995b) attempted to correct 

for this transit time error by using the BTM and 

focusing estimates on those tracers that had a low 

food/soil tracer concentration ratios. The lag time 

may also be a function of age. Davis et al. (1990) and 

Davis and Mirick (2006) assumed a 24-hour lag time 

in contrast to the 28-hour lag times used in Calabrese 

et al. (1989); Barnes (1990); and Calabrese et al. 

(1997b). ICRP (2003) suggested a lag time of 

37 hours for one year old children and 5 to 15 year 

old children. Stanek and Calabrese (1995a) describe a 

method designed to reduce bias from this error 

source. 

Regarding gastrointestinal absorption, the authors 

of three of the studies appeared to agree that the 

presence of silicon in urine represented evidence that 

silicon was being absorbed from the gastrointestinal 

tract (Davis and Mirick, 2006; Barnes, 1990; Davis et 

al., 1990; Calabrese et al., 1989). There was some 

evidence of aluminum absorption in Calabrese et al. 

(1989); Barnes (1990); Davis and Mirick (2006) 

stated that aluminum and titanium did not appear to 

have been absorbed, based on low urinary levels. 

Davis et al. (1990) stated that silicon appears to have 

been absorbed to a greater degree than aluminum and 

titanium, based on urine concentrations. 

Aside from the gastrointestinal absorption, lag 

time, and missed fecal sample issues, Davis and 

Mirick (2006) offered another possible explanation 

for the negative soil and dust ingestion rates 

estimated for some study participants. Negative 

values result when the tracer amount in food and 

medicine is greater than that in urine/fecal matter. 

Given that some analytical error may occur, any 

overestimation of tracer amounts in the food samples 

would be greater than an overestimation in 

urine/feces, since the food samples were many times 

heavier than the urine and fecal samples. 

Another limitation on accuracy of tracer elementbased estimates of soil and dust ingestion relates to 

inaccuracies inherent in environmental sampling and 

laboratory analytical techniques. The “percent 

recovery” of different tracer elements varies 

[according to validation of the study methodology 

performed with adults who swallowed gelatin 

capsules with known quantities of sterilized soil, as 

part of the Calabrese et al. (1997b; 1989) studies]. 

Estimates based on a particular tracer element with a 

lower or higher recovery than the expected 100% in 

any of the study samples would be influenced in 

either a positive or negative direction, depending on 

the recoveries in the various samples and their degree 

of deviation from 100% (Calabrese et al., 1989). 

Soil/dust size fractions, and digestion/extraction 

methods of sample analysis may be additional 

limitations. 

Davis et al. (1990) offered an assessment of the 

impact of swallowed toothpaste on the tracer-based 

estimates by adjusting estimates for those children 

whose caregivers reported that they had swallowed 

toothpaste. Davis et al. (1990) had supplied study 

children with toothpaste that had been pre-analyzed 

for its tracer element content, but it is not known to 

what extent the children actually used the supplied 

toothpaste. Similarly, Calabrese et al. (1997b; 1989) 

supplied children in the Amherst, Massachusetts and 

Anaconda, Montana studies with toothpaste 

containing low levels of most tracers, but it is unclear 

to what extent those children used the supplied 

toothpaste. 

Other research suggests additional possible 

limitations that have not yet been explored. First, 

lymph tissue structures in the gastrointestinal tract 

might serve as reservoirs for titanium dioxide food 

additives and soil particles, which could bias 

estimates either upward or downward depending on 

tracers’ entrapment within, or release from, these 

reservoirs during the study period (ICRP, 2003; 

Powell et al., 1996; Shepherd et al., 1987). Second, 

gastrointestinal uptake of silicon may have occurred, 

which could bias those estimates downward. 

Evidence of silicon’s role in bone formation (Carlisle, 

1980) supported by newer research on dietary silicon 

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uptake (Jugdaohsingh et al., 2002); Van Dyck et al. 

(2000) suggests a possible negative bias in the 

silicon-based soil ingestion estimates, depending on 

the quantities of silicon absorbed by growing 

children. Third, regarding the potential for swallowed 

toothpaste to bias soil ingestion estimates upward, 

commercially available toothpaste may contain 

quantities of titanium and perhaps silicon and 

aluminum in the range that could be expected to 

affect the soil and dust ingestion estimates. Fourth, 

for those children who drank bottled or tap water 

during the study period, and did not include those 

drinking water samples in their duplicate food 

samples, slight upward bias may exist in some of the 

estimates for those children, since drinking water 

may contain small, but relevant, quantities of silicon 

and potentially other tracer elements. Fifth, the tracer 

element studies conducted to date have not explored 

the impact of soil properties’ influence on toxicant 

uptake or excretion within the gastrointestinal tract. 

Nutrition researchers investigating influence of clay 

geophagy behavior on human nutrition have begun 

using in vitro models of the human digestion 

(Dominy et al., 2004; Hooda et al., 2004). A recent 

review (Wilson, 2003) covers a wide range of 

geophagy research in humans and various hypotheses 

proposed to explain soil ingestion behaviors, with 

emphasis on the soil properties of geophagy 

materials. 

5.4.2. Biokinetic Model Comparison Methodology 

It is possible that the IEUBK biokinetic model 

comparison methodology contained sources of both 

positive and negative bias, like the tracer element 

studies, and that the net impact of the competing 

biases was in either the positive or negative direction. 

U.S. EPA’s judgment about the major sources of bias 

in biokinetic model comparison studies is that there 

may be several significant sources of bias. The first 

source of potential bias was the possibility that the 

biokinetic model failed to account for sources of lead 

exposure that are important for certain children. For 

these children, the model might either under-predict, 

or accurately predict, blood lead levels compared to 

actual measured lead levels. However, this result may 

actually mean that the default assumed lead intake 

rates via either soil and dust ingestion, or another 

lead source that is accounted for by the model, are 

too high. A second source of potential bias was use of 

the biokinetic model for predicting blood lead levels 

in children who have not spent a significant amount 

of time in the areas characterized as the main sources 

of environmental lead exposure. Modeling this 

population could result in either upward or downward 

biases in predicted blood lead levels. Comparing 

upward-biased predictions with actual measured 

blood lead levels and finding a relatively good match 

could lead to inferences that the model’s default soil 

and dust ingestion rates are accurate, when in fact the 

children’s soil and dust ingestion rates, or some other 

lead source, were actually higher than the default 

assumption. A third source of potential bias was the 

assumption within the model itself regarding the 

biokinetics of absorbed lead, which could result in 

either positively or negatively biased predictions and 

the same kinds of incorrect inferences as the second 

source of potential bias. 

In addition, there was no extensive sensitivity 

analysis. The calibration step used to fix model 

parameters limits the degree that most parameters can 

reasonably be varied. Second, the IEUBK model was 

not designed to predict blood lead levels greater than 

25−30 μg/dL; there are few data to develop such 

predictions and less to validate them. If there are sitespecific data that indicate soil ingestion rates (or 

other ingestion/intake rates) are higher than the 

defaults on average (not for specific children), the 

site-specific data should be considered. U.S. EPA 

considers the default IEUBK value of 30% 

reasonable for most data sets/sites. Bioavailability 

has been assayed for soils similar to those in the 

calibration step and the empirical comparison data 

sets; 30% was used in the calibration step, and is 

therefore recommended for similar sites. The default 

provides a reasonable substitute when there are no 

specific data. Speciation of lead compounds for a 

particular exposure scenario could support adjusting 

bioavailability if they are known to differ strongly 

from 30%. In general, U.S. EPA supports using 

bioavailability rates determined for the particular 

soils of interest if available. 

5.4.3. Activity Pattern Methodology 

The limitations associated with the activity 

pattern methodology relate to the availability and 

quality of the underlying data used to model soil 

ingestion rates. Real-time hand recording, where 

observations are made by trained professionals 

(rather than parents), may offer the advantage of 

consistency in interpreting visible behaviors and may 

be less subjective than observations made by 

someone who maintains a care giving relationship to 

the child. On the other hand, young children’s 

behavior may be influenced by the presence of 

unfamiliar people (Davis et al., 1995). Groot et al. 

(1998) indicated that parent observers perceived that 

deviating from their usual care giving behavior by 

observing and recording mouthing behavior appeared 

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to have influenced the children’s behavior. With 

video-transcription methodology, an assumption is 

made that the presence of the videographer or camera 

does not influence the child’s behavior. This 

assumption may result in minimal biases introduced 

when filming newborns, or when the camera and 

videographer are not visible to the child. However, if 

the children being studied are older than newborns 

and can see the camera or videographer, biases may 

be introduced. Ferguson et al. (2006) described 

apprehension caused by videotaping and described 

situations where a child’s awareness of the 

videotaping crew caused “play-acting” to occur, or 

parents indicated that the child was behaving 

differently during the taping session. Another 

possible source of measurement error may be 

introduced when children’s movements or positions 

cause their mouthing not to be captured by the 

camera. Data transcription errors can bias results in 

either the negative or positive direction. Finally, 

measurement error can occur if situations arise in 

which care givers are absent during videotaping and 

researchers must stop videotaping and intervene to 

prevent risky behaviors (Zartarian et al., 1995). 

Survey response studies rely on responses to 

questions about a child’s mouthing behavior posed to 

parents or care givers. Measurement errors from 

these studies could occur for a number of different 

reasons, including language/dialect differences 

between interviewers and respondents, question 

wording problems and lack of definitions for terms 

used in questions, differences in respondents’ 

interpretation of questions, and recall/memory 

effects. 

Other data collection methodologies (in-person 

interview, mailed questionnaire, or questions 

administered in “test” format in a school setting) may 

have had specific limitations. In-person interviews 

could result in either positive or negative response 

bias due to distractions posed by young children, 

especially when interview respondents 

simultaneously care for young children and answer 

questions. Other limitations include positive or 

negative response bias due to respondents’ 

perceptions of a “correct” answer, question wording 

difficulties, lack of understanding of definitions of 

terms used, language and dialect differences between 

investigators and respondents, respondents’ desires to 

avoid negative emotions associated with giving a 

particular type of answer, and respondent memory 

problems (“recall” effects) concerning past events. 

Mailed questionnaires have many of the same 

limitations as in-person interviews, but may allow 

respondents to respond when they are not distracted 

by childcare duties. An in-school test format is more 

problematic than either interviews or mailed surveys, 

because respondent bias related to teacher 

expectations could influence responses. 

One approach to evaluating the degree of bias in 

survey response studies may be to make use of a 

surrogate biomarker indicator providing suggestive 

evidence of ingestion of significant quantities of soil 

(although quantitative estimates would not be 

possible). The biomarker technique measures the 

presence of serum antibodies to Toxocara species, a 

parasitic roundworm from cat and dog feces. Two 

U.S. studies have found associations between 

reported soil ingestion and positive serum antibody 

tests for Toxocara infection (Marmor et al., 1987; 

Glickman et al., 1981); a third (Nelson et al., 1996) 

has not, but the authors state that reliability of survey 

responses regarding soil ingestion may have been an 

issue. Further refinement of survey response 

methodologies, together with recent NHANES data 

on U.S. prevalence of positive serum antibody status 

regarding infection with Toxocara species, may be 

useful. 

5.4.4. Key Studies: Representativeness of the U.S. 

Population 

The two key studies of Dutch and Jamaican 

children may represent different conditions and 

different study populations than those in the United 

States; thus, it is unclear to what extent those 

children’s soil ingestion behaviors may differ from 

U.S. children’s soil ingestion behaviors. The subjects 

in the Davis and Mirick (2006) study may not have 

been representative of the general population since 

they were selected for their high compliance with the 

protocol from a previous study. 

Limitations regarding the key studies performed 

in the United States for estimating soil and dust 

ingestion rates in the entire population of U.S. 

children ages 0 to <21 years fall into the broad 

categories of geographic range and demographics 

(age, sex, race/ethnicity, socioeconomic status). 

Regarding geographic range, the two most 

obvious issues relate to soil types and climate. Soil 

properties might influence the soil ingestion 

estimates that are based on excreted tracer elements. 

The Davis et al. (1990); Calabrese et al. (1989); 

Barnes (1990); Davis and Mirick (2006); and 

Calabrese et al. (1997b) tracer element studies were 

in locations with soils that had sand content ranging 

from 21−80%, silt content ranging from 16−71%, and 

clay content ranging from 3−20% by weight, based 

on data from USDA (2008). The location of children 

in the Calabrese et al. (1997a) study was not 

specified, but due to the original survey response 

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study’s occurrence in western Massachusetts, the soil 

types in the vicinity of the Calabrese et al. (1997a) 

study are likely to be similar to those in the Calabrese 

et al. (1989) and Barnes (1990) study. 

The Hogan et al. (1998) study included locations 

in the central part of the United States (an area along 

the Kansas/Missouri border, and an area in western 

Illinois) and one in the eastern United States 

(Palmerton, Pennsylvania). The only key study 

conducted in the southern part of the United States 

was Vermeer and Frate (1979). 

Children might be outside and have access to soil 

in a very wide range of weather conditions (Wong et 

al., 2000). In the parts of the United States that 

experience moderate temperatures year-round, soil 

ingestion rates may be fairly evenly distributed 

throughout the year. During conditions of deep snow 

cover, extreme cold, or extreme heat, children could 

be expected to have minimal contact with outside 

soil. All children, regardless of location, could ingest 

soils located indoors in plant containers, soil derived 

particulates transported into dwellings as ambient 

airborne particulates, or outdoor soil tracked inside 

buildings by human or animal building occupants. 

Davis et al. (1990) did not find a clear or consistent 

association between the number of hours spent 

indoors per day and soil ingestion, but reported a 

consistent association between spending a greater 

number of hours outdoors and high (defined as the 

uppermost tertile) soil ingestion levels across all three 

tracers used. 

The key tracer element studies all took place in 

northern latitudes. The temperature and precipitation 

patterns that occurred during these four studies’ data 

collection periods were difficult to discern due to no 

mention of specific data collection dates in the 

published articles. The Calabrese et al. (1989) and 

Barnes (1990) study apparently took place in mid to 

late September 1987 in and near Amherst, 

Massachusetts; Calabrese et al. (1997b) apparently 

took place in late September and early October 1992, 

in Anaconda, Montana; Davis et al. (1990) took place 

in July, August, and September 1987, in Richland, 

Kennewick, and Pasco, Washington; and Davis and 

Mirick (2006) took place in the same Washington 

state location in late July, August, and very early 

September 1988 (raw data). Inferring exact data 

collection dates, a wide range of temperatures may 

have occurred during the four studies’ data collection 

periods [daily lows from 22−60°

F and 25−48°F, and 

daily highs from 53−81°

F and 55−88°F in Calabrese 

et al. (1989) and Calabrese et al. (1997b), 

respectively, and daily lows from 51−72°

F and 

51−67°

F, and daily highs from 69−103°F and 

80−102 °

F in Davis et al. (1990) and Davis and Mirick 

(2006), respectively] (NCDC, 2008). Significant 

amounts of precipitation occurred during Calabrese et 

al. (1989) (more than 0.1 inches per 24-hour period) 

on several days; somewhat less precipitation was 

observed during Calabrese et al. (1997b); 

precipitation in Kennewick and Richland during the 

data collection periods of Davis et al. (1990) was 

almost non-existent; there was no recorded 

precipitation in Kennewick or Richland during the 

data collection period for Davis and Mirick (2006) 

(NCDC, 2008). 

The key biokinetic model comparison study 

(Hogan et al., 1998) targeted three locations in more 

southerly latitudes (Pennsylvania, southern Illinois, 

and southern Kansas/Missouri) than the tracer 

element studies. The biokinetic model comparison 

methodology had an advantage over the tracer 

element studies in that the study represented longterm environmental exposures over periods up to 

several years that would include a range of seasons 

and climate conditions. 

A brief review of the representativeness of the key 

studies’ samples with respect to sex and age 

suggested that males and females were represented 

roughly equally in those studies for which study 

subjects’ sex was stated. Children up to age 8 years 

were studied in seven of the nine studies, with an 

emphasis on younger children. Wong (1988); 

Calabrese and Stanek (1993); and Vermeer and Frate 

(1979) are the only studies with children 8 years or 

older. 

A brief review of the representativeness of the key 

studies’ samples with respect to socioeconomic status 

and racial/ethnic identity suggested that there were 

some discrepancies between the study subjects and 

the current U.S. population of children age 0 to 

<21 years. The single survey response study 

(Vermeer and Frate, 1979) was specifically targeted 

toward a predominantly rural Black population in a 

particular county in Mississippi. The tracer element 

studies are of predominantly White populations, 

apparently with limited representation from other 

racial and ethnic groups. The Amherst, Massachusetts 

study (Barnes, 1990; Calabrese et al., 1989) did not 

publish the study participants’ socioeconomic status 

or racial and ethnic identities. The socioeconomic 

level of the Davis et al. (1990) studied children was 

reported to be primarily of middle to high income. 

Self-reported race and ethnicity of relatives of the 

children studied (in most cases, they were the parents 

of the children studied) in Davis et al. (1990) were 

White (86.5%), Asian (6.7%), Hispanic (4.8%), 

Native American (1.0%), and Other (1.0%), and the 

91 married or living-as-married respondents 

identified their spouses as White (86.8%), Hispanic 

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(7.7%), Asian (4.4%), and Other (1.1%). Davis and 

Mirick (2006) did not state the race and ethnicity of 

the follow-up study participants, who were a subset 

of the original study participants from Davis et al. 

(1990). For the Calabrese et al. (1997b) study in 

Anaconda, Montana, population demographics were 

not presented in the published article. The study 

sample appeared to have been drawn from a door-todoor census of Anaconda residents that identified 

642 toilet trained children who were less than 

72 months of age. Of the 414 children participating in 

a companion study (out of the 642 eligible children 

identified), 271 had complete study data for that 

companion study, and of these 271, 97.4% were 

identified as White and the remaining 2.6% were 

identified as Native American, Black, Asian, and 

Hispanic (Hwang et al., 1997). The 64 children in the 

Calabrese et al. (1997b) study apparently were a 

stratified random sample (based on such factors as 

behavior during a previous study, the existence of a 

disability, or attendance in daycare) drawn from the 

642 children identified in the door-to-door census. 

Presumably these children identified as similar races 

and ethnicities to the Hwang et al. (1997) study 

children. The Calabrese et al. (1997a) study indicated 

that 11 of the 12 children studied were White. 

In summary, the geographic range of the key 

study populations was somewhat limited. Of those 

performed in the United States, locations included 

Massachusetts, Kansas, Montana, Missouri, Illinois, 

Washington, and Pennsylvania. The two most 

obvious issues regarding geographic range relate to 

soil types and climate. Soil types were not always 

described, so the representativeness of the key studies 

related to soil types and properties is unclear. The key 

tracer element studies all took place in northern 

latitudes. The only key study conducted in the 

southern part of the United States was Vermeer and 

Frate (1979). 

In terms of sex and age, males and females were 

represented roughly equally in those studies for 

which study subjects’ sex was stated, while the 

majority of children studied were under the age of 

eight. The tracer element studies are of 

predominantly White populations, with a single 

survey response study (Vermeer and Frate, 1979) 

targeted toward a rural Black population. Other racial 

and ethnic identities were not well reported among 

the key studies, nor was socioeconomic status. The 

socioeconomic level of the Davis et al. (1990) studied 

children was reported to be primarily of middle to 

high income. 

5.5.	 SUMMARY OF SOIL AND DUST 

INGESTION ESTIMATES FROM KEY 

STUDIES 

Table 5-22 summarizes the soil and dust ingestion 

estimates from the 12 key studies in chronological 

order. For the U.S. tracer element studies, in order to 

compare estimates that were calculated in a similar 

manner, the summary is limited to estimates that use 

the same basic algorithm of ([fecal and urine tracer 

content] - [food and medication tracer content])/[soil 

or dust tracer concentration]. Note that several of the 

published reanalyses suggest different variations on 

these algorithms, or suggest adjustments that should 

be made for various reasons (Calabrese and Stanek, 

1995; Stanek and Calabrese, 1995b). Other 

reanalyses suggest that omitting some of the data 

according to statistical criteria would be a worthwhile 

exercise. Due to the current state of the science 

regarding soil and dust ingestion estimates, U.S. EPA 

does not advise omitting an individual’s soil or dust 

ingestion estimate, based on statistical criteria, at this 

point in time. 

There is a wide range of estimated soil and dust 

ingestion across key studies. Note that some of the 

soil-pica ingestion estimates from the tracer element 

studies were consistent with the estimated mean soil 

ingestion from the survey response study of 

geophagy behavior. The biokinetic model comparison 

methodology’s confirmation of central tendency soil 

and dust ingestion default assumptions corresponded 

roughly with some of the central tendency tracer 

element study estimates. Also note that estimates 

based on the activity pattern methodology are 

comparable with estimates derived from the tracer 

element methodology. 

5.6.	 DERIVATION OF RECOMMENDED 

SOIL AND DUST INGESTION VALUES 

As stated earlier in this chapter, the key studies 

were used as the basis for developing the soil and 

dust ingestion recommendations shown in Table 5-1. 

The following sections describe in more detail how 

the recommended soil and dust ingestion values were 

derived. 

5.6.1. Central Tendency Soil and Dust Ingestion 

Recommendations 

For the central tendency recommendations shown 

in Table 5-1, Van Wïjnen et al. (1990) published soil 

ingestion “LTM” estimates based on infants older 

than 6 weeks but less than 1 year old (exact ages 

unspecified). During “bad” weather (>4 days per 

week of precipitation), the geometric mean estimated 

LTM values were 67 and 94 milligrams soil 

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(dry weight)/day; during “good” weather 

(<2 days/week of precipitation) the geometric mean 

estimated LTM values were 102 milligrams soil 

(dry weight)/day (van Wijnen et al., 1990). These 

values were not corrected to exclude dietary intake of 

the tracers on which they were based. The developers 

of the IEUBK model used these data as the basis for 

the default soil and dust intakes for the 6 to 

<12 month old infants in the IEUBK model (U.S. 

EPA, 1994b) of 38.25 milligrams soil/day and 

46.75 mg house dust/day, for a total soil + dust intake 

default assumption of 85 mg/day for this age group 

(U.S. EPA, 1994a). 

Further evidence of dust intake by infants has 

been conducted in the context of evaluating blood 

lead levels and the potential contributions of lead 

from three sources: bone turnover, food sources, and 

environmental exposures such as house dust. Manton 

et al. (2000) conducted a study with older infants and 

young children, and concluded that appreciable 

quantities of dust were ingested by infants. Gulson et 

al. (2001) studied younger infants than Manton et al. 

(2000) and did not explicitly include dust sources, but 

the authors acknowledged that, based on ratios of 

different isotopes of lead found in infants' blood and 

urine, there appeared to be a non-food, non-bone 

source of lead of environmental origin that 

contributed “minimally,” relative to food intakes and 

bone turnover in 0- to 6-month-old infants. 

The Hogan et al. (1998) data for 38 infants (one 

group N = 7 and one group N = 31) indicated that the 

IEUBK default soil and dust estimate for 6 to 

<12 month olds (85 mg/day) over-predicted blood 

lead levels in this group, suggesting that applying an 

85 mg soil + dust (38 mg soil + 47 mg house dust) 

per day estimate for 6 months' exposure may be too 

high for this life stage. 

For the larger of two groups of infants aged 6 to 

<12 months in the Hogan et al. (1998) study (N = 31), 

the default IEUBK value of 85 mg/day predicted 

geometric mean blood lead levels of 5.2 μg/dL versus 

3.8 μg/dL actual measured blood lead level (a ratio of 

1.37). It is possible that the other major sources of 

lead accounted for in the IEUBK model (dietary and 

drinking water lead) are responsible for part of the 

over-prediction seen with the Hogan et al. (1998) 

study. Rounded to the ones place, the default assumed 

daily lead intakes were (dietary) 6 μg/day and 

(drinking water) 1 μg/day, compared to the soil lead 

intake of 8 μg/day and house dust lead intake of 

9 μg/day (U.S. EPA, 1994b). The dietary lead intake 

default assumption thus might be expected to be 

responsible for the over-predictions as well as the soil 

and dust intake, since these three sources (diet, soil, 

and dust) comprise the majority of the total lead 

intake in the model. Data from Manton et al. (2000) 

suggest that the default assumption for dietary lead 

intake might be somewhat high (reported geometric 

mean daily lead intake from food in Manton et al. 

(2000) was 3.2 μg/day, arithmetic mean 3.3 μg/day). 

Making use of the epidemiologic data from the 

larger group of 31 infants in the Hogan et al. (1998) 

study, it is possible to develop an extremely rough 

estimate of soil + dust intake by infants 6 weeks 

to <12 months of age. The ratio of the geometric 

mean IEUBK-predicted to actual measured blood 

lead levels in 31 infants was 1.37. This value may be 

used to adjust the soil and dust intake rate for the 6 to 

<12 month age range. Using the inverse of 1.37 

(0.73) and multiplying the 85 mg/day soil + house 

dust intake rate by this value, gives an adjusted value 

of 62 mg/day soil + dust, rounded to one significant 

figure at 60 mg/day. The 38 mg soil/day intake rate, 

multiplied by the 0.73 adjustment factor, yields 

28 mg soil per day (rounding to 30 mg soil per day); 

the 47 mg house dust/day intake rate multiplied by 

0.73 yields 34 mg house dust per day (rounding to 

30 mg house dust per day). These values, adjusted 

from the IEUBK default values, are the basis for the 

soil (30 mg/day) and dust (30 mg/day) 

recommendations for children aged 6 weeks to 

12 months. 

For children age 1 to <6 years, the IEUBK default 

values used in the Hogan et al. (1998) study were: 

135 mg/day for 1, 2, and 3 year olds; 100 mg/day for 

4 year olds; 90 mg/day for 5 year olds; and 

85 mg/day for 6 year olds. These values were based 

on an assumption of 45% soil, 55% dust (U.S. EPA, 

1994a). The time-averaged daily soil + dust ingestion 

rate for these 6 years of life is 113 mg/day, 

dry-weight basis. The Hogan et al. (1998) study 

found the following over- and under-predictions of 

blood lead levels, compared to actual measured blood 

lead levels, using the default values shown in Table 

5-23. Apportioning the 113 mg/day, on average, into 

45% soil and 55% dust (U.S. EPA, 1994a), yields an 

average for this age group of 51 mg/day soil, 

62 mg/day dust. Rounded to one significant figure, 

these values are 50 and 60 mg/day, respectively. The 

60 mg/day dust would be comprised of a combination 

of outdoor soil tracked indoors onto floors, indoor 

dust on floors, indoor settled dust on non-floor 

surfaces, and probably a certain amount of inhaled 

suspended dust that is swallowed and enters the 

gastrointestinal tract. Soil ingestion rates were 

assumed to be comparable for children age 1 to <6 

years and 6 to <21 years, and therefore the same 

recommended values were used for both age groups.

Estimates derived by Özkaynak et al. (2011) suggest 

soil and dust ingestion rates comparable to other 

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Chapter 5—Soil and Dust Ingestion 

estimates in the literature based on tracer element 

methodology (i.e., a mean value of 68 mg/day). 

The recommended soil and dust ingestion rate of 

50 mg/day for adults was taken from the overall 

mean value of 52 mg/day for the adults in the Davis 

and Mirick (2006) study. Based on this value, the 

recommended adult soil and dust ingestion value is 

estimated to be 50 mg/day. There are no available 

studies estimating the ingestion of dust by adults, 

therefore, the recommended values for soil and dust 

were derived from the soil + dust ingestion, assuming 

45% soil and 55% dust contribution. 

5.6.2. Upper Percentile, Soil Pica, and Geophagy 

Recommendations 

Upper percentile estimates for children 3 to 

<6 years old were derived from Özkaynak et al. 

(2011) and Stanek and Calabrese (1995b). These two 

studies had similar estimates of 95th percentile value 

(i.e., 224 mg/day and 207 mg/day, respectively). 

Rounding to one significant figure, the recommended 

upper percentile estimate of soil and dust ingestion is 

200 mg/day. Soil and dust ingestion

recommendations were obtained from Özkaynak et 

al. (2011). For the upper percentile soil pica and 

geophagy recommendations shown in Table 5-1, two 

primary lines of evidence suggest that at least some 

U.S. children exhibit soil-pica behavior at least once 

during childhood. First, the survey response studies 

of reported soil ingestion behavior that were 

conducted in numerous U.S. locations and of 

different populations consistently yield a certain 

proportion of respondents who acknowledge soil 

ingestion by children. The surveys typically did not 

ask explicit and detailed questions about the soil 

ingestion incidents reported by the care givers who 

acknowledged soil ingestion in children. Responses 

conceivably could fall into three categories: 

(1) responses in which care givers interpret visible 

dirt on children’s hands, and subsequent 

hand-to-mouth behavior, as soil ingestion; 

(2) responses in which care givers interpret 

intentional ingestion of clay, “dirt” or soil as soil 

ingestion; and (3) responses in which care givers 

regard observations of hand-to-mouth behavior of 

visible quantities of soil as soil ingestion. Knowledge 

of soils’ bulk density allows inferences to be made 

that these latter observed hand-to-mouth soil 

ingestion incidents are likely to represent a quantity 

of soil that meets the quantity part of the definition of 

soil-pica used in this chapter, or 1,000 mg. 

Occasionally, what is not known from survey 

response studies is whether the latter type of survey 

responses include responses regarding repeated soil 

ingestion that meets the definition of soil-pica used in 

this chapter. The second category probably does 

represent ingestion that would satisfy the definition 

of soil-pica as well as geophagy. The first category 

may represent relatively small amounts that appear to 

be ingested by many children based on the Hogan et 

al. (1998) study and the tracer element studies. 

Second, the U.S. tracer studies report a wide range of 

soil ingestion values. Due to averaging procedures 

used, for 4, 7, or 8 day periods, the rounded range of 

these estimates of soil ingestion behavior that 

apparently met the definition of soil-pica used in this 

chapter is from 400 to 41,000 mg/day. The 

recommendation of 1,000 mg/day for soil-pica is 

based on this range. 

Although there were no tracer element studies or 

biokinetic model comparison studies performed for 

children 15 to <21 years, in which soil-pica behavior 

of children in this age range has been investigated, 

U.S. EPA is aware of one study documenting pica 

behavior in a group that includes children in this age 

range (Hyman et al., 1990). The study was not 

specific regarding whether soil-pica (versus other 

pica substances) was observed, nor did it identify the 

specific ages of the children observed to practice 

pica. In the absence of data that can be used to 

develop specific soil-pica soil ingestion 

recommendations for children aged 15 years and 16 

to <21 years, U.S. EPA recommends that risk 

assessors who need to assess risks via soil and dust 

ingestion to children ages 15 to <21 years use the 

same soil ingestion rate as that recommended for 

younger children, in the 1 to <6, 6 to <11, and 11 to 

<16 year old age categories. 

Researchers who have studied human geophagy 

behavior around the world typically have studied 

populations in specific locations, and often include 

investigations of soil properties as part of the 

research (Wilson, 2003; Aufreiter et al., 1997). Most 

studies of geophagy behavior in the United States 

were survey response studies of residents in specific 

locations who acknowledged eating clays. Typically, 

study subjects were from a relatively small area such 

as a county, or a group of counties within the same 

state. Although geophagy behavior may have been 

studied in only a single county in a given state, 

documentation of geophagy behavior by some 

residents in one or more counties of a given state may 

suggest that the same behavior also occurs elsewhere 

within that state. 

A qualitative description of amounts of soil 

ingested by geophagy practitioners was provided by 

Vermeer and Frate (1979) with an estimated mean 

amount, 50 g/day, that apparently was averaged over 

32 adults and 18 children. The 18 children whose 

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caregivers acknowledged geophagy (or more 

specifically, eating of clay) were (N = 16) ages 1 to 4 

and (N = 2) ages 5 to 12 years. The definition of 

geophagy used included consumption of clay “on a 

regular basis over a period of weeks.” U.S. EPA is 

recommending this 50 g/day value for geophagy. This 

mean quantity is roughly consistent with a median 

quantity reported by Geissler et al. (1998) in a survey 

response study of geophagy in primary school 

children in Nyanza Province, Kenya (28 g/day, range 

8 to 108 g/day; interquartile range 13 to 42 g/day). 

Recent studies of pica among pregnant women in 

various U.S. locations (Corbett et al., 2003; Rainville, 

1998; Smulian et al., 1995) suggest that clay 

geophagy among pregnant women may include 

children less than 21 years old (Corbett et al., 2003; 

Smulian et al., 1995). Smulian provides a quantitative 

estimate of clay consumption of approximately 

200−500 g/week, for the very small number of 

geophagy practitioners (N = 4) in that study’s sample 

(N = 125). If consumed on a daily basis, this quantity 

(approximately 30 to 70 g/day) is roughly consistent 

with the Vermeer and Frate (1979) estimated mean of 

50 g/day. 

Johns and Duquette (1991) describe use of clays 

in baking bread made from acorn flour, in a ratio of 

1 part clay to 10 or 20 parts acorn flour, by volume, 

in a Native American population in California, and in 

Sardinia (~12 grams clay suspended in water added 

to 100 grams acorn). Either preparation method 

would add several grams of clay to the final prepared 

food; daily ingestion of the food would amount to 

several grams of clay ingested daily. 

5.7. REFERENCES FOR CHAPTER 5 

ATSDR (Agency for Toxic Substances and Disease 

Registry). (2001). Summary report for the 

ATSDR soil-pica workshop, June 2000, 

Atlanta, Georgia. Atlanta, GA. 

http://www.atsdr.cdc.gov/child/soilpica.html 

. 

Aufreiter, S; Hancock, R; Mahaney, W; StambolicRobb, A; Sanmugadas, K. (1997). 

Geochemistry and mineralogy of soils eaten 

by humans. Int J Food Sci Nutr 48: 293-305. 

Barltrop, D. (1966). The prevalence of pica. Arch 

Pediatr Adolesc Med 112: 116-123. 

Barnes, RM. (1990). Childhood soil ingestion: How 

much dirt do kids eat? Anal Chem 62: 

1023A-1033A. 

Binder, S; Sokal, D; Maughan, D. (1986). Estimating 

soil ingestion: The use of tracer elements in 

estimating the amount of soil ingested by 

young children. Arch Environ Occup Health 

41: 341-345. 

Black, K; Shalat, SL; Freeman, NCG; Jimenez, M; 

Donnelly, KC; Calvin, JA. (2005). 

Children's mouthing and food-handling 

behavior in an agricultural community on 

the US/Mexico border. J Expo Anal Environ 

Epidemiol 15: 244-251. 

http://dx.doi.org/10.1038/sj.jea.7500398. 

Bronstein, ES; Dollar, J. (1974). Pica in pregnancy. J 

Med Assoc Ga 63: 332-335. 

Bruhn,	 CM; Pangborn, RM. (1971). Reported 

incidence of pica among migrant families. J 

Am Diet Assoc 58: 417-420. 

Calabrese, EJ; Barnes, R; Stanek, EJ; Pastides, H; 

Gilbert, C; Veneman, P; Wang, X; Lasztity, 

A; Kostecki, P. (1989). How much soil do 

young children ingest: An epidemiological 

study. Regul Toxicol Pharmacol 10: 123­

137. 

Calabrese, EJ; Stanek, EJ. (1992a). What proportion 

of household dust is derived from outdoor 

soil? Soil Sediment Contam 1: 253-263. 

Calabrese, EJ; Stanek, EJ. (1993). Soil pica: Not a 

rare event. J Environ Sci Health A Tox 

Hazard Subst Environ Eng 28: 373-384. 

Calabrese, EJ; Stanek, EJ; Barnes, R. (1997a). Soil 

ingestion rates in children identified by 

parental observation as likely high soil 

ingesters. Journal of Soil Contamination 6: 

271-279. 

http://dx.doi.org/10.1080/153203897093835 

65. 

Calabrese, EJ; Stanek, EJ; Barnes, R; Burmaster, DE; 

Callahan, BG; Heath, JS; Paustenbach, D; 

Abraham, J; Gephart, LA. (1996). 

Methodology to estimate the amount and 

particle size of soil ingested by children: 

implications for exposure assessment at 

waste sites. Regul Toxicol Pharmacol 24: 

264-268. 

http://dx.doi.org/10.1006/rtph.1996.0139. 

Calabrese, EJ; Stanek, EJ; Gilbert, C; Barnes, R. 

(1990). Preliminary adult soil ingestion 

estimates: Results of a pilot study. Regul 

Toxicol Pharmacol 12: 88-95. 

Calabrese, EJ; Stanek, EJ; Gilbert, CE. (1991). 

Evidence of soil pica behavior and 

quantification of soil ingested. Hum Exp 

Toxicol 10: 245-249. 

Calabrese, EJ; Stanek, EJ, III. (1995). Resolving 

intertracer inconsistencies in soil ingestion 

estimation. Environ Health Perspect 103: 

454-457. 

Calabrese, EJ; Stanek, EJ; Pekow, P; Barnes, RM. 

(1997b). Soil ingestion estimates for 

Page Exposure Factors Handbook 

5-34 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

children residing on a superfund site. 

Ecotoxicol Environ Saf 36: 258-268. 

http://dx.doi.org/10.1006/eesa.1996.1511. 

Calabrese, EJ; Stanek, ES. (1992b). Distinguishing 

outdoor soil ingestion from indoor dust 

ingestion in a soil pica child. Regul Toxicol 

Pharmacol 15: 83-85. 

Carlisle, EM. (1980). Biochemical and 

morphological changes associated with long 

bone abnormalities in silicon deficiency. J 

Nutr 110: 1046-1056. 

Choate, LM; Ranville, JF; Bunge, AL; Macalady, DL. 

(2006). Dermally adhered soil: 1. Amount 

and particle-size distribution. Integr Environ 

Assess Manag 2: 375-384. 

Clausing, P; Brunekreef, B; van Wijnen, JH. (1987). 

A method for estimating soil ingestion by 

children. Int Arch Occup Environ Health 59: 

73-82. 

Cooksey, NR. (1995). Pica and olfactory craving of 

pregnancy: how deep are the secrets? Birth 

22: 129-137. 

Cooper, M. (1957). Pica: A survey of the historical 

literature as well as reports from the fields of 

veterinary medicine and anthropology, the 

present study of pica in young children, and 

a discussion of its pediatric and 

psychological implications. Springfield, IL: 

Charles C. Thomas. 

Corbett, RW; Ryan, C; Weinrich, SP. (2003). Pica in 

pregnancy: does it affect pregnancy 

outcomes? MCN Am J Matern Child Nurs 

28: 183-189; quiz 190-181. 

Danford, DE. (1982). Pica and nutrition. Annu Rev 

Nutr 2: 303-322. 

http://dx.doi.org/10.1146/annurev.nu.02.070 

182.001511. 

Danford, DE. (1983). Pica and zinc. In AS Prasad; 

AO Cavdar; GJ Brewer; PJ Aggett (Eds.), 

Zinc deficiency in human subjects (pp. 

185−195). New York, NY: Alan R. Liss. 

Davis, S; Mirick, DK. (2006). Soil ingestion in 

children and adults in the same family. J 

Expo Sci Environ Epidemiol 16: 63-75. 

http://dx.doi.org/10.1038/sj.jea.7500438. 

Davis, S; Myers, PA; Kohler, E; Wiggins, C. (1995). 

Soil ingestion in children with pica: Final 

report. (U.S. EPA Cooperative Agreement 

CR 816334-01). Seattle, WA: Fred 

Hutchison Cancer Research Center. 

Davis, S; Waller, P; Buschbom, R; Ballou, J; White, 

P. (1990). Quantitative estimates of soil 

ingestion in normal children between the 

ages of 2 and 7 years: Population-based 

estimates using aluminum, silicon, and 

titanium as soil tracer elements. Arch 

Environ Health 45: 112-122. 

Dickins, D; Ford, RN. (1942). Geophagy (Dirt 

Eating) Among Mississippi Negro School 

Children. Am Socio Rev 7: 59. 

http://dx.doi.org/10.2307/2086258. 

Dominy, NJ; Davoust, E; Minekus, M. (2004). 

Adaptive function of soil consumption: an in 

vitro study modeling the human stomach 

and small intestine. J Exp Biol 207: 319­

324. 

Ferguson, AC; Canales, RA; Beamer, P; Auyeung, 

W; Key, M; Munninghoff, A; Lee, KT; 

Robertson, A; Leckie, JO. (2006). Video 

methods in the quantification of children's 

exposures. J Expo Sci Environ Epidemiol 

16: 287-298. 

http://dx.doi.org/10.1038/sj.jea.7500459. 

Ferguson, JH; Keaton, AG. (1950). Studies of the 

diets of pregnant women in Mississippi: II 

diet patterns. 103: 81-87. 

Gavrelis, N; Sertkaya, A; Bertelsen, L; Cuthbertson, 

B; Phillips, L; Moya, J. (2011). An Analysis 

of the Proportion of the US Population that 

Ingests Soil or Other Non-Food Substances. 

Hum Ecol Risk Assess 17: 996-1012. 

Geissler, PW; Shulman, CE; Prince, RJ; Mutemi, W; 

Mnazi, C; Friis, H; Lowe, B. (1998). 

Geophagy, iron status and anaemia among 

pregnant women on the coast of Kenya. 

Trans Roy Soc Trop Med Hyg 92: 549-553. 

Glickman, LT; Chaudry, IU; Costantino, J; Clack, 

FB; Cypess, RH; Winslow, L. (1981). Pica 

patterns, toxocariasis, and elevated blood 

lead in children. Am J Trop Med Hyg 30: 

77-80. 

Grigsby, RK; Thyer, BA; Waller, RJ; Johnston, GA. 

(1999). Chalk eating in middle Georgia: a 

culture-bound syndrome of pica? South Med 

J 92: 190-192. 

Groot, ME; Lekkerkerk, MC; Steenbekkers, LPA. 

(1998). Mouthing behavior of young 

children: An observational study. 

Wageningen, the Netherlands: Agricultural 

University. 

Gulson, BL; Mizon, KJ; Palmer, JM; Patison, N; 

Law, AJ; Korsch, MJ; Mahaffey, KR; 

Donnelly, JB. (2001). Longitudinal study of 

daily intake and excretion of lead in newly 

born infants. Environ Res 85: 232-245. 

Harris, SG; Harper, BL. (1997). A Native American 

exposure scenario. Risk Anal 17: 789-795. 

Hawley, JK. (1985). Assessment of health risk from 

exposure to contaminated soil. Risk Anal 5: 

289-302. 

Exposure Factors Handbook Page
 

September 2011 5-35 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Hogan, K; Marcus, A; Smith, R; White, P. (1998). 

Integrated exposure uptake biokinetic model 

for lead in children: empirical comparisons 

with epidemiologic data. Environ Health 

Perspect 106: 1557-1567. 

Hooda, PS; Henry, CJ; Seyoum, TA; Armstrong, LD; 

Fowler, MB. (2004). The potential impact of 

soil ingestion on human mineral nutrition. 

Sci Total Environ 333: 75-87. 

http://dx.doi.org/10.1016/j.scitotenv.2004.04 

.023. 

Hook, EB. (1978). Dietary cravings and aversions 

during pregnancy. Am J Clin Nutr 31: 1355­

1362. 

Hwang, YH; Bornschein, RL; Grote, J; Menrath, W; 

Roda, S. (1997). Environmental arsenic 

exposure of children around a former copper 

smelter site. Environ Res 72: 72-81. 

http://dx.doi.org/10.1006/enrs.1996.3691. 

Hyman, SL; Fisher, W; Mercugliano, M; Cataldo, 

MF. (1990). Children with self-injurious 

behavior. Pediatrics 85: 437-441. 

ICRP (International Commission on Radiological 

Protection). (2003). Basic anatomical and 

physiological data for use in radiological 

protection: Reference values. (ICRP 

Publication 89). New York, NY: Pergamon 

Press. 

http://www.elsevier.com/wps/find/bookdescr 

iption.cws_home/672826/description#descri 

ption. 

Johns, T; Duquette, M. (1991). Detoxification and 

mineral supplementation as functions of 

geophagy. Am J Clin Nutr 53: 448-456. 

Jugdaohsingh, R; Anderson, SH; Tucker, KL; Elliott, 

H; Kiel, DP; Thompson, RP; Powell, JJ. 

(2002). Dietary silicon intake and 

absorption. Am J Clin Nutr 75: 887-893. 

Kinnell, HG. (1985). Pica as a feature of autism. Br J 

Psychiatry 147: 80-82. 

Kissel, JC; Shirai, JH; Richter, KY; Fenske, RA. 

(1998). Empirical investigation of hand-tomouth transfer of soil. Bull Environ Contam 

Toxicol 60: 379-386. 

Klitzman, S; Sharma, A; Nicaj, L; Vitkevich, R; 

Leighton, J. (2002). Lead poisoning among 

pregnant women in New York City: risk 

factors and screening practices. Bull NY 

Acad Med 79: 225-237. 

http://dx.doi.org/10.1093/jurban/79.2.225. 

Korman, SH. (1990). Pica as a presenting symptom 

in childhood celiac disease. Am J Clin Nutr 

51: 139-141. 

Lásztity, A; Wang, X; Viczián, M; Israel, Y; Barnes, 

RM. (1989). Inductively coupled plasma 

spectrometry in the study of childhood soil 

ingestion. Part 2. Recovery. J Anal At 

Spectrom 4: 737-742. 

Manton, WI; Angle, CR; Stanek, KL; Reese, YR; 

Kuehnemann, TJ. (2000). Acquisition and 

retention of lead by young children. Environ 

Res 82: 60-80. 

http://dx.doi.org/10.1006/enrs.1999.4003. 

Marmor, M; Glickman, L; Shofer, F; Faich, LA; 

Rosenberg, C; Cornblatt, B; Friedman, S. 

(1987). Toxocara canis infection of children: 

epidemiologic and neuropsychologic 

findings. Am J Public Health 77: 554-559. 

Mody, V; Jakhete, R. (1987). Chapter 1: Dust and its 

control. In Dust control handbook for 

minerals processing. Pittsburgh, PA: U.S. 

Bureau of Mines. 

http://www.osha.gov/dsg/topics/silicacrystall 

ine/dust/chapter_1.html. 

NCDC (National Climatic Data Center). (2008). Data 

set TD3200: U.S. cooperative summary of 

the day data. Washington, DC: National 

Oceanic and Atmospheric Administration, 

National Environmental Satellite, Data and 

Information Service. Retrieved from 

http://www.ncdc.noaa.gov/oa/documentlibra 

ry/surface-doc.html#3200 

Nelson, S; Greene, T; Ernhart, CB. (1996). Toxocara 

canis infection in preschool age children: 

risk factors and the cognitive development 

of preschool children. Neurotoxicol Teratol 

18: 167-174. 

Obialo, CI; Crowell, AK; Wen, XJ; Conner, AC; 

Simmons, EL. (2001). Clay pica has no 

hematologic or metabolic correlate in 

chronic hemodialysis patients. J Ren Nutr 

11: 32-36. 

Ozkaynak, H; Xue, J; Zartarian, VG; Glen, G; Smith, 

L. (2011). Modeled estimates of soil and 

dust ingestion rates for children. 31: 592­

608. http://dx.doi.org/10.1111/j.1539­

6924.2010.01524.x. 

Powell, JJ; Ainley,	 CC; Harvey, RS; Mason, IM; 

Kendall, MD; Sankey, EA; Dhillon, AP; 

Thompson, RP. (1996). Characterisation of 

inorganic microparticles in pigment cells of 

human gut associated lymphoid tissue. Gut 

38: 390-395. 

Rainville, AJ. (1998). Pica practices of pregnant 

women are associated with lower maternal 

hemoglobin level at delivery. J Am Diet 

Assoc 98: 293-296. 

http://dx.doi.org/10.1016/S0002­

8223(98)00069-8. 

Robischon, P. (1971). Pica practice and other handPage Exposure Factors Handbook 

5-36 September 2011 
Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Exposure Factors Handbook Page
 

September 2011 5-37 

mouth behavior and children's 

developmental level. Nurs Res 20: 4-16. 

Shepherd, NA; Crocker, PR; Smith, AP; Levison, 

DA. (1987). Exogenous pigment in Peyer's 

patches. Hum Pathol 18: 50-54. 

Simpson, E; Mull, JD; Longley, E; East, J. (2000). 

Pica during pregnancy in low-income 

women born in Mexico. West J Med 173: 

20-24; discussion 25. 

Smulian, JC; Motiwala, S; Sigman, RK. (1995). Pica 

in a rural obstetric population. South Med J 

88: 1236-1240. 

Stanek, EJ, III; Calabrese, EJ. (1995a). Daily 

estimates of soil ingestion in children. 

Environ Health Perspect 103: 276-285. 

Stanek, EJ, III; Calabrese, EJ. (1995b). Soil ingestion 

estimates for use in site evaluations based on 

the best tracer method. Hum Ecol Risk 

Assess 1: 133-157. 

http://dx.doi.org/10.1080/108070395093799 

98. 

Stanek, EJ, III; Calabrese, EJ. (2000). Daily soil 

ingestion estimates for children at a 

superfund site. Risk Anal 20: 627-635. 

Stanek, EJ, III; Calabrese, EJ; Barnes, RM. (1999). 

Soil ingestion estimates for children in 

Anaconda using trace element 

concentrations in different particle size 

fractions. Hum Ecol Risk Assess 5: 547-558. 

Stanek, EJ, III; Calabrese, EJ; Mundt, K; Pekow, P; 

Yeatts, KB. (1998). Prevalence of soil 

mouthing/ingestion among healthy children 

aged 1 to 6. Journal of Soil Contamination 

7: 227-242. 

Stanek, EJ, III; Calabrese, EJ; Zorn, M. (2001a). 

Biasing factors for simple soil ingestion 

estimates in mass balance studies of soil 

ingestion. Hum Ecol Risk Assess 7: 329­

355. 

Stanek, EJ, III; Calabrese, EJ; Zorn, M. (2001b). Soil 

ingestion distributions for Monte Carlo risk 

assessment in children. Hum Ecol Risk 

Assess 7: 357-368. 

U.S.	 Department of Commerce. (2008). Table 2: 

Annual estimates of the population by sex 

and selected age groups for the United 

States: April 1, 2000 to July 1, 2007. (NCEST2007-02). 

U.S. EPA (U.S. Environmental Protection Agency). 

(1994a). Guidance manual for the IEUBK 

model for lead in children. (EPA 540/R93/081). 

U.S. EPA (U.S. Environmental Protection Agency). 

(1994b). Technical support document: 

Parameters and equations used in integrated 

exposure uptake biokinetic model for lead in 

children (v 099d). (EPA/54O/R-94/04O). 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum. 

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2008). Child-specific exposure factors 

handbook [EPA Report]. (EPA/600/R06/096F). Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=199243. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2010). SHEDS-multimedia: Details of 

SHEDS-multimedia version 3: 

ORD/NERL’s model to estimate aggregate 

and cumulative exposures to chemicals. 

Research Triangle Park, NC. 

http://www.epa.gov/heasd/products/sheds_m 

ultimedia/sheds_mm.html. 

USDA (U.S. Department of Agriculture). (1999). Soil 

taxonomy: A basic system of soil 

classification for making and interpreting 

soil surveys. Washington, DC. 

http://soils.usda.gov/technical/classification/ 

taxonomy/. 

USDA (U.S. Department of Agriculture). (2008). 

Web soil survey. Washington, DC. 

http://websoilsurvey.nrcs.usda.gov/app/Hom 

ePage.htm. 

Van Dyck, K; Robberecht, H; Van Cauwenbergh, R; 

Van Vlaslaer, V; Deelstra, H. (2000). 

Indication of silicon essentiality in humans: 

serum concentrations in Belgian children 

and adults, including pregnant women. Biol 

Trace Elem Res 77: 25-32. 

http://dx.doi.org/10.1385/BTER:77:1:25. 

van Wijnen, JH; Clausing, P; Brunekreef, B. (1990). 

Estimated soil ingestion by children. 

Environ Res 51: 147-162. 

Vermeer, DE; Frate, DA. (1979). Geophagia in rural 

Mississippi: environmental and cultural 

contexts and nutritional implications. Am J 

Clin Nutr 32: 2129-2135. 

Von Lindern, I; Spalinger, S; Petroysan, V; Von 

Braun, M. (2003). Assessing remedial 

effectiveness through the blood lead 

soil/dust lead relationship at the Bunker Hill 

Superfund site in the Silver Valley of Idaho. 
 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Sci Total Environ 303: 139-170. 

http://dx.doi.org/10.1016/S0048­

9697(02)00352-2. 

Ward, P; Kutner, NG. (1999). Reported pica behavior 

in a sample of incident dialysis patients. J 

Ren Nutr 9: 14-20. 

White, PD; Van Leeuwan, P; Davis, BD; Maddaloni, 

M; Hogan, KA; Marcus, AH; Elias, RW. 

(1998). The conceptual structure of the 

integrated exposure uptake biokinetic model 

for lead in children. Environ Health Perspect 

6: 1513-1530. 

Wilson, MJ. (2003). Clay mineralogical and related 

characteristics of geophagic materials. J 

Chem Ecol 29: 1525-1547. 

Wong, EY; Shirai, JH; Garlock, TJ; Kissel, JC. 

(2000). Adult proxy responses to a survey of 

children's dermal soil contact activities. J 

Expo Anal Environ Epidemiol 10: 509-517. 

Wong, MS. (1988) The role of environmental and 

host behavioural factors in determining 

exposure to infection with Ascaris 

lumbricoides and Trichuris trichiura. 

(Doctoral Dissertation). University of the 

West Indies, Faculty of the Natural Sciences, 

Mona, Kingston, Jamaica. 

Yamamoto, N; Takahashi, Y; Yoshinaga, J; Tanaka, 

A; Shibata, Y. (2006). Size distributions of 

soil particles adhered to children's hands. 

Arch Environ Contam Toxicol 51: 157-163. 

http://dx.doi.org/10.1007/s00244-005-7012­

y. 

Zartarian, VG; Streicker, J; Rivera, A; Cornejo, CS; 

Molina, S; Valadez, OF; Leckie, JO. (1995). 

A pilot study to collect micro-activity data 

of two- to four-year-old farm labor children 

in Salinas Valley, California. J Expo Anal 

Environ Epidemiol 5: 21-34. 

Page Exposure Factors Handbook 

5-38 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-3. Soil, Dust, and Soil + Dust Ingestion Estimates for Amherst, Massachusetts Study Children 

Tracer Element N Ingestion (mg/day) 

Mean Median SD 95th Percentile Maximum 

Aluminum 

soil 

dust 

soil/dust combined 

64 

64 

64 

153 

317 

154 

29 

31 

30 

852 

1,272 

629 

223 

506 

478 

6,837 

8,462 

4,929 

Barium 

soil 

dust 

soil/dust combined 

64 

64 

64 

32 

31 

29 

–37 

–18 

–19 

1,002 

860 

868 

283 

337 

331 

6,773 

5,480 

5,626 

Manganese 

soil 

dust 

soil/dust combined 

64 

64 

64 

–294 

–1,289 

–496 

–261 

–340 

–340 

1,266 

9,087 

1,974 

788 

2,916 

3,174 

7,281 

20,575 

4,189 

Silicon 

soil 

dust 

soil/dust combined 

64 

64 

64 

154 

964 

483 

40 

49 

49 

693 

6,848 

3,105 

276 

692 

653 

5,549 

54,870 

24,900 

Vanadium 

soil 

dust 

soil//dust combined 

62 

64 

62 

459 

453 

456 

96 

127 

123 

1,037 

1,005 

1,013 

1,903 

1,918 

1,783 

5,676 

6,782 

6,736 

Yttrium 

soil 

dust 

soil/dust combined 

62 

64 

62 

85 

62 

65 

9 

15 

11 

890 

687 

717 

106 

169 

159 

6,736 

5,096 

5,269 

Zirconium 

soil 

dust 

soil/dust combined 

62 

64 

62 

21 

27 

23 

16 

12 

11 

209 

133 

138 

110 

160 

159 

1,391 

789 

838 

Titanium 

soil 

dust 

soil/dust combined 

64 

64 

64 

218 

163 

170 

55 

28 

30 

1,150 

659 

691 

1,432 

1,266 

1,059 

6,707 

3,354 

3,597 

SD = Standard deviation. 

N = Number of subjects. 

Source: Calabrese et al. (1989). 

Exposure Factors Handbook Page
 

September 2011 5-39 
 

 

Table 5-4. Amherst, Massachusetts Soil-Pica Child’s Daily Ingestion Estimates by Tracer and by Week 

(mg/day) 

Tracer Estimated Soil Ingestion (mg/day) 

element Week 1 Week 2 

Al 74 13,600 

Ba 458 12,088 

Mn 2,221 12,341 

Si 142 10,955 

Ti 1,543 11,870 

V 1,269 10,071 

Y 147 13,325 

Zr 86 2,695 

Source: Calabrese et al. (1991). 

 

 

 

Table 5-5. Van Wïjnen et al. (1990) Limiting Tracer Method (LTM) Soil Ingestion Estimates for Sample of Dutch Children 

Daycare Center Campground 

Age (years) Sex GM LTM GSD LTM GM LTM GSD LTM 

N (mg/day) (mg/day) N (mg/day) (mg/day) 

Birth to <1 Girls 3 81 1.09 NA NA NA 

Boys 1 75 NA NA NA 

1 to <2 Girls 20 124 1.87 3 207 1.99 

Boys 17 114 1.47 5 312 2.58 

2 to <3 Girls 34 118 1.74 4 367 2.44 

Boys 17 96 1.53 8 232 2.15 

3 to <4 Girls 26 111 1.57 6 164 1.27 

Boys 29 110 1.32 8 148 1.42 

4 to <5 Girls 1 180 19 164 1.48 

Boys 4 99 1.62 18 136 1.30 

All girls 86 117 1.70 36 179 1.67 

All boys 

Total 

72 

162a 

104 

111 

1.46 

1.60 

42 

78b 

169 

174 

1.79 

1.73 a Age and/or sex not registered for 8 children; one untransformed value = 0.
 b Age not registered for 7 children; geometric mean LTM value = 140.
 

N = Number of subjects.
 

GM = Geometric mean.
 

LTM = Limiting tracer method.
 

GSD = Geometric standard deviation.
 

NA = Not available.
 

Source: Adapted from Van Wïjnen et al. (1990). 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Page Exposure Factors Handbook 

5-40 September 2011 
 

 

 

Table 5-6. Estimated Geometric Mean Limiting Tracer Method (LTM) Soil Ingestion Values of Children 

Attending Daycare Centers According to Age, Weather Category, and Sampling Period
 First Sampling Period Second Sampling Period 

Estimated Geometric Estimated Geometric 

Weather Category Age (years) N Mean 

LTM Value N Mean LTM Value 

(mg/day) (mg/day) 

Bad <1 3 94 3 67 

(>4 days/week 1 to <2 18 103 33 80 

precipitation) 2 to <3 33 109 48 91 

4 to <5 5 124 6 109 

Reasonable <1 1 61 

(2−3 days/week 1 to <2 10 96 

precipitation) 2 to <3 13 99 

3 to <4 19 94 

4 to <5 1 61 

Good <1 4 102 

(<2 days/week 1 to <2 42 229 

precipitation) 2 to <3 65 166 

3 to <4 67 138 

4 to <5 10 132 

N = Number of subjects. 

LTM = Limiting tracer method. 

Source: Van Wïjnen et al. (1990). 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-7. Estimated Soil Ingestion for Sample of Washington State Childrena 

Element Mean 

(mg/day) 

Median 

(mg/day) 

Standard Error of the 

Mean 

(mg/day) 

Range 

(mg/day)b 

Aluminum 38.9 25.3 14.4 –279.0 to 904.5 

Silicon 82.4 59.4 12.2 –404.0 to 534.6 

Titanium 245.5 81.3 119.7 –5,820.8 to 6,182.2 

Minimum 38.9 25.3 12.2 –5,820.8 

Maximum 245.5 81.3 119.7 6,182.2 a Excludes three children who did not provide any samples (N = 101). b Negative values occurred as a result of correction for non-soil sources of the tracer elements. For aluminum, lower end of range 

published as 279.0 mg/day in article appears to be a typographical error that omitted the negative sign. 

Source: Adapted from Davis et al. (1990). 

Exposure Factors Handbook Page
 

September 2011 5-41 
 

 

 

Table 5-8. Soil Ingestion Estimates for 64 Anaconda Children 

Tracer Estimated Soil Ingestion (mg/day) 

p1 p50 p75 p90 p95 Max Mean SD 

Al –202.8 –3.3 17.7 66.6 94.3 461.1 2.7 95.8 

Ce –219.8 44.9 164.6 424.7 455.8 862.2 116.9 186.1 

La –10,673 84.5 247.9 460.8 639.0 1,089.7 8.6 1,377.2 

Nd –387.2 220.1 410.5 812.6 875.2 993.5 269.6 304.8 

Si –128.8 –18.2 1.4 36.9 68.9 262.3 –16.5 57.3 

Ti –15,736 11.9 398.2 1,237.9 1,377.8 4,066.6 –544.4 2,509.0 

Y –441.3 32.1 85.0 200.6 242.6 299.3 42.3 113.7 

Zr –298.3 –30.8 17.7 94.6 122.8 376.1 –19.6 92.5 

BTM soil NA 20.1 68.9 223.6 282.4 609.9 65.5 120.3 

BTM dust NA 26.8 198.1 558.6 613.6 1,499.4 127.2 299.1 

p = Percentile. 

SD = Standard deviation. 

BTM = Best Tracer Methodology. 

NA Not available. 

Note: Negative values are a result of limitations in the methodology. 

Source: Calabrese et al. (1997b). 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-9. Soil Ingestion Estimates for Massachusetts Children Displaying Soil Pica Behavior (mg/day) 

Study day Al-based estimate Si-based estimate Ti-based estimate 

1 53 9 153 

2 7,253 2,704 5,437 

3 2,755 1,841 2,007 

4 725 534 801 

5 5 –10 21 

6 1,452 1,373 794 

7 238 76 84 

Note: Negative values are a result of limitations in the methodology. 

Source: Calabrese et al. (1997a). 

Page Exposure Factors Handbook 

5-42 September 2011 
 

Table 5-10. Average Daily Soil and Dust Ingestion Estimate (mg/day) 

Type of Estimate Soil Ingestion Dust Ingestion 

Al Si Ti Al Si Ti 

Mean 168 89 448 260 297 415 

Median 7 0 32 13 2 66 

SD 510 270 1,056 759 907 1,032 

Range –15 to +1,783 –46 to +931 –47 to +3,581 –39 to +2,652 –351 to +3,145 –98 to +3,632 

SD = Standard deviation. 

Note: Negative values are a result of limitations in the methodology. 

Source: Calabrese et al. (1997a). 

 

 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-11. Mean and Median Soil Ingestion (mg/day) by Family Member 

Participant Tracer Element Estimated Soil Ingestiona (mg/day) Maximum Mean Median SD 

Childb 

Motherc 

Fatherd 

Aluminum 36.7 33.3 35.4 107.9 

Silicon 38.1 26.4 31.4 95.0 

Titanium 206.9 46.7 277.5 808.3 

Aluminum 92.1 0 218.3 813.6 

Silicon 23.2 5.2 37.0 138.1 

Titanium 359.0 259.5 421.5 1,394.3 

Aluminum 68.4 23.2 129.9 537.4 

Silicon 26.1 0.2 49.0 196.8 

Titanium 624.9 198.7 835.0 2,899.1 

a 

b 

c 

d 

SD 

Source: 

For some study participants, estimated soil ingestion resulted in a negative value. These estimates have been set to 0 mg/day for 

tabulation and analysis. 

Results based on 12 children with complete food, excreta, and soil data. 

Results based on 16 mothers with complete food, excreta, and soil data. 

Results based on 17 fathers with complete food, excreta, and soil data. 

= Standard deviation. 

Davis and Mirick (2006). 

Exposure Factors Handbook Page
 

September 2011 5-43 
 

 

Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children 

Child Month Estimated soil ingestion (mg/day) 

11 1 

2 

3 

4 

55 

1,447 

22 

40 

12 1 

2 

3 

4 

0 

0 

7,924 

192 

14 1 

2 

3 

4 

1,016 

464 

2,690 

898 

18 1 

2 

3 

4 

30 

10,343 

4,222 

1,404 

22 1 

2 

3 

4 

0 

-

5,341 

0 

27 1 

2 

3 

4 

48,314 

60,692 

51,422 

3,782 

-

Source: 

= No data. 

Calabrese and Stanek (1993). 

 

 

 

 

Table 5-13. Positive/Negative Error (bias) in Soil Ingestion Estimates in Calabrese et al. (1989) Study: Effect 

on Mean Soil Ingestion Estimate (mg/day)a 

Negative Error 

Tracer Lack of Fecal 

Sample on Final 

Study Day 

Other Causeb Total Negative 

Error 

Total Positive 

Error Net Error Original Mean Adjusted Mean 

Aluminum 14 11 25 43 +18 153 136 

Silicon 15 6 21 41 +20 154 133 

Titanium 82 187 269 282 +13 218 208 

Vanadium 66 55 121 432 +311 459 148 

Yttrium 8 26 34 22 –12 85 97 

Zirconium 6 91 97 5 –92 21 113 a	 How to read table: for example, aluminum as a soil tracer displayed both negative and positive error. The cumulative total negative 

error is estimated to bias the mean estimate by 25 mg/day downward. However, aluminum has positive error biasing the original mean 

upward by 43 mg/day. The net bias in the original mean was 18 mg/day positive bias. Thus, the original 156 mg/day mean for 

aluminum should be corrected downward to 136 mg/day. b	 Values indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day. 

Source:	 Calabrese and Stanek (1995). 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Page Exposure Factors Handbook 

5-44 September 2011 
 

 

 

 

 

 

Table 5-14. Predicted Soil and Dust Ingestion Rates for Children Age 3 to <6 Years (mg/day) 

Percentile Mean 5 25 50 75 95 100 

Dust ingestion/hand­ 1,000 19.8 0.6 3.4 8.4 21.3 73.7 649.3 to-mouth 

Dust ingestion/ 1,000 6.9 0.1 0.7 2.4 7.4 27.2 252.7 object-to-mouth 

Total dust ingestiona 1,000 27 13 109 360 

Soil ingestion/hand­ 1,000 41.0 0.2 5.3 15.3 44.9 175.6 1,367.4 to-mouth 

Total ingestion 1,000 67.6 4.9 16.8 37.8 83.2 224.0 1,369.7 a Email from Haluk Özkaynak (NERL, U.S. EPA) to Jacqueline Moya (NCEA, EPA) dated 3/8/11. 

Source: Özkaynak et al. (2011). 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-15. Estimated Daily Soil Ingestion for East Helena, Montana Children 

Estimation Method 

Mean 

(mg/day) 

Median 

(mg/day) 

Standard Deviation 

(mg/day) 

Range 

(mg/day) 

95th Percentile 

(mg/day) 

Geometric Mean 

(mg/day) 

Aluminum 181 121 203 25−1,324 584 

Silicon 184 136 175 31−799 578 

Titanium 1,834 618 3,091 4−17,076 9,590 

Minimum 108 88 121 4−708 386 

128 

130 

401 

65 

Source: Binder et al. (1986). 

Exposure Factors Handbook Page
 

September 2011 5-45 
 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-16. Estimated Soil Ingestion for Sample of Dutch Nursery School Children 

Child Sample 

Number 

Soil Ingestion as 

Calculated from Ti 

(mg/day) 

Soil Ingestion as 

Calculated from Al 

(mg/day) 

Soil Ingestion as 

Calculated from AIR 

(mg/day) 

Limiting Tracer 

(mg/day) 

1 L3 

L14 

L25 

103 

154 

130 

300 

211 

23 

107 

172 

-

103 

154 

23 

2 L5 

L13 

L27 

131 

184 

142 

-

103 

81 

71 

82 

84 

71 

82 

81 

3 L2 

L17 

124 

670 

42 

566 

84 

174 

42 

174 

4 L4 

L11 

246 

2,990 

62 

65 

145 

139 

62 

65 

5 L8 

L21 

293 

313 

-

-

108 

152 

108 

152 

6 L12 

L16 

1,110 

176 

693 

-

362 

145 

362 

145 

7 L18 

L22 

11,620 

11,320 

-

77 

120 

-

120 

77 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

L1 

L6 

L7 

L9 

L10 

L15 

L19 

L20 

L23 

L24 

L26 

3,060 

624 

600 

133 

354 

2,400 

124 

269 

1,130 

64 

184 

82 

979 

200 

-

195 

-

71 

212 

51 

566 

56 

96 

111 

124 

95 

106 

48 

93 

274 

84 

-

-

82 

111 

124 

95 

106 

48 

71 

212 

51 

64 

56 

Arithmetic Mean 1,431 232 129 105 

- = No data. 

AIR = Acid insoluble residue. 

Source: Adapted from Clausing et al. (1987). 

Table 5-17. Estimated Soil Ingestion for Sample of Dutch Hospitalized, Bedridden Children 

Child Sample 

Soil Ingestion as Calculated 

from Ti 

(mg/day) 

Soil Ingestion as Calculated 

from Al 

(mg/day) 

Limiting Tracer 

(mg/day) 

1 G5 

G6 

3,290 

4,790 

57 

71 

57 

71 

2 G1 28 26 26 

3 G2 

G8 

6,570 

2,480 

94 

57 

84 

57 

4 G3 28 77 28 

5 G4 1,100 30 30 

6 G7 58 38 38 

Arithmetic Mean 2,293 56 49 

Source: Adapted from Clausing et al. (1987). 

Page Exposure Factors Handbook 

5-46 September 2011 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-18. Items Ingested by Low-Income Mexican-Born Women Who Practiced 

Pica During Pregnancy in the United States (N = 46) 

Item Ingested Number (%) Ingesting Items 

Dirt 11 (24) 

Bean stonesa 17 (37) 

Magnesium carbonate 8 (17) 

Ashes 5 (11) 

Clay 4 (9) 

Ice 18 (39) 

Otherb 17 (37) a Little clods of dirt found among unwashed beans. b Including eggshells, starch, paper, lipstick, pieces of clay pot, and adobe. 

N = Number of individuals reporting pica behavior. 

Source: Simpson et al. (2000). 

Table 5-19. Distribution of Average (mean) Daily Soil Ingestion Estimates per Child for 64 Childrena (mg/day) 

Type of Estimate Overall Al Ba Mn Si Ti V Y Zr 

Number of Samples 64 64 33 19 63 56 52 61 62 

Mean 179 122 655 1,053 139 271 112 165 23 

25th Percentile 10 10 28 35 5 8 8 0 0 

50th Percentile 45 19 65 121 32 31 47 15 15 

75th Percentile 88 73 260 319 94 93 177 47 41 

90th Percentile 186 131 470 478 206 154 340 105 87 

95th Percentile 208 254 518 17,374 224 279 398 144 117 

Maximum 7,703 4,692 17,991 17,374 4,975 12,055 845 8,976 208 a For each child, estimates of soil ingestion were formed on days 4–8 and the mean of these estimates was then evaluated for each child. 

The values in the column “overall” correspond to percentiles of the distribution of these means over the 64 children. When specific 

trace elements were not excluded via the relative standard deviation criteria, estimates of soil ingestion based on the specific trace 

element were formed for 108 days for each subject. The mean soil ingestion estimate was again evaluated. The distribution of these 

means for specific trace elements is shown. 

Source: Stanek and Calabrese (1995a). 

Exposure Factors Handbook Page
 

September 2011 5-47 
 

 

 

 

 

 

 

 

 

 

c 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-20. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on 

Data for 64 Subjects Projected Over 365 Daysa 

Range 1−2,268 mg/dayb 

50th Percentile (median) 75 mg/day 

90th Percentile 1,190 mg/day 

95th Percentile 1,751 mg/day a Based on fitting a lognormal distribution to model daily soil ingestion values. b Subject with pica excluded. 

Source: Stanek and Calabrese (1995a). 

Table 5-21. Prevalence of Non-Food Consumption by Substance for NHANES I and NHANES II 

NHANES I (age 1−74 years) NHANES II (age 6 months−74 years) 

N (sample size) = 20,724 (unweighted); N (sample size) = 25,271 (unweighted); 

193,716,939 (weighted) 203,432,944 (weighted) 

Substance 

N 

Unweighted 

(Weighted) 

Prevalencea 95% Confidence 

Interval 

N 

Unweighted 

(Weighted) 

Prevalencea 95% Confidence 

Interval 

Any Non-Food 

Substance 

732 

(4,900,370) 2.5% 2.2−2.9% 480 (2,237,993) 1.1% 1.0−1.2% 

Clay 46 

(223,361) 0.1% 0.1−0.2% 

Starch 131 

(582,101) 0.3% 0.2−0.4% 61 (450,915) 0.2% 0.1−0.3% 

Paint and 

Plaster 

39 

(195,764) 0.5%b 0.3−0.7% 55 (213,588) 0.6%c 0.4−0.8% 

Dirt 216 

(772,714) 2.1%d 1.7−2.5% 

Dirt and Clay 385 

(2,466,210) 1.3% 1.1−1.5% 

Other 190 

(1,488,327) 0.8% 0.6−0.9% 218 (1,008,476) 0.5% 0.4−0.6% 

Unweighted = Raw counts. 

Weighted	 = Adjusted to account for the unequal selection probabilities caused by the cluster design, item non-response, and planned 

oversampling of certain subgroups, and representative of the civilian non-institutionalized Census population in the coterminous 

United States. a	 Prevalence = Frequency (n) (weighted)/Sample Size (N) (weighted). b NHANES I sample size (<12 years): 4,968 (unweighted); 40,463,951 (weighted). 

NHANES II sample size (<12 years): 6,834 (unweighted); 37,697,059 (weighted). d	 For those aged <12 years only; question not prompted for those >12 years. 

Source:	 Gavrelis et al. (2011). 

Page Exposure Factors Handbook 

5-48 September 2011 
 

 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Table 5-22. Summary of Estimates of Soil and Dust Ingestion by Adults and Children (0.5 to 14 years old) 

From Key Studies (mg/day) 

Sample 

Size Age (year) Ingestion medium Mean p25 p50 p75 p90 p95 Reference 

140 1 to13+ Soil 50,000a NR NR NR NR NR Vermeer and Frate 

(1979) 

89 Adult Soil 50,000a NR NR NR NR NR Vermeer and Frate 

(1979) 

52 0.3 to14 Soil NR NR NR NR ~1,267 ~4,000 Wong (1988); 

Calabrese and 

Stanek (1993) 

64 1 to <4 Soil 

Dust 

Soil and Dust 

–294 to +459 

–1,289 to +964 

–496 to +483 

NR 

NR 

NR 

–261 to +96 

–340 to +127 

–340 to +456 

NR 

NR 

NR 

67 to 1,366 

91 to 1,700 

89 to 1,701 

106 to 1,903 

160 to 2,916 

159 to 3,174 

Calabrese et al. 

(1989) 

292 0.1 to <1 

1 to <5 

Soil 

Soil 

0 to 30b 

0 to 200b 

NR 

NR 

NR 

NR 

NR 

NR 

NR 

≤300

NR 

NR 

Van Wijnen et al. 

(1990) 

101 2 to <8 Soil 39 to 246 NR 25 to 81 NR NR NR Davis et al. (1990) 

Soil and Dust 65 to 268 NR 52 to 117 NR NR NR 

64 1 to <4 Soil 97 to 208 NR NR NR NR NR Calabrese and 

Stanek (1995) 

165 1 to <8 Soil 104 NR 37 NR NR 217 Stanek and 

Calabrese (1995b) 

64 1 to <4 Soil –544 to +270 –582to +65 –31 to +220 1 to 411 37 to 1,238 69 to 1,378 Calabrese et al. 

(1997b) 

478 <1 to <7 Soil and Dust 113 NR NR NR NR NR Hogan et al. (1998) 

33 Adult Soil 23 to 625 NR 0 to 260 NR NR 138 to 2,899 Davis and Mirick 

(2006) 

12 3 to <8 Soil 37 to 207 NR 26 to 47 NR NR 95 to 808 Davis and Mirick 

(2006) 

1,000c 3 to <6 Soil 

Dust 

Soil and Dust 

41 

27 

68 

5.3 

NR 

16.8 

15.3 

13 

37.8 

44.9 

NR 

83.2 

NR 

NR 

NR 

175.6 

109 

224 

Özkaynak et al. 

(2011) 

a Average includes adults and children. b Geometric mean. c Simulated. 

NR = Not reported. 

p = Percentile. 

Table 5-23. Comparison of Hogan et al. (1998) Study Subjects’ Predicted Blood Lead Levels With Actual 

Measured Blood Lead Levels, and Default Soil + Dust Intakes Used in IEUBK Modeling 

Age 

(year) 

N N 

prediction >actual 

N 

prediction <actual 

time-averaged default 

soil + dust intake (mg/day) 

1 and 2 164 14 150 135 

3 and 4 142 104 38 117.5 

5 and 6 134 0 134 87.5 

Average 113 

N = Number. 

Source: Adapted from Hogan et al. (1998). 

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Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Figure 5-1. Prevalence of Non-Food Substance Consumption by Age, NHANES I and NHANES II. 

Source: Gavrelis et al. (2011). 

Page Exposure Factors Handbook 

5-50 September 2011 
Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Figure 5-2. Prevalence of Non-Food Substance Consumption by Race, NHANES I and NHANES II. 

Source: Gavrelis et al. (2011). 

Exposure Factors Handbook Page
 

September 2011 5-51 
 

 

Exposure Factors Handbook 

Chapter 5—Soil and Dust Ingestion 

Figure 5-3. Prevalence of Non-Food Substance Consumption by Income, NHANES I and NHANES II. 

Source: Gavrelis et al. (2011). 

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5-52 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

6. INHALATION RATES 

6.1. INTRODUCTION 

Ambient and indoor air are potential sources of 

exposure to toxic substances. Adults and children can 

be exposed to contaminated air during a variety of 

activities in different environments. They may be 

exposed to contaminants in ambient air and may also 

inhale chemicals from the indoor use of various 

sources (e.g., stoves, heaters, fireplaces, and 

consumer products) as well as from those that 

infiltrate from ambient air. 

The Agency defines exposure as the chemical 

concentration at the boundary of the body (U.S. EPA, 

1992). In the case of inhalation, the situation is 

complicated by the fact that oxygen exchange with 

carbon dioxide takes place in the distal portion of the 

lung. The anatomy and physiology of the respiratory 

system as well as the characteristics of the inhaled 

agent diminishes the pollutant concentration in 

inspired air (potential dose) such that the amount of a 

pollutant that actually enters the body through the 

upper respiratory tract (especially the 

nasal-pharyngeal and tracheo-bronchial regions) and 

lung (internal dose) is less than that measured at the 

boundary of the body. A detailed discussion of this 

concept can be found in Guidelines for Exposure 

Assessment (U.S. EPA, 1992). Suggestions for further 

reading on the anatomy and physiology of the 

respiratory system include Phalen et al. (1990), Bates 

(1989), Cherniack (1972), Forster et al. (1986), and 

West (2008a, b). When constructing risk assessments 

that concern the inhalation route of exposure, one 

must be aware of any adjustments that have been 

employed in the estimation of the pollutant 

concentration to account for this reduction in 

potential dose. 

There are also a number of resources available in 

the literature describing various approaches and 

techniques related to inhalation rate estimates, 

including Ridley et al. (2008), Ridley and Olds 

(2008), Speakman and Selman (2003), Thompson et 

al. (2009), and Westerterp (2003). 

Inclusion of this chapter in the Exposure Factors 

Handbook does not imply that assessors will always 

need to select and use inhalation rates when 

evaluating exposure to air contaminants. For 

example, it is unnecessary to calculate inhaled dose 

when using dose-response factors from the Integrated 

Risk Information System (IRIS) (U.S. EPA, 1994), 

because the IRIS methodology accounts for 

inhalation rates in the development of 

“dose-response” relationships. Information in this 

chapter may be used by toxicologists in their 

derivation of human equivalent concentrations 

(HECs), where adjustments are usually required to 

account for differences in exposure scenarios or 

populations (U.S. EPA, 1994). Inhalation dosimetry 

and the factors affecting the disposition of particles 

and gases that may be deposited or taken up in the 

respiratory tract are discussed in more detail in the 

U.S. Environmental Protection Agency’s (EPA’s) 

report on Methods for Derivation of Inhalation 

Reference Concentrations (RfCs) and Application of 

Inhalation Dosimetry (U.S. EPA, 1994). When using 

IRIS for inhalation risk assessments, “dose-response” 

relationships require only an average air 

concentration to evaluate health concerns: 

 For non-carcinogens, IRIS uses Reference 

Concentrations (RfCs), which are expressed in 

concentration units. Hazard is evaluated by 

comparing the inspired air concentration to the 

RfC. 

 For carcinogens, IRIS uses unit risk values, 

which are expressed in inverse concentration 

units. Risk is evaluated by multiplying the 

unit risk by the inspired air concentration. 

Detailed descriptions of the IRIS methodology for 

derivation of inhalation RfCs can be found in two 

methods manuals produced by the Agency (U.S. 

EPA, 1994, 1992). 

The Superfund Program has also updated its 

approach for determining inhalation risk, eliminating 

the use of inhalation rates when evaluating exposure 

to air contaminants (U.S. EPA, 2009b). The current 

methodology recommends that risk assessors use the 

concentration of the chemical in air as the exposure 

metric (e.g., mg/m3

), instead of the intake of a 

contaminant in air based on inhalation rate and body 

weight (e.g., mg/kg-day). 

Due to their size, physiology, behavior, and 

activity level, the inhalation rates of children differ 

from those of adults. Infants and children have a 

higher resting metabolic rate and oxygen 

consumption rate per unit of body weight than adults 

because of their rapid growth and relatively larger 

lung surface area (SA) per unit of body weight. For 

example, the oxygen consumption rate for a resting 

infant between 1 week and 1 year of age is 

7 milliliters per kilogram of body weight (mL/kg) per 

minute, while the rate for an adult under the same 

conditions is 3−5 mL/kg per minute (WHO, 1986). 

Thus, while greater amounts of air and pollutants are 

inhaled by adults than children over similar time 

periods on an absolute basis, the relative volume of 

air passing through the lungs of a resting infant is up 

to twice that of a resting adult on a body-weight 

basis. It should be noted that lung volume is 

correlated, among other factors, with a person’s 

Exposure Factors Handbook Page 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

height. Also, people living in higher altitudes have 

larger lung capacity than those living at sea level. 

Children’s inhalation dosimetry and health effects 

were topics of discussion at a U.S. Environmental 

Protection Agency workshop held in June 2006 (Foos 

and Sonawane, 2008). Age-related differences in lung 

structure and function, breathing patterns, and how 

these affect the inhaled dose and the deposition of 

particles in the lung are important factors in assessing 

risks from inhalation exposures (Foos et al., 2008). 

Children more often than adults, breathe through 

their mouths and, therefore, may have a lesser nasal 

contribution to breathing during rest and while 

performing various activities. The uptake of particles 

in the nasal airways is also less efficient in children 

(Bennett et al., 2008). Thus, the deposition of 

particles in the lower respiratory tract may be greater 

in children (Foos et al., 2008). In addition, the rate of 

fine particle deposition has been significantly 

correlated with increased body mass index (BMI), an 

important point as childhood obesity becomes a 

greater issue (Bennett and Zeman, 2004). 

Recommended inhalation rates (both long- and 

short-term) for adults and children are provided in 

Section 6.2, along with the confidence ratings for 

these recommendations, which are based on four key 

studies identified by U.S. EPA for this factor. 

Long-term inhalation is repeated exposure for more 

than 30 days, up to approximately 10% of the life 

span in humans (more than 30 days). Long-term 

inhalation rates for adults and children (including 

infants) are presented as daily rates (m3

/day). 

Short-term exposure is repeated exposure for more 

than 24 hours, up to 30 days. Short-term inhalation 

rates are reported for adults and children (including 

infants) performing various activities in m3

/minute. 

Following the recommendations, the available studies 

(both key and relevant studies) on inhalation rates are 

summarized. 

6.2. RECOMMENDATIONS 

The recommended inhalation rates for adults and 

children are based on three recent studies (U.S. EPA, 

2009a; Stifelman, 2007; Brochu et al., 2006b), as 

well as an additional study of children (Arcus-Arth 

and Blaisdell, 2007). These studies represent an 

improvement upon those previously used for 

recommended inhalation rates in earlier versions of 

this handbook, because they use a large data set that 

is representative of the United States as a whole and 

consider the correlation between body weight and 

inhalation rate. 

The selection of inhalation rates to be used for 

exposure assessments depends on the age of the 

exposed population and the specific activity levels of 

this population during various exposure scenarios. 

Table 6-1 presents the recommended long-term 

values for adults and children (including infants) for 

use in various exposure scenarios. For children, the 

age groups included are from U.S. EPA’s Guidance 

on Selecting Age Groups for Monitoring and 

Assessing Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005a). Section 6.3.5 

describes how key studies were combined to derive 

the mean and 95th percentile inhalation rate values 

and the concordance between the age groupings used 

for adults and children in this chapter and the original 

age groups in the key studies. 

As shown in Table 6-1, the daily average 

inhalation rates for long-term exposures for children 

(males and females combined, unadjusted for body 

weight) range from 3.5 m3

/day for children from 1 to 

<3 months to 16.3 m3

/day for children aged 16 to <21 

years. Mean values for adults range from 12.2 m3

/day 

(81 years and older) to 16.0 m3

/day (31 to <51 years). 

The 95th percentile values for children range from 

5.8 m3

/day (1 to <3 months) to 24.6 m3/day (16 to 

<21 years) and for adults range from 15.7 m3

/day 

(81 years and older) to 21.4 m3

/day (31 to <41 years). 

The mean and 95th percentile values shown in 

Table 6-1 represent averages of the inhalation rate 

data from the key studies for which data were 

available for selected age groups. 

It should be noted that there may be a high degree 

of uncertainty associated with the upper percentiles. 

These values represent unusually high estimates of 

caloric intake per day and are not representative of 

the average adult or child. For example, using 

Layton’s equation (Layton, 1993) for estimating 

metabolically consistent inhalation rates to calculate 

caloric equivalence (see Section 6.4.9), the 

95th percentile value for 16 to <21-year-old children 

is greater than 4,000 kcal/day (Stifelman, 2003). All 

of the 95th percentile values listed in Table 6-1 

represent unusually high inhalation rates for 

long-term exposures, even for the upper end of the 

distribution, but were included in this handbook to 

provide exposure assessors a sense of the possible 

range of inhalation rates for adults and children. 

These values should be used with caution when 

estimating long-term exposures. 

Short-term mean and 95th percentile data in 

m3

/minute are provided in Table 6-2 for males and 

females combined for adults and children for whom 

activity patterns are known. These values represent 

averages of the activity level data from the one key 

study from which short-term inhalation rate data were 

available (U.S. EPA, 2009a). 

Table 6-3 shows the confidence ratings for the 

inhalation rate recommendations. Table 6-4, 

Table 6-6 through Table 6-8, Table 6-10, Table 6-14, 

Table 6-15, and Table 6-17 through Table 6-20 

provide multiple percentiles for long- and short-term 

inhalation rates for both males and females. 

Page Exposure Factors Handbook 

6-2 September 2011 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-1. Recommended Long-Term Exposure Values for Inhalation (males and females combined) 

Age Groupa 

Mean 

(m3/day) 

Sources 

Used for 

Means 

95th Percentileb 

(m3/day) 

Sources Used 

for 95th 

Percentiles Multiple Percentiles 

Birth to <1 

month 

3.6 c 7.1 c 

See Table 6-4, Table 6-6 

through Table 6-8, 

Table 6-10, Table 6-14 

Table 6-15 [none 

available for Stifelman 

(2007)] 

1 to <3 months 3.5 c, d 5.8 c, d 

3 to <6 months 4.1 c, d 6.1 c, d 

6 to <12 months 5.4 c, d 8.0 c, d 

Birth to <1 year 5.4 c, d, e, f 9.2 c, d, e 

1 to <2 years 8.0 c, d, e, f 12.8 c, d, e 

2 to <3 years 8.9 c, d, e, f 13.7 c, d, e 

3 to <6 years 10.1 c, d, e, f 13.8 c, d, e 

6 to <11 years 12.0 c, d, e, f 16.6 c, d, e 

11 to <16 years 15.2 c, d, e, f 21.9 c, d, e 

16 to <21 years 16.3 c, d, e, f 24.6 c, d, e 

21 to <31 years 15.7 d, e, f 21.3 d, e 

31 to <41 years 16.0 d, e, f 21.4 d, e 

41 to <51 years 16.0 d, e, f 21.2 d, e 

51 to <61 years 15.7 d, e, f 21.3 d, e 

61 to <71 years 14.2 d, e, f 18.1 d, e 

71 to <81 years 12.9 d, e 16.6 d, e 

≥81 years 12.2 d, e 15.7 d, e 

a When age groupings in the original reference did not match the U.S. EPA groupings used for this 

handbook, means from all age groupings in the original reference that overlapped U.S. EPA’s age 

groupings by more than one year were averaged, weighted by the number of observations 

contributed from each age group. Similar calculations were performed for the 95th percentiles. 

See Table 6-25 for concordance with U.S. EPA age groupings. b Some 95th percentile values may be unrealistically high and not representative of the average 

person. c Arcus-Arth and Blaisdell (2007). d Brochu et al. (2006b). e U.S. EPA (2009a). f Stifelman (2007). 

Exposure Factors Handbook Page 

September 2011 6-3 
 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-2. Recommended Short-Term Exposure Values for Inhalation (males and females combined) 

Activity Level 

Age Group 

(years) 

Mean 

(m3/minute) 

95th Percentile 

(m3/minute) Multiple Percentiles 

Sleep or Nap Birth to <1 3.0E−03 4.6E−03 

See Table 6-17 and 

Table 6-19 

1 to <2 4.5E−03 6.4E−03 

2 to <3 4.6E−03 6.4E−03 

3 to <6 4.3E−03 5.8E−03 

6 to <11 4.5E−03 6.3E−03 

11 to <16 5.0E−03 7.4E−03 

16 to <21 4.9E−03 7.1E−03 

21 to <31 4.3E−03 6.5E−03 

31 to <41 4.6E−03 6.6E−03 

41 to <51 5.0E−03 7.1E−03 

51 to <61 5.2E−03 7.5E−03 

61 to <71 5.2E−03 7.2E−03 

71 to <81 5.3E−03 7.2E−03 

≥81 5.2E−03 7.0E−03 

Sedentary/ 

Passive 

Birth to <1 3.1E−03 4.7E−03 

1 to <2 4.7E−03 6.5E−03 

2 to <3 4.8E−03 6.5E−03 

3 to <6 4.5E−03 5.8E−03 

6 to <11 4.8E−03 6.4E−03 

11 to <16 5.4E−03 7.5E−03 

16 to <21 5.3E−03 7.2E−03 

21 to <31 4.2E−03 6.5E−03 

31 to <41 4.3E−03 6.6E−03 

41 to <51 4.8E−03 7.0E−03 

51 to <61 5.0E−03 7.3E−03 

61 to <71 4.9E−03 7.3E−03 

71 to <81 5.0E−03 7.2E−03 

≥81 4.9E−03 7.0E−03 

Light Intensity Birth to <1 7.6E−03 1.1E−02 

1 to <2 1.2E−02 1.6E−02 

2 to <3 1.2E−02 1.6E−02 

3 to <6 1.1E−02 1.4E−02 

6 to <11 1.1E−02 1.5E−02 

11 to <16 1.3E−02 1.7E−02 

16 to <21 1.2E−02 1.6E−02 

Page Exposure Factors Handbook 

6-4 September 2011 
 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-2. Recommended Short-Term Exposure Values for Inhalation (males and females combined) 

(continued) 

Activity Level 

Age Group 

(year) 

Mean 

(m3/minute) 

95th Percentile 

(m3/minute) Multiple Percentiles 

Light Intensity 

(continued) 

21 to <31 1.2E−02 1.6E−02 

31 to <41 1.2E−02 1.6E−02 

41 to <51 1.3E−02 1.6E−02 

51 to <61 1.3E−02 1.7E−02 

61 to <71 1.2E−02 1.6E−02 

71 to <81 1.2E−02 1.5E−02 

≥81 1.2E−02 1.5E−02 

Moderate 

Intensity 

Birth to <1 1.4E−02 2.2E−02 

1 to <2 2.1E−02 2.9E−02 

2 to <3 2.1E−02 2.9E−02 

3 to <6 2.1E−02 2.7E−02 

6 to <11 2.2E−02 2.9E−02 

11 to <16 2.5E−02 3.4E−02 

16 to <21 2.6E−02 3.7E−02 

21 to <31 2.6E−02 3.8E−02 

31 to <41 2.7E−02 3.7E−02 

41 to <51 2.8E−02 3.9E−02 

51 to <61 2.9E−02 4.0E−02 

61 to <71 2.6E−02 3.4E−02 

71 to <81 2.5E−02 3.2E−02 

≥81 2.5E−02 3.1E−02 

High Intensity Birth to <1 2.6E−02 4.1E−02 

1 to <2 3.8E−02 5.2E−02 

2 to <3 3.9E−02 5.3E−02 

3 to <6 3.7E−02 4.8E−02 

6 to <11 4.2E−02 5.9E−02 

11 to <16 4.9E−02 7.0E−02 

16 to <21 4.9E−02 7.3E−02 

21 to <31 5.0E−02 7.6E−02 

31 to <41 4.9E−02 7.2E−02 

41 to <51 5.2E−02 7.6E−02 

51 to <61 5.3E−02 7.8E−02 

61 to <71 4.7E−02 6.6E−02 

71 to <81 4.7E−02 6.5E−02 

≥81 4.8E−02 6.8E−02 

Source: U.S. EPA (2009a). 

Exposure Factors Handbook Page 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-3. Confidence in Recommendations for Long- and Short-Term Inhalation Rates 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The survey methodology and data analysis was 

adequate. Measurements were made by indirect 

methods. The studies analyzed existing primary 

data. 

Potential bias within the studies was fairly well 

documented. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data-Collection Period 

The studies focused on inhalation rates and factors 

influencing them. 

The studies focused on the U.S. population. A wide 

range of age groups were included. 

The studies were published during 2006 and 2009 

and represent current exposure conditions. 

The data-collection period for the studies may not be 

representative of long-term exposures. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

All key studies are available from the peer-reviewed 

literature. 

The methodologies were clearly presented; enough 

information was included to reproduce most results. 

Information on ensuring data quality in the key 

studies was limited. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

In general, the key studies addressed variability in 

inhalation rates based on age and activity level. 

Although some factors affecting inhalation rate, such 

as body mass, are discussed, other factors (e.g., 

ethnicity) are omitted. 

Multiple sources of uncertainty exist for these 

studies. Assumptions associated with energy 

expenditure (EE)-based estimation procedures are a 

source of uncertainty in inhalation rate estimates. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

Three of the key studies appeared in peer-reviewed 

journals, and one key study is a U.S. EPA peerreviewed report. 

There are four key studies. The results of studies 

from different researchers are in general agreement. 

High 

Overall Rating Medium 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

6.3.	 KEY INHALATION RATE STUDIES 

6.3.1.	 Brochu et al. (2006b)—Physiological 

Daily Inhalation Rates for Free-Living 

Individuals Aged 1 Month to 96 Years, 

Using Data From Doubly Labeled Water 

Measurements: A Proposal for Air 

Quality Criteria, Standard Calculations, 

and Health Risk Assessment 

Brochu et al. (2006b) calculated physiological 

daily inhalation rates (PDIRs) for 2,210 individuals 

aged 3 weeks to 96 years using the reported 

disappearance rates of oral doses of doubly labeled 

water (DLW) (2

H2O and H2

18O) in urine, monitored 

by gas-isotope-ratio mass spectrometry for an 

aggregate period of more than 30,000 days. DLW 

data were complemented with indirect calorimetry 

and nutritional balance measurements. 

In the DLW method, the disappearance of the 

stable isotopes deuterium (2

H) and heavy oxygen-18 

(

18O) are monitored in urine, saliva, or blood samples 

over a long period of time (from 7 to 21 days) after 

subjects receive oral doses of 2

H2O and H2

18O. The 

disappearance rate of 2

H reflects water output and 18 that of O represents water output plus carbon 

dioxide (CO2) production rates. The CO2 production 

rate is then calculated by finding the difference 

between the two disappearance rates. Total daily 

energy expenditures (TDEEs) are determined from 

CO2 production rates using classic respirometry 

formulas, in which values for the respiratory quotient 

(RQ = CO2 produced/O2 consumed) are derived from the 

composition of the diet during the period of time of 

each study. The DLW method also allows for 

measurement of the energy cost of growth (ECG). 

TDEE and ECG measurements can be converted into 

PDIR values using the following equation developed 

by Layton (1993): 

PDIR = (TDEE + ECG) × H × VQ × 10−3 (Eqn. 6-1) 

where: 

PDIR = physiological daily inhalation 

rates (m3

/day); 

TDEE = total daily energy expenditure 

(kcal/day); 

ECG = stored daily energy cost for 

growth (kcal/day); 

H =	 oxygen uptake factor, volume 

of 0.21 L of oxygen (at 

standard temperature and 

pressure, dry air) consumed to 

produce 1 kcal of energy 

expended; 

VQ = ventilatory equivalent (ratio of 

the minute volume [VE] at 

body temperature pressure 

saturation to the oxygen uptake 

rate [VO2] at standard 

temperature and pressure, dry 

air) VE/VO2 = 27; and 

10−3 = conversion factor (L/m3

). 

Brochu et al. (2006b) calculated daily inhalation 

rates (DIRs) (expressed in m3

/day and m3/kg-day) for 

the following age groups and physiological 

conditions: (1) healthy newborns aged 3 to 5 weeks 

old (N = 33), (2) healthy normal-weight males and 

females aged 2.6 months to 96 years (N = 1,252), 

(3) low-BMI subjects (underweight women, N = 17; 

adults from less affluent societies N = 59) and 

(4) overweight/obese individuals (N = 679), as well 

as (5) athletes, explorers, and soldiers when reaching 

very high energy expenditures (N = 170). Published 

data on BMI, body weight, basal metabolic rate 

(BMR), ECG, and TDEE measurements (based on 

DLW method and indirect calorimetry) for subjects 

aged 2.6 months to 96 years were used. Data for 

underweight, healthy normal-weight, and 

overweight/obese individuals were gathered and 

defined according to BMI cutoffs. Data for newborns 

were included regardless of BMI values because they 

were clinically evaluated as being healthy infants. 

Table 6-4 to Table 6-8 present the distribution of 

daily inhalation rates for normal-weight and 

overweight/obese individuals by sex and age groups. 

Table 6-9 presents mean inhalation rates for 

newborns. Due to the insufficient number of subjects, 

no distributions were derived for this group. 

An advantage of this study is that data are 

provided for age groups of less than 1 year. A 

limitation of this study is that data for individuals 

with pre-existing medical conditions were lacking. 

6.3.2.	 Arcus-Arth and Blaisdell (2007)— 

Statistical Distributions of Daily 

Breathing Rates for Narrow Age Groups 

of Infants and Children 

Arcus-Arth and Blaisdell (2007) derived daily 

breathing rates for narrow age ranges of children 

using the metabolic conversion method of Layton 

(1993) and energy intake (EI) data adjusted to 

represent the U.S. population from the Continuing 

Survey of Food Intake for Individuals (CSFII) 

1994−1996, 1998. Normalized (m3

/kg-day) and nonnormalized (m3

/day) breathing rates for children 

0−18 years of age were derived using the general 

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equation developed by Layton (1993) to calculate 

energy-dependent inhalation rates: 

VE = H × VQ × EE (Eqn. 6-2) 

where: 

VE = volume of air breathed per day 

(m3

/day), 

H = volume of oxygen consumed to 

produce 1 kcal of energy (m3

/kcal), 

VQ = ratio of the volume of air to the 

volume of oxygen breathed per unit 

time (unitless), and 

EE = energy (kcal) expended per day. 

Arcus-Arth and Blaisdell (2007) calculated H 

values of 0.22 and 0.21 for infants and non-infant 

children, respectively, using the 1977−1978 

Nationwide Food Consumption Survey (NFCS) and 

CSFII data sets. Ventilatory equivalent (VQ) data, 

including those for infants, were obtained from 

13 studies that reported VQ data for children aged 

4−8 years. Separate preadolescent (4−8 years) and 

adolescent (9−18 years) VQ values were calculated in 

addition to separate VQ values for adolescent boys 

and girls. Two-day-averaged daily EI values reported 

in the CSFII data set were used as a surrogate for EE. 

CSFII records that did not report body weight and 

those for children who consumed breast milk or were 

breast-fed were excluded from their analyses. The EIs 

of children 9 years of age and older were multiplied 

by 1.2, the value calculated by Layton (1993) to 

adjust for potential bias related to under-reporting of 

dietary intakes by older children. For infants, EI 

values were adjusted by subtracting the amount of 

energy put into storage by infants as estimated by 

Scrimshaw et al. (1996). Self-reported body weights 

for each individual from the CSFII data set were used 

to calculate non-normalized (m3

/day) and normalized 

(m3

/kg-day) breathing rates, which decreased the 

variability in the resulting breathing rate data. Daily 

breathing rates were grouped into three 1-month 

groups for infants, 1-year age groups for children 1 to 

18 years of age, and the age groups recommended by 

U.S. EPA Supplemental Guidance for Assessing 

Susceptibility from Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005b) to receive greater 

weighting for mutagenic carcinogens (0 to <2 years 

of age, and 2 to <16 years of age). Data were also 

presented for adolescent boys and girls, aged 9 to 

18 years (see Table 6-10). For each age and age-sex 

group, Arcus-Arth and Blaisdell (2007) calculated the 

arithmetic mean, standard error of the mean, 

percentiles (50th, 90th, and 95th), geometric mean, 

standard deviation, and best-fit parametric models of 

the breathing rate distributions. Overall, the 

CSFII-derived non-normalized breathing rates 

progressively increased with age from infancy 

through 18 years of age, while normalized breathing 

rates progressively decreased. The data are presented 

in Table 6-11 in units of m3

/day. There were 

statistical differences between boys and girls 9 to 

18 years of age, both for these years combined 

(p < 0.00) and for each year of age separately 

(p < 0.05). The authors reasoned that since the 

fat-free mass (basically muscle mass) of boys 

typically increases during adolescence, and because 

fat-free mass is highly correlated to basal metabolism 

which accounts for the majority of EE, nonnormalized breathing rates for adolescent boys may 

be expected to increase with increasing age. 

Table 6-11 presents the mean and 95th percentile 

values for males and females combined, averaged to 

fit within the standard U.S. EPA age groups. 

The CSFII-derived mean breathing rates derived 

by Arcus-Arth and Blaisdell (2007) were compared to 

the mean breathing rates estimated in studies that 

utilized DLW technique EE data that had been 

coupled with the Layton (1993) method. Infants’ 

breathing rates estimated using the CSFII data were 

15 to 27% greater than the comparison DLW EE 

breathing rates. In contrast, the children’s CSFII 

breathing rates ranged from 23% less to 14% greater 

than comparison rates. Arcus-Arth and Blaisdell 

(2007) concluded that taking into account the 

differences in methods, data, and some age 

definitions between the two sets of breathing rates, 

the CSFII and comparison rates were similar across 

age groups. 

An advantage of this study is that it provides 

breathing rates specific to narrow age ranges, which 

can be useful for assessing inhalation dose during 

periods of greatest susceptibility. However, the study 

is limited by the potential for misreporting, 

underestimating, or overestimating of food intake 

data in the CSFII. In addition to underreporting of 

food intake by adolescents, EI values for younger 

children may be under- or overestimated. Overweight 

children (or their parents) may also under-report food 

intakes. In addition, adolescents who misreport food 

intake may have also misreported body weights. 

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Chapter 6—Inhalation Rates 

6.3.3.	 Stifelman (2007)—Using Doubly Labeled 

Water Measurements of Human Energy 

Expenditure to Estimate Inhalation Rates 

Stifelman (2007) estimated inhalation rates using 

DLW energy data. The DLW method administers two 

forms of stable isotopically labeled water: 

deuterium-labeled (2

H2O) and 18oxygen-labeled 

(H2

18O). The difference in disappearance rates 

between the two isotopes represents the energy 

expended over a period of 1−3 half-lives of the 

labeled water (Stifelman, 2007). The resulting 

duration of observation is typically 1−3 weeks, 

depending on the size and activity level. 

The DLW database contains subjects from areas 

around the world and represents diversity in ethnicity, 

age, activity, body type, and fitness level. DLW data 

have been compiled by the Institute of Medicine 

(IOM) Panel on Macronutrients and the Food and 

Agriculture Organization of the United Nations. 

Stifelman (2007) used the equation of Layton (1993) 

to convert the recommended energy levels of IOM 

for the active to very-active people to their equivalent 

inhalation rates. The IOM reports recommend energy 

expenditure levels organized by sex, age, and body 

size (Stifelman, 2007). 

The equivalent inhalation rates are shown in Table 

6-12. Shown in Table 6-13 are the mean values for 

the IOM “active” energy level category, averaged to 

fit within the standard U.S. EPA age groups. 

Stifelman (2007) noted that the estimates based on 

the DLW are consistent with previous findings of 

Layton (1993) and the Exposure Factors Handbook 

(U.S. EPA, 1997) and that inhalation rates based on 

the IOM active classification are consistent with the 

mean inhalation rate in the handbook. 

The advantages of this study are that the 

inhalation rates were estimated using the DLW data 

from a large data set. Stifelman (2007) noted that 

DLW methods are advantageous; the data are robust, 

measurements are direct and avoid errors associated 

with indirect measurements (heart rate [HR]), 

subjects are free-living, and the period of observation 

is longer than what is possible from staged activity 

measures. Observations over a longer period of time 

reduce the uncertainties associated with using short 

duration studies to infer long-term inhalation rates. A 

limitation with the study is that the inhalation rates 

that are presented are for active/very active persons 

only. 

6.3.4.	 U.S. EPA (2009a)—Metabolically Derived 

Human Ventilation Rates: A Revised 

Approach Based Upon Oxygen 

Consumption Rates 

U.S. EPA (2009a) conducted a study to ascertain 

inhalation rates for children and adults. Specifically, 

U.S. EPA sought to improve upon the methodology 

used by Layton (1993) and other studies that relied 

upon the VQ and a linear relationship between 

oxygen consumption and fitness rate. A revised 

approach, developed by U.S. EPA’s National 

Exposure Research Laboratory, was used, in which 

an individual’s inhalation rate was derived from his 

or her assumed oxygen consumption rate. U.S. EPA 

applied this revised approach using body-weight data 

from the 1999−2002 National Health and Nutrition 

Examination Survey (NHANES) and metabolic 

equivalents of work (METS) data from U.S. EPA’s 

Consolidated Human Activity Database (CHAD). In 

this database, metabolic cost is given in units of 

“METS” or “metabolic equivalents of work,” an 

energy expenditure metric used by exercise 

physiologists and clinical nutritionists to represent 

activity levels. An activity’s METS value represents a 

dimensionless ratio of its metabolic rate (energy 

expenditure) to a person’s resting, or BMR. 

NHANES provided age, sex, and body-weight 

data for 19,022 individuals from throughout the 

United States. From these data, BMR was estimated 

using an age-specific linear equation used in the 

Exposure Factors Handbook (U.S. EPA, 1997), and 

in several other studies and reference works. 

The CHAD database is a compilation of several 

databases of human activity patterns. U.S. EPA used 

one of these studies, the National Human Activity 

Pattern Survey (NHAPS), as its source for METS 

values because it was more representative of the 

entire U.S. population than the other studies in the 

database. The NHAPS data set included activity data 

for 9,196 individuals, each of which provided 

24 hours of activity pattern data using a diary-based 

questionnaire. While NHAPS was identified as the 

best available data source for activity patterns, there 

were some shortcomings in the quality of the data. 

Study respondents did not provide body weights; 

instead, body weights were simulated using statistical 

sampling. Also, the NHAPS data extracted from 

CHAD could not be corrected to account for 

non-random sampling of study participants and 

survey days. 

NHANES and NHAPS data were grouped 

according to the age categories presented elsewhere 

in this handbook, with the exception that children 

under the age of 1 year were placed into a single 

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category to preserve an adequate sample size within 

the category. For each NHANES participant, a 

“simulated” 24-hour activity pattern was generated 

by randomly sampling activity patterns from the set 

of NHAPS participants with the same sex and age 

category as the NHANES participant. Twenty such 

patterns were selected at random for each NHANES 

participant, resulting in 480 hours of simulated 

activity data for each NHANES participant. The data 

were then scaled down to a 24-hour time frame to 

yield an average 24-hour activity pattern for each of 

the 19,022 NHANES individuals. 

Each activity was assigned a METS value based 

on statistical sampling of the distribution assigned by 

CHAD to each activity code. For most codes, these 

distributions were not age dependent, but age was a 

factor for some activities for which intensity level 

varies strongly with age. Using statistical software, 

equations for METS based on normal, lognormal, 

exponential, triangular, and uniform distributions 

were generated as needed for the various activity 

codes. The METS values were then translated into 

EE by multiplying the METS by the BMR, which 

was calculated as a linear function of body weight. 

The oxygen consumption rate (VO2) was calculated 

by multiplying EE by H, the volume of oxygen 

consumed per unit of energy. VO2 was calculated 

both as volume per time and as volume per time per 

unit of body weight. 

The inhalation rate for each activity within the 

24-hour simulated activity pattern for each individual 

was estimated as a function of VO2, body weight, 

age, and sex. Following this, the average inhalation 

rate was calculated for each individual for the entire 

24-hour period, as well as for four separate classes of 

activities based on METS value (sedentary/passive 

[METS less than or equal to 1.5], light intensity 

[METS greater than 1.5 and less than or equal to 3.0], 

moderate intensity [METS greater than 3.0 and less 

than or equal to 6.0], and high intensity [METS 

greater than 6.0]). Data for individuals were then 

used to generate summary tables based on sex and 

age categories. 

U.S. EPA (2009a) also conducted a validation 

exercise using the Air Pollutants Exposure Model to 

estimate ventilation rates (VRs) and compared results 

with recently published estimates of ventilation rates 

from Brochu et al. (2006b; 2006a) and Arcus-Arth 

and Blaisdell (2007). The results compared 

reasonably well when ventilation rates were 

normalized by BMI. 

Table 6-14 through Table 6-22 present data from 

this study. Table 6-14 and Table 6-15 present, for 

male and female subjects, respectively, summary 

statistics for daily average inhalation rate by age 

category on a volumetric (m3

/day) and body-weight 

adjusted (m3

/day-kg) basis. Table 6-16 presents the 

mean and 95th percentile values for males, females, 

and males and females combined. Table 6-17 through 

Table 6-20 present, for male and female subjects, 

respectively, mean ventilation rates by age category 

on a volumetric (m3

/minute) and body-weight 

adjusted (m3

/minute-kg) basis for the five different 

activity level ranges described above. Table 6-21 and 

Table 6-22 present the number of hours spent per day 

at each activity level by males and females. 

An advantage of this study is the large sample 

size. In addition, the data sets used, NHAPS and 

NHANES, are representative of the U.S. general 

population. One limitation is that the NHAPS data 

are more than 15 years old. Also, day-to-day 

variability cannot be characterized because data were 

collected over a 24-hour period. There is also 

uncertainty in the METs randomization, all of which 

were noted by the authors. In addition, the approach 

does not take into consideration correlations that may 

exist between body weight and activity patterns. 

Therefore, high physical activity levels can be 

associated with individuals of high body weight, 

leading to unrealistically high inhalation rates at the 

upper percentile levels. The validation exercise 

presented in U.S. EPA (2009a) used normal-weight 

individuals. It is unclear if similar results would be 

obtained for overweight individuals. 

6.3.5.	 Key Studies Combined 

In order to provide the recommended long-term 

inhalation rates shown in Table 6-1, data from the 

four key studies were combined. Mean and 

95th percentile inhalation rate values for the four key 

studies are shown in Table 6-23 and Table 6-24, 

respectively. The data from each study were averaged 

by sex and grouped according to the age groups 

selected for use in this handbook, when possible. 

Table 6-25 shows concordance between the age 

groupings used in this handbook and the original age 

groups in the key studies. 

6.4.	 RELEVANT INHALATION RATE 

STUDIES 

6.4.1.	 International Commission on 

Radiological Protection (ICRP) (1981)— 

Report of the Task Group on Reference 

Man 

The International Commission on Radiological 

Protection (ICRP, 1981) estimated daily inhalation 

rates for reference adult males and females, children 

(10 years old), infants (1 year old), and newborn 

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Chapter 6—Inhalation Rates 

babies by using a time-activity-ventilation approach. 

This approach for estimating an inhalation rate over a 

specified period of time was based on calculating a 

time weighted average of inhalation rates associated 

with physical activities of varying durations (see 

Table 6-26). ICRP (1981) compiled reference values 

(see Table 6-27) of minute volume/inhalation rates 

from various literature sources. ICRP (1981) assumed 

that the daily activities of a reference male, female, 

and child (10 years of age) consisted of 8 hours of 

rest and 16 hours of light activities. It was also 

assumed that for adults only, the 16 hours of light 

activities were divided evenly between occupational 

and non-occupational activities. It was assumed that a 

day consisted of 14 hours resting and 10 hours light 

activity for an infant (1 year). A newborn’s daily 

activities consisted of 23 hours resting and 1-hour 

light activity. The estimated inhalation rates were 

22.8 m3

/day for adult males, 21.1 m3/day for adult 

females, 14.8 m3

/day for children (age 10 years), 

3.76 m3

/day for infants (age 1 year), and 0.78 m3/day 

for newborns (see Table 6-26). 

The advantages of this study are that they account 

fairly well for time and activity, and are sex specific. 

A limitation associated with this study is that it is 

almost 30 years old. In addition, the validity and 

accuracy of the inhalation rate data used in the 

compilation of reference values were not specified. 

This introduces some degree of uncertainty in the 

results obtained. Also, the approach used required 

that assumptions be made regarding the hours spent 

by various age/sex cohorts in specific activities. 

These assumptions may over-/under-estimate the 

inhalation rates obtained. 

6.4.2.	 U.S. EPA (1985)—Development of 

Statistical Distributions or Ranges of 

Standard Factors Used in Exposure 

Assessment 

The U.S. EPA (1985) compiled measured values 

of minute ventilation for various age/sex cohorts 

from early studies. The data compiled by the 

U.S. EPA (1985) for each of the age/sex cohorts were 

obtained at various activity levels (see Table 6-28). 

These levels were categorized as light, moderate, or 

heavy according to the criteria developed by the 

U.S. EPA Office of Environmental Criteria and 

Assessment for the Ozone Criteria Document. These 

criteria were developed for a reference male adult 

with a body weight of 70 kg (U.S. EPA, 1985). 

Table 6-29 details the estimated minute ventilation 

rates for adult males based on these activity level 

categories. 

Table 6-28 presents a summary of inhalation rates 

by age and activity level. A description of activities 

included in each activity level is also presented in 

Table 6-28. Table 6-28 indicates that at rest, the 

average adult inhalation rate is 0.5 m3

/hour. 

Table 6-28 indicates that at rest, the mean inhalation 

rate for children, ages 6 and 10 years, is 0.4 m3

/hour. 

Table 6-30 presents activity pattern data aggregated 

for three microenvironments by activity level for all 

age groups. The total average hours spent indoors 

was 20.4, outdoors was 1.77, and in a transportation 

vehicle was 1.77. Based on the data presented in 

Table 6-28 and Table 6-30, a daily inhalation rate was 

calculated for adults and children by using a 

time-activity-ventilation approach. These data are 

presented for adults and children in Table 6-31. The 

calculated average daily inhalation rate is 16 m3

/day 

for adults. The average daily inhalation rate for 6­

and 10-year-old children is 16.74 and 21.02 m3

/day, 

respectively. 

Limitations associated with this study are its age 

and that many of the values used in the data 

compilation were from early studies. The accuracy 

and/or validity of the values used and data collection 

method were not presented in U.S. EPA (1985). This 

introduces uncertainty in the results obtained. An 

advantage of this study is that the data are actual 

measurement data for a large number of adults and 

children. 

6.4.3.	 Shamoo et al. (1990)—Improved 

Quantitation of Air Pollution Dose Rates 

by Improved Estimation of Ventilation 

Rate 

Shamoo et al. (1990) conducted a study to 

develop and validate new methods to accurately 

estimate ventilation rates for typical individuals 

during their normal activities. Two practical 

approaches were tested for estimating ventilation 

rates indirectly: (1) volunteers were trained to 

estimate their own VR at various controlled levels of 

exercise; and (2) individual VR and HR relationships 

were determined in another set of volunteers during 

supervised exercise sessions (Shamoo et al., 1990). In 

the first approach, the training session involved 

9 volunteers (3 females and 6 males) from 21 to 

37 years old. Initially the subjects were trained on a 

treadmill with regularly increasing speeds. VR 

measurements were recorded during the last minute 

of the 3-minute interval at each speed. VR was 

reported to the subjects as low (1.4 m3

/hour), medium 

(1.5−2.3 m3

/hour), heavy (2.4−3.8 m3/hour), and very 

heavy (3.8 m3

/hour or higher) (Shamoo et al., 1990). 

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Following the initial test, treadmill training 

sessions were conducted on a different day in which 

7 different speeds were presented, each for 3 minutes 

in arbitrary order. VR was measured, and the subjects 

were given feedback with the four ventilation ranges 

provided previously. After resting, a treadmill testing 

session was conducted in which seven speeds were 

presented in different arbitrary order from the 

training session. VR was measured, and each subject 

estimated their own ventilation level at each speed. 

The correct level was then revealed to each subject 

after his/her own estimate. Subsequently, two 3-hour 

outdoor supervised exercise sessions were conducted 

in the summer on 2 consecutive days. Each hour 

consisted of 15 minutes each of rest, slow walking, 

jogging, and fast walking. The subjects’ ventilation 

level and VR were recorded; however, no feedback 

was given to the subjects. Electrocardiograms were 

recorded via direct connection or telemetry, and HR 

was measured concurrently with ventilation 

measurement for all treadmill sessions. 

The second approach consisted of two protocol 

phases (indoor/outdoor exercise sessions and field 

testing). Twenty outdoor adult workers between 19 

and 50 years old were recruited. Indoor and outdoor 

supervised exercises similar to the protocols in the 

first approach were conducted; however, there were 

no feedbacks. Also, in this approach, 

electrocardiograms were recorded, and HR was 

measured concurrently with VR. During the field 

testing phase, subjects were trained to record their 

activities during three different 24-hour periods 

during 1 week. These periods included their most 

active working and non-working days. HR was 

measured quasi-continuously during the 24-hour 

periods that activities were recorded. The subjects 

recorded in a diary all changes in physical activity, 

location, and exercise levels during waking hours. 

Self-estimated activities in supervised exercises and 

field studies were categorized as slow (resting, slow 

walking or equivalent), medium (fast walking or 

equivalent), and fast (jogging or equivalent). 

Inhalation rates were not presented in this study. 

In the first approach, about 68% of all self-estimates 

were correct for the 9 subjects sampled (Shamoo et 

al., 1990). Inaccurate self-estimates occurred in the 

younger male population who were highly physically 

fit and were competitive aerobic trainers. This subset 

of the sample population tended to underestimate 

their own physical activity levels at higher VR 

ranges. Shamoo et al. (1990) attributed this to a 

“macho effect,” in which these younger male subjects 

were reluctant to report “very heavy” exercise even 

when it was obvious to an observer, because they 

considered it an admission of poor physical 

condition. In the second approach, a regression 

analysis was conducted that related the logarithm of 

VR to HR. The logarithm of VR correlated better 

with HR than VR itself (Shamoo et al., 1990). 

Limitations associated with this study are its age 

and that the population sampled is not representative 

of the general U.S. population. Also, ventilation rates 

were not presented. Training individuals to estimate 

their VR may contribute to uncertainty in the results 

because the estimates are subjective. Another 

limitation is that calibration data were not obtained at 

extreme conditions; therefore, the VR/HR 

relationship obtained may be biased. An additional 

limitation is that training subjects may be too 

labor-intensive for widespread use in exposure 

assessment studies. An advantage of this study is that 

HR recordings are useful in predicting ventilation 

rates, which, in turn, are useful in estimating 

exposure. 

6.4.4.	 Shamoo et al. (1991)—Activity Patterns in 

a Panel of Outdoor Workers Exposed to 

Oxidant Pollution 

Shamoo et al. (1991) investigated summer 

activity patterns in 20 adult volunteers with 

potentially high exposure to ambient oxidant 

pollution. The selected volunteer subjects were 

15 men and 5 women ages 19−50 years from the Los 

Angeles area. All volunteers worked outdoors at least 

10 hours per week. The experimental approach 

involved two stages: (1) indirect objective estimation 

of VR from HR measurements, and 

(2) self-estimation of inhalation/ventilation rates 

recorded by subjects in diaries during their normal 

activities. 

The approach consisted of calibrating the 

relationship between VR and HR for each test subject 

in controlled exercise; monitoring by subjects of their 

own normal activities with diaries and electronic HR 

recorders; and then relating VR with the activities 

described in the diaries (Shamoo et al., 1991). 

Calibration tests were conducted for indoor and 

outdoor supervised exercises to determine individual 

relationships between VR and HR. Indoors, each 

subject was tested on a treadmill at rest and at 

increasing speeds. HR and VR were measured at the 

third minute at each 3-minute interval speed. In 

addition, subjects were tested while walking a 

90-meter course in a corridor at 3 self-selected speeds 

(normal, slower than normal, and faster than normal) 

for 3 minutes. 

Two outdoor testing sessions (1 hour each) were 

conducted for each subject, 7 days apart. Subjects 

exercised on a 260-meter asphalt course. A session 

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involved 15 minutes each of rest, slow walking, 

jogging, and fast walking during the first hour. The 

sequence was also repeated during the second hour. 

HR and VR measurements were recorded starting at 

the 8th minute of each 15-minute segment. Following 

the calibration tests, a field study was conducted in 

which subjects self-monitored their activities by 

filling out activity diary booklets, self-estimated their 

breathing rates, and their HR. Breathing rates were 

defined as sleep; slow (slow or normal walking); 

medium (fast walking); and fast (running) (Shamoo 

et al., 1991). Changes in location, activity, or 

breathing rates during three 24-hour periods within a 

week were recorded. These periods included their 

most active working and non-working days. Each 

subject wore Heart Watches, which recorded their HR 

once per minute during the field study. Ventilation 

rates were estimated for the following categories: 

sleep, slow, medium, and fast. 

Calibration data were fit to the equation log 

(VR) = intercept + (slope × HR), each individual’s 

intercept and slope were determined separately to 

provide a specific equation that predicts each 

subject’s VR from measured HR (Shamoo et al., 

1991). The average measured VRs were 0.48, 0.90, 

1.68, and 4.02 m3

/hour for rest, slow walking or 

normal walking, fast walking, and jogging, 

respectively (Shamoo et al., 1991). Collectively, the 

diary recordings showed that sleep occupied about 

33% of the subject's time; slow activity 59%; 

medium activity 7%; and fast activity 1%. The diary 

data covered an average of 69 hours per subject 

(Shamoo et al., 1991). Table 6-32 presents the 

distribution pattern of predicted ventilation rates and 

equivalent ventilation rates (EVR) obtained at the 

four activity levels. EVR was defined as the VR per 

square meter of body surface area, and also as a 

percentage of the subjects average VR over the entire 

field monitoring period (Shamoo et al., 1991). The 

overall mean predicted VR was 0.42 m3

/hour for 

sleep; 0.71 m3

/hour for slow activity; 0.84 m3/hour 

for medium activity; and 2.63 m3

/hour for fast 

activity. 

Table 6-33 presents the mean predicted VR and 

standard deviation, and the percentage of time spent 

in each combination of VR, activity type (essential 

and non-essential), and location (indoor and outdoor). 

Essential activities include income-related work, 

household chores, child care, study and other school 

activities, personal care, and destination-oriented 

travel. Non-essential activities include sports and 

active leisure, passive leisure, some travel, and social 

or civic activities (Shamoo et al., 1991). Table 6-33 

shows that inhalation rates were higher outdoors than 

indoors at slow, medium, and fast activity levels. 

Also, inhalation rates were higher for outdoor 

non-essential activities than for indoor non-essential 

activity levels at slow, medium, and fast self-reported 

breathing rates (see Table 6-33). 

An advantage of this study is that subjective 

activity diary data can provide exposure modelers 

with useful rough estimates of VR for groups of 

generally healthy people. A limitation of this study is 

its age and that the results obtained show high 

within-person and between-person variability in VR 

at each diary-recorded level, indicating that VR 

estimates from diary reports could potentially be 

substantially misleading in individual cases. Another 

limitation of this study is that elevated HR data of 

slow activity at the second hour of the exercise 

session reflect persistent effects of exercise and/or 

heat stress. Therefore, predictions of VR from the 

VR/HR relationship may be biased. 

6.4.5.	 Linn et al. (1992)—Documentation of 

Activity Patterns in “High-Risk” Groups 

Exposed to Ozone in the Los Angeles 

Area 

Linn et al. (1992) conducted a study that 

estimated the inhalation rates for “high-risk” 

population groups exposed to ozone in their daily 

activities in the Los Angeles area. The population 

surveyed consisted of seven subject panels: Panel 1: 

20 healthy outdoor workers (15 males, 5 females, 

ages 19−50 years); Panel 2: 17 healthy elementary 

school students (5 males, 12 females, ages 

10−12 years); Panel 3: 19 healthy high school 

students (7 males, 12 females, ages 13−17 years); 

Panel 4: 49 asthmatic adults (clinically mild, 

moderate, and severe, 15 males, 34 females, ages 

18−50 years); Panel 5: 24 asthmatic adults from 

2 neighborhoods of contrasting O3 air quality 

(10 males, 14 females, ages 19−46 years); Panel 6: 

13 young asthmatics (7 males, 6 females, ages 

11−16 years); and Panel 7: construction workers 

(7 males, ages 26−34 years). An initial calibration 

test was conducted, followed by a training session. 

Finally, a field study that involved the subjects 

collecting their own HRs and diary data was 

conducted. During the calibration tests, VR, 

breathing rate, and HR were measured 

simultaneously at each exercise level. From the 

calibration data, an equation was developed using 

linear regression analysis to predict VR from 

measured HR. 

In the field study, each subject (except 

construction workers) recorded in diaries their daily 

activities, change in locations (indoors, outdoors, or 

in a vehicle), self-estimated breathing rates during 

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each activity/location, and time spent at each 

activity/location. Healthy subjects recorded their HR 

once every 60 seconds using a Heart Watch, an 

automated system consisting of a transmitter and 

receiver worn on the body. Asthmatic subjects 

recorded their diary information once every hour. 

Subjective breathing rates were defined as slow 

(walking at their normal pace), medium (faster than 

normal walking), and fast (running or similarly 

strenuous exercise). Table 6-34 presents the 

calibration and field protocols for self-monitoring of 

activities for each subject panel. 

Table 6-35 presents the mean, 99th percentile, and 

mean VR at each subjective activity level (slow, 

medium, fast). The mean and 99th percentile VR were 

derived from all HR recordings that appeared to be 

valid, without considering the diary data. Each of the 

three activity levels was determined from both the 

concurrent diary data and HR recordings by direct 

calculation or regression. The mean VR for healthy 

adults was 0.78 m3

/hour, while the mean VR for 

asthmatic adults was 1.02 m3

/hour (see Table 6-35). 

The preliminary data for construction workers 

indicated that during a 10-hour work shift, their mean 

VR (1.50 m3

/hour) exceeded the VRs of all other 

subject panels (see Table 6-35). The authors reported 

that the diary data showed that on a typical day, most 

individuals spent most of their time indoors at slow 

activity level. During slow activity, asthmatic 

subjects had higher VRs than healthy subjects (see 

Table 6-35). The authors also reported that in every 

panel, the predicted VR correlated significantly with 

the subjective estimates of activity levels. 

A limitation of this study is that calibration 

data may overestimate the predictive power of HR 

during actual field monitoring. The wide variety of 

exercises in everyday activities may result in greater 

variation of the VR-HR relationship than was 

calibrated. Another limitation is the small sample size 

of each population surveyed. An advantage of this 

study is that diary data can provide rough estimates 

of ventilation patterns, which are useful in exposure 

assessments. Another advantage is that inhalation 

rates were presented for various populations (i.e., 

healthy outdoor adult workers, healthy children, 

asthmatics, and construction workers). 

6.4.6.	 Shamoo et al. (1992)—Effectiveness of 

Training Subjects to Estimate Their Level 

of Ventilation 

Shamoo et al. (1992) conducted a study where 

nine non-sedentary subjects in good health were 

trained on a treadmill to estimate their own 

ventilation rates at four activity levels: low, medium, 

heavy, and very heavy. The purpose of the study was 

to train the subjects’ self-estimation of ventilation in 

the field and to assess the effectiveness of the training 

(Shamoo et al., 1992). The subjects included 

3 females and 6 males between 21 to 37 years of age. 

The tests were conducted in four stages. First, an 

initial treadmill pretest was conducted indoors at 

various speeds until the four ventilation levels were 

experienced by each subject; VR was measured and 

feedback was given to the subjects. Second, two 

treadmill training sessions, which involved seven 

3-minute segments of varying speeds based on initial 

tests, were conducted; VR was measured and 

feedback was given to the subjects. Another similar 

session was conducted; however, the subjects 

estimated their own ventilation level during the last 

20 seconds of each segment and VR was measured 

during the last minute of each segment. Immediate 

feedback was given to the subject’s estimate; and the 

third and fourth stages involved 2 outdoor sessions of 

3 hours each. Each hour comprised 15 minutes each 

of rest, slow walking, jogging, and fast walking. The 

subjects estimated their own ventilation level at the 

middle of each segment. The subject's estimate was 

verified by a respirometer, which measured VR in the 

middle of each 15-minute activity. No feedback was 

given to the subject. The overall percent correct score 

obtained for all ventilation levels was 68% (Shamoo 

et al., 1992). Therefore, Shamoo et al. (1992) 

concluded that this training protocol was effective in 

training subjects to correctly estimate their minute 

ventilation levels. 

For this handbook, inhalation rates were analyzed 

from the raw data provided by Shamoo et al. (1992). 

Table 6-36 presents the mean inhalation rates 

obtained from this analysis at four ventilation levels 

in two microenvironments (i.e., indoors and 

outdoors) for all subjects. The mean inhalation rates 

for all subjects were 0.93, 1.92, 3.01, and 4.80 

m3

/hour for low, medium, heavy, and very heavy 

activities, respectively. 

Limitations of this study are its age and the 

population sample size used in this study was small 

and was not selected to represent the general U.S. 

population. The training approach employed may not 

be cost effective because it was labor intensive; 

therefore, this approach may not be viable in field 

studies especially for field studies within large 

sample sizes. 

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6.4.7.	 Spier et al. (1992)—Activity Patterns in 

Elementary and High School Students 

Exposed to Oxidant Pollution 

Spier et al. (1992) investigated the activity 

patterns of 17 elementary school students 

(10−12 years old) and 19 high school students 

(13−17 years old) in suburban Los Angeles from late 

September to October (oxidant pollution season). 

Calibration tests were conducted in supervised 

outdoor exercise sessions. The exercise sessions 

consisted of 5 minutes each of rest, slow walking, 

jogging, and fast walking. HR and VR were 

measured during the last 2 minutes of each exercise. 

Individual VR and HR relationships for each 

individual were determined by fitting a regression 

line to HR values and log VR values. Each subject 

recorded their daily activities, changes in location, 

and breathing rates in diaries for 3 consecutive days. 

Self-estimated breathing rates were recorded as slow 

(slow walking), medium (walking faster than 

normal), and fast (running). HR was recorded once 

per minute during the 3 days using a Heart Watch. 

VR values for each self-estimated breathing rate and 

activity type were estimated from the HR recordings 

by employing the VR and HR equation obtained from 

the calibration tests. 

The data shown in Table 6-37 represent HR 

distribution patterns and corresponding predicted VR 

for each age group during hours spent awake. At the 

same self-reported activity levels for both age groups, 

inhalation rates were higher for outdoor activities 

than for indoor activities. The total number of hours 

spent indoors was higher for high school students 

(21.2 hours) than for elementary school students 

(19.6 hours). The converse was true for outdoor 

activities: 2.7 hours for high school students and 4.4 

hours for elementary school students (see 

Table 6-38). Table 6-39 describes the distribution 

patterns of daily inhalation rates for elementary and 

high school students grouped by activity level. 

A limitation of this study is the small sample size. 

The results may not be representative of all children 

in these age groups. Another limitation is that the 

accuracy of the self-estimated breathing rates 

reported by younger age groups is uncertain. This 

may affect the validity of the data set generated. An 

advantage of this study is that inhalation rates were 

determined for children and adolescents. 

6.4.8.	 Adams (1993)—Measurement of 

Breathing Rate and Volume in Routinely 

Performed Daily Activities, Final Report 

Adams (1993) conducted research to accomplish 

two main objectives: (1) identification of mean and 

ranges of inhalation rates for various age/sex cohorts 

and specific activities, and (2) derivation of simple 

linear and multiple regression equations that could be 

used to predict inhalation rates through other 

measured variables: breathing frequency (fB) and 

oxygen consumption. A total of 160 subjects 

participated in the primary study. There were four 

age-dependent groups: (1) children 6 to 12.9 years 

old, (2) adolescents between 13 and 18.9 years old, 

(3) adults between 19 and 59.9 years old, and (4) 

seniors >60 years old (Adams, 1993). An additional 

40 children from 6 to 12.9 years old and 12 young 

children from 3 to 5.9 years old were identified as 

subjects for pilot testing purposes. 

Resting protocols conducted in the laboratory for 

all age groups consisted of three phases (25 minutes 

each) of lying, sitting, and standing. The phases were 

categorized as resting and sedentary activities. Two 

active protocols—moderate (walking) and heavy 

(jogging/running) phases—were performed on a 

treadmill over a progressive continuum of intensity 

levels made up of 6-minute intervals at three speeds 

ranging from slow to moderately fast. All protocols 

involved measuring VR, HR, fB, and VO2. 

Measurements were taken in the last 5 minutes of 

each phase of the resting protocol and the last 3 

minutes of the 6-minute intervals at each speed 

designated in the active protocols. 

In the field, all children completed spontaneous 

play protocols. The older adolescent population (16 

to 18 years) completed car driving and riding, car 

maintenance (males), and housework (females) 

protocols. All adult females (19 to 60 years) and most 

of the senior (60 to 77 years) females completed 

housework, yardwork, and car driving and riding 

protocols. Adult and senior males completed car 

driving and riding, yardwork, and mowing protocols. 

HR, VR, and fB were measured during each protocol. 

Most protocols were conducted for 30 minutes. All 

the active field protocols were conducted twice. 

During all activities in either the laboratory or 

field protocols, VR for the children’s group revealed 

no significant sex differences, but those for the adult 

groups demonstrated sex differences. Therefore, 

inhalation rate (IR) data presented in Table 6-40 and 

Table 6-41 were categorized as young children, 

children (no sex), and adult female, and adult male, 

and adult combined by activity type (lying, sitting, 

standing, walking, and running). These categorized 

data from Table 6-40 and Table 6-41 are summarized 

as inhalation rates in Table 6-42 and Table 6-43. 

Table 6-42 shows the laboratory protocols. 

Table 6-43 presents the mean inhalation rates by 

group and for moderate activity levels in field 

protocols. A comparison of the data shown in 

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Table 6-42 and Table 6-43 suggest that during light 

and sedentary activities in laboratory and field 

protocols, similar inhalation rates were obtained for 

adult females and adult males. Accurate predictions 

of inhalation rates across all population groups and 

activity types were obtained by including body SA, 

HR, and breathing frequency in multiple regression 

analysis (Adams, 1993). Adams (1993) calculated SA 

from measured height and body weight using the 

equation: 

SA = Height(0.725) × Weight(0.425) × 71.84 (Eqn. 6-3) 

A limitation associated with this study is that the 

population does not represent the general U.S. 

population. Also, the classification of activity types 

(i.e., laboratory and field protocols) into activity 

levels may bias the inhalation rates obtained for 

various age/sex cohorts. Age groups for which data 

are provided are limited and do not conform to 

U.S. EPA’s recommended age groups for children. 

The estimated rates were based on short-term data 

and may not reflect long-term patterns. 

6.4.9.	 Layton (1993)—Metabolically Consistent 

Breathing Rates for Use in Dose 

Assessments 

Layton (1993) presented a method for estimating 

metabolically consistent inhalation rates for use in 

quantitative dose assessments of airborne 

radionuclides. Generally, the approach for estimating 

the breathing rate for a specified time frame was to 

calculate a time-weighted-average of ventilation rates 

associated with physical activities of varying 

durations. However, in this study, breathing rates 

were calculated on the basis of oxygen consumption 

associated with energy expenditures for short (hours) 

and long (weeks and months) periods of time, using 

the following general equation to calculate 

energy-dependent inhalation rates: 

VE = E × H × VQ (Eqn. 6-4) 

where: 

V ventilation rate (m3 E =	 /minute or 

m3

/day); 

E =	 energy expenditure rate;

[kilojoules/minute (KJ/minute) or 

megajoules/hour (MJ/hour)]; 

H =	 volume of oxygen (at standard 

temperature and pressure, dry air 

consumed in the production of 

1 kilojoule [KJ] of energy 

expended [L/KJ or m3

/MJ]); and 

VQ =	 ventilatory equivalent (ratio of 

minute volume [m3

/minute] to 

oxygen uptake [m3

/minute]) 

unitless. 

Layton (1993) used three approaches to estimate 

daily chronic (long term) inhalation rates for different 

age/sex cohorts of the U.S. population using this 

methodology. 

First Approach 

Inhalation rates were estimated by multiplying 

average daily food-energy intakes (EFDs) for 

different age/sex cohorts, H, and VQ, as shown in the 

equation above. The average food-energy intake data 

(see Table 6-44) are based on approximately 

30,000 individuals and were obtained from the 

1977−1978 USDA-NFCS. The food-energy intakes 

were adjusted upwards by a constant factor of 1.2 for 

all individuals 9 years and older. This factor 

compensated for a consistent bias in USDA-NFCS 

that was attributed to under-reporting of the foods 

consumed or the methods used to ascertain dietary 

intakes. Layton (1993) used a weighted average 

oxygen uptake of 0.05 L O2/KJ, which was 

determined from data reported in the 1977−1978 

USDA-NFCS and the second NHANES 

(NHANES II). The survey sample for NHANES II 

was approximately 20,000 participants. A VQ of 27 

used in the calculations was calculated as the 

geometric mean of VQ data that were obtained from 

several studies. 

The inhalation rate estimation techniques are 

shown in the footnotes in Table 6-45. Table 6-46 

presents the daily inhalation rate for each age/sex 

cohort. As shown in Table 6-45, the highest daily 

inhalation rates were 10 m3

/day for children between 

the ages of 6 and 8 years, 17 m3

/day for males 

between 15 and 18 years, and 13 m3

/day for females 

between 9 and 11 years. Estimated average lifetime 

inhalation rates for males and females are 14 m3

/day 

and 10 m3

/day, respectively (see Table 6-45). 

Inhalation rates were also calculated for active and 

inactive periods for the various age/sex cohorts. 

The inhalation rate for inactive periods was 

estimated by multiplying the BMR times H times 

VQ. BMR was defined as “the minimum amount of 

energy required to support basic cellular respiration 

while at rest and not actively digesting food” 

(Layton, 1993). The inhalation rate for active periods 

was calculated by multiplying the inactive inhalation 

rate by the ratio of the rate of energy expenditure 

during active hours to the estimated BMR. This ratio 

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is presented as F in Table 6-45. Table 6-45 also 

presents these data for active and inactive inhalation 

rates. For children, inactive and active inhalation 

rates ranged from 2.35 to 5.95 m3

/day and from 6.35 

to 13.09 m3

/day, respectively. For adult males (19 to 

64 years old), the average inactive and active 

inhalation rates were approximately 10 and 

19 m3

/day, respectively. Also, the average inactive 

and active inhalation rates for adult females (19 to 

64 years old) were approximately 8 and 12 m3

/day, 

respectively. 

Second Approach 

Inhalation rates were calculated as the product of 

the BMR of the population cohorts, the ratio of total 

daily energy expenditure to daily BMR, H, and VQ. 

The BMR data obtained from the literature were 

statistically analyzed, and regression equations were 

developed to predict BMR from body weights of 

various age/sex cohorts. Table 6-46 presents the 

statistical data used to develop the regression 

equations. Table 6-47 presents the data obtained from 

the second approach. Inhalation rates for children 

(6 months−10 years) ranged from 7.3−9.3 m3

/day for 

male and 5.6−8.6 m3

/day for female children; for 

older children (10−18 years), inhalation rates were 15 

m3

/day for males and 12 m3/day for females. Adult 

females (18 years and older) ranged from 9.9−11 

m3

/day and adult males (18 years and older) ranged 

from 13−17 m3

/day. These rates are similar to the 

daily inhalation rates obtained using the first 

approach. Also, the inactive inhalation rates obtained 

from the first approach are lower than the inhalation 

rates obtained using the second approach. This may 

be attributed to the BMR multiplier employed in the 

equation of the second approach to calculate 

inhalation rates. 

Third Approach 

Inhalation rates were calculated by multiplying 

estimated energy expenditures associated with 

different levels of physical activity engaged in over 

the course of an average day by VQ and H for each 

age/sex cohort. The energy expenditure associated 

with each level of activity was estimated by 

multiplying BMRs of each activity level by the MET 

and by the time spent per day performing each 

activity for each age/sex population. The 

time-activity data used in this approach were 

obtained from a survey conducted by Sallis et al. 

(1985) (Layton, 1993). In that survey, the 

physical-activity categories and associated MET 

values used were sleep, MET = 1; light-activity, 

MET = 1.5; moderate activity, MET = 4; hard 

activity, MET = 6; and very hard activity, MET = 10. 

The physical activities were based on recall by the 

test subject (Layton, 1993). The survey sample was 

2,126 individuals (1,120 women and 1,006 men) ages 

20−74 years that were randomly selected from four 

communities in California. The body weights were 

obtained from a study conducted by Najjar and 

Rowland (1987) that randomly sampled individuals 

from the U.S. population (Layton, 1993). Table 6-48 

presents the daily inhalation rates (VE) in m3

/day and 

m3

/hour for adult males and females aged 

20−74 years at five physical activity levels. The total 

daily inhalation rates ranged from 13−17 m3

/day for 

adult males and 11−15 m3

/day for adult females. 

The rates for adult females were higher when 

compared with the other two approaches. Layton 

(1993) reported that the estimated inhalation rates 

obtained from the third approach were particularly 

sensitive to the MET value that represented the 

energy expenditures for light activities. Layton 

(1993) stated further that in the original time-activity 

survey [i.e., conducted by Sallis et al. (1985)], time 

spent performing light activities was not presented. 

Therefore, the time spent at light activities was 

estimated by subtracting the total time spent at sleep, 

moderate, heavy, and very heavy activities from 

24 hours (Layton, 1993). The range of inhalation 

rates for adult females were 9.6−11 m3

/day, 

9.9−11 m3

/day, and 11−15 m3/day, for the first, 

second, and third approaches, respectively. The 

inhalation rates for adult males ranged from 13−16 

m3

/day for the first approach, and 13−17 m3/day for 

the second and third approaches. 

Inhalation rates were also obtained for short-term 

exposures for various age/sex cohorts and five 

energy-expenditure categories (rest, sedentary, light, 

moderate, and heavy). BMRs were multiplied by the 

product of MET, H, and VQ. Table 6-49 presents the 

inhalation-rate data obtained for short-term 

exposures. 

The major strengths of the Layton (1993) study 

are that it obtains similar results using three different 

approaches to estimate inhalation rates in different 

age groups and that the populations are large, 

consisting of men, women, and children. 

Explanations for differences in results due to 

metabolic measurements, reported diet, or activity 

patterns are supported by observations reported by 

other investigators in other studies. Major limitations 

of this study are (1) the estimated activity pattern 

levels are somewhat subjective; (2) the explanation 

that activity pattern differences are responsible for 

the lower level obtained with the metabolic approach 

(25%) compared to the activity pattern approach is 

not well supported by the data; and (3) different 

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populations were used in each approach, which may 

have introduced error. 

6.4.10.	 Linn et al. (1993)—Activity Patterns in 

Ozone Exposed Construction Workers 

Linn et al. (1993) estimated the inhalation rates of 

19 construction workers who perform heavy outdoor 

labor before and during a typical work shift. The 

workers (laborers, iron workers, and carpenters) were 

employed at a site on a hospital campus in suburban 

Los Angeles. The construction site included a new 

hospital building and a separate medical office 

complex. The study was conducted between mid-July 

and early November, 1991. During this period, ozone 

(O3) levels were typically high. Initially, each subject 

was calibrated with a 25-minute exercise test that 

included slow walking, fast walking, jogging, lifting, 

and carrying. All calibration tests were conducted in 

the mornings. VR and HR were measured 

simultaneously during the test. The data were 

analyzed using least squares regression to derive an 

equation for predicting VR at a given HR. Following 

the calibration tests, each subject recorded the type of 

activities to be performed during their work shift (i.e., 

sitting/standing, walking, lifting/carrying, and 

“working at trade”—defined as tasks specific to the 

individual’s job classification). Location, and 

self-estimated breathing rates (“slow” similar to slow 

walking, “medium” similar to fast walking, and 

“fast” similar to running) were also recorded in the 

diary. During work, an investigator recorded the diary 

information dictated by the subjects. HR was 

recorded minute by minute for each subject before 

work and during the entire work shift. Thus, VR 

ranges for each breathing rate and activity category 

were estimated from the HR recordings by employing 

the relationship between VR and HR obtained from 

the calibration tests. 

A total of 182 hours of HR recordings were 

obtained during the survey from the 19 volunteers; 

144 hours reflected actual working time according to 

the diary records. The lowest actual working hours 

recorded was 6.6 hours, and the highest recorded for 

a complete work shift was 11.6 hours (Linn et al., 

1993). Table 6-50 presents summary statistics for 

predicted VR distributions for outdoor workers, and 

for job- or site-defined subgroups. The data reflect all 

recordings before and during work, and at break 

times. For all subjects, the mean inhalation rate was 

1.68 m3

/hour with a standard deviation of ±0.72 (see 

Table 6-50). Also, for most subjects, the 1st and 

99th percentiles of HR were outside of the calibration 

range. Therefore, corresponding IR percentiles were 

extrapolated using the calibration data (Linn et al., 

1993). 

The data shown in Table 6-51 represent 

distribution patterns of mean inhalation rate for each 

subject, total subjects, and job- or site-defined 

subgroups by self-estimated breathing rates (slow, 

medium, or fast) or by type of job activity. All data 

include working and non-working hours. The mean 

inhalation rates for most individuals showed 

statistically significant increases with higher 

self-estimated breathing rates or with increasingly 

strenuous job activity (Linn et al., 1993). Inhalation 

rates were higher in hospital site workers when 

compared with office site workers (see Table 6-51). 

In spite of their higher predicted VR workers at the 

hospital site reported a higher percentage of slow 

breathing time (31%) than workers at the office site 

(20%), and a lower percentage of fast breathing time, 

3% and 5%, respectively (Linn et al., 1993). 

Therefore, individuals whose work was objectively 

heavier than average (from VR predictions) tended to 

describe their work as lighter than average (Linn et 

al., 1993). Linn et al. (1993) also concluded that 

during an O3 pollution episode, construction workers 

should experience similar microenvironmental O3 

exposure concentrations as other healthy outdoor 

workers, but with approximately twice as high a VR. 

Therefore, the inhaled dose of O3 should be almost 

two times higher for typical heavy-construction 

workers than for typical healthy adults performing 

less strenuous outdoor jobs. 

Limitations associated with this study are its age 

and the small sample size. Another limitation of this 

study is that calibration data were not obtained at 

extreme conditions. Therefore, it was necessary to 

predict inhalation rate values that were outside the 

calibration range. This may introduce an unknown 

amount of uncertainty to the data set. Subjective 

self-estimated breathing rates may be another source 

of uncertainty in the inhalation rates estimated. An 

advantage is that this study provides empirical data 

useful in exposure assessments for a population 

thought to be the most highly exposed common 

occupational group (outdoor workers). 

6.4.11.	 Rusconi et al. (1994)—Reference Values 

for Respiratory Rate in the First 3 Years 

of Life 

Rusconi et al. (1994) examined a large number of 

infants and children in Milano, Italy, in order to 

determine the reference values for respiratory rate in 

children aged 15 days to 3 years. A total of 618 

infants and children (336 males and 282 females), 

who did not have respiratory infections or any severe 

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Chapter 6—Inhalation Rates 

disease, were included in the study. Of the 618, a 

total of 309 were in good health and were observed in 

daycare centers, while the remaining 309 were seen 

in hospitals or as outpatients. 

Respiratory rates were recorded twice, 30 to 

60 minutes apart, listening to breath sounds for 

60 seconds with a stethoscope, when the child was 

awake and calm and when the child was sleeping 

quietly (sleep not associated with any spontaneous 

movement, including eye movements or 

vocalizations) (see Table 6-52). The children were 

assessed for 1 year in order to determine the 

repeatability of the recordings, to compare respiratory 

rate counts obtained by stethoscope and by 

observation, and to construct reference percentile 

curves by age in a large number of subjects. 

The authors plotted the differences between 

respiratory rate counts determined by stethoscope at 

30- to 60-minute intervals against their mean count in 

waking and sleeping subjects. The standard deviation 

of the differences between the two counts was 2.5 

and 1.7 breaths/minute, respectively, for waking and 

sleeping children. This standard deviation yielded 

95% repeatability coefficients of 4.9 breaths/minute 

when the infants and children were awake and 

3.3 breaths/minute when they were asleep. 

In both waking and sleeping states, the respiratory 

rate counts determined by stethoscope were found to 

be higher than those obtained by observation. The 

mean difference was 2.6 and 1.8 breaths per minute, 

respectively, in waking and sleeping states. The mean 

respiratory rate counts were significantly higher in 

infants and children at all ages when awake and calm 

than when asleep. A decrease in respiratory rate with 

increasing age was seen in waking and sleeping 

infants and children. A scatter diagram of respiratory 

rate counts by age in waking and sleeping subjects 

showed that the pattern of respiratory rate decline 

with age was similar in both states, but it was much 

faster in the first few months of life. The authors 

constructed centile curves by first log-transforming 

the data and then applying a second degree 

polynormal curve, which allowed excellent fitting to 

observed data. Figure 6-1 and Figure 6-2 show 

smoothed percentiles by age in waking and sleeping 

subjects, respectively. The variability of respiratory 

rate among subjects was higher in the first few 

months of life, which may be attributable to 

biological events that occur during these months, 

such as maturation of the neurologic control of 

breathing and changes in lung and chest wall 

compliance and lung volumes. 

An advantage of this study is that it provides 

distribution data for respiratory rate for children from 

infancy (less than 2 months) to 36 months old. The 

main limitation of this study is that data are provided 

in breaths/minute for awake and asleep subjects. 

Activity pattern data for the awake subjects are 

limited, which prevents characterization of breathing 

rates for various levels of exertion. These data are not 

U.S. data; U.S. distributions were not available. 

Although, there is no reason to believe that the 

respiratory rates for Italian children would be 

different from that of U.S. children, this study only 

provided data for a narrow range of activities. 

6.4.12.	 Price et al. (2003)—Modeling 

Interindividual Variation in Physiological 

Factors Used in PBPK Models of Humans 

Price et al. (2003) developed a database of values 

for physiological parameters often used in 

physiologically based pharmacokinetic (PBPK) 

models. The database consisted of approximately 

31,000 records containing information on volumes 

and masses of selected organs and tissues, blood 

flows for the organ and tissues, and total resting 

cardiac output and average inhalation rates. Records 

were created based on data from the NHANES III 

survey. 

The study authors note that the database provides 

a source of data for human physiological parameters 

where the parameter values for an individual are 

correlated with one another and capture 

interindividual variation in populations of a specific 

sex, race, and age range. A publicly available 

computer program, Physiological Parameters for 

PBPK Modeling, was also developed to randomly 

retrieve records from the database for groups of 

individuals of specified age ranges, sex, and 

ethnicities (Lifeline Group, 2006). Price et al. (2003) 

recommends that output sets be used as inputs to 

Monte Carlo-based PBPK models of interindividual 

variation in dose. A limitation of this study is that 

these data have not been validated against actual 

physiological data. Ideally, the database records 

would have been obtained from detailed 

physiological analyses of individuals, however, such 

a survey was not conducted for this study. 

6.4.13.	 Brochu et al. (2006a)—Physiological 

Daily Inhalation Rates for Free-Living 

Pregnant and Lactating Adolescents and 

Women Aged 11 to 55 Years, Using Data 

From Doubly Labeled Water 

Measurements for Use in Health Risk 

Assessment 

PDIRs were determined by Brochu et al. (2006a) 

for underweight, normal-weight, and 

overweight/obese pregnant and lactating females 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

aged 11 to 55 years using published data on total 

daily energy expenditures, and energy costs for 

growth, pregnancy and lactation (breast-energy 

output and maternal milk-energy synthesis) in 

free-living females. These data were obtained using 

the DLW methodology in which disappearance rates 

of predetermined doses of DLW (2

H2O and H2

18O) in 

urine from non-pregnant and non-lactating females 

(N = 357) and normal-weight males (N = 131) as well 

as saliva from gravid and breast-feeding females 

(N = 91) were monitored by gas-isotope-ratio mass 

spectrometry. 

PDIRs were calculated for underweight, 

normal-weight, and overweight/obese females aged 

11 to 55 years in pre-pregnancy, at Weeks 9, 22, and 

36 during pregnancy, and Weeks 6 and 27 

postpartum. Weight groups were determined by BMI 

cutoffs settled by the Institute of Medicine for prepregnant females. Underweight, normal-weight, and 

overweight/obese individuals were defined as those 

having BMIs lower than 19.8 kg/m2

, between 19.8 

and 26 kg/m2

, and greater than 26 kg/m2, 

respectively. Parameters used for breast-energy 

output and the extra energy cost for milk synthesis 

were 539.29 ± 106.26 kcal/day and 107.86 ± 21.25 

kcal/day, respectively. Monte Carlo simulations were 

necessary to integrate total daily energy requirements 

of non-pregnant and non-lactating females into 

energy costs and weight changes at the 9th, 22nd, and 

36th weeks of pregnancy and at the 6th and 27th 

postpartum weeks. A total of 108 sets of 5,000 

energetic data were run, resulting in a simulation of 

540,000 data, pertaining to 45,000 simulated 

subjects. Means, standard deviations, and percentiles 

of energetic values in kcal/day and kcal/kg-day for 

males and females were converted into PDIRs in 

m3

/day and m3/kg-day by using the equation 

developed by Layton (1993). 

Table 6-53, Table 6-54, and Table 6-55 present the 

distribution of physiological daily inhalation rate 

percentiles in m3

/day for underweight, 

normal-weight, and overweight/obese females, 

respectively, during pregnancy and postpartum 

weeks. Table 6-56, Table 6-57, and Table 6-58 

present physiological daily inhalation rate percentiles 

in m3

/kg-day for the same categories. PDIRs for 

under-, normal-, and overweight/obese pregnant and 

lactating females were higher than those for males 

reported in Brochu et al. (2006b). In normal-weight 

subjects, inhalation rates are higher by 18 to 41% 

throughout pregnancy and 23 to 39% during 

postpartum weeks: actual values were higher in 

females by 1.13 to 2.01 m3

/day at the 9th week of 

pregnancy, 3.74 to 4.53 m3

/day at the 22nd week, and 

4.41 to 5.20 m3

/day at the 36th week, and by 4.43 to 

5.30 m3

/day at the 6th postpartum week and 4.22 to 

5.11 m3

/day at the 27th postpartum week. The highest 

99th percentiles were found to be 0.622 m3

/kg-day in 

pregnant females and 0.647 m3

/kg-day in lactating 

females. By comparison, the highest 99th percentile 

value for individuals aged 2.6 months to 96 years was 

determined to be 0.725 m3

/kg-day (Brochu et al., 

2006b). The authors concluded that air quality criteria 

and standard calculations based on the latter value for 

non-carcinogenic toxic compounds should, therefore, 

be protective for virtually all pregnant and lactating 

females. Brochu et al. (2006a) also noted that the 

default assumption used by IRIS to derive HECs 

(total respiratory tract surface of an adult human male 

of 54.3 m2 is exposed to a total daily air intake of 20 

m3

) would underestimate exposures to pregnant or 

lactating females since approximately one pregnant 

or lactating female out of two is exposed to a total 

daily air intake of 20 m3 up to the highest 99th 

percentile of 47.3 m3

. 

An advantage of this study is that it includes 

pregnant and lactating females, and that data are 

provided for adolescents aged 11 years and older. A 

limitation of this study is that the study population 

was partially drawn from Canada and may not 

represent the general U.S. population. Also, age 

groups for adolescents for which data are provided do 

not conform to U.S. EPA’s recommended age groups 

for children. 

6.4.14.	 Allan et al. (2009)—Inhalation Rates for 

Risk Assessments Involving Construction 

Workers in Canada 

Allan et al. (2009) generated probability density 

distributions by performing a Monte Carlo simulation 

to describe inhalation rates for Canadian male and 

female construction workers. Construction workers in 

this study were those involved in the construction or 

physical maintenance of buildings, structures, or 

other facilities, and their ages ranged from 16 to 65 

years. Information regarding activity patterns and/or 

inhalation rates was obtained from published 

literature and used to estimate male construction 

workers’ hourly inhalation rates. Female construction 

worker inhalation rates were estimated using the ratio 

of general public female-to-male inhalation rates and 

male construction workers’ hourly inhalation rates. 

Published energy expenditure and inhalation rates 

were compared by occupation within the construction 

industry, and these data were used to develop 

trade-specific scaling factors. All inhalation rates 

were developed as probability density functions 

through Monte Carlo simulation. Ten thousand 

iterations of random sampling were performed, and at 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

the end of the simulation, the results for all 10,000 

iterations were summarized into frequency 

histograms. The mean, standard deviation, and 

percentiles were calculated based on the frequency 

counts. 

Inhalation rates for male construction workers 

were represented by a log normal distribution, with a 

mean rate of 1.40 ± 0.51 m3

/hour. Hourly inhalation 

rates for female construction workers were scaled 

down from those of their male counterparts, based on 

relative awake-time inhalation rates for men and 

women in the general public. Inhalation rates for 

female construction workers were also represented by 

a log normal distribution, with a mean rate of 1.25 ±

0.66 m3

/hour. Construction trade-specific scaling 

factors were developed and ranged from 0.78 for 

electricians to 1.11 for ironworkers. 

An advantage of this study is that it provides 

estimated inhalation rates for a population of 

construction workers. A limitation of this study is that 

the construction workers in this study were solely 

male construction workers; no females were among 

the cohorts monitored. 

6.5. REFERENCES FOR CHAPTER 6 

Adams, WC. (1993). Measurement of breathing rate 

and volume in routinely performed daily 

activities [final report]. Adams, WC. 

Allan, M; Jones-Otazo, H; Richardson, GM. (2009). 

Inhalation rates for risk assessments 

involving construction workers in Canada. 

Hum Ecol Risk Assess 15: 371-387. 

http://dx.doi.org/10.1080/108070309027614 

45. 

Arcus-Arth, A; Blaisdell, RJ. (2007). Statistical 

distributions of daily breathing rates for 

narrow age groups of infants and children. 

Risk Anal 27: 97-110. 

http://dx.doi.org/10.1111/j.1539­

6924.2006.00862.x. 

Basiotis, PP; Thomas, RG; Kelsay, JL; Mertz, W. 

(1989). Sources of variation in energy intake 

by men and women as determined from one 

year's daily dietary records. Am J Clin Nutr 

50: 448-453. 

Bates, DV. (1989). [Excerpt]. In Respiratory function 

in disease (3rd ed.). Philadelphia, PA: W.B. 

Saunders Company. 

Bennett, WD; Zeman, KL. (2004). Effect of body 

size on breathing pattern and fine-particle 

deposition in children. J Appl Physiol 97: 

821-826. 

http://dx.doi.org/10.1152/japplphysiol.01403 

.2003. 

Bennett, WD; Zeman, KL; Jarabek, AM. (2008). 

Nasal contribution to breathing and fine 

particle deposition in children versus adults. 

J Toxicol Environ Health A 71: 227-237. 

http://dx.doi.org/10.1080/152873907015982 

00. 

Brochu, P; Ducre-Robitaille, JF; Brodeur, J. (2006a). 

Physiological daily inhalation rates for freeliving pregnant and lactating adolescents 

and women aged 11 to 55 years, using data 

from doubly labeled water measurements for 

use in health risk assessment. Hum Ecol 

Risk Assess 12: 702-735. 

http://dx.doi.org/10.1080/108070306008015 

92. 

Brochu, P; Ducré-Robitaille, JF; Brodeur, J. (2006b). 

Physiological daily inhalation rates for freeliving individuals aged 1 month to 96 years, 

using data from doubly labeled water 

measurements: A proposal for air quality 

criteria, standard calculations and health risk 

assessment. Hum Ecol Risk Assess 12: 675­

701. 

http://dx.doi.org/10.1080/108070306008015 

50. 

Cherniack, RM; Cherniack, L; Naimark, A. (1972). 

Respiration in health and disease (2nd ed.). 

Philadelphia, PA: W.B. Saunders Company. 

FASEB/LSRO (Federation of American Societies for 

Experimental Biology, Life Sciences 

Research Office). (1995). Joint policy on 

variance estimation and statistical standards 

on NHANES III and CSFII reports 

(Appendix III). In Third report on nutrition 

monitoring in the United States. 

Washington, DC: Interagency Board for 

Nutrition Monitoring and Related Research. 

Foos, B; Marty, M; Schwartz, J; Bennett, W; Moya, 

J; Jarabek, AM; Salmon, AG. (2008). 

Focusing on children's inhalation dosimetry 

and health effects for risk assessment: An 

introduction. J Toxicol Environ Health A 71: 

149-165. 

http://dx.doi.org/10.1080/152873907015978 

71. 

Foos, B; Sonawane, B. (2008). Overview: Workshop 

on children's inhalation dosimetry and health 

effects for risk assessment. J Toxicol 

Environ Health A 71: 147-148. 

http://dx.doi.org/10.1080/152873907015978 

55. 

Forster, RE; DuBois, AB; Briscoe, WA; Fisher, AB. 

(1986). The Lung: Physiologic basis of 

pulmonary function tests (3rd ed.). Chicago, 

IL: Year Book Medical Publishers. 

Exposure Factors Handbook Page
 

September 2011 6-21 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

ICRP (International Commission on Radiological 

Protection). (1981). Report of the task group 

on reference man. ICRP publication 23. 

New York, NY: Pergammon Press. 

Layton, DW. (1993). Metabolically consistent 

breathing rates for use in dose assessments. 

Health Phys 64: 23-36. 

Lifeline Group. (2006). Physiological parameters for 

PBPK modeling version 1.3 (P3M) 

[Computer Program]. Retrieved from 

http://www.thelifelinegroup.org/p3m/index.p 

hp 

Linn, WS; Shamoo, DA; Hackney, JD. (1992). 

Documentation of activity patterns in 'highrisk' groups exposed to ozone in the Los 

Angeles area. In RL Berglund (Ed.), 

Tropospheric ozone and the environment II: 

Effects, modeling and control (pp. 701-712). 

Pittsburgh, PA: Air and Waste Management 

Association. 

Linn, WS; Spier, CE; Hackney, JD. (1993). Activity 

patterns in ozone-exposed construction 

workers. J Occup Med Toxicol 2: 1-14. 

Najjar, MF; Rowland, M. (1987). Anthropometric 

reference data and prevalence of overweight, 

United States, 1976-80. 1-73. 

Phalen, PD; Landau, LI; Olinsky, A. (1990). 

Respiratory illness in children (3rd ed.). 

Oxford, United Kingdom: Blackwell 

Scientific Publishers. 

Price, PS; Conolly, RB; Chaisson, CF; Gross, EA; 

Young, JS; Mathis, ET; Tedder, DR. (2003). 

Modeling interindividual variation in 

physiological factors used in PBPK models 

of humans. Crit Rev Toxicol 33: 469-503. 

http://dx.doi.org/10.1080/104084403902423 

24. 

Ridley, K; Ainsworth, BE; Olds, TS. (2008). 

Development of a compendium of energy 

expenditures for youth. Int J Behav Nutr 

Phys Activ 5: 45. 

http://dx.doi.org/10.1186/1479-5868-5-45. 

Ridley, K; Olds, TS. (2008). Assigning energy costs 

to activities in children: a review and 

synthesis. Med Sci Sports Exerc 40: 1439­

1446. 

http://dx.doi.org/10.1249/MSS.0b013e31817 

279ef. 

Rusconi, F; Castagneto, M; Gagliardi, L; Leo, G; 

Pellegatta, A; Porta, N; Razon, S; Braga, M. 

(1994). Reference values for respiratory rate 

in the first 3 years of life. Pediatrics 94: 350­

355. 

Sallis, JF; Haskell, WL; Wood, PD; Fortmann, SP; 

Rogers, T; Blair, SN; Paffenbarger, RS. 

(1985). Physical activity assessment 

methodology in the Five-City Project. Am J 

Epidemiol 121: 91-106. 

Scrimshaw, NS; Waterlow, JC; Schurch, B. (1996). 

Energy and protein requirements: 

Proceedings of an IDECG workshop. In NS 

Scrimshaw; JC Waterlow; B Schurch (Eds.). 

Basingstoke, UK: Stockton Press. 

Shamoo, DA; Johnson, TR; Trim, SC; Little, DE; 

Linn, WS; Hackney, JD. (1991). Activity 

patterns in a panel of outdoor workers 

exposed to oxidant pollution. J Expo Sci 

Environ Epidemiol 1: 423-438. 

Shamoo, DA; Trim, SC; Little, DE; Linn, WS; 

Hackney, JD. (1990). Improved quantitation 

of air pollution dose rates by improved 

estimation of ventilation rate. In Total 

exposure assessment methodology: A new 

horizon. Pittsburgh, PA: Air and Waste 

Management Association. 

Shamoo, DA; Trim, SC; Little, DE; Whynot, JD; 

Linn, WS. (1992). Effectiveness of training 

subjects to estimate their level of ventilation. 

J Occup Med Toxicol (US) 1: 55-62. 

Speakman, JR; Selman, C. (2003). Physical activity 

and resting metabolic rate. Proc Nutr Soc 

62: 621-634. 

http://dx.doi.org/10.1079/PNS2003282. 

Spier, CE; Little, DE; Trim, SC; Johnson, TR; Linn, 

WS; Hackney, JD. (1992). Activity patterns 

in elementary and high school students 

exposed to oxidant pollution. J Expo Sci 

Environ Epidemiol 2: 277-293. 

Stifelman, M. (2003). Letter to the editor [Letter]. 

Risk Anal 23: 859-860. 

http://dx.doi.org/10.1111/1539-6924.00363. 

Stifelman, M. (2007). Using doubly-labeled water 

measurements of human energy expenditure 

to estimate inhalation rates. Sci Total 

Environ 373: 585-590. 

http://dx.doi.org/10.1016/j.scitotenv.2006.11 

.041. 

Thompson, CM; Johns, DO; Sonawane, B; Barton, 

HA; Hattis, D; Tardiff, R; Krishnan, K. 

(2009). Database for physiologically based 

pharmacokinetic (PBPK) modeling: 

physiological data for healthy and healthimpaired elderly. J Toxicol Environ Health B 

Crit Rev 12: 1-24. 

http://dx.doi.org/10.1080/109374008025450 

60. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1985). Development of statistical 

distributions or ranges of standard factors 

used in exposure assessments. 

Page Exposure Factors Handbook 

6-22 September 2011 
Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Exposure Factors Handbook Page
 

September 2011 6-23 

(EPA600885010). 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB85242667. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992). Guidelines for exposure assessment. 

(EPA/600/Z-92/001). Washington, DC: U.S. 

Environmental Protection Agency, Risk 

Assessment Forum. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=15263. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1994). Methods for derivation of inhalation 

reference concentrations and application of 

inhalation dosimetry. (EPA/600/8-90/066F). 

Research Triangle Park, NC: U.S. 

Environmental Protection Agency, Office of 

Research and Development, Office of 

Health and Environmental Assessment, 

Environmental Criteria and Assessment 

Office. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=71993. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1997). Exposure factors handbook (final 

report). (EPA/600/P-95/002Fa-c). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Research and 

Development, National Center for 

Environmental Assessment. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=12464. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005a). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum. 

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005b). Supplemental guidance for 

assessing susceptibility from early-life 

exposure to carcinogens. (EPA/630/R03/003F). Washington, DC: U.S. 

Environmental Protection Agency, Risk 

Assessment Forum. 

http://www.epa.gov/cancerguidelines/guideli 

nes-carcinogen-supplement.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009a). Metabolically derived human 

ventilation rates: A revised approach based 

upon oxygen consumption rates (final 

report) [EPA Report]. (EPA/600/R-06/129F). 

Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=202543. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009b). Risk assessment guidance for 

superfund volume I: Human health 

evaluation manual (Part F, supplemental 

guidance for inhalation risk assessment): 

Final. (EPA/540/-R-070/002). Washington, 

DC: U.S. Environmental Protection Agency, 

Office of Superfund Remediation and 

Technology Innovation. 

http://www.epa.gov/oswer/riskassessment/ra 

gsf/index.htm. 

West, JB. (2008a). Pulmonary pathophysiology: the 

essentials: Lippincott Williams & Wilkins. 

West, JB. (2008b). Respiratory physiology: the 

essentials: Lippincott Williams & Wilkins. 

Westerterp, KR. (2003). Impacts of vigorous and 

non-vigorous activity on daily energy 

expenditure. Proc Nutr Soc 62: 645-650. 

http://dx.doi.org/10.1079/PNS2003279. 

WHO (World Health Organization). (1986). 

Principles for evaluating health risks from 

chemicals during infancy and early 

childhood: The need for a special approach 

[WHO EHC] (pp. 55). Geneva, Switzerland. 

http://www.inchem.org/documents/ehc/ehc/e 

hc59.htm. 
 

 

 

 

Table 6-4. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/day) for Free-Living 

Normal-Weight Males and Females Aged 2.6 Months to 96 Years 

Age Group 

(years) N 

Body Weighta 

(kg) 

Mean ± SD 

Physiological Daily Inhalation Ratesb (m3/day) 

Mean ± SD 

Percentilec 

5th 10th 25th 50th 75th 90th 95th 99th 

Males 

0.22 to <0.5 32 6.7 ± 1.0 3.38 ± 0.72 2.19 2.46 2.89 3.38 3.87 4.30 4.57 5.06 

0.5 to <1 40 8.8 ± 1.1 4.22 ± 0.79 2.92 3.21 3.69 4.22 4.75 5.23 5.51 6.05 

1 to <2 35 10.6 ± 1.1 5.12 ± 0.88 3.68 3.99 4.53 5.12 5.71 6.25 6.56 7.16 

2 to <5 25 15.3 ± 3.4 7.60 ± 1.28 5.49 5.95 6.73 7.60 8.47 9.25 9.71 10.59 

5 to <7 96 19.8 ± 2.1 8.64 ± 1.23 6.61 7.06 7.81 8.64 9.47 10.21 10.66 11.50 

7 to <11 38 28.9 ± 5.6 10.59 ± 1.99 7.32 8.04 9.25 10.59 11.94 13.14 13.87 15.22 

11 to <23 30 58.6 ± 13.9 17.23 ± 3.67 11.19 12.53 14.75 17.23 19.70 21.93 23.26 25.76 

23 to <30 34 70.9 ± 6.5 17.48 ± 2.81 12.86 13.88 15.59 17.48 19.38 21.08 22.11 24.02 

30 to <40 41 71.5 ± 6.8 16.88 ± 2.50 12.77 13.68 15.20 16.88 18.57 20.09 21.00 22.70 

40 to <65 33 71.1 ± 7.2 16.24 ± 2.67 11.84 12.81 14.44 16.24 18.04 19.67 20.64 22.46 

65 to ≤96 50 68.9 ± 6.7 12.96 ± 2.48 8.89 9.79 11.29 12.96 14.63 16.13 17.03 18.72 

Females 

0.22 to <0.5 53 6.5 ± 0.9 3.26 ± 0.66 2.17 2.41 2.81 3.26 3.71 4.11 4.36 4.81 

0.5 to <1 63 8.5 ± 1.0 3.96 ± 0.72 2.78 3.05 3.48 3.96 4.45 4.88 5.14 5.63 

1 to <2 66 10.6 ± 1.3 4.78 ± 0.96 3.20 3.55 4.13 4.78 5.43 6.01 6.36 7.02 

2 to <5 36 14.4 ± 3.0 7.06 ± 1.16 5.15 5.57 6.28 7.06 7.84 8.54 8.97 9.76 

5 to <7 102 19.7 ± 2.3 8.22 ± 1.31 6.06 6.54 7.34 8.22 9.11 9.90 10.38 11.27 

7 to <11 161 28.3 ± 4.4 9.84 ± 1.69 7.07 7.68 8.70 9.84 10.98 12.00 12.61 13.76 

11 to <23 87 50.0 ± 8.9 13.28 ± 2.60 9.00 9.94 11.52 13.28 15.03 16.61 17.56 19.33 

23 to <30 68 59.2 ± 6.6 13.67 ± 2.28 9.91 10.74 12.13 13.67 15.21 16.59 17.42 18.98 

30 to <40 59 58.7 ± 5.9 13.68 ± 1.76 10.78 11.42 12.49 13.68 14.87 15.94 16.58 17.78 

40 to <65 58 58.8 ± 5.1 12.31 ± 2.07 8.91 9.66 10.92 12.31 13.70 14.96 15.71 17.12 

65 to ≤96 45 57.2 ± 7.3 9.80 ± 2.17 6.24 7.02 8.34 9.80 11.27 12.58 13.37 14.85 a Measured body weight. Normal-weight individuals defined according to the BMI cut-offs. b Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG) × H × 

(VE/VO2) × 10−3, where H = 0.21 L of O2/Kcal, VE/VO2 = 27 (Layton, 1993) and ECG = stored daily energy 

cost for growth (kcal/day). c Percentiles based on a normal distribution assumption for age groups. 

N = Number of individuals. 

SD = Standard deviation. 

Source: Brochu et al. (2006b). 

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Chapter 6—Inhalation Rates
 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-5. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Free-Living Normal-Weight 

Males, Females, and Males and Females Combined 

Age Groupa, b N Meanc 95th, c 

Males 

1 to <3 months 32 3.38 4.57 

3 to <6 months 32 3.38 4.57 

6 to <12 months 40 4.22 5.51 

Birth to <1 year 72 3.85 5.09 

1 to <2 years 35 5.12 6.56 

2 to <3 years 25 7.60 9.71 

3 to <6 years 25 7.60 9.71 

6 to <11 years 38 10.59 13.87 

11 to <16 years 30 17.23 23.26 

16 to <21 years 30 17.23 23.26 

21 to <31 years 64 17.36 22.65 

31 to <41 years 41 16.88 21.00 

41 to <51 years 33 16.24 20.64 

51 to <61 years 33 16.24 20.64 

61 to <71 years 83 14.26 18.47 

71 to <81 years 50 12.96 17.03 

≥81 years 50 12.96 17.03 

Females 

1 to <3 months 53 3.26 4.36 

3 to <6 months 53 3.26 4.36 

6 to <12 months 63 3.96 5.14 

Birth to <1 year 116 3.64 4.78 

1 to <2 years 66 4.78 6.36 

2 to <3 years 36 7.06 8.97 

3 to <6 years 36 7.06 8.97 

6 to <11 years 161 9.84 12.61 

11 to <16 years 87 13.28 17.56 

16 to <21 years 87 13.28 17.56 

21 to <31 years 155 13.45 17.50 

31 to <41 years 59 13.68 16.58 

41 to <51 years 58 12.31 15.71 

51 to <61 years 58 12.31 15.71 

61 to <71 years 103 11.21 14.69 

71 to <81 years 45 9.80 13.37 

≥81 years 45 9.80 13.37 

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Table 6-5. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Free-Living Normal-Weight 

Males, Females, and Males and Females Combined (continued) 

Age Groupa,b N Meanc 95th,c 

Males and Females Combined 

1 to <3 months 85 3.31 4.44 

3 to <6 months 85 3.31 4.44 

6 to <12 months 103 4.06 5.28 

Birth to <1 years 188 3.72 4.90 

1 to <2 years 101 4.90 6.43 

2 to <3 years 61 7.28 9.27 

3 to <6 years 61 7.28 9.27 

6 to <11 years 199 9.98 12.85 

11 to <16 years 117 14.29 19.02 

16 to <21 years 117 14.29 19.02 

21 to <31 years 219 14.59 19.00 

31 to <41 years 100 14.99 18.39 

41 to <51 years 91 13.74 17.50 

51 to <61 years 91 13.74 17.50 

61 to <71 years 186 12.57 16.37 

71 to <81 years 95 11.46 15.30 

≥81 years 95 11.46 15.30 

a No other age groups from Table 6-4 (Brochu et al., 2006b) fit into the U.S. EPA age groupings. b See Table 6-25 for concordance with U.S. EPA age groupings. c Weighted (where possible) average of reported study means and 95th percentiles. 

N = Number of individuals. 

Source: Brochu et al. (2006b). 

Page Exposure Factors Handbook 

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Table 6-6. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/day) for Free-Living 

Normal-Weight and Overweight/Obese Males and Females Aged 4 to 96 Years 

Age Group 

(years) N 

Body Weighta 

(kg) 

Mean ± SD 

Physiological Daily Inhalation Ratesb (m3/day) 

Mean ± SD 

Percentilec 

5th 10th 25th 50th 75th 90th 95th 99th 

Males—Normal-weight 

4 to <5.1 77 19.0 ± 1.9 7.90 ± 0.97 6.31 6.66 7.25 7.90 8.56 9.15 9.50 10.16 

5.1 to <9.1 52 22.6 ± 3.5 9.14 ± 1.44 6.77 7.29 8.17 9.14 10.11 10.99 11.51 12.49 

9.1 to <18.1 36 41.4 ± 12.1 13.69 ± 3.95 7.19 8.63 11.02 13.69 16.35 18.75 20.19 22.88 

18.1 to <40.1 98 71.3 ± 6.1 17.41± 2.70 12.96 13.94 15.58 17.41 19.23 20.87 21.85 23.69 

40.1 to <70.1 34 70.0 ± 7.8 15.60 ± 2.89 10.85 11.89 13.65 15.60 17.54 19.30 20.34 22.31 

70.1 to ≤96 38 68.9 ± 6.8 12.69 ± 2.33 8.85 9.70 11.11 12.69 14.26 15.68 16.53 18.12 

Males—Overweight/obese 

4 to <5.1 54 26.5 ± 4.9 9.59 ± 1.26 7.52 7.98 8.74 9.59 10.44 11.21 11.66 12.52 

5.1 to <9.1 40 32.5 ± 9.2 10.88 ± 2.49 6.78 7.69 9.20 10.88 12.56 14.07 14.98 16.68 

9.1 to <18.1 33 55.8 ± 10.8 14.52 ± 1.98 11.25 11.98 13.18 14.52 15.85 17.06 17.78 19.13 

18.1 to <40.1 52 98.1 ± 25.2 20.39 ± 3.62 14.44 15.75 17.95 20.39 22.83 25.03 26.35 28.81 

40.1 to <70.1 81 93.2 ± 14.9 17.96 ± 3.71 11.85 13.20 15.45 17.96 20.46 22.71 24.06 26.59 

70.1 to ≤96 32 82.3 ± 10.3 14.23 ± 2.94 9.40 10.46 12.25 14.23 16.21 18.00 19.06 21.07 

Females—Normal-weight 

4 to <5.1 82 18.7 ± 2.0 7.41 ± 0.91 5.92 6.25 6.80 7.41 8.02 8.57 8.90 9.52 

5.1 to <9.1 151 25.5 ± 4.1 9.39 ± 1.62 6.72 7.31 8.30 9.39 10.48 11.47 12.05 13.16 

9.1 to <18.1 124 42.7 ± 11.1 12.04 ± 2.86 7.34 8.38 10.11 12.04 13.97 15.70 16.74 18.68 

18.1 to <40.1 135 59.1 ± 6.3 13.73 ± 2.01 10.41 11.15 12.37 13.73 15.09 16.31 17.04 18.41 

40.1 to <70.1 79 59.1 ± 5.3 11.93 ± 2.16 8.38 9.16 10.47 11.93 13.38 14.69 15.48 16.95 

70.1 to ≤96 24 54.8 ± 7.5 8.87 ± 1.79 5.92 6.57 7.66 8.87 10.07 11.16 11.81 13.03 

Females—Overweight/obese 

4 to <5.1 56 26.1 ± 5.5 8.70 ± 1.13 6.84 7.26 7.94 8.70 9.47 10.15 10.56 11.33 

5.1 to <9.1 68 34.6 ± 9.9 10.55 ± 2.23 6.88 7.69 9.05 10.55 12.06 13.41 14.22 15.75 

9.1 to <18.1 68 59.2 ± 12.8 14.27 ± 2.70 9.83 10.81 12.45 14.27 16.09 17.73 18.71 20.55 

18.1 to <40.1 76 84.4 ± 16.3 15.66 ± 2.11 12.18 12.95 14.23 15.66 17.08 18.36 19.13 20.57 

40.1 to <70.1 91 81.7 ± 17.2 13.01 ± 2.82 8.37 9.40 11.11 13.01 14.91 16.62 17.64 19.56 

70.1 to ≤96 28 69.0 ± 7.8 10.00 ± 1.78 7.07 7.71 8.80 10.00 11.20 12.28 12.93 14.14 

a Measured body weight. Normal-weight and overweight/obese males defined according to the BMI cut-offs. b Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG) × H × (VE/VO2) × 

10−3, where H = 0.21 L of O2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily energy expenditure (kcal/day) 

and ECG = stored daily energy cost for growth (kcal/day). c Percentiles based on a normal distribution assumption for age groups. 

N = Number of individuals. 

SD = Standard deviation. 

Source: Brochu et al. (2006b). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Exposure Factors Handbook Page
 

September 2011 6-27 
 

 

 

Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) per Unit of Body 

Weight (m3/kg-day) for Free-Living Normal-Weight Males and Females Aged 2.6 Months to 96 Years 

Age Group 

(years) 

Physiological Daily Inhalation Ratesa (m3/kg-day) 

Mean ± SD 

Percentileb 

5th 10th 25th 50th 75th 90th 95th 99th 

Males 

0.22 to <0.5 0.51 ± 0.09 0.36 0.39 0.45 0.51 0.57 0.63 0.66 0.73 

0.5 to <1 0.48 ± 0.07 0.36 0.39 0.43 0.48 0.53 0.57 0.60 0.64 

1 to <2 0.48 ± 0.06 0.38 0.41 0.44 0.48 0.52 0.56 0.58 0.62 

2 to <5 0.44 ± 0.04 0.38 0.39 0.42 0.44 0.47 0.50 0.51 0.54 

5 to <7 0.42 ± 0.05 0.34 0.35 0.38 0.42 0.45 0.48 0.49 0.52 

7 to <11 0.37 ± 0.06 0.27 0.29 0.33 0.37 0.41 0.45 0.47 0.52 

11 to <23 0.30 ± 0.05 0.22 0.24 0.27 0.30 0.33 0.36 0.38 0.41 

23 to <30 0.25 ± 0.04 0.18 0.20 0.22 0.25 0.27 0.30 0.31 0.34 

30 to <40 0.24 ± 0.03 0.18 0.19 0.21 0.24 0.26 0.28 0.29 0.32 

40 to <65 0.23 ± 0.04 0.16 0.18 0.20 0.23 0.26 0.28 0.30 0.33 

65 to ≤96 0.19 ± 0.03 0.14 0.15 0.17 0.19 0.21 0.23 0.24 0.26 

Females 

0.22 to <0.5 0.50 ± 0.09 0.35 0.39 0.44 0.50 0.57 0.62 0.66 0.72 

0.5 to <1 0.46 ± 0.06 0.36 0.38 0.42 0.46 0.51 0.55 0.57 0.61 

1 to <2 0.45 ± 0.08 0.33 0.35 0.40 0.45 0.50 0.55 0.58 0.63 

2 to <5 0.44 ± 0.07 0.32 0.35 0.39 0.44 0.49 0.53 0.56 0.61 

5 to <7 0.40 ± 0.05 0.32 0.33 0.36 0.40 0.43 0.46 0.47 0.51 

7 to <11 0.35 ± 0.06 0.25 0.27 0.31 0.35 0.39 0.43 0.45 0.50 

11 to <23 0.27 ± 0.05 0.19 0.21 0.24 0.27 0.30 0.33 0.35 0.38 

23 to <30 0.23 ± 0.04 0.16 0.18 0.20 0.23 0.26 0.29 0.30 0.33 

30 to <40 0.24 ± 0.04 0.18 0.19 0.21 0.24 0.26 0.28 0.29 0.32 

40 to <65 0.21 ± 0.04 0.15 0.16 0.19 0.21 0.24 0.26 0.27 0.30 

65 to ≤96 0.17 ± 0.04 0.11 0.13 0.15 0.17 0.20 0.22 0.23 0.26 

a Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG) × 

H × (VE/VO2) × 10−3, where H = 0.21 L of O2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily 

energy expenditure (kcal/day) and ECG = stored daily energy cost for growth (kcal/day). b Percentiles based on a normal distribution assumption for age groups. 

SD = Standard deviation. 

Source: Brochu et al. (2006b). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Page Exposure Factors Handbook 

6-28 September 2011 
 

Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates (PDIRs) (m3/kg-day) for 

Free-Living Normal-Weight and Overweight/Obese Males and Females Aged 4 to 96 Years 

Age Group (years) 

Physiological Daily Inhalation Ratesa (m3/kg-day) 

Mean ± SD 

Percentileb 

5th 10th 25th 50th 75th 90th 95th 99th 

Males—Normal-weight 

4 to <5.1 0.42 ± 0.04 0.35 0.36 0.39 0.42 0.45 0.47 0.49 0.52 

5.1 to <9.1 0.41 ± 0.06 0.31 0.34 0.37 0.41 0.45 0.48 0.50 0.54 

9.1 to <18.1 0.33 ± 0.05 0.26 0.27 0.30 0.33 0.37 0.40 0.41 0.45 

18.1 to <40.1 0.25± 0.04 0.18 0.20 0.22 0.25 0.27 0.29 0.31 0.33 

40.1 to <70.1 0.22 ± 0.04 0.16 0.17 0.20 0.22 0.25 0.28 0.29 0.32 

70.1 to ≤96 0.19 ± 0.03 0.13 0.14 0.16 0.19 0.21 0.23 0.24 0.26 

Males—Overweight/obese 

4 to <5.1 0.37 ± 0.04 0.30 0.31 0.34 0.37 0.40 0.42 0.44 0.47 

5.1 to <9.1 0.35 ± 0.08 0.22 0.25 0.29 0.35 0.40 0.45 0.47 0.53 

9.1 to <18.1 0.27 ± 0.04 0.20 0.22 0.24 0.27 0.29 0.32 0.33 0.36 

18.1 to <40.1 0.21 ± 0.04 0.15 0.17 0.19 0.21 0.22 0.26 0.27 0.30 

40.1 to <70.1 0.19 ± 0.03 0.14 0.15 0.17 0.19 0.22 0.24 0.25 0.28 

70.1 to ≤96 0.17 ± 0.03 0.12 0.13 0.15 0.17 0.19 0.21 0.22 0.24 

Females—Normal-weight 

4 to <5.1 0.40 ± 0.05 0.32 0.34 0.37 0.40 0.43 0.46 0.48 0.51 

5.1 to <9.1 0.37 ± 0.06 0.27 0.29 0.33 0.37 0.41 0.45 0.47 0.52 

9.1 to <18.1 0.29 ± 0.06 0.20 0.22 0.25 0.29 0.33 0.36 0.38 0.42 

18.1 to <40.1 0.23 ± 0.04 0.17 0.19 0.21 0.23 0.26 0.28 0. 30 0.32 

40.1 to <70.1 0.20 ± 0.04 0.14 0.15 0.18 0.20 0.23 0.25 0.27 0.29 

70.1 to ≤96 0.16 ± 0.04 0.11 0.12 0.14 0.16 0.19 0.20 0.22 0.24 

Females—Overweight/obese 

4 to <5.1 0.34 ± 0.04 0.27 0.28 0.31 0.34 0.37 0.40 0.41 0.44 

5.1 to <9.1 0.32 ± 0.07 0.21 0.23 0.27 0.32 0.36 0.40 0.43 0.47 

9.1 to <18.1 0.25 ± 0.05 0.17 0.18 0.21 0.25 0.28 0.31 0.33 0.36 

18.1 to <40.1 0.19 ± 0.03 0.14 0.15 0.17 0.19 0.21 0.22 0.23 0.25 

40.1 to <70.1 0.16 ± 0.03 0.11 0.12 0.14 0.16 0.18 0.20 0.21 0.23 

70.1 to ≤96 0.15 ± 0.03 0.10 0.11 0.13 0.15 0.16 0.18 0.19 0.21 

a Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG) × H × 

(VE/VO2) × 10−3, where H = 0.21 L of O2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily energy 

expenditure (kcal/day) and ECG = stored daily energy cost for growth (kcal/day). b Percentiles based on a normal distribution assumption for age groups. 

SD = Standard deviation. 

Source: Brochu et al. (2006b). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Exposure Factors Handbook Page
 

September 2011 6-29 
 

 

 

 

 

 

 

c 

Table 6-9. Physiological Daily Inhalation Rates (PDIRs) for Newborns Aged 1 Month or Less 

Physiological Daily Inhalation Ratesa 

Body Weight (kg) Mean ± SD 

Age Group N Mean ± SD (m3/day) (m3/kg-day) 

21 days (3 weeks) 13b,c 1.2 ± 0.2 0.85 ± 0.17d 0.74 ± 0.09d 

32 days (~1 month) 10e,f 4.7 ± 0.7 2.45 ± 0.59g 0.53 ± 0.10g 

33 days (~1 month) 10b,f 4.8 ± 0.3 2.99 ± 0.47g 0.62 ±0.09g 

a	 Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG) 

× H × (VE/VO2) × 10−3, where H = 0.21 L of O2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total 

daily energy expenditure (kcal/day) and ECG = stored daily energy cost for growth (kcal/day). b	 Formula-fed infants. 

Healthy infants with very low birth weight. d	 TDEEs based on nutritional balance measurements during 3-day periods. e	 Breast-fed infants. f	 Infants evaluated as being clinically healthy and neither underweight or overweight. g TDEEs based on 2

H2O and H2

18O disappearance rates from urine. 

N = Number of individuals. 

SD = Standard deviation. 

Source:	 Brochu et al. (2006b). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Page Exposure Factors Handbook 

6-30 September 2011 
 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-10. Non-Normalized Daily Inhalation Rates (m3/day) Derived Using Layton’s (1993) Method and 

CSFII Energy Intake Data 

Age 

Sample Size 

(Non-Weighted) Mean SEM 

Percentiles SE of 95th 

50 Percentile th 90th 95th 

Infancy 

0 to 2 months 182 3.63 0.14 3.30 5.44 7.10 0.64 

3 to 5 months 294 4.92 0.14 4.56 6.86 7.72 0.48 

6 to 8 months 261 6.09 0.15 5.67 8.38 9.76 0.86 

9 to 11 months 283 7.41 0.20 6.96 10.21 11.77 -

0 to 11 months 1,020 5.70 0.10 5.32 8.74 9.95 0.55 

Children 

1 year 934 8.77 0.08 8.30 12.19 13.79 0.25 

2 years 989 9.76 0.10 9.38 13.56 14.81 0.35 

3 years 1,644 10.64 0.10 10.28 14.59 16.03 0.27 

4 years 1,673 11.40 0.09 11.05 15.53 17.57 0.23 

5 years 790 12.07 0.13 11.56 15.72 18.26 0.47 

6 years 525 12.25 0.18 11.95 16.34 17.97 0.87 

7 years 270 12.86 0.21 12.51 16.96 19.06 1.27 

8 years 253 13.05 0.25 12.42 17.46 19.02 1.08 

9 years 271 14.93 0.29 14.45 19.68 22.45a 1.35 

10 years 234 15.37 0.35 15.19 20.87 22.90a 1.02 

11 years 233 15.49 0.32 15.07 21.04 23.91a 1.62 

12 years 170 17.59 0.54 17.11 25.07a 29.17a 1.61 

13 years 194 15.87 0.44 14.92 22.81a 26.23a 1.11 

14 years 193 17.87 0.62 15.90 25.75a 29.45a 4.38 

15 years 185 18.55 0.55 17.91 28.11a 29.93a 1.79 

16 years 201 18.34 0.54 17.37 27.56 31.01 2.07 

17 years 159 17.98 0.96 15.90 31.42a 36.69a -

18 years 135 18.59 0.78 17.34 28.80a 35.24a 4.24 

Adolescent Boys 

9 to 18 years 983 19.27 0.28 17.96 28.78 32.82 1.39 

Adolescent Girls 

9 to 18 years 992 14.27 0.22 13.99 21.17 23.30 0.61 

U.S. EPA Cancer Guidelines’ Age Groups with Greater Weighting 

0 through 1 year 1,954 7.50 0.08 7.19 11.50 12.86 0.17 

2 through 15 years 7,624 14.09 0.12 13.13 20.99 23.88 0.50 a FASEB/LSRO (1995) convention, adopted by CSFII, denotes a value that might be less statistically reliable 

than other estimates due to small cell size. 

- Denotes unable to calculate. 

SEM = Standard error of the mean. 

SE = Standard error. 

Source: Arcus-Arth and Blaisdell (2007). 

Exposure Factors Handbook Page
 

September 2011 6-31 
 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-11. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males and Females Combined 

Age Groupa,b Sample Size Meanc 95th,c 

Birth to <1 month 182 3.63 7.10 

1 to <3 months 182 3.63 7.10 

3 to <6 months 294 4.92 7.72 

6 to <12 months 544 6.78 10.81 

Birth to <1 year 1,020 5.70 9.95 

1 to <2 years 934 8.77 13.79 

2 to <3 years 989 9.76 14.81 

3 to <6 years 4,107 11.22 17.09 

6 to <11 years 1,553 13.42 19.86 

11 to <16 years 975 16.98 27.53 

16 to <21 years 495 18.29 33.99 a No other age groups from Table 6-10 (Arcus-Arth and Blaisdell, 2007) fit into the U.S. EPA age 

groupings. b See Table 6-25 for concordance with U.S. EPA age groupings. c Weighted (where possible) average of reported study means and 95th percentiles. 

Source: Arcus-Arth and Blaisdell (2007). 

Page Exposure Factors Handbook 

6-32 September 2011 
Table 6-12. Summary of Institute of Medicine (IOM) Energy Expenditure Recommendations 

for Active and Very Active People With Equivalent Inhalation Rates 

Males Females 

Energy 

Age Expenditure Inhalation Rate Energy Expenditure Inhalation Rate 

(years) (kcal/day) (m3/day) (kcal/day) (m3/day) 

<1 607 3.4 607 3.4 

1 869 4.9 869 4.9 

2 1,050 5.9 977 5.5 

3 1,485−1,683 8.4−9.5 1,395−1,649 7.9−9.3 

4 1,566−1,783 8.8−10.1 1,475−1,750 8.3−9.9 

5 1,658−1,894 9.4−10.7 1,557−1,854 8.8−10.5 

6 1,742−1,997 9.8−11.3 1,642−1,961 9.3−11.1 

7 1,840−2,115 10.4−11.9 1,719−2,058 9.7−11.6 

8 1,931−2,225 10.9−12.6 1,810−2,173 10.2−12.3 

9 2,043−2,359 11.5−13.3 1,890−2,273 10.7−12.8 

10 2,149−2,486 12.1−14.0 1,972−2,376 11.1−13.4 

11 2,279−2,640 12.9−14.9 2,071−2,500 11.7−14.1 

12 2,428−2,817 13.7−15.9 2,183−2,640 12.3−14.9 

13 2,618−3,038 14.8−17.2 2,281−2,762 12.9−15.6 

14 2,829−3,283 16.0−18.5 2,334−2,831 13.2−16.0 

15 3,013−3,499 17.0−19.8 2,362−2,870 13.3−16.2 

16 3,152−3,663 17.8−20.7 2,368−2,883 13.4−16.3 

17 3,226−3,754 18.2−21.2 2,353−2,871 13.3−16.2 

18 2,823−3,804 18.4−21.5 2,336−2,858 13.2−16.1 

19 to 30 3,015−3,490 17.0−19.7 2,373−2,683 13.4−15.2 

31 to 50 2,862−3,338 16.2−18.9 2,263−2,573 12.8−14.5 

51 to 70 2,671−3,147 15.1−17.8 2,124−2,435 12.0−13.8 

Source: Stifelman (2007). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Exposure Factors Handbook Page
 

September 2011 6-33 
 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-13. Mean Inhalation Rate Values (m3/day) for Males, Females, and 

Males and Females Combineda 

Age Groupb,c (years) Malesd Femalesd Combinedd 

Birth to <1 3.4 3.4 3.4 

1 to <2 4.9 4.9 4.9 

2 to <3 5.9 5.5 5.7 

3 to <6 9.5 9.1 9.3 

6 to <11 11.8 11.2 11.5 

11 to <16 16.1 14.0 15.0 

16 to <21 19.3 14.6 17.0 

21 to <31 18.4 14.3 16.3 

31 to <41 17.6 13.7 15.6 

41 to <51 17.6 13.7 15.6 

51 to <61 16.5 12.9 14.7 

61 to <71 16.5 12.9 14.7 

a Inhalation rates are for IOM Physical Activity Level (PAL) category “active”; the total number of 

subjects for all PAL categories was 3,007. Sample sizes were not reported. b Age groups from Table 6-12 were regrouped to fit into the U.S. EPA age groupings. c See Table 6-25 for concordance with U.S. EPA age groupings. d Weighted (where possible) average of reported study means. 

Source: Stifelman (2007). 

Page Exposure Factors Handbook 

6-34 September 2011 
 

 

Table 6-14. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Categorya 

Daily Average Inhalation Rate, Unadjusted for Body Weight 

(m3/day) 

Percentiles Age Group 

5th 10th 25th 50th 75th 90th 95th (years) N Mean Maximum 

Birth to <1 419 8.76 4.78 5.70 7.16 8.70 10.43 11.92 12.69 17.05 

1 to <2 308 13.49 9.73 10.41 11.65 13.12 15.02 17.02 17.90 24.24 

2 to <3 261 13.23 9.45 10.21 11.43 13.19 14.50 16.27 17.71 28.17 

3 to <6 540 12.64 10.43 10.87 11.39 12.59 13.64 14.63 15.41 19.53 

6 to <11 940 13.42 10.08 10.68 11.74 13.09 14.73 16.56 17.73 24.97 

11 to <16 1,337 15.32 11.40 12.11 13.28 14.79 16.82 19.54 21.21 28.54 

16 to <21 1,241 17.21 12.60 13.41 14.49 16.63 19.17 21.93 23.37 39.21 

21 to <31 701 18.82 12.69 13.56 15.49 18.17 21.24 24.57 27.13 43.42 

31 to <41 728 20.29 14.00 14.96 16.96 19.83 23.01 26.77 28.90 40.72 

41 to <51 753 20.94 14.66 15.54 17.50 20.59 23.89 26.71 28.37 45.98 

51 to <61 627 20.91 14.99 16.07 17.60 20.40 23.16 27.01 29.09 38.17 

61 to <71 678 17.94 13.91 14.50 15.88 17.60 19.54 21.77 23.50 28.09 

71 to <81 496 16.34 13.10 13.61 14.66 16.23 17.57 19.43 20.42 24.52 

≥81 255 15.15 11.95 12.57 13.82 14.90 16.32 18.01 18.69 22.64 

Daily Average Inhalation Rate, Adjusted for Body Weight 

(m3/day-kg) 

Percentiles Age Group 

5th 10th 25th 50th 75th 90th 95th (years) N Mean Maximum 

Birth to <1 419 1.09 0.91 0.94 1.00 1.09 1.16 1.26 1.29 1.48 

1 to <2 308 1.19 0.96 1.02 1.09 1.17 1.26 1.37 1.48 1.73 

2 to <3 261 0.95 0.78 0.82 0.87 0.94 1.01 1.09 1.13 1.36 

3 to <6 540 0.70 0.52 0.56 0.61 0.69 0.78 0.87 0.92 1.08 

6 to <11 940 0.44 0.32 0.34 0.38 0.43 0.50 0.55 0.58 0.80 

11 to <16 1,337 0.29 0.21 0.22 0.25 0.28 0.32 0.36 0.38 0.51 

16 to <21 1,241 0.23 0.17 0.18 0.20 0.23 0.25 0.28 0.30 0.39 

21 to <31 701 0.23 0.16 0.17 0.19 0.22 0.26 0.30 0.32 0.51 

31 to <41 728 0.24 0.16 0.18 0.20 0.23 0.27 0.31 0.34 0.46 

41 to <51 753 0.24 0.17 0.18 0.20 0.23 0.28 0.32 0.34 0.47 

51 to <61 627 0.24 0.16 0.18 0.20 0.24 0.27 0.30 0.34 0.43 

61 to <71 678 0.21 0.17 0.18 0.19 0.20 0.22 0.24 0.25 0.32 

71 to <81 496 0.20 0.17 0.18 0.19 0.20 0.21 0.23 0.24 0.31 

≥81 255 0.20 0.17 0.18 0.19 0.20 0.22 0.23 0.25 0.28 

a Individual daily averages are weighted by their 4-year sampling weights as assigned within NHANES 1999−2002 

when calculating the statistics in this table. Inhalation rate was estimated using a multiple linear regression model. 

N = Number of individuals. 

BW = Body weight. 

Source: U.S. EPA (2009a). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Exposure Factors Handbook Page
 

September 2011 6-35 
 

 

 

 

Table 6-15. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Categorya 

Daily Average Inhalation Rate, Unadjusted for Body Weight 

(m3/day) 

Age Group (years) N Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Birth to <1 415 8.52 4.84 5.49 6.84 8.41 9.78 11.65 12.66 26.25 

1 245 13.31 9.09 10.12 11.25 13.03 14.64 17.45 18.62 24.77 

2 255 12.74 8.91 10.07 11.38 12.60 13.95 15.58 16.36 23.01 

3 to <6 543 12.17 9.88 10.38 11.20 12.02 13.02 14.03 14.93 19.74 

6 to <11 894 12.41 9.99 10.35 11.02 11.95 13.42 15.13 16.34 20.82 

11 to <16 1,451 13.44 10.47 11.12 12.04 13.08 14.54 16.26 17.41 26.58 

16 to <21 1,182 13.59 9.86 10.61 11.78 13.20 15.02 17.12 18.29 30.11 

21 to <31 1,023 14.57 10.15 10.67 11.94 14.10 16.62 19.32 21.14 30.23 

31 to <41 869 14.98 11.07 11.81 13.02 14.69 16.32 18.50 20.45 28.28 

41 to <51 763 16.20 12.11 12.57 14.16 15.88 17.96 19.92 21.34 35.88 

51 to <61 622 16.19 12.33 12.96 14.07 15.90 17.80 19.93 21.21 25.70 

61 to <71 700 12.99 10.40 10.77 11.78 12.92 13.91 15.39 16.14 20.33 

71 to <81 470 12.04 9.89 10.20 10.89 11.82 12.96 14.11 15.19 17.70 

≥81 306 11.15 9.19 9.46 10.14 11.02 11.87 12.84 13.94 16.93 

Daily Average Inhalation Rate, Adjusted for Body Weight 

(m3/day-kg) 

Age Group (years) N Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Birth to <1 415 1.14 0.91 0.97 1.04 1.13 1.24 1.33 1.38 1.60 

1 245 1.20 0.97 1.01 1.10 1.18 1.30 1.41 1.46 1.73 

2 255 0.95 0.82 0.84 0.89 0.96 1.01 1.07 1.10 1.23 

3 to <6 543 0.69 0.48 0.54 0.60 0.68 0.77 0.88 0.92 1.12 

6 to <11 894 0.43 0.28 0.31 0.36 0.43 0.49 0.55 0.58 0.75 

11 to <16 1,451 0.25 0.19 0.20 0.22 0.24 0.28 0.31 0.34 0.47 

16 to <21 1,182 0.21 0.16 0.17 0.19 0.21 0.23 0.27 0.28 0.36 

21 to <31 1,023 0.21 0.14 0.16 0.18 0.20 0.23 0.26 0.28 0.40 

31 to <41 869 0.21 0.14 0.15 0.18 0.20 0.23 0.27 0.30 0.43 

41 to <51 763 0.22 0.15 0.16 0.19 0.21 0.25 0.28 0.31 0.41 

51 to <61 622 0.22 0.15 0.16 0.18 0.21 0.24 0.28 0.30 0.40 

61 to <71 700 0.18 0.14 0.15 0.16 0.17 0.19 0.21 0.22 0.27 

71 to <81 470 0.18 0.14 0.15 0.16 0.17 0.19 0.21 0.23 0.34 

≥81 306 0.18 0.14 0.15 0.16 0.18 0.20 0.21 0.22 0.28 

a Individual daily averages are weighted by their 4-year sampling weights as assigned within NHANES 1999−2002 

when calculating the statistics in this table. Inhalation rate was estimated using a multiple linear regression model. 

N = Number of individuals. 

Source: U.S. EPA (2009a) 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Page Exposure Factors Handbook 

6-36 September 2011 
Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-16. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males, Females, and 

Males and Females Combined 

Age Group (years) N Mean 95th 

Males 

Birth to <1 419 8.76 12.69 

1 to <2 308 13.49 17.90 

2 to <3 261 13.23 17.71 

3 to <6 540 12.64 15.41 

6 to <11 940 13.42 17.73 

11 to <16 1,337 15.32 21.21 

16 to <21 1,241 17.21 23.37 

21 to <31 701 18.82 27.13 

31 to <41 728 20.29 28.90 

41 to <51 753 20.94 28.37 

51 to <61 627 20.91 29.09 

61 to <71 678 17.94 23.50 

71 to <81 496 16.34 20.42 

≥81 255 15.15 18.69 

Females 

Birth to <1 415 8.52 12.66 

1 to <2 245 13.31 18.62 

2 to <3 255 12.74 16.36 

3 to <6 543 12.17 14.93 

6 to <11 894 12.41 16.34 

11 to <16 1,451 13.44 17.41 

16 to <21 1,182 13.59 18.29 

21 to <31 1,023 14.57 21.14 

31 to <41 869 14.98 20.45 

41 to <51 763 16.20 21.34 

51 to <61 622 16.19 21.21 

61 to <71 700 12.99 16.14 

71 to <81 470 12.04 15.19 

≥81 306 11.15 13.94 

Exposure Factors Handbook Page
 

September 2011 6-37 
 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-16. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males, Females, and Males 

and Females Combined (continued) 

Age Group (years) N Mean 95th 

Males and Females Combineda 

Birth to <1 834 8.64 12.67 

1 to <2 553 13.41 18.22 

2 to <3 516 12.99 17.04 

3 to <6 1,083 12.40 15.17 

6 to <11 1,834 12.93 17.05 

11 to <16 2,788 14.34 19.23 

16 to <21 2,423 15.44 20.89 

21 to <31 1,724 16.30 23.57 

31 to <41 1,597 17.40 24.30 

41 to <51 1,516 18.55 24.83 

51 to <61 1,249 18.56 25.17 

61 to <71 1,378 15.43 19.76 

71 to <81 966 14.25 17.88 

≥81 561 12.97 16.10 

a Weighted average of reported male and female means and 95th percentiles. 

N = Number of individuals. 

Source: U.S. EPA (2009a). 

Page Exposure Factors Handbook 

6-38 September 2011 
 

 

 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Table 6-17. Descriptive Statistics for Average Ventilation Rate, 

a Unadjusted for Body Weight, While Performing Activities Within 

the Specified Activity Category, for Males by Age Category 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 419 

1 308 

2 261 

3 to <6 540 

6 to <11 940 

11 to <16 1,337 

16 to <21 1,241 

21 to <31 701 

31 to <41 728 

41 to <51 753 

51 to <61 627 

61 to <71 678 

71 to <81 496 

≥81 255 

3.08E−03 1.66E−03 1.91E−03 2.45E−03 3.00E−03 3.68E−03 4.35E−03 4.77E−03 7.19E−03 

4.50E−03 3.11E−03 3.27E−03 3.78E−03 4.35E−03 4.95E−03 5.90E−03 6.44E−03 1.00E−02 

4.61E−03 3.01E−03 3.36E−03 3.94E−03 4.49E−03 5.21E−03 6.05E−03 6.73E−03 8.96E−03 

4.36E−03 3.06E−03 3.30E−03 3.76E−03 4.29E−03 4.86E−03 5.54E−03 5.92E−03 7.67E−03 

4.61E−03 3.14E−03 3.39E−03 3.83E−03 4.46E−03 5.21E−03 6.01E−03 6.54E−03 9.94E−03 

5.26E−03 3.53E−03 3.78E−03 4.34E−03 5.06E−03 5.91E−03 6.94E−03 7.81E−03 1.15E−02 

5.31E−03 3.55E−03 3.85E−03 4.35E−03 5.15E−03 6.09E−03 6.92E−03 7.60E−03 1.28E−02 

4.73E−03 3.16E−03 3.35E−03 3.84E−03 4.56E−03 5.42E−03 6.26E−03 6.91E−03 1.12E−02 

5.16E−03 3.37E−03 3.62E−03 4.23E−03 5.01E−03 5.84E−03 6.81E−03 7.46E−03 1.09E−02 

5.65E−03 3.74E−03 4.09E−03 4.73E−03 5.53E−03 6.47E−03 7.41E−03 7.84E−03 1.08E−02 

5.78E−03 3.96E−03 4.20E−03 4.78E−03 5.57E−03 6.54E−03 7.74E−03 8.26E−03 1.18E−02 

5.98E−03 4.36E−03 4.57E−03 5.13E−03 5.81E−03 6.68E−03 7.45E−03 7.93E−03 1.23E−02 

6.07E−03 4.26E−03 4.55E−03 5.17E−03 6.00E−03 6.77E−03 7.65E−03 8.33E−03 1.05E−02 

5.97E−03 4.20E−03 4.49E−03 5.23E−03 5.90E−03 6.68E−03 7.36E−03 7.76E−03 1.00E−02 

Sedentary and Passive Activities (METS ≤1.5—Includes Sleep or Nap) 

Birth to <1 419 

1 308 

2 261 

3 to <6 540 

6 to <11 940 

11 to <16 1,337 

3.18E−03 1.74E−03 1.99E−03 2.50E−03 3.10E−03 3.80E−03 4.40E−03 4.88E−03 7.09E−03 

4.62E−03 3.17E−03 3.50E−03 3.91E−03 4.49E−03 5.03E−03 5.95E−03 6.44E−03 9.91E−03 

4.79E−03 3.25E−03 3.66E−03 4.10E−03 4.69E−03 5.35E−03 6.05E−03 6.71E−03 9.09E−03 

4.58E−03 3.47E−03 3.63E−03 4.07E−03 4.56E−03 5.03E−03 5.58E−03 5.82E−03 7.60E−03 

4.87E−03 3.55E−03 3.78E−03 4.18E−03 4.72E−03 5.40E−03 6.03E−03 6.58E−03 9.47E−03 

5.64E−03 4.03E−03 4.30E−03 4.79E−03 5.43E−03 6.26E−03 7.20E−03 7.87E−03 1.11E−02 

Exposure Factors Handbook PageSeptember 2011 6-39
 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-40 September 2011 

Table 6-17. Descriptive Statistics for Average Ventilation Rate,a Unadjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Males by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

1,241 5.76E−03 4.17E−03 4.42E−03 4.93E−03 5.60E−03 6.43E−03 7.15E−03 7.76E−03 1.35E−02 

701 5.11E−03 3.76E−03 3.99E−03 4.33E−03 5.00E−03 5.64E−03 6.42E−03 6.98E−03 1.03E−02 

728 5.57E−03 3.99E−03 4.42E−03 4.86E−03 5.45E−03 6.17E−03 6.99E−03 7.43E−03 1.00E−02 

753 6.11E−03 4.65E−03 4.92E−03 5.37E−03 6.02E−03 6.65E−03 7.46E−03 7.77E−03 1.05E−02 

627 6.27E−03 4.68E−03 5.06E−03 5.50E−03 6.16E−03 6.89E−03 7.60E−03 8.14E−03 1.04E−02 

678 6.54E−03 5.02E−03 5.31E−03 5.85E−03 6.47E−03 7.12E−03 7.87E−03 8.22E−03 1.09E−02 

496 6.65E−03 5.26E−03 5.55E−03 5.96E−03 6.59E−03 7.18E−03 7.81E−03 8.26E−03 9.9E−03 

255 6.44E−03 5.09E−03 5.37E−03 5.82E−03 6.43E−03 7.01E−03 7.57E−03 7.90E−03 9.13E−03 

Light Intensity Activities (1.5< METS ≤3.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 7.94E−03 4.15E−03 5.06E−03 6.16E−03 7.95E−03 9.57E−03 1.08E−02 1.19E−02 1.55E−02 

308 1.16E−02 8.66E−03 8.99E−03 9.89E−03 1.14E−02 1.29E−02 1.44E−02 1.58E−02 2.11E−02 

261 1.17E−02 8.52E−03 9.14E−03 9.96E−03 1.14E−02 1.30E−02 1.47E−02 1.53E−02 1.90E−02 

540 1.14E−02 9.20E−03 9.55E−03 1.02E−02 1.11E−02 1.23E−02 1.34E−02 1.40E−02 1.97E−02 

940 1.16E−02 8.95E−03 9.33E−03 1.02E−02 1.13E−02 1.28E−02 1.46E−02 1.56E−02 2.18E−02 

1,337 1.32E−02 9.78E−03 1.03E−02 1.13E−02 1.28E−02 1.47E−02 1.64E−02 1.87E−02 2.69E−02 

1,241 1.34E−02 1.00E−02 1.05E−02 1.15E−02 1.30E−02 1.50E−02 1.70E−02 1.80E−02 2.91E−02 

701 1.30E−02 9.68E−03 1.02E−02 1.13E−02 1.24E−02 1.40E−02 1.65E−02 1.77E−02 2.72E−02 

728 1.36E−02 1.06E−02 1.11E−02 1.20E−02 1.33E−02 1.48E−02 1.65E−02 1.81E−02 2.55E−02 

753 1.44E−02 1.12E−02 1.18E−02 1.30E−02 1.41E−02 1.56E−02 1.74E−02 1.83E−02 2.30E−02 

627 1.46E−02 1.11E−02 1.16E−02 1.30E−02 1.44E−02 1.59E−02 1.80E−02 1.94E−02 2.55E−02 

678 1.41E−02 1.11E−02 1.17E−02 1.27E−02 1.39E−02 1.54E−02 1.69E−02 1.80E−02 2.05E−02 

496 1.39E−02 1.12E−02 1.17E−02 1.27E−02 1.37E−02 1.50E−02 1.62E−02 1.69E−02 2.00E−02 

255 1.38E−02 1.10E−02 1.17E−02 1.26E−02 1.38E−02 1.47E−02 1.60E−02 1.67E−02 2.07E−02 
 

 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Exposure Factors Handbook PageSeptember 2011 6-41

Table 6-17. Descriptive Statistics for Average Ventilation Rate,a Unadjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Males by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Moderate Intensity Activities (3.0< METS ≤6.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 1.45E−02 7.41E−03 8.81E−03 1.15E−02 1.44E−02 1.70E−02 2.01E−02 2.25E−02 3.05E−02 

308 2.14E−02 1.45E−02 1.59E−02 1.80E−02 2.06E−02 2.41E−02 2.69E−02 2.89E−02 3.99E−02 

261 2.15E−02 1.54E−02 1.67E−02 1.84E−02 2.08E−02 2.41E−02 2.69E−02 2.97E−02 5.09E−02 

540 2.10E−02 1.63E−02 1.72E−02 1.87E−02 2.06E−02 2.29E−02 2.56E−02 2.71E−02 3.49E−02 

940 2.23E−02 1.64E−02 1.72E−02 1.93E−02 2.16E−02 2.50E−02 2.76E−02 2.95E−02 4.34E−02 

1,337 2.64E−02 1.93E−02 2.05E−02 2.26E−02 2.54E−02 2.92E−02 3.38E−02 3.69E−02 5.50E−02 

1,241 2.90E−02 2.03E−02 2.17E−02 2.45E−02 2.80E−02 3.17E−02 3.82E−02 4.21E−02 6.74E−02 

701 2.92E−02 1.97E−02 2.10E−02 2.42E−02 2.79E−02 3.30E−02 3.88E−02 4.31E−02 7.17E−02 

728 3.03E−02 2.14E−02 2.27E−02 2.51E−02 2.91E−02 3.41E−02 3.96E−02 4.35E−02 5.77E−02 

753 3.16E−02 2.26E−02 2.44E−02 2.72E−02 3.04E−02 3.51E−02 4.03E−02 4.50E−02 6.34E−02 

627 3.27E−02 2.24E−02 2.40E−02 2.80E−02 3.14E−02 3.70E−02 4.17E−02 4.58E−02 7.05E−02 

678 2.98E−02 2.25E−02 2.40E−02 2.61E−02 2.92E−02 3.23E−02 3.69E−02 4.00E−02 5.23E−02 

496 2.93E−02 2.28E−02 2.39E−02 2.61E−02 2.88E−02 3.20E−02 3.57E−02 3.73E−02 4.49E−02 

255 2.85E−02 2.25E−02 2.34E−02 2.55E−02 2.82E−02 3.10E−02 3.34E−02 3.55E−02 4.11E−02 
 

 

 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-42 September 2011 

Table 6-17. Descriptive Statistics for Average Ventilation Rate,a Unadjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Males by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

High Intensity (METS >6.0) 

Birth to <1 183 2.75E−02 1.51E−02 1.73E−02 2.06E−02 2.78E−02 3.25E−02 3.84E−02 4.22E−02 5.79E−02 

1 164 4.03E−02 2.83E−02 3.17E−02 3.47E−02 3.98E−02 4.43E−02 5.16E−02 5.59E−02 6.07E−02 

2 162 4.05E−02 2.82E−02 2.97E−02 3.45E−02 4.06E−02 4.62E−02 5.19E−02 5.51E−02 9.20E−02 

3 to <6 263 3.90E−02 2.95E−02 3.14E−02 3.40E−02 3.78E−02 4.32E−02 4.89E−02 5.22E−02 6.62E−02 

6 to <11 637 4.36E−02 3.07E−02 3.28E−02 3.58E−02 4.19E−02 4.95E−02 5.66E−02 6.24E−02 8.99E−02 

11 to <16 1,111 5.08E−02 3.43E−02 3.68E−02 4.15E−02 4.91E−02 5.74E−02 6.63E−02 7.29E−02 1.23E−01 

16 to <21 968 5.32E−02 3.60E−02 3.83E−02 4.35E−02 5.05E−02 5.93E−02 7.15E−02 8.30E−02 1.30E−01 

21 to <31 546 5.39E−02 3.36E−02 3.80E−02 4.48E−02 5.15E−02 6.16E−02 7.24E−02 8.21E−02 1.12E−01 

31 to <41 567 5.43E−02 3.78E−02 4.04E−02 4.54E−02 5.21E−02 6.12E−02 7.14E−02 7.74E−02 1.04E−01 

41 to <51 487 5.73E−02 3.83E−02 4.25E−02 4.83E−02 5.52E−02 6.45E−02 7.56E−02 8.44E−02 1.10E−01 

51 to <61 452 5.84E−02 3.90E−02 4.16E−02 4.87E−02 5.59E−02 6.60E−02 7.86E−02 8.65E−02 1.41E−01 

61 to <71 490 5.41E−02 3.63E−02 3.95E−02 4.52E−02 5.24E−02 6.08E−02 7.20E−02 7.52E−02 1.02E−01 

71 to <81 343 5.25E−02 3.70E−02 3.95E−02 4.41E−02 5.00E−02 5.90E−02 6.76E−02 7.65E−02 9.73E−02 

≥81 168 5.33E−02 3.54E−02 3.92E−02 4.55E−02 5.09E−02 6.12E−02 6.96E−02 7.71E−02 9.68E−02 

a An individual’s ventilation rate for the given activity category equals the weighted average of the individual’s activity-specific ventilation rates for 

activities falling within the category, estimated using a multiple linear regression model, with weights corresponding to the number of minutes spent 

performing the activity. Numbers in these two columns represent averages, calculated across individuals in the specified age category, of these 

weighted averages. These are weighted averages, with the weights corresponding to the 4-year sampling weights assigned within NHANES 

1999−2002. 

N = Number of individuals. 

MET = Metabolic equivalent. 

Source: U.S. EPA (2009a). 
 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Exposure Factors Handbook PageSeptember 2011 6-43

Table 6-18. Descriptive Statistics for Average Ventilation Rate, 

a Adjusted for Body Weight, While Performing Activities Within the 

Specified Activity Category, for Males by Age Category 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 419 3.85E−04 2.81E−04 3.01E−04 3.37E−04 3.80E−04 4.27E−04 4.65E−04 5.03E−04 6.66E−04 

1 308 3.95E−04 2.95E−04 3.13E−04 3.45E−04 3.84E−04 4.41E−04 4.91E−04 5.24E−04 6.26E−04 

2 261 3.30E−04 2.48E−04 2.60E−04 2.89E−04 3.26E−04 3.62E−04 4.05E−04 4.42E−04 5.38E−04 

3 to <6 540 2.43E−04 1.60E−04 1.74E−04 1.98E−04 2.37E−04 2.79E−04 3.14E−04 3.50E−04 4.84E−04 

6 to <11 940 1.51E−04 1.02E−04 1.09E−04 1.25E−04 1.48E−04 1.74E−04 2.00E−04 2.15E−04 3.02E−04 

11 to <16 1,337 9.80E−05 6.70E−05 7.20E−05 8.10E−05 9.40E−05 1.10E−04 1.29E−04 1.41E−04 2.08E−04 

16 to <21 1,241 7.10E−05 4.70E−05 5.20E−05 6.10E−05 6.90E−05 8.00E−05 9.00E−05 9.80E−05 1.47E−04 

21 to <31 701 5.80E−05 3.80E−05 4.20E−05 4.80E−05 5.60E−05 6.60E−05 7.60E−05 8.30E−05 1.32E−04 

31 to <41 728 6.10E−05 3.80E−05 4.30E−05 5.00E−05 6.00E−05 7.00E−05 8.00E−05 8.60E−05 1.27E−04 

41 to <51 753 6.50E−05 4.40E−05 4.70E−05 5.40E−05 6.40E−05 7.40E−05 8.60E−05 9.20E−05 1.37E−04 

51 to <61 627 6.60E−05 4.50E−05 4.90E−05 5.50E−05 6.40E−05 7.60E−05 8.60E−05 9.30E−05 1.41E−04 

61 to <71 678 6.90E−05 5.10E−05 5.40E−05 6.00E−05 6.80E−05 7.60E−05 8.60E−05 9.30E−05 1.17E−04 

71 to <81 496 7.50E−05 5.50E−05 5.80E−05 6.40E−05 7.30E−05 8.30E−05 9.30E−05 9.90E−05 1.25E−04 

≥81 255 8.00E−05 6.10E−05 6.40E−05 7.10E−05 7.80E−05 8.80E−05 9.70E−05 1.11E−04 1.22E−04 

Sedentary and Passive Activities (METS ≤1.5—Includes Sleep or Nap) 

Birth to <1 419 3.97E−04 3.03E−04 3.17E−04 3.51E−04 3.91E−04 4.37E−04 4.70E−04 4.98E−04 6.57E−04 

1 308 4.06E−04 3.21E−04 3.31E−04 3.63E−04 3.97E−04 4.48E−04 4.88E−04 5.25E−04 6.19E−04 

2 261 3.43E−04 2.74E−04 2.86E−04 3.09E−04 3.40E−04 3.69E−04 4.05E−04 4.46E−04 5.10E−04 

3 to <6 540 2.55E−04 1.78E−04 1.93E−04 2.15E−04 2.50E−04 2.88E−04 3.27E−04 3.46E−04 4.54E−04 

6 to <11 940 1.60E−04 1.13E−04 1.18E−04 1.35E−04 1.57E−04 1.80E−04 2.09E−04 2.18E−04 2.89E−04 

11 to <16 1,337 1.05E−04 7.70E−05 8.00E−05 8.80E−05 1.01E−04 1.18E−04 1.35E−04 1.42E−04 1.95E−04 
 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-44 September 2011 

Table 6-18. Descriptive Statistics for Average Ventilation Rate,a Adjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Males by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

1,241 7.70E−05 5.50E−05 6.00E−05 6.80E−05 7.60E−05 8.50E−05 9.50E−05 1.02E−04 1.32E−04 

701 6.20E−05 4.70E−05 4.90E−05 5.50E−05 6.10E−05 6.90E−05 7.70E−05 8.20E−05 1.18E−04 

728 6.60E−05 4.60E−05 5.00E−05 5.70E−05 6.50E−05 7.40E−05 8.20E−05 8.60E−05 1.19E−04 

753 7.10E−05 5.40E−05 5.70E−05 6.20E−05 7.00E−05 7.80E−05 8.60E−05 9.10E−05 1.29E−04 

627 7.20E−05 5.50E−05 5.80E−05 6.30E−05 7.10E−05 7.90E−05 8.80E−05 9.20E−05 1.35E−04 

678 7.60E−05 6.10E−05 6.40E−05 6.90E−05 7.50E−05 8.10E−05 8.90E−05 9.40E−05 1.11E−04 

496 8.20E−05 6.70E−05 7.00E−05 7.50E−05 8.10E−05 8.80E−05 9.40E−05 9.80E−05 1.15E−04 

255 8.60E−05 7.10E−05 7.50E−05 8.00E−05 8.60E−05 9.20E−05 9.90E−05 1.06E−04 1.15E−04 

Light Intensity Activities (1.5< METS ≤3.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 9.88E−04 7.86E−04 8.30E−04 8.97E−04 9.72E−04 1.07E−03 1.17E−03 1.20E−03 1.44E−03 

308 1.02E−03 8.36E−04 8.59E−04 9.18E−04 1.01E−03 1.10E−03 1.22E−03 1.30E−03 1.49E−03 

261 8.37E−04 6.83E−04 7.16E−04 7.61E−04 8.26E−04 8.87E−04 9.95E−04 1.03E−03 1.18E−03 

540 6.33E−04 4.41E−04 4.80E−04 5.44E−04 6.26E−04 7.11E−04 7.94E−04 8.71E−04 1.08E−03 

940 3.84E−04 2.67E−04 2.86E−04 3.24E−04 3.77E−04 4.37E−04 4.93E−04 5.29E−04 7.09E−04 

1,337 2.46E−04 1.76E−04 1.87E−04 2.09E−04 2.38E−04 2.82E−04 3.11E−04 3.32E−04 4.42E−04 

1,241 1.79E−04 1.37E−04 1.44E−04 1.56E−04 1.78E−04 1.99E−04 2.18E−04 2.30E−04 3.32E−04 

701 1.58E−04 1.24E−04 1.30E−04 1.42E−04 1.54E−04 1.71E−04 1.90E−04 2.07E−04 2.90E−04 

728 1.61E−04 1.18E−04 1.28E−04 1.40E−04 1.57E−04 1.77E−04 1.98E−04 2.09E−04 2.81E−04 

753 1.66E−04 1.26E−04 1.33E−04 1.47E−04 1.64E−04 1.81E−04 2.00E−04 2.14E−04 3.32E−04 

627 1.67E−04 1.27E−04 1.35E−04 1.48E−04 1.65E−04 1.83E−04 2.01E−04 2.16E−04 2.87E−04 

678 1.64E−04 1.37E−04 1.41E−04 1.50E−04 1.63E−04 1.75E−04 1.87E−04 1.95E−04 2.69E−04 

496 1.71E−04 1.43E−04 1.48E−04 1.58E−04 1.70E−04 1.82E−04 1.95E−04 2.03E−04 2.63E−04 

255 1.85E−04 1.52E−04 1.60E−04 1.68E−04 1.83E−04 1.98E−04 2.12E−04 2.24E−04 2.47E−04 
 

 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Exposure Factors Handbook PageSeptember 2011 6-45

Table 6-18. Descriptive Statistics for Average Ventilation Rate,a Adjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Males by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Moderate Intensity Activities (3.0< METS ≤6.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 1.80E−03 1.40E−03 1.49E−03 1.62E−03 1.78E−03 1.94E−03 2.18E−03 2.28E−03 3.01E−03 

308 1.88E−03 1.41E−03 1.50E−03 1.65E−03 1.82E−03 2.02E−03 2.34E−03 2.53E−03 3.23E−03 

261 1.55E−03 1.21E−03 1.28E−03 1.40E−03 1.54E−03 1.66E−03 1.84E−03 2.02E−03 2.29E−03 

540 1.17E−03 8.05E−04 8.83E−04 9.99E−04 1.12E−03 1.31E−03 1.56E−03 1.68E−03 2.10E−03 

940 7.36E−04 5.03E−04 5.45E−04 6.18E−04 7.14E−04 8.34E−04 9.58E−04 1.04E−03 1.43E−03 

1,337 4.91E−04 3.59E−04 3.75E−04 4.18E−04 4.73E−04 5.52E−04 6.35E−04 6.81E−04 1.06E−03 

1,241 3.87E−04 2.81E−04 2.96E−04 3.34E−04 3.80E−04 4.31E−04 4.86E−04 5.18E−04 7.11E−04 

701 3.57E−04 2.43E−04 2.64E−04 2.96E−04 3.45E−04 4.04E−04 4.68E−04 5.09E−04 8.24E−04 

728 3.57E−04 2.42E−04 2.65E−04 3.00E−04 3.44E−04 4.00E−04 4.71E−04 5.21E−04 7.62E−04 

753 3.66E−04 2.55E−04 2.72E−04 3.10E−04 3.53E−04 4.08E−04 4.69E−04 5.18E−04 7.16E−04 

627 3.76E−04 2.59E−04 2.78E−04 3.13E−04 3.66E−04 4.31E−04 4.82E−04 5.49E−04 7.64E−04 

678 3.44E−04 2.72E−04 2.84E−04 3.13E−04 3.42E−04 3.71E−04 3.99E−04 4.24E−04 5.73E−04 

496 3.60E−04 2.91E−04 3.06E−04 3.28E−04 3.59E−04 3.88E−04 4.18E−04 4.36E−04 5.49E−04 

255 3.83E−04 3.12E−04 3.23E−04 3.47E−04 3.77E−04 4.16E−04 4.47E−04 4.70E−04 5.29E−04 
 

 

 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-46 September 2011 

Table 6-18. Descriptive Statistics for Average Ventilation Rate,a Adjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Males by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

High Intensity (METS >6.0) 

Birth to <1 183 3.48E−03 2.70E−03 2.93E−03 3.10E−03 3.46E−03 3.81E−03 4.14E−03 4.32E−03 5.08E−03 

1 164 3.52E−03 2.52E−03 2.89E−03 3.22E−03 3.57E−03 3.91E−03 4.11E−03 4.34E−03 4.86E−03 

2 162 2.89E−03 2.17E−03 2.34E−03 2.58E−03 2.87E−03 3.20E−03 3.43E−03 3.54E−03 4.30E−03 

3 to <6 263 2.17E−03 1.55E−03 1.66E−03 1.81E−03 2.11E−03 2.50E−03 2.73E−03 2.98E−03 3.62E−03 

6 to <11 637 1.41E−03 9.36E−04 1.03E−03 1.19E−03 1.38E−03 1.59E−03 1.83E−03 1.93E−03 2.68E−03 

11 to <16 1,111 9.50E−04 6.35E−04 6.96E−04 7.90E−04 9.09E−04 1.09E−03 1.27E−03 1.36E−03 1.98E−03 

16 to <21 968 7.11E−04 4.75E−04 5.27E−04 5.99E−04 6.91E−04 8.02E−04 9.17E−04 9.97E−04 1.94E−03 

21 to <31 546 6.60E−04 4.49E−04 4.74E−04 5.43E−04 6.44E−04 7.49E−04 8.55E−04 9.73E−04 1.27E−03 

31 to <41 567 6.44E−04 4.42E−04 4.70E−04 5.33E−04 6.25E−04 7.31E−04 8.53E−04 9.30E−04 1.23E−03 

41 to <51 487 6.55E−04 4.38E−04 4.85E−04 5.48E−04 6.25E−04 7.41E−04 8.56E−04 9.44E−04 1.77E−03 

51 to <61 452 6.75E−04 4.46E−04 4.81E−04 5.47E−04 6.43E−04 7.67E−04 9.13E−04 1.02E−03 1.32E−03 

61 to <71 490 6.24E−04 4.41E−04 4.70E−04 5.31E−04 6.12E−04 7.03E−04 7.88E−04 8.55E−04 1.08E−03 

71 to <81 343 6.46E−04 4.66E−04 5.02E−04 5.53E−04 6.26E−04 7.16E−04 8.49E−04 9.10E−04 1.04E−03 

≥81 168 7.16E−04 5.05E−04 5.44E−04 6.02E−04 7.00E−04 8.05E−04 9.42E−04 9.91E−04 1.35E−03 

a An individual’s ventilation rate for the given activity category equals the weighted average of the individual’s activity-specific ventilation rates for 

activities falling within the category, estimated using a multiple linear regression model, with weights corresponding to the number of minutes spent 

performing the activity. Numbers in these two columns represent averages, calculated across individuals in the specified age category, of these 

weighted averages. These are weighted averages, with the weights corresponding to the 4-year sampling weights assigned within NHANES 

1999−2002. 

N = Number of individuals. 

MET = Metabolic equivalent. 

Source: U.S. EPA (2009a). 
 

 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Exposure Factors Handbook PageSeptember 2011 6-47

Table 6-19. Descriptive Statistics for Average Ventilation Rate,a Unadjusted for Body Weight, While Performing Activities Within 

the Specified Activity Category, for Females by Age Category 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 415 

1 245 

2 255 

3 to <6 543 

6 to <11 894 

11 to <16 1,451 

16 to <21 1,182 

21 to <31 1,023 

31 to <41 869 

41 to <51 763 

51 to <61 622 

61 to <71 700 

71 to <81 470 

≥81 306 

2.92E−03 1.54E−03 1.72E−03 2.27E−03 2.88E−03 3.50E−03 4.04E−03 4.40E−03 8.69E−03 

4.59E−03 3.02E−03 3.28E−03 3.76E−03 4.56E−03 5.32E−03 5.96E−03 6.37E−03 9.59E−03 

4.56E−03 3.00E−03 3.30E−03 3.97E−03 4.52E−03 5.21E−03 5.76E−03 6.15E−03 9.48E−03 

4.18E−03 2.90E−03 3.20E−03 3.62E−03 4.10E−03 4.71E−03 5.22E−03 5.73E−03 7.38E−03 

4.36E−03 2.97E−03 3.17E−03 3.69E−03 4.24E−03 4.93E−03 5.67E−03 6.08E−03 8.42E−03 

4.81E−03 3.34E−03 3.57E−03 3.99E−03 4.66E−03 5.39E−03 6.39E−03 6.99E−03 9.39E−03 

4.40E−03 2.78E−03 2.96E−03 3.58E−03 4.26E−03 5.05E−03 5.89E−03 6.63E−03 1.23E−02 

3.89E−03 2.54E−03 2.74E−03 3.13E−03 3.68E−03 4.44E−03 5.36E−03 6.01E−03 9.58E−03 

4.00E−03 2.66E−03 2.86E−03 3.31E−03 3.89E−03 4.54E−03 5.28E−03 5.77E−03 8.10E−03 

4.40E−03 3.00E−03 3.23E−03 3.69E−03 4.25E−03 4.95E−03 5.66E−03 6.25E−03 8.97E−03 

4.56E−03 3.12E−03 3.30E−03 3.72E−03 4.41E−03 5.19E−03 6.07E−03 6.63E−03 8.96E−03 

4.47E−03 3.22E−03 3.35E−03 3.78E−03 4.38E−03 4.99E−03 5.72E−03 6.37E−03 9.57E−03 

4.52E−03 3.31E−03 3.47E−03 3.89E−03 4.40E−03 5.11E−03 5.67E−03 6.06E−03 7.35E−03 

4.49E−03 3.17E−03 3.49E−03 3.82E−03 4.39E−03 4.91E−03 5.61E−03 6.16E−03 8.27E−03 

Sedentary and Passive Activities (METS ≤1.5—Includes Sleep or Nap) 

Birth to <1 415 

1 245 

2 255 

3 to <6 543 

6 to <11 894 

11 to <16 1,451 

3.00E−03 1.60E−03 1.80E−03 2.32E−03 2.97E−03 3.58E−03 4.11E−03 4.44E−03 9.59E−03 

4.71E−03 3.26E−03 3.44E−03 3.98E−03 4.73E−03 5.30E−03 5.95E−03 6.63E−03 9.50E−03 

4.73E−03 3.34E−03 3.53E−03 4.19E−03 4.67E−03 5.25E−03 5.75E−03 6.22E−03 9.42E−03 

4.40E−03 3.31E−03 3.49E−03 3.95E−03 4.34E−03 4.84E−03 5.29E−03 5.73E−03 7.08E−03 

4.64E−03 3.41E−03 3.67E−03 4.04E−03 4.51E−03 5.06E−03 5.88E−03 6.28E−03 8.31E−03 

5.21E−03 3.90E−03 4.16E−03 4.53E−03 5.09E−03 5.68E−03 6.53E−03 7.06E−03 9.07E−03 
 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-48 September 2011 

Table 6-19. Descriptive Statistics for Average Ventilation Rate,a Unadjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Females by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

1,182 4.76E−03 3.26E−03 3.56E−03 4.03E−03 4.69E−03 5.32E−03 6.05E−03 6.60E−03 1.18E−02 

1,023 4.19E−03 3.04E−03 3.19E−03 3.55E−03 4.00E−03 4.63E−03 5.38E−03 6.02E−03 9.22E−03 

869 4.33E−03 3.22E−03 3.45E−03 3.77E−03 4.24E−03 4.80E−03 5.33E−03 5.79E−03 7.70E−03 

763 4.75E−03 3.60E−03 3.82E−03 4.18E−03 4.65E−03 5.19E−03 5.74E−03 6.26E−03 8.70E−03 

622 4.96E−03 3.78E−03 4.00E−03 4.36E−03 4.87E−03 5.44E−03 6.06E−03 6.44E−03 8.30E−03 

700 4.89E−03 3.81E−03 4.02E−03 4.34E−03 4.81E−03 5.30E−03 5.86E−03 6.29E−03 8.18E−03 

470 4.95E−03 4.07E−03 4.13E−03 4.41E−03 4.89E−03 5.42E−03 5.89E−03 6.15E−03 7.59E−03 

306 4.89E−03 3.93E−03 4.10E−03 4.39E−03 4.79E−03 5.25E−03 5.71E−03 6.12E−03 7.46E−03 

Light Intensity Activities (1.5< METS ≤3.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

415 7.32E−03 3.79E−03 4.63E−03 5.73E−03 7.19E−03 8.73E−03 9.82E−03 1.08E−02 1.70E−02 

245 1.16E−02 8.59E−03 8.80E−03 1.00E−02 1.12E−02 1.29E−02 1.52E−02 1.58E−02 2.02E−02 

255 1.20E−02 8.74E−03 9.40E−03 1.03E−02 1.17E−02 1.32E−02 1.56E−02 1.63E−02 2.36E−02 

543 1.09E−02 8.83E−03 9.04E−03 9.87E−03 1.07E−02 1.17E−02 1.29E−02 1.38E−02 1.64E−02 

894 1.11E−02 8.51E−03 9.02E−03 9.79E−03 1.08E−02 1.20E−02 1.35E−02 1.47E−02 2.22E−02 

1,451 1.20E−02 9.40E−03 9.73E−03 1.06E−02 1.18E−02 1.31E−02 1.47E−02 1.58E−02 2.21E−02 

1,182 1.11E−02 8.31E−03 8.73E−03 9.64E−03 1.08E−02 1.23E−02 1.38E−02 1.49E−02 2.14E−02 

1,023 1.06E−02 7.75E−03 8.24E−03 9.05E−03 1.02E−02 1.17E−02 1.34E−02 1.43E−02 2.15E−02 

869 1.11E−02 8.84E−03 9.30E−03 9.96E−03 1.09E−02 1.19E−02 1.31E−02 1.39E−02 1.74E−02 

763 1.18E−02 9.64E−03 1.00E−02 1.07E−02 1.16E−02 1.27E−02 1.39E−02 1.45E−02 1.77E−02 

622 1.20E−02 9.76E−03 1.02E−02 1.09E−02 1.18E−02 1.30E−02 1.42E−02 1.49E−02 1.79E−02 

700 1.08E−02 8.87E−03 9.28E−03 9.85E−03 1.06E−02 1.17E−02 1.26E−02 1.32E−02 1.74E−02 

470 1.08E−02 8.84E−03 9.23E−03 9.94E−03 1.07E−02 1.17E−02 1.25E−02 1.30E−02 1.76E−02 
 

 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Exposure Factors Handbook PageSeptember 2011 6-49

Table 6-19. Descriptive Statistics for Average Ventilation Rate,a Unadjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Females by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

≥81 306 1.04E−02 8.69E−03 8.84E−03 9.36E−03 1.03E−02 1.14E−02 1.21E−02 1.26E−02 1.61E−02 

Moderate Intensity Activities (3.0< METS ≤6.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

415 1.40E−02 7.91E−03 9.00E−03 1.12E−02 1.35E−02 1.63E−02 1.94E−02 2.23E−02 4.09E−02 

245 2.10E−02 1.56E−02 1.63E−02 1.79E−02 2.01E−02 2.35E−02 2.71E−02 2.93E−02 3.45E−02 

255 2.13E−02 1.42E−02 1.56E−02 1.82E−02 2.15E−02 2.39E−02 2.76E−02 2.88E−02 3.76E−02 

543 2.00E−02 1.53E−02 1.63E−02 1.78E−02 1.98E−02 2.16E−02 2.38E−02 2.59E−02 3.29E−02 

894 2.10E−02 1.60E−02 1.68E−02 1.85E−02 2.04E−02 2.30E−02 2.61E−02 2.81E−02 4.31E−02 

1,451 2.36E−02 1.82E−02 1.95E−02 2.08E−02 2.30E−02 2.54E−02 2.84E−02 3.14E−02 4.24E−02 

1,182 2.32E−02 1.66E−02 1.76E−02 1.96E−02 2.24E−02 2.61E−02 3.03E−02 3.20E−02 5.25E−02 

1,023 2.29E−02 1.56E−02 1.67E−02 1.90E−02 2.19E−02 2.60E−02 3.00E−02 3.28E−02 5.42E−02 

869 2.27E−02 1.69E−02 1.76E−02 1.95E−02 2.20E−02 2.48E−02 2.89E−02 3.11E−02 4.73E−02 

763 2.45E−02 1.76E−02 1.89E−02 2.08E−02 2.39E−02 2.74E−02 3.08E−02 3.36E−02 5.07E−02 

622 2.52E−02 1.88E−02 1.98E−02 2.18E−02 2.43E−02 2.81E−02 3.19E−02 3.50E−02 4.62E−02 

700 2.14E−02 1.69E−02 1.77E−02 1.92E−02 2.09E−02 2.32E−02 2.57E−02 2.73E−02 3.55E−02 

470 2.11E−02 1.69E−02 1.76E−02 1.89E−02 2.07E−02 2.29E−02 2.49E−02 2.64E−02 3.44E−02 

306 2.09E−02 1.65E−02 1.75E−02 1.91E−02 2.06E−02 2.25E−02 2.46E−02 2.60E−02 2.93E−02 
 

 

 

 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-50 September 2011 

Table 6-19. Descriptive Statistics for Average Ventilation Rate,a Unadjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Females by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

High Intensity (METS >6.0) 

Birth to <1 79 2.42E−02 1.24E−02 1.33E−02 1.72E−02 2.25E−02 2.93E−02 3.56E−02 4.07E−02 7.46E−02 

1 55 3.65E−02 2.59E−02 2.62E−02 3.04E−02 3.61E−02 4.20E−02 4.73E−02 4.86E−02 7.70E−02 

2 130 3.76E−02 2.90E−02 3.05E−02 3.23E−02 3.64E−02 4.08E−02 4.81E−02 5.14E−02 7.30E−02 

3 to <6 347 3.45E−02 2.70E−02 2.82E−02 3.00E−02 3.33E−02 3.76E−02 4.32E−02 4.47E−02 5.66E−02 

6 to <11 707 3.94E−02 2.86E−02 3.01E−02 3.37E−02 3.80E−02 4.41E−02 5.05E−02 5.46E−02 8.29E−02 

11 to <16 1,170 4.66E−02 3.11E−02 3.38E−02 3.88E−02 4.53E−02 5.29E−02 6.08E−02 6.63E−02 1.02E−01 

16 to <21 887 4.41E−02 2.87E−02 3.06E−02 3.65E−02 4.27E−02 5.02E−02 5.82E−02 6.34E−02 1.09E−01 

21 to <31 796 4.57E−02 2.88E−02 3.12E−02 3.67E−02 4.31E−02 5.22E−02 6.19E−02 6.89E−02 1.08E−01 

31 to <41 687 4.44E−02 3.03E−02 3.29E−02 3.70E−02 4.22E−02 5.05E−02 5.95E−02 6.53E−02 8.95E−02 

41 to <51 515 4.70E−02 3.10E−02 3.40E−02 3.84E−02 4.56E−02 5.41E−02 6.15E−02 6.74E−02 8.87E−02 

51 to <61 424 4.74E−02 3.15E−02 3.48E−02 3.94E−02 4.57E−02 5.41E−02 6.23E−02 6.88E−02 8.44E−02 

61 to <71 465 4.00E−02 2.76E−02 3.06E−02 3.46E−02 3.87E−02 4.53E−02 5.08E−02 5.64E−02 7.13E−02 

71 to <81 304 4.06E−02 2.85E−02 3.01E−02 3.43E−02 3.96E−02 4.70E−02 5.20E−02 5.41E−02 7.53E−02 

≥81 188 4.19E−02 2.85E−02 3.09E−03 3.44E−02 4.14E−02 4.76E−02 5.56E−02 5.83E−02 7.21E−02 

a An individual’s ventilation rate for the given activity category equals the weighted average of the individual’s activity-specific ventilation rates for 

activities falling within the category, estimated using a multiple linear regression model, with weights corresponding to the number of minutes spent 

performing the activity. Numbers in these two columns represent averages, calculated across individuals in the specified age category, of these 

weighted averages. These are weighted averages, with the weights corresponding to the 4-year sampling weights assigned within NHANES 

1999−2002. 

N = Number of individuals. 

MET = Metabolic equivalent. 

Source: U.S. EPA (2009a). 
 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Exposure Factors Handbook PageSeptember 2011 6-51

Table 6-20. Descriptive Statistics for Average Ventilation Rate,a Adjusted for Body Weight, While Performing Activities Within the 

Specified Activity Category, for Females by Age Category 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 415 3.91E−04 2.80E−04 3.01E−04 3.35E−04 3.86E−04 4.34E−04 4.79E−04 5.17E−04 7.39E−04 

1 245 4.14E−04 3.15E−04 3.29E−04 3.61E−04 4.05E−04 4.64E−04 5.21E−04 5.36E−04 6.61E−04 

2 255 3.42E−04 2.58E−04 2.71E−04 2.93E−04 3.33E−04 3.91E−04 4.25E−04 4.53E−04 4.94E−04 

3 to <6 543 2.38E−04 1.45E−04 1.63E−04 1.95E−04 2.33E−04 2.75E−04 3.20E−04 3.53E−04 5.19E−04 

6 to <11 894 1.51E−04 8.90E−05 9.70E−05 1.20E−04 1.46E−04 1.76E−04 2.11E−04 2.29E−04 2.97E−04 

11 to <16 1,451 9.00E−05 5.90E−05 6.50E−05 7.50E−05 8.70E−05 1.02E−04 1.18E−04 1.30E−04 1.76E−04 

16 to <21 1,182 6.90E−05 4.40E−05 4.70E−05 5.70E−05 6.70E−05 8.00E−05 9.30E−05 1.02E−04 1.52E−04 

21 to <31 1,023 5.50E−05 3.50E−05 3.80E−05 4.50E−05 5.40E−05 6.50E−05 7.40E−05 8.20E−05 9.80E−05 

31 to <41 869 5.60E−05 3.40E−05 3.70E−05 4.50E−05 5.40E−05 6.50E−05 7.60E−05 8.20E−05 1.15E−04 

41 to <51 763 6.00E−05 3.90E−05 4.10E−05 4.80E−05 5.70E−05 7.00E−05 8.40E−05 9.00E−05 1.14E−04 

51 to <61 622 6.10E−05 3.90E−05 4.20E−05 5.00E−05 5.90E−05 7.10E−05 8.30E−05 8.80E−05 1.35E−04 

61 to <71 700 6.10E−05 4.30E−05 4.60E−05 5.20E−05 5.90E−05 6.70E−05 7.60E−05 8.10E−05 1.01E−04 

71 to <81 470 6.60E−05 4.70E−05 5.10E−05 5.60E−05 6.40E−05 7.40E−05 8.40E−05 9.00E−05 1.25E−04 

≥81 306 7.20E−05 5.10E−05 5.60E−05 6.30E−05 7.00E−05 7.90E−05 9.10E−05 9.60E−05 1.15E−04 

Sedentary and Passive Activities (METS ≤1.5—Includes Sleep or Nap) 

Birth to <1 415 4.02E−04 2.97E−04 3.16E−04 3.52E−04 3.96E−04 4.46E−04 4.82E−04 5.19E−04 7.19E−04 

1 245 4.25E−04 3.35E−04 3.48E−04 3.76E−04 4.18E−04 4.69E−04 5.12E−04 5.43E−04 6.42E−04 

2 255 3.55E−04 2.85E−04 2.96E−04 3.20E−04 3.48E−04 3.91E−04 4.20E−04 4.42E−04 4.85E−04 

3 to <6 543 2.51E−04 1.64E−04 1.79E−04 2.11E−04 2.48E−04 2.84E−04 3.28E−04 3.58E−04 4.89E−04 

6 to <11 894 1.60E−04 9.90E−05 1.10E−04 1.31E−04 1.57E−04 1.85E−04 2.12E−04 2.34E−04 2.93E−04 

11 to <16 1,451 9.70E−05 7.10E−05 7.50E−05 8.30E−05 9.50E−05 1.09E−04 1.23E−04 1.33E−04 1.74E−04 
 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-52 September 2011 

Table 6-20. Descriptive Statistics for Average Ventilation Rate,a Adjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Females by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

1,182 7.50E−05 5.30E−05 5.70E−05 6.30E−05 7.40E−05 8.50E−05 9.60E−05 1.04E−04 1.41E−04 

1,023 6.00E−05 4.30E−05 4.50E−05 5.10E−05 5.90E−05 6.70E−05 7.50E−05 8.00E−05 9.90E−05 

869 6.00E−05 4.00E−05 4.20E−05 5.10E−05 5.90E−05 6.90E−05 7.80E−05 8.30E−05 1.05E−04 

763 6.50E−05 4.40E−05 4.80E−05 5.50E−05 6.30E−05 7.30E−05 8.30E−05 9.10E−05 1.14E−04 

622 6.70E−05 4.60E−05 5.10E−05 5.70E−05 6.50E−05 7.60E−05 8.30E−05 9.00E−05 1.18E−04 

700 6.60E−05 5.20E−05 5.40E−05 5.90E−05 6.60E−05 7.20E−05 7.80E−05 8.40E−05 1.04E−04 

470 7.20E−05 5.50E−05 6.00E−05 6.50E−05 7.10E−05 7.80E−05 8.80E−05 9.20E−05 1.48E−04 

306 7.80E−05 6.30E−05 6.50E−05 7.00E−05 7.70E−05 8.60E−05 9.30E−05 9.60E−05 1.12E−04 

Light Intensity Activities (1.5< METS ≤3.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

415 9.78E−04 7.91E−04 8.17E−04 8.80E−04 9.62E−04 1.05E−03 1.18E−03 1.23E−03 1.65E−03 

245 1.05E−03 8.45E−04 8.68E−04 9.49E−04 1.04E−03 1.14E−03 1.25E−03 1.27E−03 1.64E−03 

255 8.97E−04 7.30E−04 7.63E−04 8.19E−04 8.93E−04 9.64E−04 1.04E−03 1.10E−03 1.26E−03 

543 6.19E−04 4.48E−04 4.84E−04 5.37E−04 5.99E−04 6.98E−04 7.83E−04 8.28E−04 1.02E−03 

894 3.82E−04 2.52E−04 2.70E−04 3.15E−04 3.76E−04 4.42E−04 5.03E−04 5.39E−04 7.10E−04 

1,451 2.25E−04 1.63E−04 1.74E−04 1.96E−04 2.17E−04 2.49E−04 2.84E−04 3.05E−04 3.96E−04 

1,182 1.74E−04 1.29E−04 1.38E−04 1.54E−04 1.73E−04 1.93E−04 2.13E−04 2.24E−04 2.86E−04 

1,023 1.49E−04 1.16E−04 1.23E−04 1.34E−04 1.49E−04 1.63E−04 1.78E−04 1.90E−04 2.27E−04 

869 1.54E−04 1.07E−04 1.15E−04 1.33E−04 1.54E−04 1.76E−04 1.92E−04 2.02E−04 2.67E−04 

763 1.61E−04 1.14E−04 1.23E−04 1.38E−04 1.58E−04 1.82E−04 2.03E−04 2.16E−04 2.83E−04 

622 1.61E−04 1.20E−04 1.27E−04 1.41E−04 1.58E−04 1.80E−04 1.99E−04 2.10E−04 2.65E−04 

700 1.47E−04 1.17E−04 1.22E−04 1.32E−04 1.45E−04 1.61E−04 1.73E−04 1.82E−04 2.44E−04 

470 1.58E−04 1.24E−04 1.30E−04 1.43E−04 1.56E−04 1.69E−04 1.88E−04 2.02E−04 2.77E−04 

306 1.67E−04 1.31E−04 1.38E−04 1.50E−04 1.64E−04 1.82E−04 1.97E−04 2.08E−04 2.34E−04 
 

 

 

Chapter 6—Exposure Factors Handbook

Inhalation Rates

Exposure Factors Handbook PageSeptember 2011 6-53

Table 6-20. Descriptive Statistics for Average Ventilation Rate,a Adjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Females by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Moderate Intensity Activities (3.0< METS ≤6.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

415 1.87E−03 1.47E−03 1.52E−03 1.67E−03 1.85E−03 2.01E−03 2.25E−03 2.40E−03 2.83E−03 

245 1.90E−03 1.52E−03 1.62E−03 1.73E−03 1.87E−03 2.02E−03 2.24E−03 2.37E−03 3.24E−03 

255 1.60E−03 1.27E−03 1.31E−03 1.44E−03 1.58E−03 1.75E−03 1.92E−03 2.02E−03 2.59E−03 

543 1.14E−03 7.92E−04 8.53E−04 9.64E−04 1.11E−03 1.31E−03 1.45E−03 1.56E−03 1.93E−03 

894 7.23E−04 4.62E−04 5.12E−04 5.98E−04 7.15E−04 8.38E−04 9.42E−04 1.01E−03 1.37E−03 

1,451 4.41E−04 3.17E−04 3.38E−04 3.80E−04 4.31E−04 4.92E−04 5.51E−04 6.11E−04 9.86E−04 

1,182 3.65E−04 2.67E−04 2.82E−04 3.10E−04 3.51E−04 4.07E−04 4.63E−04 4.94E−04 6.50E−04 

1,023 3.25E−04 2.35E−04 2.45E−04 2.81E−04 3.16E−04 3.60E−04 4.16E−04 4.52E−04 6.57E−04 

869 3.16E−04 2.13E−04 2.31E−04 2.68E−04 3.04E−04 3.50E−04 4.10E−04 4.60E−04 7.08E−04 

763 3.33E−04 2.21E−04 2.36E−04 2.76E−04 3.25E−04 3.76E−04 4.41E−04 4.88E−04 6.20E−04 

622 3.39E−04 2.35E−04 2.54E−04 2.83E−04 3.26E−04 3.83E−04 4.38E−04 4.86E−04 3.69E−04 

700 2.92E−04 2.24E−04 2.38E−04 2.59E−04 2.85E−04 3.20E−04 3.51E−04 3.71E−04 5.11E−04 

470 3.08E−04 2.40E−04 2.50E−04 2.70E−04 2.99E−04 3.40E−04 3.75E−04 4.07E−04 6.77E−04 

306 3.35E−04 2.47E−04 2.66E−04 2.98E−04 3.33E−04 3.72E−04 4.02E−04 4.20E−04 5.20E−04 
 

 

 

 

 

 

Chapter 6—

Exposure Factors Handbook

Inhalation Rates

Page Exposure Factors Handbook 6-54 September 2011 

Table 6-20. Descriptive Statistics for Average Ventilation Rate,a Adjusted for Body Weight, While Performing Activities Within the Specified 

Activity Category, for Females by Age Category (continued) 

Age Group 

(years) N 

Average Ventilation Rate (m3/minute-kg) 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

High Intensity (METS >6.0) 

Birth to <1 79 3.26E−03 2.53E−03 2.62E−03 2.89E−03 3.23E−03 3.63E−03 3.96E−03 4.08E−03 5.02E−03 

1 55 3.38E−03 2.57E−03 2.75E−03 2.97E−03 3.24E−03 3.71E−03 4.16E−03 4.87E−03 4.88E−03 

2 130 2.80E−03 2.20E−03 2.31E−03 2.48E−03 2.81E−03 3.13E−03 3.36E−03 3.48E−03 3.88E−03 

3 to <6 347 1.98E−03 1.36E−03 1.51E−03 1.69E−03 1.90E−03 2.19E−03 2.50E−03 2.99E−03 3.24E−03 

6 to <11 707 1.33E−03 8.85E−04 9.67E−04 1.12E−03 1.33E−03 1.52E−03 1.72E−03 1.81E−03 2.22E−03 

11 to <16 1,170 8.79E−04 5.89E−04 6.25E−04 7.12E−04 8.53E−04 1.01E−03 1.18E−03 1.31E−03 2.05E−03 

16 to <21 887 6.96E−04 4.52E−04 4.96E−04 5.67E−04 6.86E−04 7.93E−04 9.16E−04 1.00E−03 1.50E−03 

21 to <31 796 6.50E−04 4.17E−04 4.62E−04 5.46E−04 6.27E−04 7.30E−04 8.84E−04 9.39E−04 1.30E−03 

31 to <41 687 6.13E−04 3.84E−04 4.20E−04 4.96E−04 5.90E−04 7.08E−04 8.35E−04 9.05E−04 1.55E−03 

41 to <51 515 6.35E−04 3.79E−04 4.44E−04 5.17E−04 6.41E−04 7.65E−04 8.79E−04 9.50E−04 1.61E−03 

51 to <61 424 6.34E−04 3.93E−04 4.31E−04 5.07E−04 6.12E−04 7.55E−04 8.51E−04 9.28E−04 1.37E−03 

61 to <71 465 5.44E−04 3.64E−04 4.04E−04 4.49E−04 5.29E−04 6.10E−04 7.18E−04 8.03E−04 1.11E−03 

71 to <81 304 5.94E−04 3.95E−04 4.45E−04 4.98E−04 5.80E−04 6.75E−04 7.76E−04 8.29E−04 1.26E−03 

≥81 188 6.66E−04 4.54E−04 4.80E−04 5.43E−04 6.26E−04 7.68E−04 9.32E−04 9.72E−04 1.22E−03 

a An individual’s ventilation rate for the given activity category equals the weighted average of the individual’s activity-specific ventilation rates for 

activities falling within the category, estimated using a multiple linear regression model, with weights corresponding to the number of minutes spent 

performing the activity. Numbers in these two columns represent averages, calculated across individuals in the specified age category, of these 

weighted averages. These are weighted averages, with the weights corresponding to the 4-year sampling weights assigned within NHANES 

1999−2002. 

N = Number of individuals. 

MET = Metabolic equivalent. 

Source: U.S. EPA (2009a). 
 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing 

Activities Within the Specified Activity Category, by Age for Malesa 

Age Group 

(years) N 

Duration (hours/day) Spent at Activity 

Mean 

Percentiles 

5th 10th 25th 50th 75th 90th 95th Maximum 

Sleep or nap (Activity ID = 14500) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 13.51 12.63 12.78 13.19 13.53 13.88 14.24 14.46 

308 12.61 11.89 12.15 12.34 12.61 12.89 13.13 13.29 

261 12.06 11.19 11.45 11.80 12.07 12.39 12.65 12.75 

540 11.18 10.57 10.70 10.94 11.18 11.45 11.63 11.82 

940 10.18 9.65 9.75 9.93 10.19 10.39 10.59 10.72 

1,337 9.38 8.84 8.94 9.15 9.38 9.61 9.83 9.95 

1,241 8.69 7.91 8.08 8.36 8.67 9.03 9.34 9.50 

701 8.36 7.54 7.70 8.02 8.36 8.67 9.03 9.23 

728 8.06 7.36 7.50 7.77 8.06 8.36 8.59 8.76 

753 7.89 7.15 7.30 7.58 7.88 8.17 8.48 8.68 

627 7.96 7.29 7.51 7.69 7.96 8.23 8.48 8.66 

678 8.31 7.65 7.78 8.01 8.30 8.6 8.83 9.01 

496 8.51 7.80 8.02 8.27 8.53 8.74 8.99 9.10 

255 9.24 8.48 8.64 8.97 9.25 9.54 9.74 9.96 

15.03 

13.79 

13.40 

12.39 

11.24 

10.33 

10.44 

9.77 

9.82 

9.38 

9.04 

9.66 

9.89 

10.69 

Sedentary and Passive Activities (METS ≤1.5—Includes Sleep or Nap) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 14.95 13.82 14.03 14.49 14.88 15.44 15.90 16.12 

308 14.27 13.22 13.33 13.76 14.25 14.74 15.08 15.38 

261 14.62 13.52 13.67 14.11 14.54 15.11 15.60 15.77 

540 14.12 13.01 13.18 13.54 14.03 14.53 15.26 15.62 

940 13.51 12.19 12.45 12.86 13.30 13.85 14.82 15.94 

1,337 13.85 12.39 12.65 13.06 13.61 14.30 15.41 16.76 

1,241 13.21 11.39 11.72 12.32 13.08 13.97 14.83 15.44 

701 12.41 10.69 11.06 11.74 12.39 13.09 13.75 14.16 

728 12.31 10.73 10.98 11.61 12.24 12.98 13.63 14.05 

753 12.32 10.56 11.00 11.67 12.30 12.95 13.67 13.98 

627 13.06 11.47 11.86 12.36 13.03 13.72 14.38 14.76 

678 14.49 12.96 13.24 13.76 14.48 15.16 15.72 16.24 

496 15.90 14.22 14.67 15.25 15.94 16.65 17.11 17.46 

255 16.58 15.13 15.45 15.92 16.64 17.21 17.7 18.06 

17.48 

16.45 

17.28 

17.29 

19.21 

18.79 

18.70 

15.35 

15.58 

15.48 

15.95 

17.50 

18.47 

18.76 

Exposure Factors Handbook Page
 

September 2011 6-55 
 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the 

Specified Activity Category, by Age for Malesa (continued) 

Age Group 

(years) N 

Duration (hours/day) Spent at Activity 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Light Intensity Activities (1.5< METS ≤3.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 5.30 2.97 3.25 3.71 4.52 7.29 8.08 8.50 9.91 

308 5.52 2.68 2.89 3.37 4.31 8.23 9.04 9.73 10.90 

261 5.48 3.06 3.26 3.85 4.58 7.58 8.83 9.04 9.92 

540 6.60 3.86 4.25 5.16 6.20 8.26 9.31 9.70 10.74 

940 7.62 5.07 5.57 6.63 7.63 8.72 9.78 10.12 11.59 

1,337 7.50 4.48 5.59 6.75 7.67 8.51 9.19 9.63 10.91 

1,241 7.13 4.37 4.97 6.00 7.02 8.29 9.43 10.03 11.50 

701 6.09 3.15 3.50 4.20 5.08 8.49 9.96 10.47 12.25 

728 5.72 2.80 3.12 3.70 4.64 8.34 9.87 10.49 12.10 

753 6.07 2.97 3.41 3.92 4.82 8.56 10.19 10.79 12.68 

627 5.64 3.21 3.44 4.03 4.79 7.59 8.94 9.75 12.09 

678 5.49 3.50 3.82 4.58 5.29 6.41 7.40 7.95 10.23 

496 4.96 3.45 3.75 4.29 4.81 5.59 6.26 6.59 9.90 

255 4.86 3.54 3.71 4.17 4.74 5.39 6.33 6.59 7.56 

Moderate Intensity Activities (3.0< METS ≤6.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

419 3.67 0.63 0.97 1.74 4.20 5.20 5.80 6.21 7.52 

308 4.04 0.45 0.59 1.14 5.29 6.06 6.61 6.94 7.68 

261 3.83 0.59 0.76 1.23 4.74 5.37 5.82 6.15 7.40 

540 3.15 0.55 0.75 1.30 3.80 4.52 5.11 5.32 6.30 

940 2.66 0.65 0.92 1.65 2.68 3.57 4.36 4.79 5.95 

1,337 2.35 0.88 1.09 1.66 2.30 3.02 3.62 3.89 5.90 

1,241 3.35 1.13 1.42 2.19 3.45 4.37 5.24 5.59 6.83 

701 5.24 1.15 1.58 2.52 6.01 7.15 7.95 8.39 9.94 

728 5.69 1.26 1.65 2.84 6.67 7.75 8.45 8.90 9.87 

753 5.40 1.21 1.55 2.39 6.46 7.57 8.40 8.85 10.52 

627 5.00 1.29 1.63 2.72 5.68 6.75 7.60 8.01 9.94 

678 3.73 1.62 1.97 2.81 3.70 4.67 5.45 6.01 7.45 

496 2.87 1.56 1.83 2.28 2.86 3.45 3.95 4.31 5.44 

255 2.35 1.32 1.45 1.79 2.29 2.85 3.28 3.61 4.37 

Page Exposure Factors Handbook 

6-56 September 2011 
 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-21. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the 

Specified Activity Category, by Age for Malesa (continued) 

Age Group 

(years) N 

Duration (hours/day) Spent at Activity 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

High Intensity (METS >6.0) 

Birth to <1 183 0.20 0.00 0.00 0.01 0.14 0.28 0.50 0.59 0.96 

1 164 0.31 0.01 0.01 0.03 0.22 0.56 0.78 0.93 1.52 

2 162 0.10 0.00 0.01 0.03 0.05 0.14 0.25 0.33 0.48 

3 to <6 263 0.27 0.02 0.03 0.04 0.13 0.33 0.75 1.16 1.48 

6 to <11 637 0.32 0.01 0.01 0.03 0.13 0.38 1.10 1.50 3.20 

11 to <16 1,111 0.38 0.03 0.04 0.10 0.21 0.47 1.03 1.34 2.35 

16 to <21 968 0.40 0.03 0.04 0.14 0.27 0.53 0.99 1.29 2.59 

21 to <31 546 0.33 0.02 0.05 0.11 0.27 0.45 0.69 0.85 1.95 

31 to <41 567 0.38 0.03 0.07 0.14 0.28 0.51 0.83 1.03 1.77 

41 to <51 487 0.34 0.03 0.05 0.09 0.23 0.50 0.78 1.00 2.40 

51 to <61 452 0.41 0.03 0.05 0.13 0.34 0.59 0.87 1.13 1.95 

61 to <71 490 0.37 0.03 0.05 0.13 0.28 0.49 0.80 1.08 2.21 

71 to <81 343 0.39 0.01 0.03 0.10 0.29 0.57 0.90 1.11 2.06 

≥81 168 0.32 0.02 0.03 0.08 0.25 0.47 0.71 0.88 1.76 

a Individual measures are weighted by their 4-year sampling weights as assigned within NHANES 

1999−2000 when calculating the statistics in this table. Ventilation rate was estimated using a multiple 

linear regression model. 

N = Number of individuals. 

MET = Metabolic equivalent. 

Source: U.S. EPA (2009a). 

Exposure Factors Handbook Page
 

September 2011 6-57 
 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing 

Activities Within the Specified Activity Category, by Age for Femalesa 

Age Group 

(years) N 

Duration (hours/day) Spent at Activity 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 415 12.99 12.00 12.16 12.53 12.96 13.44 13.82 14.07 14.82 

1 245 12.58 11.59 11.88 12.29 12.63 12.96 13.16 13.31 14.55 

2 255 12.09 11.45 11.68 11.86 12.08 12.34 12.57 12.66 13.48 

3 to <6 543 11.13 10.45 10.70 10.92 11.12 11.38 11.58 11.75 12.23 

6 to <11 894 10.26 9.55 9.73 10.01 10.27 10.54 10.74 10.91 11.43 

11 to <16 1,451 9.57 8.82 8.97 9.27 9.55 9.87 10.17 10.31 11.52 

16 to <21 1,182 9.08 8.26 8.44 8.74 9.08 9.39 9.79 10.02 11.11 

21 to <31 1,023 8.60 7.89 7.99 8.26 8.59 8.90 9.20 9.38 10.35 

31 to <41 869 8.31 7.54 7.70 7.98 8.28 8.59 8.92 9.17 10.22 

41 to <51 763 8.32 7.58 7.75 7.99 8.31 8.63 8.93 9.13 10.02 

51 to <61 622 8.12 7.36 7.53 7.81 8.11 8.43 8.73 8.85 9.29 

61 to <71 700 8.40 7.67 7.88 8.15 8.40 8.68 8.93 9.09 9.80 

71 to <81 470 8.58 7.85 8.01 8.26 8.55 8.89 9.19 9.46 10.34 

≥81 306 9.11 8.35 8.53 8.84 9.10 9.34 9.73 10.04 10.55 

Sedentary and Passive Activities (METS ≤1.5—Includes Sleep or Nap) 

Birth to <1 415 14.07 12.86 13.05 13.53 14.08 14.54 15.08 15.49 16.14 

1 245 14.32 13.02 13.25 13.73 14.31 14.88 15.36 15.80 16.40 

2 255 14.86 13.81 13.95 14.44 14.81 15.32 15.78 16.03 16.91 

3 to <6 543 14.27 12.88 13.15 13.56 14.23 14.82 15.43 15.85 17.96 

6 to <11 894 13.97 12.49 12.74 13.22 13.82 14.50 15.34 16.36 18.68 

11 to <16 1,451 14.19 12.38 12.76 13.34 14.05 14.82 15.87 16.81 19.27 

16 to <21 1,182 13.58 11.80 12.17 12.79 13.52 14.29 15.08 15.67 16.96 

21 to <31 1,023 12.59 10.97 11.29 11.88 12.60 13.21 13.75 14.19 16.24 

31 to <41 869 12.29 10.91 11.14 11.61 12.24 12.91 13.50 13.90 15.18 

41 to <51 763 12.22 10.78 11.08 11.56 12.18 12.82 13.40 13.79 15.17 

51 to <61 622 12.66 11.08 11.40 12.08 12.64 13.30 13.89 14.12 15.80 

61 to <71 700 14.25 12.89 13.16 13.68 14.22 14.86 15.38 15.69 17.14 

71 to <81 470 15.38 13.66 14.20 14.76 15.41 16.05 16.62 16.94 17.90 

≥81 306 16.48 14.87 15.09 15.80 16.59 17.15 17.71 18.07 19.13 

Page Exposure Factors Handbook 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the 

Specified Activity Category, by Age for Femalesa (continued) 

Age Group 

(years) N 

Duration (hours/day) Spent at Activity 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

Light Intensity Activities (1.5< METS ≤3.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

415 6.00 3.49 3.70 4.26 5.01 8.43 9.31 9.77 10.53 

245 5.61 2.83 2.94 3.46 4.39 8.28 9.03 9.39 10.57 

255 5.78 3.20 3.54 4.29 5.33 7.48 8.46 8.74 9.93 

543 6.25 3.78 4.10 4.79 5.84 7.86 8.84 9.38 10.32 

894 7.27 4.63 5.46 6.33 7.17 8.34 9.42 9.79 11.06 

1,451 7.55 4.89 5.62 6.75 7.67 8.55 9.27 9.57 10.85 

1,182 6.98 4.60 5.08 5.91 6.85 7.96 9.16 9.57 12.29 

1,023 6.42 3.66 4.09 4.84 5.82 8.18 9.56 10.14 12.11 

869 6.51 4.06 4.33 5.06 5.98 8.14 9.46 9.93 13.12 

763 6.56 3.99 4.30 4.97 5.90 8.40 9.75 10.18 11.83 

622 6.52 4.09 4.42 5.19 6.05 7.95 9.12 9.43 11.58 

700 6.23 4.40 4.74 5.47 6.23 6.96 7.67 8.17 11.13 

470 5.96 4.22 4.51 5.24 5.92 6.63 7.46 7.91 9.43 

306 5.3 3.67 3.96 4.63 5.16 6.00 6.70 7.01 8.78 

Moderate Intensity Activities (3.0< METS ≤6.0) 

Birth to <1 

1 

2 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <31 

31 to <41 

41 to <51 

51 to <61 

61 to <71 

71 to <81 

≥81 

415 3.91 0.53 0.74 1.10 4.87 5.77 6.27 6.54 7.68 

245 4.02 0.52 0.73 1.08 5.14 6.10 7.00 7.37 8.07 

255 3.27 0.50 0.78 1.22 4.01 4.88 5.35 5.57 6.93 

543 3.35 0.70 0.89 1.61 3.88 4.71 5.29 5.65 7.58 

894 2.57 0.65 0.95 1.82 2.66 3.41 3.95 4.32 6.10 

1,451 2.01 0.89 1.08 1.45 1.96 2.51 3.03 3.28 4.96 

1,182 3.26 1.27 1.48 2.21 3.39 4.24 4.74 5.07 6.68 

1,023 4.80 1.62 1.94 2.78 5.37 6.42 7.19 7.52 9.21 

869 5.00 1.71 2.06 3.09 5.41 6.60 7.31 7.58 9.59 

763 5.05 1.75 2.00 2.97 5.48 6.66 7.50 7.97 10.16 

622 4.58 1.71 2.13 3.10 4.79 5.98 6.89 7.14 8.97 

700 3.31 1.65 1.97 2.56 3.34 4.01 4.61 5.01 6.90 

470 2.48 1.19 1.36 1.82 2.48 2.99 3.64 4.01 5.63 

306 2.06 1.01 1.25 1.55 1.99 2.51 3.07 3.44 4.68 

Exposure Factors Handbook Page
 

September 2011 6-59 
 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-22. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the 

Specified Activity Category, by Age for Femalesa (continued) 

Age Group 

(years) N 

Duration (hours/day) Spent at Activity 

Mean 

Percentiles 

5 Maximum th 10th 25th 50th 75th 90th 95th 

High Intensity (METS >6.0) 

Birth to <1 79 0.17 0.03 0.05 0.09 0.14 0.21 0.33 0.40 0.58 

1 55 0.22 0.03 0.05 0.09 0.18 0.35 0.40 0.43 0.48 

2 130 0.15 0.00 0.01 0.03 0.08 0.16 0.48 0.65 1.01 

3 to <6 347 0.19 0.01 0.02 0.05 0.10 0.22 0.46 0.73 1.43 

6 to <11 707 0.24 0.02 0.03 0.06 0.12 0.26 0.67 0.98 1.71 

11 to <16 1,170 0.30 0.03 0.04 0.08 0.19 0.40 0.66 0.96 3.16 

16 to <21 887 0.24 0.01 0.03 0.08 0.18 0.34 0.51 0.60 1.61 

21 to <31 796 0.26 0.03 0.05 0.10 0.19 0.36 0.56 0.67 1.40 

31 to <41 687 0.25 0.03 0.05 0.09 0.19 0.33 0.52 0.72 1.40 

41 to <51 515 0.26 0.03 0.04 0.09 0.20 0.36 0.55 0.68 1.49 

51 to <61 424 0.34 0.03 0.04 0.12 0.28 0.50 0.74 0.85 1.58 

61 to <71 465 0.32 0.03 0.04 0.10 0.23 0.46 0.68 0.89 1.77 

71 to <81 304 0.29 0.03 0.05 0.10 0.25 0.43 0.60 0.71 1.24 

≥81 188 0.26 0.02 0.03 0.09 0.21 0.38 0.59 0.71 1.23 

a Individual measures are weighted by their 4-year sampling weights as assigned within NHANES 

1999−2000 when calculating the statistics in this table. Ventilation rate was estimated using a multiple 

linear regression model. 

N = Number of individuals. 

MET = Metabolic equivalent. 

Source: U.S. EPA (2009a). 

Page Exposure Factors Handbook 

6-60 September 2011 
Table 6-23. Mean Inhalation Rate Values (m3

/day) From Key Studies for Males and Females Combined 

Age Groupa 

U.S. EPA 

(2009a)

b 

Brochu et al. 

(2006b)

b 

Arcus-Arth and 

Blaisdell (2007)

b Stifelman (2007)c 

Combined Key 

Studies

d 

Nc Mean N Mean N Mean N Mean N Mean 

Birth to <1 

month 

- - - - 182 3.63 - - 182 3.63 

1 to <3 months - - 85 3.31 182 3.63 - - 267 3.47 

3 to <6 months - - 85 3.31 294 4.92 - - 379 4.11 

6 to <12 months - - 103 4.06 544 6.78 - - 647 5.42 

Birth to <1 year 834 8.64 188 3.72 1,020 5.70 - 3.4 2,042 5.36 

1 to <2 years 553 13.41 101 4.90 934 8.77 - 4.9 1,588 7.99 

2 to <3 years 516 12.99 61 7.28 989 9.76 - 5.7 1,566 8.93 

3 to <6 years 1,083 12.40 61 7.28 4,107 11.22 - 9.3 5,251 10.05 

6 to <11 years 1,834 12.93 199 9.98 1,553 13.42 - 11.5 3,586 11.96 

11 to <16 years 2,788 14.34 117 14.29 975 16.98 - 15.0 3,880 15.17 

16 to <21 years 2,423 15.44 117 14.29 495 18.29 - 17.0 3,035 16.25 

21 to <31 years 1,724 16.30 219 14.59 - - - 16.3 1,943 15.74 

31 to <41 years 1,597 17.40 100 14.99 - - - 15.6 1,697 16.00 

41 to <51 years 1,516 18.55 91 13.74 - - - 15.6 1,607 15.96 

51 to <61 years 1,249 18.56 91 13.74 - - - 14.7 1,340 15.66 

61 to <71 years 1,378 15.43 186 12.57 - - - 14.7 1,564 14.23 

71 to <81 years 966 14.25 95 11.46 - - - - 1,061 12.86 

≥81 years 561 12.97 95 11.46 - - - - 656 12.21 

a When age groupings in the original reference did not match the U.S. EPA groupings used for this 

handbook, means from all age groupings in the original reference that overlapped U.S. EPA’s age 

groupings by more than 1 year were averaged, weighted by the number of observations contributed from 

each age group. See Table 6-25 for concordance with U.S. EPA age groupings. b Weighted (where possible) average of reported study means. c The total number of subjects for Stifelman (2007) was 3,007. d Unweighted average of means from key studies. 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Exposure Factors Handbook Page
 

September 2011 6-61 
Table 6-24. 95th Percentile Inhalation Rate Values (m3

/day) From Key Studies for 

Males and Females Combined 

Age Groupa 

U.S. EPA 

(2009a)

b 

Brochu et al. 

(2006b)

b 

Arcus-Arth and 

Blaisdell (2007)

b Stifelman (2007)c 

Combined Key 

Studies

d 

Na 95th N 95th N 95th N 95th N 95th 

Birth to <1 month -

b - - - 182 7.10 - - 182 7.10 

1 to <3 months - - 85 4.44 182 7.10 - - 267 5.77 

3 to <6 months - - 85 4.44 294 7.72 - - 379 6.08 

6 to <12 months - - 103 5.28 544 10.81 - - 647 8.04 

Birth to <1 year 834 12.67 188 4.90 1,020 9.95 - - 2,042 9.17 

1 to <2 years 553 18.22 101 6.43 934 13.79 - - 1,588 12.81 

2 to <3 years 516 17.04 61 9.27 989 14.81 - - 1,566 13.71 

3 to <6 years 1,083 15.17 61 9.27 4,107 17.09 - - 5,251 13.84 

6 to <11 years 1,834 17.05 199 12.85 1,553 19.86 - - 3,586 16.59 

11 to <16 years 2,788 19.23 117 19.02 975 27.53 - - 3,880 21.93 

16 to <21 years 2,423 20.89 117 19.02 495 33.99 - - 3,035 24.63 

21 to <31 years 1,724 23.57 219 19.00 - - - - 1,943 21.29 

31 to <41 years 1,597 24.30 100 18.39 - - - - 1,697 21.35 

41 to <51 years 1,516 24.83 91 17.50 - - - - 1,607 21.16 

51 to <61 years 1,249 25.17 91 17.50 - - - - 1,340 21.33 

61 to <71 years 1,378 19.76 186 16.37 - - - - 1,564 18.07 

71 to <81 years 966 17.88 95 15.30 - - - - 1,061 16.59 

≥81 years 561 16.10 95 15.30 - - - - 656 15.70 

a When age groupings in the original reference did not match the U.S. EPA groupings used for this 

handbook, 95th percentiles from all age groupings in the original reference that overlapped U.S. EPA’s 

age groupings by more than 1 year were averaged, weighted by the number of observations contributed 

from each age group. See Table 6-25 for concordance with U.S. EPA age groupings. b Weighted (where possible) average of reported study 95th percentiles. c The total number of subjects for Stifelman (2007) was 3,007. d Unweighted average of 95th percentiles from key studies. 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Page Exposure Factors Handbook 

6-62 September 2011 
 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-25. Concordance of Age Groupings Among Key Studies 

Age Groupa U.S. EPA (2009a) 

Brochu et al. 

(2006b) 

Arcus-Arth and Blaisdell 

(2007) Stifelman (2007) 

Birth to <1 month — — 0 to 2 months — 

1 to <3 months — 0.22 to <0.5 year 0 to 2 months — 

3 to <6 months — 0.22 to <0.5 year 3 to 5 months — 

6 to <12 months — 0.5 to <1 year 6 to 8 months — 

— — 9 to 11 months — 

Birth to <1 year Birth to <1 year 0.22 to <0.5 year 0 to 11 months <1 year 

— 0.5 to <1 year — — 

1 to <2 years 1 to <2 years 1 to <2 years 1 year 1 year 

2 to <3 years 2 to <3 years 2 to <5 years 2 years 2 years 

3 to <6 years 3 to <6 years 2 to <5 years 3 years 3 years 

— — 4 years 4 years 

— — 5 years 5 years 

6 to <11 years 6 to <11 years 7 to <11 years 6 years 6 years 

— — 7 years 7 years 

— — 8 years 8 years 

— — 9 years 9 years 

— — 10 years 10 years 

11 to <16 years 11 to <16 years 11 to <23 years 11 years 11 years 

— — 12 years 12 years 

— — 13 years 13 years 

— — 14 years 14 years 

— — 15 years 15 years 

16 to <21 years 16 to <21 years 11 to <23 years 16 years 16 years 

— — 17 years 17 years 

— — 18 years 18 years 

— — — 19 to 30 years 

21 to <31 years 21 to <31 years 11 to <23 years — 19 to 30 years 

— 23 to <30 years — — 

31 to <41 years 31 to <41 years 30 to <40 years — 31 to 50 years 

41 to <51 years 41 to <51 years 40 to <65 years — 31 to 50 years 

51 to <61 years 51 to <61 years 40 to <65 years — 51 to 70 years 

61 to <71 years 61 to <71 years 40 to <65 years — 51 to 70 years 

— 65 to ≤96 years — — 

71 to <81 years 71 to <81 years 65 to ≤96 years — — 

≥81 years ≥81 years 65 to ≤96 years — — 

a When age groups in the original reference did not match the U.S. EPA groupings used for this handbook, statistics 

were averaged from all age groupings in the original reference that overlapped U.S. EPA’s age groupings by more 

than 1 year, weighted by the number of observations contributed from each age group. For example, Brochu et al. 

(2006b) contributes its 2 to <5-year age group data to both U.S. EPA’s 2 to <3-year and 3 to <6-year age groups. 

Exposure Factors Handbook Page
 

September 2011 6-63 
 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-26. Time Weighted Average of Daily Inhalation Rates (DIRs) Estimated From 

Daily Activitiesa 

Subject 

Inhalation Rate (m3/hour) DIRb 

(m3 Resting Light Activity /day) 

Adult Man 0.45 1.2 22.8 

Adult Woman 0.36 1.14 21.1 

Child (10 years) 0.29 0.78 14.8 

Infant (1 year) 0.09 0.25 3.76 

Newborn 0.03 0.09 0.78 

a Assumptions made were based on 8 hr resting and 16 hr light activity for adults and children (10 years); 

14 hr resting and 10 hr light activity for infants (1 year); 23 hr resting and 1 hr light activity for 

newborns. b 

1 

1 K 

i i 

i 

DIR IR t 

T =

= ∑

DIR = Daily Inhalation Rate, 

IRi = Corresponding inhalation rate at ith activity, 

ti = Hours spent during the ith activity, 

k = Number of activity periods, and 

T = Total time of the exposure period (i.e., a day). 

Source: ICRP (1981). 

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6-64 September 2011 
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Exposure Factors Handbook Chapter Exposur

6—

e F

In

actors Handbook 

halation Rates 

Table 6-27. Selected Inhalation Rate Values During Different Activity Levels Obtained From Various Literature Sources 

Maximal Work 

Resting Light Activity Heavy Work During Exercise 

Subject BW (kg) f VT V* f VT V* f VT V* f VT V* 

Adolescent 

Male, 14−16 years 16 330 5.2 53 2,520 113 

Male, 14−15 years 59.4 

Female, 14−16 years 15 300 4.5 

Female, 14−15 years; 164.9 cm L 56 52 1,870 88 

Children 

10 year; 140 cm L 16 300 4.8 24 600 14 

Males, 10−11 years 36.5 58 1,330 71 

Males, 10−11 years; 140.6 cm L 32.5 61 1,050 61 

Females, 4−6 years 20.8 70 600 40 

Females, 4−6 years; 111.6 cm L 18.4 66 520 34 

Infant, 1 year 30 48 1.4a 

Newborn 2.5 34 15 

0.5 

20 hours−13 weeks 2.5−5.3 68b 51a,b 

3.5b 

9.6 hours 3.6 25 21 

0.5 

6.6 days 3.7 29 21 0.6 

Adult Man 

1.7 m2 SA 

68.5 12 

12 

750 

500 

7.4 

6 

17 1,670 29 21 2,030 43 

30 years; 170 cm L 15 500 7.5 16 1,250 20 

20−33 years 70.4 40 3,050 111 

Woman 54 12 340 4.5 19 860 16 30 880 25 

30 years; 160 cm L 15 400 6 20 940 19 

20−25 years; 165.8 cm L 

Pregnant (8th month) 

60.3 

16 650 10 

46 2,100 90 

a 

Calculated from V* = f × VT. b Crying. BW = body weights. 

f = frequency (breaths/minute). 

VT = tidal volume (mL). 

V* = minute volume (L/minute). 

cm L = length/height. 

Source: ICRP (1981). 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-28. Summary of Human Inhalation Rates by Activity Level (m3/hour)a 

Nb Restingc Nb Lightd Nb Moderatee Nb Heavyf 

Child, 6 years 8 0.4 16 0.8 4 2.0 5 2.3 

Child, 10 years 10 0.4 40 1.0 29 3.2 43 3.9 

Adult male 454 0.7 102 0.8 102 2.5 267 4.8 

Adult female 595 0.3 786 0.5 106 1.6 211 2.9 

Average adult 1,049 0.5 888 0.6 208 2.1 478 3.9 

a Values of inhalation rates for children (male and female) presented in this table represent the mean of 

values reported for each activity level in 1985. b Number of observations at each activity level. c Includes watching television, reading, and sleeping. d Includes most domestic work, attending to personal needs and care, hobbies, and conducting minor indoor 

repairs and home improvements. e Includes heavy indoor cleanup, performance of major indoor repairs and alterations, and climbing stairs. f Includes vigorous physical exercise and climbing stairs carrying a load. 

Source: Adapted from U.S. EPA (1985). 

Table 6-29. Estimated Minute Ventilation Associated With Activity Level for 

Average Male Adulta 

Level of work L/minute Representative activities 

Light 13 Level walking at 2 mph; washing clothes 

Light 19 Level walking at 3 mph; bowling; scrubbing floors 

Light 25 Dancing; pushing wheelbarrow with 15-kg load; simple construction; stacking 

firewood 

Moderate 30 Easy cycling; pushing wheelbarrow with 75-kg load; using sledgehammer 

Moderate 35 Climbing stairs; playing tennis; digging with spade 

Moderate 40 Cycling at 13 mph; walking on snow; digging trenches 

Heavy 

Heavy 

Very heavy 

55 

63 

72 

Cross-country skiing; rock climbing; stair climbing 

with load; playing squash or handball; chopping 

with axe 

Very heavy 85 Level running at 10 mph; competitive cycling 

Severe 100+ Competitive long distance running; cross-country skiing a Average adult assumed to weigh 70 kg. 

Source: Adapted from U.S. EPA (1985). 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-30. Activity Pattern Data Aggregated for Three Microenvironments by 

Activity Level for All Age Groups 

Microenvironment Activity Level 

Average Hours Per Day in Each 

Microenvironment at Each 

Activity Level 

Indoors 

Outdoors 

In Transportation 

Vehicle 

Resting 

Light 

Moderate 

Heavy 

TOTAL 

Resting 

Light 

Moderate 

Heavy 

TOTAL 

Resting 

Light 

Moderate 

Heavy 

TOTAL 

9.82 

9.82 

0.71 

0.10 

20.4 

0.51 

0.51 

0.65 

0.12 

1.77 

0.86 

0.86 

0.05 

0.0012 

1.77 

Source: Adapted from U.S. EPA (1985). 

Table 6-31. Summary of Daily Inhalation Rates (DIRs) Grouped by Age and Activity Level 

Subject 

Daily Inhalation Rate (m3/day)a 

Total Daily IRb 

(m3 Resting Light Moderate Heavy /day) 

Child, 6 years 4.47 8.95 2.82 0.50 16.74 

Child, 10 years 4.47 11.19 4.51 0.85 21.02 

Adult Male 7.83 8.95 3.53 1.05 21.4 

Adult Female 3.35 5.59 2.26 0.64 11.8 

Adult Average 5.60 6.71 2.96 0.85 16 

a Daily inhalation rate was calculated using the following equation: 

∑=

=

k 

i 

IRti T

IR 

1 

1 

IRi = Inhalation rate at ith activity, 

ti = Hours spent per day during ith activity, 

k = Number of activity periods, and 

T = Total time of the exposure period (e.g., a day). 

b Total daily inhalation rate was calculated by summing the specific activity (resting, light, moderate, 

heavy) and dividing them by the total amount of time spent on all activities. 

Source: Generated using the data from U.S. EPA (1985) as shown in Table 6-28 and Table 6-30. 

Exposure Factors Handbook Page
 

September 2011 6-67 
 

Table 6-32. Distribution Pattern of Predicted Ventilation Rate (VR) and Equivalent Ventilation Rate (EVR) 

for 20 Outdoor Workers 

VR (m3/hour)

a EVRb (m3

/hour/m2 body surface) 

Self-Reported 

Activity Level Nc 

Arithmetic 

Mean ± SD 

Geometric 

Mean ± SD 

Arithmetic 

Mean ± SD 

Geometric 

Mean ± SD 

Sleep 18,597 0.42 ± 0.16 0.39 ± 0.08 0.23 ± 0.08 0.22 ± 0.08 

Slow 41,745 0.71 ± 0.4 0.65 ± 0.09 0.38 ± 0.20 0.35 ± 0.09 

Medium 3,898 0.84 ± 0.47 0.76 ± 0.09 0.48 ± 0.24 0.44 ± 0.09 

Fast 572 2.63 ± 2.16 1.87 ± 0.14 1.42 ± 1.20 1.00 ± 0.14 

Percentile Rankings, VR 

1 5 10 50 90 95 99 99.9 

Sleep 

Slow 

Medium 

Fast 

0.18 

0.30 

0.36 

0.42 

0.18 

0.36 

0.42 

0.54 

0.24 

0.36 

0.48 

0.60 

0.36 

0.66 

0.72 

1.74 

0.66 

1.08 

1.32 

5.70 

0.72 

1.32 

1.68 

6.84 

0.90 

1.98 

2.64 

9.18 

1.20 

4.38 

3.84 

10.26 

Percentile Rankings, EVR 

1 5 10 50 90 95 99 99.9 

Sleep 

Slow 

Medium 

Fast 

0.12 

0.18 

0.18 

0.24 

0.12 

0.18 

0.24 

0.30 

0.12 

0.24 

0.30 

0.36 

0.24 

0.36 

0.42 

0.90 

0.36 

0.54 

0.72 

3.24 

0.36 

0.66 

0.90 

3.72 

0.48 

1.08 

1.38 

4.86 

0.60 

2.40 

2.28 

5.52 a Data presented by Shamoo et al. (1991) in L/minute were converted to m3

/hour. b EVR = VR per square meter of body surface area. c Number of minutes with valid appearing heart rate records and corresponding daily records of breathing 

rate. 

Source: Shamoo et al. (1991). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Page Exposure Factors Handbook 

6-68 September 2011 
 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-33. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor Workers 

Location Activity Typea 

Self-Reported 

Activity Level % of Time 

Inhalation rate 

(m3/hour)b 

± SD % of Avg.c 

Indoor Essential Sleep 

Slow 

Medium 

Fast 

28.7 

29.5 

2.4 

0 

0.42 ± 0.12 

0.72 ± 0.36 

0.72 ± 0.30 

0 

69 ± 15 

106 ± 43 

129 ± 38 

0 

Indoor Non-essential Slow 

Medium 

Fast 

20.4 

0.9 

0.2 

0.66 ± 0.36 

0.78 ± 0.30 

1.86 ± 0.96 

98 ± 36 

120 ± 50 

278 ± 124 

Outdoor Essential Slow 

Medium 

Fast 

11.3 

1.8 

0 

0.78 ± 0.36 

0.84 ± 0.54 

0 

117 ± 42 

130 ± 56 

0 

Outdoor Non-essential Slow 

Medium 

Fast 

3.2 

0.8 

0.7 

0.90 ± 0.66 

1.26 ± 0.60 

2.82 ± 2.28 

136 ± 90 

213 ± 91 

362 ± 275 a Essential activities include income-related work, household chores, child care, study and other school 

activities, personal care, and destination-oriented travel; Non-essential activities include sports and active 

leisure, passive leisure, some travel, and social or civic activities. b Data presented by Shamoo et al. (1991) in L/min were converted to m3

/hour. c Statistic was calculated by converting each VR for a given subject to a percentage of her/his overall 

average. 

Source: Adapted from Shamoo et al. (1991). 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-34. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subject Panels 

Panel Calibration Protocol Field Protocol 

Panel 1: Healthy Outdoor 

Workers—15 female, 5 male, 

age 19−50 

Laboratory treadmill exercise 

tests, indoor hallway walking tests 

at different self-chosen speeds, 

2 outdoor tests consisted of 

1-hour cycles each of rest, 

walking, and jogging. 

3 days in 1 typical summer week 

(included most active workday and 

most active day off); HR 

recordings and activity diary 

during waking hours. 

Panel 2: Healthy Elementary 

School Students—5 male, 

12 female, ages 10−12 

Outdoor exercises each consisted 

of 20 minute rest, slow walking, 

jogging and fast walking. 

Saturday, Sunday and Monday 

(school day) in early autumn; heart 

rate recordings and activity diary 

during waking hours and during 

sleep. 

Panel 3: Healthy High School 

Students—7 male, 12 female, 

ages 13−17 

Outdoor exercises each consisted 

of 20 minute rest, slow walking, 

jogging and fast walking. 

Same as Panel 2, however, no heart 

rate recordings during sleep for 

most subjects. 

Panel 4: Adult Asthmatics, 

clinically mild, moderate, and 

severe—15 male, 34 female, 

age 18−50 

Treadmill and hallway exercise 

tests. 

1 typical summer week, 1 typical 

winter week; hourly activity/health 

diary during waking hours; lung 

function tests 3 times daily; HR 

recordings during waking hours on 

at least 3 days (including most 

active work day and day off). 

Panel 5: Adult Asthmatics from 

2 neighborhoods of contrasting O3 

air quality—10 male, 14 female, 

age 19−46 

Treadmill and hallway exercise 

tests. 

Similar to Panel 4, personal NO2 

and acid exposure monitoring 

included. (Panels 4 and 5 were 

studied in different years, and had 

10 subjects in common). 

Panel 6: Young Asthmatics— 

7 male, 6 female, ages 11−16 

Laboratory exercise tests on 

bicycles and treadmills. 

Summer monitoring for 

2 successive weeks, including 

2 controlled exposure studies with 

few or no observable respiratory 

effects. 

Panel 7: Construction Workers— 

7 male, age 26−34 

Performed similar exercises as 

Panel 2 and 3, and also performed 

job-related tests including lifting 

and carrying a 9-kg pipe. 

HR recordings and diary 

information during 1 typical 

summer work day. 

Source: Linn et al. (1992). 

Page Exposure Factors Handbook 

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c 

Table 6-35. Subject Panel Inhalation Rates by Mean Ventilation Rate (VR), Upper Percentiles, and 

Self-Estimated Breathing Rates 

Inhalation Rates (m3/hour) 

Mean VR at Activity Levels

b 

Panel Number 99th Percentile 

and Description Na Mean VR VR Slow Medium Fast 

Healthy 

1—Adults 20 0.78 2.46 0.72 1.02 3.06 

2—Elementary School Students 17 0.90 1.98 0.84 0.96 1.14 

3—High School Students 19 0.84 2.22 0.78 1.14 1.62 

7—Construction Workers

c 7 1.50 4.26 1.26 1.50 1.68 

Asthmatics 

4—Adults 49 1.02 1.92 1.02 1.68 2.46 

5—Adultsd 24 1.20 2.40 1.20 2.04 4.02 

6—Elementary and High School 13 1.20 2.40 1.20 1.20 1.50 

Students 

a	 Number of individuals in each survey panel. b	 Some subjects did not report medium and/or fast activity. Group means were calculated from individual 

means (i.e., give equal weight to each individual who recorded any time at the indicated activity level). 

Construction workers recorded only on 1 day, mostly during work, while others recorded on ≥1 work or 

school day and ≥1 day off. d	 Excluding subjects also in Panel 4. 

VR	 = Ventilation rate. 

Source:	 Linn et al. (1992). 

Table 6-36. Actual Inhalation Rates Measured at Four Ventilation Levels 

Mean Inhalation Rate

a (m3

/hour) 

Subject Location Low Medium Heavy Very Heavy 

All Indoor (treadmill post) 1.23 1.83 3.13 4.13 

subjects Outdoor 0.88 1.96 2.93 4.90 

Total 0.93 1.92 3.01 4.80 a Original data were presented in L/minute. Conversion to m3

/hour was obtained as follows: 

L/minute × 0.001 m3/L × 60 minute/hour = m3/hour 

Source:	 Adapted from Shamoo et al. (1992). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Exposure Factors Handbook Page
 

September 2011 6-71 
 

c 

Table 6-37. Distribution of Predicted Inhalation Rates by Location and Activity Levels for Elementary and 

High School Students 

Inhalation Rates (m3/hour) 

Activity % Recorded Percentile Rankings

b 

Age (years) Student Location Level Time

a Mean ± SD 1st 50th 99.9th 

10−12 ELc Indoors slow 49.6 0.84 ± 0.36 0.18 0.78 2.34 

(Nd = 17) medium 23.6 0.96 ± 0.36 0.24 0.84 2.58 

fast 2.4 1.02 ± 0.60 0.24 0.84 3.42 

Outdoors slow 8.9 0.96 ± 0.54 0.36 0.78 4.32 

medium 11.2 1.08 ± 0.48 0.24 0.96 3.36 

fast 4.3 1.14 ± 0.60 0.48 0.96 3.60 

13−17 HSc Indoors slow 70.7 0.78 ± 0.36 0.30 0.72 3.24 

(Nd = 19) medium 10.9 0.96 ± 0.42 0.42 0.84 4.02 

fast 1.4 1.26 ± 0.66 0.54 1.08 6.84e 

Outdoors slow 8.2 0.96 ± 0.48 0.42 0.90 5.28 

medium 7.4 1.26 ± 0.78 0.48 1.08 5.70 

fast 1.4 1.44 ± 1.08 0.48 1.02 5.94 a	 Recorded time averaged about 23 hours per elementary school student and 33 hours per high school 

student over 72-hour periods. b	 Geometric means closely approximated 50th percentiles; geometric standard deviations were 1.2−1.3 for 

HR, 1.5−1.8 for VR. 

Elementary school student (EL) or high school student (HS). d	 Number of students that participated in survey. e	 Highest single value. 

SD	 = Standard deviation. 

Source:	 Spier et al. (1992). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Page Exposure Factors Handbook 

6-72 September 2011 
 

c 

Table 6-39. Distribution Patterns of Daily Inhalation Rates (DIRs) for Elementary (EL) and High School (HS) 

Students Grouped by Activity Level 

Age Mean IRb Percentile Rankings a 1st Students (years) Location Activity Type (m3

/day)	 50th 99.9th 

EL (Nc = 17) 10 to 12 Indoor Light 13.7 2.93 12.71 38.14 

Moderate 2.8 0.70 2.44 7.48 

Heavy 0.4 0.10 0.34 1.37 

EL Outdoor Light 2.1 0.79 1.72 9.5 

Moderate 1.84 0.41 1.63 5.71 

Heavy 0.57 0.24 0.48 1.80 

HS (N = 19) 13 to 17 Indoor Light 15.2 5.85 14.04 63.18 

Moderate 1.4 0.63 1.26 6.03 

Heavy 0.25 0.11 0.22 1.37 

HS Outdoor Light 1.15 0.5 1.08 6.34 

Moderate 1.64 0.62 1.40 7.41 

Heavy 0.29 0.10 0.20 1.19 a	 For this report, activity type presented in Table 6-37 and Table 6-38 was redefined as light activity for slow, 

moderate activity for medium, and heavy activity for fast. b	 Daily inhalation rate was calculated by multiplying the hours spent at each activity level (see Table 6-38) by 

the corresponding inhalation rate (see Table 6-37). 

Number of elementary (EL) and high school students (HS). 

Source:	 Adapted from Spier et al. (1992) (Generated using data from Table 6-37 and Table 6-38). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Table 6-38. Average Hours Spent per Day in a Given Location and Activity Level for Elementary and 

High School Students 

Students Location 

Activity Level Total Time Spent 

Slow Medium Fast (hours/day) 

Elementary school, 

ages 10 to 12 years 

(N = 17) 

Indoors 16.3 2.9 0.4 19.6 

Outdoors 2.2 1.7 0.5 4.4 

High school, 

ages 13 to 17 years 

(N = 19) 

Indoors 19.5 1.5 0.2 21.2 

Outdoors 1.2 1.3 0.2 2.7 

N = Number of students that participated in survey. 

Source: Spier et al. (1992). 

Exposure Factors Handbook Page
 

September 2011 6-73 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-40. Mean Minute Inhalation Rate (m3/minute) by Group and Activity for Laboratory Protocols 

Activity Young Childrena Childrena Adult Femalesa Adult Malesa Adults (combined)a 

Lying 

Sitting 

Standing 

6.19E−03 

6.48E−03 

6.76E−03 

7.51E−03 

7.28E−03 

8.49E−03 

7.12E−03 

7.72E−03 

8.36E−03 

8.93E−03 

9.30E−03 

10.65E−03 

8.03E−03 

8.51E−03 

9.51E−03 

Walking 

1.5 mph 

1.875 mph 

2.0 mph 

2.25 mph 

2.5 mph 

3.0 mph 

3.3 mph 

4.0 mph 

1.03E−02 

1.05E−02 

DNP 

1.17E−02 

DNP 

DNP 

DNP 

DNP 

DNPb 

DNP 

1.41E−02 

DNP 

1.56E−02 

1.78E−02 

DNP 

DNP 

DNP 

DNP 

DNP 

DNP 

2.03E−02 

2.42E−02 

DNP 

DNP 

DNP 

DNP 

DNP 

DNP 

2.41E−02 

DNP 

2.79E−02 

3.65E−02 

DNP 

DNP 

DNP 

DNP 

2.22E−02 

DNP 

DNP 

DNP 

Running 

3.5 mph 

4.0 mph 

4.5 mph 

5.0 mph 

6.0 mph 

DNP 

DNP 

DNP 

DNP 

DNP 

2.68E−02 

3.12E−02 

3.72E−02 

DNP 

DNP 

DNP 

4.60E−02b 

4.79E−02b 

5.08E−02b 

DNP 

DNP 

DNP 

5.73E−02 

5.85E−02 

6.57E−02b 

DNP 

DNP 

5.26E−02 

5.47E−02 

DNP 

a Young children, male and female 3−5.9 year olds; children, male and female 6−12.9 year olds; adult females, 

adolescent, young to middle-aged, and older adult females; adult males, adolescent, young to middle-aged, 

and older adult males. DNP, group did not perform this protocol or N was too small for appropriate mean 

comparisons. b Older adults not included in the mean value since they did not perform running protocol at particular speeds. 

Source: Adams (1993). 

Table 6-41. Mean Minute Inhalation Rate (m3/minute) by Group and Activity for Field Protocols 

Activity Young Childrena Childrena Adult Femalesa Adult Malesa Adults (combined) a 

Play 

Car Driving 

Car Riding 

Yardwork 

Housework 

Car Maintenance 

Mowing 

Woodworking 

1.13E−02 

DNP 

DNP 

DNP 

DNP 

DNP 

DNP 

DNP 

1.79E−02 

DNP 

DNP 

DNP 

DNP 

DNP 

DNP 

DNP 

DNP 

8.95E−03 

8.19E−03 

1.92E−02b 

1.74E−02 

DNP 

DNP 

DNP 

DNP 

1.08E−02 

9.83E−03 

2.61E−02c

/3.19E−02d 

DNP 

2.32E−02e 

3.66E−02b 

2.44E−02b 

DNP 

9.87E−03 

9.01E−03 

2.27E−02c

/2.56E−02d 

DNP 

DNP 

DNP 

DNP 

a Young children, male and female 3−5.9 year olds; children, male and female 6−12.9 year olds; adult females, adolescent, 

young to middle-aged, and older adult females; adult males, adolescent, young to middle-aged, and older adult males; 

DNP, group did not perform this protocol or N was too small for appropriate mean comparisons. b Adolescents not included in mean value since they did not perform this activity. c Mean value for young to middle-aged adults only. d Mean value for older adults only. e Older adults not included in the mean value since they did not perform this activity. 

Source: Adams (1993). 

Page Exposure Factors Handbook 

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c 

Table 6-42. Summary of Average Inhalation Rates (m3/hour) by Age Group and Activity Levels for
 

Laboratory Protocols
 

Activity Level 

Age Group Restinga Sedentaryb Light

c Moderated Heavye 

Young Children 

(3−5.9 years) 

Average inhalation rate (m3

/hour) 

(N = 12, sex not specified) 

0.37 0.40 0.65 DNPf DNP 

Children 

(6−12.9 years) 

Average inhalation rate (m3

/hour) 

(N = 40, 20 male and 20 female) 

0.45 0.47 0.95 1.74 2.23 

Adults (females) 

(Adolescent, young to middle aged, and 

older adult females) 

(N = 37) 

0.43 0.48 1.33 2.76 2.96g 

Adults (males) 

(Adolescent, young to middle aged, and 

older adult males) 

(N = 39) 

0.54 0.60 1.45 1.93 3.63 

Adults (combined) 0.49 0.54 1.38 2.35 3.30 

(N = 76) 

a Resting defined as lying (see Table 6-40 for original data). b Sedentary defined as sitting and standing (see Table 6-40 for original data). 

Light defined as walking at speed level 1.5−3.0 mph (see Table 6-40 for original data). d Moderate defined as fast walking (3.3−4.0 mph) and slow running (3.5−4.0 mph) (see Table 6-40 for original 

data). e Heavy defined as fast running (4.5−6.0 mph) (see Table 6-40 for original data). f Group did not perform (DNP) this protocol or N was too small for appropriate mean comparisons. All young 

children did not run. g Older adults not included in mean value since they did not perform running protocols at particular speeds. 

Source: Adapted from Adams (1993). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Exposure Factors Handbook Page
 

September 2011 6-75 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-43. Summary of Average Inhalation Rates (m3/hour) by Age Group And Activity Levels in 

Field Protocols 

Age Group 

Sedentary 

Activitya 

Light 

Activityb Moderate Activityc 

Young Children (3 to 5.9 years) 

Average inhalation rate (m3/hour) 

(N = 12, sex not specified) 

DNP DNPd 0.68 

Children (6 to 12.9 years) 

Average inhalation rate (m3/hour) 

(N = 40, 20 male and 20 female) 

DNP DNP 1.07 

Adults (females) 

(Adolescent, young to middle aged, and older adult females) 

(N = 37) 

0.51 1.10e DNP 

Adults (males) 

(Adolescent, young to middle aged, and older adult males) 

(N = 39) 

0.62 1.40 1.78f 

Adults (combined) 

(N = 76) 

0.57 1.25 DNP 

a Sedentary activity was defined as car driving and riding (both sexes) (see Table 6-41 for original data). b Light activity was defined as car maintenance (males), housework (females), and yard work (females) (see 

Table 6-41 for original data). c Moderate activity was defined as mowing (males); wood working (males); yard work (males); and play 

(children) (see Table 6-41 for original data). d DNP. Group did not perform this protocol or N was too small for appropriate mean comparisons. e Older adults not included in mean value since they did not perform this activity. f Adolescents not included in mean value since they did not perform this activity. 

N = Number of individuals. 

Source: Adams (1993). 

Page Exposure Factors Handbook 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-44. Comparisons of Estimated Basal Metabolic Rates (BMR) With Average Food-Energy Intakes 

(EFDs) for Individuals Sampled in the 1977−1978 NFCS 

Cohort/Age 

(years) 

Body Weight 

(kg) 

BMRa EFD 

Ratio 

EFDd MJ/day /BMR b Kcal/dayc MJ/day Kcal/day 

Males and Females 

<1 7.6 1.74 416 3.32 793 1.90 

1 to 2 13 3.08 734 5.07 1,209 1.65 

3 to 5 18 3.69 881 6.14 1,466 1.66 

6 to 8 26 4.41 1,053 7.43 1,774 1.68 

Males 

9 to 11 36 5.42 1,293 8.55 2,040 1.58 

12 to 14 50 6.45 1,540 9.54 2,276 1.48 

15 to 18 66 7.64 1,823 10.8 2,568 1.41 

19 to 22 74 7.56 1,804 10.0 2,395 1.33 

23 to 34 79 7.87 1,879 10.1 2,418 1.29 

35 to 50 82 7.59 1,811 9.51 2,270 1.25 

51 to 64 80 7.49 1,788 9.04 2,158 1.21 

65 to 74 76 6.18 1,476 8.02 1,913 1.30 

≥75 71 5.94 1,417 7.82 1,866 1.32 

Females 

9 to 11 36 4.91 1,173 7.75 1,849 1.58 

12 to 14 49 5.64 1,347 7.72 1,842 1.37 

15 to 18 56 6.03 1,440 7.32 1,748 1.21 

19 to 22 59 5.69 1,359 6.71 1,601 1.18 

23 to 34 62 5.88 1,403 6.72 1,603 1.14 

35 to 50 66 5.78 1,380 6.34 1,514 1.10 

51 to 64 67 5.82 1,388 6.40 1,528 1.10 

65 to 74 66 5.26 1,256 5.99 1,430 1.14 

≥75 62 5.11 1,220 5.94 1,417 1.16 

a Calculated from the appropriate age and sex-based BMR equations given in Table 6-46. b MJ/day = megajoules/day. c Kcal/day = kilocalories/day. d Food-energy intake (Kcal/day) or (MJ/day). 

Source: Layton (1993). 

Exposure Factors Handbook Page
 

September 2011 6-77 
 

c 

Table 6-45. Daily Inhalation Rates (DIRs) Calculated From Food-Energy Intakes (EFDs) 

METa Value Inhalation Rates 

Cohort/Age (years) Lb 

Daily Inhalation Ratec 

(m3/day) 

Sleep 

(hours) Ad Fe 

Inactivef 

(m3/day) 

Activef 

(m3/day) 

Males and Females 

<1 1 4.5 11 1.9 2.7 2.35 6.35 

1 to 2 2 6.8 11 1.6 2.2 4.16 9.15 

3 to 5 3 8.3 10 1.7 2.2 4.98 10.96 

6 to 8 3 10 10 1.7 2.2 5.95 13.09 

Males 

9 to 11 3 14 9 1.9 2.5 7.32 18.3 

12 to 14 3 15 9 1.8 2.2 8.71 19.16 

15 to 18 4 17 8 1.7 2.1 10.31 21.65 

19 to 22 4 16 8 1.6 1.9 10.21 19.4 

23 to 34 11 16 8 1.5 1.8 10.62 19.12 

35 to 50 16 15 8 1.5 1.8 10.25 18.45 

51 to 64 14 15 8 1.4 1.7 10.11 17.19 

65 to 74 10 13 8 1.6 1.8 8.34 15.01 

≥75 1 13 8 1.6 1.9 8.02 15.24 

Lifetime average

g 14 

Females 

9 to 11 3 13 9 1.9 2.5 6.63 16.58 

12 to 14 3 12 9 1.6 2.0 7.61 15.22 

15 to 18 4 12 8 1.5 1.7 8.14 13.84 

19 to 22 4 11 8 1.4 1.6 7.68 12.29 

23 to 34 11 11 8 1.4 1.6 7.94 12.7 

35 to 50 16 10 8 1.3 1.5 7.80 11.7 

51 to 64 14 10 8 1.3 1.5 7.86 11.8 

65 to 74 10 9.7 8 1.4 1.5 7.10 10.65 

≥75 1 9.6 8 1.4 1.6 6.90 11.04 

Lifetime average

g 10 

a	 MET = Metabolic equivalent. b	 L is the number of years for each age cohort. 

Daily inhalation rate was calculated by multiplying the EFD values (see Table 6-44) by H × VQ × (m3 1,000 L−1

) for subjects under 

9 years of age and by 1.2 × H × VQ × (m3 1,000 L−1

) (for subjects 9 years of age and older (see text for explanation). 

where: 

EFD = (Kcal/day) or (MJ/day), 

H = Oxygen uptake = 0.05 L O2/KJ or 0.21 L O2/Kcal, and 

VQ = Ventilation equivalent = 27 = geometric mean of VQs (unitless). 

d	 For individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitless) (see Table 6-44) by the 

factor 1.2 (see text for explanation). 

e	 F = (24A − S)/(24 − S) (unitless), ratio of the rate of energy expenditure during active hours to the estimated BMR (unitless). 

where: 

S = Number of hours spent sleeping each day (hours). 

f	 Inhalation rate for inactive periods was calculated as BMR × H × VQ × (d 1,440 minute−1

) and for active periods by multiplying 

inactive inactive inhalation rate by F (See footnote e); BMR values are from Table 6-44. 

where: 

BMR = Basal metabolic rate (MJ/day) or (kg/hour). 

g	 Lifetime average was calculated by multiplying individual inhalation rate by corresponding L values summing the products across 

cohorts and dividing the result by 75, the total of the cohort age spans. 

Source:	 Layton (1993). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

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Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Table 6-46. Statistics of the Age/Sex Cohorts Used to Develop Regression Equations for Predicting Basal Metabolic Rates 

(BMR) 

Sex, 

Age (years) 

BMR 

CV 

Body Weight 

(kg) N BMR Equationa MJ d r −1 SD 

Males 

Under 3 

3 to <10 

10 to <18 

18 to <30 

30 to <60 

≥60 

1.51 

4.14 

5.86 

6.87 

6.75 

5.59 

0.92 

0.50 

1.17 

0.84 

0.87 

0.93 

0.61 

0.12 

0.20 

0.12 

0.13 

0.17 

6.6 

21 

42 

63 

64 

62 

162 

338 

734 

2,879 

646 

50 

0.249 BW − 0.127 

0.095 BW + 2.110 

0.074 BW + 2.754 

0.063 BW + 2.896 

0.048 BW + 3.653 

0.049 BW + 2.459 

0.95 

0.83 

0.93 

0.65 

0.60 

0.71 

Females 

Under 3 

3 to <10 

10 to <18 

18 to <30 

30 to <60 

≥60 

1.54 

3.85 

5.04 

5.33 

5.62 

4.85 

0.92 

0.49 

0.78 

0.72 

0.63 

0.61 

0.59 

0.13 

0.15 

0.14 

0.11 

0.12 

6.9 

21 

38 

53 

61 

56 

137 

413 

575 

829 

372 

38 

0.244 BW − 0.130 

0.085 BW + 2.033 

0.056 BW + 2.898 

0.062 BW + 2.036 

0.034 BW + 3.538 

0.038 BW + 2.755 

0.96 

0.81 

0.80 

0.73 

0.68 

0.68 

a Body weight (BW) in kg. 

SD = Standard deviation. 

CV = Coefficient of variation (SD/mean). 

N = Number of observations. 

r = Coefficient of correlation. 

Source: Layton (1993). 

Table 6-47. Daily Inhalation Rates (DIRs) Obtained From the Ratios of Total Energy 

Expenditure to Basal Metabolic Rate (BMR) 

Sex/Age 

(years) 

Body Weighta 

(kg) 

BMRb 

(MJ/day) VQ Ac 

H 

(m3O2/MJ) 

Inhalation Rate, VE 

(m3/day)d 

Males 

0.5 to <3 

3 to <10 

10 to <18 

18 to <30 

30 to <60 

≥60 

14 

23 

53 

76 

80 

75 

3.4 

4.3 

6.7 

7.7 

7.5 

6.1 

27 

27 

27 

27 

27 

27 

1.6 

1.6 

1.7 

1.59 

1.59 

1.59 

0.05 

0.05 

0.05 

0.05 

0.05 

0.05 

7.3 

9.3 

15 

17 

16 

13 

Females 

0.5 to <3 

3 to <10 

10 to <18 

18 to <30 

30 to <60 

≥60 

11 

23 

50 

62 

68 

67 

2.6 

4.0 

5.7 

5.9 

5.8 

5.3 

27 

27 

27 

27 

27 

27 

1.6 

1.6 

1.5 

1.38 

1.38 

1.38 

0.05 

0.05 

0.05 

0.05 

0.05 

0.05 

5.6 

8.6 

12 

11 

11 

9.9 

a Body weight was based on the average weights for age/sex cohorts in the U.S. population. b The BMRs are calculated using the respective body weights and BMR equations (see Table 6-46). c The values of the BMR multiplier (EFD/BMR) for those 18 years and older were derived from the Basiotis et al. (1989) 

study: male = 1.59, female = 1.38. For males and females under 10 years old, the mean BMR multiplier used was 1.6. 

For males and females aged 10 to <18 years, the mean values for A given in Table 6-45 for 12−14 years and 15−18 

years, age brackets for males and females were used: male = 1.7 and female = 1.5. d Inhalation rate = BMR × A × H × VQ; VQ = ventilation equivalent and H = oxygen uptake. 

Source: Layton (1993). 

Exposure Factors Handbook Page
 

September 2011 6-79 
Chapter 6 -

Exposure Factors Handbook 

Inhalation Rates 

Page Exposure Factors Handbook 6-80 September 2011 

Table 6-48. Daily Inhalation Rates (DIRs) Based on Time-Activity Survey 

Age (years) 

and Activity MET 

Males Females 

Body Weighta 

(kg) 

BMRb 

(KJ/hour) 

Durationc 

(hour/day) 

Ed 

(MJ/day) 

VE 

e 

(m3/day) 

VE 

f 

(m3/hour) 

Body Weighta 

(kg) 

BMRb 

(KJ/hour) 

Durationc 

(hour/day) 

Ed 

(MJ/day) 

VE 

e 

(m3/day) 

VE 

f 

(m3/hour) 

20−34 

Sleep 

Light 

Moderate 

Hard 

Very Hard 

Totals 

1 

1.5 

4 

6 

10 

76 

76 

76 

76 

76 

320 

320 

320 

320 

320 

7.2 

14.5 

1.2 

0.64 

0.23 

24 

2.3 

7.0 

1.5 

1.2 

0.74 

17 

3.1 

9.4 

2.1 

1.7 

1.0 

17 

0.4 

0.7 

1.7 

2.6 

4.3 

62 

62 

62 

62 

62 

283 

283 

283 

283 

283 

7.2 

14.5 

1.2 

0.64 

0.23 

24 

2.0 

6.2 

1.4 

1.1 

0.65 

11 

2.8 

8.3 

1.8 

1.5 

0.88 

15 

0.4 

0.6 

1.5 

2.3 

3.8 

35−49 

Sleep 

Light 

Moderate 

Hard 

Very Hard 

Totals 

1 

1.5 

4 

6 

10 

81 

81 

81 

81 

81 

314 

314 

314 

314 

314 

7.1 

14.6 

1.4 

0.59 

0.29 

24 

2.2 

6.9 

1.8 

1.1 

0.91 

13 

3.0 

9.3 

2.4 

1.5 

1.2 

17 

0.4 

0.6 

1.7 

2.5 

4.2 

67 

67 

67 

67 

67 

242 

242 

242 

242 

242 

7.1 

14.6 

1.4 

0.59 

0.29 

24 

1.7 

5.3 

1.4 

0.9 

0.70 

9.9 

2.3 

7.2 

1.8 

1.2 

0.95 

13 

0.3 

0.5 

1.3 

2.0 

3.2 

50−64 

Sleep 

Light 

Moderate 

Hard 

Very Hard 

Totals 

1 

1.5 

4 

6 

10 

80 

80 

80 

80 

80 

312 

312 

312 

312 

312 

7.3 

14.9 

1.1 

0.50 

0.14 

24 

2.3 

7.0 

1.4 

0.94 

0.44 

12 

3.1 

9.4 

1.9 

1.3 

0.6 

16 

0.4 

0.6 

1.7 

2.5 

4.2 

68 

68 

68 

68 

68 

244 

244 

244 

244 

244 

7.3 

14.9 

1.1 

0.5 

0.14 

24 

1.8 

5.4 

1.1 

0.7 

0.34 

9.4 

2.4 

7.4 

1.4 

1.0 

0.46 

13 

0.3 

0.5 

1.3 

2.0 

3.3 

65−74 

Sleep 

Light 

Moderate 

Hard 

Very Hard 

Totals 

1 

1.5 

4 

6 

10 

75 

75 

75 

75 

75 

256 

256 

256 

256 

256 

7.3 

14.9 

1.1 

0.5 

0.14 

24 

1.9 

5.7 

1.1 

0.8 

0.36 

9.8 

2.5 

7.7 

1.5 

1.0 

0.48 

13 

0.3 

0.5 

1.4 

2.1 

3.5 

67 

67 

67 

67 

67 

221 

221 

221 

221 

221 

7.3 

14.9 

1.1 

0.5 

0.14 

24 

1.6 

4.9 

1.0 

0.7 

0.31 

8.5 

2.2 

6.7 

1.3 

0.9 

0.42 

11 

0.3 

0.4 

1.2 

1.8 

3.0 

a Body weights were obtained from Najjar and Rowland (1987). b The BMRs for the age/sex cohorts were calculated using the respective body weights and the BMR equations (see Table 6-46). c Duration of activities were obtained from Sallis et al. (1985). d Energy expenditure rate (E) was calculated by multiplying BMR (KJ/hour) × (MJ/1,000 KJ) × duration (hour/day) × MET. e VE (inhalation rate) was calculated by multiplying E (MJ/day) by H (0.05 m3 oxygen/MJ) by VQ (27). f VE (m3

/hour) was calculated by multiplying BMR (KJ/hour) × (MJ/1,000 KJ) × MET × H (0.05 m3 oxygen/MJ) × VQ (27). 

Source: Layton (1993). 
 

Table 6-49. Inhalation Rates for Short-Term Exposures 

Activity Type 

Rest Sedentary Light Moderate Heavy 

MET (BMR Multiplier) 

Sex/Age 

(years) 

Body 

Weight 

(kg)a 

BMRb 

(MJ/day) 

1 1.2 2c 4d 

Inhalation Rate (m3/minute)

f,g 

10e 

Males 

0.5 to <3 14 3.40 3.2E−03 3.8E−03 6.3E−03 1.3E−02 –h 

3 to <10 23 4.30 4.0E−03 4.8E−03 8.2E−03 1.6E−02 –h 

10 to <18 53 6.70 6.3E−03 7.5E−03 1.3E−02 2.5E−02 6.3E−02 

18 to <30 76 7.70 7.2E−03 8.7E−03 1.4E−02 2.9E−02 7.2E−02 

30 to <60 80 7.50 7.0E−03 8.3E−03 1.4E−02 2.8E−02 7.0E−02 

≥60 75 6.10 5.7E−03 6.8E−03 1.1E−02 2.3E−02 5.7E−02 

Females 

0.5 to <3 11 2.60 2.4E−03 2.8E−03 4.8E−03 1.0E−02 –h 

3 to <10 23 4.00 3.8E−03 4.5E−03 7.5E−03 1.5E−02 –h 

10 to <18 50 5.70 5.3E−03 6.3E−03 1.1E−02 2.1E−02 5.3E−02 

18 to <30 62 5.90 5.5E−03 6.7E−03 1.1E−02 2.2E−02 5.5E−02 

30 to <60 68 5.80 5.3E−03 6.5E−03 1.1E−02 2.2E−02 5.4E−02 

≥60 67 5.30 5.0E−03 6.0E−03 9.8E−03 2.0E−02 5.0E−02 

a Body weights were based on average weights for age/sex cohorts of the U.S. population. b The BMRs for the age/sex cohorts were calculated using the respective body weights and the BMR 

equations (see Table 6-46). c Range = 1.5−2.5. d Range = 3−5. e Range = >5−20. f	 The inhalation rate was calculated as IR = BMR (MJ/day) × H (0.05 L/KJ) × MET × VQ (27) × 

(day/1,440 minutes). g O 3 riginal data were presented in L/minute. Conversion to m3

/minute was obtained as follows: m × L 

1000L min h	 The maximum possible MET sustainable for more than 5 minutes does not reach 10 for females and males 

until ages 13 and 12, respectively. Therefore, an MET of 10 is not possible for this age category. 

Source:	 Layton (1993). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Exposure Factors Handbook Page
 

September 2011 6-81 
c 

Table 6-50. Distributions of Individual and Group Inhalation/Ventilation Rate (VR) for Outdoor Workers 

VR (m3/hour) 

Percentile 

1st 99th Population Group and Subgroupa Mean ± SD 50th 

All Subjects (Nb= 19) 1.68 ± 0.72 0.66 1.62 3.90 

Job 

GCWc/Laborers (N = 5) 1.44 ± 0.66 0.48 1.32 3.66
 

Iron Workers (N = 3) 1.62 ± 0.66 0.60 1.56 3.24
 

Carpenters (N = 11) 1.86 ± 0.78 0.78 1.74 4.14
 

Site 

Medical Office Site (N = 7) 1.38 ± 0.66 0.60 1.20 3.72 

Hospital Site (N = 12) 1.86 ± 0.78 0.72 1.80 3.96 a Each group or subgroup mean was calculated from individual means, not from pooled data. b N = number of individuals performing specific jobs or number of individuals at survey sites. 

GCW = general construction worker. 

Source: Linn et al. (1993). 

Table 6-51. Individual Mean Inhalation Rate (m3/hour) by Self-Estimated Breathing Rate or Job Activity 

Category for Outdoor Workers 

Self-Estimated 

Breathing Rate (m3/hour) Job Activity Category (m3/hour) 

Population Group and Subgroup Slow Medium Fast Sit/Stand Walk Carry Trade

a 

All Subjects (N = 19) 1.44 1.86 2.04 1.56 1.80 2.10 1.92 

Job 

GCWb/Laborers (N = 5) 1.20 1.56 1.68 1.26 1.44 1.74 1.56 

Iron Workers (N = 3) 1.38 1.86 2.10 1.62 1.74 1.98 1.92 

Carpenters (N = 11) 1.62 2.04 2.28 1.62 1.92 2.28 2.04 

Site 

Office Site (N = 12) 1.14 1.44 1.62 1.14 1.38 1.68 1.44 

Hospital Site (N = 12) 1.62 2.16 2.40 1.80 2.04 2.34 2.16 

a Trade = “Working at Trade” (i.e., tasks specific to the individual’s job classification). b GCW = general construction worker. 

Source: Linn et al. (1993). 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Page Exposure Factors Handbook 

6-82 September 2011 
Table 6-52. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in 618 Infants 

and Children Grouped in Classes of Age 

Age (months) N 

<2 104 48.0 ± 9.1 47 39.8 ± 8.7 39 

2 to <6 106 44.1 ± 9.9 42 33.4 ± 7.0 32 

6 to <12 126 39.1 ± 8.5 38 29.6 ± 7.0 28 

12 to <18 77 34.5 ± 5.8 34 27.2 ± 5.6 26 

18 to <24 65 32.0 ± 4.8 32 25.3 ± 4.6 24 

24 to <30 79 30.0 ± 6.2 30 23.1 ± 4.6 23 

30 to 36 61 27.1 ± 4.1 28 21.5 ± 3.7 21 

SD = Standard deviation. 

N = Number of individuals. 

Source: Rusconi et al. (1994). 

Inhalation Rate (breaths/minute) 

Waking Sleeping 

Mean ± SD Median Mean ± SD Median 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates 

Exposure Factors Handbook Page
 

September 2011 6-83 
Chapter 6—

Exposure Factors Handbook 

Inhalation Rates 

Page Exposure Factors Handbook 

September 2011 6-84 

 

 

 

c 

Table 6-53. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/day) Percentiles for Free-Living Underweighta Adolescents and Women Aged 11 to 55 Years 

During Pregnancy and Postpartum Weeks
 

Physiological Daily Inhalation Rates

c (m3

/day) Number of 

Age Group 

(years) 

Progression of the 

Reproductive Cycle 

Subjectsb 

NExp or 

NSim Mean ± SD 5th 10th 25th 

Percentile 

50th 75th 90th 95th 99th 

11 to <23 Non-pregnant females 50 12.18 ± 2.08 8.76 9.52 10.78 12.18 13.58 14.84 15.60 17.02 

Pre-pregnancy 0 week 5,000 12.27 ± 1.95 9.35 9.74 10.79 12.18 13.72 14.63 15.48 16.90 

Pregnancy 9th week 5,000 17.83 ± 4.52 13.20 13.91 15.40 17.34 19.55 21.38 23.13 27.40 

Pregnancy 22nd week 5,000 17.98 ± 4.77 13.19 13.95 15.47 17.46 19.73 22.09 23.90 30.69 

Pregnancy 36th week 5,000 18.68 ± 4.73 13.44 14.25 15.96 17.88 20.24 23.01 25.59 34.45 

Postpartum 6th week 5,000 20.39 ± 2.69 16.31 17.02 18.47 20.31 22.22 23.79 24.82 26.62 

Postpartum 27th week 5,000 20.21 ± 2.66 16.17 16.88 18.31 20.14 22.02 23.58 24.61 26.39 

23 to <30 Non-pregnant females 17 13.93 ± 2.27 10.20 11.02 12.40 13.93 13.93 16.83 17.65 19.20 

Pre-pregnancy 0 week 5,000 13.91 ± 2.17 11.41 11.50 12.08 13.92 15.32 16.01 17.81 19.97 

Pregnancy 9th week 5,000 20.03 ± 5.01 15.83 16.17 17.08 19.75 21.60 23.76 26.94 34.21 

Pregnancy 22nd week 5,000 20.15 ± 4.24 15.81 16.16 17.07 19.80 21.67 24.49 27.46 32.69 

Pregnancy 36th week 5,000 20.91 ± 5.37 15.97 16.37 17.56 20.29 22.31 26.42 28.95 38.26 

Postpartum 6th week 5,000 22.45 ± 2.91 18.70 19.15 20.14 22.23 24.15 25.65 27.68 30.57 

Postpartum 27th week 5,000 22.25 ± 2.89 18.53 18.98 19.96 22.04 23.94 25.42 27.44 30.30 

30 to 55 Non-pregnant females 14 12.89 ± 1.40 10.58 11.09 11.94 12.89 12.89 14.69 15.20 16.16 

Pre-pregnancy 0 week 5,000 12.91 ± 1.36 10.85 11.28 11.99 12.49 13.98 14.99 15.13 15.18 

Pregnancy 9th week 5,000 18.68 ± 3.95 15.33 15.93 16.79 18.05 20.22 21.39 22.69 27.38 

Pregnancy 22nd week 5,000 18.84 ± 4.08 15.30 15.93 16.80 18.07 20.23 21.52 23.20 30.80 

Pregnancy 36th week 5,000 19.60 ± 4.66 15.54 16.14 17.03 18.73 20.74 23.04 25.58 34.26 

Postpartum 6th week 5,000 21.19 ± 1.96 18.30 18.86 19.79 20.92 22.58 23.98 24.53 25.28 

Postpartum 27th week 5,000 21.01 ± 1.94 18.14 18.69 19.62 20.74 22.39 23.77 24.31 25.07 

a Underweight females are defined as those having a body mass index lower than 19.8 kg/m2 in pre-pregnancy. b	 NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females. 

Resulting total energy requirements (TDERs) from the integration of energetic measurements in underweight non-pregnant and non-lactating females with those during pregnancy and 

lactation by Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER × H × (VE/VO2) × 10-3. TDER = total energy 

requirement (ECG + TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy. 

SD = Standard deviation. 

Source:	 Brochu et al. (2006a).
 

 

 

Table 6-54. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/day) Percentiles for Free-Living Normal-Weighta Adolescents and Women Aged 11 to 55 Years 

During Pregnancy and Postpartum Weeks 

Age Group 

(years) 

Progression of the 

Reproductive Cycle 

Number of 

Subjectsb 

NExp or 

NSim 

Physiological Daily Inhalation Rates

c (m3

/day) 

Percentile 

Mean ± SD 5th 10th 25th 50th 75th 90th 95th 99th 

11 to <23 Non-pregnant females 57 14.55 ± 2.70 10.11 11.09 12.73 14.55 16.37 18.01 18.99 20.83 

Pre-pregnancy 0 week 5,000 14.55 ± 2.69 9.71 10.83 13.29 14.78 15.89 17.34 18.71 20.91 

Pregnancy 9th week 5,000 19.99 ± 3.89 13.32 14.84 18.32 20.26 21.86 23.86 25.89 28.75 

Pregnancy 22nd week 5,000 22.59 ± 4.83 15.35 17.09 20.06 22.27 24.69 28.25 30.75 35.88 

Pregnancy 36th week 5,000 23.27 ± 4.63 16.01 17.76 20.69 23.10 25.55 28.77 31.07 35.65 

Postpartum 6th week 5,000 23.28 ± 3.60 16.91 18.36 21.40 23.56 25.24 27.17 28.98 31.80 

Postpartum 27th week 5,000 23.08 ± 3.56 16.76 18.20 21.21 23.36 25.02 26.93 28.73 31.52 

23 to <30 Non-pregnant females 54 13.59 ± 2.23 9.92 10.73 12.09 13.59 15.09 16.45 17.26 18.78 

Pre-pregnancy 0 week 5,000 13.66 ± 2.29 10.19 10.64 12.12 13.73 14.90 16.49 17.87 19.09 

Pregnancy 9th week 5,000 19.00 ± 9.98 13.92 14.55 16.55 18.76 20.49 22.80 24.49 27.04 

Pregnancy 22nd week 5,000 21.36 ± 4.36 15.54 16.70 18.63 20.89 23.58 26.59 28.43 33.98 

Pregnancy 36th week 5,000 22.14 ± 4.13 16.21 17.34 19.35 21.69 24.55 27.59 29.27 32.77 

Postpartum 6th week 5,000 22.15 ± 30.5 17.37 18.26 20.11 22.11 23.96 26.21 27.53 29.21 

Postpartum 27th week 5,000 21.96 ± 3.02 17.22 18.10 19.93 21.91 23.75 25.98 27.29 28.96 

30 to 55 Non-pregnant females 61 13.82 ± 1.91 10.67 11.37 12.53 13.82 15.12 16.28 16.97 18.28 

Pre-pregnancy 0 week 5,000 13.79 ± 1.83 11.07 11.48 12.54 13.61 14.91 16.40 17.02 18.32 

Pregnancy 9th week 5,000 19.02 ± 3.81 15.18 15.74 17.14 18.63 20.46 22.45 23.38 27.39 

Pregnancy 22nd week 5,000 21.53 ± 4.06 16.71 17.56 19.01 20.85 23.45 26.03 28.30 33.44 

Pregnancy 36th week 5,000 22.20 ± 3.68 17.45 18.19 19.69 21.73 24.16 26.78 28.53 32.75 

Postpartum 6th week 5,000 22.31 ± 2.50 18.72 19.35 20.58 22.09 23.84 25.70 26.70 28.39 

Postpartum 27th week 5,000 22.12 ± 2.48 18.55 19.18 20.40 21.90 23.64 25.47 26.47 28.14 

a Normal-weight females are defined as those having a body mass index varying between 19.8 and 26 kg/m2 in pre-pregnancy. b NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females. c Resulting TDERs from the integration of energetic measurements in underweight non-pregnant and non-lactating females with those during pregnancy and lactation by Monte Carlo 

simulations were converted into physiological daily inhalation rates by the following equation: TDER × H × (VE/VO2) × 10-3 . TDER = total energy requirement (ECG + TDEE). 

ECG = stored daily energy cost for growth; TDEE = total daily energy. 

SD = Standard deviation. 

Source: Brochu et al. (2006a). 

Chapter 6—Exposure Factors Handbook 

Inhalation Rates 

Exposure Factors Handbook Page September 2011 6-85 
Chapter 6—

Exposure Factors Handbook 

Inhalation Rates 

Page Exposure Factors Handbook 6-86 September 2011 

 

 

 

 

 

 

Table 6-55. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/day) Percentiles for Free-Living Overweight/Obesea Adolescents and Women Aged 11 to 55 Years 

During Pregnancy and Postpartum Weeks 

Age Group 

(years) 

Progression of the 

Reproductive Cycle 

Number of 

Subjectsb 

NExp or 

NSim 

Physiological Daily Inhalation Ratesc (m3/day) 

Percentile 

Mean ± SD 5th 10th 25th 50th 75th 90th 95th 99th 

11 to <23 Non-pregnant females 15 16.62 ± 2.91 11.82 12.88 14.65 16.62 18.58 20.35 21.41 23.39 

Pre-pregnancy 0 week 5,000 16.64 ± 2.81 10.21 12.13 15.52 17.22 18.52 19.68 20.06 20.16 

Pregnancy 9th week 5,000 25.51 ± 6.48 16.11 19.09 23.04 25.38 27.85 30.62 33.32 41.61 

Pregnancy 22nd week 5,000 26.10 ± 6.96 16.38 19.29 23.12 25.65 28.17 31.56 34.93 45.94 

Pregnancy 36th week 5,000 25.71 ± 8.09 15.67 18.78 22.73 25.23 27.84 31.14 34.95 46.76 

Postpartum 6th week 5,000 25.93 ± 3.70 17.94 20.12 24.52 26.61 28.38 29.87 30.53 31.27 

Postpartum 27th week 5,000 25.71 ± 3.67 17.79 19.94 24.30 26.38 28.13 29.61 30.26 31.00 

23 to <30 Non-pregnant females 25 15.45 ± 2.32 11.63 12.47 13.88 15.45 17.02 18.43 19.27 20.86 

Pre-pregnancy 0 week 5,000 15.47 ± 2.27 11.94 13.12 14.36 15.50 16.86 17.96 19.46 20.41 

Pregnancy 9th week 5,000 23.93 ± 5.94 17.75 19.13 21.08 23.22 25.62 29.09 31.77 40.74 

Pregnancy 22nd week 5,000 24.44 ± 6.24 18.06 19.45 21.32 23.51 26.44 29.92 33.49 44.56 

Pregnancy 36th week 5,000 24.15 ± 6.82 17.60 19.00 20.91 23.05 26.02 30.04 34.18 47.31 

Postpartum 6th week 5,000 24.47 ± 3.04 19.31 21.07 22.80 24.45 26.16 27.93 29.43 31.08 

Postpartum 27th week 5,000 24.25 ± 3.02 19.14 20.88 22.60 24.23 25.93 27.68 29.17 30.81 

30 to 55 Non-pregnant females 64 15.87 ± 2.52 11.72 12.63 14.17 15.87 17.57 19.10 20.01 21.73 

Pre-pregnancy 0 week 5,000 15.83 ± 2.46 11.92 12.79 14.30 15.79 17.19 18.78 19.47 22.03 

Pregnancy 9th week 5,000 24.47 ± 5.68 17.87 19.17 21.38 23.77 26.37 29.77 33.08 41.49 

Pregnancy 22nd week 5,000 25.02 ± 6.65 18.13 19.41 21.44 23.92 26.93 30.98 35.01 46.88 

Pregnancy 36th week 5,000 24.46 ± 6.24 17.67 18.83 20.92 23.40 26.37 30.32 34.27 45.08 

Postpartum 6th week 5,000 24.91 ± 3.28 19.82 20.92 22.82 24.91 26.81 28.70 29.75 32.94 

Postpartum 27th week 5,000 24.70 ± 3.25 19.65 20.74 22.63 24.69 26.58 28.45 29.50 32.65 

a Overweight/obese females are defined as those having a body mass index higher than 26 kg/m2 in pre-pregnancy. b NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females. c Resulting TDERs from the integration of energetic measurements in underweight non-pregnant and non-lactating females with those during pregnancy and lactation by Monte Carlo 

simulations were converted into physiological daily inhalation rates by the following equation: TDER × H × (VE/VO2) × 10-3 . TDER = total energy requirement (ECG + TDEE). 

ECG = stored daily energy cost for growth; TDEE = total daily energy. 

SD = Standard deviation. 

Source: Brochu et al. (2006a). 
Chapter 6—

Exposure Factors Handbook 

Inhalation Rates 

Exposure Factors Handbook Page September 2011 6-87 

 

 

 

 

 

 

Table 6-56. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for Free-Living Underweighta Adolescents and Women Aged 11 to 55 Years 

During Pregnancy and Postpartum Weeks 

Age Group 

(years) 

Progression of the 

Reproductive Cycle 

Number of 

Subjectsb 

NExp or 

NSim 

Physiological Daily Inhalation Ratesc (m3/kg-day) 

Percentile 

Mean ± SD 5th 10th 25th 50th 75th 90th 95th 99th 

11 to <23 Non-pregnant females 50 0.277 ± 0.046 0.201 0.218 0.246 0.277 0.277 0.335 0.352 0.383 

Pre-pregnancy 0 week 5,000 0.276 ± 0.045 0.209 0.218 0.238 0.277 0.313 0.337 0.345 0.368 

Pregnancy 9th week 5,000 0.385 ± 0.110 0.278 0.291 0.327 0.377 0.428 0.474 0.504 0.622 

Pregnancy 22nd week 5,000 0.343 ± 0.093 0.246 0.259 0.291 0.335 0.378 0.419 0.455 0.602 

Pregnancy 36th week 5,000 0.323 ± 0.083 0.230 0.243 0.274 0.314 0.357 0.404 0.452 0.575 

Postpartum 6th week 5,000 0.368 ± 0.058 0.321 0.337 0.370 0.414 0.467 0.517 0.548 0.596 

Postpartum 27th week 5,000 0.383 ± 0.064 0.329 0.348 0.383 0.433 0.491 0.549 0.584 0.647 

23 to <30 Non-pregnant females 17 0.264 ± 0.047 0.186 0.203 0.232 0.264 0.264 0.325 0.342 0.374 

Pre-pregnancy 0 week 5,000 0.264 ± 0.046 0.206 0.212 0.228 0.257 0.284 0.342 0.361 0.362 

Pregnancy 9th week 5,000 0.366 ± 0.098 0.277 0.287 0.311 0.351 0.400 0.468 0.501 0.591 

Pregnancy 22nd week 5,000 0.332 ± 0.076 0.250 0.260 0.282 0.318 0.362 0.421 0.452 0.532 

Pregnancy 36th week 5,000 0.317 ± 0.086 0.233 0.242 0.266 0.301 0.346 0.402 0.439 0.582 

Postpartum 6th week 5,000 0.352 ± 0.056 0.307 0.320 0.348 0.385 0.431 0.486 0.518 0.573 

Postpartum 27th week 5,000 0.364 ± 0.061 0.316 0.330 0.357 0.397 0.449 0.508 0.545 0.606 

30 to 55 Non-pregnant females 14 0.249 ± 0.027 0.204 0.214 0.231 0.249 0.249 0.283 0.293 0.312 

Pre-pregnancy 0 week 5,000 0.249 ± 0.026 0.208 0.220 0.232 0.242 0.268 0.286 0.294 0.299 

Pregnancy 9th week 5,000 0.347 ± 0.075 0.279 0.291 0.311 0.337 0.370 0.405 0.431 0.529 

Pregnancy 22nd week 5,000 0.315 ± 0.071 0.252 0.262 0.280 0.305 0.335 0.368 0.401 0.529 

Pregnancy 36th week 5,000 0.301 ± 0.074 0.233 0.243 0.260 0.287 0.321 0.360 0.404 0.529 

Postpartum 6th week 5,000 0.337 ± 0.038 0.312 0.326 0.347 0.376 0.408 0.439 0.457 0.489 

Postpartum 27th week 5,000 0.349 ± 0.042 0.320 0.333 0.357 0.389 0.425 0.462 0.483 0.518 

a Underweight females are defined as those having a body mass index lower than 19.8 kg/m2 in pre-pregnancy. b NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females. c Resulting TDERs from the integration of energetic and weight measurements in normal-weight non-pregnant and non-lactating females with those during pregnancy and lactation by 

Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER × H × (VE/VC > 2) × 10-3 . TDER = total energy requirement 

(ECG + TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy expenditure. 

SD = Standard deviation. 

Source: Brochu et al. (2006a). 
Chapter 6—

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Inhalation Rates 

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Table 6-57. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for Free-Living Normal-Weight

a and Women Aged 11 to 55 Years 

During Pregnancy and Postpartum Weeks 

Age Group 

(years) 

Progression of the 

Reproductive Cycle 

Number of 

Subjectsb 

NExp or 

NSim 

Physiological Daily Inhalation Rates

c (m3

/kg-day) 

Percentile 

Mean ± SD 5th 10th 25th 50th 75th 90th 95th 99th 

11 to <23 Non-pregnant females 15 0.252 ± 0.051 0.168 0.186 0.217 0.252 0.286 0.317 0.336 0.370 

Pre-pregnancy 0 week 5,000 0.252 ± 0.051 0.169 0.189 0.218 0.246 0.282 0.324 0.339 0.361 

Pregnancy 9th week 5,000 0.344 ± 0.074 0.232 0.259 0.297 0.336 0.388 0.440 0.468 0.518 

Pregnancy 22nd week 5,000 0.360 ± 0.085 0.243 0.268 0.304 0.349 0.406 0.462 0.500 0.594 

Pregnancy 36th week 5,000 0.329 ± 0.072 0.225 0.247 0.281 0.323 0.372 0.422 0.453 0.517 

Postpartum 6th week 5,000 0.342 ± 0.062 0.272 0.292 0.327 0.369 0.418 0.469 0.499 0.544 

Postpartum 27th week 5,000 0.352 ± 0.067 0.279 0.298 0.334 0.380 0.433 0.490 0.527 0.580 

23 to <30 Non-pregnant females 54 0.221 ± 0.035 0.164 0.176 0.197 0.221 0.244 0.265 0.278 0.301 

Pre-pregnancy 0 week 5,000 0.222 ± 0.035 0.174 0.181 0.199 0.218 0.242 0.269 0.285 0.317 

Pregnancy 9th week 5,000 0.308 ± 0.189 0.233 0.243 0.269 0.298 0.333 0.371 0.395 0.458 

Pregnancy 22nd week 5,000 0.321 ± 0.067 0.239 0.252 0.277 0.310 0.351 0.399 0.433 0.521 

Pregnancy 36th week 5,000 0.297 ± 0.056 0.220 0.233 0.258 0.289 0.328 0.369 0.399 0.448 

Postpartum 6th week 5,000 0.309 ± 0.045 0.265 0.278 0.302 0.333 0.368 0.402 0.425 0.464 

Postpartum 27th week 5,000 0.317 ± 0.049 0.269 0.283 0.309 0.342 0.380 0.416 0.441 0.490 

30 to 55 Non-pregnant females 61 0.229 ± 0.035 0.171 0.184 0.206 0.229 0.253 0.274 0.287 0.311 

Pre-pregnancy 0 week 5,000 0.229 ± 0.035 0.174 0.187 0.202 0.229 0.253 0.275 0.287 0.302 

Pregnancy 9th week 5,000 0.314 ± 0.069 0.237 0.252 0.276 0.309 0.346 0.382 0.400 0.443 

Pregnancy 22nd week 5,000 0.330 ± 0.069 0.242 0.257 0.285 0.321 0.365 0.409 0.439 0.522 

Pregnancy 36th week 5,000 0.303 ± 0.057 0.225 0.238 0.264 0.297 0.336 0.373 0.401 0.461 

Postpartum 6th week 5,000 0.316 ± 0.046 0.267 0.280 0.307 0.343 0.382 0.416 0.434 0.467 

Postpartum 27th week 5,000 0.325 ± 0.050 0.272 0.285 0.314 0.352 0.394 0.432 0.453 0.491 

a Normal-weight females are defined as those having a body mass index varying between 19.8 and 26 kg/m2 in pre-pregnancy. b NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females. c Resulting TDERs from the integration of energetic and weight measurements in normal-weight non-pregnant and non-lactating females with those during pregnancy and lactation by 

Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER × H × (VE/VC > 2) × 10-3 

. TDER = total energy requirement (ECG 

+ TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy expenditure. 

SD = Standard deviation. 

Source: Brochu et al. (2006a). 
Chapter 6—

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Inhalation Rates 

Exposure Factors Handbook Page September 2011 6-89 

 

 

 

Table 6-58. Distribution of Physiological Daily Inhalation Rate (PDIR) (m3/kg-day) Percentiles for Free-Living Overweight/Obesea Adolescents and Women Aged 11 to 55 Years 

During Pregnancy and Postpartum Weeks 

Age Group 

(years) 

Progression of the 

Reproductive Cycle 

Number of 

Subjectsb 

NExp or 

NSim 

Physiological Daily Inhalation Rates

c (m3

/kg-day) 

Percentile 

Mean ± SD 5th 10th 25th 50th 75th 90th 95th 99th 

11 to <23 Non-pregnant females 15 0.206 ± 0.033 0.151 0.163 0.184 0.206 0.229 0.249 0.261 0.284 

Pre-pregnancy 0 week 5,000 0.207 ± 0.032 0.146 0.153 0.188 0.214 0.227 0.240 0.253 0.259 

Pregnancy 9th week 5,000 0.302 ± 0.075 0.205 0.223 0.263 0.298 0.329 0.368 0.401 0.515 

Pregnancy 22nd week 5,000 0.287 ± 0.079 0.191 0.206 0.246 0.279 0.314 0.357 0.391 0.512 

Pregnancy 36th week 5,000 0.270 ± 0.090 0.179 0.193 0.225 0.259 0.296 0.337 0.377 0.521 

Postpartum 6th week 5,000 0.280 ± 0.050 0.213 0.230 0.266 0.301 0.337 0.372 0.395 0.444 

Postpartum 27th week 5,000 0.285 ± 0.053 0.214 0.233 0.269 0.307 0.344 0.381 0.409 0.464 

23 to <30 Non-pregnant females 54 0.186 ± 0.025 0.144 0.153 0.169 0.186 0.203 0.218 0.227 0.244 

Pre-pregnancy 0 week 5,000 0.186 ± 0.025 0.143 0.155 0.172 0.183 0.201 0.222 0.233 0.236 

Pregnancy 9th week 5,000 0.274 ± 0.068 0.203 0.217 0.238 0.263 0.298 0.337 0.374 0.476 

Pregnancy 22nd week 5,000 0.261 ± 0.069 0.193 0.205 0.224 0.248 0.283 0.323 0.360 0.466 

Pregnancy 36th week 5,000 0.245 ± 0.074 0.175 0.185 0.205 0.231 0.268 0.314 0.360 0.498 

Postpartum 6th week 5,000 0.256 ± 0.042 0.205 0.217 0.241 0.271 0.304 0.338 0.360 0.406 

Postpartum 27th week 5,000 0.260 ± 0.046 0.209 0.222 0.246 0.277 0.311 0.349 0.372 0.426 

30 to 55 Non-pregnant females 61 0.184 ± 0.031 0.132 0.144 0.163 0.184 0.205 0.224 0.235 0.257 

Pre-pregnancy 0 week 5,000 0.184 ± 0.031 0.127 0.141 0.166 0.185 0.205 0.221 0.226 0.246 

Pregnancy 9th week 5,000 0.272 ± 0.068 0.184 0.203 0.234 0.263 0.299 0.343 0.378 0.465 

Pregnancy 22nd week 5,000 0.259 ± 0.071 0.176 0.194 0.222 0.249 0.282 0.322 0.363 0.490 

Pregnancy 36th week 5,000 0.242 ± 0.068 0.162 0.177 0.201 0.230 0.265 0.313 0.351 0.455 

Postpartum 6th week 5,000 0.253 ± 0.048 0.188 0.205 0.237 0.270 0.305 0.340 0.364 0.404 

Postpartum 27th week 5,000 0.257 ± 0.051 0.191 0.208 0.239 0.273 0.310 0.348 0.374 0.430 

a Overweight/obese females are defined as those having a body mass index higher than 26 kg/m2 in pre-pregnancy. b NExp = number of experimental non-pregnant and non-lactating females; NSim = number of simulated females. c Resulting TDERs from the integration of energetic and weight measurements in normal-weight non-pregnant and non-lactating females with those during pregnancy and lactation by 

Monte Carlo simulations were converted into physiological daily inhalation rates by the following equation: TDER × H × (VE/VC > 2) × 10-3 . TDER = total energy requirement (ECG 

+ TDEE). ECG = stored daily energy cost for growth; TDEE = total daily energy expenditure. 

SD = Standard deviation. 

Source: Brochu et al. (2006a). 
 

Exposure Factors Handbook 

Chapter 6—Inhalation Rates
 

Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Awake Subjects. 

RR = respiratory rate.
 

Source: Rusconi et al. (1994).
 

Figure 6-2. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Asleep Subjects. 

RR = respiratory rate. 

Source: Rusconi et al. (1994). 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

7. DERMAL EXPOSURE FACTORS 

7.1. INTRODUCTION 

Dermal exposure can occur during a variety of 

activities in different environmental media and 

microenvironments [U.S. Environmental Protection 

Agency (U.S. EPA), (2004, 1992a, b)]. These 

include: 

 water (e.g., bathing, washing, swimming); 

 soil (e.g., outdoor recreation, gardening, 

construction); 

 sediment (e.g., wading, fishing); 

 other liquids (e.g., use of commercial 

products); 

 vapors/fumes/gases (e.g., use of commercial 

products); and 

 other solids or residues (e.g., soil/dust or 

chemical residues on carpets, floors, counter 

tops, outdoor surfaces, or clothing). 

Exposure via the dermal route may be estimated 

in various ways, depending on the exposure media 

and scenario of interest. For example, dermal 

exposure to contaminants in soil, sediment, or dust 

may be evaluated using information on the 

concentration of contaminant in these materials in 

conjunction with information on the amount of 

material that adheres to the skin per unit surface area 

and the total area of skin surface exposed. An 

approach for estimating dermal exposure to 

contaminants in liquids uses information on the 

concentration of contaminant in the liquid in 

conjunction with information on the film thickness of 

liquid remaining on the skin after contact. When 

assessing dermal exposure to water (e.g., bathing or 

swimming) or to vapors and fumes, the concentration 

of chemical in water or vapor with the total exposed 

skin surface area may be considered. An approach for 

estimating exposure to surface residues is to use 

information on the rate of transfer of chemical 

residues to the skin as a result of contact with the 

surfaces. Dermal exposure also may result from 

leaching of chemicals that are impregnated in 

materials that come into contact with skin. For 

example, Snodgrass (1992) evaluated transfer of 

pesticides from treated clothing onto the skin. For 

information on various methods used to estimate 

dermal exposure, refer to Guidelines for Exposure 

Assessment (U.S. EPA, 1992b), Dermal Exposure 

Assessment: Principles and Applications (U.S. EPA, 

1992a), and Dermal Exposures Assessment: A 

Summary of EPA Approaches (U.S. EPA, 2007a). 

Additional scenario-specific information on dermal 

exposure assessment is available in Risk Assessment 

Guidance for Superfund (RAGS) Part E (U.S. EPA, 

2004), Standard Operating Procedures for 

Residential Pesticide Exposure Assessment, draft 

(U.S. EPA, 2009), and Methods for Assessing 

Exposure to Chemical Substances: Volume 7, 

Methods for Assessing Consumer Exposure to 

Chemical Substances (U.S. EPA, 1987). In general, 

these methods for estimating dermal exposure require 

information on the surface area of the skin that is 

exposed. Some methods also require information on 

the adherence of solids to the skin or information on 

the film thickness of liquids on the skin. Others 

utilize information on the transfer of residues from 

contaminated surfaces to the skin surface and/or rate 

of contact with objects or surfaces. This chapter 

focuses on measurements of body surface area and 

non-chemical-specific factors related to dermal 

exposure (i.e., the deposition of contaminants onto 

the skin), such as adherence of solids to the skin, film 

thickness of liquids on the skin, and residue transfer 

from contaminated surfaces to the skin. However, this 

chapter only provides recommendations for surface 

area and solids adherence to skin. According to Riley 

et al. (2004), numerous factors may affect loading 

and retention of chemicals on the skin, including the 

form of the contaminant (particle, liquid, residue), 

surface characteristics (hard, plush, porous, surface 

loading, previous transfers), skin characteristics 

(moisture, age, loading), contact mechanics (pressure, 

duration, repetition), and environmental conditions 

(temperature, relative humidity, air exchange). These 

factors are discussed in this chapter, as reported by 

the various study authors. Information on other 

factors that may affect dermal exposure (e.g., contact 

frequency and duration, and skin thickness) also is 

provided in this chapter. 

Factors that influence dermal uptake (i.e., 

absorption) and internal dose, including 

chemical-specific factors, are not provided in this 

handbook. These include factors such as the 

concentration of chemical in contact with the skin, 

weight fraction of chemicals in consumer products, 

and characteristics of the chemical (i.e., lipophilicity, 

polarity, volatility, solubility). Also, factors affecting 

the rate of absorption of the chemical through the 

skin at the site of application and the amount of 

chemical delivered to the target organ are not covered 

in this chapter. Absorption may be affected by the age 

and condition of the skin, including presence of 

perspiration (Williams et al., 2005; Williams et al., 

2004). Also, the thickness of the stratum corneum 

(outer layer of the skin) varies over parts of the body 

and may affect absorption. While not the primary 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

focus of this chapter, some limited information on 

skin thickness is presented in Section 7.7―Other 

Factors. For guidance on how to use information on 

factors needed to assess dermal dose, refer to Dermal 

Exposure Assessment: Principles and Applications 

(U.S. EPA, 1992a) and Risk Assessment Guidelines 

for Superfund (RAGs) Part E (U.S. EPA, 2004). 

Frequency and duration of contact also may affect 

dermal exposure and dose. Data on dermal contact 

frequency and duration of hand contact with objects 

and surfaces are presented in Section 7.7.1 of this 

chapter. Additional information on consumer 

products use and activity factors that may affect 

dermal exposure is presented in Chapters 16 and 17. 

Section 7.3 of this chapter provides data on 

surface area of the human skin. Section 7.4 provides 

data on adherence of solids to human skin. 

Information on the film thickness of liquids on the 

skin is limited. However, studies that estimated film 

thickness of liquids on the skin are presented in 

Section 7.5. Section 7.6 presents available 

information on the transfer of residues from 

contaminated surfaces to the skin. Section 7.7 

provides information on other factors affecting 

dermal exposure (e.g., frequency and duration of 

dermal contact with objects and surfaces, and skin 

thickness). 

Recommendations for skin surface area and 

dermal adherence of solids to skin are provided in the 

next section, along with a summary of the confidence 

ratings for these recommendations. The 

recommended values are based on key studies 

identified by U.S. EPA for these factors. Relevant 

data on these and other factors also are presented in 

this chapter to provide added perspective on the 

state-of-knowledge pertaining to dermal exposure 

factors. 

7.2. RECOMMENDATIONS 

7.2.1. Body Surface Area 

Table 7-1 summarizes the recommended mean 

and 95th percentile total body surface area values. For 

children under 21 years of age, the recommendations 

for total body surface area are based on the U.S. EPA 

analysis of 1999–2006 data from the National Health 

and Nutrition Examination Survey (NHANES). 

These data are presented for the standard age 

groupings recommended by U.S. EPA (2005) for 

male and female children combined. For adults 

21 years and over, the recommendations for total 

body surface area are based on the U.S. EPA analysis 

of NHANES (2005–2006) data. The U.S. EPA 

analysis of NHANES data uses correlations with 

body weight and height for deriving skin surface area 

(see Section 7.3.1.3 and Appendix 7A). NHANES 

(1999–2006) used a statistically based survey design 

that should ensure that the data are reasonably 

representative of the general population for each 

2-year interval (e.g., 1999 to 2000, 2001 to 2002). 

Multiple NHANES study years, supplying a larger 

sample size, were necessary for estimating surface 

area for children given the multiple stratifications by 

age. The advantage of using the NHANES data sets 

to derive the total surface area recommendations is 

that data are nationally representative and remain the 

principal source of body-weight and height data 

collected nationwide from a large number of subjects. 

Note that differences between the surface area 

recommendations presented here and those in the 

previous Exposure Factors Handbook (U.S. EPA, 

1997) reflect changes in the body weights used in 

calculating these surface areas. If sex-specific data 

for children, sex-combined data for adults, or data for 

statistics other than the mean or 95th percentile are 

needed, refer to Table 7-9 through Table 7-13 of this 

chapter. 

Table 7-2 presents the recommendations for the 

percentage of total body surface area represented by 

individual body parts for children based on data from 

U.S. EPA (1985) and Boniol et al. (2008) (see 

Section 7.3.1). The data from Boniol et al. (2008) are 

used for the recommendations for children greater 

than 2 years of age because they are based on a larger 

sample size than those in U.S. EPA (1985) for the 

same age groups. Because the Boniol et al. (2008) 

study does not include data for children less than 

2 years of age, recommendations for this age group 

are based on the data from U.S. EPA (1985). It should 

be noted, however, that the sample size for the 

percentages of the total body represented by various 

body parts in this age group is very small. Table 7-2 

also provides age-specific body part surface areas 

(m2

) for children. These values were obtained by 

multiplying the age-specific mean body part 

percentages (for males and females combined) by the 

total body surface areas presented in Table 7-1. If 

sex-specific data are needed for children equal to or 

greater than 2 years of age, or if data for additional 

body parts not summarized in Table 7-2 are needed, 

refer to Table 7-8. The body part data in this table 

may be applied to data in Table 7-9 through 

Table 7-11 to calculate surface area for the various 

body parts. 

The recommendations for surface area of adult 

body parts are based on the U.S. EPA Analysis of 

NHANES 2005–2006 data and algorithms from 

U.S. EPA (1985). The U.S. EPA Analysis of the 

NHANES data was used to develop 

recommendations for body parts because the data are 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

nationally representative and based on a large number 

of subjects. Table 7-2 presents the data for adult 

males and adult females (21+ years of age). If sexcombined data for adults or data for statistics other 

than the mean and 95th percentile are needed, refer to 

Table 7-12 and Table 7-13. These tables present the 

surface area of body parts for males and females, 

respectively, 21 years of age and older. Table 7-3 

presents the confidence ratings for the 

recommendations for body surface area. 

For swimming and bathing scenarios, past 

exposure assessments have assumed that 75 to 

100% of the skin surface is exposed (U.S. EPA, 

1992a). More recent guidance recommends assuming 

100% exposure for these scenarios (U.S. EPA, 2004). 

For other exposure scenarios, it is reasonable to 

assume that clothing reduces the contact area. 

However, while it is generally assumed that 

adherence of solids to skin only occurs to the areas of 

the body not covered by clothing, it is important to 

understand that soil and dust particles can get under 

clothing and be deposited on skin to varying degrees 

depending on the protective properties of the 

clothing. Likewise, liquids or chemical residues on 

surfaces may soak through clothing and contact 

covered areas of the skin. Assessors should consider 

these possibilities for the scenario of concern and 

select skin areas that are judged appropriate. Also, 

surface area of the body and body weight are highly 

correlated (Phillips et al., 1993). The relationship 

between these factors, therefore, should be 

considered when selecting body weights for use with 

the surface area data for estimating dermal exposure. 

7.2.2. Adherence of Solids to Skin 

The adherence factor (AF) describes the amount 

of solid material that adheres to the skin per unit of 

surface area. Although most research in this area has 

focused on soils, a variety of other solid residues can 

accumulate on skin, including household dust, 

sediments, and commercial powders. Studies on soil 

adherence have shown that (1) soil properties 

influence adherence, (2) soil adherence varies 

considerably across different parts of the body, and 

(3) soil adherence varies with activity (U.S. EPA, 

2004). It is recommended that exposure assessors use 

adherence data derived from testing that matches the 

exposure scenario of concern in terms of solid type, 

exposed body parts, and activities as closely as 

possible. Refer to the activities described in Table 

7-19 to select those that best represent the exposure 

scenarios of concern and use the corresponding 

adherence values from Table 7-20. Table 7-19 also 

lists the age ranges covered by each study. This may 

be used as a general guide to the ages covered by 

these data. 

Table 7-4 summarizes recommended mean AF 

values according to common activities. The key 

studies used to develop the recommendations for 

adherence of solids to skin are those based on field 

studies in which specific activities relevant to dermal 

exposure were evaluated (compared to relevant 

studies that evaluated adherence in controlled 

laboratory trials using sieved or standardized soil). 

Insufficient data were available to develop activityspecific distributions or probability functions for 

these studies. Also, the small number of subjects in 

these studies prevented the development of 

recommendations for the childhood specific age 

groups recommended by U.S. EPA (2005). 

U.S. EPA (2004) recommends that 

scenario-specific adherence values be weighted 

according to the body parts exposed. Weighted 

adherence factors may be estimated according to the 

following equation: 

AFwtd = (AF1)(SA1) + (AF2)(SA2) + . . . . (AFi)(SAi) 

SA1 + SA2 + . . . SAi 

(Eqn. 7-1) 

where: 

AFwtd = weighted adherence factor, 

AF = adherence factor, and 

SA = surface area. 

For the purposes of this calculation, the surface 

area of the face may be assumed to be 1/3 that of the 

head, forearms may be assumed to represent 45% of 

the arms, and lower legs may be assumed to represent 

40% of the legs (U.S. EPA, 2004). 

The recommended dermal AFs represent the 

amount of material on the skin at the time of 

measurement. U.S. EPA (1992a) recommends 

interpreting AFs as representative of contact events. 

Assuming that the amount of solids measured on the 

skin represents accumulation between washings, and 

that people wash at least once per day, these 

adherence values can be interpreted as daily contact 

rates (U.S. EPA, 1992a). The rate of solids 

accumulation on skin over time has not been well 

studied but probably occurs fairly quickly. Therefore, 

prorating the adherence values for exposure time 

periods of less than 1 day is not recommended. 

Table 7-5 shows the confidence ratings for these 

AF recommendations. While the recommendations 

are based on the best available estimates of activityExposure Factors Handbook Page 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

specific adherence, they are based on limited data 

from studies that have focused primarily on soil. 

Therefore, they have a high degree of uncertainty, 

and considerable judgment must be used when 

selecting them for an assessment. It also should be 

noted that the skin-adherence studies on which these 

recommendations are based have generally not 

considered the influence of skin moisture on 

adherence. Skin moisture varies depending on a 

number of factors, including activity level and 

ambient temperature/humidity. It is uncertain how 

well this variability has been captured in the dermaladherence studies used for the recommendations. 

7.2.3. Film Thickness of Liquids on Skin 

The film thickness of liquids on skin represents 

the amount of material that remains on the skin after 

contact with a liquid (e.g., consumer product such as 

cleaning solution or soap). The data on film thickness 

of liquids on the hand are limited, and recommended 

values are not provided in this chapter. Refer to 

Section 7.5 for a description of the available data that 

may be used to assess dermal contact with liquid 

using the film thickness approach. 

7.2.4. Residue Transfer 

Several studies have developed methods for 

quantifying the rates of transfer of chemical residues 

to the skin of individuals performing activities on 

contaminated surfaces. These studies have been 

conducted primarily for the purpose of estimating 

exposure to pesticides. Section 7.6 describes studies 

that have estimated residue transfer to human skin. 

Because use of residue transfer depends on the 

specific conditions under which exposure occurs 

(e.g., activity, contact surfaces, age), general 

recommendations are not provided. Instead, refer to 

Section 7.6 for a description of the available data 

from which appropriate values may be selected. 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-1. Recommended Values for Total Body Surface Area, 

for Children (sexes combined) and Adults by Sex 

Age Group 

Mean 95th Percentile Multiple 

m Percentiles Source 2 

Male and Female Children Combined 

Birth to <1 month 0.29 0.34 

See Table 7-9, 

Table 7-10, 

and Table 7-11 

(for sexspecific 

data) 

U.S. EPA Analysis of 

NHANES 1999−2006 data 

1 to <3 months 0.33 0.38 

3 to <6 months 0.38 0.44 

6 to <12 months 0.45 0.51 

1 to <2 years 0.53 0.61 

2 to <3 years 0.61 0.70 

3 to <6 years 0.76 0.95 

6 to <11 years 1.08 1.48 

11 to <16 years 1.59 2.06 

16 to <21 years 1.84 2.33 

Adult Male 

See Table 7-9 

(for sexcombined data) 

and Table 7-10 

U.S. EPA Analysis of 

NHANES 2005−2006 data 

21 to 30 years 2.05 2.52 

30 to <40 years 2.10 2.50 

40 to <50 years 2.15 2.56 

50 to <60 years 2.11 2.55 

60 to <70 years 2.08 2.46 

70 to <80 years 2.05 2.45 

80 years and over 1.92 2.22 

Adult Female 

See Table 

7-9(for sexcombined data) 

and Table 7-11 

U.S. EPA Analysis of 

NHANES 2005−2006 data 

21 to 30 years 1.81 2.25 

30 to <40 years 1.85 2.31 

40 to <50 years 1.88 2.36 

50 to <60 years 1.89 2.38 

60 to <70 years 1.88 2.34 

70 to <80 years 1.77 2.13 

80 years and over 1.69 1.98 

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Chapter 7—Dermal Exposure Factors 

Table 7-2. Recommended Values for Surface Area of Body Parts 

Age Group Head 

Trunk a Armsb Hands Legsc Feet 

Mean Percent of Total Surface Area 

Source 

Male and Female Children Combined 

Birth to <1 d 18.2 35.7 13.7 5.3 20.6 6.5 

1 to <3 monthsd 18.2 35.7 13.7 5.3 20.6 6.5 

3 to <6 monthsd 18.2 35.7 13.7 5.3 20.6 6.5 

6 to <12 monthsd 18.2 35.7 13.7 5.3 20.6 6.5 

1 to <2 yearsd 16.5 35.5 13.0 5.7 23.1 6.3 

U.S. EPA (1985) 

2 to <3 yearse 8.4 41.0 14.4 4.7 25.3 6.3 

3 to <6 yearsf 8.0 41.2 14.0 4.9 25.7 6.4 

6 to <11 yearsg 6.1 39.6 14.0 4.7 28.8 6.8 

11 to <16 yearsh 4.6 39.6 14.3 4.5 30.4 6.6 

16 to <21 yearsi 4.1 41.2 14.6 4.5 29.5 6.1 

Boniol et al. 

(2008) (average of 

data for males and 

females) 

Adult Male 

21+ years 6.6 40.1 15.2 5.2 33.1 6.7 

Adult Female 

21+ years 6.2 35.4 12.8 4.8 32.3 6.6 

U.S. EPA Analysis 

of NHANES 

2005−2006 data 

and U.S. EPA 

(1985) 

Mean Surface Area by Body Partj 

m2 

Male and Female Children Combined 

Birth to <1 

monthd 

0.053 0.104 0.040 0.015 0.060 0.019 

1 to <3 monthsd 0.060 0.118 0.045 0.017 0.068 0.021 

3 to <6 monthsd 0.069 0.136 0.052 0.020 0.078 0.025 

6 to <12 monthsd 0.082 0.161 0.062 0.024 0.093 0.029 

1 to <2 yearsd 0.087 0.188 0.069 0.030 0.122 0.033 

U.S. EPA Analysis 

of NHANES 

1999−2006 data 

and U.S. EPA 

(1985) 

2 to <3 yearse 0.051 0.250 0.088 0.028 0.154 0.038 

3 to <6 yearsf 0.061 0.313 0.106 0.037 0.195 0.049 

6 to <11 yearsg 0.066 0.428 0.151 0.051 0.311 0.073 

11 to <16 yearsh 0.073 0.630 0.227 0.072 0.483 0.105 

16 to <21 yearsi 0.075 0.759 0.269 0.083 0.543 0.112 

U.S. EPA Analysis 

of NHANES 

1999−2006 data 

and Boniol et al. 

(2008) 

Adult Male 

21+ years 0.136 0.827 0.314 0.107 0.682 0.137 

Adult Female 

21+ years 0.114 0.654 0.237 0.089 0.598 0.122 

U.S. EPA Analysis 

of NHANES 

2005−2006 data 

and U.S. EPA 

(1985) 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-2. Recommended Values for Surface Area of Body Parts (continued) 

Age Group 

Head Trunka Armsb Hands Legsc Feet 

95 Source th Percentile Surface Area by Body Partk 

m2 

Male and Female Children Combined 

Birth to <1 

monthd 

0.062 0.121 0.047 0.018 0.070 0.022 

U.S. EPA Analysis 

of NHANES 

1999−2006 data 

and U.S. EPA 

(1985) 

1 to <3 monthsd 0.069 0.136 0.052 0.020 0.078 0.025 

3 to <6 monthsd 0.080 0.157 0.060 0.023 0.091 0.029 

6 to <12 monthsd 0.093 0.182 0.070 0.027 0.105 0.033 

1 to <2 yearsd 0.101 0.217 0.079 0.035 0.141 0.038 

2 to <3 yearse 0.059 0.287 0.101 0.033 0.177 0.044 U.S. EPA Analysis 

of NHANES 

1999−2006 data 

and Boniol et al. 

(2008) 

3 to <6 yearsf 0.076 0.391 0.133 0.046 0.244 0.061 

6 to <11 yearsg 0.090 0.586 0.207 0.070 0.426 0.100 

11 to <16 yearsh 0.095 0.816 0.295 0.093 0.626 0.136 

16 to <21 yearsi 0.096 0.960 0.340 0.105 0.687 0.142 

Adult Male U.S. EPA Analysis 

of NHANES 

2005−2006 data 

and U.S. EPA 

(1985) 

21+ years 0.154 1.10 0.399 0.131 0.847 0.161 

Adult Female 

21+ years 

0.121 0.850 0.266 0.106 0.764 0.146 

a For children, ages 2 to <21 years, data from Boniol et al. (2008) for the neck, bosom, shoulders, 

abdomen, back, genitals, and buttocks were combined to represent the trunk. b For children, ages 2 to <21 years, data from Boniol et al. (2008) for the upper and lower arms 

were combined to represent the arms. c For children, ages 2 to <21 years, data from Boniol et al. (2008) for the thigh and legs were 

combined to represent the legs. d Percentages based on a small number of observations for this age group. e Based on data for 2 year olds from Boniol et al. (2008). f Based on data for 4 year olds from Boniol et al. (2008). g Based on average of data for 6, 8, and 10 year olds from Boniol et al. (2008). h Based on average of data for 12 and 14 year olds from Boniol et al. (2008). i Based on average of data for 16 and 18 year olds from Boniol et al. (2008). 

j Children’s values calculated as mean percentage of body part times mean total body surface area. k Children’s values calculated as mean percentage of body part times 95th percentile total body 

surface area. 

Note: Surface area values reported in m2 can be converted to cm2 by multiplying by 10,000 cm2/m2 . 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-3. Confidence in Recommendations for Body Surface Area 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

Total surface area estimates were based on algorithms 

developed using direct measurements and data from NHANES 

surveys. The methods used for developing these algorithms 

were adequate. The NHANES data and the secondary data 

analyses to estimate total surface areas were appropriate. 

NHANES included large sample sizes; sample size varied with 

age. Body-part percentages for children <2 years of age were 

based on direct measurements from a very small number of 

subjects (N = 4). Percentages for children >2 years were based 

on 2,050 children; adult values were based on 89 adults. 

The data used to develop the algorithms for estimating surface 

area from height and weight data were limited. NHANES 

collected physical measurements of weight and height for a 

large sample of the population. 

Medium 

Applicability and Utility 

Exposure Factor of 

Interest 

Representativeness 

Currency 

Data Collection Period 

The key studies were directly relevant to surface area estimates. 

The direct measurement data used to develop the algorithms for 

estimating total body surface area from weight and height may 

not be representative of the U.S. population. However, 

NHANES height and weight data were collected using a 

complex, stratified, multi-stage probability cluster sampling 

design intended to be representative of the U.S. population. 

Body part percentages for children <2 years of age were based 

on direct measurements from a very small number of subjects 

(N = 4). Percentages for children >2 years were based on 

2,050 children from various states in the United States and are 

assumed to be representative of U.S. children; adult values 

were based on 89 adults. 

The U.S. EPA analysis used the most current NHANES data to 

generate surface area data using algorithms based on older 

direct measurements. The data on body part percentages were 

dated. However, the age of the percentage data is not expected 

to affect its utility if the percentages are applied to total surface 

area data that has been updated based on the most recent 

NHANES body-weight and height data. 

The U.S. EPA analysis was based on four NHANES data sets 

covering 1999−2006 for children and one NHANES data set, 

2005−2006, for adults. 

Medium 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-3. Confidence in Recommendations for Body Surface Area (continued) 

General Assessment Factors Rationale Rating 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The U.S. EPA analysis of the NHANES data is 

unpublished, but used the same methodology as that 

described in the 1997 Exposure Factors Handbook 

(U.S. EPA, 1997). U.S. EPA (1985) is a U.S. EPApublished report. Boniol et al. (2008) is a published 

paper. 

The methodology was clearly presented; enough 

information was included to reproduce the results. 

Quality assurance of NHANES data was good; 

quality control of secondary data analysis was not 

well described. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

The full distributions were given for total surface 

area. 

A source of uncertainty in total surface areas resulted 

from the limitations in data used to develop the 

algorithms for estimating total surface from height 

and weight. Because of the small sample size for 

some ages, there is uncertainty in the body part 

percentage estimates for these age groups. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of 

Studies 

The NHANES surveys received a high level of peer 

review. The U.S. EPA analysis was not published in a 

peer-reviewed journal, but used the same 

methodology as that described in the 1997 Exposure 

Factors Handbook (U.S. EPA, 1997). 

There is one key study for total surface area and 

two key studies for the surface area of body parts. 

Medium 

Overall Rating Medium for 

Total Surface 

Area and Low 

for Surface Area 

of Individual 

Body Parts 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-4. Recommended Values for Mean Solids Adherence to Skin 

Face Arms Hands Legs Feet 

Source mg/cm2 

Children 

Residential (indoors)a - 0.0041 0.011 0.0035 0.010 Holmes et al. (1999) 

Daycare (indoors and 

outdoors)b 

- 0.024 0.099 0.020 0.071 Holmes et al. (1999) 

Outdoor sportsc 0.012 0.011 0.11 0.031 - Kissel et al. (1996b) 

Indoor sportsd - 0.0019 0.0063 0.0020 0.0022 Kissel et al. (1996b) 

Activities with soile 0.054 0.046 0.17 0.051 0.20 Holmes et al. (1999) 

Playing in mudf - 11 47 23 15 Kissel et al. (1996b) 

Playing in sedimentg 0.040 0.17 0.49 0.70 21 Shoaf et al. (2005b) 

Adults 

Outdoor sportsh 0.0314 0.0872 0.1336 0.1223 -

Holmes et al. (1999); 

Kissel et al. (1996b) 

Activities with soili 0.0240 0.0379 0.1595 0.0189 0.1393 

Holmes et al. (1999); 

Kissel et al. (1996b) 

Construction activities

j 0.0982 0.1859 0.2763 0.0660 - Holmes et al. (1999) 

Clammingk 0.02 0.12 0.88 0.16 0.58 Shoaf et al. (2005a) a Based on weighted average of geometric mean soil loadings for 2 groups of children (ages 3 to13 years; N = 10) 

playing indoors. b Based on weighted average of geometric mean soil loadings for 4 groups of daycare children (ages 1 to 6.5 years; 

N = 21) playing both indoors and outdoors. c Based on geometric mean soil loadings of 8 children (ages 13 to 15 years) playing soccer. d Based on geometric mean soil loadings of 6 children (ages >8 years) and one adult engaging in Tae Kwon Do. e Based on weighted average of geometric mean soil loadings for gardeners and archeologists (ages 16 to 35 years). f Based on weighted average of geometric mean soil loadings of 2 groups of children (age 9 to 14 years; N = 12) 

playing in mud. g Based on geometric mean soil loadings of 9 children (ages 7 to 12 years) playing in tidal flats. h Based on weighted average of geometric mean soil loadings of 3 groups of adults (ages 23 to 33 years) playing 

rugby and 2 groups of adults (ages 24 to 34) playing soccer. i Based on weighted average of geometric mean soil loadings for 69 gardeners, farmers, groundskeepers, 

landscapers and archeologists (ages 16 to 64 years) for faces, arms and hands; 65 gardeners, farmers, 

groundskeepers, and archeologists (ages 16 to 64 years) for legs; and 36 gardeners, groundskeepers and 

archeologists (ages 16 to 62) for feet. j Based on weighted average of geometric mean soil loadings for 27 construction workers, utility workers and 

equipment operators (ages 21 to 54) for faces, arms and hands; and based on geometric mean soil loadings for 

8 construction workers (ages 21 to 30 years) for legs. k Based on geometric mean soil loadings of 18 adults (ages 33 to 63 years) clamming in tidal flats. 

- = No data. 

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Chapter 7—Dermal Exposure Factors 

Table 7-5. Confidence in Recommendations for Solids Adherence to Skin 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The approach was adequate; the skin-rinsing technique is 

widely employed for purposes similar to this. Small 

sample sizes were used in the studies; the key studies 

directly measured soil adherence to skin. 

The studies attempted to measure soil adherence for 

selected activities and conditions. The number of activities 

and study participants was limited. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The studies were relevant to the factor of interest; the goal 

was to determine soil adherence to skin. 

The soil/dust studies were limited to the State of 

Washington, and the sediment study was limited to Rhode 

Island. The data may not be representative of other 

locales. All three studies were conducted by researchers 

from a laboratory where a similar methodology was used. 

This may limit the representativeness of the data in terms 

of a wider population. 

The studies were published between 1996 and 2005. 

Short-term data were collected. Seasonal factors may be 

important, but have not been studied adequately. 

Low 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

Articles were published in widely circulated 

journals/reports. 

The reports clearly describe the experimental methods, 

and enough information was provided to allow for the 

study to be reproduced. 

Quality control was not well described. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Variability in soil adherence is affected by many factors 

including soil properties, activity and individual behavior 

patterns. Not all age groups were represented in the 

sample. 

The estimates are highly uncertain; the soil adherence 

values were derived from a small number of observations 

for a limited set of activities. 

Low 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-5. Confidence in Recommendations for Solids Adherence to Skin (continued) 

General Assessment Factors Rationale Rating 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The studies were reported in peer-reviewed journal 

articles. 

There are three key studies that evaluated different 

activities in children and adults. 

Medium 

Overall Rating Low 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

7.3. SURFACE AREA 

Surface area of the skin can be determined by 

using measurement or estimation techniques. 

Coating, triangulation, and surface integration are 

direct measurement techniques that have been used to 

measure total body surface area and the surface area 

of specific body parts. The coating method consists 

of coating either the whole body or specific body 

regions with a substance of known density and 

thickness. Triangulation consists of marking the area 

of the body into geometric figures, then calculating 

the figure areas from their linear dimensions. Surface 

integration is performed by using a planimeter and 

adding the areas. The results of studies conducted 

using these various techniques have been 

summarized in Development of Statistical 

Distributions or Ranges of Standard Factors Used in 

Exposure Assessments (U.S. EPA, 1985). Because of 

the difficulties associated with direct measurements 

of body surface area, the existing direct measurement 

data are limited and dated. However, several 

researchers have developed methods for estimating 

body surface area from measurements of other body 

dimensions (Du Bois and Du Bois, 1989; Gehan and 

George, 1970; Boyd, 1935). Generally, these 

formulas are based on the observation that body 

weight and height are correlated with surface area 

and are derived using multiple regression techniques. 

U.S. EPA (1985) evaluated the various formulas for 

estimating total body surface area. Appendix 7A 

presents a discussion and comparison of formulas. 

The key studies on body surface area that are 

presented in Section 7.3.1 are based on these 

formulas, as well as weight and height data from 

NHANES. 

7.3.1. Key Body Surface Area Studies 

7.3.1.1.	 U.S. EPA (1985)—Development of 

Statistical Distributions or Ranges of 

Standard Factors Used in Exposure 

Assessments 

U.S. EPA (1985) summarized the direct 

measurements of the surface area of adults’ and 

children's body parts provided by Boyd (1935) and 

USDA (1969) as a percentage of total surface area. 

Table 7-6 presents these percentages. A total of 

21 children less than 18 years of age were included. 

Because of the small sample size, it is unclear how 

accurately these estimates represent averages for the 

age groups. A total of 89 adults, 18 years and older, 

were included in the analysis of body parts, providing 

greater accuracy for the adult estimates. Note that the 

proportion of total body surface area contributed by 

the head decreases from childhood to adulthood, 

whereas the proportion contributed by the leg 

increases. 

U.S. EPA (1985) analyzed the direct surface area 

measurement data of Gehan and George (1970) using 

the Statistical Processing System (SPS) software 

package of Buhyoff et al. (1982). Gehan and George 

(1970) selected 401 measurements made by Boyd 

(1935) that were complete for surface area, height, 

weight, and age for their analysis. Boyd (1935) had 

reported surface area estimates for 1,114 individuals 

using coating, triangulation, or surface integration 

methods (U.S. EPA, 1985). 

U.S. EPA (1985) used SPS to generate equations 

to calculate surface area as a function of height and 

weight. These equations were subsequently used by 

U.S. EPA to calculate body surface area distributions 

of the U.S. population using the height and weight 

data obtained from the National Health and Nutrition 

Examination Survey, 1999–2006 [CDC (2006); see 

Section 7.3.1.3]. 

The equation proposed by Gehan and George 

(1970) was determined by U.S. EPA (1985) to be the 

best choice for estimating total body surface area. 

However, the paper by Gehan and George (1970) 

gave insufficient information to estimate the standard 

error about the regression. Therefore, U.S. EPA 

(1985) used the 401 direct measurements of children 

and adults and reanalyzed the data using the formula 

of Du Bois and Du Bois (1989) and SPS to obtain the 

standard error (U.S. EPA, 1985). 

Regression equations were developed for specific 

body parts using the Du Bois and Du Bois (1989) 

formula and using the surface area of various body 

parts provided by Boyd (1935) and USDA (1969) in 

conjunction with SPS. Regression equations for 

adults were developed for the head, trunk (including 

the neck), upper extremities (arms and hands, upper 

arms, and forearms) and lower extremities (legs and 

feet, thighs, and lower legs) (U.S. EPA, 1985). Table 

7-7 presents a summary of the equation parameters 

developed by U.S. EPA (1985) for calculating surface 

area of adult body parts. Equations to estimate the 

body part surface area of children were not developed 

because of insufficient data. 

7.3.1.2.	 Boniol et al. (2008)—Proportion of Skin 

Surface Area of Children and Young 

Adults from 2 to 18 Years Old 

Boniol et al. (2008) applied measurement data for 

87 body parts to a computer model to estimate the 

surface area of body parts of children. The 

measurement data were collected in the late 1970s by 

Snyder et al. (1978) for the purpose of product safety 

design (e.g., toys and ergonomics) and represent 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

1,075 boys and 975 girls from various states in the 

United States. A surface area module of the computer 

model MAN3D was used to construct models of the 

human body for children (ages 2, 4, 6, 8, 10, 12, 14, 

16, and 18 years) to estimate surface area of 13 body 

parts for use in treating skin lesions. The body parts 

included head, neck, bosom, shoulders, abdomen, 

back, genitals and buttocks, thighs, legs, feet, upper 

arms, lower arms, and feet. The proportion of the skin 

surface area of these body parts relative to total 

surface area was computed. Table 7-8 presents these 

data for the various ages of male and female children. 

Except for the head, for which the percentages are 

much lower in this study than in U.S. EPA (1985), the 

body part proportions in this study appear to be 

similar to those presented in U.S. EPA (1985). For 

example, the proportions for hands range from 4.2 to 

4.9% in this study and from 5.0 to 5.9% in U.S. EPA 

(1985). Because this study provides additional body 

parts that were not included in the U.S. EPA (1985) 

study, it is necessary to combine some body parts for 

the purpose of comparing their results. For example, 

upper arms and lower arms can be combined to 

represent total arms, and thighs plus legs can be 

combined to represent total legs. Upper arms plus 

lower arms for 4-year-olds from this study represent 

14% of the total body surface, compared to 14.2% for 

arms for 3- to 6-year-olds from U.S. EPA (1985). 

Thighs plus legs for 2-year-olds from this study 

represent 25.3% of the total surface, compared to 

23.2% for 2- to 3-year-olds from U.S. EPA (1985). 

Likewise, neck, bosom, shoulders, abdomen, back, 

and genitals/buttocks can be combined to represent 

the trunk. 

The advantages of this study are that the data 

represent a larger sample size of children and are 

more recent than those used in U.S. EPA (1985). This 

study also provides data for more body parts than 

U.S. EPA (1985). However, the age groups presented 

in this study differ from those recommended in 

U.S. EPA (2005) and used elsewhere in this 

handbook, and no data are available for children 

1 year of age and younger. 

7.3.1.3.	 U.S. EPA Analysis of NHANES 

2005−2006 and 1999–2006 Data 

The U.S. EPA estimated total body surface areas 

by using the empirical relationship shown in 

Appendix 7A and U.S. EPA (1985), and body-weight 

and height data from the 1999–2006 NHANES for 

children and the 2005–2006 NHANES for adults. 

NHANES is conducted annually by the Centers for 

Disease Control (CDC) National Center of Health 

Statistics. The survey’s target population is the 

civilian, non-institutionalized U.S. population. The 

NHANES 1999–2006 survey was conducted on a 

nationwide probability sample of approximately 

40,000 people for all ages, of which approximately 

20,000 were children. The survey is designed to 

obtain nationally representative information on the 

health and nutritional status of the population of the 

United States through interviews and direct physical 

examinations. A number of anthropometrical 

measurements were taken for each participant in the 

study, including body weight and height. Unit 

non-response to the household interview was 19%, 

and an additional 4% did not participate in the 

physical examinations (including body-weight 

measurements). 

The NHANES 1999–2006 survey includes 

oversampling of low-income persons, adolescents 12 

to 19 years of age, persons 60+ years of age, African 

Americans, and Mexican Americans. Sample data 

were assigned weights to account both for the 

disparity in sample sizes for these groups and for 

other inadequacies in sampling, such as the presence 

of non-respondents. For children’s estimates, the 

U.S. EPA utilized four NHANES data sets in its 

analysis (NHANES 1999–2000, 2001–2002, 

2003−2004, and 2005–2006) to ensure adequate 

sample size for the age groupings of interest. Sample 

weights were developed for the combined data set in 

accordance with CDC guidance from the NHANES’ 

Web site (http://www.cdc.gov/nchs/about/major/ 

nhanes/nhanes20052006/faqs05_06.htm#question%2 

012). For adult estimates, the U.S. EPA utilized 

NHANES 2005–2006 in its estimates for currency 

and the same analytical methodology as in the earlier 

version of the Exposure Factors Handbook (U.S. 

EPA, 1997). 

Table 7-9 presents the mean and percentile 

estimates of total body surface area by age category 

for males and females combined. Table 7-10 and 

Table 7-11 present the mean and percentiles of total 

body surface area by age category for males and 

females, respectively. Table 7-12 and Table 7-13 

present the mean and percentile estimates of body 

surface area of specific body parts for males and 

females 21 years and older, respectively. 

An advantage of using the NHANES data sets to 

derive total surface area estimates is that data are 

available for infants from birth and older. In addition, 

the NHANES data are nationally representative and 

remain the principal source of body-weight and 

height data collected nationwide from a large number 

of subjects. It should be noted that in the NHANES 

surveys, height measurements for children less than 

2 years of age were based on recumbent length 

whereas standing height information was collected 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

for children aged 2 years and older. Some studies 

have reported differences between recumbent length 

and standing height measurements for the same 

individual, ranging from 0.5 to 2 cm, with recumbent 

length being the larger of the two measurements 

(Buyken et al., 2005). The use of height data obtained 

from two different types of height measurements to 

estimate surface area of children may potentially 

introduce errors into the estimates. 

7.3.2. Relevant Body Surface Area Studies 

7.3.2.1.	 Murray and Burmaster 

(1992)―Estimated Distributions for Total 

Body Surface Area of Men and Women in 

the United States 

Murray and Burmaster (1992) generated 

distributions of total body surface area for men and 

women ages 18 to 74 years using Monte Carlo 

simulations based on height and weight distribution 

data. Four different formulae for estimating body 

surface area as a function of height and weight were 

employed: Du Bois and Du Bois (1989), Boyd 

(1935), U.S. EPA (1985), and Costeff (1966). The 

formulae of Du Bois and Du Bois (1989), Boyd 

(1935), and U.S. EPA (1985) are based on height and 

weight. The formula developed by Costeff (1966) is 

based on 220 observations that estimate body surface 

area based on weight only. Formulae were compared, 

and the effect of the correlation between height and 

weight on the body surface area distribution was 

analyzed. 

Monte Carlo simulations were conducted to 

estimate body surface area distributions. They were 

based on the bivariate distributions estimated by 

Brainard and Burmaster (1992) for height and natural 

logarithm of weight and the formulae described 

previously. A total of 5,000 random samples each for 

men and women were selected from the 

two correlated bivariate distributions. Body surface 

area calculations were made for each sample, and for 

each formula, resulting in body surface area 

distributions. Murray and Burmaster (1992) found 

that the body surface area frequency distributions 

were similar for the four models (see Table 7-14). 

Using the U.S. EPA (1985) formula, the median 

surface area values were calculated to be 1.96 m2 for 

men and 1.69 m2 for women. The median value for 

women is identical to that generated by U.S. EPA 

(1985) but differs for men by approximately 

1%. Body surface area was found to have lognormal 

distributions for both men and women (see Figure 

7-1). It also was found that assuming correlation 

between height and weight influences the final 

distribution by less than 1%. 

The advantages of this study are that it compared 

the various formulae for computing surface area and 

confirmed that the formula used by the U.S. EPA in 

its analysis—as described in Section 7.3.1.3—is 

appropriate. This study is considered relevant 

because the height and weight data used in this 

analysis predates the height and weight data used in 

the more recent U.S. EPA analysis (see 

Section 7.3.1.3). 

7.3.2.2.	 Phillips et al. (1993)—Distributions of 

Total Skin Surface Area to Body-Weight 

Ratios 

Phillips et al. (1993) observed a strong correlation 

(0.986) between body surface area and body weight 

and studied the effect of using these factors as 

independent variables in the lifetime average daily 

dose (LADD) equation (see Chapter 1). The authors 

suggested that, because of the correlation between 

these two variables, the use of body surface area-tobody-weight (SA/BW) ratios in human exposure 

assessments may be more appropriate than treating 

these factors as independent variables. Direct 

measurement data from the scientific literature were 

used to calculate SA/BW ratios for three age groups 

of the population (infants age 0 to 2 years, children 

age 2.1 to 17.9 years, and adults age 18 years and 

older). These ratios were calculated by dividing body 

surface areas by corresponding body weights for the 

401 individuals analyzed by Gehan and George 

(1970) and summarized by U.S. EPA (1985). 

Distributions of SA/BW ratios were developed, and 

summary statistics were calculated for the three age 

groups and the combined data set. 

Table 7-15 presents summary statistics for both 

adults and children. The shapes of these SA/BW 

distributions were determined using D'Agostino's 

test, as described in D’Agostino et al. (1990). The 

results indicate that the SA/BW ratios for infants 

were lognormally distributed. The SA/BW ratios for 

adults and all ages combined were normally 

distributed. SA/BW ratios for children were neither 

normally nor lognormally distributed. According to 

Phillips et al. (1993), SA/BW ratios may be used to 

calculate LADDs by replacing the body surface area 

factor in the numerator of the LADD equation with 

the SA/BW ratio and eliminating the body-weight 

factor in the denominator of the LADD equation. 

The effect of sex and age on SA/BW distribution 

also was analyzed by classifying the 401 observations 

by sex and age. Statistical analyses indicated no 

significant differences between SA/BW ratios for 

males and females. SA/BW ratios were found to 

decrease with increasing age. 

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The advantage of this study is that it studied 

correlations between surface area and body weight. 

However, data could not be broken out by finer age 

categories. 

7.3.2.3.	 Garlock et al. (1999)—Adult Responses to 

a Survey of Soil Contact Scenarios 

Garlock et al. (1999) reported on a survey 

conducted during the summer of 1996. The objective 

of the study was to evaluate behaviors relevant to 

dermal contact with soil and dust. Garlock et al. 

(1999) conducted computer-aided telephone 

interviews designed to be nationally representative of 

the U.S. population. The survey response rate was 

61.4%, with a sample size of 450. Adult respondents 

were asked to provide information on what they 

usually wore while engaging in the following 

activities during warm or cold weather: gardening, 

outdoor team sports (e.g., soccer, softball, football), 

and home construction projects that include digging, 

as well as whether they washed or bathed following 

these activities. Information also was collected on 

frequency and duration of these activities (see 

Chapter 16). Similar information was collected for 

children’s outdoor activities and is reported in Wong 

et al. (2000). Using the activity-specific clothing 

choices reported for each survey participant and body 

surface area data from U.S. EPA (1985), Garlock 

et al. (1999) estimated the percentages of adult total 

body surface areas that would be uncovered for each 

of the warm weather and cold weather activities (see 

Table 7-16). The median ranged from 28 to 33% for 

warm weather activities and 3 to 8% for cold weather 

activities. 

The advantages of this study are that it provides 

information on the percentage of adult total surface 

area that may be exposed to soil during a variety of 

outdoor activities. These data represent outdoor 

activities only (no data are provided for exposure to 

indoor surface dusts). 

7.3.2.4.	 Wong et al. (2000)—Adult Proxy 

Responses to a Survey of Children’s 

Dermal Soil Contact Activities 

Wong et al. (2000) reported on two national 

phone surveys that gathered information on activity 

patterns related to dermal contact with soil. The first 

[also reported on by Garlock et al. (1999)] was 

conducted in 1996 using random digit dialing. 

Information about 211 children was gathered from 

adults more than 18 years of age. For older children 

(those between the ages of 5 and 17 years), 

information was gathered on their participation in 

“gardening and yardwork,” “outdoor sports,” and 

“outdoor play activities.” For children less than 

5 years of age, information was gathered on “outdoor 

play activities,” including whether the activity 

occurred on a playground or yard with “bare dirt or 

mixed grass and dirt” surfaces. Information on the 

types of clothing worn while participating in these 

play activities during warm weather months (April 

through October) was obtained. The results of this 

survey indicated that most children wore short pants, 

a dress or skirt, short sleeve shirts, no socks, and 

leather or canvas shoes during the outdoor play 

activities of interest. Using the survey data on 

clothing and total body surface area data from 

U.S. EPA (1985), estimates were made of the skin 

area exposed (expressed as percentages of total body 

surface area) associated with various age ranges and 

activities. Table 7-17 provides these estimates. 

The advantage of this study is that it provides 

information on the percentage of children’s bodies 

exposed to soil. These data reflect exposed skin areas 

during warm weather for outdoor activities only. 

7.3.2.5.	 AuYeung et al. (2008)—The Fraction of 

Total Hand Surface Area Involved in 

Young Children’s Outdoor Hand-toMouth Contacts 

AuYeung et al. (2008) videotaped a total of 

38 children (20 girls and 18 boys) between the ages 

of 1 and 6 years while they engaged in unstructured 

play activities in outdoor residential locations. The 

data were reviewed, and contact information was 

recorded according to the objects contacted and the 

associated contact configurations (e.g., full palm 

press, closed hand grip, open hand grip, side hand 

contact, partial palm, fingers only). The fraction of 

the hand associated with each of the various 

configuration categories then was estimated for a 

convenience sample of children and adults using 

hand traces and handprints consistent with the 

various contact configurations. Statistical 

distributions of the fraction of children’s total hand 

surface associated with outdoor contacts were 

estimated by combining the information on 

occurrence and configuration of contacts from the 

videotaped activity study with the data on the fraction 

of the hand associated with the various contact 

configurations. Table 7-18 provides the per-contact 

fractional surface areas for the various types of 

objects contacted and for all objects combined. For 

all objects contacted, fractional surface areas ranged 

from 0.13 to 0.27. AuYeung et al. (2008) suggested 

that “the majority of children’s outdoor contacts with 

objects involve a relatively small fraction of the 

hand’s total surface area.” 

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The advantage of this study is that it provides 

information on the fraction of the hand that contacts 

various surfaces and objects. However, the data are 

for a relatively small sample size of children (ages 1 

to 6 years). Similar data for adults and older children 

were not provided. 

7.4. ADHERENCE OF SOLIDS TO SKIN 

Several field studies have been conducted to 

estimate the adherence of solids to skin. These field 

studies consider factors such as activity, sex, age, 

field conditions, and clothing worn. Section 7.4.1 

provides information on key studies that measured 

adherence of solids to skin according to specific 

activities. Section 7.4.2 provides relevant 

information. Relevant studies provide additional 

perspective on adherence, including information on 

loading per contact event and the effects of soil/dust 

type, particle size, soil organic and moisture content, 

skin condition, and contact pressure and duration. 

This information may be useful for models based on 

individual contact events. 

7.4.1. Key Adherence of Solids to Skin Studies 

7.4.1.1.	 Kissel et al. (1996b)—Field Measurements 

of Dermal Soil Loading Attributable to 

Various Activities: Implications for 

Exposure Assessment 

Kissel et al. (1996b) collected direct 

measurements of soil loading on the surface of the 

skin of volunteers before and after activities expected 

to result in soil contact. Soil adherence associated 

with the following indoor and outdoor activities were 

estimated: greenhouse gardening, Tae Kwon Do, 

soccer, rugby, reed gathering, irrigation installation, 

truck farming, outdoor gardening and landscaping 

(groundskeepers), and playing in mud. Skin-surface 

areas monitored included hands, forearms, lower 

legs, faces, and feet (Kissel et al., 1996b). 

Table 7-19 provides the activities, information on 

their duration, sample size, and clothing worn by 

participants. The subjects’ body surfaces (forearms, 

hands, lower legs for all sample groups; faces and/or 

feet in some sample groups) were washed before and 

after the monitored activities. Paired samples were 

pooled into single ones. The mass recovered was 

converted to soil loading by using allometric models 

of surface area. 

Table 7-20 presents geometric means for postactivity soil adherence by activity and body region 

for the four groups of volunteers evaluated. Children 

playing in the mud had the highest soil loadings 

among the groups evaluated. The results also indicate 

that, in general, the amount of soil adherence to the 

hands is higher than for other parts of the body 

during the same activity. 

An advantage of this study is that it provides 

information on soil adherence to various body parts 

resulting from unscripted activities. However, the 

study authors noted that because the activities were 

unstaged, “control of variables such as specific 

behaviors within each activity, clothing worn by 

participants, and duration of activity was limited.” In 

addition, soil adherence values were estimated based 

on a small number of observations, and very young 

children and indoor activities were under represented. 

7.4.1.2.	 Holmes et al. (1999)—Field 

Measurements of Dermal Loadings in 

Occupational and Recreational Activities 

Holmes et al. (1999) collected pre- and 

post-activity soil loadings on various body parts of 

individuals within groups engaged in various 

occupational and recreational activities. These groups 

included children at a daycare center (“Daycare 

Kids”), children playing indoors in a residential 

setting (“Indoor Kids”), individuals removing 

historical artifacts from a site (“Archeologists”), 

individuals erecting a corrugated metal wall 

(“Construction Workers”), heavy equipment 

operators (“Equipment Operators”), individuals 

playing rugby (“Rugby Players”), utility workers 

jack-hammering and excavating trenches (“Utility 

Workers”), individuals conducting landscaping and 

rockery (“Landscape/Rockery”), and individuals 

performing gardening work (“Gardeners”). The study 

was conducted as a follow-up to previous field 

sampling of soil adherence on individuals 

participating in various activities (Kissel et al., 

1996b). For this round of sampling, soil loading data 

were collected utilizing the same methods used and 

described in Kissel et al. (1996b). Table 7-19 presents 

information regarding the groups studied and their 

observed activities. 

The daycare children studied were all at 

one location, and measurements were taken on 

three different days. The children freely played both 

indoors in the house and outdoors in the backyard. 

Table 7-19 describes the number of children within 

each day’s group and the clothing worn. For the 

second observation day (“Daycare Kids No. 2”), 

post-activity data were collected for five children. All 

the activities on this day occurred indoors. For the 

third daycare group (“Daycare Kids No. 3”), 

four children were studied. 

On two separate days, children playing indoors in 

a home environment were monitored. The first group 

(“Indoor Kids No. 1”) had four children while the 

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second group (“Indoor Kids No. 2”) had six. The play 

area was described by the authors as being primarily 

carpeted. Table 7-19 describes the clothing worn by 

the children within each day’s group. 

Seven individuals (“Archeologists”) were 

monitored while excavating, screening, sorting, and 

cataloging historical artifacts from an ancient Native 

American site during a single event. Eight rugby 

players were monitored on two occasions after 

playing or practicing rugby. Eight volunteers from a 

construction company were monitored for 1 day 

while erecting corrugated metal walls. 

Four volunteers (“Landscape/Rockery”) were 

monitored while relocating a rock wall in a park. 

Four excavation workers (“Equipment Operators”) 

were monitored twice after operation of heavy 

equipment. Utility workers were monitored while 

cleaning and fixing water mains, jack-hammering, 

and excavating trenches (“Utility Workers”) on 

2 days; five participated on the 1st day and four on the 

2nd . Eight volunteers (“Gardeners”) ages 16 to 

35 years were monitored while performing gardening 

activities (i.e., weeding, pruning, digging small 

irrigation trenches, picking and cleaning fruit). Table 

7-19 describes the clothing worn by these groups. 

Table 7-20 summarizes the geometric means and 

standard deviations (SDs) of the post-activity soil 

adherence for each group of individuals and for each 

body part. According to the authors, variations in the 

soil loading data from the daycare participants reflect 

differences in the weather and access to the outdoors. 

An advantage of this study is that it provides a 

supplement to soil-loading data collected in a 

previous round of studies (Kissel et al., 1996b). Also, 

the data support the assumption that hand loading can 

be used as a conservative estimate of soil loading on 

other body surfaces for the same activity. The 

activities studied represent normal child play both 

indoors and outdoors, as well as different 

combinations of clothing. The small number of 

participants is a disadvantage of this study. Also, the 

children studied and the activity setting may not be 

representative of the U.S. population. 

7.4.1.3.	 Shoaf et al. (2005b)—Child Dermal 

Sediment Loads Following Play in a Tide 

Flat 

The purpose of the Shoaf et al. (2005b) study was 

to obtain sediment adherence data for children 

playing in a tidal flat (“Shoreline Play”). The study 

was conducted 1 day in late September 2003 at a tidal 

flat in Jamestown, RI. A total of nine subjects 

(three females and six males) ages 7 to 12 years 

participated in the study. Table 7-19 presents 

information on activity duration, sample size, and 

clothing worn by participants. Participants’ parents 

completed questionnaires on their child’s typical 

activity patterns during tidal flat play, exposure 

frequency and duration, clothing choices, bathing 

practices, and clothes laundering. 

This study reported direct measurements of 

sediment loadings on five body parts (face, forearms, 

hands, lower legs, and feet) after play in a tide flat. 

Each of nine subjects participated in two timed 

sessions, and pre- and post-activity sediment loading 

data were collected. Geometric mean (geometric 

standard deviations) dermal loadings (mg/cm2

) on the 

face, forearm, hands, lower legs, and feet for the 

combined sessions, as shown in Table 7-20, were 

0.04 (2.9), 0.17 (3.1), 0.49 (8.2), 0.70 (3.6), and 21 

(1.9), respectively. Event duration did not appear to 

be associated with sediment loading on the skin. 

The primary advantage of this study is that it 

provides adherence data specific to children and 

sediments, which previously had been largely 

unavailable. Results will be useful to risk assessors 

considering exposure scenarios involving child 

activities at a coastal shoreline or tidal flat. The 

limited number of participants (nine) and sampling 

during just 1 day and at one location, make 

extrapolation to other situations uncertain. 

7.4.1.4.	 Shoaf et al. (2005a)—Adult Dermal 

Sediment Loads Following Clam Digging 

in Tide Flats 

The purpose of this study was to obtain sediment 

adherence data for adults engaged in unscripted clam 

digging activities in a tidal flat. The study was 

conducted over three days in late August 2003 at a 

tide flat near Narragansett, RI. Eighteen subjects 

(nine females and nine males) ages 33 to 63 years old 

participated in the study. This study reports direct 

measurements of sediment loadings on five body 

parts (face, forearms, hands, lower legs and feet). 

Pre- and post-activity sediment loading data were 

collected using skin rinsing techniques. The data 

from this study are presented along with the other 

field studies in Table 7-19 (populations and field 

conditions) and Table 7-20 (soil adherence results). 

Activity time was found not to be a good indicator of 

skin loading. 

The primary advantage of this study is that it 

provides adherence data for sediments which had 

previously been largely unavailable. Results will be 

useful to risk assessors considering exposure 

scenarios involving adult activities at a coastal 

shoreline or tide flat. The limited number of 

participants (18) and sampling over just 3 days and 

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Chapter 7—Dermal Exposure Factors 

one location, make extrapolation to other situations 

uncertain. 

7.4.2. Relevant Adherence of Solids to Skin 

Studies 

7.4.2.1.	 Harger (1979)—A Model for the 

Determination of an Action Level for 

Removal of Curene Contaminated Soil 

U.S. EPA (1992a, 1988, 1987) reported on 

experimental values for (soil-related) dust adherence 

as estimated by Harger (1979). According to 

U.S. EPA (1992a), “these estimates are based on 

unpublished experiments by Dr. Rolf Hartung 

(University of Michigan) as reported in a 1979 

memorandum from J. Harger to P. Cole (both from 

Michigan Toxic Substance Control Commission in 

Lansing, MI). According to this memo, Dr. Hartung 

measured adherence using his own hands and found: 

2.77 mg/cm2 for kaolin with a SD of 0.66 and N = 6; 

1.45 mg/cm2 for potting soil with SD = 0.36 and 

N = 6; and 3.44 mg/cm2 for sieved vacuum cleaner 

dust (mesh 80) with SD = 0.80 and N = 6. The details 

of the experimental procedures were not reported. 

Considering the informality of the study and lack of 

procedural details, the reliability of these estimates 

cannot be evaluated.” Accordingly, these data are not 

considered to be key for the purpose of developing 

recommendations for soil adherence to the skin. 

7.4.2.2.	 Que Hee et al. (1985)—Evolution of 

Efficient Methods to Sample Lead 

Sources, Such as House Dust and Hand 

Dust, in the Homes of Children 

Que Hee et al. (1985) used house dust having 

particle sizes ranging from 44 to 833 μm in diameter, 

fractionated into six size ranges, to estimate the 

amount that adhered to the palm of the hand of a 

small adult. The amount of dust that adhered to skin 

was determined by applying approximately 5 grams 

of dust for each size fraction, removing excess dust 

by shaking the hands, and then measuring the 

difference in weight before and after application. Que 

Hee et al. (1985) found no relationship between 

particle size and adherence for house dusts with 

particle sizes <246 μm. For all six particle sizes, an 

average of 63 ± 42 percent of applied dust adhered to 

the palm of the hand. This represents 31.2 ± 16.6 mg 

of soil. Excluding the two largest size fractions, 

58 ± 29% of the applied dust adhered to the hand, 

representing 28.9 ± 1.9 mg. 

The limitation of these data is that they were 

based on one adult hand and a single house dust 

sample. Also, the data are for hands only and are not 

linked to specific activities. 

7.4.2.3.	 Driver et al. (1989)—Soil Adherence to 

Human Skin 

Driver et al. (1989) conducted experiments to 

evaluate the conditions that may affect soil adherence 

to the skin of adult hands. Both top soils and subsoils 

of five soil types (Hyde, Chapanoke, Panorama, 

Jackland, and Montalto) were collected from sites in 

Virginia. The organic content, clay mineralogy, and 

particle size distribution of the soils were 

characterized, and the soils were dry sieved to obtain 

particle sizes of ≤250 μm and ≤150 μm. For each soil 

type, the amount of soil adhering to adult male hands 

when using both sieved and unsieved soils was 

determined gravimetrically (i.e., measuring the 

difference in soil sample weight before and after soil 

application to the hands). An attempt was made to 

measure only the minimal or “monolayer” of soil 

adhering to the hands. This was done by mixing a 

preweighed amount of soil over the entire surface 

area of the hands for a period of approximately 

30 seconds, followed by removing excess soil by 

gently rubbing the hands together after contact with 

the soil. Excess soil that was removed from the hands 

was collected, weighed, and compared to the original 

soil sample weight. Driver et al. (1989) measured 

average adherence of 1.40 mg/cm2 for particle sizes 

less than 150 μm, 0.95 mg/cm2 for particle sizes less 

than 250 μm, and 0.58 mg/cm2 for unsieved soils. 

Analysis of variance statistics showed that the most 

important factor affecting adherence variability was 

particle size (p < 0.001). The next most important 

factor was soil type and subtype (p < 0.001), but the 

interaction of soil type and particle size also was 

significant (p < 0.01). 

Driver et al. (1989) found statistically significant 

increases in soil adherence with decreasing particle 

size, whereas Que Hee et al. (1985) found that 

different size particles of house dust <246 μm 

adhered equally well to hands. 

The advantages of this study are that it provides 

additional perspective on the effects of particle size 

on adherence and that it evaluated several different 

soil types. However, it is based on data for hands 

only for a limited number of experimental 

observations (i.e., one subject). Also, the data are not 

activity based. 

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7.4.2.4.	 Sedman (1989)—The Development of 

Applied Action Levels for Soil Contact: A 

Scenario for the Exposure of Humans to 

Soil in a Residential Setting 

Sedman (1989) used estimates from Lepow et al. 

(1975), Roels et al. (1980), and Que Hee et al. (1985) 

to develop a maximum soil load that could occur on 

the skin. Lepow et al. (1975) estimated that 

approximately 0.5 mg of soil adhered to 1 cm2 of 

skin. Roels et al. (1980) estimated that 159 mg of soil 

adhered to the hand of an 11-year-old child. 

Assuming that approximately 60% (185 cm2

) of the 

surface area of the hand was sampled, the amount of 

soil adhering per unit area of skin was estimated to be 

0.9 mg/cm2

. Que Hee et al. (1985) estimated that 

approximately 31.2 mg of housedust adhered to the 

palm of a small adult. Assuming a hand surface area 

of 160 cm2

, Sedman (1989) estimated a soil loading 

of 0.2 mg/cm2

. A rounded arithmetic mean of 

0.5 mg/cm2 was calculated from these three studies. 

According to Sedman (1989), this was near the 

maximum load of soil that could occur on the skin, 

but it is unlikely that most skin surfaces would be 

covered with this amount of soil (Sedman, 1989). 

This study is considered relevant and not key 

because it does not provide any new data, but uses 

data from other studies and various assumptions to 

estimate soil adherence. 

7.4.2.5.	 Finley et al. (1994)—Development of a 

Standard Soil-to-Skin Adherence 

Probability Density Function for Use in 

Monte Carlo Analyses of Dermal 

Exposure 

Using data from several existing studies, Finley 

et al. (1994) developed probability density functions 

of soil-to-skin adherence. Finley et al. (1994) 

reviewed studies that estimated adherence among 

adults and children based on various gravimetric and 

hand wiping/rinsing methods. Several of these studies 

were originally conducted for the purpose of 

estimating lead exposure from soil contact. By 

combining data from four studies [Charney et al. 

(1980); Roels et al. (1980); Gallacher et al. (1984); 

and Duggan et al. (1985)], Finley et al. (1994) 

estimated a mean ± standard deviation soil adherence 

value for children of 0.65 ± 1.2 mg soil/cm2

-skin. 

(50th percentile = 0.36 and 95th percentile = 2.4 mg 

soil/cm2

-skin). Using data from three studies 

[Gallacher et al. (1984); Que Hee et al. (1985); and 

Driver et al. (1989)], Finley et al. (1994) estimated a 

mean ± standard deviation soil adherence value for 

adults of 0.49 ± 0.54 mg soil/cm2

-skin. 

(50th percentile = 0.06 and 95th percentile = 1.6 mg 

soil/cm2

-skin). Because the distributions of 

soil-to-skin adherence were similar for children and 

adults, Finley et al. (1994) developed a probability 

density function based on the combined data for 

children and adults. The probability density function 

is lognormally distributed with a mean ± standard 

deviation of 0.52 ± 0.9 mg soil/cm2

-skin 

(50th percentile = 0.25 and 95th percentile = 1.7 mg 

soil/cm2

-skin). 

The advantage of this study is that it provides 

distributions of soil adherence for children, adults, 

and children and adults combined. However, it is 

based on some older, relevant studies that are not 

activity- or body-part specific. 

7.4.2.6.	 Kissel et al. (1996a)—Factors Affecting 

Soil Adherence to Skin in Hand-Press 

Trials: Investigation of Soil Contact and 

Skin Coverage 

Kissel et al. (1996a) conducted soil adherence 

experiments to evaluate the effect of particle size and 

soil moisture content on adherence to the skin. 

Five soil types were obtained in the Seattle, WA, area 

(sand, two types of loamy sand, sandy loam, and silt 

loam) and were analyzed to determine composition. 

Clay content ranged from 0.5 to 7.0%, and organic 

carbon content ranged from 0.7 to 4.6%. Soils were 

dry-sieved to obtain particle size ranges of <150, 

150−250, and >250 μm. For each soil type, the 

amount of soil adhering to an adult female hand when 

using both sieved and unsieved soils was determined 

by measuring the soil sample weight before and after 

the hand was pressed into a pan containing the test 

soil. Loadings were estimated by dividing the 

recovered soil mass by the total surface area of 

one hand, although loading occurred primarily on 

only one side of the hand. Results showed that 

generally, soil adherence to hands was directly 

correlated with moisture content, inversely correlated 

with particle size, and independent of clay content or 

organic carbon content. For dry soil, mean adherence 

was the lowest for the largest particle sizes (i.e., 

>250 μm) of dry soil (0.06 to 0.34 mg/cm2

) and 

highest for the smallest particle sizes (0.42 to 

0.76 mg/cm2

). Adherence values based on moisture 

content ranged from 0.22 to 0.54 mg/cm2 for soils 

with moisture contents of 9% or less, 0.39 to 

3.09 mg/cm2 for soils with moisture contents of 10 to 

19%, and 1.64 to 14.8 mg/cm2 for soils with moisture 

contents of 21 to 27%. 

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The advantage of this study is that it provides 

information on how soil type can affect adherence to 

the skin. However, the soil adherence data are for a 

single subject, and the data are limited to five soil 

samples. 

7.4.2.7.	 Holmes et al. (1996)—Investigation of the 

Influence of Oil on Soil Adherence to 

Skin 

Holmes et al. (1996) conducted experiments to 

evaluate differences in adherence of soil to skin based 

on soil type, moisture content, and the presence of oil 

(i.e., petroleum contaminants) in the soil. Three soil 

types (loamy sand, silt loam, and sand) treated with 

three concentrations (0, 1, and 10%) of motor oil 

were used, and the experiments were conducted 

under wet and dry soil conditions. A single subject 

pressed the right hand, palm down, into a pan 

containing soil. The soil adhering to the hand was 

collected by washing and then weighed. For dry soil 

containing no oil, adherence values ranged from 

0.29 mg/cm2 for sandy soil to 0.59 mg/cm2 for silt 

loam. For wet soil containing no oil (13 to 

15% moisture), adherence values were 0.25 mg/cm2 

for silt loam, 1.6 mg/cm2 for sand, and 3.7 mg/cm2 

for loamy sand. According to Holmes et al. (1996), 

“high concentrations of petroleum contaminants can 

increase the dermal adherence of soil, but the 

magnitude of the effect is likely to be modest.” 

The advantage of this study is that it provides 

additional perspective on the factors that affect soil 

adherence to skin. However, it is based on limited 

observations (i.e., one subject) for only the hand 

under experimental conditions (i.e., not 

activity-based). 

7.4.2.8. Kissel et al. (1998)—Investigation of 

Dermal Contact With Soil in Controlled 

Trials 

Kissel et al. (1998) measured dermal exposure to 

soil from staged activities conducted in a greenhouse. 

A fluorescent marker was mixed in soil so that soil 

contact for a particular skin surface area could be 

identified. The subjects were video-imaged under a 

long-wave ultraviolet (UV) light before and after soil 

contact. In this manner, soil contact on hands, 

forearms, lower legs, and faces was assessed by 

presence of fluorescence. In addition to fluorometric 

data, gravimetric measurements for pre-activity and 

post-activity were obtained from the different body 

parts examined. The studied groups included adults 

transplanting 14 plants for 9 to 18 minutes, children 

playing for 20 minutes in a soil bed of varying 

moisture content representing wet and dry soils, and 

adults laying plastic pipes for 15, 30, or 45 minutes. 

Table 7-21 summarizes the parameters describing 

each of these activities. Before each trial, each 

participant was washed to obtain a preactivity or 

background gravimetric measurement. 

For wet soil, post-activity fluorescence results 

indicated that the hand had a much higher fractional 

coverage than other body surfaces (see Figure 7-2). 

As shown in Figure 7-3, post-activity gravimetric 

measurements for children playing and adults 

transplanting showed higher soil loading on hands 

and much lower soil loading on other body surfaces. 

This also was observed in adults laying pipe. The 

arithmetic mean percent of hand surface area 

fluorescing was 65% after 15 minutes laying pipe in 

wet soil and 85% after 30 and 45 minutes laying pipe 

in wet soil. The arithmetic mean percent of lower leg 

surface area fluorescing was ~20% after 15 minutes 

of laying pipe in wet soil, 25% after 30 minutes, and 

40% after 45 minutes. According to Kissel et al. 

(1998), the relatively low loadings observed on 

non-hand body parts may be a result of a more 

limited area of contact for the body part rather than 

lower localized loadings. Kissel et al. (1998) 

observed geometric means of up to about 3 mg/cm2 

on adults’ hands after the 30-minute pipelaying 

activity with wet soil. After children played and 

adults transplanted in wet soil, geometric mean soil 

loadings were 0.7 and 1.1 mg/cm2

, respectively. 

Mean loadings were lower on hands in the dry soil 

trial and on lower legs, forearms, and faces in both 

the wet and dry soil trials. Higher loadings were 

observed for all body surfaces with the higher 

moisture content soils. 

This report is valuable in showing soil loadings 

from soils of different moisture content and providing 

evidence that dermal exposure to soil is not uniform 

for various body surfaces. This study also provides 

some evidence of the protective effect of clothing. 

Disadvantages of the study include the small number 

of study participants and the short activity duration. 

7.4.2.9.	 Rodes et al. (2001)—Experimental 

Methodologies and Preliminary Transfer 

Factor Data for Estimation of Dermal 

Exposure to Particles 

Rodes et al. (2001) conducted a study using the 

fluorescein-tagged Arizona Test Dust (ATD) as a 

surrogate for house dust and evaluated particle mass 

transfer from surfaces to the human skin of three test 

subjects (one female and two males). Transfers to wet 

and dry skin from stainless steel, vinyl, and carpeted 

surfaces that had been preloaded with tagged ATD 

were quantified. For carpets, experiments were 

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conducted in which particles were either embedded in 

the carpet fibers or not embedded. Particles were 

embedded into carpet by dragging a steel cylinder 

across the carpet after loading. Controlled hand 

(palm) press experiments were conducted, and the 

amount of tagged ATD that had transferred to the skin 

of the palm was measured using fluorometry. Surface 

loadings that represented typical indoor conditions 

were used in the study. Rodes et al. (2001) used 

defined dust fractions (<80 μm) to evaluate the 

influence of particles size on transfer. For the 

experiments with wet hands, a surrogate saliva 

solution was used. The portion of the hand that 

contacted the material also was estimated. 

Dermal transfer factors were calculated as the 

mass of particles on the hand (μg on hand/cm2 of 

dermal contact area) divided by the mass of particles 

on the surface contacts (μg on surface/cm2 of surface 

contact). Table 7-22 shows the dermal transfer factors 

(based on the mean of left and right hand presses) for 

the various surface types and hand moisture contents. 

The results indicate that for dry hands, transfer from 

smooth surfaces (i.e., stainless steel) was higher than 

for other materials (58.2 to 76.0%; mean = 69 + 9%). 

Skin moisture content was shown to be a critical 

factor in the proportion of particles to transfer (wet 

hands resulted in 100% transfer from stainless steel). 

As surface roughness increased, transfer tended to 

decrease, with carpet surfaces having the lowest 

transfer factors (3.4 to 16.9%). Embedding particles 

into the carpet significantly reduced particle transfer. 

Rodes et al. (2001) also observed that “only about 

1/3rd of the projected hand surface typically came in 

contact with the smooth test surfaces during a 

press....[and] consecutive presses decreased the 

particle transfer by a factor of three as the skin 

became loaded, requiring ~100 presses to reach an 

equilibrium transfer rate.” 

The advantage of this study is that it evaluated 

particle transfer for a variety of surface types and 

skin conditions. However, a small number of subjects 

were involved in the study, and Rodes et al. (2001) 

suggested that when using these data, the similarities 

and differences in characteristics between ATD and 

real house dust should be considered. 

7.4.2.10.	 Edwards and Lioy (2001)—Influence of 

Sebum and Stratum Corneum Hydration 

on Pesticide/Herbicide Collection 

Efficiencies of the Human Hand 

Edwards and Lioy (2001) studied the effects of 

sebum/sweat and skin hydration on the transfer of 

pesticide residues in dust to the hands. Under normal 

conditions, the skin on the hand is covered by a layer 

of sebum, a mixture of lipids secreted from the 

sebaceous glands, and sweat that is secreted from 

sweat ducts. Edwards and Lioy (2001) measured the 

levels of sebum and moisture on the palm of the hand 

of one subject prior to conducting hand press 

experiments using house dust treated with a mixture 

of four pesticides (atrazine, diazinon, malathion, and 

chlorpyrifos). The house dust sample was obtained 

from vacuum cleaner bags and was sieved to 

<250 μm. The dust was settled onto the sample 

surfaces and sprayed with the pesticide mixture, and 

the subject pressed one hand to the surface in a series 

of trials conducted approximately 1 week apart. The 

hand was rinsed with solvent to extract any 

transferred pesticide/dust, and the solution was 

analyzed for pesticide residues. Transfer efficiencies 

(percentage) were calculated as the concentration of 

residues measured in the hand rinse solution divided 

by the concentration of pesticide on the sampling 

surface times 100. The results of this study indicated 

that the transfer efficiencies of two pesticides in dust 

were negatively correlated with sebum levels (i.e., 

increased sebum levels resulted in a 13% reduction in 

atrazine transfer and an 8% reduction in malathion 

transfer) and transfer efficiencies of two pesticides in 

dust were negatively correlated with skin hydration 

[i.e., increased skin moisture resulted in a 

7% reduction in diazinon transfer and 5% reduction 

in chlorpyrifos transfer; Edwards and Lioy (2001)]. 

The advantage of this study is that it provides 

additional perspective on factors that can affect 

adherence of solids to the skin. However, it is 

considered relevant and not key because the transfer 

of dust was studied for the hands only and used 

experimental conditions not based on 

exposure-related activities. 

7.4.2.11. Choate et al. (2006)—Dermally Adhered 

Soil: Amount and Particle Size 

Distribution 

Choate et al. (2006) investigated the soil 

characteristics that affect particle adherence to human 

skin. The factors considered included particle size, 

organic carbon content, and soil moisture. Day-to-day 

variability and differences based on whether or not 

hands were washed before contacting the soil also 

were examined. A total of 108 subjects (1/3 female) 

between 18 and 30 years of age participated in one or 

more of a series of soil adherence experiments. Some 

of the experiments were conducted using clay loam 

soil collected in Colorado, while others were 

conducted using silty-clay loam soil collected in 

Iowa. Soil moisture contents ranged from 1 to 10%. 

Choate et al. (2006) used either preweighed adhesive 

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tape or hand washing with distilled water to remove 

and collect soil that had adhered to the palm of 

subjects’ hands after contact with bulk soil under 

controlled experimental conditions. Removed soil 

was weighed, and the mass of soil per area of skin 

surface was calculated for each sample. 

Based on the adhesive tape tests, an average of 

0.7 mg/cm2 of the Colorado soil adhered to the hand 

(N = 6 subjects each sampled using the right or left 

hand on 10–12 study days). There were no significant 

differences between the left and right hands, but there 

were “large average variabilities . . . both between 

subjects on a given day (±52%) and for an individual 

subject on different days (±50%).” Differences 

between soil adherence to hands that had or had not 

been washed prior to soil contact were observed, with 

hand washing resulting in a lower mean adherence 

value (0.51 mg/cm2

; N = 76) than non-washing 

(1.1 mg/cm2

; N = 72), when soil with a moisture 

content of 4.7% was used. The authors suggested that 

this is “probably due to the removal [during washing] 

of oils from the skin that aid in the adherence of soil 

particles.” Soil adherence for the two types of soils 

(i.e., from Colorado and Iowa) with low moisture 

content (i.e., <2%) averaged 0.64 and 0.69 mg/cm2

, 

compared to 1.47 and 1.36 mg/cm2 for those with 

high moisture content (9% to 10%). Large particle 

fractions of the soils with higher moisture content 

adhered more readily than those in soils with low or 

medium moisture content. The “adhered fractions of 

dry or moderately moist soils with wide distribution 

of particle sizes generally consist[ed] of particles of 

diameters <63 μm.” The organic carbon content of 

the soils did not appear to be an important contributor 

to soil adherence. 

The advantage of this study is that it provides 

additional perspective on factors that affect soil 

adherence to skin by using a larger number of 

subjects compared to some of the earlier studies. 

However, the data are based only on controlled 

experimental conditions and may not be 

representative of the specific types of activities in 

which dermal exposure may occur. 

7.4.2.12.	 Yamamoto et al. (2006)—Size Distribution 

of Soil Particles Adhered to Children’s 

Hands 

Yamamoto et al. (2006) conducted both 

laboratory and field experiments that showed finer 

soil particles adhered more readily to children’s 

hands than coarse particles. In the laboratory, 

one female subject pressed her hand into a tray 

containing reference soil. Her hand then was washed 

in ultrapure water that was analyzed to determine the 

size distributions and the amount of soil that had 

adhered to the hand. Yamamoto et al. (2006) 

observed that the mode diameter of soil adhering to 

the hand (22.8 ± 0.0 μm) was less than that of the 

reference soil (36.9 ± 4.9 μm), indicating that finer 

particles adhered more efficiently to the hand. The 

effect of hand moisture was tested by moistening the 

hand prior to pressing it onto the tray of soil. 

Yamamoto et al. (2006) observed that while the 

amount of soil that adhered to the hand increased 

with hand moisture, the size distributions were not 

greatly changed. 

A separate field experiment was conducted in 

which ten 4-year-old children (five males and 

five females) attending a nursery school in Japan 

participated. After playing in the playground and 

sandbox for a morning or afternoon, the children’s 

hands were washed in bottles containing 500 mL 

ultrapure water, and aliquots of the water were 

analyzed to determine the size distributions and 

amounts of particles that had adhered to the hands. 

The particles sizes of soil samples collected from the 

children’s playing area (i.e., playground, field, and 

sandbox) also were analyzed. The mean, median, and 

maximum amounts of soil adhering to the children’s 

hands were 26.2, 15.2, and 162.5 mg/hand, 

respectively. Assuming a surface area of the hand of 

210 cm2

, the amounts are equivalent to 0.125, 0.73, 

and 0.774 mg/cm2

, respectively. Compared to the soil 

in the children’s play area, the soil adhering to the 

children’s hands was composed primarily of the finer 

particles. 

The advantage of this study is that both laboratory 

and field measurements were used to evaluate 

particle sizes of soil that adheres to the hands. 

However, only one subject participated in the 

laboratory study, and the children’s activities in the 

field portion were not indexed to the amount of time 

spent performing soil contact activities. 

7.4.2.13.	 Ferguson et al. (2009a; 2009c; 2009b; 

2008)―Soil-Skin Adherence: 

Computer-Controlled Chamber 

Measurements 

Ferguson et al. (2009a; 2009c; 2009b; 2008) 

conducted a series of soil adherence experiments by 

using a mechanical chamber designed to control and 

measure pressure and time of contact with surfaces 

loaded with soil. Adherence of play sand and lawn 

soil to human cadaver skin and cotton sheet samples 

was measured after contact with either loaded carpet 

or aluminum surfaces. Multiple pressure levels (20 to 

50 kPa), durations of contact (10 to 50 seconds), and 

particle sizes (<139.7 μm and >139.7 to <381.0 μm) 

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were evaluated (Ferguson et al., 2009a; Ferguson et 

al., 2009b; Beamer et al., 2008). Also, both singleand multiple-contact experiments were conducted 

(Ferguson et al., 2009c). Soil adherence was 

estimated by weighing the carpet or aluminum 

samples loaded with play sand or lawn soil both 

before and after controlled contacts occurred and 

calculating the weight differences. Each experiment, 

using different combinations of pressure, contact 

duration, particle size, soil type, surface, and contact 

material, was repeated multiple times. Table 7-23 

presents a comparison of the adherence values for 

contact with carpet and aluminum surfaces. Mean 

soil to skin adherence from contact with aluminum 

surfaces (1.18 mg/cm2

) was higher than from carpet 

(0.71 mg/cm2

). In general, soil transfer increased as 

pressure increased, and contact durations of 

30 seconds or more did not appear to result in higher 

adherence. For carpets, larger particle size was 

associated with higher adherence, while smaller 

particle size was associated with higher adherence 

from aluminum (Ferguson et al., 2009a), Based on a 

comparison of data from experiments with multiple 

contacts, Ferguson et al. (2009c) found that, “on 

average, 8% of the original transfer amount will 

transfer during a second contact. Therefore, attaching 

a soil/adherence transfer of the original magnitude for 

every contact may result in overestimates for 

exposure.” 

The advantages of these studies are that they 

provide data from controlled experiments in which a 

variety of conditions were tested. However, a single 

carpet type was used, and transfer may differ based 

on carpet type. Also, adherence may be different for 

different types of soil or house dust, as well as for 

different skin types and conditions. Differences in the 

nature of contact and the initial surface soil loadings 

also may affect adherence. 

7.5.	 FILM THICKNESS OF LIQUIDS ON 

SKIN 

Information on the thickness of liquids on human 

skin is sometimes used to estimate dermal exposure 

to contaminants in liquids that come into contact with 

the skin. For example, these data are used to estimate 

exposure to consumer products in U.S. EPA’s 

Exposure and Fate Assessment Screening Tool 

[EFAST; U.S. Environmental Protection Agency 

(2007b)]. Section 7.5.1 provides the available data on 

film thickness of liquids on the skin. However, these 

data are limited; therefore, studies related to this 

factor have not been categorized as key or relevant in 

this chapter, and specific recommendations are not 

provided for this factor. 

7.5.1. U.S. EPA (1987)—Methods for Assessing 

Consumer Exposure to Chemical 

Substances; and U.S. EPA (1992c)—A 

Laboratory Method to Determine the 

Retention of Liquids on the Surface of 

Hands 

U.S. EPA (1992c, 1987) reported on experiments 

that were conducted to measure the retention of 

liquids on hands after contact with six different types 

of liquids (mineral oil, cooking oil, water soluble 

bath oil, 50:50 oil/water emulsion, water, and 

50:50 water ethanol). These liquids were selected 

because they were non-toxic and represented a range 

of viscosities and likely retention on the hands. 

Five exposure conditions were tested to simulate 

activities in which consumers’ hands may be exposed 

to liquids, including (1) contact with dry skin (initial 

contact), (2) contact with skin previously exposed to 

the liquid and still wet (secondary contact), 

(3) immersion of a hand into a liquid, (4) contact 

from handling a wet rag, and (5) contact during spill 

cleanup. For the initial contact scenario, a cloth 

saturated with liquid was rubbed over the front and 

back of both clean, dry hands for the first time during 

an exposure event. For the secondary contact 

scenario, a cloth saturated with liquid was rubbed 

over the front and back of both hands for a 

second time, after as much as possible of the liquid 

that adhered to skin during the first contact event was 

removed using a clean cloth. For the immersion 

scenario, one hand was immersed in a container of 

liquid and then removed; the liquid was allowed to 

drip back into the container for 30 seconds 

(60 seconds for cooking oil). For the scenario 

involving the handling of a rag, a cloth saturated with 

liquid was rubbed over the palms of both hands in a 

manner simulating handling of a wet cloth. For the 

spill cleanup scenario, a subject used a clean cloth to 

wipe up 50 mL of liquid poured onto a plastic 

laminate countertop. For each of the five scenarios, 

retention was measured immediately after applying 

the liquid to the hands and after partial and full 

removal by wiping. Partial wiping was defined as 

“lightly [wiping with a removal cloth] for 5 seconds 

(superficially).” Full wiping was defined as 

“thoroughly and completely as possible within 

10 seconds removing as much liquid as possible.” 

Four human subjects were used in the experiments, 

and multiple replicates (four to six) were conducted 

for each subject and type of liquid and exposure 

condition. Retention of liquids on the skin was 

estimated by taking the difference between the 

weight of the cloth(s) before and after wiping and 

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dividing by skin surface area. For the immersion 

scenario, retention was estimated as the weight 

difference in the immersion container before and 

after immersion. Film thickness (cm) was estimated 

as the amount of liquid retained on the skin (g/cm2

) 

divided by the density of the liquid (g/cm3

) used in 

the experiment. 

Table 7-24 presents the estimated film thickness 

data from these experiments. Film thickness data may 

be used with information on the density of a liquid 

and the weight fraction of the chemical in the liquid 

to estimate the amount of contaminant retained on the 

skin (i.e., amount retained on skin [g/cm2

] = film 

thickness of liquid on skin [cm] × density of liquid 

[g/cm3

] × weight fraction [unitless]). Dermal 

exposure (g/event) may be estimated as the amount 

retained on the skin (g/cm2

) times the skin surface 

area exposed (cm2

/event). 

The advantage of this study is that it provides data 

for a factor for which information is very limited. 

Data are provided for various types of liquids under 

various conditions. However, the data are based on a 

limited number of observations and may not be 

representative of all types of exposure scenarios. 

7.6. RESIDUE TRANSFER 

Several methods have been developed to quantify 

rates of residue transfer to the human skin of 

individuals performing activities on treated surfaces. 

These methods have been used to either develop 

transfer efficiencies or estimate residue transfer 

coefficients. Transfer efficiencies are the fraction (or 

percentage) of surface residues transferred to the 

skin. Transfer coefficients (cm2

/hour) represent the 

ratio of the dermal exposure during a specified time 

period (mg/hour) based on a specific exposure 

activity (e.g., harvesting a crop or performing indoor 

or outdoor activities) to the environmental 

concentration of the pesticide (mg/cm2

). Transfer 

coefficients are estimated in studies in which 

environmental residue levels are measured 

concurrently with exposure levels for particular job 

functions or activities. These studies have been 

conducted primarily for the purpose of estimating 

exposure to pesticides. Exposure levels are typically 

measured using dosimeter clothing that is worn by 

study subjects during the conduct of specific 

activities and then removed and analyzed for 

pesticide residues. Sometimes biomonitoring studies 

(i.e., urine analyses) or other methods (e.g., hand 

wash) are used to estimate exposure levels. 

Environmental residues are estimated using various 

techniques, including use of deposition coupons, 

wipe samples, or a residue collection tool such as a 

“drag sled” or roller on indoor or outdoor surfaces, as 

described in U.S. EPA (1998). 

Although chemical-specific transfer coefficients 

are typically preferred for estimating exposure, 

U.S. EPA (2009) has used data from published and 

unpublished residue transfer studies to develop some 

generic activity-specific transfer coefficient 

assumptions to use in exposure assessments when 

chemical-specific data are unavailable. Use of these 

generic transfer coefficients for pesticides is based on 

the assumption that the transfer of residues to human 

skin is based primarily on the types of activities being 

performed rather than on the specific characteristics 

of the pesticide. This section presents data for 

published residue transfer studies only (i.e., 

unpublished data are not included here). 

A transfer coefficient, expressed in units of 

cm2

/hour, is used to estimate exposure to chemical 

residues by combining it with the environmental 

concentration (in units of mg/cm2

) and an exposure 

time in hours/days (e.g., exposure [mg/day] = transfer 

coefficient [cm2

/hour] × environmental concentration 

[mg/cm2

] × exposure time [hours/day]). When using 

transfer co-efficients, it is important to ensure that the 

residue levels used are consistent with the method for 

developing the transfer coefficient (e.g., residue 

levels based on deposition coupons should be used 

with transfer co-efficients based on deposition 

coupons; residue levels based on a residue collection 

tool such as the California Roller should be used with 

transfer coefficients based on the same type of tool). 

Information on methods that may be used to estimate 

transferrable residues from indoor surfaces and 

dislodgeable residues from turf may be found in Hsu 

et al. (1990), Geno et al. (1996), Camann et al. 

(1996), Fortune (1998a, b), and Fortune et al. (2000). 

U.S. EPA (2009) describes the use of generic transfer 

coefficients for a variety of activities involving 

pesticides. Section 7.6.1 discusses the published data 

on transfer efficiencies and transfer coefficients 

gathered from the scientific literature. Because 

residue transfer depends on the specific conditions 

under which exposure occurs (e.g., activity, contact 

surfaces, age), the studies described in Section 7.6.1 

have not been categorized as key or relevant, and 

specific recommendations are not provided for this 

factor. 

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7.6.1. Residue Transfer Studies 

7.6.1.1.	 Ross et al. (1990)—Measuring Potential 

Dermal Transfer of Surface Pesticide 

Residue Generated From Indoor Fogger 

Use: An Interim Report 

Ross et al. (1990) utilized choreographed exercise 

routines to measure the amount of pesticide residues 

that may be transferred from carpets to adult skin. 

Five adult volunteers wore dosimeter clothing (i.e., 

cotton tight, shirt, gloves, and socks) over the skin 

areas that normally would be exposed and conducted 

exercise routines for 18.2 minutes in hotel rooms 

where pesticides (i.e., chlorpyrifos and d-transallethrin) were applied (20 minutes total exposure to 

account for entry and exit from the treated rooms). 

The exercise routines were performed at times 

ranging from 0 to 13 hours after pesticide application. 

The routines included “substantial body contact 

between the subject and treated carpet” and were 

“intended to represent a person’s day-long 

(16 hours]) contact with pesticide-treated surfaces in 

a home in which a total discharge fogger had been 

used” (Krieger et al., 2000). The dosimeter clothing 

was assumed to retain the same amount of pesticide 

as the skin (Krieger et al., 2000). It was collected and 

analyzed for pesticide residues to estimate the 

amount of residues that had been transferred from the 

carpet the skin. Environmental concentrations of the 

pesticides were measured in the rooms where the 

exercise routines took place by using gauze coupons 

placed in the rooms prior to pesticide application. 

Ross et al. (1990) found that the transfer of 

pesticides (i.e., potential dermal exposure) differed 

according to the body part exposed and declined with 

time after pesticide application with a rapid decline in 

pesticide transfer between 6 and 12 hours. Some of 

the possible factors attributed to this decline were 

loss of formulation inerts, absorption by or 

adsorption to the carpet, breakdown to non-detected 

materials, downward migration into non-contact 

areas of the carpet or adsorption to dust particles, and 

volatilization. Table 7-25 provides the mean transfer 

efficiencies (i.e., percent of pesticide residues 

transferred to the various body parts from carpet), 

based on the time after application. These 

percentages represent the clothing residues divided 

by the environmental concentrations—based on 

deposition coupons—times 100 (Ross, 1990). 

The study demonstrated the efficacy of using 

choreographed activities to estimate pesticide residue 

transfer. A limitation of this study is that the exercise 

routines used may not be representative of other 

types of indoor activities. 

7.6.1.2.	 Ross et al. (1991)—Measuring Potential 

Dermal Transfer of Surface Pesticide 

Residue Generated From Indoor Fogger 

Use: Using the CDFA Roller Method: 

Interim Report II 

Ross et al. (1991) reported on the use of the 

California Food and Drug Administration (CDFA) 

roller to estimate pesticide transfer from carpet. This 

study was conducted in parallel with the Ross et al. 

(1990) study. The roller device was tested as a 

surrogate for human subjects for measuring residue 

transfer from indoor surfaces. The roller was a 12-kg, 

foam-covered rolling cylinder equipped with 

stationary handles. A cotton cloth covered with 

plastic was placed over a pesticide-treated carpet, and 

the device was rolled over it 10 times. The cloth then 

was collected and analyzed for pesticide residues. 

Environmental residue levels were measured using 

gauze coupons placed on the carpet prior to pesticide 

application. Mean gauze dosimeter residues were 

compared to the amount of material transferred to the 

roller sheet. The results showed that the carpet roller 

method transferred 1 to 3% of carpet residue to the 

roller sheet. As in the 1990 study, pesticide 

transferability decreased with time and with contact 

with the treated surface. Using the data from Ross 

et al. (1990), which involved the collection of 

pesticide residues on dosimeter clothing worn by 

human subjects who engaged in choreographed 

exercise routines, and the roller data from this study, 

Ross et al. (1991) calculated residue transfer 

coefficients as the total μg of residues transferred to 

dosimetry clothing times hours of exposure/μg/cm2 

residue transferred to the roller sheet. Mean transfer 

coefficients were 200,000 ± 50,000 cm2

/hr for 

chlorpyrifos and 140,000 ± 30,000 cm2

/hr for d-trans 

allethrin. Ross et al. (1991) concluded that the use of 

a carpet roller was a good surrogate for measuring 

residue transfer. 

A limitation of this study is that transfer of 

surface residues from the carpet to CDFA roller may 

not be representative of transfer of residues based on 

various human activities. 

7.6.1.3.	 Formoli (1996)—Estimation of Exposure 

of Persons in California to Pesticide 

Products That Contain Propetamphos 

Formoli (1996) conducted a study to estimate 

exposure to propetamphos that was applied to 

carpets. Five adult subjects (two men and 

three women) wore whole body dosimeters and 

performed structured exercise routines for 20 minutes 

on the treated carpet. The subjects’ clothing was cut 

up and analyzed for pesticide residues. Transferable 

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residues also were collected from the carpet by 

moving a roller device over cotton cloth that was 

subsequently analyzed for pesticide residues. Using 

the dermal exposure data from the dosimeters and the 

transferable residue data from the roller device, 

Formoli (1996) calculated a transfer coefficient of 

43,800 cm2

/hr. 

These data are useful because they provide 

perspective on residue transfer data based on 

controlled experimental conditions. However, the 

limitations of this study are that the exercise routines 

used may not be representative of all types of 

activities in which transfer of surface residues occurs, 

and the data are based on a single pesticide and a 

limited number of observations. 

7.6.1.4.	 Krieger et al. (2000)—Biomonitoring and 

Whole Body Dosimetry to Estimate 

Potential Human Dermal Exposure to 

Semi-Volatile Chemicals 

Krieger et al. (2000) conducted a study similar to 

the Ross et al. (1991; 1990) studies. The purpose of 

the Krieger et al. (2000) study was to compare 

dermal exposure estimated by four different methods. 

The methods included (1) measurement of residues 

deposited onto foil coupons that had been placed on 

the carpet prior to pesticide application; 

(2) measurement of residues transferred to cotton 

cloth using the CDFA roller method, as described by 

Ross et al. (1991); (3) measurement of residues 

transferred to whole body cotton dosimeters during 

structured exercise routines; and (4) analysis of 

biomonitoring (urine) from subjects who participated 

in structured activities wearing either cotton whole 

body dosimeters or swimsuits. A total of 13 subjects 

wore whole body dosimeters while 21 subjects wore 

bathing suits. Foggers containing the pesticide 

chlorpyrifos were discharged from the centers of 

two identical rectangular meeting rooms at the 

University of California, Riverside. The rooms were 

kept unventilated for 2 hours and then were opened 

with a room divider removed during 30 minutes of 

ventilation. Surface deposition and dislodgeable 

residues were measured with three aluminum foil 

coupons and cotton sheets placed at two, four, and 

six feet from each fogger. The exercise routines were 

the same as those used in Ross et al. (1990). 

Biomonitoring was conducted by collecting 

four successive 24-hour urine samples from each 

subject 1 day prior to exposure and 3 days after 

exposure to chlorpyrifos. 

The average amounts of pesticide transferred to 

the dosimeters were 0.27 μg/cm2 based on the CDFA 

roller method and 0.73 μg/cm2 based on the whole 

body dosimetry method. These transfer amounts 

represent 7.5% and 20.2%, respectively, of the 

average concentration of pesticide on the surface of 

the carpet (3.6 μg/cm2

) based on the deposition 

coupons. Calculating the transfer coefficient in the 

same way as Ross et al. (1991), the mean transfer 

coefficient would be approximately 154,000 cm2

/hr 

(13,758 μg of residues transferred to dosimetry 

clothing per 0.33 hour of exposure/0.27 μg/cm2 

residue transferred to the roller sheet). Using the 

concentration of residues on the deposition coupons 

instead of those transferred to the roller cloth as the 

environmental concentration would give a transfer 

coefficient of approximately 12,000 cm2

/hr 

(13,758 μg of residues transferred to dosimetry 

clothing per 0.33 hour of exposure/3.6 μg/cm2 

residue deposited on the carpet). Absorbed doses and 

biomonitoring data reported by Krieger et al. (2000) 

are not summarized because the data are specific to 

the pesticide (chlorpyrifos) studied. However, the 

biomonitoring data indicate that “both types of 

dosimeters [roller cloth and whole body] removed 

substantially more [pesticide] than was transferred 

and absorbed by human skin” (Krieger et al., 2000). 

The advantage of this study is that it compared 

estimates of pesticide residue transfer using a variety 

of methods. However, the results are based on a 

single pesticide and may not be representative of 

other chemicals or activities that may result in 

exposure. 

7.6.1.5.	 Clothier (2000)—Dermal Transfer 

Efficiency of Pesticides From New, Vinyl 

Sheet Flooring to Dry and Wetted Palms 

Clothier (2000) compared the transfer of pesticide 

residues from vinyl flooring to dry, water-wetted, and 

saliva-wetted hands. Three different pesticides were 

used in the study (chlorpyrifos, piperonyl butoxide, 

and pyrethrin). Three male subjects participated in 

the study by pressing their hand palm down on the 

vinyl surface. Prior to performing the hand presses, 

the hands were either treated with a sample of their 

own saliva or water or received no pretreatment (dry 

hands). Transferable residues also were collected 

using the polyurethane foam (PUF) roller method 

described by Camann et al. (1996). Deposition 

coupons also were used to measure the amount of 

pesticide applied to the flooring. Transfer efficiencies 

were estimated as the rate of transfer to hands or PUF 

roller (μg/cm2

) /mean surface loading (μg/cm2) times 

100. Table 7-26 presents the transfer efficiencies 

from this study. Transfer efficiencies were higher for 

wetted palms than for dry palms and for the PUF 

roller than for dry hands. 

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The advantage of this study is that it provides 

perspective on the effects of hand moisture on residue 

transfer. The data are based on three pesticides 

applied to vinyl surfaces and a limited number of 

subjects under controlled experimental conditions. 

However, the data may not reflect transfer associated 

with other chemicals or activities. 

7.6.1.6.	 Bernard et al. (2001)—Environmental 

Residues and Biomonitoring Estimates of 

Human Insecticide Exposure From 

Treated Residential Turf 

Bernard et al. (2001) conducted a study similar to 

those conducted by Ross et al. (1990) and Krieger 

et al. (2000), except that the exercise routines were 

conducted on pesticide-treated turf instead of on 

pesticide-treated carpets. Exposure was measured by 

analyzing whole body dosimeters worn by female 

participants during 20 minutes of exercise that 

occurred approximately 3.5 hours after pesticide had 

been applied to the turf. Pesticide deposition was 

estimated by collecting and analyzing cotton coupons 

present at the time of application. Dislodgeable 

residues were measured by collecting and rinsing 

foliage samples in an aqueous solution, and 

transferable turf residues were estimated using the 

CDFA roller 0, 1, and 3 days after application. Turf 

residues based on spray deposition (i.e., coupons), 

dislodgeable (aqueous wash) residues, and 

transferable (roller) residues were 12, 3.4, and 

0.085 μg/cm2

, respectively. This suggests that 

dislodgeable residues were approximately 28% of the 

deposition residues, and transferable residues were 

less than 1% of the deposition residues. Bernard et al. 

(2001) estimated that exposures based on transferable 

residues and those based on whole body dosimetry 

would be similar because transferable residues based 

on whole body dosimetry and those based on the 

roller technique were similar. 

This study provides perspective on residue 

transfer from treated turf. However, the data are for a 

single pesticide and may not be representative of 

other chemical substances or exposure conditions. 

7.6.1.7.	 Cohen Hubal et al. 

(2005)―Characterizing Residue Transfer 

Efficiencies Using a Fluorescent Imaging 

Technique 

Cohen Hubal et al. (2005) used a fluorescent 

tracer method to evaluate the factors that affect the 

transfer of residues from indoor surfaces to the hands. 

The non-toxic fluorescent tracer vitamin B2 riboflavin 

was applied to carpet and laminate flooring. 

Two levels of analyte loading were evaluated in the 

study (2 μg/cm2 and 10 μg/cm2

). Three adult subjects 

participated in a series of controlled experiments in 

which the hands contacted the treated surfaces using 

one of two different levels of pressure for one of 

two different durations. Transfer as a result of 

multiple sequential contacts also was evaluated. The 

hands were characterized as dry, moist, or sticky prior 

to conducting the hand presses on the treated flooring 

materials. To simulate moist hands, the hands were 

placed under a cool mist vaporizer for 20 seconds; to 

simulate sticky conditions, 1.2 grams of Karo Syrup 

was applied to the hands. Dermal loading on the 

hands was measured by using a fluorescence imaging 

system. Transfer efficiencies were estimated by 

dividing the mass of tracer on the hand per unit 

surface area (μg/cm2

) divided by the loading of tracer 

on the carpet or laminate surface (μg/cm2

) times 100. 

Incremental transfer efficiency was calculated 

separately for each individual contact, whereas 

overall transfer efficiency was calculated 

cumulatively for the series of contacts. Table 7-27 

provides the incremental and overall transfer 

efficiencies based on the hand conditions, the surface 

type, the surface loading, and the number of contacts. 

Based on the data in Table 7-27, the mean transfer 

efficiency after a single contact ranged from 3 to 14% 

for dry and sticky hands, respectively. According to 

Cohen Hubal et al. (2005), surface loading and skin 

condition were important parameters in 

characterizing transfer efficiency, but duration of 

contact and pressure did not have a significant effect 

on transfer. 

An advantage of this study is that it uses a tracer 

method to estimate transfer efficiency from surfaces 

to human skin. It also provides perspective on various 

conditions that may affect transfer efficiency. A 

limitation is that the data may not reflect transfer 

associated with specific chemicals or activities. 

7.6.1.8.	 Hubal et al. (2008)—Comparing Surface 

Residue Transfer Efficiencies to Hands 

Using Polar and Non-Polar Fluorescent 

Transfer 

As a follow up to the Cohen Hubal et al. (2005) 

study, Hubal et al. (2008) conducted a study using a 

second fluorescent tracer, Uvitex OB, which has 

different physical-chemical properties than 

riboflavin. The fluorescent tracer, which was used as 

a surrogate for pesticide residues, was applied to 

carpet or laminate surfaces at two different loading 

levels, and controlled hand transfer experiments were 

conducted by using various pressures and motions 

(i.e., press and smudge), numbers of contacts, and 

different hand conditions (i.e., dry or moist). The 

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mass of tracer transferred to the hands was measured 

using a fluorescent tracer imaging system. The results 

indicated that “overall percent transfer ranged from 

0.8 to 45.5% for the first contact and 0.6 to 19.4% for 

the seventh contact,” and dermal loadings increased 

in a near linear fashion through the seventh contact. 

“Transfer was greater for laminate (over carpet), 

smudge (over press), and moist (over dry)” (Hubal et 

al., 2008). For lower surface loadings, dermal transfer 

increased through the seventh contact, suggesting that 

multiple contacts may be required to reach an 

effective equilibrium with the surface. 

Similar to the previous study, the advantage of 

these data is that they are based on tracers and 

provide information on factors affecting residue 

transfer. However, the data may or may not 

accurately reflect transfer for specific chemicals or 

activities. 

7.6.1.9.	 Beamer et al. (2009)—Developing 

Probability Distributions for Transfer 

Efficiencies for Dermal Exposure 

Beamer et al. (2009) combined data from 

nine residue transfer studies and developed 

distributions for three pesticides (chlorpyrifos, 

pyrethrin I, and piperonyl butoxide) and three surface 

types (foil, vinyl, and carpet). The studies used for 

developing these distributions included Hsu et al. 

(1990), Ross et al. (1991), Camann et al. (1996; 

1995), Geno et al. (1996), Fortune (1998a, b), 

Clothier (2000), and Krieger et al. (2000). Beamer 

et al. (2009) stratified the data by chemical and 

surface type. Statistical methods were used to 

develop the distributions, based on combined data 

from studies that used different sampling methods, 

surface concentrations, formulations, sampling time, 

and skin conditions (i.e., dry or wet). Transfer 

efficiencies were defined as the amount transferred to 

skin or a transfer media used as a surrogate for skin 

divided by the amount of pesticide applied to the 

surface. 

Table 7-28 presents the lognormal parameter 

values for the three chemicals and three surface types 

evaluated. The results of statistical analyses indicated 

that the distributions of transfer efficiencies were 

statistically different for the surface types and 

chemicals shown in Table 7-28. Transfer efficiency 

was highest for foil for all chemicals, followed by 

vinyl and carpet. For example, the geometric mean 

transfer efficiencies ranged from 0.01 to 0.02 (i.e., 1 

to 2%) for carpet, 0.03 to 0.04 (3 to 4%) for vinyl, 

and 0.83 to 0.86 (83 to 86%) for foil. According to 

Beamer et al. (2009), these distributions can be used 

for modeling transfer efficiencies. 

An advantage of this data set is that it uses data 

from several of the studies described in this chapter 

to develop distributions for three pesticides and 

three surface types. However, there is some 

uncertainty with regard to the representativeness of 

these data for other chemicals or exposure conditions. 

7.7. OTHER FACTORS 

7.7.1. Frequency and Duration of Dermal (Hand) 

Contact 

This section provides information from studies 

that evaluated activities that may affect dermal 

exposure. This includes information on the frequency 

and duration of dermal contact with objects and 

surfaces. Additional information on activities patterns 

and consumer product use that affect the frequency 

and duration of dermal contact is provided in 

Chapters 16 and 17. Information on hand-to-mouth 

contact frequency in presented in Chapter 4. 

7.7.1.1.	 Zartarian et al. (1997)—Quantified 

Dermal Activity Data From a Four-Child 

Pilot Field Study 

Zartarian et al. (1997) conducted a pilot field 

study in California in 1993 to estimate children’s 

dermal contact with objects in their environment. 

Four Mexican American farm worker children ages 2 

to 4 years were videotaped to record their activities 

over a 1-day period. Five to 30% of the children’s 

time was spent outdoors, while the remainder was 

spent indoors. Videotape data were obtained over 6 to 

11 waking hours for the four children (i.e., a total of 

33 hours of videotape). The videotapes were 

translated to provide information about the objects 

that the children contacted, as well as the frequency 

and duration of contact. The data indicated that most 

objects were contacted for approximately 2 to 

3 seconds in duration, and hard surfaces and hard 

toys were touched by children’s hands for the longest 

percent of the time (Zartarian et al., 1997). Table 7-29 

provides the average contact frequency for the left 

and right hands of the four children who participated 

in the study. Frequency of contact was highest for 

hard surfaces and hard toys (see Table 7-29). 

The advantage of this study is that it was the first 

in a series of papers that used video-transcription 

methods to evaluate children’s micro-activities 

relative to potential dermal exposure. However, the 

number of participants in this study (four children) 

was small, and the results may not be representative 

of all U.S. children. 

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7.7.1.2.	 Reed et al. (1999)—Quantification of 

Children’s Hand and Mouthing Activities 

Through a Videotaping Methodology 

Reed et al. (1999) used a videotaping 

methodology similar to that used by Zartarian et al. 

(1997) to quantify the hand contact activities of 

30 children in New Jersey. A total of 20 children ages 

3 to 6 years were observed in daycare facilities, while 

an additional 10 children, ages 2 to 5 years were 

observed in residential settings. Total videotaping 

time ranged from 3 to 7 hours for the daycare 

children and 5 to 6 hours for the residential children. 

Frequency of hand contact with objects and surfaces 

was quantified by recording touches with clothing, 

dirt, objects, and smooth or textured surfaces, as 

observed on video. According to Reed et al. (1999), 

“comparison of activities of children in home settings 

and daycare showed that rates of many of the 

activities did not differ significantly between venues 

and therefore, data from homes and daycare were 

combined.” Table 7-30 presents the hand contact 

frequency data for the 30 children observed in this 

study. High contact frequencies were observed for 

clothing, objects, other, and smooth surfaces. 

The advantages of this study are that more 

children were observed than in the previous study, 

and both daycare and residential children were 

included. However, the children were from a single 

location and may not be representative of all U.S. 

children. 

7.7.1.3.	 Freeman et al. (2001)—Quantitative 

Analysis of Children’s Micro-Activity 

Patterns: The Minnesota Children’s 

Pesticide Exposure Study 

Freeman et al. (2001) conducted a survey 

response and video-transcription study of some of the 

respondents in a phased study of children’s pesticide 

exposures in the summer and early fall of 1997. A 

probability-based sample of 168 families with 

children ages 3 to <14 years old in urban 

(Minneapolis/St. Paul) and non-urban (Rice and 

Goodhue Counties) areas of Minnesota answered 

questions about children’s behaviors that might 

contribute to exposure via dermal contact or 

non-dietary ingestion. Of these 168 families, 19 

agreed to videotaping of the study children’s 

activities for a period of 4 consecutive hours. The 

videotaped children ranged in age from 3 to 12 years 

of age but were divided into four age groups (3 to 

4 years, 5 to 6 years, 7 to 8 years, and 10 to 12 years) 

for the purposes of quantifying microactivities. The 

frequency of touching clothing, textured surfaces 

(e.g., carpets and upholstered furniture), smooth 

surfaces (e.g., wood or plastic furniture, hardwood 

floor), or objects (e.g., toys, pencils, or other things 

that could be manipulated) was quantified by 

observing the behaviors on the videotapes during a 

4-hour observation period. Table 7-31 shows the 

frequency of hand contacts per hour for the 

19 children. 

An advantage to this study is that it included 

results for various ages of children. However, the 

children in this study may not be representative of all 

U.S. children. Also, the presence of unfamiliar 

persons following the children with a video camera 

may have influenced the video-transcription 

methodology results. 

7.7.1.4.	 Freeman et al. (2005)—Contributions of 

Children’s Activities to Pesticide Hand 

Loadings Following Residential Pesticide 

Application 

Freeman et al. (2005) gathered data on hand 

contacts with surfaces and objects as part of a study 

to evaluate pesticide exposure in residential settings. 

A convenience sample of 10 children between the 

ages of 24 and 55 months was selected for videotape 

observation on the 2nd day after their homes were 

treated with pesticides. The children were videotaped 

during a 4-hour period (only three children spent time 

outside the house, with outdoor times ranging from 

21 to 57 minutes). The videotapes were transcribed to 

quantify contact rates in terms of frequency and 

duration. According to Freeman et al. (2005), “the 

duration of contact of most contact events was very 

short (2−3 seconds),” but contact with bottles, food, 

and objects tended to be somewhat longer (median 

durations ranged from 4.5 to 7.5 seconds for these 

items). Table 7-32 presents the right-hand contact 

rates (contacts per hour) for the various objects and 

surfaces. High contact items include objects and 

smooth surfaces. 

The advantage of this study is that it provides 

additional information on hand contact frequency. 

However, the data are based on a limited number of 

children and were collected over a relatively short 

time period. Also, the presence of a video camera 

may have affected the children’s behavior. 

7.7.1.5.	 AuYeung et al. (2006)—Young Children’s 

Hand Contact Activities; an Observational 

Study via Videotaping in Primarily 

Outdoor Residential Settings 

AuYeung et al. (2006) gathered data on children’s 

hand contact activities by videotaping them in 

outdoor residential settings in 1998–1999. A total of 

38 children ages 1 to 6 years from middle class 

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suburban families were recruited from the San 

Francisco Bay peninsula area to participate in the 

study. Each child was videotaped during 2 hours of 

natural (i.e., unstructured) play in an outdoor location 

(i.e., park, playground, outdoor residential area). 

Videotapes then were translated using a software 

package specially designed for this use. Contacts 

were tabulated for 15 object surface categories and 

for all non-dietary objects and all objects and 

surfaces combined. Hourly contact frequency, median 

duration per contact, and hourly contact duration 

were calculated for each child for the left hand, right 

hand, and both hands combined, and summary 

statistics were developed for all children combined. 

Table 7-33 provides the data for outdoor locations. 

According to AuYeung et al. (2006), these data 

suggest that children have a large number of 

short-duration contacts with outdoor objects and 

surfaces. AuYeung et al. (2006) also collected some 

limited data for indoor locations. These data are 

based on nine children who were videotaped for 

15 minutes or more indoors. Table 7-34 provides 

summary data for these children. 

The advantage of this study is that it provides 

dermal (hand) contact data for a wide variety of 

outdoor objects and surfaces. The data for indoor 

environments were limited, however, and the 

presence of unfamiliar persons following the children 

with a video camera may have influenced the 

video-transcription methodology results. 

7.7.1.6.	 Ko et al. (2007)—Relationships of Video 

Assessments of Touching and Mouthing 

Behaviors During Outdoor Play in Urban 

Residential Yards to Parental Perceptions 

of Child Behaviors and Blood Lead Levels 

Ko et al. (2007) used video observation and 

transcription methods to assess children’s hand 

contacts with outdoor surfaces as part of a study to 

assess the relationship between blood level levels and 

children’s activities in urban environments. During 

the summers of 2000 and 2001, a total of 37 children 

ages 1 to 5 years were videotaped during 2-hour 

periods while playing in outdoor urban residential 

settings. The children were primarily from 

low-income, Hispanic families. Ko et al. (2007) 

tabulated surface contacts by reviewing the 

videotapes and counting the number of times a 

child’s hands touched one of the following surfaces: 

(1) cement, stone, or steel on the ground (cement); 

(2) porch floor or porch steps (porch); (3) grass; and 

(4) bare soil. Distributions of contact frequency 

(contacts per hour) were developed using the data for 

the 37 children for the four surface types and for all 

surfaces combined. According to Ko et al. (2007), the 

median contact frequency for all surfaces was 

81 contacts per hour (geometric mean = 70 contacts 

per hour), with several children touching surfaces 

approximately 400 contacts per hour (see Table 

7-35). 

Similar to the AuYeung et al. (2006) study 

described in the previous section, the advantage of 

this study is that it provides data for outdoor dermal 

(hand) contacts with a variety of objects and surfaces. 

These surface types are somewhat different from 

those in AuYeung et al. (2006) but provide additional 

perspective on contact with outdoor surfaces. As with 

all studies that use videotape methods, however, the 

presence of unfamiliar persons following the children 

with a video camera may have influenced the results. 

7.7.1.7.	 Beamer et al. (2008)—Quantified Activity 

Pattern Data From 6 to 27-Month-Old 

Farm Worker Children for Use in 

Exposure Assessment 

Beamer et al. (2008) conducted a study in which 

children were videotaped to estimate contacts with 

objects and surfaces in their environment. A 

convenience sample of 23 children residing in the 

farm worker community of Salinas Valley, CA, 

participated in the study. Participants were 6- to 

13-month-old infants and 20- to 26-month-old 

toddlers. Two researchers videotaped each child’s 

activities for a minimum of 4 hours and kept a 

detailed written log of locations visited and objects 

and surfaces contacted by the child. A questionnaire 

was administered to an adult in the household to 

acquire demographic data, housing and cleaning 

characteristics, eating patterns, and other information 

pertinent to the child’s potential pesticide exposure. 

Table 7-36 presents the mean and median object 

and surface contact frequency in events per hour. The 

most frequently contacted objects included toys 

(121 contacts per hour) and clothing/towels 

(114 contacts per hour). The mean frequency of hand 

contact of all objects and surfaces for both hands 

combined was 686.3 contacts per hour. Table 7-36 

also provides information on the duration of contact 

with these objects and surfaces in minutes per hour 

and in seconds per contact. 

The advantage of this study is that it included 

both infants and toddlers. Also, it provided data for a 

wide variety of objects and surfaces. Differences 

between the two age groups, as well as sex 

differences, were observed. As with other 

video-transcription studies, however, the presence of 

non-family-member videographers and a video 

camera may have influenced the children’s behavior. 

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7.7.2. Thickness of the Skin 

Although factors that influence dermal uptake 

(i.e., absorption) and internal dose are not the focus 

of this chapter, limited information on the 

physiological characteristics of the skin (i.e., 

thickness of the skin on various body parts) is 

presented here to provide some perspective on this 

topic. It should be noted that this is only one factor 

that may influence dermal uptake. Others include the 

condition of the skin (e.g., Williams et al. (2005; 

2004), suggested that the presence of perspiration on 

the skin may affect uptake of contaminants) and 

chemical-specific factors (e.g., concentration of 

chemical in contact with the skin and characteristics 

of the chemical that affect its rate of absorption). 

The skin consists of two distinct layers: the 

epidermis (outermost layer) and dermis. The 

outermost layer of the epidermis is the stratum 

corneum or horny layer. Because the stratum 

corneum serves as the body’s outermost boundary, it 

is the layer where chemical exposures may occur. 

According to the International Commission on 

Radiological Protection (ICRP, 1975), the thickness 

of the stratum corneum of adults is “approximately 

one-tenth that of the epidermis except for palms [of 

hands] and soles [of feet] where it may be much 

thicker.” Over most parts of the body, the stratum 

corneum is estimated to range in thickness from 

about 13 to 15 μm, but it may vary by region of the 

body, with the certain parts (e.g., the “horny pads”) of 

the palms and soles being as high as 600 μm (ICRP, 

1975). Holbrook and Odland (1974) used electron 

microscopy to measure the thickness of the stratum 

corneum from fixed tissues collected from the 

abdomen, back, forearm, and thigh of six subjects 

(three men and three women) ages 25 to 31 years old. 

The mean thicknesses for these four body regions 

were 8.2, 9.4, 12.9, and 10.9 μm, respectively. 

Schwindt et al. (1998) estimated thickness using skin 

at the same four sites in six women with a mean age 

of 33.2 years. Based on calculations from 

measurements of transepidermal water loss during 

tape stripping, mean thicknesses were estimated to be 

7.7 ± 1.7, 11.2 ± 2.6, 12.3 ± 3.6, and 13.1 ± 4.7 μm 

for the abdomen, back, forearm, and thigh, 

respectively (Schwindt et al., 1998). Using 

two methods of calculating thickness, Pirot et al. 

(1998) estimated the thickness of the stratum 

corneum on the forearms of 13 subjects (2 men and 

11 women) between the ages of 23 and 60 years. The 

mean ± standard deviation values were 11.3 ± 5.1 and 

12.6 ± 5.3 μm. Russell et al. (2008) estimated the 

thickness of the stratum corneum on the forearm to 

be approximately 10 μm, based on 18 adults (3 men 

and 15 women) between the ages of 22 and 43 years. 

Egawa et al. (2007) estimated the stratum corneum 

thickness on five body parts of 15 Japanese adults 

(6 men and 9 women) ages 23 to 49 years old. 

Mean ± standard deviation thicknesses were 16.8 ± 

2.8, 21.8 ± 3.6, 22.6 ± 4.3, 29.3 ± 6.8, and 173 ± 37.0 

for the cheek, upper arm, forearm, back of hand, and 

palm of hand, respectively (Egawa et al., 2007). 

For newborn infants, the stratum corneum “is 

extremely thin, but grows rapidly during the 

first month” (ICRP, 1975). Based on measurements 

of newborn skin that was fixed in formalin, thickness 

of the stratum corneum was about 10 μm on the back 

and about 80 to 140 μm on the sole of the foot of 

newborns. Based on measurement using non-fixed, 

fresh, frozen newborn skin, the thickness of the 

stratum corneum ranged from 10 to 50 μm for 

portions of the buttocks and abdomen and most other 

regions of the body except the hands and feet (ICRP, 

1975). 

7.8. REFERENCES FOR CHAPTER 7 

AuYeung, W; Canales, RA; Beamer, P; Ferguson, 

AC; Leckie, JO. (2006). Young children's 

hand contact activities: an observational 

study via videotaping in primarily outdoor 

residential settings. J Expo Sci Environ 

Epidemiol 16: 434-446. 

http://dx.doi.org/10.1038/sj.jes.7500480. 

AuYeung, W; Canales, RA; Leckie, JO. (2008). The 

fraction of total hand surface area involved 

in young children's outdoor hand-to-object 

contacts. Environ Res 108: 294-299. 

http://dx.doi.org/10.1016/j.envres.2008.07.0 

10. 

Beamer, P; Canales, RA; Leckie, JO. (2009). 

Developing probability distributions for 

transfer efficiencies for dermal exposure. J 

Expo Sci Environ Epidemiol 19: 274-283. 

http://dx.doi.org/10.1038/jes.2008.16. 

Beamer, P; Key, ME; Ferguson, AC; Canales, RA; 

Auyeung, W; Leckie, JO. (2008). Quantified 

activity pattern data from 6 to 27-month-old 

farmworker children for use in exposure 

assessment. Environ Res 108: 239-246. 

http://dx.doi.org/10.1016/j.envres.2008.07.0 

07. 

Bernard, CE; Nuygen, H; Truong, D; Krieger, RI. 

(2001). Environmental residues and 

biomonitoring estimates of human 

insecticide exposure from treated residential 

turf. Arch Environ Contam Toxicol 41: 237­

240. 

http://dx.doi.org/10.1007/s002440010243. 

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Boniol, M; Verriest, JP; Pedeux, R; Doré, JF. (2008). 

Proportion of skin surface area of children 

and young adults from 2 to 18 years old. J 

Invest Dermatol 128: 461-464. 

http://dx.doi.org/10.1038/sj.jid.5701032. 

Boyd, E. (1935). The growth of the surface area of 

the human body. Minneapolis, MN: 

University of Minnesota Press. 

http://www.upress.umn.edu/bookdivision/books/the-growth-of-the-surfacearea-of-the-human-body. 

Brainard, J; Burmaster, DE. (1992). Bivariate 

distributions for height and weight of men 

and women in the United States. Risk Anal 

12: 267-275. 

Buhyoff, GJ; Rauscher, HM; Hull, RB; Kolleen, K. 

(1982). User's manual for statistical 

processing system (version 3C.1). Pooler, 

GA: Southeast Technical Associates, Inc. 

Buyken, AE; Hahn, S; Kroke, A. (2005). Differences 

between recumbent length and stature 

measurement in groups of 2- and 3-y-old 

children and its relevance for the use of 

European body mass index references. Int J 

Obes (Lond) 29: 24-28. 

http://dx.doi.org/10.1038/sj.ijo.0802738. 

Camann, D; Harding, H; Geno, PW; Agrawal, SR. 

(1996). Comparison of methods to 

determine dislodgeable residue transfer from 

floors [EPA Report]. (EPA/600/R96/089). 

Research Triangle Park, NC: U.S. 

Environmental Protection Agency. 

Camann, DE; Majundar, TK; Harding, HJ. (1995). 

Comparison of salivary fluids with respect 

to transfer efficiency from carpet to salivamoistened hands. (SWRI Project No. 01­

7131). San Antonio, TX: Southwest 

Research Institute. 

CDC (Centers for Disease Control and Prevention). 

(2006). National Health and Nutrition 

Examination Survey data. Atlanta, GA. 

http://www.cdc.gov/nchs/nhanes.htm. 

Charney, E; Sayre, J; Coulter, M. (1980). Increased 

lead absorption in inner city children: Where 

does the lead come from? Pediatrics 65: 

226-231. 

Choate, LM; Ranville, JF; Bunge, AL; Macalady, DL. 

(2006). Dermally adhered soil: 1. Amount 

and particle-size distribution. Integr Environ 

Assess Manag 2: 375-384. 

Clothier, JM.	 (2000). Dermal transfer efficiency of 

pesticides from new, vinyl sheet flooring to 

dry and wetted palms [EPA Report]. 

(EPA/600/R-00/029). Research Triangle 

Park, NC: U.S. Environmental Protection 

Agency. 

Cohen Hubal, EA; Suggs, JC; Nishioka, MG; 

Ivancic, WA. (2005). Characterizing residue 

transfer efficiencies using a fluorescent 

imaging technique. J Expo Anal Environ 

Epidemiol 15: 261-270. 

http://dx.doi.org/10.1038/sj.jea.7500400. 

Costeff, H. (1966). A simple empirical formula for 

calculating approximate surface area in 

children. Arch Dis Child 41: 681-683. 

D'Agostino, RB; Belanger, A. (1990). A Suggestion 

for Using Powerful and Informative Tests of 

Normality. Am Stat 44: 316. 

http://dx.doi.org/10.2307/2684359. 

Driver, JH; Konz, JJ; Whitmyre, GK. (1989). Soil 

adherence to human skin. Bull Environ 

Contam Toxicol 43: 814-820. 

Du Bois, D; Du Bois, EF. (1989). A formula to 

estimate the approximate surface area if 

height and weight be known. 1916. Nutrition 

5: 303-311; discussion 312-303. 

Duggan, MJ; Inskip, MJ; Rundle, SA; Moorcroft, JS. 

(1985). Lead in playground dust and on the 

hands of schoolchildren. Sci Total Environ 

44: 65-79. http://dx.doi.org/10.1016/0048­

9697(85)90051-8. 

Edwards, RD; Lioy, PJ. (2001). Influence of sebum 

and stratum corneum hydration on 

pesticide/herbicide collection efficiencies of 

the human hand. Appl Occup Environ Hyg 

16: 791-797. 

http://dx.doi.org/10.1080/10473220119787. 

Egawa, M; Hirao, T; Takahashi, M. (2007). In vivo 

estimation of stratum corneum thickness 

from water concentration profiles obtained 

with Raman spectroscopy. Acta Derm 

Venereol 87: 4-8. 

http://dx.doi.org/10.2340/00015555-0183. 

Ferguson, A; Bursac, Z; Coleman, S; Johnson, W. 

(2009a). Comparisons of computercontrolled chamber measurements for soilskin adherence from aluminum and carpet 

surfaces. Environ Res 109: 207-214. 

http://dx.doi.org/10.1016/j.envres.2008.12.0 

11. 

Ferguson, AC; Biddle, D; Coleman, S; Bursac, Z; 

Johnson, W. (2009b). In-vitro soil adherence 

for dermal exposure using a controlled 

mechanical chamber. Journal of Applied 

Sciences Research 5: 232-243. 

Ferguson, AC; Bursac, Z; Biddle, D; Coleman, S; 

Johnson, W. (2008). Soil-skin adherence 

from carpet: Use of a mechanical chamber 

to control contact parameters. J Environ Sci 

Health A Tox Hazard Subst Environ Eng 43: 

Exposure Factors Handbook Page
 

November 2011 7-33 
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

1451-1458. 

http://dx.doi.org/10.1080/109345208022322 

53. 

Ferguson, AC; Bursac, Z; Coleman, S; Johnson, W. 

(2009c). Computer Controlled Chamber 

Measurements for Multiple Contacts for 

Soil-Skin Adherence from Aluminum and 

Carpet Surfaces. Hum Ecol Risk Assess 15: 

811-830. 

http://dx.doi.org/10.1080/108070309030512 

83. 

Finley, BL; Scott, PK; Mayhall, DA. (1994). 

Development of a standard soil‐to‐skin 

adherence probability density function for 

use in Monte Carlo analyses of dermal 

exposure. Risk Anal 14: 555-569. 

Formoli, TA. (1996). Estimation of exposure of 

persons in California to pesticide products 

that contain proptamphos. (HS-1731). 

Sacramento, CA: California Environmental 

Protection Agency. 

Fortune, CR. (1998a). Evaluation of methods for 

collecting dislodgeable pesticide residues 

from turf. (EPA/600/R97/119). Research 

Triangle Park, NC: U.S. Environmental 

Protection Agency. 

Fortune, CR. (1998b). Round-robin testing of 

methods for collecting dislodgeable residues 

from carpets. (EPA/600/R97/107). Research 

Triangle Park, NC: U.S. Environmental 

Protection Agency. 

Fortune, CR; Blanchard, FT; Elleson, WD; Lewis, 

RG. (2000). Analysis of aged in-home 

carpeting to determine the distribution of 

pesticide residues between dust, carpet, and 

pad compartments [EPA Report]. 

(EPA/600/R-00/030). Research Triangle 

Park, NC: U.S. Environmental Protection 

Agency. 

Freeman, NCG; Hore, P; Black, K; Jimenez, M; 

Sheldon, L; Tulve, N; Lioy, PJ. (2005). 

Contributions of children's activities to 

pesticide hand loadings following residential 

pesticide application. J Expo Sci Environ 

Epidemiol 15: 81-88. 

Freeman, NCG; Jimenez, M; Reed, KJ; Gurunathan, 

S; Edwards, RD; Roy, A; Adgate, JL; 

Pellizzari, ED; Quackenboss, J; Sexton, K; 

Lioy, PJ. (2001). Quantitative analysis of 

children's microactivity patterns: the 

Minnesota children's pesticide exposure 

study. J Expo Sci Environ Epidemiol 11: 

501-509. 

Gallacher, JEJ; Elwood, PC; Phillips, KM; Davies, 

BE; Jones, DT. (1984). Relation between 

pica and blood lead in areas of differing lead 

exposure. Arch Dis Child 59: 40-44. 

Garlock, TJ; Shirai, JH; Kissel, JC. (1999). Adult 

responses to a survey of soil contact-related 

behaviors. J Expo Anal Environ Epidemiol 

9: 134-142. 

Gehan, EA; George, SL. (1970). Estimation of 

human body surface area from height and 

weight. 54: 225-235. 

Geno, PW; Camann, DE; Harding, HJ; Villalobos, K; 

Lewis, RG. (1996). Handwipe sampling and 

analysis procedure for the measurement of 

dermal contact with pesticides. Arch 

Environ Contam Toxicol 30: 132-138. 

Harger, JRE. (1979). A model for the determination 

of an action level for removal of curene 

contaminated soil. Memorandum to P.S 

Cole, Executive Director. Lansing MI Toxic 

Substances Control Commission, October 

25, 1979. Available online at (accessed 

Holbrook, KA; Odland, GF. (1974). Regional 

differences in the thickness (cell layers) of 

the human stratum corneum: an 

ultrastructural analysis. J Invest Dermatol 

62: 415-422. 

Holmes, K; Kissel, J; Richter, K. (1996). 

Investigation of the influence of oil on soil 

adherence to skin. Journal of Soil 

Contamination 5: 301-308. 

Holmes, KK; Shirai, JH; Richter, KY; Kissel, JC. 

(1999). Field measurement of dermal soil 

loadings in occupational and recreational 

activities. Environ Res 80: 148-157. 

http://dx.doi.org/10.1006/enrs.1998.3891. 

Hsu, JP; Camann, DE; Schattenberg, H, III; Wheeler, 

B; Villalobos, K; Kyle, M; Quarderer, S; 

Lewis, RG. (1990). New dermal exposure 

sampling technique. In Measurement of 

toxic and related air pollutants. Pittsburgh, 

PA: Air & Waste Management Association. 

Hubal, EA; Nishioka, MG; Ivancic, WA; Morara, M; 

Egeghy, PP. (2008). Comparing surface 

residue transfer efficiencies to hands using 

polar and nonpolar fluorescent tracers. 

Environ Sci Technol 42: 934-939. 

ICRP (International Commission on Radiological 

Protection). (1975). Report of the task group 

on reference man: ICRP publication 23. 

New York, NY: International Commission of 

Radiological Protection, Pergamon Press. 

http://dx.doi.org/10.1016/0146­

6453(80)90047-0. 

Kissel,	 JC; Richter, KY; Fenske, RA. (1996a). 

Factors affecting soil adherence to skin in 

Page Exposure Factors Handbook 

7-34 November 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

hand-press trials. Bull Environ Contam 

Toxicol 56: 722-728. 

Kissel, JC; Richter, KY; Fenske, RA. (1996b). Field 

measurement of dermal soil loading 

attributable to various activities: 

implications for exposure assessment. Risk 

Anal 16: 115-125. 

Kissel, JC; Shirai, JH; Richter, KY; Fenske, RA. 

(1998). Investigation of dermal contact with 

soil in controlled trials. Journal of Soil 

Contamination 7: 737-752. 

Ko, S; Schaefer, PD; Vicario, CM; Binns, HJ; Safer 

Yards, P. (2007). Relationships of video 

assessments of touching and mouthing 

behaviors during outdoor play in urban 

residential yards to parental perceptions of 

child behaviors and blood lead levels. J 

Expo Sci Environ Epidemiol 17: 47-57. 

http://dx.doi.org/10.1038/sj.jes.7500519. 

Krieger, RI; Bernard, CE; Dinoff, TM; Fell, L; 

Osimitz, TG; Ross, JH; Ongsinthusak, T. 

(2000). Biomonitoring and whole body 

cotton dosimetry to estimate potential 

human dermal exposure to semivolatile 

chemicals. J Expo Anal Environ Epidemiol 

10: 50-57. 

Lepow, ML; Bruckman, L; Gillette, M; Markowitz, 

S; Robino, R; Kapish, J. (1975). 

Investigations into sources of lead in the 

environment of urban children. Environ Res 

10: 415-426. 

Murray, DM; Burmaster, DE. (1992). Estimated 

distributions for total body surface area of 

men and women in the United States. J Expo 

Anal Environ Epidemiol 2: 451-461. 

Phillips, LJ; Fares, RJ; Schweer, LG. (1993). 

Distributions of total skin surface area to 

body weight ratios for use in dermal 

exposure assessments. J Expo Anal Environ 

Epidemiol 3: 331-338. 

Pirot, F; Berardesca, E; Kalia, YN; Singh, M; 

Maibach, HI; Guy, RH. (1998). Stratum 

corneum thickness and apparent water 

diffusivity: facile and noninvasive 

quantitation in vivo. Pharm Res 15: 492­

494. 

Que Hee,	 SS; Peace, B; Clark, CS; Boyle, JR; 

Bornschein, RL; Hammond, PB. (1985). 

Evolution of efficient methods to sample 

lead sources, such as house dust and hand 

dust, in the homes of children. Environ Res 

38: 77-95. http://dx.doi.org/10.1016/0013­

9351(85)90074-X. 

Reed, KJ; Jimenez, M; Freeman, NC; Lioy, PJ. 

(1999). Quantification of children's hand 

and mouthing activities through a 

videotaping methodology. J Expo Anal 

Environ Epidemiol 9: 513-520. 

Riley, WJ; Mckone, TE; Cohen Hubal, EA. (2004). 

Estimating contaminant dose for intermittent 

dermal contact: model development, testing, 

and application. Risk Anal 24: 73-85. 

http://dx.doi.org/10.1111/j.0272­

4332.2004.00413.x. 

Rodes, CE; Newsome, JR; Vanderpool, RW; Antley, 

JT; Lewis, RG. (2001). Experimental 

methodologies and preliminary transfer 

factor data for estimation of dermal 

exposures to particles. J Expo Anal Environ 

Epidemiol 11: 123-139. 

Roels, HA; Buchet, JP; Lauwerys, RR; Bruaux, P; 

Claeys-Thoreau, F; Lafontaine, A; Verduyn, 

G. (1980). Exposure to lead by the oral and 

the pulmonary routes of children living in 

the vicinity of a primary lead smelter. 

Environ Res 22: 81-94. 

Ross, J. (1990). Measuring potential dermal transfer 

of surface pesticide residue generated from 

indoor fogger use: An interim report. 

Chemosphere 20: 349-360. 

http://dx.doi.org/10.1016/0045­

6535(90)90066-3. 

Ross, J; Fong, HR; Thongsinthusak, T; Margetich, S; 

Krieger, R. (1991). Measuring potential 

dermal transfer of surface pesticide residue 

generated from indoor fogger use: using the 

CDFA roller method; interim report II. 

Chemosphere 22: 975-984. 

Russell, LM; Wiedersberg, S; Delgado-Charro, MB. 

(2008). The determination of stratum 

corneum thickness: an alternative approach. 

Eur J Pharm Biopharm 69: 861-870. 

http://dx.doi.org/10.1016/j.ejpb.2008.02.002 

. 

Schwindt, DA; Wilhelm, KP; Maibach, HI.	 (1998). 

Water diffusion characteristics of human 

stratum corneum at different anatomical 

sites in vivo. J Invest Dermatol 111: 385­

389. http://dx.doi.org/10.1046/j.1523­

1747.1998.00321.x. 

Sedman, RM. (1989).	 The development of applied 

action levels for soil contact: a scenario for 

the exposure of humans to soil in a 

residential setting. Environ Health Perspect 

79: 291-313. 

Shoaf, MB; Shirai, JH; Kedan, G; Schaum, J; Kissel, 

JC. (2005a). Adult dermal sediment loads 

following clam digging in tide flats. Soil 

Sediment Contam 14: 463-470. 

http://dx.doi.org/10.1080/153203805001805 

Exposure Factors Handbook Page
 

November 2011 7-35 
Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 

7-36 November 2011 

15. 

Shoaf, MB; Shirai, JH; Kedan, G; Schaum, J; Kissel, 

JC. (2005b). Child dermal sediment loads 

following play in a tide flat. J Expo Anal 

Environ Epidemiol 15: 407-412. 

http://dx.doi.org/10.1038/sj.jea.7500418. 

Snodgrass, HL. (1992). Permethrin transfer from 

treated cloth to the skin surface: potential for 

exposure in humans. J Toxicol Environ 

Health 35: 91-105. 

http://dx.doi.org/10.1080/152873992095315 

98. 

Snyder, RG; Schneider, LW; Owings, CL.	 (1978). 

Infant, child and teenager anthropometry for 

product safety design. Advances in 

Consumer Research 5: 499-507. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1985). Development of statistical 

distributions or ranges of standard factors 

used in exposure assessments. 

(EPA600885010). 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB85242667. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1987). Methods for assessing exposure to 

chemical substances: Volume 7: Methods for 

assessing consumer exposure to chemical 

substances [EPA Report]. (EPA/560/5­

85/007). Washington, DC.

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=P1007I8Y.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1988). Superfund exposure assessment 

manual: OSWER Directive 9285.5-1. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992a). Dermal exposure assessment: 

Principles and applications (interim report). 

(EPA/600/8-91/011B). Washington, DC: 

U.S. Environmental Protection Agency, 

Office of Health and Environmental 

Assessment, Exposure Assessment Group. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=12188. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992b). Guidelines for exposure 

assessment. (EPA/600/Z-92/001). 

Washington, DC: U.S. Environmental 

Protection Agency, Risk Assessment Forum. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=15263. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1992c). A laboratory method to determine 

the retention of liquids on the surface of the 

hands. (EPA/747/R-92/003). 

U.S. EPA (U.S. Environmental Protection Agency). 

(1997). Exposure factors handbook (final 

report). (EPA/600/P-95/002Fa-c). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Research and 

Development, National Center for 

Environmental Assessment. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=12464. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1998). Series 875 - Occupational and 

residential exposure test guidelines: Group 

B - Postapplication exposure monitoring test 

guidelines. Washington, DC: U.S. 

Environmentla Protection Agency. 

http://www.epa.gov/scipoly/sap/meetings/19 

98/march/front.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2004). Risk Assessment Guidance for 

Superfund (RAGS), Volume I: Human 

health evaluation manual, (part E: 

Supplemental guidance for dermal risk 

assessment): Final. (EPA/540/R/99/005). 

Washington, DC.

http://www.epa.gov/oswer/riskassessment/ra 

gse/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2007a). Dermal exposure assessment: A 

summary of EPA approaches [EPA Report]. 

(EPA/600/R-07/040F). Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=183584. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2007b). Exposure and Fate Assessment 

Screening Tool Version 2.0 (E-FAST V2.0). 

Available online at

http://www.epa.gov/opptintr/exposure/pubs/ 

efast.htm (accessed June 2, 2009). 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009). Draft technical guidelines: Standard 

operating procedures for residential 

pesticide exposure assessment: Submitted to 

the FIFRA Scientific Advisory Panel for 

review and comment, October 6-9, 2009. 

http://www.biospotvictims.org/EPA-HQOPP-2009-0516-0002.pdf. 

USDA (U.S. Department of Agriculture). (1969). The 
 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

determination of body surface area. S Afr 

Med J 43: 952-959. 

Williams, RL; Aston, LS; Krieger, RI. (2004). 

Perspiration increased human pesticide 

absorption following surface contact during 

an indoor scripted activity program. J Expo 

Anal Environ Epidemiol 14: 129-136. 

http://dx.doi.org/10.1038/sj.jea.7500301. 

Williams, RL; Reifenrath, WG; Krieger, RI. (2005). 

Artificial sweat enhances dermal transfer of 

chlorpyrifos from treated nylon carpet 

fibers. J Environ Sci Health B 40: 535-543. 

http://dx.doi.org/10.1081/PFC-200061525. 

Wong, EY; Shirai, JH; Garlock, TJ; Kissel, JC. 

(2000). Adult proxy responses to a survey of 

children's dermal soil contact activities. J 

Expo Anal Environ Epidemiol 10: 509-517. 

Yamamoto, N; Takahashi, Y; Yoshinaga, J; Tanaka, 

A; Shibata, Y. (2006). Size distributions of 

soil particles adhered to children's hands. 

Arch Environ Contam Toxicol 51: 157-163. 

http://dx.doi.org/10.1007/s00244-005-7012­

y. 

Zartarian, VG; Ferguson, AC; Leckie, JO.	 (1997). 

Quantified dermal activity data from a fourchild pilot field study. J Expo Anal Environ 

Epidemiol 7: 543-552. 

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Table 7-6. Percentage of Total Body Surface Area by Body Part for Children (sexes combined) and Adults by Sex 

Percent of Total 

Age (years) N Head Trunk Arms Hands Legs Feet 

M:F Mean Min–Max Mean Min–Max Mean Min–Max Mean Min–Max Mean Min–Max Mean Min−Max 

Male and Female Children Combined 

<1 2:0 18.2 18.2−18.3 35.7 34.8−36.6 13.7 12.4−15.1 5.3 5.2−5.4 20.6 18.2−22.9 6.5 6.5−6.6 

1 <2 1:1 16.5 16.5−16.5 35.5 34.5−36.6 13.0 12.8−13.1 5.7 5.6−5.8 23.1 22.1−24.0 6.3 5.8−6.7 

2 <3 1:0 14.2 38.5 11.8 5.3 23.2 7.1 

3 <4 0:5 13.6 13.3−14.0 31.9 29.9−32.8 14.4 14.2−14.7 6.1 5.8−6.3 26.8 26.0−28.6 7.2 6.8−7.9 

4 <5 1:3 13.8 12.1−15.3 31.5 30.5−32.4 14.0 13.0−15.5 5.7 5.2−6.6 27.8 26.0−29.3 7.3 6.9−8.1 

5 <6 

6 <7 1:0 13.1 35.1 13.1 4.7 27.1 6.9 

7 <8 

8 <9 

9 <10 0:2 12.0 11.6−12.5 34.2 33.4−34.9 12.3 11.7−12.8 5.3 5.2−5.4 28.7 28.5−28.8 7.6 7.4−7.8 

10 <11 

11 <12 

12 <13 1:0 8.7 34.7 13.7 5.4 30.5 7.0 

13 <14 1:0 10.0 32.7 12.1 5.1 32.0 8.0 

14 <15 

15 <16 

16 <17 1:0 8.0 32.7 13.1 5.7 33.6 6.9 

17 <18 1:0 7.6 31.7 17.5 5.1 30.8 7.3 

Male, 18+ years 32 7.8 6.1−10.6 35.9 30.5−41.4 14.1 12.5−15.5 5.2 4.6−7.0 31.2 26.1−33.4 7.0 6.0−7.9 

Female, 18+ years 57 7.1 5.6−8.1 34.8 32.8−41.7 14.0a 12.4−14.8 5.1b 4.4−5.4 32.4a 29.8−35.3 6.5a 6.0−7.0 

a Sample size = 13. b Sample size = 12.
 

N = Number of subjects, (M:F = male:female).
 

Min = Minimum percent.
 

Max = Maximum percent.
 

Source: U.S. EPA (1985). 

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Chapter 7—Dermal Exposure Factors 

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Chapter 7—Dermal Exposure Factors 

Table 7-7. Summary of Equation Parameters for Calculating Adult Body Surface Areaa 

Body Part N 

Equation for surface areas (m2) 

P R2 ao W SE a1 Ha2 

Head 

Female 

Male 

57 

32 

0.0256 

0.0492 

0.124 

0.339 

0.189 

−0.0950 

0.01 

0.01 

0.302 

0.222 

0.00678 

0.0202 

Trunk 

Female 

Male 

57 

32 

0.188 

0.0240 

0.647 

0.808 

−0.304 

−0.0131 

0.001 

0.001 

0.877 

0.894 

0.00567 

0.0118 

Upper Extremities 

Female 

Male 

57 

48 

0.0288 

0.00329 

0.341 

0.466 

0.175 

0.524 

0.001 

0.001 

0.526 

0.821 

0.00833 

0.0101 

Arms 

Female 

Male 

13 

32 

0.00223 

0.00111 

0.201 

0.616 

0.748 

0.561 

0.01 

0.001 

0.731 

0.892 

0.00996 

0.0177 

Upper Arms 

Male 6 8.70 0.741 −1.40 0.25 0.576 0.0387 

Forearms 

Male 6 0.326 0.858 −0.895 0.05 0.897 0.0207 

Hands 

Female 

Male 

12b 

32 

0.0131 

0.0257 

0.412 

0.573 

0.0274 

−0.218 

0.1 

0.001 

0.447 

0.575 

0.0172 

0.0187 

Lower Extremitiesc 

Legs 

Thighs 

Lower legs 

105 

45 

45 

45 

0.00286 

0.00240 

0.00352 

0.000276 

0.458 

0.542 

0.629 

0.416 

0.696 

0.626 

0.379 

0.973 

0.001 

0.001 

0.001 

0.001 

0.802 

0.780 

0.739 

0.727 

0.00633 

0.0130 

0.0149 

0.0149 

Feet 45 0.000618 0.372 0.725 0.001 0.651 0.0147 a SA= ao Wa1 Ha2 where: W = Weight in kilograms; H = Height in centimeters; P = Level of significance; R2 = Coefficient of 

determination; SA = Surface Area; SE = Standard error; N = Number of observations. b One observation for a female whose body weight exceeded the 95 percentile was not used. c Although two separate regressions were marginally indicated by the F test, pooling was done for consistency with individual 

components of lower extremities. 

Source: U.S. EPA (1985). 

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Table 7-8. Mean Proportion (%) of Children's Total Skin Surface Area, by Body Part 

Age (years) 

2 4 6 8 10 12 14 16 18 

Males 

N 115 118 117 104 124 154 155 100 88 

Head 8.4 8.1 7.0 6.0 5.4 4.9 4.3 4.0 3.9 

Neck 3.9 3.8 3.2 2.7 2.6 2.3 2.2 2.0 2.0 

Bosom 12.3 12.3 12.2 12.2 12.2 12.4 12.3 12.3 12.8 

Shoulders 1.9 2.1 1.9 1.9 1.8 1.8 1.8 1.8 1.9 

Abdomen 2.7 2.9 2.7 2.8 2.7 2.8 2.8 2.8 2.9 

Back 12.9 13.2 13.1 13.1 13.1 13.4 13.4 13.3 13.9 

Genitals and Buttocks 7.1 6.9 6.9 6.8 7.1 7.0 7.2 7.2 6.8 

Thighs 14.9 15.0 16.2 16.6 17.6 17.4 18.2 18.1 18.3 

Legs 10.3 10.3 10.9 11.7 11.8 11.9 11.9 11.9 11.2 

Feet 6.5 6.5 6.7 7.2 6.8 7.0 6.6 6.7 6.1 

Upper Arms 8.7 8.5 8.6 8.6 8.8 8.7 8.9 9.6 9.6 

Lower Arms 5.8 5.6 5.7 5.7 5.5 5.5 5.7 5.8 5.9 

Hands 4.5 4.8 4.9 4.7 4.6 4.7 4.7 4.7 4.7 

Females 

N 97 110 126 93 134 133 116 98 68 

Head 8.4 7.8 6.9 6.1 5.3 4.8 4.5 4.3 4.3 

Neck 3.8 3.6 3.2 2.8 2.5 2.3 2.1 2.1 2.0 

Bosom 12.4 12.6 12.4 12.2 12.1 12.0 12.3 13.3 14.3 

Shoulders 2.0 2.0 1.9 1.9 1.8 1.8 1.7 1.8 1.8 

Abdomen 3.0 2.9 2.8 2.8 2.7 2.7 2.8 2.9 3.0 

Back 13.2 13.4 13.2 13.1 13.0 12.9 13.2 13.9 14.1 

Genitals and Buttocks 6.8 6.6 6.6 6.6 7.0 7.3 8.0 7.9 8.1 

Thighs 14.2 15.6 16.5 18.4 18.4 18.5 18.9 17.8 17.4 

Legs 11.2 10.4 11.4 11.3 12.2 12.5 12.1 11.9 11.5 

Feet 6.0 6.3 6.6 6.5 6.7 6.5 6.1 6.1 5.6 

Upper Arms 8.6 8.4 8.3 8.1 8.4 8.8 8.8 8.6 8.5 

Lower Arms 5.6 5.5 5.3 5.5 5.3 5.5 5.3 5.3 5.1 

Hands 4.8 4.9 4.9 4.7 4.5 4.5 4.2 4.2 4.4 

N = Number of observations. 

Note: Sums of columns may equal slightly more or less than 100% due to rounding. 

Source: Boniol et al. (2008). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 

7-40 November 2011 
Table 7-9. Mean and Percentile Skin Surface Area (m2

) 

Derived From U.S. EPA Analysis of NHANES 1999−2006 

Males and Females Combined for Children <21 Years and NHANES 2005–2006 for Adults >21 Years 

Age Percentiles N Mean 5th 10th 15th 25th 50th 75th 85th 90th 95th Group 

Males and Females Combined 

Birth to <1 month 154 0.29 0.24 0.25 0.26 0.27 0.29 0.31 0.31 0.33 0.34 

1 to <3 months 281 0.33 0.27 0.29 0.29 0.31 0.33 0.35 0.37 0.37 0.38 

3 to <6 months 488 0.38 0.33 0.34 0.35 0.36 0.38 0.40 0.42 0.43 0.44 

6 to <12 months 923 0.45 0.38 0.39 0.40 0.42 0.45 0.48 0.49 0.50 0.51 

1 to <2 years 1,159 0.53 0.45 0.46 0.47 0.49 0.53 0.56 0.58 0.59 0.61 

2 to <3 years 1,122 0.61 0.52 0.54 0.55 0.57 0.61 0.64 0.67 0.68 0.70 

3 to <6 years 2,303 0.76 0.61 0.64 0.66 0.68 0.74 0.81 0.85 0.89 0.95 

6 to <11 years 3,590 1.08 0.81 0.85 0.88 0.93 1.05 1.21 1.31 1.36 1.48 

11 to <16 years 5,294 1.59 1.19 1.25 1.31 1.4 1.57 1.75 1.86 1.94 2.06 

16 to <21 years 4,843 1.84 1.47 1.53 1.58 1.65 1.80 1.99 2.10 2.21 2.33 

21 to <30 years 914 1.93 1.51 1.56 1.62 1.73 1.91 2.09 2.21 2.29 2.43 

30 to <40 years 813 1.97 1.55 1.63 1.67 1.77 1.95 2.16 2.26 2.31 2.43 

40 to <50 years 806 2.01 1.59 1.66 1.71 1.80 1.99 2.21 2.31 2.40 2.48 

50 to <60 years 624 2.00 1.57 1.63 1.69 1.80 1.97 2.19 2.29 2.37 2.51 

60 to <70 years 645 1.98 1.58 1.63 1.70 1.78 1.98 2.15 2.26 2.33 2.43 

70 to <80 years 454 1.89 1.48 1.56 1.64 1.72 1.90 2.05 2.15 2.22 2.30 

80 years and over 330 1.77 1.45 1.53 1.56 1.62 1.76 1.92 2.00 2.05 2.12 

N = Number of observations. 

Source: U.S. EPA Analysis of NHANES 1999–2006 data (children) NHANES 2005–2006 data (adults). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Exposure Factors Handbook Page
 

November 2011 7-41 
 

Table 7-10. Mean and Percentile Skin Surface Area (m2) 

Derived From U.S. EPA Analysis of NHANES 1999–2006 for 

Children <21 Years and NHANES 2005–2006 for Adults >21 Years, Male 

Age Percentiles N Mean 5th 10th 15th 25th 50th 75th 85th 90th 95th Group 

Male 

Birth to <1 month 85 0.29 0.24 0.25 0.26 0.27 0.29 0.31 0.33 0.34 0.36 

1 to <3 months 151 0.33 0.28 0.29 0.30 0.31 0.34 0.36 0.37 0.37 0.38 

3 to <6 months 255 0.39 0.34 0.35 0.36 0.37 0.39 0.41 0.42 0.43 0.44 

6 to <12 months 471 0.45 0.39 0.41 0.42 0.43 0.46 0.48 0.49 0.50 0.51 

1 to <2 years 620 0.53 0.46 0.47 0.48 0.50 0.53 0.57 0.58 0.59 0.62 

2 to <3 years 548 0.62 0.54 0.56 0.56 0.58 0.62 0.65 0.67 0.68 0.70 

3 to <6 years 1,150 0.76 0.61 0.64 0.66 0.69 0.75 0.82 0.86 0.89 0.95 

6 to <11 years 1,794 1.09 0.82 0.86 0.89 0.94 1.06 1.21 1.29 1.34 1.46 

11 to <16 years 2,593 1.61 1.17 1.23 1.28 1.39 1.60 1.79 1.90 1.99 2.12 

16 to <21 years 2,457 1.94 1.61 1.66 1.7 1.76 1.91 2.08 2.22 2.30 2.42 

21 to 30 years 361 2.05 1.70 1.76 1.81 1.87 2.01 2.18 2.30 2.39 2.52 

30 to <40 years 390 2.10 1.74 1.81 1.85 1.93 2.08 2.24 2.31 2.39 2.50 

40 to <50 years 399 2.15 1.78 1.86 1.90 1.97 2.12 2.29 2.41 2.47 2.56 

50 to <60 years 310 2.11 1.68 1.81 1.86 1.94 2.12 2.26 2.34 2.46 2.55 

60 to <70 years 323 2.08 1.72 1.78 1.84 1.94 2.08 2.25 2.33 2.37 2.46 

70 to <80 years 249 2.05 1.71 1.80 1.84 1.92 2.05 2.18 2.23 2.31 2.45 

80 years and older 163 1.92 1.67 1.71 1.74 1.80 1.92 2.02 2.08 2.13 2.22 

N = Number of observations. 

Source: U.S. EPA Analysis of NHANES 1999–2006 data (children) NHANES 2005–2006 data (adults). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 

7-42 November 2011 
Table 7-11. Mean and Percentile Skin Surface Area (m2

) 

Derived From U.S. EPA Analysis of NHANES 1999–2006 for 

Children <21 Years and NHANES 2005–2006 for Adults >21 Years, Female s 

Age Percentiles N Mean 5th 10th 15th 25th 50th 75th 85th 90th 95th Group 

Female 

Birth to <1 month 69 0.28 0.24 0.25 0.26 0.27 0.28 0.30 0.30 0.31 0.33 

1 to <3 months 130 0.32 0.27 0.28 0.29 0.30 0.31 0.35 0.36 0.37 0.37 

3 to <6 months 233 0.38 0.32 0.33 0.34 0.35 0.38 0.40 0.40 0.41 0.43 

6 to <12 months 452 0.44 0.38 0.39 0.40 0.41 0.44 0.47 0.48 0.49 0.51 

1 to <2 years 539 0.52 0.44 0.46 0.47 0.48 0.52 0.56 0.57 0.58 0.59 

2 to <3 years 574 0.60 0.51 0.53 0.54 0.56 0.59 0.63 0.66 0.67 0.70 

3 to <6 years 1,153 0.75 0.61 0.64 0.66 0.68 0.74 0.80 0.84 0.88 0.94 

6 to <11 years 1,796 1.08 0.80 0.85 0.87 0.92 1.04 1.21 1.33 1.39 1.51 

11 to <16 years 2,701 1.57 1.20 1.28 1.34 1.42 1.55 1.69 1.8 1.88 2.00 

16 to <21 years 2,386 1.73 1.42 1.47 1.51 1.57 1.69 1.85 1.98 2.06 2.17 

21 to 30 years 553 1.81 1.45 1.51 1.54 1.60 1.79 1.94 2.08 2.17 2.25 

30 to <40 years 423 1.85 1.50 1.55 1.61 1.67 1.82 2.00 2.13 2.23 2.31 

40 to <50 years 407 1.88 1.54 1.59 1.63 1.70 1.83 2.04 2.19 2.27 2.36 

50 to <60 years 314 1.89 1.54 1.58 1.62 1.70 1.85 2.005 2.19 2.26 2.38 

60 to <70 years 322 1.88 1.49 1.59 1.62 1.70 1.85 2.04 2.14 2.20 2.34 

70 to <80 years 205 1.77 1.44 1.48 1.55 1.62 1.77 1.91 1.99 2.03 2.13 

80 years and older 167 1.69 1.41 1.46 1.51 1.56 1.68 1.80 1.86 1.92 1.98 

N = Number of observations. 

Source: U.S. EPA Analysis of NHANES 1999–2006 data (children) NHANES 2005–2006 data (adults). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Exposure Factors Handbook Page
 

November 2011 7-43 
 

Table 7-12. Surface Area of Adult Male s (21 years and older) in Square Meters 

Body Part 

Percentile 

Mean 5th 10th 15th 25th 50th 75th 85th 90th 95th 

Adult Males 

Total 2.06 1.73 1.80 1.84 1.93 2.07 2.23 2.34 2.41 2.52 

Head 0.136 0.123 0.126 0.128 0.131 0.136 0.143 0.147 0.149 0.154 

Trunka 0.827 0.636 0.672 0.701 0.74 0.820 0.918 0.984 1.02 1.10 

Upper Extremities 0.393 0.332 0.346 0.354 0.369 0.395 0.425 0.442 0.456 0.474 

Arms 0.314 0.253 0.265 0.274 0.289 0.316 0.346 0.364 0.379 0.399 

Upper arms 0.172 0.139 0.145 0.149 0.156 0.169 0.185 0.196 0.205 0.220 

Forearms 0.148 0.115 0.121 0.125 0.132 0.146 0.163 0.173 0.181 0.197 

Hands 0.107 0.090 0.093 0.096 0.100 0.107 0.115 0.121 0.124 0.131 

Lower Extremities 0.802 0.673 0.703 0.721 0.752 0.808 0.868 0.903 0.936 0.972 

Legs 0.682 0.560 0.587 0.603 0.634 0.686 0.746 0.780 0.811 0.847 

Thighs 0.412 0.334 0.349 0.360 0.379 0.4113 0.452 0.478 0.495 0.523 

Lower Legs 0.268 0.225 0.234 0.241 0.252 0.271 0.292 0.302 0.312 0.324 

Feet 0.137 0.118 0.123 0.125 0.130 0.138 0.147 0.152 0.156 0.161 a Trunk includes neck. 

Source: Based on U.S. EPA (1985) and NHANES 2005–2006. 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 

7-44 November 2011 
Table 7-13. Surface Area of Adult Females (21 years and older) in Square Meters 

Body Part 

Percentile 

Mean 5th 10th 15th 25th 50th 75th 85th 90th 95th 

Adult Females 

Total 1.85 1.49 1.55 1.59 1.66 1.82 1.99 2.12 2.21 2.33 

Head 0.114 0.108 0.109 0.110 0.111 0.114 0.116 0.118 0.119 0.121 

Trunka 0.654 0.511 0.530 0.544 0.571 0.633 0.708 0.765 0.795 0.850 

Upper Extremities 0.304 0.266 0.272 0.277 0.284 0.301 0.320 0.333 0.342 0.354 

Arms 0.237 0.213 0.218 0.221 0.227 0.237 0.248 0.254 0.259 0.266 

Hands 0.089 0.076 0.078 0.079 0.082 0.087 0.094 0.099 0.102 0.106 

Lower Extremities 0.707 0.579 0.599 0.616 0.643 0.698 0.761 0.805 0.835 0.875 

Legs 0.598 0.474 0.494 0.509 0.533 0.588 0.649 0.693 0.724 0.764 

Thighs 0.364 0.281 0.294 0.303 0.319 0.356 0.397 0.428 0.450 0.479 

Lower Legs 0.233 0.191 0.198 0.204 0.213 0.230 0.250 0.263 0.273 0.286 

Feet 0.122 0.103 0.106 0.109 0.113 0.121 0.130 0.136 0.140 0.146 a Trunk includes neck. 

Source: Based on U.S. EPA (1985) and NHANES 2005–2006. 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Exposure Factors Handbook Page
 

November 2011 7-45 
 

Table 7-14. Statistical Results for Total Body Surface Area Distributions (m2), for Adults 

Males 

U.S. EPA Boyd Du Bois and Du Bois Costeff 

Mean 1.97 1.95 1.94 1.89 

Median 1.96 1.94 1.94 1.89 

Mode 1.96 1.91 1.90 1.90 

Standard Deviation 0.19 0.18 0.17 0.16 

Skewness 0.27 0.26 0.23 0.04 

Kurtosis 3.08 3.06 3.02 2.92 

Females 

U.S. EPA Boyd Du Bois and Du Bois Costeff 

Mean 1.73 1.71 1.69 1.71 

Median 1.69 1.68 1.67 1.68 

Mode 1.68 1.62 1.60 1.66 

Standard Deviation 0.21 0.20 0.18 0.21 

Skewness 0.92 0.88 0.77 0.69 

Kurtosis 4.30 4.21 4.01 3.52 

Source: Murray and Burmaster (1992). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 

7-46 November 2011 
 

 

 

 

 

 

Chapter Exposure Factors Handbook 

―Dermal Exposure Factors

Table 7-15. Descriptive Statistics for Surface Area/Body-Weight (SA/BW) Ratios (m2/kg) 

Age 

(year) Mean Range 

Min–Max 

SD SE 

5th 10th 25th 

Percentiles 

50th 75th 90th 95th 

Male and Female Combined 

0 to 2 0.064 0.042−0.114 0.011 0.001 0.047 0.051 0.056 0.062 0.072 0.078 0.085 

2.1 to 17.9 0.042 0.027−0.067 0.008 0.001 0.029 0.033 0.038 0.042 0.045 0.050 0.059 

≥18 0.028 0.020−0.031 0.003 7.68e-6 0.024 0.024 0.027 0.029 0.030 0.032 0.033 

All Ages 0.049 0.020−0.114 0.019 9.33e-4 0.025 0.027 0.030 0.050 0.063 0.074 0.079 

SD = Standard deviation. 

SE = Standard error of the mean. 

Source: Phillips et al. (1993). 

Exposure Factors Handbook PageMarch 2011 7-47
 

Table 7-16. Estimated Percent of Adult Skin Surface Exposed During Outdoor Activities 

Skin Area Exposed (% of total body surface area) 

N 5th percentile 50th percentile 95th percentile 

Gardening 

Cold months 

Warm months 

31 

212 

3 

3 

8 

33 

33 

69 

Other Yard 

Work 

Cold months 

73 

245 

Team Sports 

Cold months 

Warm months 

26 

71 

Repair/Diggin 

g 

Cold months 

15 

65 

N = Number of observations. 

3 

8 

3 

14 

3 

9 

3 

33 

8 

33 

3 

28 

31 

68 

33 

43 

14 

67 

Source: Garlock et al. (1999). 

Table 7-17. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities 

Skin Area Exposed (% of total body surface area) 

Play Gardening/Yardwork Organized Team Sport 

Age (year) <5 5 to 17 5 to 17 

N 41 47 65 

Mean 38.0 33.8 29.0 

Median 36.5 33.0 30.0 

SD 6.0 8.3 10.5 

N = Number of observations. 

SD = Standard deviation. 

Source: Wong et al. (2000). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 

7-48 November 2011 
Table 7-18. Median per Contact Outdoor Fractional Surface Areas of the Hands, by Object, Both Hands Combined 

Animal Body Clothes Fabric Floor Food Footwear Metal NonDietary 

Water 

Paper Plastic Rock 

/Brick 

Toy Vegetation 

/Grass 

Wood All 

Objects 

N 12 38 38 19 37 26 30 38 9 27 36 16 37 37 

Minimum 0.02 0.06 0.11 0.05 0.13 0.02 0.02 0.00 0.08 0.02 0.08 0.06 0.08 0.02 

Maximum 0.27 0.27 0.30 0.30 1.00 1.00 0.25 0.27 1.00 0.30 0.30 0.30 0.27 0.30 

Mean 0.18 0.15 0.22 0.16 0.24 0.16 0.11 0.14 0.52 0.13 0.17 0.20 0.15 0.17 

5th percentile 0.04 0.07 0.14 0.11 0.13 0.03 0.03 0.11 0.10 0.03 0.13 0.07 0.13 0.03 

25th percentile 0.12 0.13 0.19 0.14 0.19 0.05 0.06 0.14 0.19 0.08 0.14 0.18 0.14 0.12 

50th percentile 0.20 0.16 0.22 0.15 0.24 0.11 0.10 0.14 0.31 0.13 0.15 0.23 0.14 0.16 

75th percentile 0.24 0.19 0.26 0.15 0.27 0.14 0.14 0.15 1.00 0.17 0.19 0.24 0.15 0.24 

95th percentile 0.26 0.24 0.30 0.24 0.30 0.80 0.21 0.19 1.00 0.25 0.28 0.28 0.24 0.30 

95th percentile 0.26 0.26 0.30 0.29 0.75 1.00 0.25 0.26 1.00 0.29 0.30 0.30 0.26 0.30 

38 

0.07 

0.30 

0.20 

0.11 

0.15 

0.18 

0.25 

0.30 

0.30 

38 

0.13 

0.27 

0.16 

0.13 

0.14 

0.15 

0.17 

0.26 

0.27 

N = Number of subjects. 

Source: AuYeung et al. (2008). 

Exposure Factors Handbook Chapter 7—Dermal Exposure Factors Exposure Factors Handbook 

Page

February 2012 7-49
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Expos

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xposu

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re Factors 

Handbook 

7-50 Page Exposure Fa

Nov

ctors Handbook 

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Table 7-19. Summary of Field Studies That Estimated Activity-Specific Adherence Rates 

Activity Month Eventa N M F Age (years) Conditions Clothing Study 

(hours) 

Indoor 

Tae Kwon Do Feb. 1.5 7 6 1 8 to 42 Carpeted floor All in long sleeve-long pants martial Kissel et al. 

arts uniform, sleeves rolled back, (1996b) 

barefoot 

Greenhouse Worker Mar. 5.25 2 1 1 37 to 39 Plant watering, spraying, Long pants, elbow length short 

soil blending, sterilization sleeve shirt, no gloves 

Indoor Kid No. 1 Jan. 2 4 3 1 6 to 13 Playing on carpeted floor 3 or 4 short pants, 2 of 4 short Holmes et al. 

sleeves, socks, no shoes (1999) 

Indoor Kid No. 2 Feb. 2 6 4 2 3 to 13 Playing on carpeted floor 5 of 6 long pants, 5 of 6 long sleeves, 

socks, no shoes 

Daycare Kid No. 1a Aug. 3.5 6 5 1 1 to 6.5 Indoors: linoleum surface; 4 of 6 long pants, 5 of 6 short 

Outdoors: grass, bare earth, sleeves, socks, shoes 

barked area 

Daycare Kid No. 1b Aug. 4 6 5 1 1 to 6.5 Indoors: linoleum surface; 4 of 6 long pants, 5 of 6 short 

Outdoors: grass, bare earth, sleeves, 3 of 6 barefoot all afternoon, 

barked area others barefoot half the afternoon 

Daycare Kid No. 2b Sept. 8 5 4 1 1 to 4 Indoors: low napped 4 of 5 long pants, 3 of 5 long sleeves, 

carpeting, linoleum surfaces all barefoot for part of the day 

Daycare Kid No. 3 Nov. 8 4 3 1 1 to 4.5 Indoors: linoleum surface, All long pants, 3 of 4 long sleeves, 

Outside: grass, bare earth, socks and shoes 

barked area 

Outdoor 

Soccer No. 1 Nov. 0.67 8 8 0 13 to 15 Half grass/half bare earth 6 of 8 long sleeves, 4 of 8 long pants, Kissel et al. 

3 of 4 short pants and shin guards (1996b) 

Soccer No. 2 Mar. 1.5 8 0 8 24 to 34 All weather field (sand- All in short sleeve shirts, shorts, knee 

ground tires) socks, shin guards 

Soccer No. 3 Nov. 1.5 7 0 7 24 to 34 All weather field (sand- All in short sleeve shirts, shorts, knee 

ground tires) socks, shin guards 

Groundskeeper No. 1 Mar. 1.5 2 1 1 29 to 52 Campus grounds, urban All in long pants, intermittent use of 

horticulture center, gloves 

arboretum 

Groundskeeper No. 2 Mar. 4.25 5 3 2 22 to 37 Campus grounds, urban All in long pants, intermittent use of 

horticulture center, gloves 

arboretum 

Groundskeeper No. 3 Mar. 8 7 5 2 30 to 62 Campus grounds, urban All in long pants, intermittent use of 

horticulture center, gloves 

arboretum 
 

 

 

Chapter 7—Dermal Exposure Factors Exposure Factors Handbook 

Table 7-19. Summary of Field Studies That Estimated Activity-Specific Adherence Rates (continued) 

Activity Month Eventa (hours) N M F Age (years) Conditions Clothing Study 

Outdoor (continued) 

Groundskeeper No. 4 

Groundskeeper No. 5 

Irrigation Installer 

Rugby No. 1 

Farmer No. 1 

Farmer No. 2 

Reed Gatherer 

Kid-in-Mud No. 1 

Kid-in-Mud No. 2 

Aug. 4.25 7 4 3 22 to 38 Campus grounds, urban 

horticulture center, arboretum 

5 of 7 in short sleeve shirts, 

intermittent use of gloves 

Kissel et al. 

(1996b) 

Aug. 8 8 6 2 19 to 64 Campus grounds, urban 

horticulture center, arboretum 

5 of 8 in short sleeve shirts, 

intermittent use of gloves 

Oct. 3 6 6 0 23 to 41 Landscaping, surface 

restoration 

All in long pants, 3 of 6 short sleeve 

or sleeveless shirts 

Mar. 1.75 8 8 0 20 to 22 Mixed grass-bare wet field All in short sleeve shirts, shorts, 

variable sock lengths 

May 2 4 2 2 39 to 44 Manual weeding, mechanical 

cultivation 

All in long pants, heavy shoes, short 

sleeve shirts, no gloves 

July 2 6 4 2 18 to 43 Manual weeding, mechanical 

cultivation 

2 of 6 short, 4 of 6 long pants, 1 of 

6 long sleeve shirt, no gloves 

Aug. 2 4 0 4 42 to 67 Tidal flats 2 of 4 short sleeve shirts/knee length 

pants, all wore shoes 

Sept. 0.17 6 5 1 9 to 14 Lake shoreline All in short sleeve T-shirts, shorts, 

barefoot 

Sept. 0.33 6 5 1 9 to 14 Lake shoreline All in short sleeve T-shirts, shorts, 

barefoot 

Gardener No. 1 

Gardener No. 2 

Rugby No. 2 

Rugby No. 3 

Archeologist 

Construction Worker 

Landscape/Rockery 

Aug. 4 8 1 7 16 to 35 Weeding, pruning, digging a 

trench 

6 of 8 long pants, 7 of 8 short sleeves, 

1 sleeveless, socks, shoes, intermittent 

use of gloves 

Holmes et al. 

(1999) 

Aug. 4 7 2 5 26 to 52 Weeding, pruning, digging a 

trench, picking fruit, cleaning 

3 of 7 long pants, 5 of 7 short sleeves, 

1 sleeveless, socks, shoes, no gloves 

July 2 8 8 0 23 to 33 Grass field (80% of time) and 

all-weather field (mix of gravel, 

sand, and clay) (20% of time) 

All in shorts, 7 of 8 in short sleeve 

shirts, 6 of 8 in low socks 

Sept. 2.75 8 7 0 24 to 30 Compacted mixed grass and 

bare earth field 

All short pants, 7 of 8 short or rolled 

up sleeves, socks, shoes 

July 11.5 7 3 4 16 to 35 Digging with trowel, screening 

dirt, sorting 

6 of 7 short pants, all short sleeves, 

3 no shoes or socks, 2 sandals 

Sept. 8 8 8 0 21 to 30 Mixed bare earth and concrete 

surfaces, dust and debris 

5 of 8 pants,7 of 8 short sleeves, all 

socks and shoes 

June 9 4 3 1 27 to 43 Digging (manual and 

mechanical), rock moving 

All long pants, 2 long sleeves, all 

socks and boots 

Exposure Factors Handbook PageNovember 2011 7-51
 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-19. Summary of Field Studies That Estimated Activity-Specific Adherence Rates (continued) 

Activity Month Eventa (hours) N M F Age (years) Conditions Clothing Study 

Outdoor (continued) 

Utility Worker No. 1 July 9.5 5 5 0 24 to 45 Cleaning, fixing mains, 

excavation (backhoe and 

shovel) 

All long pants, short sleeves, socks, 

boots, gloves sometimes 

Utility Worker No. 2 Aug. 9.5 6 6 0 23 to 44 Cleaning, fixing mains, 

excavation (backhoe and 

shovel) 

All long pants, 5 of 6 short sleeves, 

socks, boots, gloves sometimes 

Equip. Operator No. 1 Aug. 8 4 4 0 21 to 54 Earth scraping with heavy 

machinery, dusty conditions 

All long pants, 3 of 4 short sleeves, 

socks, boots, 2 of 4 gloves 

Equip. Operator No. 2 Aug. 8 4 4 0 21 to 54 Earth scraping with heavy 

machinery, dusty conditions 

All long pants, 3 of 4 short sleeves, 

socks, boots, 1 gloves 

Shoreline Play 

(children) 

Sept. 0.33−1.0 9 6 3 7 to 12 Tidal flat No shirt or short sleeve T-shirts, 

shorts, barefoot 

Clamming (adults) Aug. 1−2 18 9 9 33 to 63 Tidal flat T-shirt, shorts, shoes 

Holmes et al. 

(1999) 

Shoaf et al. 

(2005b) 

Shoaf et al. 

(2005a) a Event duration. b Activities were confined to the house. 

N = Number of subjects. 

M = Males. 

F = Females. 

Page Exposure Factors Handbook 7-52 November 2011 
Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Exposure Factors Handbook Page
 

November 2011 7-53 

Table 7-20. Geometr

Activity 

Tae Kwon Do 

ic Mean

N 

7 

 and Geometr

Hands 

0.0063 

ic Standard Deviations of Solids Adherence by A a Body Region

Post-Activity Dermal Solids Loadings (mg/cm2) 

Arms Legs Faces 

Indoor 

0.0019 0.0020 

ctivity and 

Feet 

0.0022 

1.9 4.1 2.0 2.1 

Greenhouse Worker 2 0.043 0.0064 0.0015 0.0050 

-­ -­ -­ -­

Indoor Kid No. 1 4 0.0073 0.0042 0.0041 0.012 

1.9 1.9 2.3 1.4 

Indoor Kid No. 2 6 0.014 0.0041 0.0031 0.0091 

1.5 2.0 1.5 1.7 

Daycare Kid No. 1a 6 0.11 0.026 0.030 0.079 

1.9 1.9 1.7 2.4 

Daycare Kid No. 1b 6 0.15 0.031 0.023 0.13 

2.1 1.8 1.2 1.4 

Daycare Kid No. 2 5 0.073 0.023 0.011 0.044 

1.6 1.4 1.4 1.3 

Daycare Kid No. 3 4 0.036 0.012 0.014 0.0053 

Soccer No. 1 8 

1.3 

0.11 

1.2 

Outdoor 

0.011 

3.0 

0.031 0.012 

5.1 

1.8 2.0 3.8 1.5 

Soccer No. 2 8 0.035 0.0043 0.014 0.016 

3.9 2.2 5.3 1.5 

Soccer No. 3 7 0.019 0.0029 0.0081 0.012 

1.5 2.2 1.6 1.6 

Groundskeeper No. 1 2 0.15 0.005 0.0021 0.018 

-­ -­ -­ --

Groundskeeper No. 2 5 0.098 0.0021 0.0010 0.010 

2.1 2.6 1.5 2.0 

Groundskeeper No. 3 7 0.030 0.0022 0.0009 0.0044 0.0040 

2.3 1.9 1.8 2.6 

Groundskeeper No. 4 7 0.045 0.014 0.0008 0.0026 0.018 

1.9 1.8 1.9 1.6 --

Groundskeeper No. 5 8 0.032 0.022 0.0010 0.0039 

1.7 2.8 1.4 2.1 

Irrigation Installer 6 0.19 0.018 0.0054 0.0063 

1.6 3.2 1.8 1.3 
 

Table 7-20. Geometric Mean and Geometric Standard Deviations of Solids Adherence by 

Activity and Body Regiona (continued) 

Post-Activity Dermal Solids Loadings (mg/cm2) Activity N 

Hands Arms Legs Faces Feet 

Rugby No. 1 8 0.40 0.27 0.36 0.059 

1.7 1.6 1.7 2.7 

Farmers No. 1 4 0.41 0.059 0.0058 0.018 

1.6 3.2 2.7 1.4 

Farmers No. 2 6 0.47 0.13 0.037 0.041 

1.4 2.2 3.9 3.0 

Reed Gatherer 4 0.66 0.036 0.16 0.63 

1.8 2.1 9.2 7.1 

Kid-in-Mud No. 1 6 35 11 36 24 

2.3 6.1 2.0 3.6 

Kid-in-Mud No. 2 6 58 11 9.5 6.7 

2.3 3.8 2.3 12.4 

Gardener No. 1 8 0.20 0.050 0.072 0.058 0.17 

1.9 2.1 -- 1.6 -­

Gardener No. 2 7 0.18 0.054 0.022 0.047 0.26 

3.4 2.9 2.0 1.6 -­

Rugby No. 2 8 0.14 0.11 0.15 0.046 

1.4 1.6 1.6 1.4 

Rugby No. 3 7 0.049 0.031 0.057 0.020 

1.7 1.3 1.2 1.5 

Archeologist 7 0.14 0.041 0.028 0.050 0.24 

1.3 1.9 4.1 1.8 1.4 

Construction Worker 8 0.24 0.098 0.066 0.029 

1.5 1.5 1.4 1.6 

Landscape/Rockery 4 0.072 0.030 0.0057 

2.1 2.1 1.9 

Utility Worker No.1 5 0.32 0.20 0.10 

1.7 2.7 1.5 

Utility Worker No. 2 6 0.27 0.30 0.10 

2.1 1.8 1.5 

Equip. Operator No. 1 4 0.26 0.089 0.10 

2.5 1.6 1.4 

Equip. Operator No. 2 4 0.32 0.27 0.23 

1.6 1.4 1.7 

Shoreline Play 9 0.49 0.17 0.70 0.04 21 

(children) 8.2 3.1 3.6 2.9 1.9 

Clamming (adults) 18 0.88 0.12 0.16 0.02 0.58 

17 1.1 4.7 0.10 12 

Means are presented above the standard deviations. The standard deviations generally exceed the means by large 

amounts indicating high variability in the data.
 

N = Number of subjects.
 

Sources: Kissel et al. (1996b); Holmes et al. (1999); Shoaf et al. (2005a, b).
 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

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Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-21. Summary of Controlled Greenhouse Trials 

Activity Ages 

(years) 

Duration 

(min) 

Soil Moisture 

(%) 

Clothinga N Male Female 

Transplanti 

ng 

Adult ~12b 17−19 

15−18 

L 

S 

4 

13 

2 

6 

2 

7 

Playing 8 to 12 20 17−18 

16−18 

3−4 

L 

S 

S 

4 

9 

5 

3 

5 

3 

1 

4 

2 

Pipe 

Laying 

Adult 15, 30, 45 9−12 

5−7 

S 

S 

7 

6 

4 

3 

3 

3 a L = long sleeves and long pants; S = short sleeves and short pants. b Arithmetic mean (range was 9 to 18 minutes). Activity was terminated after completion of the task rather 

than at a fixed time. 

N = Number of subjects. 

Source: Kissel et al. (1998). 

Table 7-22. Dermal Transfer Factors for Selected Contact Surface Types and Skin Wetness, 

Using <80 μm Tagged ATD

Mean surface Loading 

μg/cm2 

Test Subjecta Contact Surface 

Typeb 

Skin Moisture 

Levelc 

Dermal Transfer 

Factord 

36.3 F1 SS Dry 0.760 (0.000) 

39.1 M1 SS Dry 0.716 (NA) 

32.0 M1 SS Damp 1.222 (NA) 

45.0 M1 SS Wet 1.447 (NA) 

42.6 M2 SS Dry 0.582 (0.059) 

23.8 M2 SS Damp 0.970 (NA) 

30.6 M2 SS Wet 1.148 (NA) 

30.5 M2 Vinyl Dry 0.554 (0.052) 

32.7 M2 Vinyl Damp 0.485 (0.068) 

38.9 (not embedded) M2 Carpet Dry 0.087 (0.000) 

36.4 (embedded) M2 Carpet Dry 0.034 (0.007) 

33.8 (not embedded) M2 Carpet Damp 0.190 (0.002) 

33.3 (embedded) M2 Carpet Damp 0.169 (0.11) 

a F1 = female subject; M1 and M2 = male subjects. b SS = stainless steel; vinyl linoleum; nylon carpet. c Dry = no added moisture; wet = synthetic saliva moistened (moisture visible but not excessive). d Dermal transfer factor = μg on hand/cm2 of dermal contact area/μg on surface/cm2 of surface contact. 

Based on mean of left and right hand presses. Standard deviation (SD) in parenthesis; NA = not available. 

Source: Rodes et al. (2001). 

Exposure Factors Handbook Page
 

November 2011 7-55 
 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-23. Comparison of Adherence (mg/cm2) for Contact With Carpet and Aluminum Surfaces, 

Averaged Across Pressure, Contact Time, Soil Type, and Soil Particle Sizea 

Carpet 

Transfer 

Hard Surface 

(aluminum) 

Transfer 

Combined 

(carpet/aluminum) 

Transfer 

Mean Soil Adherence 0.37 ± 0.4 0.42 ± 0.6 0.39 ± 0.4 

Mean Soil-Skin Adherence 0.71 ± 0.5 1.18 ± 0.4 0.92 ± 0.5 

Mean Soil-Cloth Adherence 0.20 ± 0.3 0.15 ± 0.4 0.17 ± 0.4 a Soil adherence values averaged across pressure, time, soil type, and soil size. 

Source: Ferguson et al. (2009a). 

Page Exposure Factors Handbook 

7-56 November 2011 
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-24. Film Thickness Values of Selected Liquids Under Various Experimental Conditions (10−3cm) 

Mineral 

Oila 

Cooking Oilb Bath 

Oilc 

Oil/ 

Waterd Watere 

Water/ 

Ethanolf 

Initial Contactg 

No wipeh 

Partial wipei 

Full wipej 

1.56 

0.62 

0.27 

2.25 

0.82 

0.34 

1.74 

0.59 

0.20 

2.03 

1.55 

1.38 

2.34 

1.83 

1.97 

3.25 

2.93 

3.12 

Secondary Contactk 

No wipeh 

Partial wipei 

Full wipej 

1.40 

0.47 

0.06 

1.87 

0.52 

0.07 

1.56 

0.48 

0.08 

1.60 

1.19 

0.92 

2.05 

1.39 

1.32 

2.95 

2.67 

2.60 

Immersionl 

No wipeh 

Partial wipei 

Full wipej 

11.87 

2.00 

-

6.55 

1.46 

-

6.90 

1.55 

-

9.81 

2.42 

-

4.99 

2.14 

-

6.55 

2.93 

-

Handling Ragm 

No wipeh 

Partial wipei 

Full wipej 

1.64 

0.44 

0.13 

1.50 

0.34 

0.01 

2.04 

0.53 

0.21 

1.88 

1.21 

0.96 

2.10 

1.48 

1.37 

4.17 

3.70 

3.58 

Spill Cleanupn 

No wipeh 

Partial wipei 

Full wipej 

1.23 

0.55 

-

0.73 

0.51 

-

0.89 

0.48 

-

1.19 

1.36 

-

-

-

-

-

-

- a Density = 0.8720 g/cm3 

. b Density = 0.9161 g/cm3 

. c Density = 0.8660 g/cm3 

. d Density = 0.9357 g/cm3

; 50% water and 50% oil. e Density = 0.9989 g/cm3 

. f Density = 0.9297 g/cm3

; 50% water and 50% ethanol. g Initial contact = cloth saturated with liquid was rubbed over the front and back of both clean, dry 

hands for the first time during an exposure event. h Retention of liquid on the skin was estimated without any intentional removal of liquid by wiping. i Retention was measured after ‘partial’ removal of liquids on the skin by wiping. Partial wiping 

was defined as “lightly [wiping with a removal cloth] for 5 seconds (superficially).” 

j Retention was measured after ‘full’ removal of liquids on the skin by wiping. Full wiping was 

defined as “ thoroughly and completely as possible within 10 seconds removing as much liquid as 

possible.” k Secondary contact = cloth saturated with liquid was rubbed over the front and back of both hands 

for a second time, after as much as possible of the liquid that adhered to skin during the first 

contact event was removed using a clean cloth. l Immersion = one hand immersed in a container of liquid, removed, and liquid allowed to drip back 

into container for 30 seconds (60 seconds for cooking oil). m Handling rag = cloth saturated with liquid was rubbed over the palms of both hands for the first 

time during an exposure event in a manner simulating handling of a wet cloth. n Spill cleanup = subject used a clean cloth to wipe up 50 mL of liquid poured onto a plastic 

laminate countertop. 

- = no data. 

Note: Data for mineral oil, cooking oil, and bath oil for initial contact, secondary contact, and immersion 

from U.S. EPA (1992c). All other data from U.S. EPA (1987). 

Source: U.S. EPA (1987) and U.S. EPA (1992c). 

Exposure Factors Handbook Page
 

November 2011 7-57 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-25. Mean Transfer Efficiencies (%)a 

Time After 

Applicationb 

Legs 

(tights) 

Torso and Arms 

(shirt) 

Feet 

(socks) 

Hands 

(gloves) 

0 hours 

chlorpyrifos 

allethrin 

6.6 ± 1.6 

5.9 ± 1.5 

5.6 ± 2.6 

5.4 ± 2.4 

32.1 ± 13.4 

34.3 ± 18.3 

6 hours 

chlorpyrifos 

allethrin 

7.5 ± 4.6 

5.3 ± 2.0 

6.3 ± 5.8 

4.8 ± 2.5 

33.3 ± 12.9 

27.1 ± 8.8 

12.5 hours 

chlorpyrifos 

allethrin 

4.0 ± 1.3 

3.0 ± 0.8 

3.1 ± 0.5 

2.8 ± 0.5 

20.3 ± 3.5 

13.7 ± 4.7 

17.4 ± 8.6 

22.4 ± 12.6 

16.9 ± 11.0 

17.9 ± 9.1 

8.1 ± 1.9 

8.3 ± 2.7 

a Clothing residue values divided by floor residues and multiplied by 100. b After room was vented. 

Source: Ross et al. (1990). 

Table 7-26. Transfer Efficiencies (%) for Dry, Water-Wetted, and Saliva-Wetted Palms and PUF Roller 

Dry Palms Water-Wetted Palms Saliva-Wetted Palms PUF Roller 

Chlorpyrifos 

Mean 

SD 

1.53 

0.73 

5.22 

3.02 

4.38 

2.83 

4.19 

2.87 

Pyrethrin 

Mean 

SD 

3.64 

2.21 

11.87 

7.25 

8.89 

4.66 

5.66 

3.60 

Piperonyl Butoxide 

Mean 

SD 

1.41 

0.73 

4.85 

2.95 

4.06 

2.64 

4.28 

3.33 

SD = Standard deviation. 

PUF = Polyurethane foam. 

Source: Clothier (2000). 

Page Exposure Factors Handbook 

7-58 November 2011 
Table 7-27. Incremental and Overall Surface-to-Hand Transfer Efficiencies (%) 

Hand Condition Surface Type Surface Loading 

Contact Dry Moist Sticky Carpet Laminate High Low 

Incremental transfer %, average (SD) 

1 3.0 (2.7) 7.1 (6.1) 14 (18) 6.4 (7.0) 10 (16) 3.9 (4.0) 13 (16) 

2 2.5 (4.0) 7.7 (5.7) 7.5 (18) 8.0 (9.5) 3.6 (13) 3.7 (3.5) 8.1 (16) 

3 2.0 (5.4) 4.0 (7.3) 6.9 (7.3) 3.8 (7.2) 4.8 (6.8) 1.7 (1.7) 7.0 (9.0) 

4 0.9 (3.1) 1.9 (2.5) 2.3 (8.0) 1.1 (6.3) 2.3 (4.2) 0.9 (1.8) 2.7 (7.4) 

5 1.3 (2.2) 1.0 (3.7) 2.0 (5.3) 1.7 (2.4) 1.3 (4.9) 0.3 (1.1) 2.5 (5.0) 

Incremental transfer %, average (SD) without sticky hands 

1 3.0 (2.7) 7.1 (6.1) - 4.9 (5.3 5.2 (4.9) 2.6 (2.1) 7.5 (6.0) 

2 2.5 (4.0) 7.7 (5.7) - 5.8 (6.0) 4.2 (4.9) 2.8 (3.0) 7.3 (6.6) 

3 2.0 (5.4) 4.0 (7.3) - 2.1 (6.4) 4.0 (6.4) 1.4 (1.3) 4.7 (8.8) 

4 0.9 (3.1) 1.9 (2.5) - 0.9 (3.0) 1.9 (2.6) 1.0 (1.8) 1.8 (3.8) 

5 1.3 (2.3) 1.0 (3.7) - 1.6 (1.6) 0.7 (3.8) 0.4 (1.2) 1.9 (3.9) 

Overall transfer %, average (SD) 

1 3.0 (2.7) 7.1 (6.1) 14 (18) 6.4 (7.0) 10 (16) 3.9 (4.0) 13 (16) 

2 2.8 (2.5) 7.4 (5.2) 11 (9.7) 7.2 (7.6) 6.9 (7.1) 3.8 (3.1) 10 (8.8) 

3 2.5 (2.9) 6.2 (4.7) 9.7 (7.6) 6.1 (6.3) 6.2 (6.0) 3.1 (2.2) 9.3 (7.2) 

4 2.1 (2.4) 5.3 (4.0) 7.9 (7.0) 5.0 (5.7) 5.4 (5.4) 2.5 (1.7) 8.2 (6.6) 

5 1.6 (0.8) 4.2 (3.4) 8.2 (6.9) 4.6 (5.3) 4.6 (5.1) 1.8 (1.0) 7.1 (6.0) 

Overall transfer %, average (SD) without sticky hands 

1 3.0 (2.7) 7.1 (6.1) - 4.9 (5.3) 5.2 (4.9) 2.6 (2.1) 7.5 (6.0) 

2 2.8 (2.5) 7.4 (5.2) - 5.4 (5.0) 4.7 (4.3) 2.7 (2.1) 7.4 (5.3) 

3 2.5 (2.9) 6.2 (4.7) - 4.3 (4.0) 4.4 (4.6) 2.3 (1.4) 6.5 (5.1) 

4 2.1 (2.4) 5.3 (4.0) - 3.3 (3.3) 3.9 (4.0) 1.9 (1.1) 5.7 (4.4) 

5 1.6 (0.8) 4.2 (3.4) - 2.8 (2.4) 2.8 (3.0) 1.4 (0.5) 4.2 (3.2) 

SD = Standard deviation. 

Source: Cohen Hubal et al. (2005). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Exposure Factors Handbook Page
 

November 2011 7-59 
 

 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-28. Lognormal Distributions for Modeling Transfer Efficiencies (fraction)a 

Chemical Surface μ σ GM GSD 

Chlorpyrifos Carpet 

Vinyl 

Foil 

−4.26 

−3.30 

−0.15 

0.54 

0.85 

0.08 

0.01 

0.04 

0.86 

Pyrethrin I Carpet 

Vinyl 

Foil 

−3.86 

−3.66 

−0.19 

0.68 

0.96 

0.10 

0.02 

0.03 

0.83 

Piperonyl 

butoxide 

Carpet 

Vinyl 

−4.00 

−3.63 

0.51 

0.81 

0.02 

0.03 

1.70 

2.34 

1.08 

1.97 

2.61 

1.11 

1.67 

2.25 

a Distributions should be truncated at 1.0. 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

Source: Beamer et al. (2009). 

Table 7-29. Hand-to-Object/Surface Contact—Frequency (contacts/hour) 

Object/Surface Left Hand Averagea Right Hand Averagea 

Bedding/Towel 13.0 13.8 

Carpet/Rug 4.3 6.0 

Dirt 5.3 6.5 

Food 9.3 9.3 

Footwear 2.0 3.0 

Grass/Vegetation 6.3 5.0 

Hair 4.5 3.5 

Hard Floor 10.0 9.5 

Hard Surface 36.0 40.3 

Hard Toy 27.3 29.3 

Paper/Card 8.8 14.5 

Plush Toy 4.0 4.0 

Upholstered Furniture 17.0 15.5 

Water/Beverage 1.3 1.8 

a Average = mean of average hourly contact rates of 4 children of farm workers, ages 2 to 4 years. 

Source: Zartarian et al. (1997). 

Page Exposure Factors Handbook 

7-60 November 2011 
Table 7-30. Hand-to-Objects/Surfaces—Frequency (contacts/hour) 

Both Hands

a 

Object/Surface 

Range Mean Median 90th Percentile 

Clothing 22.8−129.2 66.6 65.0 103.3 

Dirt 0−146.3 11.4 0.3 56.4 

Object 56.2−312.0 122.9 118.7 175.8 

Other

b 8.3−243.6 82.9 64.3 199.6 

Smooth Surface 13.6−190.4 83.7 80.2 136.9 

Textured Surface 0.2−68.7 22.1 16.3 52.2 

a Based on data for 30 children (20 daycare children and 10 residential children) ages 2 to 6 years. b Other includes items such as paper, grass, and pets. 

Source: Reed et al. (1999). 

Table 7-31. Median (mean ± SD) Hand Contact Frequency With Clothing, Surfaces, or Objects (contacts/hour)

a 

Age 3 to 4 years 5 to 6 years 7 to 8 years 10 to 12 years 

N 3 7 4 5 

Touch Clothing 26 (34 ± 21) 22 (26 ± 23) 50 (54 ± 43) 35 (53 ± 66) 

Touch Textured Surface 40 (52 ± 61) 20 (32 ± 40) 22 (58 ± 88) 16 (24 ± 31) 

Touch Smooth Surface 134 (151 ± 62) 111 (120 ± 77) 120 (155 ± 119) 94 (96 ± 50) 

Touch Object 130 (153 ± 108) 117 (132 ± 88) 111 (164 ± 148) 127 (179 ± 126) 

a Based on 4-hour observation period. 

SD = Standard deviation. 

N = Number of children observed. 

Source: Freeman et al. (2001). 

Table 7-32. Hand Contact with Objects/Surfaces—Frequency (contacts/hour) 

Right Handa 

Object/Surface Mean (SD) Median (range) 

Bottle 14.6 (17.9) 11.5 (1.3−63.0) 

Carpet/Rug 6.3 (9.3) 1.1 (0−23.0) 

Clothes 38.0 (16.4) 41.9 (12.8−66.8) 

Food 9.2 (6.6) 7.3 (3.0−20.8) 

Hair 5.1 (3.6) 4.1 (1.3−11.8) 

Hard Floor 9.5 (6.2) 10.3 (1.3−17.5) 

Object 97.7 (45.8) 96.8 (25.0−176.4) 

Paper 22.9 (18.0) 21.8 (1.3−54.3) 

Skin 31.5 (15.3) 26.4 (16.0−63.5) 

Smooth Surface 83.9 (38.0) 88.0 (32.0−158.4) 

Textured Surface 6.5 (5.7) 4.1 (1.0−20.7) 

Upholstered Furniture 20.7 (15.2) 19.3 (6.8−55.5) a Only data for the right hand were reported; data for 10 children, ages 24 to 55 months. 

SD = Standard deviation. 

Source: Freeman et al. (2005). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Exposure Factors Handbook Page
 

November 2011 7-61 
Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 7-62 

Table 7-33. Outdoor Hand Contact With Objects/Surfaces, Children 1 to 6 Yearsa 

Object/Surface 

Both Hands 

Range Mean Median 95th 

Percentile 

Range Mean Median 95th 

Percentile 

Range Mean Median 95th 

Percentile 

Frequency (contacts/hour) Duration (seconds/contact) Duration (minutes/hour) 

Animal 

Body 

Clothes/Towel 

Fabric 

Floor 

Food 

Footwear 

Metal 

Non-Dietary Water 

Paper/Wrapper 

Plastic 

Rock/Brick 

Toy 

Vegetation/Grass 

Wood 

Non-Dietary Object 

All Objects/Surfaces 

0−23.3 

17−191.7 

17−199.1 

0−31.5 

0−940.4 

0−88.7 

0−23.1 

0.6−466.2 

0.7.4 

0−103.8 

0−324.6 

0−28 

0−657.8 

0−138.7 

0.6−100.9 

225.1−1,512.6 

229.9−1,517.7 

2.6 

74.8 

73.7 

3.7 

65.8 

14.5 

3.6 

58.3 

0.5 

7.3 

56.7 

2.4 

161.3 

40.6 

22.4 

575.3 

589.8 

0 

65.1 

65.7 

0.4 

27.9 

4.9 

1.5 

16 

0 

1.5 

47 

0 

129.4 

27.8 

12.7 

526.3 

540.8 

13.8 

150.4 

132 

14.7 

182.7 

56.2 

11.4 

206.4 

2.9 

21.4 

121.1 

10.3 

372.8 

128.1 

79.8 

889.2 

889.2 

1.5−7 

1−4 

1−5 

0.5−23.5 

0−13 

0−28 

0−12 

0−109.5 

0.5−9 

0−53.5 

1−21.5 

1−9 

0−25.5 

0−11 

0−9 

0−5 

0−5 

3.2 

2 

2.5 

5.9 

3 

7.6 

3.3 

7.3 

3.3 

9.4 

5.1 

2.8 

6.5 

3.7 

3.7 

3 

3 

2.5 

2 

2 

3 

2 

6 

2.5 

3 

2 

4.3 

4 

2 

6 

3 

3 

3 

3 

6.5 

3.2 

4.6 

15.4 

6.5 

20.8 

8.1 

15.8 

8.2 

28.1 

12.8 

7.5 

13.5 

9.1 

8 

4 

4.2 

0−2 

0.6−17.8 

1.4−26.3 

0−6.6 

0−16.4 

0−17.3 

0−5.6 

0−36.3 

0−1 

0−27 

0−26.3 

0−3.7 

0−63.1 

0−21.5 

0−27.8 

42.6−101.7 

42.6−102.2 

0.2 

5 

6.7 

0.7 

4 

3.9 

0.5 

7.4 

0.1 

1.8 

8 

0.2 

29.8 

5.1 

3.2 

72.9 

76.8 

0 

4.1 

4.8 

0 

2.4 

0.4 

0 

3.2 

0 

0.4 

6 

0 

28.4 

2.9 

1.2 

72.3 

77.5 

1.6 

11.2 

18.2 

3.9 

12.2 

17 

2 

27.3 

0.6 

7.8 

20.6 

1 

57 

17.9 

12.8 

94.2 

99.3 a Based on 38 children aged 1 to 6 years in parks, playgrounds, and outdoor residential areas in California. 

Source: AuYeung et al. (2006). 
 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7-34. Indoor Hand Contact With Objects/Surfaces—Frequency, Children 1 to 6 Yearsa (median contacts/hour) 

Object/Surface Left Hand Right Hand 

Carpet 

Clothing 

Hard Floor 

Paper 

Skin 

Upholstered Furniture 

Smooth Surface 

Textured Surfaces 

7.9 

41 

3.2 

3.8 

11.6 

13.1 

61.9 

18.2 

8.5 

25.2 

3.9 

7.4 

9.9 

7.7 

62.7 

22.1 a Based on 9 children aged 1 to 6 years in indoor residential settings in California. 

Source: AuYeung et al. (2006). 

Table 7-35. Outdoor Hand Contact With Surfaces—Frequency, Children 1 to 5 Yearsa (contacts/hour) 

Object/Surface Both Hands 

N Range Geometric Mean SD Median 90th Percentile 

Cement 

Porch 

Grass 

Bare Soil 

All Surfaces 

37 

22 

34 

27 

37 

0−240 

0−104 

0−183 

0−81 

3−405 

27 

12 

8 

6 

70 

0.59 

0.74 

0.71 

0.67 

0.44 

36 

16 

7 

5 

81 

107 

86 

71 

71 

193 a Based on observations of a total of 37 children aged 1 to 5 years (primarily low-income, Hispanic) in outdoor 

residential areas in Illinois. 

N = Number of subjects. 

SD = Standard deviation of log-transformed contacts/hour. 

Source: Ko et al. (2007). 

Exposure Factors Handbook Page
 

November 2011 7-63 
 

Table 7-36. Hand Contact With Objects/Surfaces, Infants and Toddlers

a 

Object/Surface 

Both Hands 

Range Mean Median Range Mean Median Range Mean Median 

Frequency (contacts/hour) Duration (minutes/hour)

b Duration (seconds/contact) 

Animal 

Body 

Clothes/Towel 

Fabric 

Floor 

Food 

Footwear 

Metal 

Non-Dietary Water 

Paper/Wrapper 

Plastic 

Rock/Brick 

Toy 

Vegetation 

Wood 

Non-Dietary Object 

All Objects/Surfaces 

0.0−4.3 

16.6−147.1 

39.2−237.9 

0.0−134.4 

0.0−594.5 

0.0−170.7 

0.0−47.0 

0.0−52.4 

0.0−2.6 

0.0−75.3 

10.9−294.9 

0.0−17.4 

28.3−300.4 

0.0−16.3 

0.0−65.4 

266.8−1,180.0 

303.1−1,206.0 

0.2 

76.8 

113.8 

45.6 

96.0 

51.8 

7.8 

17.3 

0.2 

18.1 

87.1 

3.4 

121.2 

3.8 

24.9 

600.8 

686.3 

0.0 

70.5 

100.9 

37.6 

41.5 

42.7 

2.4 

14.5 

0.0 

18.7 

76.1 

1.6 

98.8 

0.3 

27.2 

568.7 

689.4 

0.0−0.2 

1.6−21.9 

4.5−31.0 

2.1−21.6 

0.0−32.2 

0.0−37.1 

0.0−7.7 

0.0−5.2 

0.0−0.0 

0.0−13.9 

0.9−50.6 

0.0−1.8 

9.8−54.1 

0.0−2.2 

0.0−10.6 

62.6−106.2 

76.4−124.1 

0.0 

7.5 

13.1 

10.3 

7.0 

14.2 

1.1 

2.0 

0.0 

3.7 

13.5 

0.3 

25.2 

0.3 

3.5 

83.1 

99.1 

0.0 

5.9 

12.4 

9.1 

4.3 

12.1 

0.3 

1.9 

0.0 

3.1 

10.9 

0.1 

9.8 

0.0 

3.9 

83.2 

100.5 

1.5−2.0 

1.0−3.0 

1.0−4.0 

2.0−9.0 

0.5−5.0 

2.0−24.0 

1.0−11.0 

0.8−9.0 

0.5−1.0 

1.5−11.5 

0.5−8.0 

1.0−5.0 

3.0−11.5 

0.5−4.0 

1.5−8.0 

2.0−5.0 

2.0−5.0 

1.8 

2.3 

2.9 

3.6 

2.3 

7.1 

3.8 

3.4 

0.8 

4.4 

3.8 

2.7 

5.8 

2.7 

3.8 

3.2 

3.3 

1.8 

2.0 

3.0 

3.0 

2.5 

7.0 

3.0 

3.0 

0.8 

4.0 

4.0 

3.0 

5.0 

3.0 

3.0 

3.0 

3.0 a Based on 23 farm worker children (ages 6 to 26 months) from California. b Hourly contact duration for both hands is the sum of the hourly contact durations for the left and right hands 

independently. 

Source: Beamer et al. (2008). 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

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7-64 November 2011 
Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Figure 7-1. Frequency Distributions for the Surface Area of Men and Women. 

Source: Murray and Burmaster (1992) 

Exposure Factors Handbook Page
 

November 2011 7-65 
Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Page Exposure Factors Handbook 

7-66 November 2011 

Figure 7-2. Skin Coverage as Determined by Fluorescence Versus Body Part for Adults Transplanting
 

Plants and Children Playing in Wet Soils (bars are arithmetic means and corresponding
 

95% confidence intervals).
 

Source: Kissel et al. (1998). 

Figure 7-3. Gravimetric Loading Versus Body Part for Adults Transplanting Plants in Wet Soil and 

Children Playing in Wet and Dry Soils (symbols are geometric means and 95% confidence 

intervals). 

Source: Kissel et al. (1998). 
Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

APPENDIX 7A
 

FORMULAS FOR TOTAL BODY SURFACE AREA
 

Exposure Factors Handbook Page
 

November 2011 7A-1 
 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

APPENDIX 7A—FORMULAS FOR TOTAL 

BODY SURFACE AREA 

Most formulas for estimating surface area relate 

height to weight to surface area. The following 

formula was proposed by Gehan and George (1970): 

SA = KW2/3 (Eqn. 7A-1) 

where: 

SA = surface area in square meters, 

W = weight in kg, and 

K = constant. 

While this equation has been criticized because 

human bodies have different specific gravities and 

because the surface area per unit volume differs for 

individuals with different body builds, it gives a 

reasonably good estimate of surface area. 

A formula published in 1916 that still finds wide 

acceptance and use is that of Du Bois and Du Bois 

(1989). Their model can be written: 

a

1 a2 SA = a H W (Eqn. 7A-2) 0 

where: 

SA = surface area in square meters, 

H = height in centimeters, and 

W = weight in kg. 

The values of a0 (0.007182), a1 (0.725), and a2 

(0.425) were estimated from a sample of only 

nine individuals for whom surface area was directly 

measured. Boyd (1935) stated that the Du Bois 

formula was considered a reasonably adequate 

substitute for measuring surface area. Nomograms for 

determining surface area from height and mass 

presented in Volume I of the Geigy Scientific Tables 

(Lentner, 1981) are based on the Du Bois and Du 

Bois formula. 

Boyd (1935) developed new constants for the Du 

Bois and Du Bois model based on 231 direct 

measurements of body surface area found in the 

literature. These data were limited to measurements 

of surface area by coating methods (122 cases), 

surface integration (93 cases), and triangulation 

(16 cases). The subjects were Caucasians of normal 

body build for whom data on weight, height, and age 

(except for exact age of adults) were complete. 

Resulting values for the constants in the Du Bois and 

Du Bois model were a0 = 0.01787, a1 = 0.500, and 

a2 = 0.4838. Boyd also developed a formula based 

exclusively on weight, which was inferior to the Du 

Bois and Du Bois formula based on height and 

weight. 

Gehan and George (1970) proposed another set of 

constants for the Du Bois and Du Bois model. The 

constants were based on a total of 401 direct 

measurements of surface area, height, and weight of 

all postnatal subjects listed in Boyd (1935). The 

methods used to measure these subjects were coating 

(163 cases), surface integration (222 cases), and 

triangulation (16 cases). 

Gehan and George (1970) used a least-squares 

method to identify the values of the constants. The 

values of the constants chosen are those that 

minimize the sum of the squared percentage errors of 

the predicted values of surface area. This approach 

was used because the importance of an error of 

0.1 square meter depends on the surface area of the 

individual. Gehan and George (1970) used the 

401 observations summarized in Boyd (1935) in the 

least-squares method. The following estimates of the 

constants were obtained: a0 = 0.02350, a1 = 0.42246, 

and a2 = 0.51456. Hence, their equation for predicting 

surface area is: 

SA = 0.02350 H0.42246W0.51456 (Eqn. 7A-3) 

or in logarithmic form: 

ln SA = −3.75080 + 0.42246 lnH + 0.51456 lnW 

(Eqn. 7A-4) 

where: 

SA = surface area in square meters, 

H = height in centimeters, and 

W = weight in kg. 

This prediction explains more than 99% of the 

variations in surface area among the 401 individuals 

measured (Gehan and George, 1970). 

The equation proposed by Gehan and George 

(1970) was determined by the U.S. EPA (1985) to be 

the best choice for estimating total body surface area. 

However, the paper by Gehan and George gave 

insufficient information to estimate the standard error 

about the regression. Therefore, the 401 direct 

measurements of children and adults [i.e., Boyd 

(1935)] were reanalyzed in U.S. EPA (1985) using 

the formula of Du Bois and Du Bois (1989) and the 

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7A-2 November 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Statistical Processing System (SPS) software package 

to obtain the standard error. 

The Du Bois and Du Bois (1989) formula uses 

weight and height as independent variables to predict 

total body surface area and can be written as: 

a H a a SA1 = 1 W 2 

0 i i e i (Eqn. 7A-5) 

or in logarithmic form: 

ln (SA)i = lna0 + a1lnHi + a2lnWi + lnei (Eqn. 7A-6) 

where: 

SAi = surface area of the i-th 

individual (m2

), 

Hi = height of the i-th individual 

(cm), 

Wi = weight of the i-th individual 

(kg), 

a0, a1, and a2 = parameters to be estimated, 

and 

ei = a random error term with 

mean zero and constant 

variance. 

Using the least squares procedure for the 

401 observations, the following parameter estimates 

and their standard errors were obtained: 

a0 = −3.73 (0.18), a1 = 0.417 (0.054), a2 = 0.517 

(0.022) 

The model is then: 

SA = 0.0239 H0.417 W0.517 (Eqn. 7A-7) 

or in logarithmic form: 

ln SA = −3.73 + 0.417 lnH + 0.517 lnW (Eqn. 7A-8) 

with a standard error about the regression of 0.00374. 

This model explains more than 99% of the total 

variation in surface area among the observations, and 

it is identical to two significant figures with the 

model developed by Gehan and George (1970). 

When natural logarithms of the measured surface 

areas are plotted against natural logarithms of the 

surface predicted by the equation, the observed 

surface areas are symmetrically distributed around a 

line of perfect fit with only a few large percentage 

deviations. Only five subjects differed from the 

measured value by 25% or more. Because each of the 

five subjects weighed less than 13 pounds, the 

amount of difference was small. Eighteen estimates 

differed from measurements by 15 to 24%. Of these, 

12 weighed less than 15 pounds each, one was 

overweight (5 feet 7 inches, 172 pounds), one was 

very thin (4 feet 11 inches, 78 pounds), and four were 

of average build. Because the same observer 

measured surface area for these four subjects, the 

possibility of some bias in measured values cannot be 

discounted (Gehan and George, 1970). Gehan and 

George (1970) also considered separate constants for 

different age groups: less than 5 years old, 5 years old 

to less than 20 years old, and greater than 20 years 

old. Table 7A-1 presents the different values for the 

constants. 

The surface areas estimated using the parameter 

values for all ages were compared to surface areas 

estimated by the values for each age group for 

subjects at the 3rd, 50th, and 97th percentiles of weight 

and height. Nearly all differences in surface area 

estimates were less than 0.01 m2

, and the largest 

difference was 0.03 m2 for an 18-year-old at the 

97th percentile. The authors concluded that there is no 

advantage in using separate values of a0, a1, and a2 by 

age interval. 

Haycock et al. (1978), without knowledge of the 

work by Gehan and George (1970), developed values 

for the parameters a0, a1, and a2 for the Du Bois and 

Du Bois model. Their interest in making the Du Bois 

and Du Bois model more accurate resulted from their 

work in pediatrics and the fact that Du Bois and Du 

Bois (1989) included only one child in their study 

group: a severely undernourished girl who weighed 

only 13.8 pounds at age 21 months. Haycock et al. 

(1978) used their own geometric method for 

estimating surface area from 34 body measurements 

for 81 subjects. Their study included newborn infants 

(10 cases), infants (12 cases), children (40 cases), and 

adult members of the medical and secretarial staffs of 

two hospitals (19 cases). The subjects all had grossly 

normal body structure, but the sample included 

subjects of widely varying physique ranging from 

thin to obese. Black, Hispanic, and Caucasian 

children were included in their sample. The values of 

the model parameters were solved for the relationship 

between surface area and height and weight by 

multiple regression analysis. The least squares best fit 

for this equation yielded the following values for the 

three co-efficients: a0 = 0.024265, a1 = 0.3964, and 

a2 = 0.5378. The result was the following equation 

for estimating surface area: 

Exposure Factors Handbook Page
 

November 2011 7A-3 
 

SA = 0.024265H0.3964 W0.5378 (Eqn. 7A-9) 

expressed logarithmically as: 

ln SA = ln 0.024265 + 0.3964 ln H + 0.5378 ln W 

(Eqn. 7A-10) 

The co-efficients for this equation agree 

remarkably with those obtained by Gehan and 

George (1970) for 401 measurements. 

George et al. (1979) agree that a model more 

complex than the model of Du Bois and Du Bois for 

estimating surface area is unnecessary. Based on 

samples of direct measurements by Boyd (1935) and 

Gehan and George (1970), and samples of geometric 

estimates by Haycock et al. (1978), these authors 

have obtained parameters for the Du Bois and Du 

Bois model that are different than those originally 

postulated in 1916. The Du Bois and Du Bois model 

can be written logarithmically as: 

lnSA = lna0 + a1 lnH + a2 lnW (Eqn. 7A-11) 

Table 7A-2 present the values for a0, a1, and a2 

obtained by the various authors discussed in this 

section. 

The agreement between the model parameters 

estimated by Gehan and George (1970) and Haycock 

et al. (1978) is remarkable in view of the fact that 

Haycock et al. (1978) were unaware of the previous 

work. Haycock et al. (1978) used an entirely different 

set of subjects and used geometric estimates of 

surface area rather than direct measurements. It has 

been determined that the Gehan and George model is 

the formula of choice for estimating total surface area 

of the body because it is based on the largest number 

of direct measurements. 

Sendroy and Cecchini (1954) proposed a method 

of creating a nomogram, a diagram relating height 

and weight to surface area. However, they do not give 

an explicit model for calculating surface area. The 

nomogram was developed empirically based on 

252 cases, 127 of which were from the 401 direct 

measurements reported by Boyd (1935). In the other 

125 cases, the surface area was estimated using the 

linear method of Du Bois and Du Bois (1989). 

Because the Sendroy and Cecchini method is 

graphical, it is inherently less precise and less 

accurate than the formulas of other authors discussed 

in this section. 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

7A.1. REFERENCES FOR APPENDIX 7A 

Boyd, E. (1935). The growth of the surface area of 

the human body. Minneapolis, MN: 

University of Minnesota Press. 

http://www.upress.umn.edu/bookdivision/books/the-growth-of-the-surfacearea-of-the-human-body. 

Du Bois, D; Du Bois, EF. (1989). A formula to 

estimate the approximate surface area if 

height and weight be known. 1916. Nutrition 

5: 303-311; discussion 312-303. 

Gehan, EA; George, SL. (1970). Estimation of 

human body surface area from height and 

weight. 54: 225-235. 

George, SL; Gehan, EA; Haycock, GB; al., e. (1979). 

Letters to the editor [Letter]. J Pediatr 94: 

342. 

Haycock, GB; Schwartz, GJ; Wisotsky, DH. (1978). 

Geometric method for measuring body 

surface area: a height-weight formula 

validated in infants, children, and adults. J 

Pediatr 93: 62-66. 

Lentner, C. (1981). Geigy scientific tables. West 

Caldwell, NJ: CIBA-Geigy Corporation. 

Sendroy, J; Cecchini, LP.	 (1954). Determination of 

human body surface area from height and 

weight. J Appl Physiol 7: 1-12. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1985). Development of statistical 

distributions or ranges of standard factors 

used in exposure assessments. 

(EPA600885010). 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB85242667. 

Page Exposure Factors Handbook 

7A-4 November 2011 
 

Exposure Factors Handbook 

Chapter 7—Dermal Exposure Factors 

Table 7A-1. Estimated Parameter Values for Different Age Intervals 

Age 

Group 

Number 

of Persons a0 a1 a2 

All ages 401 0.02350 0.42246 

<5 years old 229 0.02667 0.38217 

≥5 to <20 years old 42 0.03050 0.35129 

≥20 years old 30 0.01545 0.54468 

0.51456 

0.53937 

0.54375 

0.46336 

Source: Gehan and George (1970). 

Table 7A-2. Summary of Surface Area Parameter Values for the Du Bois and Du Bois Model 

Author 

(year) 

Number 

of Persons a0 a1 a2 

Du Bois and Du Bois (1989) 9 0.007184 0.725 0.425 

Boyd (1935) 231 0.01787 0.500 0.4838 

Gehan and George (1970) 401 0.02350 0.42246 0.51456 

Haycock et al. (1978) 81 0.024265 0.3964 0.5378 

Exposure Factors Handbook Page
 

November 2011 7A-5 
Exposure Factors Handbook 

Chapter 8―Body Weight Studies 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

8. BODY-WEIGHT STUDIES 

8.1. INTRODUCTION 

There are several physiological factors needed to 

calculate potential exposures. These include skin 

surface area (see Chapter 7), inhalation rate (see 

Chapter 6) life expectancy (see Chapter 18), and 

body weight. The average daily dose (ADD) is a dose 

that is typically normalized to the average body 

weight of the exposed population. If exposure occurs 

only during childhood years, the average child body 

weight during the exposure period should be used to 

estimate risk (U.S. EPA, 1989). Conversely, if adult 

exposures are being evaluated, an adult body-weight 

value should be used. 

The purpose of this chapter is to describe 

published studies on body weight in the general U.S. 

population. The recommendations for body weight 

are provided in the next section, along with a 

summary of the confidence ratings for these 

recommendations. The recommended values are 

based on one key study identified by 

U.S. Environmental Protection Agency (EPA) for 

this factor. Following the recommendations, the key 

study on body weight is summarized. Relevant data 

on body weight are also provided. These relevant 

data are included because they may be useful for 

trend analysis. Since obesity is a growing concern 

and may increase the risk of chronic diseases during 

adulthood, information on body mass index (BMI) 

and height is also provided. 

8.2. RECOMMENDATIONS 

The key study described in this section was used 

in selecting recommended values for body weight. 

The recommendations for body weight are 

summarized in Table 8-1 and are based on data 

derived from the National Health and Nutrition 

Examination Survey (NHANES) 1999−2006. The 

recommended values represent mean body weights in 

kilograms for the age groups for children 

recommended by U.S. EPA in Guidance for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005) and 

for adults. Table 8-2 presents the confidence ratings 

for the body-weight recommendations. 

Table 8-1 shows the mean body weight for all 

adults (male and female, all age groups) combined is 

80 kg. Section 8.3 presents percentile data. 

The mean recommended value for adults (80 kg) 

is different from the 70 kg commonly assumed in 

U.S. EPA risk assessments. Assessors are encouraged 

to use values that most accurately reflect the exposed 

population. When using values other than 70 kg, 

however, the assessors should consider if the dose 

estimate will be used to estimate risk by combining it 

with a dose-response relationship that was derived 

assuming a body weight of 70 kg. If such an 

inconsistency exists, the assessor may need to adjust 

the dose-response relationship as described in the 

appendix to Chapter 1. 

Use of upper percentile body-weight values are 

not routinely recommended for calculating ADDs 

because inclusion of an upper percentile value in the 

denominator of the ADD equation would be a 

non-conservative approach. However, Section 8.3 

provides distributions of body-weight data. These 

distributions may be useful if probabilistic methods 

are used to assess exposure. Also, if sex-specific data 

are needed, or if data for finer age bins are needed, 

the reader should refer to the tables in Section 8.3. 

Exposure Factors Handbook Page 

September 2011 8-1 
Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-1. Recommended Values for Body Weight 

Age Group Mean (kg) Multiple Percentiles Source 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <11 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

Adults 

4.8 

Table 8-3 

through Table 8-5 

5.9 

7.4 

9.2 

11.4 

13.8 

18.6 

31.8 

56.8 

71.6 

80.0 

U.S. EPA 

analysis of 

NHANES, 

1999−2006 data 

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Exposure Factors Handbook 

Chapter 8―Body Weight Studies 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 8-2. Confidence in Recommendations for Body Weight 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodology and the secondary data analysis 

were adequate. NHANES consisted of a large sample size; 

sample size varied with age. Direct measurements were 

taken during a physical examination. 

No significant biases were apparent. 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key study is directly relevant to body weight. 

NHANES was a nationally representative sample of the 

U.S. population; participants are selected using a complex, 

stratified, multi-stage probability cluster sampling design. 

The U.S. EPA analysis used the most current NHANES 

data. 

The U.S. EPA analysis was based on four data sets of 

NHANES data covering 1999−2006. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

NHANES data are available from NCHS. 

The methods used were well-described; enough information 

was provided to allow for reproduction of results. 

NHANES follows a strict QA/QC procedures; the U.S. EPA 

analysis has only been reviewed internally. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

The full distributions were given in the key study. 

No significant biases were apparent in the NHANES data, 

nor in the secondary analyses of the data. 

High 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

NHANES received a high level of peer review. The 

U.S. EPA analysis was not published in a peer-reviewed 

journal. 

The number of studies is 1. 

Medium 

Overall Rating High 

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Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

8.3.	 KEY BODY-WEIGHT STUDY 

8.3.1.	 U.S. EPA Analysis of NHANES 

1999−2006 Data 

The U.S. EPA analyzed data from the 1999−2006 

NHANES to generate distributions of body weight 

for various age ranges of children and adults. 

NHANES is conducted annually by the Center for 

Disease Control (CDC), National Center of Health 

Statistics (NCHS). The survey’s target population is 

the civilian, non-institutionalized U.S. population. 

The NHANES 1999−2006 survey was conducted on 

a nationwide probability sample of approximately 

40,000 persons for all ages, of which approximately 

20,000 were children. The survey is designed to 

obtain nationally representative information on the 

health and nutritional status of the population of the 

United States through interviews and direct physical 

examinations. A number of anthropometric 

measurements, including body weight, were taken for 

each participant in the study. Unit non-response to 

the household interview was 19%, and an additional 

4% did not participate in the physical examinations 

(including body-weight measurements). 

The NHANES 1999−2006 survey includes 

over-sampling of low-income persons, adolescents 

12−19 years, persons 60+ years of age, African 

Americans and Mexican Americans. Sample data 

were assigned weights to account both for the 

disparity in sample sizes for these groups and for 

other inadequacies in sampling, such as the presence 

of non-respondents. Because the U.S. EPA utilized 

four NHANES data sets in its analysis (NHANES 

1999−2000, 2001−2002, 2003−2004, and 

2005−2006) sample weights were developed for the 

combined data set in accordance with CDC guidance 

from the NHANES' website 

(http://www.cdc.gov/nchs/about/major/nhanes/nhane 

s2005-2006/faqs05_06.htm#question%2012). 

Using the data and the weighting factors from the 

four NHANES data sets, U.S. EPA calculated bodyweight statistics for the standard age categories. The 

mean value for a given group was calculated using 

the following formula: 

∑ w x i i 

x =	 i (Eqn. 8-1) ∑ wi 

i 

where: 

= sample mean, 

xi = the i

th observation, and 

wi = sample weight assigned to observation xi. 

x 

Percentile values were generated by first 

calculating the sum of the sample weights for all 

observations in a given group and multiplying this 

sum by the percentile of interest (e.g., multiplying by 

0.25 to determine the 25th percentile). The 

observations were then ordered from least to greatest, 

and each observation was assigned a cumulative 

sample weight, equal to its own sample weight plus 

all sample weights listed before the observation. The 

1st observation listed with a cumulative sample 

weight greater than the value calculated for the 

percentile of interest was selected. 

Table 8-3 presents the body-weight means and 

percentiles, by age category, for males and females 

combined. Table 8-4 and Table 8-5 present the bodyweight means and percentiles for males and females, 

respectively. 

The advantage of this study is that it provides 

body-weight distributions ranging from infancy to 

adults. A limitation of the study is that combining the 

data from various years of NHANES beginning in 

1999 through 2006 may underestimate current body 

weights due to an observed upward trend in body 

weights (Ogden et al., 2004). However, these data are 

based on the most recent available NHANES data. 

The NHANES data are nationally representative and 

remain the principal source of body-weight data 

collected nationwide from a large number of subjects. 

8.4.	 RELEVANT GENERAL POPULATION 

BODY-WEIGHT STUDIES 

8.4.1.	 Najjar and Rowland 

(1987)―Anthropometric Reference Data 

and Prevalence of Overweight, United 

States, 1976−1980 

Najjar and Rowland (1987) collected 

anthropometric measurement data for body weight 

for the U.S. population as part of the 2nd National 

Health and Nutrition Examination Survey (NHANES 

II). NHANES II began in February 1976 and was 

completed in February 1980. The survey was 

conducted on a nationwide probability sample of 

27,801 persons aged six months to 74 years from the 

civilian, non-institutionalized population of the 

United States. A total of 20,322 individuals in the 

sample were interviewed and examined, resulting in a 

response rate of 73.1%. The sample was selected so 

that certain subgroups thought to be at high risk of 

malnutrition (persons with low incomes, preschool 

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children, and the elderly) were over sampled. The 

estimates were weighted to reflect national 

population estimates. The weighting was 

accomplished by inflating examination results for 

each subject by the reciprocal of selection 

probabilities, adjusting to account for those who were 

not examined, and post-stratifying by race, age, and 

sex. 

NHANES II collected standard body 

measurements of sample subjects, including height 

and weight, that were made at various times of the 

day and in different seasons of the year. This 

technique was used because an individual’s weight 

may vary between winter and summer and may 

fluctuate with patterns of food and water intake and 

other daily activities (Najjar and Rowland, 1987). 

Najjar and Rowland (1987) provided descriptive 

statistics of the body-weight data. Table 8-6 and 

Table 8-7 present means and percentiles, by age 

category, for males and females, respectively. 

Although the NHANES data are nationally 

representative, a limitation of the study is the age of 

the data used. 

8.4.2.	 Brainard and Burmaster 

(1992)―Bivariate Distributions for 

Height and Weight of Men and Women in 

the United States 

Brainard and Burmaster (1992) examined data on 

the height and weight of adults published by the U.S. 

Public Health Service and fit bivariate distributions to 

the tabulated values for men and women, separately. 

Height and weight of 5,916 men and 6,588 women in 

the age range of 18 to 74 years were taken from the 

NHANES II (1976−1980) study and statistically 

adjusted to represent the U.S. population aged 18 to 

74 years with regard to age structure, sex, and race. 

Estimation techniques were used to fit normal 

distributions to the cumulative marginal data, and 

goodness-of-fit tests were used to test the hypothesis 

that height and lognormal weight follow a normal 

distribution for each sex. It was found that the 

marginal distributions of height and lognormal 

weight for both men and women are Gaussian 

(normal) in form. This conclusion was reached by 

visual observation and the high R2 values for best-fit 

lines obtained using linear regression. The R2 values 

for men's height and lognormal weight were reported 

to be 0.999. The R2 values for women's height and 

lognormal weight were reported as 0.999 and 0.985, 

respectively. 

Brainard and Burmaster (1992) fit bivariate 

distributions to estimated numbers of men and 

women aged 18 to 74 years in cells representing oneinch height intervals and 10-pound weight intervals. 

Adjusted height and lognormal weight data for men 

were fit to a single bivariate normal distribution with 

an estimated mean height of 1.75 meters 

(69.2 inches) and an estimated mean weight of 

78.6 kg (173.2 pounds). For women, height and 

lognormal weight data were fit to a pair of 

superimposed bivariate normal distributions 

(Brainard and Burmaster, 1992). The average height 

and weight for women were estimated from the 

combined bivariate analyses. Mean height for women 

was estimated to be 1.62 meters (63.8 inches), and 

mean weight was estimated to be 65.8 kg 

(145.0 pounds). For women, a calculation using a 

single bivariate normal distribution gave poor results 

(Brainard and Burmaster, 1992). 

The advantage of this study is that it provides 

distributions that are suitable for use in Monte Carlo 

simulation. However, these distributions are now 

based on dated information. 

8.4.3.	 Burmaster and Crouch 

(1997)―Lognormal Distributions for 

Body Weight as a Function of Age for 

Males and Females in the United States, 

1976−1980 

Burmaster and Crouch (1997) performed data 

analysis to fit normal and lognormal distributions to 

the body weights of females and males aged 

9 months to 70 years. The data used in this analysis 

were from NHANES II, which was based on a 

national probability sample of 27,801 persons 

6 months to 74 years of age in the United States. 

(Burmaster and Crouch, 1997). The NHANES II data 

had been statistically adjusted for non-response and 

probability of selection, and stratified by age, sex, 

and race to reflect the entire U.S. population prior to 

reporting. Burmaster and Crouch (1997) conducted 

exploratory and quantitative data analyses and fit 

normal and lognormal distributions to percentiles of 

body weights as a function of age. Cumulative 

distribution functions were plotted for female and 

male body weights on both linear and logarithmic 

scales. 

Burmaster and Crouch (1997) used “maximum 

likelihood” estimation to fit lognormal distributions 

to the data. Linear and quadratic regression lines 

were fitted to the data. A number of goodness-of-fit 

measures were conducted on the data generated. The 

investigators found that lognormal distributions gave 

strong fits to the data for each sex across all age 

groups. Table 8-8 and Table 8-9 present the statistics 

for the lognormal probability plots for females and 

males aged 9 months to 70 years, respectively. As 

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Chapter 8—Body Weight Studies 

indicated in Burmaster and Crouch (1997), Φ2, and σ2 

are the mean and standard deviation of the logarithm 

of body weight for an age group. The exponential of 

Φ2 provides an estimate of the median of body 

weight, and σ2 is approximately equal to the 

coefficient of variation of the body weight. These 

data can be used for further analyses of body-weight 

distribution (i.e., application of Monte Carlo 

analysis). 

The advantage of this study is that NHANES data 

were used for the analysis and the data are 

representative nationally. It also provides statistics 

for probability plot regression analyses for females 

and males from 9 months to 70 years of age. 

However, the analysis is based on an older set of 

NHANES data. 

8.4.4.	 U.S. EPA (2000)―Body-Weight 

Estimates on NHANES III Data 

U.S. EPA’s Office of Water has estimated body 

weights by age and sex using data from NHANES 

III, which was conducted from 1988 to 1994. 

NHANES III collected body-weight data for 

approximately 30,000 individuals between the ages 

of 2 months and 44 years. Table 8-10 presents the 

body-weight estimates in kilograms by age and sex. 

Table 8-11 shows the body-weight estimates for 

infants 2 and 3 months of age. 

The limitations of this analysis are that data were 

not available for infants under 2 months old, and that 

the data are roughly 15 to 20 years old. With the 

upward trends in body weight from NHANES II 

(1976−1980) to NHANES III, which may still be 

valid, the data in Table 8-10 and Table 8-11 may 

underestimate current body weights. However, the 

data are national in scope and represent the general 

population. 

8.4.5.	 Kuczmarski et al. (2002)—CDC Growth 

Charts for the United States: Methods 

and Development 

NCHS published growth charts for infants, birth 

to 36 months of age, and children and adolescents, 2 

to 20 years of age (Kuczmarski et al., 2002). Growth 

charts were developed with data from five national 

health examination surveys: National Health 

Examination Survey (NHES) II (1963−1965) for ages 

6−11 years, NHES III (1966−1970) for ages 

12−17 years, NHANES I (1971−1974) for ages 

1−17 years, NHANES II (1976−1980) beginning at 

6 months of age, and NHANES III (1988−1994) 

beginning at 2 months of age. Data from these 

national surveys were pooled because no single 

survey had enough observations to develop these 

charts. For the infant charts, a limited number of 

additional data points were obtained from other 

sources where national data were either not available 

or insufficient. Birth weights <1,500 grams were 

excluded when generating the charts for weights and 

lengths. Also, the length-for-age charts exclude data 

from NHANES III for ages <3.5 months. 

Supplemental birth certificate data from the U.S. vital 

statistics were used in the weight-for-age charts and 

supplemental birth certificate data from Wisconsin 

and Missouri vital statistics, CDC Pediatric Nutrition 

Surveillance System data were used for ages 0.5, 1.5, 

2.5, 3.5, and 4.5 months for the length-for-age charts. 

The Missouri and Wisconsin birth certificate data 

were also used to supplement the surveys for the 

weight-for-length charts. Table 8-12 presents the 

percentiles of weight by sex and age. Figure 8-1 and 

Figure 8-2 present weight by age percentiles for boys 

and girls, aged birth to 36 months, respectively. 

Figure 8-3 and Figure 8-4 present weight by length 

percentiles for boys and girls, respectively. Figure 

8-5 and Figure 8-6 provide the BMI for boys and 

girls aged 2 to 20 years old. 

The advantages of this analysis are that it is based 

on a nationally representative sample of the U.S. 

population and it provides body weight on a monthby-month basis up to 36 months of age, as well as 

BMI data for children through age 20 years. A 

limitation of this analysis is that trends in the weight 

data cannot be assessed because data from various 

years were combined. Also, the analysis is based on 

an older data set. 

8.4.6.	 U.S. EPA (2004)―Estimated Per Capita 

Water Ingestion and Body Weight in the 

United States―An Update 

U.S. EPA (2004) developed estimates from 

empirical distributions of body weights based on data 

from the U.S. Department of Agriculture (USDA's) 

1994−1996 and the 1998 Continuing Survey of Food 

Intake by Individuals (CSFII). The weights recorded 

in the survey, and, consequently, the estimates 

reported, are based on self-reported data by the 

participants. 

When viewed across sexes and all age categories, 

the average self-reported body weight for individuals 

in the United States during the 1994−1996 and 1998 

period is 65 kg, or 143 lb. The estimated median 

body weight for all individuals is 67 kg (147 lb). 

Table 8-13 provides the estimated distribution of 

body weights for all individuals. 

For the fine age categories reported in the 

summary data, the mean and median estimated body 

weights are the same for children in categories less 

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than 2 years of age. This suggests that body weights 

follow an approximately normal distribution. After 

the age of 2 years, estimated mean body weights are 

higher than estimated median body weights as age 

categories increase. This suggests that the 

distributions of body weights are skewed to the right. 

When viewed across ages, the estimated median body 

weight is higher than the estimated mean body 

weight. This suggests that the body-weight 

distribution across the entire survey weighted sample 

is slightly skewed to the left. The limitations of this 

analysis are that body weights were self-reported and 

that it is based on an older data set. 

8.4.7.	 Ogden et al. (2004)―Mean Body Weight, 

Height, and Body Mass Index, United 

States, 1960−2002 

Ogden et al. (2004) analyzed trends in body 

weight measured by the NHES II and III, NHANES 

I, II, and III, and NHANES 1999−2002. The surveys 

covered the period from 1960 to 2002. Table 8-14 

presents the measured body weights for various age 

groups as measured in NHES and NHANES. Table 

8-15 and Table 8-16 present the mean height and 

BMI data for the same population, respectively. The 

BMI data were calculated as weight (in kilograms) 

divided by the square of height (in meters). 

Population means were calculated using sample 

weights to account for variation in sampling for 

certain subsets of the U.S. population, non-response, 

and non-coverage (Ogden et al., 2004). The data 

indicate that mean body weight has increased over 

the period analyzed. 

There is some uncertainty inherent in such an 

analysis, however, because of changes in sampling 

methods during the 42-year time span covered by the 

studies. This serves to illustrate the importance of the 

use of timely data when analyzing body weight. 

Because this study is based on an analysis of 

NHANES data, its limitations are the same as those 

for that study. Another limitation is that the data are 

based on an older NHANES data set and may not be 

entirely representative of current BMI values. 

8.4.8.	 Freedman et al. (2006)―Racial and 

Ethnic Differences in Secular Trends for 

Childhood BMI, Weight, and Height 

Freedman et al. (2006) examined sex and 

race/ethnicity differences in secular trends for 

childhood BMI, overweight, weight, and height in the 

United States using data from NHANES I 

(1971−1974), NHANES II (1976–1980), NHANES 

III (1988–1994), and NHANES 1999−2002. The 

analyses includes children 2 to 17 years old. Persons 

with missing weight or height information were 

excluded from the analyses (Freedman et al., 2006). 

The authors categorized the data across the 

four examinations and presented the data for 

non-Hispanic White, non-Hispanic Black, or 

Mexican American. Freedman et al. (2006) excluded 

other categories of race/ethnicity, such as other 

Hispanics, because the sample sizes were small. 

Height and weight data were obtained for each 

survey, and BMI was calculated as weight in 

kilograms divided by height in meters square. Sex 

specific z-scores and percentiles of weight-for-age, 

height-for-age, and BMI-for-age were calculated. 

Childhood overweight was defined as BMI-for-age 

≥95th percentile, and childhood obesity was defined 

as children with a BMI-for-age ≥99th percentile. 

In the analyses, sample weights were used to 

account for differential probabilities, non-selection, 

non-response, and non-coverage. Table 8-17 presents 

the sample sizes used in the analyses by age, sex, 

race, and survey. Table 8-18 provides mean BMI 

levels for ages 2 to 17. Table 8-19 shows BMI mean 

levels for adults 20 years and older (Ogden et al., 

2004). Table 8-18 shows that in the 1971−1974 

survey total population, Mexican American children 

had the highest mean BMI level (18.6 kg/m2

). 

However, the greatest increase throughout the survey 

occurred among Black children, increasing from 17.8 

to 20 kg/m2 (Freedman et al., 2006). Table 8-20 

shows the prevalence of overweight and obesity for 

children 2 to 17 years old. These results show that 2 

to 5 year-old White children had slightly larger 

increases in overweight, but among the older 

children, the largest increases were among the Black 

and Mexican American children (Freedman et al., 

2006). Overall, in most sex-age groups, Mexican 

Americans experienced the greater increase in BMI 

and overweight than what was experienced by Black 

and White children (Freedman et al., 2006). Black 

children experienced larger secular increases in BMI, 

weight, and height than did White children 

(Freedman et al., 2006). According to Freedman et al. 

(2006), racial/ethnicity differences were less marked 

in the children aged two to five years old. 

The advantages of the study are that the sample 

size is large and the analysis was designed to 

represent the general population of the racial and 

ethnic groups studied. The disadvantage is that some 

ethnic population groups were excluded because of 

small sample sizes and that it is based on older 

NHANES data sets. 

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8.4.9.	 Martin et al. (2007)―Births: Final Data 

for 2005 

Martin et al. (2007) provided statistics on the 

percentage of live births categorized as having low or 

very low birth weights in the United States. Low 

birth weight was defined as <2,500 grams (<5 pounds 

8 ounces), and very low birth weight was defined as 

<1,500 grams (<three pounds four ounces). The data 

used in the analysis were from birth certificates 

registered in all states and the District of Columbia 

for births occurring in 2005. Data were presented for 

maternal demographic characteristics including race 

ethnicity: non-Hispanic White, non-Hispanic Black, 

and Hispanic. 

The numbers of live births within various weight 

ranges, and the percentages of live births with low or 

very low birth weights are presented in Table 8-21. 

The percentage of live births with low birth weights 

was 8.2, and the percentage of very low birth weights 

was 1.5 in 2005. Non-Hispanic Blacks had the 

highest percentage of low birth weights (14.0%) and 

very low birth weights (3.3%). Martin et al. (2007) 

also provided statistics on the numbers and 

percentages of pre-term live births in the United 

States. Of the 4,138,349 live births in the United 

States in 2005, 522,913 were defined as pre-term 

(i.e., less than 37 weeks gestation). A total of 43.3% 

of these pre-term infants had low birth weights, and 

11.3% had very low birth weights. The advantage of 

this data set is that it is nationally representative and 

provides data for infants. It provides data on 

prevalence of low birth weight in the population. 

8.4.10.	 Portier et al. (2007)―Body Weight 

Distributions for Risk Assessment 

Portier et al. (2007) provided age-specific 

distributions of body weight based on NHANES II, 

III, and IV data. The number of observations in these 

surveys is 20,322, 33,311, and 9,965, respectively. 

Portier et al. (2007) computed the means and 

standard deviations of body weight as back 

transformations of the weighted means and standard 

deviations of natural log-transformed body weights. 

Body-weight distributions were computed by sex and 

various age brackets (Portier et al., 2007). The 

estimated mean body weights are shown in Table 

8-22, Table 8-23, and Table 8-24 using NHANES II, 

III, and IV data, respectively. The sample size (N) 

shown in the tables is the observed number of 

individuals and not the expected population size (sum 

of the sample weights) in each age category (Portier 

et al., 2007). Table 8-25 provides estimates for age 

groups that are often considered in risk assessments 

(Portier et al., 2007). The authors concluded that the 

data show changes in the average body weight over 

time and that the changes are not constant for all 

ages. The reader is referred to Portier et al. (2007) for 

equations suggested by the authors to be used when 

performing risk assessments where shifts and 

changes in body-weight distributions need factoring 

in. 

The advantages of this study are that it represents 

the U.S. general population, it provides distribution 

data, and can be used for trend analysis. In addition, 

the data are provided for both sexes and for 

single-year age groups. The study results are also 

based on a large sample size. 

8.4.11.	 Kahn and Stralka (2009)―Estimated 

Daily Average Per Capita Water 

Ingestion by Child and Adult Age 

Categories Based on USDA’s 1994−1996 

and 1998 Continuing Survey of Food 

Intakes 

As part of an analysis of water ingestion, Kahn 

and Stralka (2009) provided body-weight 

distributions for the U.S. population. The analysis 

was based on self-reported body weights from the 

1994−1996, 1998 CSFII. The average body weight 

across all individuals was 65 kg. According to Kahn 

and Stralka (2009), 10 kg, which is often used as the 

default body weight for babies, is the 95th value of the 

distribution of body weight for children in the 3 to <6 

months category. The median weight is 9 kg for the 6 

to 12-month age category and 11 kg for the one-totwo-year old-category (Kahn and Stralka, 2009). 

Table 8-26 presents the body-weight distributions, 

and Table 8-27 presents the intervals around the 

mean and 90th and 95th percentiles. 

The advantages of the study are its large sample 

size and that it is representative of the U.S. 

population for the age groups presented. A limitation 

of the study is that the data are based on 

self-reporting from the participants and that the data 

are now somewhat dated. 

8.5.	 RELEVANT STUDIES—PREGNANT 

WOMEN BODY-WEIGHT STUDIES 

8.5.1.	 Carmichael et al. (1997)―The Pattern of 

Maternal Weight Gain in Women With 

Good Pregnancy Outcomes 

The Institute of Medicine (IOM) publishes 

recommendations for total gestational weight gain. 

Carmichael et al. (1997) conducted a study in a 

cohort of 7,002 who had good pregnancy outcomes to 

obtain the distribution of maternal weight gain by 

trimester and to compare these with women who 

achieved the IOM recommendations. Good outcome 

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was defined as having a vaginal delivery, 37 weeks 

or more of gestation, delivery of a live infant of an 

average size for gestational age, and from mothers 

with no diabetes or hypertension. The women were 

selected from records from the Department of 

Obstetrics, Gynecology and Reproductive Sciences 

Perinatal Database at the University of California, 

San Francisco. Distributions were derived for 

4,218 women for whom complete data on pattern of 

gain for all trimesters were obtained. The mean age 

of the women was 27.7 years with a mean 

pre-pregnancy weight of 57.6 kg. 

Twenty-nine percent of the women were 

underweight, 61% were of normal weight, 5% were 

overweight, and 4% were obese, based on BMI 

calculations. Total weight gain was calculated as the 

difference between the self-reported pre-pregnancy 

weight and the last measured weight. A linear 

regression was applied to estimate the rate of gain in 

the 2nd and 3rd trimesters. Table 8-28 presents the 

distributions of weight gain in underweight, normal 

weight, overweight, and obese women during the 1st

, 

2nd, and 3rd trimesters. The average weight gains for 

the 1st

, 2nd, and 3rd trimesters were 1.98 kg, 6.73 kg, 

and 6.37 kg, respectively. The weight gain for the 2nd 

and 3rd trimesters was calculated by taking the gain 

rate from Table 8-28 and multiplying it by 13 weeks. 

These data can be used to calculate the average 

weight of pregnant women for the 1st, 2nd, and 

3rd trimesters by adding the average weight gain for 

the 1st trimester to the average pre-pregnancy weight 

of 57.6 kg and subsequently adding the average 

weight gain for the 2nd and 3rd trimesters to the 

resulting weight from the previous trimester. These 

calculations result in a total weight of 59.6 kg, 

66.3 kg, and 72.7 kg for the 1st, 2nd, and 3rd trimesters, 

respectively. 

The advantages of this study are that it has a large 

sample size, and it provides distributional data. The 

sample, however, may not be representative of the 

United States. The sample also only included 

pregnancies with good outcomes. The study did not 

provide estimates of the weight for each trimester. 

Instead, it provides weight gain for the 1st trimester 

and the rates of weight gain for the 2nd and 

3rd trimesters. The total weight was estimated by the 

U.S. EPA based on the mean weight gain for each 

trimester. 

8.5.2.	 U.S. EPA Analysis of 1999−2006 

NHANES Data on Body Weight of 

Pregnant Women 

In 2010, U.S. EPA analyzed the combined 

1999−2006 NHANES data sets to examine body 

weight of pregnant women. Data for 1,248 pregnant 

women with weight measurements were extracted 

based from the data set based on either a positive lab 

pregnancy test or self-reporting of pregnancy at the 

examination. The NHANES data included a few very 

large and improbable body weights, as extreme as 

186 kg from a respondent in the 1st trimester. These 

outliers were removed from the database (N = 26) 

using SAS. Table 8-29 presents the body-weight data 

by trimester, based on the remaining 

1,222 respondents. The statistically weighted average 

body weight of all pregnant women was 75 kg. Due 

to a few large weight (>90 kg) respondents with very 

large sample weights (>18,000), the weighted mean 

body weight of 1st trimester women (76 kg) is larger 

than that of 2nd trimester women (73 kg). 

The advantage of this study is that by combining 

eight years of the most recent NHANES data, an 

adequate sample size was achieved to estimate body 

weight of pregnant women by trimester. A limitation 

of this analysis is that high-weight respondents with 

large sample weight may result in uncertainties as 

described above. 

8.6.	 RELEVANT FETAL WEIGHT 

STUDIES 

8.6.1.	 Brenner et al. (1976)―A Standard of 

Fetal Growth for the United States of 

America 

Brenner et al. (1976) determined fetal weights for 

430 fetuses aborted at 8 to 20 weeks of gestation and 

for 30,772 liveborn infants delivered at 21 to 

44 weeks of gestation. Gestational age for the aborted 

fetuses was determined through a combination of the 

physician’s estimate of uterine size and the patient’s 

stated last normal menstrual period. Data were not 

used when these two estimates differed by more than 

two weeks. To determine fetal growth, the fetuses 

were weighed and measured (crown-to-rump and 

crown-to-heel lengths). All abortions were legally 

performed at Memorial Hospital, University of North 

Carolina, at Chapel Hill, from 1972 to 1975. For the 

liveborn infants, data were analyzed from single birth 

deliveries with the infant living at the onset of labor, 

among pregnancies not complicated by preeclampsia, diabetes or other disorders. Infants were 

weighed on a balance scale immediately after 

delivery. The liveborn infants were delivered at 

MacDonald House, University Hospitals of 

Cleveland, OH, from 1962 to 1969. 

Table 8-30 shows percentiles for fetal weight, 

calculated from the data at each week of gestation. 

The resulting percentile curves were smoothed with 

two-point weighted means. Variables associated with 

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Chapter 8—Body Weight Studies 

significant differences in fetal weight in the latter part 

of pregnancy (after 34−38 weeks of gestation) 

included maternal parity and race, and fetal sex. 

The advantage of this study is the large sample 

size. Limitations of the study are that the data were 

collected more than 30 years ago in only two U.S. 

states. In addition, a number of variables that may 

affect fetal weight (i.e., maternal smoking, disease, 

nutrition, and addictions) were not evaluated in this 

study. 

8.6.2. Doubilet et al. (1997)―Improved Birth 

Weight Table for Neonates Developed 

From Gestations Dated by Early 

Ultrasonography 

Doubilet et al. (1997) matched a database of 

obstetrical ultrasonograms over a period of five years 

from 1988 to 1993 to birth records for 3,718 infants 

(1,857 males and 1,861 females). The study 

population included 1,514 Whites, 770 Blacks, 

1,256 Hispanics, and 178 who were either 

unclassified, or classified as “other.” Birth weights 

were obtained from hospital records, and a 

gestational age was assigned based on the earliest 

1st trimester sonogram. The database was screened 

for possible outliers, defined as infants with birth 

weights that exceeded 5,000 grams. Labor and 

delivery records and mother-infant medical records 

were retrieved to correct any errors in data entry for 

infants with birth weights exceeding 5,000 grams. 

The mean gestational age at initial sonogram was 9.5 

± 2.3 weeks. Regression analysis techniques were 

used to derive weight tables for neonates at each 

gestational age for 25 weeks of gestation onward. 

Weights for each gestational age were found to 

conform to a natural logarithm distribution. 

Polynomial equations were derived from the 

regression analysis to estimate mean weight by 

gestational age for males, females, and males and 

females combined. Table 8-31 provides the 

distribution of neonatal weights by gestational age 

from 25 weeks of gestation onward. The advantage of 

this study is that it provides body weights for 

neonates based on a relatively large sample. A 

limitation is the age of the data. 

8.7. REFERENCES FOR CHAPTER 8 

Brainard, J; Burmaster, DE. (1992). Bivariate 

distributions for height and weight of men 

and women in the United States. Risk Anal 

12: 267-275. 

Brenner, WE; Edelman, DA; Hendricks, CH. (1976). 

A standard of fetal growth for the United 

States of America. Am J Obstet Gynecol 

126: 555-564. 

Burmaster, DE; Crouch, EA. (1997). Lognormal 

distributions for body weight as a function 

of age for males and females in the United 

States, 1976-1980. Risk Anal 17: 499-505. 

Carmichael, S; Abrams, B; Selvin, S. (1997). The 

pattern of maternal weight gain in women 

with good pregnancy outcomes. Am J Public 

Health 87: 1984-1988. 

Doubilet, PM; Benson, CB; Nadel, AS; Ringer, SA. 

(1997). Improved birth weight table for 

neonates developed from gestations dated by 

early ultrasonography. J Ultrasound Med 16: 

241-249. 

FASEB/LSRO (Federation of American Societies for 

Experimental Biology, Life Sciences 

Research Office). (1995). Third report on 

nutrition monitoring in the United States: 

Volume 1. Washington, DC: Interagency 

Board for Nutrition Monitoring and Related 

Research. 

Freedman, DS; Khan, LK; Serdula, MK; Ogden, CL; 

Dietz, WH. (2006). Racial and ethnic 

differences in secular trends for childhood 

BMI, weight, and height. Obesity (Silver 

Spring) 14: 301-308. 

http://dx.doi.org/10.1038/oby.2006.39. 

Kahn, HD; Stralka, K. (2009). Estimated daily 

average per capita water ingestion by child 

and adult age categories based on USDA's 

1994-1996 and 1998 continuing survey of 

food intakes by individuals. J Expo Sci 

Environ Epidemiol 19: 396-404. 

http://dx.doi.org/10.1038/jes.2008.29. 

Kuczmarski, RJ; Ogden, CL; Guo, SS; GrummerStrawn, LM; Flegal, KM; Mei, Z; Wei, R; 

Curtin, LR; Roche, AF; Johnson, CL. 

(2002). 2000 CDC Growth Charts for the 

United States: methods and development. 1­

190. 

Martin, JA; Hamilton, BE; Sutton, PD; Ventura, SJ; 

Menacker, F; Kirmeyer, S; Munson, ML. 

(2007). Births: final data for 2005. National 

Vital Statistics Reports 56: 1-103. 

Najjar, MF; Rowland, M. (1987). Anthropometric 

reference data and prevalence of overweight, 

United States, 1976-80. 1-73. 

Ogden, CL; Fryar, CD; Carroll, MD; Flegal, KM. 

(2004). Mean body weight, height, and body 

mass index, United States 1960-2002. 1-17. 

Portier, K; Tolson, JK; Roberts, SM. (2007). Body 

weight distributions for risk assessment. 

Risk Anal 27: 11-26. 

Page Exposure Factors Handbook 

8-10 September 2011 
Exposure Factors Handbook 

Chapter 8―Body Weight Studies 

Exposure Factors Handbook Page 
 

September 2011 8-11 

http://dx.doi.org/10.1111/j.1539­

6924.2006.00856.x. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1989). Risk assessment guidance for 

superfund: Volume 1: Human health 

evaluation manual (part A): Interim final 

[EPA Report]. (EPA/540/1-89/002). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Emergency 

and Remedial Response. 

http://www.epa.gov/oswer/riskassessment/ra 

gsa/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000). Memorandum entitled: Body weight 

estimates on NHANES III data, revised. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2004). Estimated per capita water ingestion 

and body weight in the United States: An 

update. (EPA-822/R-00-001). Washington, 

DC: U.S. Environmental Protection Agency, 

Office of Water, Office of Science and 

Technology. 

http://water.epa.gov/action/advisories/drinki 

ng/upload/2005_05_06_criteria_drinking_pe 

rcapita_2004.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum. 

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 
Table 8-3. Mean and Percentile Body Weights (kg) Derived From NHANES (1999−2006) 

Males and Females Combined 

Age Group N Mean 

Percentiles 

5th 10th 15th 25th 50th 75th 85th 90th 95th 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <30 years 

30 to <40 years 

40 to <50 years 

50 to <60 years 

60 to <70 years 

70 to <80 years 

Over 80 years 

158 

284 

489 

927 

1,176 

1,144 

2,318 

3,593 

5,297 

4,851 

3,232 

3,176 

3,121 

2,387 

2,782 

2,033 

1,430 

4.8 

5.9 

7.4 

9.2 

11.4 

13.8 

18.6 

31.8 

56.8 

71.6 

78.4 

80.8 

83.6 

83.4 

82.6 

76.4 

68.5 

3.6 

4.5 

5.7 

7.1 

8.9 

10.9 

13.5 

19.7 

34.0 

48.2 

50.8 

53.5 

54.3 

54.7 

55.2 

52.0 

46.9 

3.9 

4.7 

6.1 

7.5 

9.3 

11.5 

14.4 

21.3 

37.2 

52.0 

54.7 

57.4 

58.8 

59.0 

59.8 

56.5 

51.4 

4.1 

4.9 

6.3 

7.9 

9.7 

11.9 

14.9 

22.3 

40.6 

54.5 

57.9 

60.1 

62.1 

62.8 

63.3 

59.7 

53.8 

4.2 

5.2 

6.7 

8.3 

10.3 

12.4 

15.8 

24.4 

45.0 

58.4 

63.3 

66.1 

68.3 

69.1 

69.0 

64.4 

58.2 

4.8 

5.9 

7.3 

9.1 

11.3 

13.6 

17.8 

29.3 

54.2 

67.6 

75.2 

77.9 

81.4 

80.8 

80.5 

74.9 

67.4 

5.1 

6.6 

8.0 

10.1 

12.4 

14.9 

20.3 

36.8 

65.0 

80.6 

88.2 

92.4 

95.0 

95.5 

94.2 

86.8 

77.4 

5.5 

6.9 

8.4 

10.5 

13.0 

15.8 

22.0 

42.1 

73.0 

90.8 

98.5 

101.0 

104.0 

104.0 

103.0 

93.8 

82.6 

5.8 

7.1 

8.7 

10.8 

13.4 

16.3 

23.6 

45.6 

79.3 

97.7 

106.0 

107.0 

111.0 

110.0 

109.0 

98.0 

87.2 

6.2 

7.3 

9.1 

11.3 

14.0 

17.1 

26.2 

52.5 

88.8 

108.0 

118.0 

118.0 

122.0 

120.0 

116.0 

106.0 

93.6 

Source: U.S. EPA Analysis of NHANES 1999−2006 data. 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 

8-12 September 2011 
 

Table 8-4. Mean and Percentile Body Weights (kg) for Males Derived From NHANES (1999−2006) 

Age Group N Mean 

Percentiles 

5th 10th 15th 25th 50th 75th 85th 90th 95th 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <30 years 

30 to <40 years 

40 to <50 years 

50 to <60 years 

60 to <70 years 

70 to <80 years 

Over 80 years 

88 

153 

255 

472 

632 

558 

1,158 

1,795 

2,593 

2,462 

1,359 

1,445 

1,545 

1,189 

1,360 

1,079 

662 

4.9 

6.0 

7.6 

9.4 

11.6 

14.1 

18.8 

31.9 

57.6 

77.3 

84.9 

87.0 

90.5 

89.5 

89.1 

83.9 

76.1 

3.6 

4.6 

5.9 

7.3 

9.0 

11.4 

13.5 

20.0 

33.6 

54.5 

58.7 

61.1 

64.9 

64.1 

63.4 

60.6 

56.7 

3.6 

5.0 

6.4 

7.9 

9.7 

12.0 

14.4 

21.8 

36.3 

57.6 

63.0 

65.7 

69.5 

68.8 

67.5 

64.6 

60.6 

4.0 

5.1 

6.6 

8.2 

10.0 

12.2 

14.9 

22.9 

38.9 

60.0 

66.2 

68.7 

73.0 

71.4 

71.6 

68.3 

63.9 

4.4 

5.4 

6.9 

8.5 

10.5 

12.8 

15.9 

24.8 

44.2 

63.9 

70.7 

73.8 

77.7 

77.0 

77.2 

73.1 

67.2 

4.8 

6.1 

7.5 

9.4 

11.5 

14.0 

18.1 

29.6 

55.5 

73.1 

81.2 

84.0 

87.4 

87.8 

86.9 

82.1 

75.1 

5.5 

6.8 

8.2 

10.3 

12.6 

15.2 

20.8 

36.4 

66.5 

86.0 

94.0 

96.5 

99.7 

99.8 

99.4 

93.8 

84.0 

5.8 

7.0 

8.6 

10.6 

13.2 

15.9 

22.6 

41.2 

75.5 

96.8 

103.0 

104.0 

109.0 

107.0 

108.0 

98.6 

89.4 

6.2 

7.2 

8.8 

10.8 

13.5 

16.4 

23.8 

45.2 

81.2 

104.0 

111.0 

110.0 

114.0 

112.0 

113.0 

104.0 

92.5 

6.8 

7.3 

9.1 

11.5 

14.3 

17.0 

26.2 

51.4 

91.8 

113.0 

123.0 

124.0 

125.0 

123.0 

120.0 

113.0 

100.0 

Source: U.S. EPA Analysis of NHANES 1999−2006 data. 

Exposure Factors Handbook 

Chapter 8―Body Weight Studies 

Exposure Factors Handbook Page
 

September 2011 8-13 
Table 8-5. Mean and Percentile Body Weights (kg) for Females Derived From NHANES (1999−2006) 

Age Group N Mean 

Percentiles 

5th 10th 15th 25th 50th 75th 85th 90th 95th 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <30 years 

30 to <40 years 

40 to <50 years 

50 to <60 years 

60 to <70 years 

70 to <80 years 

Over 80 years 

70 

131 

234 

455 

544 

586 

1,160 

1,798 

2,704 

2,389 

1,873 

1,731 

1,576 

1,198 

1,422 

954 

768 

4.6 

5.7 

7.2 

9.0 

11.1 

13.5 

18.3 

31.7 

55.9 

65.9 

71.9 

74.8 

77.1 

77.5 

76.8 

70.8 

64.1 

3.6 

4.3 

5.5 

7.1 

8.7 

10.5 

13.5 

19.3 

34.9 

46.2 

48.0 

50.9 

51.7 

52.2 

51.9 

49.6 

45.5 

4.0 

4.6 

5.9 

7.3 

9.1 

11.0 

14.3 

20.9 

38.6 

48.6 

51.4 

54.0 

54.7 

55.7 

56.5 

53.3 

48.7 

4.1 

4.74 

6.2 

7.6 

9.4 

11.5 

14.7 

22.0 

41.6 

51.1 

53.8 

56.2 

57.3 

57.9 

59.2 

55.7 

51.3 

4.2 

5.1 

6.4 

8.0 

10.0 

12.1 

15.6 

23.9 

45.7 

54.5 

57.8 

60.0 

61.7 

62.8 

63.9 

60.3 

54.9 

4.6 

5.5 

7.2 

8.9 

11.1 

13.2 

17.5 

29.0 

53.3 

61.5 

67.9 

70.2 

72.7 

73.6 

73.9 

69.0 

62.8 

4.9 

6.4 

7.9 

9.8 

12.2 

14.6 

19.7 

37.3 

62.8 

73.3 

81.4 

85.0 

88.0 

87.7 

86.6 

79.4 

71.8 

5.0 

6.6 

8.2 

10.3 

12.9 

15.5 

21.3 

43.1 

70.7 

83.4 

90.2 

95.1 

97.8 

97.7 

95.4 

85.6 

77.0 

5.2 

6.9 

8.4 

10.6 

13.2 

16.2 

23.2 

46.7 

76.5 

89.9 

98.7 

104.0 

105.0 

105.0 

102.0 

91.4 

80.5 

5.9 

7.3 

9.0 

11.2 

13.7 

17.1 

26.2 

53.4 

86.3 

99.7 

109.0 

113.0 

118.0 

117.0 

112.0 

98.2 

89.1 

Source: U.S. EPA Analysis of NHANES 1999−2006 data. 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 

8-14 September 2011 
 

 

 

 

 

 

 

 

 

 

Table 8-6. Weight in Kilograms for Males 2 Months−21 Years of Age―Number Examined, Mean, and Selected Percentiles, by 

Age Category: United States, 1976–1980a 

Age Group 

Number of 

Persons 

Examined 

Mean 

(kg) 

Percentiles 

5th 10th 15th 25th 50th 75th 85th 90th 95th 

Birth to <1 month - - - - - - - - - - -

1 to <2 months - - - - - - - - - - -

2 to <3 months 103 6.6 5.3 5.5 5.7 5.9 6.8 7.2 7.6 7.8 8.4 

3 to <6 months 287 7.7 6.3 6.6 6.7 7.0 7.7 8.4 8.9 9.2 9.6 

6 to <12 months 589 9.4 7.5 7.9 8.1 8.6 9.4 10.2 10.6 10.9 11.4 

1 to <2 years 613 11.7 9.4 9.8 10.1 10.8 11.7 12.6 13.1 13.7 14.5 

2 to <3 years 627 13.7 11.4 11.8 12.2 12.6 13.6 14.6 15.2 15.8 16.5 

3 to <6 years 1,556 18.0 13.7 14.6 14.9 15.7 17.5 19.7 21.0 22.0 24.0 

6 to <11 years 1,373 30.7 19.5 21.1 22.1 24.0 28.5 35.2 40.5 43.5 48.7 

11 to <16 years 1,037 55.2 34.0 36.5 38.7 42.8 53.0 63.0 69.4 74.8 84.3 

16 to <21 years 890 71.8 54.1 56.6 58.3 61.8 68.7 77.9 84.3 89.7 101.0 

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kg. 

- No data available for infants less than 2 months old. 

Source: Najjar and Rowland (1987). 

Exposure Factors Handbook Chapter 8—Body Weight Studies Exposure Factors Handbook 

Page

September 2011 8-15 
Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 8-16 September 2011 

 

 

 

 

 

 

 

 

 

 

 

 

Table 8-7. Weight in Kilograms for Females 6 Months−21 Years of Age―Number Examined, Mean, and Selected Percentiles, by 

Age Category: United States, 1976−1980a 

Age Group 

Number of 

Persons 

Examined 

Mean 

(kg) 

Percentiles 

5th 10th 15th 25th 50th 75th 85th 90th 95th 

Birth to <1 month - - - - - - - - - - -

1 to <2 months - - - - - - - - - - -

2 to <3 months 131 6.0 4.7 5.1 5.2 5.6 6.0 6.5 7.1 7.3 7.8 

3 to <6 months 269 7.1 5.8 5.9 6.1 6.4 7.1 7.7 7.9 8.4 8.7 

6 to <12 months 574 8.8 7.2 7.5 7.7 8.0 8.7 9.4 10.1 10.4 10.8 

1 to <2 years 617 11.0 9.1 9.4 9.6 9.9 10.9 11.9 12.6 12.9 13.4 

2 to <3 years 597 13.4 10.8 11.2 11.6 12.1 13.2 14.6 15.4 15.6 16.3 

3 to <6 years 1,658 18.0 13.3 14.0 14.5 15.4 17.2 19.7 21.1 22.6 25.1 

6 to <11 years 1,321 30.6 19.0 20.5 21.3 23.4 28.9 35.0 39.6 44.3 50.2 

11 to <16 years 1,144 53.2 34.1 37.2 40.4 45.2 51.6 60.0 67.2 70.6 78.2 

16 to <21 years 1,001 62.2 46.7 48.2 49.7 52.2 58.9 68.3 74.7 80.8 92.6 

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kg. 

- No data available for infants less than 2 months old. 

Source: Najjar and Rowland (1987). 
Exposure Factors Handbook 

Chapter 8―Body Weight Studies 

 

 

Table 8-8. Statistics for Probability Plot Regression Analyses: Female Body Weights 6 Months to 70 Years 

of Age 

Lognormal Probability Plots 

Age Midpoint (years) Linear Curve 

μ2

a σ2a 

0.75 

1.5 

2.5 

3.5 

4.5 

5.5 

6.5 

7.5 

8.5 

9.5 

10.5 

11.5 

12.5 

13.5 

14.5 

15.5 

16.5 

17.5 

18.5 

19.5 

21.5 

30 

40 

50 

60 

70 

2.16 0.145 

2.38 0.129 

2.56 0.112 

2.69 0.136 

2.83 0.134 

2.98 0.164 

3.10 0.174 

3.19 0.174 

3.31 0.156 

3.46 0.214 

3.57 0.199 

3.71 0.226 

3.82 0.213 

3.92 0.215 

3.99 0.187 

4.00 0.156 

4.05 0.167 

4.08 0.165 

4.07 0.147 

4.10 0.149 

4.10 0.168 

4.15 0.204 

4.19 0.207 

4.20 0.208 

4.20 0.205 

4.18 0.198 

a Φ2, σ2—correspond to the mean and the standard deviation, respectively, of the logarithm of body weight (kg) for an age group. 

Source: Burmaster and Crouch (1997). 

Exposure Factors Handbook Page
 

September 2011 8-17 
 

Table 8-9. Statistics for Probability Plot Regression Analyses: Male Body Weights 6 Months to 

70 Years of Age 

Lognormal Probability Plots 

Age Midpoint (years) Linear Curve 

μ2 

a σ2 a 

0.75 2.23 0.131 

1.5 2.46 0.120 

2.5 2.60 0.120 

3.5 2.75 0.114 

4.5 2.87 0.133 

5.5 2.98 0.138 

6.5 3.13 0.145 

7.5 3.21 0.151 

8.5 3.33 0.181 

9.5 3.43 0.165 

10.5 3.59 0.195 

11.5 3.69 0.252 

12.5 3.78 0.224 

13.5 3.88 0.215 

14.5 4.02 0.181 

15.5 4.09 0.159 

16.5 4.20 0.168 

17.5 4.19 0.167 

18.5 4.25 0.159 

19.5 4.26 0.154 

21.5 4.29 0.163 

30 4.35 0.163 

40 4.38 0.165 

50 4.38 0.166 

60 4.35 0.157 

70 4.29 0.174 

a Φ2, σ2—correspond to the mean and the standard deviation, respectively, of the logarithm of body weight (kg) for an age group. 

Source: Burmaster and Crouch (1997). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 

8-18 September 2011 
Exposure Factors Handbook 

Chapter 8―Body Weight Studies 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 8-10. Body-Weight Estimates (kg) by Age and Sex, U.S. Population Derived From NHANES III 

(1988−1994) 

Males and Females Males Females 

Age Group Sample Size Population 

Median Mean Median Mean Median Mean 

2 to 6 months 1,020 1,732,702 7.4 7.4 7.6 7.7 7.0 7.0 

7 to 12 months 1,072 1,925,573 9.4 9.4 9.7 9.7 9.1 9.1 

1 year 1,258 3,935,114 11.3 11.4 11.7 11.7 10.9 11.0 

2 years 1,513 4,459,167 13.2 12.9 13.5 13.1 13.0 12.5 

3 years 1,309 4,317,234 15.3 15.1 15.5 15.2 15.1 14.9 

4 years 1,284 4,008,079 17.2 17.1 17.2 17.0 17.3 17.2 

5 years 1,234 4,298,097 19.6 19.4 19.7 19.3 19.6 19.4 

6 years 750 3,942,457 21.3 21.7 21.5 22.1 20.9 21.3 

7 years 736 4,064,397 25.0 25.5 25.4 25.5 24.1 25.6 

8 years 711 3,863,515 27.4 28.1 27.2 28.4 27.9 27.9 

9 years 770 4,385,199 31.8 32.7 32.0 32.3 31.1 33.0 

10 years 751 3,991,345 35.2 35.6 35.9 36.0 34.3 35.2 

11 years 754 4,270,211 40.6 41.5 38.8 40.0 43.4 42.8 

12 years 431 3,497,661 47.2 46.9 48.1 49.1 45.7 48.6 

13 years 428 3,567,181 53.0 55.1 52.6 54.5 53.7 55.9 

14 years 415 4,054,117 56.9 61.1 61.3 64.5 53.7 57.9 

15 years 378 3,269,777 59.6 62.8 62.6 66.9 57.1 59.2 

16 years 427 3,652,041 63.2 65.8 66.6 69.4 56.3 61.6 

17 years 410 3,719,690 65.1 67.5 70.0 72.4 60.7 62.2 

≥1 years 31,311 251,097,002 66.5 64.5 73.9 89.0 80.8 80.3 

1 to 3 years 4,080 12,711,515 13.2 13.1 13.4 13.4 13.0 12.9 

1 to 14 years 12,344 56,653,796 24.9 29.9 25.1 30.0 24.7 29.7 

15 to 44 years 10,393 118,430,653 70.8 73.5 77.5 80.2 63.2 67.3 

Source: U.S. EPA (2000). 

Exposure Factors Handbook Page
 

September 2011 8-19 
 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-11. Body-Weight Estimates (in kg) by Age, U.S. Population Derived From NHANES III (1988−1994) 

Age Group (months) Sample Size Population Males and Females 

Median Mean 95% CI 

2 243 408,837 6.3 6.3 6.1−6.4 

3 190 332,823 7.0 6.9 6.7−7.1 

3 and younger 433 741,660 6.6 6.6 6.4−6.7 

CI = Confidence Interval. 

Source: U.S. EPA (2000). 

Page Exposure Factors Handbook 

8-20 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 8-12. Observed Mean, Standard Deviation, and Selected Percentiles for Weight (kg) by Sex and 

Age: Birth to 36 Months 

Age Group 

(mo) Mean SD 

Percentile 

10th 25th 50th 75th 90th 95th 

Boys 

Birth 3.4 0.6 2.7 3.1 3.4 3.8 4.1 4.3 

0 to <1 - - - - - - - -

1 to <2 - - - - - - - -

2 to <3 6.5 0.8 5.6 5.8 6.7 6.9 7.4 7.5 

3 to <4 7.0 0.9 5.9 6.5 7.0 7.5 8.2 8.5 

4 to <5 7.2 0.8 6.3 6.7 7.2 7.7 8.0 8.4 

5 to <6 7.9 0.9 6.7 7.5 7.8 8.6 9.4 9.6 

6 to <7 8.4 1.1 7.3 7.6 8.4 9.0 10.2 10.7 

7 to <8 8.6 1.1 7.1 7.8 8.6 9.5 10.1 10.4 

8 to <9 9.3 1.1 7.9 8.6 9.2 10.1 10.5 11.0 

9 to <10 9.3 0.9 8.2 8.6 9.3 10.0 10.8 10.9 

10 to <11 9.5 1.1 8.3 8.7 9.3 10.1 11.3 11.5 

11 to <12 10.0 1.0 8.7 9.5 10.0 10.6 11.1 11.6 

12 to <15 10.6 1.2 9.2 9.8 10.6 11.3 12.1 12.4 

15 to < 8 11.4 1.9 9.9 10.5 11.3 12.0 12.8 13.5 

18 to <21 12.1 1.5 10.4 11.0 11.9 12.7 13.9 15.5 

21 to <24 12.4 1.3 10.9 11.6 12.4 13.1 14.4 14.7 

24 to <30 13.1 1.7 11.3 12.1 12.9 14.1 15.1 15.9 

30 to <36 14.0 1.5 12.0 13.0 13.8 14.7 16.0 16.6 

Girls 

Birth 3.3 0.5 2.6 3.0 3.3 3.6 3.9 4.1 

0 to <1 - - - - - - - -

1 to <2 - - - - - - - -

2 to <3 5.4 0.5 4.8 5.0 5.6 5.9 6.0 -

3 to <4 6.3 0.7 5.6 5.8 6.3 6.8 7.4 7.8 

4 to <5 6.7 0.9 5.8 6.1 6.6 7.4 8.0 8.3 

5 to <6 7.3 0.9 6.3 6.7 7.1 7.7 8.5 8.8 

6 to <7 7.7 0.8 6.6 7.1 7.6 8.1 8.9 9.0 

7 to <8 8.0 1.4 6.7 7.4 7.8 8.6 9.4 9.8 

8 to <9 8.3 0.9 7.3 7.8 8.3 8.9 9.4 9.8 

9 to <10 8.9 0.9 7.8 8.1 8.7 9.4 10.1 10.5 

10 to <11 9.0 1.1 7.8 8.4 9.0 9.5 10.4 10.9 

11 to <12 9.3 1.0 7.9 8.6 9.2 10.1 10.6 10.9 

12 to <15 9.8 1.1 8.5 9.1 9.8 10.4 11.3 11.6 

15 to <18 10.4 1.1 9.1 9.7 10.3 11.2 11.8 12.0 

18 to <21 11.1 1.4 9.6 10.2 11.0 11.9 12.8 13.5 

21 to <24 11.8 1.3 10.1 10.9 11.8 12.8 13.5 13.9 

24 to <30 12.5 1.5 10.8 11.5 12.4 13.3 14.5 15.1 

30 to <36 13.6 1.7 11.8 12.5 13.4 14.52 15.7 16.4 

- No data available. 

Source: Kuczmarski et al. (2002). 

Exposure Factors Handbook 

Chapter 8―Body Weight Studies 

Exposure Factors Handbook Page
 

September 2011 8-21 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 8-13. Estimated Distribution of Body Weight by Fine Age Categories All 

Individuals, Males and Females Combined (kg) 

Ages 

(years) Sample Size Population Mean Percentiles 

10th 25th 50th 75th 90th 95th 

<0.5 744 1,890,461 6 3 4 6 7 8 9 

0.5 to 0.9 678 1,770,700 9 7 8 9 10 11 12 

1 to 3 3,645 11,746,146 14 10 11 13 16 18 19 

4 to 6 2,988 11,570,747 21 16 17 20 22 26 28 

7 to 10 1,028 14,541,011 32 22 26 29 36 43 48 

11 to 14 790 15,183,156 51 35 42 50 58 68 79 

15 to 19 816 17,825,164 67 50 56 63 73 85 99 

20 to 24 676 18,402,877 72 53 59 68 81 94 104 

25 to 54 4,830 111,382,877 77 54 63 75 86 100 109 

55 to 64 1,516 20,691,260 77 57 65 75 87 99 105 

65+ 2,139 30,578,210 72 54 62 71 81 93 100 

Summary Data 

20 + 9,161 181,055,224 76 54 63 73 86 98 107 

<2 2,424 7,695,535 10 5 7 10 11 13 14 

2 to 15 7,449 49,006,686 33 15 19 28 43 56 63 

15+ 9,977 198,880,388 75 54 61 72 84 97 106 

<6 7,530 23,160,174 15 8 11 14 18 21 23 

6 to 15 2,343 33,542,047 40 22 27 36 50 59 68 

All ages 19,850 255,582,609 65 22 52 67 81 95 104 

Note: 757 individuals did not report body weight. They represent 6,314,627 individuals in the population. 

Source: U.S. EPA (2004) (based on 1994−1996, 1998 USDA CSFII). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 

8-22 September 2011 
 

 

Chapter 8—Body Weight Studies Exposure Factors Handbook 

Table 8-14. Mean Body Weight (kg) by Age and Sex Across Multiple Surveys 

Sex 

and Age

(years) 

NHES II, 1963−1965 NHES III, 1966−1970 NHANES II, 1976−1980 NHANES III, 1988−1994 

N Mean SE N Mean SE N Mean SE N Mean SE 

NHANES, 1999−2002 

N Mean SE 

Male 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 74 

75+ 

-

-

-

-

575 

632 

618 

603 

576 

595 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

22.0 

24.7 

27.8 

31.2 

33.7 

38.2 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.1 

0.2 

0.2 

0.4 

0.3 

0.3 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

643 

626 

618 

613 

556 

458 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

42.9 

50.0 

56.7 

61.6 

64.8 

68.1 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.4 

0.5 

0.6 

0.4 

0.6 

0.4 

-

-

-

-

-

-

-

-

370 

421 

405 

393 

146 

150 

145 

141 

165 

153 

147 

165 

188 

180 

180 

183 

156 

150 

1,261 

871 

695 

691 

2,086 

-

13.4 

15.5 

17.6 

19.7 

22.8 

24.9 

28.0 

30.7 

36.2 

39.7 

44.1 

49.5 

56.4 

61.2 

66.5 

66.7 

71.1 

71.8 

76.3 

79.8 

81.7 

80.0 

76.1 

-

0.1 

0.1 

0.1 

0.1 

0.4 

0.4 

0.6 

0.6 

0.7 

0.9 

1.0 

1.2 

0.9 

1.0 

1.2 

0.8 

1.2 

0.8 

0.5 

0.4 

0.5 

0.6 

0.5 

-

644 

516 

549 

497 

283 

269 

266 

281 

297 

281 

203 

187 

188 

187 

194 

196 

176 

168 

1,638 

1,468 

1,220 

851 

1,683 

895 

13.6 

15.8 

17.6 

20.1 

23.2 

26.3 

30.2 

34.4 

37.3 

42.5 

49.1 

54.0 

64.1 

66.9 

68.7 

72.9 

71.3 

73.0 

78.4 

82.9 

85.1 

86.0 

82.2 

75.4 

0.1 

0.2 

0.2 

0.2 

0.6 

0.4 

0.8 

1.0 

0.9 

0.9 

1.1 

1.0 

3.6 

1.9 

1.6 

1.3 

1.7 

2.2 

0.6 

0.9 

0.8 

0.5 

0.5 

0.7 

262 

216 

179 

147 

182 

185 

214 

174 

187 

182 

299 

298 

266 

283 

306 

313 

284 

270 

712 

704 

776 

598 

1,001 

523 

13.7 

15.9 

18.5 

21.3 

23.5 

27.2 

32.7 

36.0 

38.6 

43.7 

50.4 

53.9 

63.9 

68.3 

74.4 

75.6 

75.6 

78.2 

83.4 

86.0 

89.1 

88.8 

87.1 

78.5 

0.1 

0.2 

0.2 

0.5 

0.4 

0.4 

1.0 

0.7 

0.8 

1.1 

1.3 

1.9 

1.6 

1.1 

1.4 

1.4 

1.1 

1.3 

0.7 

0.9 

0.7 

0.9 

0.6 

0.6 

Exposure Factors Handbook PageSeptember 2011 8-23 
 

 

 

 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-14. Mean Body Weight (kg) by Age and Sex Across Multiple Surveys (continued) 

Sex 

and Age 

(years) 

NHES II, 1963−1965 NHES III, 1966−1970 NHANES II, 1976−1980 NHANES III, 1988−1994 NHANES, 1999−2002 

N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Female 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 74 

75+ 

-

-

-

-

536 

609 

613 

581 

584 

525 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

21.5 

24.2 

27.5 

31.4 

35.2 

39.8 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.2 

0.2 

0.2 

0.4 

0.4 

0.4 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

547 

582 

586 

503 

536 

442 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

46.6 

50.5 

54.2 

56.5 

58.1 

57.6 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.4 

0.5 

0.4 

0.5 

0.7 

0.6 

-

-

-

-

-

-

-

-

330 

367 

388 

369 

150 

154 

125 

154 

128 

143 

146 

155 

181 

144 

167 

134 

156 

158 

1,290 

964 

765 

793 

2,349 

-

12.8 

14.8 

16.8 

19.4 

21.9 

24.6 

27.5 

31.7 

35.7 

41.4 

46.1 

50.9 

54.3 

55.0 

57.7 

59.6 

59.0 

59.8 

61.7 

66.1 

67.6 

68.4 

66.8 

-

0.1 

0.1 

0.2 

0.3 

0.4 

0.5 

0.4 

0.7 

0.6 

0.9 

0.9 

1.2 

1.0 

0.8 

0.9 

1.0 

1.0 

1.0 

0.5 

0.6 

0.6 

0.6 

0.4 

-

624 

587 

537 

554 

272 

274 

248 

280 

258 

275 

236 

220 

218 

191 

208 

201 

175 

177 

1,663 

1,773 

1,355 

996 

1,674 

1,022 

13.2 

15.4 

17.9 

20.2 

22.6 

26.4 

29.9 

34.4 

37.9 

44.1 

49.0 

55.8 

58.5 

58.1 

61.3 

62.4 

61.2 

63.2 

64.4 

70.2 

71.6 

74.3 

70.1 

63.4 

0.1 

0.1 

0.3 

0.2 

0.6 

0.8 

0.6 

1.2 

1.2 

1.1 

1.2 

1.6 

1.4 

1.1 

1.4 

1.2 

1.9 

1.9 

0.6 

0.8 

0.8 

0.8 

0.5 

0.6 

248 

178 

191 

186 

171 

196 

184 

183 

164 

194 

316 

321 

324 

266 

273 

256 

243 

225 

656 

699 

787 

593 

1,010 

554 

13.3 

15.2 

17.9 

20.6 

22.4 

25.9 

31.9 

35.4 

40.0 

47.9 

52.0 

57.7 

59.9 

61.1 

63.0 

61.7 

65.2 

67.9 

71.1 

74.1 

76.5 

76.9 

74.9 

66.6 

0.1 

0.2 

0.3 

0.6 

0.5 

0.5 

1.2 

0.7 

1.0 

1.3 

1.1 

1.4 

1.0 

1.7 

1.2 

1.2 

1.5 

1.2 

0.9 

0.9 

1.1 

1.1 

0.6 

0.9 

-

N 

SE 

Source: 

= Data not available. 

= Number of individuals. 

= Standard error. 

Ogden et al. (2004). 

Page Exposure Factors Handbook 8-24 September 2011 
 

Chapter 8—Body Weight Studies Exposure Factors Handbook 

Table 8-15. Mean Height (cm) by Age and Sex Across Multiple Surveys 

Sex 

and Age 

(years) 

NHES II, 1963−1965 NHES III, 1966−1970 NHANES II, 1976−1980 NHANES III, 1988−1994 

N Mean SE N Mean SE N Mean SE N Mean SE 

NHANES, 1999−2002 

N Mean SE 

Male 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 74 

75+ 

-

-

-

-

575 

632 

618 

603 

576 

595 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

118.9 

124.5 

130.0 

135.5 

140.2 

145.5 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.2 

0.3 

0.3 

0.4 

0.3 

0.3 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

643 

626 

618 

613 

556 

458 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

152.3 

159.8 

166.7 

171.4 

174.3 

175.6 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.4 

0.4 

0.5 

0.3 

0.4 

0.4 

-

-

-

-

-

-

-

-

350 

421 

405 

393 

146 

150 

145 

141 

165 

153 

147 

165 

188 

180 

180 

183 

156 

150 

1,261 

871 

695 

691 

2,086 

-

91.1 

98.7 

105.5 

112.3 

119.1 

124.5 

129.6 

135.0 

141.3 

145.5 

152.5 

158.3 

166.8 

171.2 

173.4 

174.8 

177.3 

176.1 

177.1 

176.3 

175.9 

174.7 

172.1 

-

0.2 

0.3 

0.4 

0.3 

0.5 

0.5 

0.7 

0.6 

0.6 

0.6 

0.7 

0.8 

0.6 

0.7 

0.5 

0.5 

0.6 

0.5 

0.3 

0.3 

0.3 

0.3 

0.2 

-

589 

513 

551 

497 

283 

270 

269 

280 

297 

285 

207 

190 

191 

188 

197 

196 

176 

169 

1,639 

1,468 

1,220 

851 

1,684 

895 

90.9 

98.8 

105.2 

112.3 

118.9 

125.9 

131.3 

137.7 

142.0 

147.4 

155.5 

161.6 

169.0 

172.8 

175.0 

176.5 

177.3 

175.5 

176.1 

176.6 

176.3 

175.8 

173.6 

170.7 

0.2 

0.3 

0.4 

0.3 

0.7 

0.6 

0.6 

0.7 

1.1 

0.7 

1.1 

0.8 

0.9 

1.0 

0.9 

0.9 

1.0 

0.6 

0.3 

0.3 

0.3 

0.3 

0.2 

0.3 

254 

222 

183 

156 

188 

187 

217 

177 

188 

187 

301 

298 

267 

287 

310 

317 

289 

275 

724 

717 

784 

601 

1,010 

505 

91.2 

98.6 

106.5 

113.0 

119.2 

126.2 

132.5 

138.1 

141.4 

148.7 

154.8 

160.1 

168.5 

173.8 

175.3 

175.3 

176.4 

176.7 

176.7 

176.4 

177.2 

175.8 

174.4 

171.3 

0.3 

0.3 

0.4 

0.5 

0.5 

0.6 

0.7 

0.4 

0.6 

0.9 

0.7 

0.8 

0.9 

0.6 

0.6 

0.6 

0.7 

0.6 

0.3 

0.3 

0.3 

0.3 

0.3 

0.4 

Exposure Factors Handbook PageSeptember 2011 8-25 
 

 

 

 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-15. Mean Height (cm) by Age and Sex Across Multiple Surveys (continued) 

Sex 

and Age 

(years) 

NHES II, 1963−1965 NHES III, 1966−1970 NHANES II, 1976−1980 NHANES III, 1988−1994 NHANES, 1999−2002 

N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Female 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 74 

75+ 

-

-

-

-

536 

609 

613 

581 

584 

525 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

117.8 

123.5 

129.4 

135.5 

140.9 

147.3 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.3 

0.2 

0.3 

0.3 

0.3 

0.3 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

547 

582 

586 

503 

536 

442 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

46.6 

50.5 

54.2 

56.5 

58.1 

57.6 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.3 

0.3 

0.3 

0.5 

0.3 

0.3 

-

-

-

-

-

-

-

-

314 

367 

388 

369 

150 

154 

125 

154 

128 

143 

146 

155 

181 

144 

167 

134 

156 

158 

1,290 

964 

765 

793 

2,349 

-

89.4 

97.1 

104.2 

111.2 

117.9 

123.4 

129.5 

134.1 

141.7 

147.4 

143.8 

158.7 

160.7 

163.3 

162.8 

163.5 

162.8 

163.2 

163.3 

163.1 

162.3 

160.5 

158.8 

-

0.3 

0.2 

0.4 

0.4 

0.6 

0.7 

0.5 

0.5 

0.6 

0.7 

0.6 

0.5 

0.7 

0.5 

0.5 

0.6 

0.5 

0.4 

0.2 

0.2 

0.3 

0.3 

0.2 

-

564 

590 

535 

557 

274 

275 

247 

282 

262 

275 

239 

225 

224 

195 

214 

201 

175 

178 

1,665 

1,776 

1,354 

998 

1,680 

1,025 

89.7 

98.2 

105.1 

112.2 

117.9 

124.3 

131.1 

136.6 

142.7 

150.2 

155.5 

159.9 

161.2 

162.8 

163.0 

163.6 

163.2 

163.4 

162.8 

163.4 

162.8 

161.8 

159.8 

156.2 

0.2 

0.2 

0.3 

0.5 

0.6 

0.7 

0.6 

0.7 

0.6 

0.7 

0.7 

0.9 

0.7 

0.6 

0.7 

0.6 

0.9 

0.7 

0.2 

0.3 

0.3 

0.3 

0.2 

0.4 

233 

187 

195 

190 

172 

200 

184 

189 

164 

194 

318 

324 

326 

271 

275 

258 

249 

231 

663 

708 

794 

601 

1,004 

538 

90.1 

97.6 

105.9 

112.4 

117.1 

124.4 

130.9 

136.9 

143.3 

151.4 

156.0 

159.1 

161.8 

162.0 

161.9 

163.2 

163.0 

163.1 

162.8 

163.0 

163.4 

162.3 

160.0 

157.4 

0.4 

0.5 

0.5 

0.7 

0.7 

0.5 

0.6 

0.7 

0.9 

0.7 

0.7 

0.6 

0.6 

0.6 

0.5 

0.6 

0.5 

0.7 

0.3 

0.3 

0.2 

0.3 

0.2 

0.3 

-

N 

SE 

Source: 

= Data not available. 

= Number of individuals. 

= Standard error. 

Ogden et al. (2004). 

Page Exposure Factors Handbook 8-26 September 2011 
Exposure Factors Handbook 

Chapter 8—Body Weight Studies Exposure Factors Handbook 

Page 

September 2011 8-27 

Table 8-16. Mean Body Mass Index (kg/m 2) by Age and Sex Across Multiple Surveys 

Sex 

and Age 

(years) 

NHES II, 1963−1965 NHES III, 1966−1970 NHANES I, 1971−1974 NHANES II, 1976−1980 NHANES III, 1988−1994 NHANES, 1999−2002 

N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Male 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 74 

75+ 

-

-

-

-

575 

632 

618 

603 

576 

595 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

15.6 

15.9 

16.3 

16.9 

17.1 

17.9 

-

-

-

-

-

-

-

-

-

-

-

-

-

-­

-

-

-

-

0.1 

0.1 

0.1 

0.2 

0.1 

0.1 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

643 

626 

618 

613 

556 

458 

-

-

-

-

-

-

-

-­

-

-

-

-

-

-

-

-

-

-

18.4 

19.4 

20.2 

20.9 

21.3 

22.1 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.1 

0.1 

0.2 

0.1 

0.1 

0.1 

-

-

-

-

-

-

-

-

298 

308 

304 

273 

179 

164 

152 

169 

184 

178 

200 

174 

174 

171 

169 

176 

124 

136 

986 

654 

715 

717 

1,920 

-

16.3 

16.0 

15.7 

15.6 

15.7 

15.8 

15.8 

17.1 

17.3 

18.0 

18.7 

19.6 

20.2 

20.5 

21.8 

21.9 

23.7 

23.3 

24.5 

26.1 

26.2 

26.0 

25.4 

-

0.1 

0.1 

0.1 

0.1 

0.2 

0.2 

0.2 

0.3 

0.2 

0.3 

0.2 

0.3 

0.3 

0.3 

0.3 

0.3 

0.3 

0.5 

0.1 

0.2 

0.2 

0.2 

0.1 

-

350 

421 

405 

393 

146 

150 

145 

141 

165 

153 

147 

165 

188 

180 

180 

183 

156 

150 

1,261 

871 

695 

691 

2,086 

-

16.2 

15.9 

15.8 

15.6 

16.0 

16.0 

16.5 

16.8 

18.0 

18.6 

18.8 

19.5 

20.2 

20.8 

22.0 

21.8 

22.6 

23.1 

24.3 

25.6 

26.4 

26.2 

25.7 

-

0.1 

0.1 

0.1 

0.1 

0.2 

0.2 

0.2 

0.2 

0.3 

0.3 

0.3 

0.4 

0.2 

0.3 

0.3 

0.2 

0.4 

0.3 

0.1 

0.1 

0.2 

0.2 

0.1 

-

588 

512 

547 

495 

282 

269 

266 

279 

297 

280 

203 

187 

188 

187 

194 

196 

176 

168 

1,638 

1,468 

1,220 

851 

1,683 

895 

16.5 

16.1 

15.9 

15.9 

16.3 

16.5 

17.3 

18.0 

18.4 

19.4 

20.1 

20.5 

22.3 

22.3 

22.3 

23.4 

22.6 

23.7 

25.2 

26.5 

27.3 

27.8 

27.2 

25.9 

0.1 

0.2 

0.1 

0.1 

0.3 

0.2 

0.4 

0.7 

0.3 

0.3 

0.3 

0.3 

1.1 

0.5 

0.5 

0.4 

0.5 

0.6 

0.2 

0.2 

0.2 

0.2 

0.2 

0.2 

225 

209 

178 

147 

182 

185 

214 

174 

187 

182 

299 

298 

266 

283 

306 

313 

284 

269 

712 

704 

774 

594 

991 

487 

16.6 

16.2 

16.3 

16.5 

16.4 

17.0 

18.4 

18.7 

19.1 

19.6 

20.7 

20.7 

22.3 

22.5 

24.1 

24.5 

24.2 

24.9 

26.6 

27.5 

28.4 

28.7 

28.6 

26.8 

0.1 

0.1 

0.2 

0.3 

0.2 

0.2 

0.4 

0.3 

0.3 

0.4 

0.4 

0.5 

0.4 

0.3 

0.4 

0.4 

0.3 

0.4 

0.2 

0.3 

0.3 

0.3 

0.2 

0.2 
Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 8-28 September 2011 

 

 

 

 

Table 8-16. Mean Body Mass Index (kg/m2) by Age and Sex Across Multiple Surveys (continued) 

Sex 

and Age 

(years) 

NHES II, 1963−1965 NHES III, 1966−1970 NHANES I, 1971−1974 NHANES II, 1976−1980 NHANES III, 

1988−1994 NHANES, 1999−2002 

N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Female 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 74 

75+ 

-

-

-

-

536 

609 

613 

581 

584 

525 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

115.4 

15.8 

16.4 

17.0 

17.6 

18.2 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.1 

0.1 

0.1 

0.1 

0.2 

0.2 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

547 

582 

586 

503 

536 

442 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

19.2 

19.9 

20.8 

21.4 

21.9 

21.7 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

0.1 

0.1 

0.1 

0.2 

0.2 

0.2 

-

-

-

-

-

-

-

-

272 

292 

281 

314 

176 

169 

152 

171 

197 

166 

177 

198 

184 

167 

171 

150 

141 

130 

2,122 

1,654 

1,232 

780 

2,131 

-

15.9 

15.7 

15.5 

15.5 

15.4 

15.6 

16.4 

17.2 

17.1 

18.6 

19.5 

20.4 

21.1 

21.1 

21.7 

22.6 

21.5 

22.5 

23.0 

24.7 

25.7 

26.2 

26.5 

-

0.1 

0.1 

0.1 

0.1 

0.1 

0.2 

0.2 

0.2 

0.2 

0.3 

0.4 

0.3 

0.3 

0.3 

0.3 

0.5 

0.3 

0.6 

0.1 

0.2 

0.2 

0.2 

0.2 

-

314 

367 

388 

369 

150 

154 

125 

154 

128 

143 

146 

155 

181 

144 

167 

134 

156 

158 

1,290 

964 

765 

793 

2,349 

-

16.1 

15.6 

15.5 

15.6 

15.6 

16.1 

16.3 

17.5 

17.7 

18.9 

19.3 

20.1 

21.0 

20.6 

21.8 

22.3 

22.3 

22.4 

23.1 

24.9 

25.7 

26.5 

26.5 

-

0.1 

0.1 

0.1 

0.1 

0.2 

0.2 

0.2 

0.3 

0.3 

0.3 

0.3 

0.4 

0.3 

0.3 

0.3 

0.4 

0.4 

0.3 

0.2 

0.2 

0.2 

0.2 

0.1 

-

562 

582 

533 

554 

272 

274 

247 

280 

258 

275 

236 

220 

218 

191 

208 

201 

175 

177 

1,663 

1,773 

1,354 

996 

1,673 

1,021 

16.5 

15.9 

16.0 

15.9 

16.1 

16.9 

17.3 

18.2 

18.4 

19.4 

20.2 

21.8 

22.4 

21.9 

23.0 

23.3 

22.9 

23.7 

24.3 

26.3 

27.1 

28.4 

27.4 

25.9 

0.1 

0.1 

0.2 

0.1 

0.3 

0.3 

0.3 

0.5 

0.4 

0.4 

0.5 

0.6 

0.5 

0.4 

0.5 

0.5 

0.6 

0.8 

0.2 

0.3 

0.3 

0.3 

0.2 

0.2 

214 

173 

190 

186 

170 

196 

184 

183 

163 

194 

315 

321 

324 

266 

273 

255 

243 

225 

654 

698 

783 

591 

993 

524 

16.4 

16.0 

15.9 

16.1 

16.2 

16.6 

18.3 

18.7 

19.3 

20.7 

21.2 

22.6 

22.9 

23.2 

24.0 

23.1 

24.4 

25.5 

26.8 

27.9 

28.6 

29.2 

29.2 

26.8 

0.1 

0.1 

0.2 

0.3 

0.2 

0.2 

0.5 

0.3 

0.3 

0.4 

0.4 

0.4 

0.4 

0.5 

0.4 

0.4 

0.5 

0.4 

0.3 

0.3 

0.4 

0.4 

0.2 

0.4 

- = Data not available. 

N = Number of individuals. 

SE = Standard error. 

Source: Ogden et al. (2004). 
 

 

 

 c 

Table 8-17. Sample Sizes by Age, Sex, Race, and Examination 

NHANES Examination 

Age Group 

(years) 

Sex Racea 

II (1976−1980) III (1988−1994) 1999−2002 

Overall 

(2 to 17) 6,395 (10.6)b 9,610 (9.9) 6,710 (10.1) 

2 to 5 Boys White 1,082 (4.1) 605 (4.0) 226 (3.9) 

Black 273 (4.1) 693 (3.9) 234 (4.0) 

Mexican American 105 (4.2) 732 (4.0) 231 (3.9) 

Girls White 1,028 (4.0) 639 (4.0) 235 (4.1) 

Black 234 (4.0) 684 (3.9) 222 (4.0) 

Mexican American 102 (4.2) 800 (3.9) 238 (4.1 

6 to 11 Boys White 667 (9.0) 446 (8.9) 298 (8.9) 

Black 137 (9.0) 584 (9.0) 371 (9.0) 

Mexican American 60 (9.2) 565 (9.0) 384 (9.0) 

Girls White 631 (9.1) 428 (9.1) 293 (8.9) 

Black 155 (9.0) 538 (9.0) 363 (9.1) 

Mexican American 40 (9.3) 581 (8.9) 361 (9.0) 

12 to 17 Boys White 786 (15.1) 282 (14.9) 449 (14.9) 

Black 155 (15.1) 412 (15.0) 543 (14.9) 

Mexican American 49 (15.0) 406 (15.0) 648 (15.0) 

Girls White 695 (15.1) 344 (15.0) 456 (14.9) 

Black 159 (15.0) 450 (14.9) 528 (14.8) 

Mexican American 37 (15.2) 421 (14.8) 631 (14.9) 

20 to 39 Male White - - 607 

Black - - 279 

Mexican American - - 399 

Female White - - 569 

Black - - 298 

Mexican American - - 358 

40 to 59 Male White - - 676 

Black - - 289 

Mexican American - - 310 

Female White - - 632 

Black - - 297 

Mexican American - - 332 

60 and overc Male White - - 866 

Black - - 256 

Mexican American - - 318 

Female White - - 862 

Black - - 275 

Mexican American - - 329 a Race was recorded in the 1st two examinations (using data concerning ancestry/national origin) to create comparable 

categories in all surveys. b	 Mean ages are shown in parentheses. There are no mean ages available for the older age group data (ages 20 and 

above). 

Data from Ogden et al. (2004). 

- No data available. 

Sources:	 Freedman et al. (2006); Ogden et al. (2004). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Exposure Factors Handbook Page
 

September 2011 8-29 
Table 8-18. Mean BMI (kg/m2

) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex (ages 2 to 17) 

Increase in Mean z-score Examination Yeara 

from 1971−1974 to 1999−2002 

Race 1971−1974 1976−1980 1988−1994 1999−2002 BMI Weight Height 

Overall	 White 18.0b 18.0 18.8 19.0 +0.33 +0.36 +0.20 

Black 17.8 18.2 19.1 20.0 +0.61 +0.63 +0.31 

Mexican American 18.6 18.8 19.5 20.1 +0.32 +0.52 +0.39 

Sex 

Boys	 White 17.9 18.0 18.8 19.0 +0.37 +0.42 +0.25 

Black 17.7 17.8 18.8 19.6 +0.53 +0.58 +0.32 

Mexican American 18.6 18.9 19.4 20.3 +0.38 +0.67 +0.57 

Girls	 White 18.0 18.0 18.7 19.0 +0.30 +0.32 +0.16 

Black 17.9 18.6 19.5 20.4 +0.71 +0.69 +0.30 

Mexican American 18.5 18.6 19.6 19.9 +0.25 +0.35 +0.21 

Age (years) 

2 to 5 White 15.8 15.7 16.0 16.2 +0.21 +0.22 +0.13 

Black 15.8 15.7 15.9 16.2 +0.34 +0.32 +0.18 

Mexican American 16.5 16.2 16.5 16.5 -0.02 +0.29 +0.43 

6 to 11 White 16.7 16.9 17.6 17.9 +0.42 +0.47 +0.30 

Black 16.5 17.1 17.9 18.7 +0.67 +0.69 +0.36 

Mexican American 16.9 17.7 18.5 18.8 +0.50 +0.65 +0.41 

12 to 17 White 20.7 20.6 21.8 22.0 +0.32 +0.35 +0.15 

Black 20.4 20.9 22.4 23.7 +0.72 +9,77 +0.33 

Mexican American 21.6 21.5 22.6 24.0 +0.37 +0.55 +0.34 a Secular trends for BMI, BMI-for-age, weight-for-age, and height-for-age were each statistically significant at the 0.001 level. Trends in BMI, BMI-forage, and weight also differed (p < 0.001) by race. b Mean BMI levels have been adjusted for differences in age and sex across exams. 

Source: Freedman et al. (2006). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 8-30 September 2011 
Exposure Factors Handbook Page 

September 2011 8-31 Chapter 8—Body Weight Studies Exposure Factors Handbook 

Table 8-19. Mean Body Mass Index (kg/m2) by Survey, Sex, Race/Ethnicity, and Age Group; Adults: United States 

Sex, Race/Ethnicity, and Age 

(years) 

HHANES, 1982−1984 NHANES III, 1988−1994 NHANES, 1999−2002 

Sample 

Size Mean 

Standard Error 

of the Mean 

Sample 

Size Mean 

Standard Error 

of the Mean 

Sample 

Size Mean 

Standard Error 

of the Mean 

Males 

Non-Hispanic White:

a 

20 and over - - - 3,152 26.8 0.1 2,116 27.9 0.2 

20 to 39 - - - 846 25.9 0.2 607 27.1 0.2 

40 to 59 - - - 842 27.6 0.2 673 28.7 0.3 

60 and over - - - 1,464 27.0 0.1 836 28.3 0.1 

Non-Hispanic Black: 

20 and over

a - - - 2,091 26.6 0.1 820 27.5 0.2 

20 to 39 yr

a - - - 985 26.3 0.2 279 27.1 0.3 

40 to 59 - - - 583 27.1 0.2 289 27.7 0.4 

60 and over

a - - - 523 26.4 0.3 252 28.0 0.3 

Mexican American:

a 

20 and over - - - 2,229 27.3 0.1 1,018 28.0 0.2 

20 to 74 2,273 26.2 0.2 2,127 27.3 0.1 959 28.1 0.2 

20 to 39 1,133 25.6 0.3 1,143 26.1 0.2 399 27.1 0.3 

40 to 59 856 26.9 0.1 558 28.6 0.2 309 28.9 0.3 

60 to 74 284 26.3 0.2 426 27.4 0.3 251 28.6 0.3 

60 and over - - - 528 27.1 0.3 310 28.1 0.3 

Females 

Non-Hispanic white:

a 

20 and over - - - 3,554 26.1 0.2 2,026 27.6 0.2 

20 to 39 - - - 1,030 24.7 0.2 567 26.7 0.3 

40 to 59 - - - 950 27.2 0.3 629 28.3 0.4 

60 and over - - - 1,574 26.7 0.2 830 28.2 0.2 

Non-Hispanic Black:

a 

20 and over - - - 2,451 29.1 0.2 863 31.1 0.3 

20 to 39 - - - 1,191 27.6 0.3 298 30.2 0.5 

40 to 59 - - - 721 30.4 0.3 294 32.1 0.5 

60 and over - - - 539 29.4 0.4 271 31.1 0.6 

Mexican American: 

20 and over - - - 2,106 28.4 0.2 1,012 29.0 0.3 

20 to 74a 3,039 27.1 0.1 2,013 28.5 0.2 960 29.1 0.3 

20 to 39a 1,482 25.6 0.2 1,063 27.2 0.2 358 27.8 0.4 

40–to 59a 1,159 28.2 0.2 557 29.7 0.3 332 30.4 0.5 

60 to 74a 398 28.1 0.3 393 29.2 0.4 270 29.5 0.3 

60 and over - - - 486 28.7 0.4 322 28.9 0.4 a Statistically significant trend or difference p < 0.05 for all years available. 

- Data not available. 

Notes: BMI is calculated as weight in kilograms divided by square of height in meters. HHANES: Hispanic Health and Nutrition Examination Survey. 

Source: Ogden et al. (2004). 
Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 8-32 September 2011 

Table 8-20. Prevalence of Overweight and Obesitya Among Children 

Increase in Prevalence from Examination Year 1971−1974 to 1999−2002 

Race 1971−1974 1976−1980 1988−1994 1999−2002 Overweight Obesity 

Overall White 5% (1)b 5% (1) 9% (2) 12% (3) +8 +2 

Black 6% (1) 7% (2) 12% (3) 18% (5) +12 +4 

Mexican American 8% (1) 10% (1) 14% (4) 21% (5) +12 +4 

Sex 

Boys White 5% (1) 5% (1) 10% (2) 13% (4) +8 +3 

Black 6% (2) 5% (1) 11% (3) 16% (5) +10 +3 

Mexican American 8% (1) 12% (1) 15% (4) 24% (4) +16 +6 

Girls White 5% (1) 5% (1) 9% (2) 12% (2) +7 +1 

Black 6% (1) 9% (2) 14% (3) 21% (6) +14 +5 

Mexican American 8% (2) 7% (0) 14% (3) 17% (4) +9 +2 

Age (yr) 

2 to 5 White 4% (1) 3% (1) 5% (1) 9% (3) +5 +2 

Black 7% (3) 4% (0) 8% (3) 9% (4) +2 +1 

Mexican American 10% (5) 11% (3) 12% (5) 13% (5) +3 0 

6 to 11 White 4% (0) 6% (1) 11% (3) 13% (4) +10 +3 

Black 4% (0) 9% (3) 15% (3) 20% (5) +15 +4 

Mexican American 6% (0) 11% (0) 17% (4) 22% (5) +16 +5 

12 to 17 White 6% (1) 4% (0) 11% (2) 13% (2) +7 +1 

Black 8% (1) 8% (1) 13% (3) 22% (6) +14 +5 

Mexican American 9% (0) 8% (1) 14% (2) 25% (5) +15 +5 a Overweight is defined as a BMI >95th percentile or >30 kg/m2

; obesity is defined as a BMI >99th percentile or >40 kg/m2. b Values are percentage of overweight children (percentage of obese children). 

Source: Freedman et al. (2006). 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-21. Numbers of Live Births by Weight and Percentages of Live Births With Low and Very Low 

Birth Weights, by Race, and Hispanic Origin of Mother: United States, 2005 

All Racesa Non-Hispanic 

Whiteb 

Non-Hispanic 

Blackb 

Hispanicc 

Total Births 4,138,349 2,279,768 583,759 985,505 

Weight (g) Number of Live Births 

<500 6,599 2,497 2,477 1,212 

500−999 23,864 10,015 8,014 4,586 

1,000−1,499 31,325 14,967 8,573 5,988 

1,500−1,999 66,453 33,687 15,764 12,710 

2,000−2,499 210,324 104,935 46,846 43,300 

2,500−2,999 748,042 364,726 144,803 176,438 

3,000−3,499 1,596,944 857,136 221,819 399,295 

3,500−3,999 1,114,887 672,270 108,698 266,338 

4,000−4,499 289,098 167,269 22,149 64,704 

4,500−4,999 42,119 27,541 3,203 9,167 

>5,000 4,715 2,840 405 1,174 

Not stated 3,979 1,885 1,008 593 

% of Total 

Low Birth Weightd 8.2 7.3 14.0 6.9 

Very Low Birth Weighte 1.5 1.2 3.3 1.2 

a All Races includes White, Black, and races other than White and Black and origin not stated. b Race categories are consistent with the 1977 Office of Management and Budget standards. c Hispanic includes all persons of Hispanic origin of any race. d Low birth weight is birth weight less than 2,500 g (5 lb 8 oz). e Very low birth weight is birth weight less than 1,500 g (3 lb 4 oz). 

Source: Martin et al. (2007). 

Exposure Factors Handbook Page
 

September 2011 8-33 
Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES II Data
 

Age Groupa 

(years) 

Males (kg) Females (kg) Overall (kg) 

Mean SD N Mean SD N Mean SD N 

0 to 1 

1 to 2 

2 to 3 

3 to 4 

4 to 5 

5 to 6 

6 to 7 

7 to 8 

8 to 9 

9 to 10 

10 to 11 

11 to 12 

12 to 13 

13 to 14 

14 to 15 

15 to 16 

16 to 17 

17 to 18 

18 to 19 

19 to 20 

20 to 21 

21 to 22 

22 to 23 

23 to 24 

24 to 25 

25 to 26 

26 to 27 

27 to 28 

28 to 29 

29 to 30 

30 to 31 

31 to 32 

32 to 33 

33 to 34 

34 to 35 

35 to 36 

36 to 37 

37 to 38 

38 to 39 

39 to 40 

40 to 41 

41 to 42 

42 to 43 

43 to 44 

44 to 45 

45 to 46 

46 to 47 

47 to 48 

48 to 49 

49 to 50 

50 to 51 

51 to 52 

52 to 53 

53 to 54 

9.4 

11.8 

13.6 

15.6 

17.8 

19.8 

23.0 

25.1 

28.2 

31.1 

36.4 

40.2 

44.2 

49.8 

57.1 

61.0 

67.1 

66.7 

71.0 

71.7 

71.6 

74.76 

76.10 

75.93 

75.18 

76.34 

79.49 

76.17 

79.80 

77.64 

78.63 

78.19 

79.15 

80.73 

81.24 

79.04 

80.41 

79.06 

83.01 

79.85 

84.20 

81.20 

79.67 

81.50 

82.76 

80.91 

82.83 

82.29 

81.52 

80.60 

81.14 

81.25 

82.38 

79.37 

1.3 

1.6 

1.8 

1.9 

2.4 

2.8 

3.7 

3.8 

5.6 

5.8 

7.2 

9.8 

9.8 

11.4 

10.7 

10.4 

11.7 

11.3 

12.0 

11.3 

12.0 

12.73 

12.88 

11.76 

11.65 

11.52 

14.18 

12.34 

14.15 

11.63 

13.63 

14.19 

12.99 

12.67 

14.83 

12.81 

14.10 

12.41 

15.40 

13.02 

13.22 

15.07 

11.86 

14.04 

13.41 

13.77 

15.28 

11.83 

12.63 

13.31 

14.23 

11.27 

15.03 

12.94 

179 

370 

375 

418 

404 

397 

133 

148 

147 

145 

157 

155 

145 

173 

186 

184 

178 

173 

164 

148 

114 

150 

135 

148 

129 

118 

127 

112 

104 

124 

103 

108 

102 

86 

83 

91 

79 

83 

65 

71 

76 

73 

74 

68 

65 

62 

68 

55 

77 

77 

79 

69 

73 

69 

8.8 

10.8 

13.0 

14.9 

17.0 

19.6 

22.1 

24.7 

27.8 

31.8 

36.1 

41.8 

46.4 

50.9 

54.7 

55.1 

58.1 

59.6 

59.0 

60.1 

60.5 

60.39 

60.51 

61.21 

62.71 

62.64 

61.74 

62.83 

63.79 

63.33 

64.90 

67.71 

68.94 

63.43 

63.03 

67.30 

65.41 

66.81 

66.56 

67.21 

70.56 

65.25 

65.81 

68.45 

66.96 

65.18 

70.45 

68.02 

67.39 

66.83 

70.81 

67.20 

66.07 

68.83 

1.3 

1.4 

1.5 

2.1 

2.3 

3.2 

3.9 

4.6 

4.8 

7.3 

7.7 

10.1 

10.1 

11.2 

10.7 

9.0 

9.6 

10.4 

10.2 

10.1 

10.7 

11.14 

10.11 

11.48 

13.44 

12.46 

11.77 

12.18 

14.34 

12.92 

13.71 

14.45 

17.51 

11.77 

14.43 

15.62 

11.27 

13.08 

15.72 

13.85 

17.70 

12.91 

12.14 

14.89 

15.19 

14.78 

15.91 

13.67 

15.71 

14.54 

14.67 

11.99 

14.58 

14.83 

177 

336 

336 

366 

396 

364 

135 

157 

123 

149 

136 

140 

147 

162 

178 

145 

170 

134 

170 

158 

162 

170 

150 

133 

123 

120 

118 

130 

138 

122 

139 

116 

104 

92 

91 

113 

84 

97 

71 

79 

77 

70 

98 

84 

71 

65 

82 

73 

67 

79 

98 

67 

88 

73 

9.1 

11.3 

13.3 

15.2 

17.4 

19.7 

22.5 

24.8 

28.1 

31.4 

36.2 

41.0 

45.4 

50.4 

55.9 

58.0 

62.4 

63.3 

64.6 

65.3 

65.2 

66.71 

67.30 

68.43 

68.43 

68.80 

70.57 

68.24 

69.79 

69.97 

70.44 

72.33 

73.43 

71.82 

70.91 

72.24 

72.03 

71.82 

74.14 

73.19 

76.49 

73.47 

71.23 

73.38 

73.70 

72.33 

75.24 

73.42 

74.28 

73.07 

75.12 

73.81 

72.70 

73.71 

1.2 

1.5 

1.6 

1.8 

2.4 

2.8 

3.6 

3.8 

5.6 

5.9 

7.1 

9.9 

10.0 

11.5 

10.5 

9.9 

10.9 

10.7 

10.9 

10.3 

10.9 

11.35 

11.39 

10.60 

10.60 

10.38 

12.59 

11.06 

12.38 

10.48 

12.21 

13.13 

12.05 

11.27 

12.94 

11.71 

12.63 

11.27 

13.76 

11.94 

12.01 

13.63 

10.60 

12.64 

11.94 

12.31 

13.89 

10.55 

11.51 

12.06 

13.17 

10.23 

13.27 

12.02 

356 

706 

711 

784 

800 

761 

268 

305 

270 

294 

293 

295 

292 

335 

364 

329 

348 

307 

334 

306 

276 

320 

285 

281 

252 

238 

245 

242 

242 

246 

242 

224 

206 

178 

174 

204 

163 

180 

136 

150 

153 

143 

172 

152 

136 

127 

150 

128 

144 

156 

177 

136 

161 

142 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 

8-34 September 2011 
 

 

 

 

 

Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES II Data (continued) 

Age Groupa 

(years) 

Males (kg) Females (kg) Overall (kg) 

Mean SD N Mean SD N Mean SD N 

54 to 55 76.63 13.36 61 67.62 14.64 71 71.52 12.47 132 

55 to 56 81.92 15.12 62 71.93 16.17 90 75.32 13.90 152 

56 to 57 77.36 11.28 69 70.82 15.40 67 73.59 10.73 136 

57 to 58 79.85 13.02 64 66.87 14.41 99 71.60 11.68 163 

58 to 59 79.23 12.52 73 68.73 13.60 70 73.28 11.58 143 

59 to 60 80.00 12.47 72 64.43 12.88 70 71.45 11.14 142 

60 to 61 79.76 12.92 183 67.28 12.83 218 72.75 11.79 401 

61 to 62 78.42 11.75 169 68.12 13.83 176 72.68 10.89 345 

62 to 63 77.06 12.33 188 66.09 13.69 184 71.00 11.36 372 

63 to 64 77.07 11.31 162 66.41 14.03 178 70.72 10.38 340 

64 to 65 77.27 13.63 185 67.45 13.77 177 72.26 12.74 362 

65 to 66 77.36 13.25 158 68.48 14.68 185 71.84 12.30 343 

66 to 67 75.35 13.21 138 67.36 13.95 182 70.40 12.34 320 

67 to 68 73.98 12.82 143 65.98 13.47 149 69.19 11.99 292 

68 to 69 74.14 14.60 124 68.87 13.63 161 71.02 13.98 285 

69 to 70 74.40 13.20 129 65.59 13.39 119 69.37 12.30 248 

70 to 71 75.17 13.03 128 65.04 12.47 136 69.32 12.01 264 

71 to 72 74.45 12.60 115 65.62 13.53 139 69.00 11.67 254 

72 to 73 73.47 12.36 100 64.89 11.58 135 68.17 11.46 235 

73 to 74 72.80 12.17 82 65.59 12.71 108 68.36 11.43 190 

74+ 75.89 13.38 82 67.20 14.48 102 70.55 12.44 184 

a Data were converted from ages in months to ages in years. For instance, age 1–2 yr represents ages from 12 to 23 mo. 

SD = Standard deviation. 

N = Number of individuals. 

Source: Portier et al. (2007). 

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Chapter 8—Body Weight Studies 

Exposure Factors Handbook Page
 

September 2011 8-35 
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8-36 September 2011 

 

 

 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-23. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using NHANES 

III Data 

Age Groupa Males (kg) Females (kg) Overall (kg) 

(years) Mean SD N Mean SD N Mean SD N 

0 to 1 8.5 1.5 902 7.8 1.6 910 8.17 1.7 1,812 

1 to 2 11.6 1.5 660 10.9 1.4 647 11.2 1.5 1,307 

2 to 3 13.6 1.5 644 13.2 1.8 624 13.4 1.8 1,268 

3 to 4 15.8 2.3 516 15.4 2.2 587 15.6 2.2 1,103 

4 to 5 17.6 2.4 549 17.9 3.2 537 17.8 3.2 1,086 

5 to 6 20.1 3.0 497 20.2 3.5 554 20.2 3.5 1,051 

6 to 7 23.2 5.0 283 22.6 4.7 272 22.9 4.8 555 

7 to 8 26.3 5.0 269 26.3 6.2 274 26.4 6.2 543 

8 to 9 30.1 6.9 266 29.8 6.7 248 30.0 6.7 514 

9 to 10 34.4 7.9 281 34.3 9.0 280 34.4 9.0 561 

10 to 11 37.3 8.6 297 37.9 9.5 258 37.7 9.4 555 

11 to 12 42.5 10.5 281 44.2 10.5 275 43.4 10.3 556 

12 to 13 49.1 11.1 203 49.1 11.6 236 49.1 11.7 439 

13 to 14 54.0 12.9 187 55.7 13.2 220 54.8 13.0 407 

14 to 15 63.7 17.1 188 58.3 11.8 220 60.6 12.2 408 

15 to 16 66.8 14.9 187 58.3 10.1 197 61.7 10.7 384 

16 to 17 68.6 14.9 194 61.5 12.8 215 65.2 13.6 409 

17 to 18 72.7 13.3 196 62.4 11.9 217 67.6 12.9 413 

18 to 19 71.2 14.3 176 61.5 14.2 193 66.4 15.3 369 

19 to 20 73.0 12.8 168 63.6 14.5 193 68.3 15.6 361 

20 to 21 72.5 13.4 149 61.7 12.9 180 66.1 13.8 329 

21 to 22 72.92 12.86 161 65.01 16.03 188 69.24 17.08 349 

22 to 23 76.34 14.72 160 64.07 13.61 193 69.48 14.75 353 

23 to 24 77.85 14.37 172 66.99 16.24 205 72.72 17.63 377 

24 to 25 78.56 15.38 187 62.79 12.62 200 70.16 14.10 387 

25 to 26 80.33 17.89 171 66.19 16.05 157 74.11 17.97 328 

26 to 27 75.88 12.84 143 64.89 15.19 184 69.73 16.33 327 

27 to 28 81.17 14.90 176 65.10 14.43 184 73.33 16.25 360 

28 to 29 81.10 18.23 154 66.97 15.26 190 73.28 16.70 344 

29 to 30 81.93 16.89 156 65.89 13.65 177 73.33 15.19 333 

30 to 31 83.56 16.71 163 67.76 16.85 202 75.11 18.68 365 

31 to 32 79.48 13.12 155 72.48 19.32 204 77.04 20.54 359 

32 to 33 81.65 15.82 159 67.53 17.22 179 74.33 18.95 338 

33 to 34 84.03 16.63 153 68.49 16.03 176 75.09 17.58 329 

34 to 35 82.95 15.56 162 67.55 14.27 186 76.47 16.16 348 

35 to 36 81.24 16.16 143 71.45 17.47 188 76.02 18.59 331 

36 to 37 87.67 21.26 163 66.02 14.29 180 77.32 16.74 343 

37 to 38 83.33 17.61 123 72.04 17.69 202 76.42 18.77 325 

38 to 39 82.53 14.47 136 71.58 17.43 183 76.85 18.71 319 

39 to 40 82.62 12.46 122 74.57 19.41 157 79.34 20.65 279 

40 to 41 85.84 15.23 152 68.70 15.80 198 75.55 17.37 350 

41 to 42 86.19 18.93 148 70.11 13.80 183 78.34 15.42 331 

42 to 43 85.12 16.76 161 72.72 19.46 171 79.25 21.21 332 

43 to 44 86.37 17.71 139 68.94 15.35 123 77.80 17.33 262 

44 to 45 90.62 20.37 120 72.61 17.15 152 79.13 18.69 272 

45 to 46 83.58 13.46 108 71.78 15.76 125 78.22 17.18 233 

46 to 47 80.70 13.00 102 72.07 15.53 113 76.30 16.44 215 

47 to 48 85.54 17.28 116 72.09 15.98 102 79.28 17.57 218 

48 to 49 82.29 14.93 93 75.80 16.09 95 79.21 16.82 188 

49 to 50 82.25 16.11 85 73.41 18.26 106 77.95 19.39 191 

50 to 51 81.69 13.24 77 74.05 18.03 118 77.31 18.82 195 

51 to 52 85.78 15.39 84 79.48 19.60 85 83.81 20.67 169 

52 to 53 87.02 13.66 93 72.00 16.86 100 79.97 18.72 193 

53 to 54 89.44 14.86 86 73.92 17.08 97 81.86 18.91 183 
 

 

 

 

 

Table 8-23. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES III Data (continued) 

Age Groupa 

(years) 

Males(kg) Females (kg) Overall (kg) 

Mean SD N Mean SD N Mean SD N 

54 to 55 86.02 16.76 86 74.63 19.97 113 79.88 21.38 199 

55 to 56 83.10 14.99 82 72.56 14.06 102 76.59 14.84 184 

56 to 57 87.16 15.10 96 77.69 16.74 105 83.15 17.91 201 

57 to 58 86.31 15.04 89 75.65 17.87 97 82.12 19.40 186 

58 to 59 83.54 15.67 81 72.26 16.47 100 76.89 17.52 181 

59 to 60 87.93 16.14 74 74.00 15.33 82 80.48 16.67 156 

60 to 61 83.54 14.22 130 68.73 13.60 104 75.88 15.02 234 

61 to 62 81.91 15.03 119 72.26 15.42 141 76.50 16.32 260 

62 to 63 81.98 15.47 116 72.97 17.54 114 77.18 18.55 230 

63 to 64 84.15 14.50 118 71.32 14.48 111 76.88 15.61 229 

64 to 65 84.28 15.73 116 74.34 17.40 126 78.86 18.46 242 

65 to 66 85.10 14.75 127 67.47 16.08 118 76.14 18.14 245 

66 to 67 81.43 15.03 102 71.82 14.58 118 76.49 15.53 220 

67 to 68 84.35 15.22 117 68.98 15.22 95 76.08 16.78 212 

68 to 69 80.60 11.75 98 70.72 16.56 110 76.07 17.81 208 

69 to 70 84.81 18.18 113 66.57 11.74 97 74.84 13.20 210 

70 to 71 80.18 14.14 92 68.36 15.72 124 72.95 16.78 216 

71 to 72 79.34 14.64 126 70.74 17.89 98 75.64 19.13 224 

72 to 73 78.97 13.36 119 66.70 13.89 101 72.76 15.15 220 

73 to 74 82.07 17.26 109 68.24 14.14 115 74.37 15.41 224 

74 to 75 79.32 15.37 84 69.08 13.67 97 73.57 14.56 181 

75 to 76 77.18 10.47 75 68.58 13.50 85 72.89 14.35 160 

76 to 77 79.30 14.88 64 65.68 13.88 94 70.38 14.87 158 

77 to 78 80.70 13.98 64 67.33 14.16 86 72.43 15.23 150 

78 to 79 75.21 11.34 50 63.67 14.31 63 67.94 15.27 113 

79 to 80 78.75 11.32 45 60.21 14.41 61 67.28 16.10 106 

80 to 81 76.94 15.15 108 63.55 13.10 101 68.77 14.18 209 

81 to 82 73.70 13.30 96 63.17 12.70 112 66.94 13.45 208 

82 to 83 73.25 12.32 81 61.96 12.01 69 67.05 12.99 150 

83 to 84 72.10 15.31 63 62.78 12.23 63 65.80 12.82 126 

84 to 85 72.09 10.73 62 63.68 11.43 57 66.74 11.97 119 

85+ 70.08 11.64 189 59.67 11.69 240 63.11 12.36 429 

a Data were converted from ages in months to ages in years. For instance, age 1–2 yr represents ages from 12 to 23 mo. 

SD = Standard deviation. 

N = Number of individuals. 

Source: Portier et al. (2007). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Exposure Factors Handbook Page
 

September 2011 8-37 
Page Exposure Factors Handbook 

8-38 September 2011 

 

 

 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-24. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES IV Data 

Age Groupa Males (kg) Females (kg) Overall (kg) 

(years) Mean SD N Mean SD N Mean SD N 

0 to 1 9.3 1.8 116 9.3 1.5 101 9.3 1.5 217 

1 to 2 11.3 1.4 144 11.5 1.9 98 11.4 1.8 242 

2 to 3 13.7 2.0 130 13.3 1.9 113 13.5 2.0 243 

3 to 4 16.4 2.3 105 15.2 2.1 77 15.9 2.2 182 

4 to 5 18.8 2.6 95 18.1 3.2 87 18.5 3.3 182 

5 to 6 20.2 3.3 65 20.7 4.9 92 20.6 4.9 157 

6 to 7 22.9 4.3 94 22.0 4.5 74 22.5 4.6 168 

7to 8 28.1 5.6 100 26.0 6.2 82 27.4 6.5 182 

8 to 9 31.9 8.6 100 30.8 7.2 89 31.3 7.3 189 

9 to 10 36.1 7.5 76 36.0 8.4 84 36.2 8.5 160 

10 to 11 39.5 9.0 92 39.4 10.2 84 39.5 10.2 176 

11 to 12 42.0 10.2 84 47.2 12.2 97 44.6 11.6 181 

12 to 13 49.4 12.7 158 51.6 12.3 160 50.3 11.9 318 

13 to 14 54.9 16.2 161 59.8 15.3 156 56.9 14.6 317 

14 to 15 65.1 19.9 137 59.9 13.3 158 61.5 13.7 295 

15 to 16 68.2 15.7 142 63.4 13.9 126 65.9 14.4 268 

16 to 17 72.5 18.6 153 63.4 16.0 142 68.0 17.1 295 

17 to 18 75.4 17.9 146 59.9 11.9 128 66.6 13.2 274 

18 to 19 74.8 15.9 131 65.0 15.2 139 70.2 16.4 270 

19 to 20 80.1 17.2 129 68.7 17.4 132 74.6 19.0 261 

20 to 21 80.0 15.5 37 66.3 15.5 44 74.3 17.4 81 

21 to 22 73.84 12.87 33 65.89 15.49 47 69.40 16.32 80 

22 to 23 89.62 23.98 37 67.27 15.47 49 75.85 17.44 86 

23 to 24 83.39 18.31 36 73.58 23.21 53 80.27 25.32 89 

24 to 25 80.26 19.38 20 71.81 21.27 54 75.04 22.23 74 

25 to 26 87.47 14.89 27 71.64 20.31 44 80.45 22.80 71 

26 to 27 72.11 14.64 33 78.09 20.98 47 75.63 20.32 80 

27 to 28 85.78 22.69 30 72.48 18.10 49 78.75 19.67 79 

28 to 29 88.04 26.64 36 76.18 16.18 34 81.29 17.26 70 

29 to 30 84.02 15.16 35 71.88 16.60 50 78.10 18.04 85 

30 to 31 80.10 22.28 29 74.00 22.71 48 77.01 23.63 77 

31 to 32 84.65 18.59 33 79.12 22.51 49 82.51 23.48 82 

32 to 33 90.99 15.77 35 77.53 18.15 55 83.82 19.62 90 

33 to 34 90.90 18.74 37 76.60 22.28 29 85.94 25.00 66 

34 to 35 79.09 19.50 33 73.26 16.92 49 75.72 17.49 82 

35 to 36 91.15 25.45 33 79.91 22.74 37 84.60 24.07 70 

36 to 37 88.96 17.15 29 72.10 20.29 38 80.17 22.55 67 

37 to 38 84.62 17.62 47 70.75 15.39 35 79.21 17.23 82 

38 to 39 80.52 17.26 29 80.86 22.32 40 81.18 22.41 69 

39 to 40 84.77 14.26 37 78.08 19.34 43 81.92 20.29 80 

40 to 41 92.21 26.63 40 73.87 18.14 47 82.13 20.17 87 

41 to 42 83.11 14.06 37 75.91 17.38 37 79.56 18.21 74 

42 to 43 91.94 15.56 46 82.03 21.78 41 88.15 23.41 87 

43 to 44 89.48 16.15 40 71.59 17.81 27 83.18 20.69 67 

44 to 45 87.00 14.63 34 74.86 18.15 42 80.04 19.41 76 

45 to 46 84.61 17.53 33 81.15 23.52 50 83.21 24.12 83 

46 to 47 93.27 20.48 28 74.94 16.84 34 82.90 18.63 62 

47 to 48 80.87 11.38 29 68.24 16.97 38 74.29 18.48 67 

48 to 49 85.58 17.91 21 82.10 29.55 34 84.51 30.42 55 

49 to 50 88.84 24.90 28 75.55 21.74 24 82.17 23.64 52 

50 to 51 90.09 14.51 26 83.22 27.42 27 88.10 29.03 53 

51 to 52 90.63 18.22 35 76.89 16.09 36 83.63 17.50 71 

52 to 53 90.62 19.52 24 80.89 19.78 42 85.03 20.79 66 

53 to 54 92.42 21.93 28 76.12 16.64 32 82.96 18.13 60 
 

 

 

 

 

 

 

Table 8-24. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using 

NHANES IV Data (continued) 

Age Groupa 

(years) 

Males (kg) Females (kg) Overall (kg) 

Mean SD N Mean SD N Mean SD N 

54 to 55 90.51 21.10 32 75.19 18.07 36 81.46 19.58 68 

55 to 56 84.84 18.72 20 79.87 16.71 25 82.39 17.24 45 

56 to 57 84.48 18.55 26 80.68 20.24 32 82.72 20.75 58 

57 to 58 86.02 20.50 26 73.07 13.79 24 80.20 15.13 50 

58 to 59 89.11 21.33 19 71.21 16.01 17 79.97 17.97 36 

59 to 60 83.82 16.33 25 76.28 16.36 17 80.76 17.32 42 

60 to 61 89.53 17.90 60 75.97 18.66 43 83.70 20.56 103 

61 to 62 86.04 15.44 34 77.01 16.67 37 81.12 17.56 71 

62 to 63 84.46 16.28 41 75.78 13.13 45 79.50 13.78 86 

63 to 64 86.51 20.07 24 77.95 16.96 39 80.73 17.56 63 

64 to 65 91.45 16.88 39 76.75 18.29 42 83.98 20.01 81 

65 to 66 89.46 18.44 41 72.95 18.37 41 80.38 20.24 82 

66 to 67 90.40 20.13 49 79.00 17.67 26 86.09 19.26 75 

67 to 68 85.34 19.18 36 77.76 18.21 35 81.18 19.01 71 

68 to 69 84.48 12.92 26 73.28 14.12 35 78.20 15.07 61 

69 to 70 92.35 16.95 24 69.94 9.20 32 80.53 10.59 56 

70 to 71 81.91 16.38 47 70.50 12.94 32 76.06 13.96 79 

71 to 72 79.65 21.31 25 66.22 13.04 35 68.99 13.58 60 

72 to 73 84.67 17.45 32 76.89 15.30 21 81.08 16.13 53 

73 to 74 89.70 15.36 35 72.75 16.80 27 81.69 18.87 62 

74 to 75 80.85 17.00 17 69.21 16.35 31 73.34 17.32 48 

75 to 76 84.26 11.94 25 68.61 10.42 21 75.14 11.41 46 

76 to 77 86.13 15.45 20 67.42 11.34 25 73.62 12.38 45 

77 to 78 81.68 14.15 18 78.35 17.45 21 80.09 17.84 39 

78 to 79 81.99 16.39 26 72.30 14.16 17 77.77 15.23 43 

79 to 80 80.18 10.39 19 67.95 12.54 21 73.39 13.54 40 

80 to 81 75.90 12.07 27 60.97 14.46 23 65.39 15.51 50 

81 to 82 73.77 7.40 31 68.76 13.75 25 71.28 14.25 56 

82 to 83 81.01 13.46 20 62.93 9.81 20 68.51 10.68 40 

83 to 84 76.07 10.63 12 66.24 11.68 12 70.90 12.50 24 

84 to 85 73.06 12.88 12 66.29 15.04 17 68.79 15.60 29 

85+ 74.10 12.23 46 59.68 10.04 59 64.45 10.84 105 a Data were converted from ages in months to ages in years. For instance, age 1–2 yr represents ages from 12 to 

23 mo. 

SD = Standard deviation. 

N = Number of individuals. 

Source: Portier et al. (2007). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Exposure Factors Handbook Page
 

September 2011 8-39 
 

 

 

Table 8-25. Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessmentsa 

Age Group 

(years) NHANES Males (kg) Females (kg) Overall (kg) 

Mean SD N Mean SD N Mean SD N 

1 to 6 

II 17.0 4.6 2,097 16.3 4.7 1,933 16.7 4.5 4,030 

III 16.9 4.7 3,149 16.5 4.9 3,221 16.8 5.0 6,370 

IV 17.1 4.9 633 17.5 5.0 541 17.3 5.0 1,174 

7 to 16 

II 45.2 17.6 1,618 43.9 15.9 1,507 44.8 17.5 3,125 

III 49.3 20.9 2,549 46.8 18.0 2,640 47.8 18.4 5,189 

IV 47.9 20.1 1,203 47.9 19.2 1,178 47.7 19.1 2,381 

18 to 65 

II 78.65 13.23 4,711 65.47 13.77 5,187 71.23 11.97 9,898 

III 82.19 16.18 6,250 69.45 16.55 7,182 75.61 18.02 13,462 

IV 85.47 19.03 1,908 74.55 19.32 2,202 79.96 20.73 4,110 

65+ 

II 74.45 13.05 1,041 66.26 13.25 1,231 69.56 12.20 2,272 

III 79.42 14.66 1,857 66.76 14.52 1,986 72.25 15.71 3,843 

IV 83.50 16.35 547 69.59 14.63 535 75.54 15.88 1,082 a Estimates were weighted using the sample weights provided with each survey. 

SD = Standard deviation. 

N = Number of individuals. 

Source: Portier et al. (2007). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Page Exposure Factors Handbook 

8-40 September 2011 
 

 

Table 8-26. Estimated Percentile Distribution of Body Weight by Fine Age Categories 

Derived From 1994−1996, 1998 CSFII 

Weight (kg) 

Age Group Sample 

Size Mean Percentile 

1st 5th 10th 25th 50th 75th 90th 95th 99th 

Birth to 1 month 88 4 1a 2a 3a 3 3 4 4a 5a 5a 

1 to <3 months 245 5 2a 3a 4 4 5 6 6 7a 8a 

3 to <6 months 411 7 4a 5 5 6 7 8 9 10 12a 

6 to <12 months 678 9 6a 7 7 8 9 10 11 12 13a 

1 to <2 years 1,002 12 8a 9 9 10 11 13 14 15 19a 

2 to <3 years 994 14 10a 10 11 12 14 16 18 19 22a 

3 to <6 years 4,112 18 11 13 13 16 18 20 23 25 32 

6 to <11 years 1,553 30 16a 18 20 23 27 35 41 45 57a 

11 to <16 years 975 54 29a 33 36 44 52 61 72 82 95a 

16 to <18 years 360 67 41a 46a 50 56 63 73 86 100a 114a 

18 to <21 years 383 69 45a 48a 51 58 66 77 89 100a 117a 

≥21 years 9,049 76 45 51 54 63 74 86 99 107 126 

≥65 years 2,139 72 44 50 54 62 71 81 93 100 113 

All ages 19,850 65 8 15 22 52 67 81 95 104 122 

a Sample size does meet minimum reporting requirements as described in the 3rd Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source: Kahn and Stralka (2009). 

Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Exposure Factors Handbook Page
 

September 2011 8-41 
Table 8-27. Estimated Percentile Distribution of Body Weight by Fine Age Categories With Confidence Interval 

Weight (kg) 

Mean 90th Percentile 95th Percentile 

90% CI 90% BI 90% BI Age Group Sample Size 

Estimate Estimate Estimate Lower Upper Lower Upper Lower Upper 

Bound Bound Bound Bound Bound Bound 

4a 4a 5a 5a 5a 5a Birth to 1 month 88 4 3 4 

7a 1 to <3 months 245 5 5 5 6 6 7 7 7 

3 to <6 months 411 7 7 7 9 9 9 10 10 10 

6 to <12 months 678 9 9 9 11 11 11 12 12 12 

1 to <2 years 1,002 12 12 12 14 14 15 15 15 16 

2 to <3 years 994 14 14 14 18 17 18 19 18 19 

3 to <6 years 4,112 18 18 18 23 23 23 25 25 25 

6 to <11 years 1,553 30 29 30 41 41 43 45 44 48 

11 to <16 years 975 54 53 55 72 70 75 82 81 84 

16 to <18 years 360 67 66 68 86 84 95 100a 95a 109a 

18 to <21 years 383 69 68 70 89 88 95 100a 95a 104a 

≥21 years 9,049 76 - - 99 - - 107 - -

≥65 years 2,139 72 - - 93 - - 100 - -

All ages 19,850 65 - - 95 - - 104 - -

a Sample size does meet minimum reporting requirements as described in the 3rd Report on Nutrition Monitoring in the United States (Vol. I) (FASEB/LSRO, 

1995). Interval estimates may involve aggregation of variance estimation units when data are too sparse to support estimation of variance. 

CI = Confidence interval. 

BI = Percentile intervals estimated using percentile bootstrap method with 1,000 bootstrap replications. 

- = Data unavailable. 

Source: Kahn and Stralka (2009). 

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Chapter 8—Body Weight Studies 

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Table 8-28. Distribution of 1st Trimester Weight Gain and 2nd and 3rd Trimester Rates of Gain in Women With 

Good Pregnancy Outcomes
 

Percentile of Weight Gain 

Trimester 

10th 25th 50th 75th 90th Mean ± SD 

1st Trimester, kg 

Underweight −1.81 −0.14 1.92 3.78 5.77 1.92 ± 3.06 

Normal weight −2.21 −0.09 2.20 4.37 6.59 2.19 ± 3.47 

Overweight −2.91 −0.59 2.38 4.63 7.04 2.16 ± 3.95 

Obese −3.08 −0.86 1.17 3.89 7.22 1.65 ±3. 94 

2nd Trimester, kg/wka 

Underweight 0.33 0.44 0.56 0.69 0.82 0.57 ± 0.20 

Normal weight 0.31 0.44 0.56 0.71 0.85 0.58 ± 0.22 

Overweight 0.21 0.36 0.49 0.65 0.83 0.51 ± 0.24 

Obese 0.06 0.24 0.42 0.56 0.78 0.41 ± 0.27 

3rd Trimester, kg/wka 

Underweight 0.26 0.36 0.47 0.60 0.71 0.48 ± 0.19 

Normal weight 0.26 0.37 0.50 0.64 0.77 0.51 ± 0.21 

Overweight 0.21 0.34 0.47 0.63 0.77 0.49 ± 0.22 

Obese 0.19 0.31 0.43 0.64 0.80 0.47 ± 0.24 

a To calculate the distribution of total gain (kg) in the 2nd and 3rd trimesters, multiply the values in the 

table by 13 wk. 

SD = Standard deviation. 

Source: Carmichael et al. (1997). 

Exposure Factors Handbook Exposure Factors Handbook Chapter 8—Body Weight Studies 

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Chapter 8—Body Weight Studies 

Table 8-29. Estimated Body Weights of Pregnant Women―NHANES (1999−2006) 

Weight (kg) 

Mean Percentiles 

Trimester Sample size Estimate SD 5th 10th 15th 25th 50th 75th 85th 90th 95th 

1 204 76 3 48 50 55 60 74 91 98 106 108 

2 430 73 1 50 53 57 61 72 83 93 95 98 

3 402 80 1 60 63 65 69 77 88 99 104 108 

Ref/Dka 186 69 2 46 52 55 60 65 77 84 87 108 

All 1,222 75 1 50 55 59 63 73 85 94 99 107 a Refers to pregnant women who either refused to tell which trimester they were in or didn't know or data were missing. 

SD = Standard deviation. 

Source: U.S. EPA Analysis of NHANES 1999−2006 data. 

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Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Table 8-30. Fetal Weight (g) Percentiles Throughout Pregnancy 

Gestational 

Age (wk) 

Number of 

Women 10th 25th 50th 75th 90th 

8 6 –a – 6.1b – – 

9 7 – – 7.3b – – 

10 15 – – 8.1b – – 

11 13 – – 11.9b – – 

12 18 – 11 21 34 – 

13 43 – 23 35 55 – 

14 61 – 3,405 51 77 – 

15 63 – 51 77 108 – 

16 59 – 80 117 151 – 

17 36 – 125 166 212 – 

18 58 – 172 220 298 – 

19 31 – 217 283 394 – 

20 21 – 255 325 460 – 

21 43 280 330 410 570 860 

22 69 320 410 480 630 920 

23 71 370 460 550 690 990 

24 74 420 530 640 780 1,080 

25 48 490 630 740 890 1,180 

26 86 570 730 860 1,020 1,320 

27 76 660 840 990 1,160 1,470 

28 91 770 980 1,150 1,350 1,660 

29 88 890 1,100 1,310 1,530 1,890 

30 128 1,030 1,260 1,460 1,710 2,100 

31 113 1,180 1,410 1,630 1,880 2,290 

32 210 1,310 1,570 1,810 2,090 2,500 

33 242 1,480 1,720 2,010 2,280 2,690 

34 373 1,670 1,910 2,220 2,510 2,880 

35 492 1,870 2,130 2,430 2,730 3,090 

36 1,085 2,190 2,470 2,650 2,950 3,290 

37 1,798 2,310 2,580 2,870 3,160 3,470 

38 3,908 2,510 2,770 3,030 3,320 3,610 

39 5,413 2,680 2,910 3,170 3,470 3,750 

40 10,586 2,750 3,010 3,280 3,590 3,870 

41 3,399 2,800 3,070 3,360 3,680 3,980 

42 1,725 2,830 3,110 3,410 3,740 4,060 

43 507 2,840 3,110 3,420 3,780 4,100 

44 147 2,790 3,050 3,390 3,770 4,110 

a Data not available. b Median fetal weights may be overestimated. They were derived from only a small proportion of the fetuses 

delivered at these gestational weeks. 

Source: Brenner et al. (1976). 

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Table 8-31. Neonatal Weight by Gestational Age for Males and Females Combined 

Weight (g) Gestational Age 

(weeks) 5th 10th 25th 50th 75th 90th 95th 

25 450 490 564 660 772 889 968 

26 523 568 652 760 885 1,016 1,103 

27 609 660 754 875 1,015 1,160 1,257 

28 707 765 870 1,005 1,162 1,322 1,430 

29 820 884 1,003 1,153 1,327 1,504 1,623 

30 947 1,020 1,151 1,319 1,511 1,706 1,836 

31 1,090 1,171 1,317 1,502 1,713 1,928 2,070 

32 1,249 1,338 1,499 1,702 1,933 2,167 2,321 

33 1,422 1,519 1,696 1,918 2,169 2,421 2,587 

34 1,608 1,714 1,906 2,146 2,416 2,687 2,865 

35 1,804 1,919 2,125 2,383 2,671 2,959 3,148 

36 2,006 2,129 2,349 2,622 2,927 3,230 3,428 

37 2,210 2,340 2,572 2,859 3,177 3,493 3,698 

38 2,409 2,544 2,786 3,083 3,412 3,736 3,947 

39 2,595 2,735 2,984 3,288 3,622 3,952 4,164 

40 2,762 2,904 3,155 3,462 3,798 4,127 4,340 

41 2,900 3,042 3,293 3,597 3,930 4,254 4,462 

42 3,002 3,142 3,388 3,685 4,008 4,322 4,523 

43 3,061 3,195 3,432 3,717 4,026 4,324 4,515 

Source: Doubilet et al. (1997). 

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Chapter 8—Body Weight Studies 

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Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months. 

Source: Kuczmarski et al. (2002). 

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Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months. 

Source: Kuczmarski et al. (2002). 

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Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months. 

Source: Kuczmarski et al. (2002). 

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Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months. 

Source: Kuczmarski et al. (2002). 

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Chapter 8—Body Weight Studies 

Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years. 

Source: Kuczmarski et al. (2002). 

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Exposure Factors Handbook 

Chapter 8—Body Weight Studies 

Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years. 

Source: Kuczmarski et al. (2002). 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

9. INTAKE OF FRUITS AND 

VEGETABLES 

9.1. INTRODUCTION 

The American food supply is generally 

considered to be one of the safest in the world. 

Nevertheless, fruits and vegetables may become 

contaminated with toxic chemicals by several 

different pathways. Ambient pollutants from the air 

may be deposited on or absorbed by the plants or 

dissolved in rainfall or irrigation waters that contact 

the plants. Pollutants may also be absorbed through 

plant roots from contaminated soil and ground water. 

The addition of pesticides, soil additives, and 

fertilizers may also result in contamination of fruits 

and vegetables. To assess exposure through this 

pathway, information on fruit and vegetable ingestion 

rates is needed. 

A variety of terms may be used to define intake of 

fruits and vegetables (e.g., consumer-only intake, per 

capita intake, total fruit intake, total vegetable intake, 

as-consumed intake, dry-weight intake). These terms 

are defined below to assist the reader in interpreting 

and using the intake rates that are appropriate for the 

exposure scenario being assessed. 

Consumer-only intake is defined as the quantity 

of fruits and vegetables consumed by individuals 

during the survey period. These data are generated by 

averaging intake across only the individuals in the 

survey who consumed these food items. Per capita 

intake rates are generated by averaging 

consumer-only intakes over the entire population 

(including those individuals that reported no intake). 

In general, per capita intake rates are appropriate for 

use in exposure assessments for which average dose 

estimates are of interest because they represent both 

individuals who ate the foods during the survey 

period and individuals who may eat the food items at 

some time, but did not consume them during the 

survey period. Per capita intake, therefore, represents 

an average across the entire population of interest, 

but does so at the expense of underestimating 

consumption for the subset of the population that 

consumed the food in question. Total fruit intake 

refers to the sum of all fruits consumed in a day 

including canned, dried, frozen, and fresh fruits. 

Likewise, total vegetable intake refers to the sum of 

all vegetables consumed in a day including canned, 

dried, frozen, and fresh vegetables. 

Intake rates may be expressed on the basis of the 

as-consumed weight (e.g., cooked or prepared) or on 

the uncooked or unprepared weight. As-consumed 

intake rates are based on the weight of the food in the 

form that it is consumed and should be used in 

assessments where the basis for the contaminant 

concentrations in foods is also indexed to the 

as-consumed weight. Some of the food ingestion 

values provided in this chapter are expressed as 

as-consumed intake rates because this is the fashion 

in which data were reported by survey respondents. 

Others are provided as uncooked weights based on 

analyses of survey data that account for weight 

changes that occur during cooking. This is of 

importance because concentration data to be used in 

the dose equation are often measured in uncooked 

food samples. It should be recognized that cooking 

can either increase or decrease food weight. 

Similarly, cooking can increase the mass of 

contaminant in food (due to formation reactions, or 

absorption from cooking oils or water) or decrease 

the mass of contaminant in food (due to vaporization, 

fat loss, or leaching). The combined effects of 

changes in weight and changes in contaminant mass 

can result in either an increase or decrease in 

contaminant concentration in cooked food. Therefore, 

if the as-consumed ingestion rate and the uncooked 

concentration are used in the dose equation, dose may 

be under-estimated or over-estimated. It is important 

for the assessor to be aware of these issues and 

choose intake rate data that best match the 

concentration data that are being used. For more 

information on cooking losses and conversions 

necessary to account for such losses, refer to 

Chapter 13 of this handbook. 

Sometimes contaminant concentrations in food 

are reported on a dry-weight basis. When these data 

are used in an exposure assessment, it is 

recommended that dry-weight intake rates also be 

used. Dry-weight food concentrations and intake 

rates are based on the weight of the food consumed 

after the moisture content has been removed. For 

information on converting the intake rates presented 

in this chapter to dry-weight intake rates, refer to 

Section 9.4. 

The purpose of this chapter is to provide intake 

data for fruits and vegetables. The recommendations 

for fruit and vegetable ingestion rates are provided in 

the next section, along with a summary of the 

confidence ratings for these recommendations. The 

recommended values are based on the key study 

identified by U.S. Environmental Protection Agency 

(EPA) for this factor. Following the 

recommendations, the key study on fruit and 

vegetable ingestion is summarized. Relevant data on 

ingestion of fruits and vegetables are also provided. 

These data are presented to provide the reader with 

added perspective on the current state-of-knowledge 

pertaining to ingestion of fruits and vegetables. 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

9.2. RECOMMENDATIONS 

Table 9-1 presents a summary of the 

recommended values for per capita and 

consumer-only intake of fruits and vegetables. 

Table 9-2 provides confidence ratings for the fruit 

and vegetable intake recommendations. 

The U.S. EPA analysis of data from the 

2003−2006 National Health and Nutrition 

Examination Survey (NHANES) was used in 

selecting recommended intake rates for the general 

population. The U.S. EPA analysis was conducted 

using childhood age groups that differed slightly 

from U.S. EPA’s Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood Exposures 

to Environmental Contaminants (U.S. EPA, 2005). 

However, for the purposes of the recommendations 

presented here, childhood data were placed in the 

standardized age categories closest to those used in 

the analysis. 

The NHANES data on which the 

recommendations are based are short-term survey 

data and may not necessarily reflect the long-term 

distribution of average daily intake rates. However, 

since broad categories of food (i.e., total fruits and 

total vegetables), are eaten on a daily basis 

throughout the year with minimal seasonality, the 

short-term distribution may be a reasonable 

approximation of the long-term distribution, although 

it will display somewhat increased variability. This 

implies that the upper percentiles shown here may 

tend to overestimate the corresponding percentiles of 

the true long-term distribution. In general, the 

recommended values based on U.S. EPA’s analysis of 

NHANES data represent the i.e., uncooked weight of 

the edible portion of fruits and vegetables. 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-1. Recommended Values for Intake of Fruits and Vegetables, Edible Portion, Uncookeda 

Age Group 

(years) 

Per Capita Consumers Only Multiple 

Percentiles 

Mean 95 Source th Percentile Mean 95th Percentile 

g/kg-day g/kg-day g/kg-day g/kg-day 

Total Fruits 

Birth to 1 6.2 23.0b 10.1 25.8b 

See Table 9-3 

and Table 9-4 

U.S. EPA 

Analysis of 

NHANES 

2003−2006 

1 to <2 7.8 21.3b 8.1 21.4b 

2 to <3 7.8 21.3b 8.1 21.4b 

3 to <6 4.6 14.9 4.7 15.1 

6 to <11 2.3 8.7 2.5 9.2 

11 to <16 0.9 3.5 1.1 3.8 

16 to <21 0.9 3.5 1.1 3.8 

21 to <50 0.9 3.7 1.1 3.8 

≥50 1.4 4.4 1.5 4.6 

Total Vegetables 

Birth to 1 5.0 16.2b 6.8 18.1b 

See Table 9-3 

and Table 9-4 

U.S. EPA 

Analysis of 

NHANES 

2003−2006 

1 to <2 6.7 15.6b 6.7 15.6b 

2 to <3 6.7 15.6b 6.7 15.6b 

3 to <6 5.4 13.4 5.4 13.4 

6 to <11 3.7 10.4 3.7 10.4 

11 to <16 2.3 5.5 2.3 5.5 

16 to <21 2.3 5.5 2.3 5.5 

21 to <50 2.5 5.9 2.5 5.9 

≥50 2.6 6.1 2.6 6.1 

Individual Fruits and Vegetables—See Table 9-5 and Table 9-6 a Analysis was conducted using slightly different childhood age groups than those recommended in Guidance on 

Selecting Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 

2005). Data were placed in the standardized age categories closest to those used in the analysis. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and 

Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group 

Recommendations (NCHS, 1993). 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodology and data analysis were adequate. The 

survey sampled more than 16,000 individuals. However, 

sample sizes for some individual fruits and vegetables for some 

of the age groups are small. An analysis of primary data was 

conducted. 

No physical measurements were taken. The method relied on 

recent recall of fruits and vegetables eaten. 

High for total fruits and 

vegetables, low for some 

individual fruits and vegetables 

with small sample size 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key study was directly relevant to fruit and vegetable 

intake. 

The data were demographically representative of the U.S. 

population (based on stratified random sample). 

Data were collected between 2003 and 2006. 

Data were collected for two non-consecutive days. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The NHANES data are publicly available. 

The methodology used was clearly described; enough 

information was included to reproduce the results. 

NHANES follows a strict QA/QC procedure. The U.S. EPA 

analysis has only been reviewed internally, but the 

methodology used has been peer reviewed in an analysis of 

previous data. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were provided for total fruits and total 

vegetables. Means were provided for individual fruits and 

vegetables. 

Data collection was based on recall of consumption for a 2-day 

period; the accuracy of using these data to estimate long-term 

intake (especially at the upper percentiles) is uncertain. 

However, use of short-term data to estimate chronic ingestion 

can be assumed for broad categories of foods such as total 

fruits and total vegetables. Uncertainty is greater for 

individual fruits and vegetables. 

Medium to high for averages, 

low for long-term upper 

percentiles; low for individual 

fruits and vegetables 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The NCHS NHANES survey received a high level of peer 

review. The U.S. EPA analysis of these data has not been peer 

reviewed outside the Agency, but the methodology used has 

been peer reviewed in an analysis of previous data. 

There was one key study. 

Medium 

Overall Rating Medium to High confidence 

in the averages; Low for some 

individual fruits and vegetables 

with small sample size; Low 

confidence in the long-term 

upper percentiles 

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9.3.	 INTAKE STUDIES 

9.3.1.	 Key Fruits and Vegetables Intake Study 

9.3.1.1.	 U.S. EPA Analysis of Consumption Data 

From 2003−2006 National Health and 

Nutrition Examination Survey (NHANES) 

The key source of recent information on 

consumption rates of fruits and vegetables is the U.S. 

Centers for Disease Control and Prevention’s 

National Center for Health Statistics’ (NCHS) 

NHANES. Data from NHANES 2003−2006 have 

been used by the U.S. EPA, Office of Pesticide 

Programs (OPP) to generate per capita and consumeronly intake rates for both individual fruits and 

vegetables and total fruits and vegetables. 

NHANES is designed to assess the health and 

nutritional status of adults and children in the United 

States. In 1999, the survey became a continuous 

program that interviews a nationally representative 

sample of approximately 7,000 persons each year and 

examines a nationally representative sample of about 

5,000 persons each year, located in counties across 

the country, 15 of which are visited each year. Data 

are released on a 2-year basis, thus, for example, the 

2003 data are combined with the 2004 data to 

produce NHANES 2003−2004. 

The dietary interview component of NHANES is 

called What We Eat in America and is conducted by 

the U.S. Department of Agriculture (USDA) and the 

U.S. Department of Health and Human Services 

(DHHS). DHHS’ NCHS is responsible for the sample 

design and data collection, and USDA’s Food 

Surveys Research Group is responsible for the dietary 

data collection methodology, maintenance of the 

databases used to code and process the data, and data 

review and processing. Beginning in 2003, 

2 non-consecutive days of 24-hour intake data were 

collected. The first day is collected in-person, and the 

second day is collected by telephone 3 to 10 days 

later. These data are collected using USDA’s dietary 

data collection instrument, the Automated Multiple 

Pass Method. This method provides an efficient and 

accurate means of collecting intakes for large-scale 

national surveys. It is fully computerized and uses a 

5-step interview. Details can be found at USDA’s 

Agriculture Research Service 

(http://www.ars.usda.gov/ba/bhnrc/fsrg). 

For NHANES 2003−2004, there were 

12,761 persons selected; of these, 9,643 were 

considered respondents to the mobile examination 

center (MEC) examination and data collection. 

However, only 9,034 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,354 provided complete dietary intakes for Day 2. 

For NHANES 2005−2006, there were 12,862 persons 

selected; of these, 9,950 were considered respondents 

to the MEC examination and data collection. 

However, only 9,349 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,429 provided complete dietary intakes for Day 2. 

The 2003−2006 NHANES surveys are stratified, 

multistage probability samples of the civilian 

non-institutionalized U.S. population. The sampling 

frame was organized using 2000 U.S. population 

census estimates. NHANES oversamples low-income 

persons, adolescents 12 to 19 years, persons 60 years 

and older, African Americans, and Mexican 

Americans. Several sets of sampling weights are 

available for use with the intake data. By using 

appropriate weights, data for all four years of the 

surveys can be combined. Additional information on 

NHANES can be obtained at 

http://www.cdc.gov/nchs/nhanes.htm. 

In 2010, U.S. EPA, OPP used NHANES 

2003−2006 data to update the Food Commodity 

Intake Database (FCID) that was developed in earlier 

analyses of data from the USDA’s Continuing Survey 

of Food Intake among Individuals (CSFII) (U.S. 

EPA, 2000; USDA, 2000) (see Section 9.3.2.4), 

NHANES data on the foods people reported eating 

were converted to the quantities of agricultural 

commodities eaten. “Agricultural commodity” is a 

term used by U.S. EPA to mean plant (or animal) 

parts consumed by humans as food; when such items 

are raw or unprocessed, they are referred to as “raw 

agricultural commodities.” For example, an apple pie 

may contain the commodities apples, flour, fat, sugar, 

and spices. FCID contains approximately 558 unique 

commodity names and 8-digit codes. The FCID 

commodity names and codes were selected and 

defined by U.S. EPA and were based on the U.S. EPA 

Food Commodity Vocabulary 

(http://www.epa.gov/pesticides/foodfeed/). 

Intake rates were generated for a variety of food 

items/groups based on the agricultural commodities 

included in the FCID. These intake rates represent 

intake of all forms of the product (e.g., both home 

produced and commercially produced) for individuals 

who provided data for 2 days of the survey. Note that 

if the person reported consuming food for only one 

day, their 2-day average would be half the amount 

reported for the one day of consumption. Individuals 

who did not provide information on body weight or 

for whom identifying information was unavailable 

were excluded from the analysis. Two-day average 

intake rates were calculated for all individuals in the 

database for each of the food items/groups. These 

average daily intake rates were divided by each 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

individual’s reported body weight to generate intake 

rates in units of grams per kilogram of body weight 

per day (g/kg-day). The data were weighted 

according to the 4-year, 2-day sample weights 

provided in NHANES 2003−2006 to adjust the data 

for the sample population to reflect the national 

population. 

Summary statistics were generated on a 

consumer-only and on a per capita basis. Summary 

statistics, including: number of observations, 

percentage of the population consuming the fruits or 

vegetables being analyzed, mean intake rate, and 

standard error of the mean intake rate were calculated 

for total fruits, total vegetables, and selected 

individual fruits and vegetables. Individual fruits and 

vegetables were selected to be consistent with 

Chapter 13, which was based on having at least 

30 households reporting consumption for the 

particular fruit or vegetable. Percentiles of the intake 

rate distribution (i.e., 1st, 5th, 10th, 25th, 50th, 75th, 90th, 

95th, 99th, and the maximum value) were also 

provided for total fruits and total vegetables. Data 

were provided for the following age groups: birth to 

1 year, 1 to 2 years, 3 to 5 years, 6 to 12 years, 13 to 

19 years, 20 to 49 years, and ≥50 years. Data for 

females 13 to 49 years were also provided. Because 

these data were developed for use in U.S. EPA’s 

pesticide registration program, the childhood age 

groups used are slightly different than those 

recommended in U.S. EPA’s Guidance on Selecting 

Age Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. 

EPA, 2005). 

Table 9-3 presents per capita intake data for total 

fruits and total vegetables in g/kg-day; Table 9-4 

provides consumer-only intake data for total fruits 

and total vegetables in g/kg-day. Table 9-5 provides 

per capita intake data for individual fruits and 

vegetables in g/kg-day, and Table 9-6 provides 

consumer-only intake data for individual fruits and 

vegetables in g/kg-day. In general, these data 

represent intake of the edible portions of uncooked 

foods. 

The results are presented in units of g/kg-day. 

Thus, use of these data in calculating potential dose 

does not require the body-weight factor to be 

included in the denominator of the average daily dose 

(ADD) equation. It should be noted that converting 

these intake rates into units of g/day by multiplying 

by a single average body weight is inappropriate, 

because individual intake rates were indexed to the 

reported body weights of the survey respondents. 

Also, it should be noted that the distribution of 

average daily intake rates generated using short-term 

data (e.g., 2-day) does not necessarily reflect the 

long-term distribution of average daily intake rates. 

The distributions generated from short-term and 

long-term data will differ to the extent that each 

individual’s intake varies from day to day; the 

distributions will be similar to the extent that 

individuals’ intakes are constant from day to day. 

Day-to-day variation in intake among individuals will 

be high for fruits and vegetables that are highly 

seasonal and for fruits and vegetables that are eaten 

year-round, but that are not typically eaten every day. 

For these fruits and vegetables, the intake distribution 

generated from short-term data will not be a good 

reflection of the long-term distribution. On the other 

hand, for broad categories of foods (e.g., total fruits 

and total vegetables) that are eaten on a daily basis 

throughout the year, the short-term distribution may 

be a reasonable approximation of the true long-term 

distribution, although it will show somewhat more 

variability. In this chapter, distributions are provided 

only for broad categories of fruits and vegetables 

(i.e., total fruits and total vegetables). Because of the 

increased variability of the short-term distribution, 

the short-term upper percentiles shown here may 

overestimate the corresponding percentiles of the 

long-term distribution. For individual foods, only the 

mean, standard error, and percent consuming are 

provided. 

An advantage of using the U.S. EPA’s analysis of 

NHANES data is that it provides distributions of 

intake rates for various age groups of children and 

adults, normalized by body weight. The data set was 

designed to be representative of the U.S. population 

and includes four years of intake data combined. 

Another advantage is the currency of the data; the 

NHANES data are from 2003−2006. However, 

short-term dietary data may not accurately reflect 

long-term eating patterns and may under-represent 

infrequent consumers of a given food. This is 

particularly true for the tails (extremes) of the 

distribution of food intake. Because these are 2-day 

averages, consumption estimates at the upper end of 

the intake distribution may be underestimated if these 

consumption values are used to assess acute (i.e., 

short-term) exposures, also, the analysis was 

conducted using slightly different childhood age 

groups than those recommended in U.S. EPA’s 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

However, given the similarities in the age groups 

used, the data should provide suitable intake 

estimates for the age groups of interest. 

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9.3.2.	 Relevant Fruit and Vegetable Intake 

Studies 

9.3.2.1.	 U.S. Department of Agriculture (USDA) 

(1996a, b, 1993, 1980)—Food and Nutrient 

Intakes of Individuals in One Day in the 

United States 

USDA calculated mean intake rates for total fruits 

and total vegetables using data from the 1977−1978 

and 1987−1988 Nationwide Food Consumption 

Surveys (NFCS) (USDA, 1993, 1980) and CSFII data 

from 1994 and 1995 (USDA, 1996a, b). Table 9-7 

presents the mean per capita total intake rates for 

total fruits and total vegetables from the 1977−1978 

NFCS. Table 9-8 presents similar data from the 

1987−1988 NFCS and the 1994 and 1995 CSFII. 

Note that the age classifications used in these surveys 

were slightly different than those used in the 

1977−1978 NFCS. Table 9-7 and Table 9-8 include 

both per capita intake rates and intake rates for 

consumers only for various ages of individuals. 

Intake rates for consumers only were calculated by 

dividing the per capita consumption rate by the 

fraction of the population consuming vegetables or 

fruits in a day. 

The advantages of using these data are that they 

provide intake estimates for all fruits or all 

vegetables, combined. Again, these estimates are 

based on one-day dietary data, which may not reflect 

usual consumption patterns. These data are based on 

older surveys and may not be entirely representative 

of current eating patterns. 

9.3.2.2.	 U.S. Department of Agriculture (USDA) 

(1999b)—Food Consumption, Prices, and 

Expenditures, 1970−1997 

The USDA’s Economic Research Service 

calculates the amount of food available for human 

consumption in the United States on an annual basis 

(USDA, 1999b). Supply and utilization balance 

sheets are generated based on the flow of food items 

from production to end uses for the years 1970 to 

1997. Total available supply is estimated as the sum 

of production and imports (USDA, 1999b). The 

availability of food for human use commonly termed 

as “food disappearance” is determined by subtracting 

exported foods from the total available supply 

(USDA, 1999b). USDA (1999b) calculates the per 

capita food consumption by dividing the total food 

disappearance by the total U.S. population. USDA 

(1999b) estimated per capita consumption data for 

various fruit and vegetable products from 

1970−1997. Table 9-9 presents retail weight per 

capita data. These data have been derived from the 

annual per capita values in units of pounds per year, 

presented by USDA (1999b), by converting to units 

of g/day. 

An advantage of this study is that it provides per 

capita consumption rates for fruits and vegetables 

that are representative of long-term intake because 

disappearance data are generated annually. One of the 

limitations of this study is that disappearance data do 

not account for losses from the food supply from 

waste or spoilage. As a result, intake rates based on 

these data may overestimate daily consumption 

because they are based on the total quantity of 

marketable commodity utilized. Thus, these data 

represent bounding estimates of intake rates only. It 

should also be noted that per capita estimates based 

on food disappearance are not a direct measure of 

actual consumption or quantity ingested; instead, the 

data are used as indicators of changes in usage over 

time (USDA, 1999b). These data are based on older 

surveys and may not be entirely representative of 

current consumption patterns. 

9.3.2.3.	 U.S. Department of Agriculture (USDA) 

(1999a)—Food and Nutrient Intakes by 

Children 1994−1996, 1998, Table Set 17 

USDA (1999a) calculated national probability 

estimates of food and nutrient intake by children 

based on four years of the CSFII (1994−1996 and 

1998) for children age nine years and under, and on 

CSFII 1994−1996 only for children age 10 years and 

over. The CSFII was a series of surveys designed to 

measure the kinds and amounts of foods eaten by 

Americans. Intake data, based on 24-hour dietary 

recall, were collected through in-person interviews on 

two non-consecutive days. Section 9.3.2.4 provides 

additional information on these surveys. 

USDA (1999a) used sample weights to adjust for 

non-response, to match the sample to the U.S. 

population in terms of demographic characteristics, 

and to equalize intakes over the four quarters of the 

year and the seven days of the week. A total of 

503 breast-fed children were excluded from the 

estimates, but both consumers and non-consumers 

were included in the analysis. 

USDA (1999a) provided data on the mean per 

capita quantities (grams) of various food 

products/groups consumed per individual for one day, 

and the percent of individuals consuming those foods 

in one day of the survey. Table 9-10 through 

Table 9-13 present data on the mean quantities 

(grams) of fruits and vegetables consumed per 

individual for one day, and the percentage of survey 

individuals consuming fruits and vegetables on that 

survey day. Data on mean intakes or mean 

percentages are based on respondents’ Day-1 intakes. 

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The advantage of the USDA (1999a) study is that 

it uses the 1994−1996, 1998 CSFII data set, which 

includes four years of intake data, combined, and 

includes the supplemental data on children. These 

data are expected to be generally representative of the 

U.S. population, and they include data on a wide 

variety of fruits and vegetables. The data set is one of 

a series of USDA data sets that are publicly available. 

One limitation of this data set is that it is based on 

1 day, and short-term dietary data may not accurately 

reflect long-term eating patterns. Other limitations of 

this study are that it only provides mean values of 

food intake rates, consumption is not normalized by 

body weight, and presentation of results is not 

consistent with U.S. EPA’s recommended age groups. 

These data are based on older surveys and may not be 

entirely representative of current eating patterns. 

9.3.2.4.	 U.S. EPA Analysis of Continuing Survey of 

Food Intake Among Individuals (CSFII) 

1994−1996, 1998 Based on U.S. 

Department of Agriculture (USDA) (2000) 

and U.S. EPA (2000) 

U.S. EPA/OPP, in cooperation with USDA’s 

Agricultural Research Service, used data from the 

1994−1996, 1998 CSFII to develop the FCID (U.S. 

EPA, 2000; USDA, 2000), as described in 

Section 9.3.1.1. The CSFII 1994−1996 was 

conducted between January 1994 and January 1997 

with a target population of non-institutionalized 

individuals in all 50 states and Washington, DC. In 

each of the three survey years, data were collected for 

a nationally representative sample of individuals of 

all ages. The CSFII 1998 was conducted between 

December 1997 and December 1998 and surveyed 

children 9 years of age and younger. It used the same 

sample design as the CSFII 1994−1996 and was 

intended to be merged with CSFII 1994−1996 to 

increase the sample size for children. The merged 

surveys are designated as CSFII 1994−1996, 1998 

(USDA, 2000). Additional information on the CSFII 

can be obtained at http://www.ars.usda.gov/Services/ 

docs.htm?docid=14531. 

The CSFII 1994−1996, 1998 collected dietary 

intake data through in-person interviews on 

2 non-consecutive days. The data were based on 

24-hour recall. A total of 21,662 individuals provided 

data for the first day; of those individuals, 20,607 

provided data for a second day. The 2-day response 

rate for the 1994−1996 CSFII was approximately 

76%. The 2-day response rate for CSFII 1998 was 

82%. The CSFII 1994−1996, 1998 surveys were 

based on a complex multistage area probability 

sample design. The sampling frame was organized 

using 1990 U.S. population census estimates, and the 

stratification plan took into account geographic 

location, degree of urbanization, and socioeconomic 

characteristics. Several sets of sampling weights are 

available for use with the intake data. By using 

appropriate weights, data for all four years of the 

surveys can be combined. USDA recommends that 

all four years be combined in order to provide an 

adequate sample size for children. 

The fruits and vegetable items/groups selected for 

the U.S. EPA analysis included total fruits and 

vegetables, and various individual fruits and 

vegetables. CSFII data on the foods people reported 

eating were converted to the quantities of agricultural 

commodities eaten. Intake rates for these food 

items/groups were calculated, and summary statistics 

were generated on both a per capita and a 

consumer-only basis using the same general 

methodology as in the U.S. EPA analysis of 

2003−2006 NHANES data, as described in 

Section 9.3.1.1. Because these data were developed 

for use in U.S. EPA’s pesticide registration program, 

the childhood age groups used are slightly different 

than those recommended in U.S. EPA’s Guidance on 

Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005). 

Table 9-14 presents per capita intake data for total 

fruits and total vegetables in g/kg-day; Table 9-15 

provides consumer-only intake data for total fruits 

and total vegetables in g/kg-day. Table 9-16 provides 

per capita intake data for individual fruits and 

vegetables, and Table 9-17 provides consumer-only 

intake data for individual fruits and vegetables. In 

general, these data represent intake of the edible 

portions of uncooked foods. Table 9-18 through 

Table 9-22 present data for exposed/protected fruits 

and vegetables and root vegetables. These five tables 

were created using only CSFII 1994−1996. These 

data represent as-consumed intake rates. 

The results are presented in units of g/kg-day. 

Thus, use of these data in calculating potential dose 

does not require the body-weight factor to be 

included in the denominator of the ADD equation. 

The cautions concerning converting these intake rates 

into units of g/day by multiplying by a single average 

body weight and the discussion of the use of short 

term data in the NHANES description in 

Section 9.3.1.1, apply to the CSFII estimates as well. 

A strength of U.S. EPA’s analysis is that it provides 

distributions of intake rates for various age groups of 

children and adults, normalized by body weight. The 

analysis uses the 1994−1996, 1998 CSFII data set, 

which was designed to be representative of the U.S. 

population. Also, the data set includes four years of 

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intake data combined and is based on a 2-day survey 

period. However, as discussed above, short-term 

dietary data may not accurately reflect long-term 

eating patterns and may under-represent infrequent 

consumers of a given food. This is particularly true 

for the tails (extremes) of the distribution of food 

intake. Also, the analysis was conducted using 

slightly different childhood age groups than those 

recommended in U.S. EPA’s Guidance on Selecting 

Age Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. 

EPA, 2005). However, given the similarities in the 

age groups used, the data should provide suitable 

intake estimates for the age groups of interest. While 

the CSFII data are older than the NHANES data, they 

provide relevant information on consumption by 

season, region of the United States, and urbanization, 

breakdowns that are not available in the publicly 

released NHANES data. 

9.3.2.5.	 Smiciklas-Wright et al. (2002)—Foods 

Commonly Eaten in the United States: 

Quantities Consumed per Eating Occasion 

and in a Day, 1994−1996 

Using data gathered in the 1994−1996 USDA 

CSFII, Smiciklas-Wright et al. (2002) calculated 

distributions for the quantities of fruits and 

vegetables consumed per eating occasion by 

members of the U.S. population (i.e., serving sizes). 

The estimates of serving size were based on data 

obtained from 14,262 respondents, ages 2 years and 

above, who provided 2 days of dietary intake 

information. Only dietary intake data from users of 

the specified food were used in the analysis (i.e., 

consumer-only data). 

Table 9-23 presents serving size data for selected 

fruits and vegetables, and Table 9-24 presents serving 

size data by age group. These data are presented on 

an as-consumed basis (grams) and represent the 

quantity of fruits and vegetables consumed per eating 

occasion. These estimates may be useful for assessing 

acute exposures to contaminants in specific foods, or 

other assessments where the amount consumed per 

eating occasion is necessary. Only the mean and 

standard deviation serving size data and percent of 

the population consuming the food during the 2-day 

survey period are presented in this handbook. 

Percentiles of serving sizes of the foods consumed by 

these age groups of the U.S. population can be found 

in Smiciklas-Wright et al. (2002). 

The advantages of using these data are that they 

were derived from the USDA CSFII and are 

representative of the U.S. population. The analysis 

conducted by Smiciklas-Wright et al. (2002) 

accounted for individual foods consumed as 

ingredients of mixed foods. Mixed foods were 

disaggregated via recipe files so that the individual 

ingredients could be grouped together with similar 

foods that were reported separately. Thus, weights of 

foods consumed as ingredients were combined with 

weights of foods reported separately to provide a 

more thorough representation of consumption. 

However, it should be noted that since the recipes for 

the mixed foods consumed were not provided by the 

respondents, standard recipes were used. As a result, 

the estimates of quantity consumed for some food 

types are based on assumptions about the types and 

quantities of ingredients consumed as part of mixed 

foods. This study used data from the 1994 to 1996 

CSFII; data from the 1998 children’s supplement 

were not included. 

9.3.2.6.	 Vitolins et al. (2002)—Quality of Diets 

Consumed by Older Rural Adults 

Vitolins et al. (2002) conducted a survey to 

evaluate the dietary intake, by food groups, of older 

(>70 years) rural adults. The sample consisted of 

130 community dwelling residents from two rural 

counties in North Carolina. Data on dietary intake 

over the preceding year were obtained in face-to-face 

interviews conducted in participants’ homes, or in a 

few cases, a senior center. The food frequency 

questionnaire used in the survey was a modified 

version of the National Cancer Institute Health Habits 

and History Questionnaire; this modified version 

included an expanded food list containing a greater 

number of ethnic foods than the original food 

frequency form. Demographic and personal data 

collected included sex, ethnicity, age, education, 

denture use, marital status, chronic disease, and 

weight. Food items reported in the survey were 

separated into food groups similar to the USDA Food 

Guide Pyramid and the National Cancer Institute’s 

5 A Day for Better Health program. These groups are: 

(1) fruits and vegetables; (2) bread, cereal, rice, and 

pasta; (3) milk, yogurt, and cheese; (4) meat, fish, 

poultry, beans, and eggs; and (5) fats, oils, sweets, 

and snacks. Medians, ranges, frequencies, and 

percentages were used to summarize intake of each 

food group, broken down by demographic and health 

characteristics. To assess the univariate associations 

of these characteristics with consumption, Wilcoxon 

rank-sum tests were used. In addition, multivariate 

regression models were used to determine which 

demographic and health factors were jointly 

predictive of intake of each of the five food groups. 

Thirty-four percent of the survey participants 

were African American, 36% were European 

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American, and 30% were Native American. 

Sixty-two percent were female, 62% were not 

married at the time of the interview, and 65% had 

some high school education or were high school 

graduates. Almost all of the participants (95%) had 

one or more chronic diseases. Sixty percent of the 

respondents were between 70 and 79 years of age; the 

median age was 78 years old. Table 9-25 presents the 

median servings of fruits and vegetables broken 

down by demographic and health characteristic. The 

only variable predictive of fruit and vegetable intake 

was ethnicity (p = 0.02), with European Americans 

consuming significantly more than either African 

Americans or Native Americans. The multiple 

regression model indicated a statistically significant 

interaction between sex and ethnicity (p = 0.04) and a 

significant main effect for chronic disease (p = 0.04) 

for fruit and vegetable consumption. Among males, 

European Americans consumed significantly more 

fruits and vegetables than either African Americans 

or Native Americans. Men and women did not differ 

significantly in their fruit and vegetable consumption, 

except for African Americans, where women had a 

significantly greater intake (p = 0.01). 

An advantage of this study is that dietary 

information was collected on older individuals 

(>70 years of age). One limitation of the study, as 

noted by the study authors, is that the study did not 

collect information on the length of time the 

participants had been practicing the dietary behaviors 

reported in the survey. Also, the survey results are 

based on dietary recall; the questionnaire required 

participants to report the frequency of food 

consumption during the past year. The study authors 

noted that, currently, there are no dietary assessment 

tools that allow collecting comprehensive dietary 

data over years of food consumption. Another 

limitation of the study is that the small sample size 

used makes associations by sex and ethnicity 

difficult. 

9.3.2.7.	 Fox et al. (2004)—Feeding Infants and 

Toddlers Study: What Foods Are Infants 

and Toddlers Eating 

Fox et al. (2004) used data from the Feeding 

Infants and Toddlers Study (FITS) to assess food 

consumption patterns in infants and toddlers. The 

FITS was sponsored by Gerber Products Company 

and was conducted to obtain current information on 

food and nutrient intakes of children, ages 4 to 

24 months old, in the 50 states and the District of 

Columbia. The FITS is described in detail in 

Devaney et al. (2004). FITS was based on a random 

sample of 3,022 infants and toddlers for which 

dietary intake data were collected by telephone from 

their parents or caregivers between March and 

July 2002. An initial recruitment and household 

interview was conducted, followed by an interview to 

obtain information on intake based on 24-hour recall. 

The interview also addressed growth, development, 

and feeding patterns. A second dietary recall 

interview was conducted for a subset of 

703 randomly selected respondents. The study 

over-sampled children in the 4 to 6 and 9 to 

11 months age groups; sample weights were adjusted 

for non-response, over-sampling, and under-coverage 

of some population groups. The response rate for the 

FITS was 73% for the recruitment interview. Of the 

recruited households, there was a response rate of 

94% for the dietary recall interviews (Devaney et al., 

2004). Table 9-26 shows the characteristics of the 

FITS study population. 

Fox et al. (2004) analyzed the first set of 24-hour 

recall data collected from all study participants. For 

this analysis, children were grouped into six age 

categories: 4 to 6 months, 7 to 8 months, 9 to 

11 months, 12 to 14 months, 15 to 18 months, and 19 

to 24 months. Table 9-27 provides the percentage of 

infants and toddlers consuming different types of 

vegetables at least once in a day. The percentages of 

children eating any type of vegetable ranged from 

39.9% for 4 to 6 month olds to 81.6% for 19 to 24 

month olds. Table 9-28 provides the top 

five vegetables consumed by age group. Some of the 

highest percentages ranged from baby food carrots 

(9.6%) in the 4 to 6 month old group to French fries 

(25.5%) in the 19 to 24 month old group. Table 9-29 

provides the percentage of children consuming 

different types of fruit at least once per day. The 

percentages of children eating any type of fruit 

ranged from 41.9% to 4 to 6 month olds to 77.2% for 

12 to 14 month olds. Table 9-30 provides information 

on the top five fruits eaten by infants and toddlers at 

least once per day. The highest percentages were for 

bananas among infants 9 to 24 months, and baby 

food applesauce among infants 4 to 8 months old. 

The advantages of this study are that the study 

population represented the U.S. population and the 

sample size was large. One limitation of the analysis 

done by Fox et al. (2004) was that only frequency 

data were provided; no information on actual intake 

rates was included. In addition, Devaney et al. (2004) 

noted several limitations associated with the FITS 

data. For the FITS, a commercial list of infants and 

toddlers was used to obtain the sample used in the 

study. Since many of the households could not be 

located and did not have children in the target 

population, a lower response rate than would have 

occurred in a true national sample was obtained 

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(Devaney et al., 2004). In addition, the sample was 

likely from a higher socioeconomic status when 

compared with all U.S. infants in this age group (4 to 

24 months old), and the use of a telephone survey 

may have omitted lower-income households without 

telephones (Devaney et al., 2004). 

9.3.2.8.	 Ponza et al. (2004)—Nutrient Food Intakes 

and Food Choices of Infants and Toddlers 

Participating in Women, Infants, and 

Children (WIC) 

Ponza et al. (2004) conducted a study using 

selected data from the FITS to assess feeding 

patterns, food choices, and nutrient intake of infants 

and toddlers participating in the Special 

Supplemental Nutrition Program for Women, Infants, 

and Children (WIC). Ponza et al. (2004) evaluated 

FITS data for the following age groups: 4 to 

6 months (N = 862), 7 to 11 months (N = 1,159), and 

12 to 24 months (N = 996). Table 9-31 shows the 

total sample size described by WIC participants and 

non-participants. 

The foods consumed were analyzed by tabulating 

the percentage of infants who consumed specific 

foods/food groups per day (Ponza et al., 2004). 

Weighted data were used in all of the analyses used in 

the study (Ponza et al., 2004). Table 9-31 presents the 

demographic data for WIC participants and 

non-participants. Table 9-32 provides information on 

the food choices for the infants and toddlers studied. 

There was little difference in vegetable choices 

among WIC participants and non-participants (see 

Table 9-32). However, there were some differences 

for fruits. 

An advantage of this study is that it had a 

relatively large sample size and was representative of 

the U.S. general population of infants and children. A 

limitation of the study is that intake values for foods 

were not provided. Other limitations are those 

associated with the FITS data, as described 

previously in Section 9.3.2.7. 

9.3.2.9.	 Fox et al. (2006)—Average Portion of 

Foods Commonly Eaten by Infants and 

Toddlers in the United States 

Fox et al. (2006) estimated average portion sizes 

consumed per eating occasion by children 4 to 

24 months of age who participated in the FITS. 

Section 9.3.2.7 describes the FITS, which is a 

cross-sectional study designed to collect and analyze 

data on feeding practices, food consumption, and 

usual nutrient intake of U.S. infants and toddlers. It 

included a stratified random sample of 3,022 children 

between 4 and 24 months of age. 

Using the 24-hour recall data, Fox et al. (2006) 

derived average portion sizes for major food groups, 

including fruits and vegetables. Average portion sizes 

for select individual foods within these major groups 

were also estimated. For this analysis, children were 

grouped into six age categories: 4 to 5 months, 6 to 

8 months, 9 to 11 months, 12 to 14 months, 15 to 

18 months, and 19 to 24 months. Table 9-33 and 

Table 9-34 present the average portion sizes for fruits 

and vegetables for infants and toddlers, respectively. 

An advantage of this study is that it had a 

relatively large sample size and was representative of 

the U.S. general population of infants and children. 

Limitations are those associated with the FITS data, 

as described previously in Section 9.3.2.7. 

9.3.2.10.Mennella et al. (2006)—Feeding Infants 

and Toddlers Study: The Types of Foods 

Fed to Hispanic Infants and Toddlers 

Mennella et al. (2006) investigated the types of 

food and beverages consumed by Hispanic infants 

and toddlers in comparison to the non-Hispanic 

infants and toddlers in the United States. The FITS 

2002 data for children between 4 and 24 months of 

age were used for the study. The data represent a 

random sample of 371 Hispanic and 

2,367 non-Hispanic infants and toddlers (Mennella et 

al., 2006). Menella et al. (2006) grouped the infants 

as follows: 4 to 5 months (N = 84 Hispanic; 

538 non-Hispanic), 6 to 11 months (N = 163 

Hispanic; 1,228 non-Hispanic), and 12 to 24 months 

(N = 124 Hispanic; 871 non-Hispanic) of age. 

Table 9-35 provides the percentages of Hispanic 

and non-Hispanic infants and toddlers consuming 

fruits and vegetables. In most instances, the 

percentages consuming the different types of fruits 

and vegetables were similar. However, 4-to-5-monthold Hispanic infants were more likely to eat fruits 

than non-Hispanic infants in this age group. 

Table 9-36 provides the top five fruits and vegetables 

consumed and the percentage of children consuming 

these foods at least once in a day. Apples and bananas 

were the foods with the highest percent consuming 

for both the Hispanic and non-Hispanic study groups. 

Potatoes and carrots were the vegetables with the 

highest percentage of infants and toddlers consuming 

in both study groups. 

The advantage of the study is that it provides 

information on food preferences for Hispanic and 

non-Hispanic infants and toddlers. A limitation is that 

the study did not provide food intake data, but 

provided frequency-of-use data instead. Other 

limitations are those noted previously in 

Section 9.3.2.7 for the FITS data. 

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Chapter 9—Intake of Fruits and Vegetables 

9.4.	 CONVERSION BETWEEN WET- AND 

DRY-WEIGHT INTAKE RATES 

The intake data presented in this chapter are 

reported in units of wet weight (i.e., as-consumed or 

edible portion uncooked fruits and vegetables 

consumed per day or per eating occasion). However, 

data on the concentration of contaminants in fruits 

and vegetables may be reported in units of either wet 

or dry weight (e.g., mg contaminant per gram dry 

weight of fruits and vegetables). It is essential that 

exposure assessors be aware of this difference so that 

they may ensure consistency between the units used 

for intake rates and those used for concentration data 

(i.e., if the contaminant concentration is measured in 

dry weight of fruits and vegetables, then the 

dry-weight units should be used for their intake 

values). 

If necessary, wet-weight (e.g., as-consumed) 

intake rates may be converted to dry-weight intake 

rates using the moisture content percentages 

presented in Table 9-37 (USDA, 2007) and the 

following equation: 

IRdw = IRww 100 −W  (Eqn. 9-1) 

 100 

where: 

IRdw = dry-weight intake rate, 

IRww = wet-weight intake rate, and 

W = percent water content. 

Alternatively, dry-weight residue levels in fruits and 

vegetables may be converted to wet-weight residue 

levels for use with wet-weight (e.g., as-consumed) 

intake rates as follows: 

Cww = Cdw 100 −W  (Eqn. 9-2) 

 100 

where: 

Cww = wet-weight concentration, 

Cdw = dry-weight concentration, and 

W = percent water content. 

Table 9-37 presents moisture data for selected fruits 

and vegetables taken from USDA (2007). 

9.5.	 REFERENCES FOR CHAPTER 9 

Devaney, B; Kalb, L; Briefel, R; Zavitsky-Novak, T; 

Clusen, N; Ziegler, P. (2004). Feeding 

infants and toddlers study: overview of the 

study design. J Am Diet Assoc 104: s8-13. 

http://dx.doi.org/10.1016/j.jada.2003.10.023. 

Fox, MK; Pac, S; Devaney, B; Jankowski, L. (2004). 

Feeding infants and toddlers study: What 

foods are infants and toddlers eating? J Am 

Diet Assoc 104: s22-s30. 

http://dx.doi.org/10.1016/j.jada.2003.10.026. 

Fox, MK; Reidy, K; Karwe, V; Ziegler, P. (2006). 

Average portions of foods commonly eaten 

by infants and toddlers in the United States. 

J Am Diet Assoc 106: S66-S76. 

http://dx.doi.org/10.1016/j.jada.2005.09.042. 

Mennella, JA; Ziegler, P; Briefel, R; Novak, T. 

(2006). Feeding Infants and Toddlers Study: 

the types of foods fed to Hispanic infants 

and toddlers. J Am Diet Assoc 106: S96­

106. 

http://dx.doi.org/10.1016/j.jada.2005.09.038. 

NCHS (National Center for Health Statistics). (1993). 

Joint policy on variance estimation and 

statistical reporting standards on NHANES 

III and CSFII reports: HNIS/NCHS Analytic 

Working Group recommendations. 

Riverdale, MD: Human Nutrition 

Information Service (HNIS)/Analytic 

Working Group. Agricultural Research 

Service, Survey Systems/Food Consumption 

Laboratory. 

Ponza, M; Devaney, B; Ziegler, P; Reidy, K; 

Squatrito, C. (2004). Nutrient intakes and 

food choices of infants and toddlers 

participating in WIC. J Am Diet Assoc 104: 

s71-s79. 

http://dx.doi.org/10.1016/j.jada.2003.10.018. 

Smiciklas-Wright, H; Mitchell, DC; Mickle, SJ; 

Cook, AJ; Goldman, JD. (2002). Foods 

commonly eaten in the United States: 

Quantities consumed per eating occasion 

and in a day, 1994−96 [pre-publication 

version]. (NFS Report No. 96-5). Beltsville, 

MD: U.S. Department of Agriculture. 

http://www.ars.usda.gov/sp2userfiles/place/1 

2355000/pdf/portion.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000). Food commodity intake database 

[Database]. 

Page Exposure Factors Handbook 

9-12 September 2011 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

 

 

 

 

 

 

 

 

 

 

 

 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum. 

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

USDA (U.S. Department of Agriculture). (1980). 

Food and nutrient intakes of individuals in 1 

day in the United States, Spring 1977. 

Nationwide Food Consumption Survey 

1977–78: Preliminary report no. 2. 

Washington, DC. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/7778/nfcs7778_prelim_2.pdf 

. 

USDA (U.S. Department of Agriculture). (1993). 

Food and nutrient intakes by individuals in 

the United States, 1 day, 1987–88. 

Nationwide Food Consumption Survey 

1987-88: Report no. 87-I-1. (87-I-1). 

Washington, DC. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/8788/nfcs8788_rep_87-i1.pdf. 

USDA (U.S. Department of Agriculture). (1996a). 

Data tables: Results from USDA's 1994 

continuing survey of food intakes by 

individuals and 1994 diet and health 

knowledge survey. Riverdale, MD. 

USDA (U.S. Department of Agriculture). (1996b). 

Data tables: results from USDA’s 1995 

Continuing survey of food intakes by 

individuals and 1995 diet and health 

knowledge survey. Riverdale, MD. 

USDA (U.S. Department of Agriculture). (1999a). 

Food and nutrient intakes by children 1994­

96, 1998: table set 17. Beltsville, MD. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/scs_all.pdf. 

USDA (U.S. Department of Agriculture). (1999b). 

Food consumption prices and expenditures 

(1970−1997). Statistical Bulletin, No. 965. 

Washington, DC: Economic Research 

Service. 

USDA (U.S. Department of Agriculture). (2000). 

1994-1996, 1998 continuing survey of food 

intakes by individuals (CSFII). Beltsville, 

MD: Agricultural Research Service, 

Beltsville Human Nutrition Research Center. 

USDA (U.S. Department of Agriculture). (2007). 

USDA nutrient database for standard 

reference, release 20. Riverdale, MD. 

http://www.ars.usda.gov/main/site_main.htm 

?modecode=12-35-45-00. 

Vitolins, MZ; Quandt, SA; Bell, RA; Arcury, TA; 

Case, LD. (2002). Quality of diets consumed 

by older rural adults. J Rural Health 18: 49­

56. 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-3. Per Capita Intake of Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

Percent 

Consuming 

Percentiles 

Population Group N Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Fruits 

Whole Population 16,783 85 1.6 0.05 0.0 0.0 0.0 0.0 0.7 2.0 4.0 6.1 14.6 65.6* 

Age Group 

Birth to 1 year 865 61 6.2 0.46 0.0* 0.0* 0.0 0.0 2.2 10.2 17.6 23.0* 35.9* 56.5* 

1 to 2 years 1,052 97 7.8 0.42 0.0* 0.0* 0.2 2.2 5.6 11.7 16.8 21.3* 39.3* 65.6* 

3 to 5 years 978 97 4.6 0.25 0.0* 0.0 0.0 0.9 3.2 6.6 11.1 14.9 20.0* 32.1* 

6 to 12 years 2,256 93 2.3 0.12 0.0* 0.0 0.0 0.1 1.3 3.2 6.4 8.7 13.8* 24.4* 

13 to 19 years 3,450 80 0.9 0.04 0.0 0.0 0.0 0.0 0.2 1.3 2.6 3.5 6.1 16.7* 

20 to 49 years 4,289 81 0.9 0.04 0.0 0.0 0.0 0.0 0.3 1.3 2.6 3.7 6.2 15.9* 

Female 13 to 49 years 4,103 85 1.0 0.05 0.0 0.0 0.0 0.0 0.4 1.4 2.8 3.7 6.4 16.7* 

50 years and older 3,893 89 1.4 0.05 0.0 0.0 0.0 0.1 0.9 2.0 3.4 4.4 6.5 17.3* 

Race 

Mexican American 4,450 87 2.3 0.11 0.0 0.0 0.0 0.1 1.1 2.7 5.8 9.6 18.3 39.2* 

Non-Hispanic Black 4,265 82 1.2 0.06 0.0 0.0 0.0 0.0 0.2 1.3 3.2 5.0 12.4 39.1* 

Non-Hispanic White 6,757 85 1.5 0.05 0.0 0.0 0.0 0.0 0.7 1.9 3.8 5.5 14.0 65.6* 

Other Hispanic 562 87 2.1 0.20 0.0* 0.0 0.0 0.0 1.0 2.8 4.9 7.1 19.5* 32.7* 

Other Race—Including Multiple 749 89 2.0 0.13 0.0* 0.0 0.0 0.1 0.9 2.6 5.2 8.6 15.3* 42.1* 

Vegetables 

Whole Population 16,783 100 2.9 0.04 0.0 0.4 0.7 1.3 2.3 3.7 5.7 7.5 13.2 36.1* 

Age Group 

Birth to 1 year 865 73 5.0 0.28 0.0* 00* 0.0 0.0 3.3 8.7 12.9 16.2* 22.7* 36.1* 

1 to 2 years 1,052 100 6.7 0.26 0.0* 1.0* 1.6 3.0 5.7 8.9 13.3 15.6* 28.7* 32.8* 

3 to 5 years 978 100 5.4 0.25 0.1* 0.6 1.5 2.3 4.2 7.2 10.6 13.4 21.4* 30.3* 

6 to 12 years 2,256 100 3.7 0.18 0.1* 0.5 0.9 1.5 2.8 4.8 7.6 10.4 14.8* 23.1* 

13 to 19 years 3,450 100 2.3 0.05 0.0 0.3 0.5 1.1 1.8 3.0 4.3 5.5 8.9 20.0* 

20 to 49 years 4,289 100 2.5 0.06 0.1 0.4 0.7 1.3 2.2 3.3 4.9 5.9 8.6 18.3* 

Female 13 to 49 years 4,103 100 2.5 0.08 0.1 0.4 0.6 1.2 2.0 3.3 4.7 5.9 8.9 18.3* 

50 years and older 3,893 100 2.6 0.05 0.0 0.4 0.7 1.3 2.2 3.4 4.9 6.1 9.1 22.6* 

Race 

Mexican American 4,450 99 3.2 0.06 0.0 0.5 0.8 1.5 2.5 4.1 6.4 8.6 13.5 36.1* 

Non-Hispanic Black 4,265 100 2.4 0.05 0.0 0.2 0.5 0.9 1.7 3.0 4.7 6.5 11.5 30.3* 

Non-Hispanic White 6,757 100 2.9 0.05 0.0 0.4 0.7 1.4 2.3 3.7 5.6 7.2 12.8 29.5* 

Other Hispanic 562 99 3.1 0.16 0.0* 0.2 0.7 1.2 2.2 3.8 6.3 9.4 16.3* 26.2* 

Other Race—Including Multiple 749 100 3.4 0.20 0.1* 0.4 0.7 1.5 2.7 4.2 6.8 9.3 15.6* 32.8* 

N = Sample size. 

SE = Standard error. 

Max = Maximum value. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III 

and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Source: U.S. EPA analysis of the 2003−2006 NHANES. 

Page Exposure Factors Handbook 9-14 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-4. Consumer-Only Intake of Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

Percentiles 

Population Group N Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Fruits 

Whole Population 14,362 1.9 0.05 0.0 0.0 0.0 0.2 1.0 2.3 4.4 6.7 15.2 65.6* 

Age Group 

Birth to 1 year 536 10.1 0.59 0.0* 0.3* *0.8 3.6 8.1 14.7 21.2* 25.8* 43.7* 56.5* 

1 to 2 years 1,002 8.1 0.43 0.0* 0.1* 0.5 2.6 6.2 11.8 16.8 21.4* 39.3* 65.6* 

3 to 5 years 924 4.7 0.24 0.0* 0.0 0.1 1.1 3.5 6.7 11.3 15.1 20.0* 32.1* 

6 to 12 years 2,077 2.5 0.12 0.0* 0.0 0.0 0.2 1.6 3.4 6.6 9.2 14.5* 24.4* 

13 to 19 years 2,830 1.1 0.04 0.0 0.0 0.0 0.0 0.7 1.6 2.9 3.8 6.2 16.7* 

20 to 49 years 3,529 1.1 0.05 0.0 0.0 0.0 0.1 0.6 1.6 2.9 3.8 6.7 15.9* 

Female 13 to 49 years 3,508 1.2 0.06 0.0 0.0 0.0 0.1 0.7 1.7 3.1 4.1 6.5 16.7* 

50 years and older 3,464 1.5 0.05 0.0 0.0 0.0 0.4 1.1 2.2 3.6 4.6 6.7 17.3* 

Race 

Mexican American 3,835 2.6 0.12 0.0 0.0 0.0 0.4 1.4 3.0 6.3 10.6 19.3 39.2* 

Non-Hispanic Black 3,595 1.4 0.07 0.0 0.0 0.0 0.0 0.6 1.7 3.8 5.7 12.9 39.1* 

Non-Hispanic White 5,795 1.8 0.05 0.0 0.0 0.0 0.2 1.0 2.2 4.1 6.1 14.5 65.6* 

Other Hispanic 478 2.5 0.23 0.0* 0.0 0.0 0.3 1.5 3.0 5.0 8.6 19.5* 32.7* 

Other Race—Including 

Multiple 659 2.3 0.16 0.0* 0.0 0.0 0.2 1.1 2.8 6.0 9.4 15.3* 42.1* 

Vegetables 

Whole Population 16,531 2.9 0.04 0.0 0.4 0.7 1.3 2.3 3.7 5.7 7.5 13.2 36.1* 

Age Group 

Birth to 1 year 623 6.8 0.33 0.0* 0.1* 0.4* 2.6 5.5 10.1 14.5* 18.1* 22.7* 36.1* 

1 to 2 years 1,048 6.7 0.26 0.0* 1.0* 1.7 3.0 5.7 8.9 13.3 15.6* 28.7* 32.8* 

3 to 5 years 977 5.4 0.25 0.1* 0.6 1.5 2.3 4.2 7.2 10.6 13.4 21.4* 30.3* 

6 to 12 years 2,256 3.7 0.18 0.1* 0.5 0.9 1.5 2.8 4.8 7.6 10.4 14.8* 23.1* 

13 to 19 years 3,447 2.3 0.05 0.0 0.3 0.5 1.1 1.8 3.0 4.3 5.5 8.9 20.0* 

20 to 49 years 4,288 2.5 0.06 0.1 0.4 0.7 1.3 2.2 3.3 4.9 5.9 8.6 18.3* 

Female 13 to 49 years 4,102 2.5 0.08 0.1 0.4 0.6 1.2 2.0 3.3 4.7 5.9 8.9 18.3* 

50 years and older 3,892 2.6 0.05 0.0 0.4 0.7 1.3 2.2 3.4 4.9 6.1 9.1 22.6* 

Race 

Mexican American 4,341 3.3 0.06 0.1 0.5 0.8 1.5 2.5 4.1 6.4 8.6 13.5 36.1* 

Non-Hispanic Black 4,228 2.4 0.05 0.0 0.3 0.5 0.9 1.7 3.0 4.7 6.5 11.5 30.3* 

Non-Hispanic White 6,683 2.9 0.05 0.1 0.4 0.7 1.4 2.3 3.7 5.6 7.2 12.8 29.5* 

Other Hispanic 544 3.1 0.16 0.1* 0.3 0.7 1.3 2.2 3.8 6.4 9.4 16.3* 26.2* 

Other Race—Including 

Multiple 735 3.4 0.21 0.2* 0.4 0.7 1.5 2.7 4.3 6.9 9.3 15.6* 32.8* 

N = Sample size. 

SE = Standard error. 

Max = Maximum value. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III and CSFII 

Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Source: U.S. EPA analysis of the 2003−2006 NHANES. 

Exposure Factors Handbook PageSeptember 2011 9-15
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Apples Asparagus Bananas Beans 

Whole Population 16,783 

Age Group 

33 0.41 0.01 2 0.01 0.00 55 0.37 0.01 45 0.24 0.01 

Birth to 1 year 865 39 2.23 0.24 1 0.00 0.00 46 1.83 0.19 30 0.54 0.06 

1 to 2 years 1,052 50 1.96 0.14 2 0.03 0.01 77 2.35 0.26 49 0.69 0.06 

3 to 5 years 978 42 1.21 0.10 1 0.01 0.01 73 1.00 0.09 43 0.61 0.07 

6 to 12 years 2,256 39 0.74 0.06 1 0.01 0.00 68 0.42 0.04 37 0.30 0.03 

13 to 19 years 3,450 27 0.27 0.02 1 0.00 0.00 50 0.15 0.01 31 0.13 0.01 

20 to 49 years 4,289 28 0.21 0.02 2 0.01 0.00 48 0.20 0.01 46 0.19 0.01 

Female 13 to 49 years 4,103 29 0.23 0.02 2 0.01 0.00 50 0.20 0.01 45 0.17 0.01 

50 years and older 3,893 

Race 

38 0.28 0.02 3 0.02 0.00 58 0.33 0.02 51 0.22 0.01 

Mexican American 4,450 33 0.58 0.03 1 0.00 0.00 56 0.56 0.04 59 0.32 0.01 

Non-Hispanic Black 4,265 27 0.31 0.02 0 0.00 0.00 55 0.25 0.02 43 0.25 0.01 

Non-Hispanic White 6,757 35 0.40 0.02 3 0.02 0.00 54 0.36 0.02 43 0.22 0.01 

Other Hispanic 562 32 0.47 0.06 1 0.00 0.00 55 0.53 0.06 58 0.25 0.03 

Other Race—Including Multiple 749 32 0.47 0.04 3 0.01 0.00 58 0.43 0.04 50 0.30 0.04 

Page Exposure Factors Handbook 9-16 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Beets Berries and Small Fruit Broccoli Bulb Vegetables 

Whole Population 16,783 

Age Group 

3 0.01 0.00 67 0.30 0.01 15 0.10 0.01 97 0.18 0.00 

Birth to 1 year 865 5 0.00 0.00 19 0.24 0.09 6 0.07 0.02 39 0.07 0.01 

1 to 2 years 1,052 1 0.00 0.00 83 1.46 0.14 16 0.30 0.06 94 0.28 0.02 

3 to 5 years 978 1 0.01 0.01 84 0.97 0.11 12 0.19 0.04 96 0.28 0.02 

6 to 12 years 2,256 0 0.00 0.00 80 0.46 0.04 11 0.10 0.02 98 0.21 0.02 

13 to 19 years 3,450 1 0.00 0.00 64 0.19 0.01 9 0.05 0.01 98 0.15 0.01 

20 to 49 years 4,289 2 0.01 0.00 62 0.17 0.01 16 0.09 0.01 98 0.19 0.01 

Female 13 to 49 years 4,103 2 0.01 0.00 67 0.20 0.01 17 0.09 0.01 97 0.16 0.01 

50 years and older 3,893 

Race 

5 0.01 0.00 71 0.28 0.02 16 0.09 0.01 97 0.16 0.00 

Mexican American 4,450 1 0.00 0.00 59 0.23 0.02 12 0.07 0.01 96 0.27 0.01 

Non-Hispanic Black 4,265 1 0.00 0.00 64 0.18 0.01 12 0.07 0.01 96 0.13 0.01 

Non-Hispanic White 6,757 4 0.01 0.00 69 0.33 0.02 15 0.10 0.01 97 0.17 0.00 

Other Hispanic 562 3 0.00 0.00 59 0.30 0.05 16 0.13 0.04 93 0.23 0.01 

Other Race—Including Multiple 749 1 0.00 0.00 66 0.38 0.06 19 0.13 0.03 97 0.25 0.02 

Exposure Factors Handbook PageSeptember 2011 9-17
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Cabbage Carrots Citrus Fruits Corn 

Whole Population 16,783 

Age Group 

13 0.05 0.00 47 0.14 0.00 20 0.16 0.01 96 0.43 0.01 

Birth to 1 year 865 1 0.01 0.01 15 0.17 0.05 2 0.05 0.02 56 0.62 0.10 

1 to 2 years 1,052 7 0.05 0.02 50 0.47 0.04 25 0.65 0.08 97 1.13 0.05 

3 to 5 years 978 5 0.04 0.01 45 0.32 0.05 18 0.46 0.06 100 1.26 0.07 

6 to 12 years 2,256 7 0.04 0.01 43 0.21 0.03 15 0.21 0.02 99 0.88 0.03 

13 to 19 years 3,450 6 0.02 0.00 35 0.08 0.01 13 0.08 0.01 96 0.37 0.01 

20 to 49 years 4,289 13 0.05 0.01 46 0.11 0.01 20 0.11 0.01 96 0.32 0.01 

Female 13 to 49 years 4,103 12 0.05 0.01 46 0.11 0.01 21 0.11 0.01 96 0.31 0.01 

50 years and older 3,893 

Race 

18 0.08 0.00 54 0.12 0.01 25 0.14 0.01 96 0.27 0.01 

Mexican American 4,450 10 0.03 0.00 45 0.15 0.01 27 0.37 0.03 96 0.78 0.03 

Non-Hispanic Black 4,265 12 0.06 0.01 36 0.08 0.01 16 0.17 0.03 96 0.46 0.02 

Non-Hispanic White 6,757 13 0.05 0.00 49 0.14 0.01 20 0.12 0.01 97 0.37 0.01 

Other Hispanic 562 9 0.03 0.01 49 0.17 0.02 23 0.26 0.03 94 0.45 0.05 

Other Race—Including Multiple 749 17 0.12 0.02 52 0.23 0.02 21 0.20 0.05 91 0.41 0.03 

Page Exposure Factors Handbook 9-18 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Cucumbers Cucurbits Fruiting Vegetables Leafy Vegetables 

Whole Population 16,783 

Age Group 

40 0.09 0.00 48 0.34 0.03 95 0.80 0.02 92 0.54 0.01 

Birth to 1 year 865 3 0.02 0.01 20 0.64 0.09 31 0.30 0.05 40 0.22 0.04 

1 to 2 years 1,052 24 0.14 0.02 37 1.01 0.18 93 1.45 0.07 82 0.71 0.07 

3 to 5 years 978 26 0.19 0.03 36 0.66 0.08 95 1.53 0.08 87 0.61 0.06 

6 to 12 years 2,256 30 0.11 0.01 38 0.56 0.11 97 1.05 0.05 90 0.43 0.02 

13 to 19 years 3,450 34 0.06 0.01 40 0.20 0.02 96 0.75 0.03 89 0.35 0.01 

20 to 49 years 4,289 45 0.09 0.01 52 0.26 0.03 97 0.76 0.02 94 0.55 0.02 

Female 13 to 49 years 4,103 44 0.10 0.01 51 0.30 0.04 96 0.70 0.03 93 0.58 0.03 

50 years and older 3,893 

Race 

43 0.08 0.01 54 0.31 0.02 95 0.66 0.03 93 0.60 0.02 

Mexican American 4,450 30 0.07 0.01 42 0.27 0.02 96 1.13 0.03 90 0.40 0.02 

Non-Hispanic Black 4,265 37 0.06 0.01 42 0.18 0.02 94 0.62 0.03 90 0.46 0.02 

Non-Hispanic White 6,757 43 0.10 0.01 51 0.37 0.03 96 0.78 0.02 92 0.56 0.02 

Other Hispanic 562 33 0.09 0.02 41 0.25 0.05 92 0.97 0.06 90 0.48 0.05 

Other Race—Including Multiple 749 38 0.11 0.03 47 0.44 0.14 92 0.75 0.04 91 0.69 0.07 

Exposure Factors Handbook PageSeptember 2011 9-19
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Legumes Lettuce Onions Peaches 

Whole Population 16,783 

Age Group 

96 0.45 0.01 53 0.23 0.01 96 0.18 0.00 49 0.11 0.01 

Birth to 1 year 865 58 1.58 0.15 1 0.01 0.00 38 0.07 0.01 27 0.77 0.09 

1 to 2 years 1,052 97 1.65 0.24 21 0.15 0.02 94 0.27 0.02 70 0.55 0.08 

3 to 5 years 978 98 1.07 0.17 29 0.23 0.03 95 0.26 0.02 68 0.31 0.05 

6 to 12 years 2,256 97 0.48 0.04 37 0.17 0.01 98 0.20 0.02 67 0.13 0.02 

13 to 19 years 3,450 95 0.23 0.01 53 0.20 0.01 97 0.15 0.01 45 0.05 0.01 

20 to 49 years 4,289 96 0.34 0.02 62 0.26 0.01 97 0.18 0.01 43 0.04 0.01 

Female 13 to 49 years 4,103 95 0.32 0.02 60 0.28 0.01 96 0.16 0.01 46 0.05 0.01 

50 years and older 3,893 

Race 

98 0.41 0.02 56 0.24 0.01 97 0.16 0.00 51 0.10 0.01 

Mexican American 4,450 95 0.46 0.03 52 0.20 0.01 96 0.26 0.01 44 0.12 0.02 

Non-Hispanic Black 4,265 96 0.39 0.02 45 0.15 0.01 95 0.13 0.01 52 0.09 0.01 

Non-Hispanic White 6,757 97 0.42 0.02 55 0.25 0.01 97 0.17 0.00 50 0.11 0.01 

Other Hispanic 562 96 0.63 0.17 50 0.19 0.03 93 0.22 0.01 38 0.09 0.03 

Other Race—Including Multiple 749 95 0.76 0.10 51 0.22 0.03 96 0.24 0.02 46 0.09 0.02 

Page Exposure Factors Handbook 9-20 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Pears Peas Pome Fruit Pumpkins 

Whole Population 16,783 

Age Group 

10 0.09 0.01 19 0.07 0.00 38 0.50 0.02 2 0.00 0.00 

Birth to 1 year 865 19 0.70 0.10 36 0.66 0.07 45 2.94 0.29 0 0.00 0.00 

1 to 2 years 1,052 25 0.44 0.07 27 0.29 0.04 61 2.40 0.15 0 0.01 0.01 

3 to 5 years 978 25 0.32 0.06 17 0.17 0.02 54 1.53 0.11 0 0.00 0.00 

6 to 12 years 2,256 17 0.13 0.02 13 0.06 0.01 48 0.87 0.06 1 0.01 0.00 

13 to 19 years 3,450 8 0.03 0.00 13 0.04 0.01 31 0.30 0.02 1 0.00 0.00 

20 to 49 years 4,289 6 0.04 0.01 18 0.05 0.00 31 0.25 0.02 2 0.00 0.00 

Female 13 to 49 years 4,103 8 0.04 0.01 18 0.05 0.00 32 0.28 0.02 2 0.00 0.00 

50 years and older 3,893 

Race 

9 0.07 0.01 23 0.07 0.00 42 0.35 0.02 3 0.00 0.00 

Mexican American 4,450 10 0.13 0.02 15 0.05 0.01 39 0.71 0.04 5 0.01 0.00 

Non-Hispanic Black 4,265 9 0.05 0.01 20 0.08 0.01 31 0.36 0.02 0 0.00 0.00 

Non-Hispanic White 6,757 10 0.08 0.01 19 0.07 0.00 39 0.48 0.02 2 0.00 0.00 

Other Hispanic 562 8 0.07 0.02 19 0.07 0.02 35 0.54 0.08 4 0.01 0.01 

Other Race—Including Multiple 749 11 0.16 0.05 27 0.13 0.02 36 0.63 0.06 2 0.00 0.00 

Exposure Factors Handbook PageSeptember 2011 9-21
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Root Tuber Vegetables Stalk/Stem Vegetables Stone Fruit Strawberries 

Whole Population 16,783 

Age Group 

99 1.15 0.02 19 0.05 0.00 52 0.16 0.01 41 0.10 0.01 

Birth to 1 year 865 69 2.66 0.19 3 0.01 0.00 32 0.94 0.11 10 0.06 0.03 

1 to 2 years 1,052 100 3.15 0.13 13 0.07 0.02 72 0.67 0.08 52 0.36 0.06 

3 to 5 years 978 100 2.60 0.16 10 0.05 0.02 72 0.41 0.06 53 0.27 0.05 

6 to 12 years 2,256 100 1.79 0.07 11 0.03 0.00 68 0.21 0.03 50 0.14 0.03 

13 to 19 years 3,450 100 0.99 0.04 12 0.02 0.00 47 0.08 0.01 35 0.07 0.01 

20 to 49 years 4,289 100 0.89 0.03 24 0.05 0.00 46 0.08 0.01 36 0.06 0.01 

Female 13 to 49 years 4,103 100 0.87 0.02 21 0.04 0.00 49 0.09 0.01 39 0.07 0.01 

50 years and older 3,893 

Race 

100 0.91 0.03 21 0.05 0.01 55 0.17 0.02 45 0.10 0.01 

Mexican American 4,450 99 1.17 0.04 12 0.02 0.00 47 0.18 0.03 34 0.07 0.01 

Non-Hispanic Black 4,265 99 1.09 0.03 12 0.02 0.00 54 0.13 0.01 29 0.04 0.01 

Non-Hispanic White 6,757 100 1.14 0.03 21 0.06 0.00 54 0.17 0.01 44 0.11 0.01 

Other Hispanic 562 98 1.24 0.09 15 0.03 0.01 41 0.13 0.03 33 0.09 0.02 

Other Race—Including Multiple 749 99 1.35 0.08 27 0.06 0.01 49 0.13 0.03 36 0.10 0.02 

Page Exposure Factors Handbook 9-22 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables Based on the 2003−2006 (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Tomatoes Tropical Fruits White Potatoes 

Whole Population 16,783 

Age Group 

87 0.72 0.02 66 0.46 0.02 91 0.65 0.02 

Birth to 1 year 865 26 0.29 0.04 48 1.97 0.20 46 0.52 0.08 

1 to 2 years 1,052 83 1.40 0.07 83 2.65 0.28 94 1.74 0.10 

3 to 5 years 978 85 1.46 0.08 81 1.19 0.09 94 1.38 0.15 

6 to 12 years 2,256 91 0.99 0.04 75 0.52 0.04 93 0.96 0.07 

13 to 19 years 3,450 89 0.69 0.03 59 0.22 0.02 92 0.61 0.03 

20 to 49 years 4,289 89 0.66 0.02 61 0.27 0.02 91 0.54 0.02 

Female 13 to 49 years 4,103 88 0.62 0.02 64 0.28 0.02 90 0.50 0.02 

50 years and older 3,893 

Race 

84 0.59 0.03 68 0.40 0.02 93 0.54 0.03 

Mexican American 4,450 91 0.99 0.03 70 0.73 0.05 87 0.65 0.03 

Non-Hispanic Black 4,265 84 0.57 0.02 64 0.32 0.03 91 0.64 0.03 

Non-Hispanic White 6,757 87 0.71 0.02 65 0.42 0.02 93 0.65 0.03 

Other Hispanic 562 86 0.90 0.05 71 0.86 0.09 86 0.66 0.08 

Other Race—Including Multiple 749 82 0.66 0.03 68 0.59 0.04 87 0.69 0.06 

N = Sample size. 

SE = Standard error. 

Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and vegetables with higher 

percentages consuming. 

Source: U.S. EPA analysis of the 2003−2006 NHANES. 

Exposure Factors Handbook PageSeptember 2011 9-23
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Whole Population 

Age Group 

Apples Asparagus Bananas Beans Beets 

5,743 1.23 0.03 204 0.63 0.05 9,644 0.68 0.02 7,635 0.53 0.01 353 0.29 0.04 

Birth to 1 year 318 5.79 0.38 1 0.21 --­ 396 3.97 0.31 235 1.80 0.20 30 0.01 0.00 

1 to 2 years 508 3.95 0.23 8 1.61 0.15 795 3.04 0.34 530 1.41 0.10 12 0.00 0.00 

3 to 5 years 432 2.91 0.21 5 0.77 0.31 716 1.37 0.12 461 1.42 0.13 11 0.97 0.63 

6 to 12 years 837 1.88 0.12 15 0.60 0.15 1,553 0.61 0.05 936 0.79 0.05 8 0.78 0.33 

13 to 19 years 938 1.00 0.05 13 0.26 0.06 1,817 0.31 0.02 1,264 0.41 0.02 20 0.10 0.03 

20 to 49 years 1,233 0.75 0.04 61 0.50 0.07 2,142 0.41 0.03 2,141 0.41 0.01 81 0.30 0.09 

Female 13 to 49 years 1,195 0.81 0.05 41 0.42 0.07 2,215 0.39 0.03 1,845 0.39 0.01 58 0.39 0.13 

50 years and older 

Race 

1,477 0.75 0.03 101 0.73 0.06 2,225 0.58 0.02 2,068 0.43 0.01 191 0.28 0.05 

Mexican American 1,601 1.72 0.09 18 0.44 0.08 2,490 1.00 0.05 2,482 0.54 0.02 55 0.07 0.04 

Non-Hispanic Black 1,228 1.16 0.05 14 0.57 0.13 2,533 0.46 0.04 1,722 0.58 0.03 42 0.21 0.04 

Non-Hispanic White 2,458 1.15 0.04 154 0.67 0.05 3,863 0.66 0.03 2,809 0.52 0.02 235 0.31 0.05 

Other Hispanic 202 1.45 0.19 3 0.61 0.25 322 0.98 0.08 291 0.44 0.05 12 0.12 0.04 

Other Race—Including Multiple 254 1.45 0.13 15 0.38 0.11 436 0.74 0.07 331 0.61 0.06 9 0.11 0.07 

Page Exposure Factors Handbook 9-24 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Whole Population 

Age Group 

Berries and Small Fruit Broccoli Bulb Vegetables Cabbage Carrots 

10,981 0.45 0.02 2,047 0.65 0.03 15,773 0.19 0.00 1,833 0.43 0.02 7,231 0.30 0.01 

Birth to 1 year 166 1.26 0.42 45 1.14 0.19 346 0.19 0.03 13 0.96 0.44 166 1.13 0.23 

1 to 2 years 839 1.76 0.15 132 1.84 0.27 1,003 0.30 0.02 72 0.73 0.26 525 0.93 0.08 

3 to 5 years 788 1.15 0.12 108 1.50 0.25 947 0.29 0.02 67 0.71 0.15 449 0.71 0.09 

6 to 12 years 1,751 0.57 0.05 228 0.96 0.12 2,216 0.21 0.02 164 0.56 0.16 912 0.49 0.05 

13 to 19 years 2,210 0.30 0.02 289 0.53 0.04 3,354 0.16 0.01 218 0.31 0.04 1,152 0.24 0.02 

20 to 49 years 2,601 0.27 0.01 664 0.53 0.03 4,194 0.19 0.01 577 0.41 0.03 1,948 0.24 0.01 

Female 13 to 49 years 2,705 0.31 0.02 560 0.54 0.04 3,994 0.17 0.01 461 0.41 0.05 1,755 0.24 0.01 

50 years and older 

Race 

2,626 0.40 0.02 581 0.56 0.02 3,713 0.17 0.00 722 0.43 0.02 2,079 0.23 0.01 

Mexican American 2,563 0.38 0.02 456 0.61 0.07 4,132 0.28 0.01 390 0.32 0.04 1,912 0.33 0.02 

Non-Hispanic Black 2,899 0.28 0.02 474 0.61 0.04 4,022 0.14 0.01 442 0.51 0.04 1,471 0.22 0.01 

Non-Hispanic White 4,686 0.47 0.02 925 0.65 0.04 6,410 0.18 0.00 852 0.41 0.02 3,220 0.29 0.01 

Other Hispanic 333 0.51 0.08 82 0.85 0.22 514 0.25 0.01 48 0.32 0.04 272 0.34 0.05 

Other Race—Including Multiple 500 0.58 0.10 110 0.66 0.09 695 0.25 0.02 101 0.70 0.08 356 0.44 0.04 

Exposure Factors Handbook PageSeptember 2011 9-25
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Whole Population 

Age Group 

Citrus Fruits Corn Cucumbers Cucurbits Fruiting Vegetables 

3,398 0.77 0.04 15,899 0.44 0.01 5,728 0.23 0.01 7,109 0.70 0.05 15,483 0.84 0.02 

Birth to 1 year 30 2.90 0.96 465 1.12 0.14 25 0.70 0.31 138 3.16 0.16 281 0.98 0.12 

1 to 2 years 256 2.61 0.30 1,028 1.16 0.06 210 0.58 0.09 332 2.75 0.42 987 1.56 0.07 

3 to 5 years 191 2.50 0.29 971 1.26 0.07 247 0.74 0.12 335 1.86 0.25 926 1.61 0.09 

6 to 12 years 440 1.39 0.09 2,237 0.88 0.04 666 0.37 0.03 828 1.47 0.22 2,192 1.08 0.05 

13 to 19 years 549 0.66 0.04 3,332 0.38 0.01 1,191 0.18 0.01 1,347 0.50 0.06 3,304 0.78 0.03 

20 to 49 years 896 0.55 0.05 4,134 0.33 0.01 1,827 0.20 0.01 2,138 0.50 0.06 4,155 0.78 0.02 

Female 13 to 49 years 860 0.53 0.04 3,967 0.32 0.01 1,596 0.24 0.01 1,874 0.59 0.08 3,945 0.73 0.03 

50 years and older 

Race 

1,036 0.57 0.04 3,732 0.28 0.01 1,562 0.19 0.01 1,991 0.57 0.03 3,638 0.69 0.03 

Mexican American 1,148 1.40 0.06 4,185 0.81 0.03 1,218 0.25 0.02 1,733 0.65 0.05 4,079 1.18 0.03 

Non-Hispanic Black 669 1.04 0.14 4,058 0.48 0.02 1,471 0.17 0.01 1,647 0.44 0.04 3,943 0.66 0.03 

Non-Hispanic White 1,323 0.59 0.04 6,454 0.39 0.01 2,627 0.23 0.01 3,211 0.73 0.06 6,293 0.82 0.02 

Other Hispanic 127 1.10 0.14 516 0.48 0.05 166 0.26 0.05 212 0.60 0.10 498 1.05 0.06 

Other Race—Including Multiple 131 0.96 0.24 686 0.45 0.03 246 0.29 0.06 306 0.94 0.29 670 0.81 0.04 

Page Exposure Factors Handbook 9-26 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Whole Population 

Age Group 

Leafy Vegetables Legumes Lettuce Onions Peaches 

14,824 0.59 0.01 15,808 0.46 0.01 7,946 0.44 0.01 15,695 0.18 0.00 8,542 0.22 0.01 

Birth to 1 year 351 0.55 0.09 459 2.74 0.21 17 0.34 0.16 342 0.19 0.02 215 2.80 0.31 

1 to 2 years 896 0.86 0.08 1,011 1.70 0.25 216 0.70 0.09 998 0.28 0.02 700 0.79 0.10 

3 to 5 years 861 0.70 0.06 957 1.09 0.17 297 0.78 0.11 941 0.28 0.02 676 0.45 0.07 

6 to 12 years 2,035 0.48 0.02 2,198 0.49 0.04 931 0.45 0.02 2,209 0.20 0.02 1,517 0.20 0.03 

13 to 19 years 3,106 0.39 0.01 3,256 0.24 0.01 1,882 0.38 0.02 3,333 0.15 0.01 1,675 0.11 0.02 

20 to 49 years 4,008 0.59 0.02 4,135 0.35 0.02 2,576 0.43 0.02 4,177 0.19 0.01 1,845 0.10 0.01 

Female 13 to 49 years 3,789 0.62 0.03 3,915 0.34 0.02 2,379 0.47 0.02 3,969 0.16 0.01 1,996 0.11 0.01 

50 years and older 

Race 

3,567 0.65 0.02 3,792 0.42 0.02 2,027 0.43 0.01 3,695 0.16 0.00 1,914 0.21 0.02 

Mexican American 3,847 0.44 0.02 4,089 0.49 0.03 2,120 0.38 0.02 4,115 0.27 0.01 1,951 0.28 0.04 

Non-Hispanic Black 3,786 0.51 0.03 4,044 0.41 0.02 1,803 0.34 0.02 4,004 0.14 0.01 2,432 0.18 0.02 

Non-Hispanic White 6,046 0.61 0.02 6,454 0.44 0.02 3,438 0.46 0.01 6,369 0.17 0.00 3,530 0.22 0.01 

Other Hispanic 475 0.53 0.06 517 0.66 0.18 248 0.39 0.05 514 0.24 0.01 250 0.25 0.08 

Other Race—Including Multiple 670 0.76 0.07 704 0.79 0.10 337 0.43 0.04 693 0.25 0.02 379 0.19 0.04 

Exposure Factors Handbook PageSeptember 2011 9-27
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Whole Population 

Age Group 

Pears Peas Pome Fruit Pumpkins Root Tuber Vegetables 

1,965 0.89 0.04 3,133 0.39 0.02 6,699 1.31 0.03 285 0.22 0.02 16,478 1.16 0.02 

Birth to 1 year 144 3.77 0.38 236 1.83 0.11 371 6.50 0.42 3 0.73 0.39 583 3.88 0.24 

1 to 2 years 243 1.79 0.21 257 1.05 0.11 621 3.92 0.23 4 2.13 0.41 1,050 3.15 0.13 

3 to 5 years 221 1.31 0.20 180 0.97 0.13 537 2.82 0.18 8 0.80 0.21 978 2.60 0.16 

6 to 12 years 403 0.77 0.12 309 0.51 0.06 1,071 1.82 0.10 35 0.55 0.16 2,256 1.79 0.07 

13 to 19 years 272 0.35 0.04 416 0.34 0.04 1,085 0.98 0.05 40 0.19 0.06 3,447 0.99 0.04 

20 to 49 years 278 0.63 0.05 780 0.26 0.02 1,362 0.81 0.04 95 0.20 0.04 4,278 0.90 0.03 

Female 13 to 49 years 323 0.56 0.07 675 0.27 0.02 1,352 0.87 0.05 87 0.22 0.04 4,097 0.87 0.02 

50 years and older 

Race 

404 0.72 0.06 955 0.29 0.01 1,652 0.84 0.04 100 0.17 0.02 3,886 0.92 0.03 

Mexican American 518 1.25 0.14 644 0.37 0.04 1,851 1.81 0.09 160 0.28 0.06 4,316 1.18 0.04 

Non-Hispanic Black 489 0.61 0.07 812 0.42 0.04 1,512 1.15 0.05 10 0.71 0.33 4,218 1.10 0.03 

Non-Hispanic White 807 0.84 0.05 1,364 0.38 0.02 2,821 1.23 0.03 91 0.17 0.02 6,667 1.15 0.03 

Other Hispanic 54 0.90 0.12 116 0.39 0.08 223 1.55 0.21 11 0.28 0.12 544 1.26 0.09 

Other Race—Including Multiple 97 1.51 0.32 197 0.49 0.07 292 1.78 0.16 13 0.23 0.14 733 1.36 0.08 

Page Exposure Factors Handbook 9-28 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Whole Population 

Age Group 

Stalk/Stem Vegetables Stone Fruit Strawberries Tomatoes Tropical Fruits 

2,409 0.24 0.01 8,966 0.30 0.02 6,168 0.24 0.02 14,240 0.83 0.02 11,299 0.70 0.02 

Birth to 1 year 15 0.26 0.07 235 2.98 0.33 88 0.60 0.28 246 1.11 0.12 423 4.12 0.30 

1 to 2 years 101 0.58 0.10 721 0.92 0.10 480 0.70 0.12 895 1.68 0.09 862 3.19 0.33 

3 to 5 years 81 0.50 0.10 691 0.56 0.08 460 0.51 0.09 840 1.72 0.09 800 1.47 0.11 

6 to 12 years 212 0.24 0.04 1,545 0.31 0.04 1,019 0.28 0.06 2,071 1.09 0.05 1,733 0.69 0.05 

13 to 19 years 387 0.15 0.01 1,719 0.16 0.02 1,076 0.20 0.03 3,093 0.77 0.03 2,151 0.37 0.03 

20 to 49 years 941 0.22 0.01 1,961 0.17 0.02 1,466 0.17 0.02 3,894 0.74 0.02 2,692 0.44 0.02 

Female 13 to 49 years 719 0.20 0.01 2,101 0.18 0.02 1,492 0.19 0.03 3,679 0.71 0.02 2,720 0.44 0.03 

50 years and older 

Race 

672 0.26 0.03 2,094 0.30 0.03 1,579 0.23 0.03 3,201 0.70 0.03 2,638 0.58 0.02 

Mexican American 411 0.18 0.02 2,043 0.38 0.05 1,438 0.22 0.02 3,897 1.09 0.03 3,031 1.03 0.07 

Non-Hispanic Black 409 0.15 0.01 2,497 0.24 0.02 1,276 0.15 0.02 3,547 0.68 0.02 2,865 0.51 0.05 

Non-Hispanic White 1,336 0.26 0.02 3,753 0.31 0.02 2,979 0.25 0.03 5,714 0.82 0.02 4,498 0.64 0.02 

Other Hispanic 71 0.17 0.03 270 0.31 0.08 198 0.29 0.06 470 1.05 0.06 399 1.21 0.12 

Other Race—Including Multiple 182 0.22 0.02 403 0.27 0.04 277 0.27 0.05 612 0.81 0.04 506 0.86 0.06 

Exposure Factors Handbook PageSeptember 2011 9-29
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-6. Consumer-Only Intake of Individual Fruits and Vegetables Based on the 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Whole Population 

Age Group 

White Potatoes 

14,944 0.72 0.02 

Birth to 1 year 389 1.14 0.15 

1 to 2 years 982 1.86 0.10 

3 to 5 years 915 1.46 0.15 

6 to 12 years 2,111 1.03 0.07 

13 to 19 years 3,163 0.67 0.03 

20 to 49 years 3,861 0.59 0.02 

Female 13 to 49 years 3,691 0.56 0.02 

50 years and older 

Race 

3,523 0.58 0.03 

Mexican American 3,773 0.75 0.03 

Non-Hispanic Black 3,881 0.70 0.03 

Non-Hispanic White 6,180 0.71 0.03 

Other Hispanic 466 0.77 0.08 

Other Race—Including Multiple 644 0.79 0.06 

N = Sample size. 

SE = Standard error. 

Source: U.S. EPA analysis of the 2003−2006 NHANES. 

Page Exposure Factors Handbook 9-30 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-7. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age 

(1977−1978)a 

Age 

(years) 

Per Capita Intake 

(g/day) 

Percent of Population 

Consuming in a Day 

Consumer-Only Intake 

(g/day)b 

Fruits 

Males and Females 

≤1 

1 to 2 

3 to 5 

6 to 8 

169 

146 

134 

152 

86.8 

62.9 

56.1 

60.1 

196 

231 

239 

253 

Males 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

≥75 

133 

120 

147 

107 

141 

115 

171 

174 

186 

50.5 

51.2 

47.0 

39.4 

46.4 

44.0 

62.4 

62.2 

62.6 

263 

236 

313 

271 

305 

262 

275 

281 

197 

Females 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

≥75 

148 

120 

126 

133 

122 

133 

171 

179 

189 

59.7 

48.7 

49.9 

48.0 

47.7 

52.8 

66.7 

69.3 

64.7 

247 

247 

251 

278 

255 

252 

256 

259 

292 

Males and Females 

All ages 142 54.2 263 

Vegetables 

Males and Females 

≤1 

1 to 2 

3 to 5 

6 to 8 

76 

91 

100 

136 

62.7 

78.0 

79.3 

84.3 

121 

116 

126 

161 

Males 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

≥75 

138 

184 

216 

226 

248 

261 

285 

265 

264 

83.5 

84.5 

85.9 

84.7 

88.5 

86.8 

90.3 

88.5 

93.6 

165 

217 

251 

267 

280 

300 

316 

300 

281 

Females 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

≥75 

139 

154 

178 

184 

187 

187 

229 

221 

198 

83.7 

84.6 

83.8 

81.1 

84.7 

84.6 

89.8 

87.2 

88.1 

166 

183 

212 

227 

221 

221 

255 

253 

226 

Males and Females 

All ages 201 85.6 235 a Based on USDA Nationwide Food Consumption Survey (1977−1978) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population consuming fruit 

in a day. 

Source: USDA (1980). 

Exposure Factors Handbook Page
 

September 2011 9-31 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-8. Mean Total Fruit and Total Vegetable Intake (as-consumed) in a Day by Sex and Age 

(1987−1988, 1994, and 1995)a 

Age 

(years) 

Per Capita Intake 

(g/day) 

Percent of Population 

Consuming in 1 Day 

Consumer-Only Intake (g/day)b 

1987−1988 1994 1995 1987−1988 1994 1995 1987−1988 1994 1995 

Fruits 

Males and Females 

5 and under 

Males 

157 230 221 59.2 70.6 72.6 265 326 304 

6 to 11 182 176 219 63.8 59.8 62.2 285 294 352 

12 to 19 158 169 210 49.4 44.0 47.1 320 384 446 

≥20 

Females 

133 175 170 46.5 50.2 49.6 286 349 342 

6 to 11 154 174 172 58.3 59.3 63.6 264 293 270 

12 to 19 131 148 167 47.1 47.1 44.4 278 314 376 

≥20 

Males and Females 

140 157 155 52.7 55.1 54.4 266 285 285 

All Ages 142 171 173 51.4 54.1 54.2 276 316 319 

Vegetables 

Males and Females 

5 and under 

Males 

81 80 83 74.0 75.2 75.0 109 106 111 

6 to 11 129 118 111 86.8 82.4 80.6 149 143 138 

12 to 19 173 154 202 85.2 74.9 79.0 203 206 256 

≥20 

Females 

232 242 241 85.0 85.9 86.4 273 282 278 

6 to 11 129 115 108 80.6 82.9 79.1 160 139 137 

12 to 19 129 132 144 75.8 78.5 76.0 170 168 189 

≥20 

Males and Females 

183 190 189 82.9 84.7 83.2 221 224 227 

All Ages 182 186 188 82.6 83.2 82.6 220 223 228 a Based on USDA NFCS (1987−1988) and CSFII (1994 and 1995) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population consuming 

fruits in a day. 

Source: USDA (1996a, b). 

Page Exposure Factors Handbook 

9-32 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-9. Per Capita Consumption of Fresh Fruits and Vegetables in 1997a 

Fresh Fruits Fresh Vegetables 

Food Item 

Per Capita 

Consumption 

(g/day)b Food Item 

Per Capita 

Consumption 

(g/day)b 

Citrus 

Oranges (includes Temple oranges) 

Tangerines and Tangelos 

Lemons 

Limes 

Grapefruit 

Total Fresh Citrus 

Non-citrus 

Apples 

Apricots 

Avocados 

Bananas 

Cherries 

Cranberries 

Grapes 

Kiwi Fruit 

Mangoes 

Peaches and Nectarines 

Pears 

Pineapple 

Papayas 

Plums and Prunes 

Strawberries 

Melons 

Total Fresh Non-citrus 

Total Fresh Fruits 

16.9 

3.0 

3.4 

1.4 

7.6 

32.2 

22.0 

0.1 

1.6 

34.5 

0.6 

0.1 

9.1 

0.5 

1.7 

6.7 

4.1 

2.9 

0.6 

1.9 

4.9 

34.5 

125.6 

157.8 

Artichokes 

Asparagus 

Bell Peppers 

Broccoli 

Brussel Sprouts 

Cabbage 

Carrots 

Cauliflower 

Celery 

Sweet Corn 

Cucumber 

Eggplant 

Escarole/Endive 

Garlic 

Head Lettuce 

Romaine Lettuce 

Onions 

Radishes 

Snap Beans 

Spinach 

Tomatoes 

Total Fresh Vegetables 

0.6 

0.7 

8.3 

6.0 

0.4 

11.8 

15.1 

1.9 

7.0 

9.2 

7.2 

0.5 

0.2 

2.1 

28.1 

7.0 

20.9 

0.5 

1.6 

0.6 

20.0 

149.8 

a Based on retail-weight equivalent. Includes imports; excludes exports and foods grown in home gardens. Data for 

1997 were used. b Original data were presented in lbs/year; data were converted to g/day by multiplying by a factor of 454 g/lb and 

dividing by 365 day/year. 

Source: USDA (1999b). 

Exposure Factors Handbook Page
 

September 2011 9-33 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-10. Mean Quantities of Vegetables Consumed Daily by Sex and Age, for Children, per Capita (g/day, as-consumed)a 

Age Group 

(years) Sample Size Total 

White Potatoes 

Dark Green 

Vegetables 

Deep Yellow 

Vegetables Tomatoes 

Lettuce, Lettucebased Salads Green 

Beans 

Corn, Green 

Peas, Lima 

Total Fried Beans 

Other 

Vegetables 

Males and Females 

Under 1 1,126 57 9 1 2 19 1

b b,c 6 5 

1 1,016 79 26 11 5 9 7 1 8 9 

2 1,102 87 32 17 4 5 11 2 7 10 

1 to 2 2,118 83 29 14 5 7 9 1 7 9 

3 1,831 91 34 17 5 5 13 2 5 11 

4 1,859 97 37 19 6 5 11 3 5 12 

5 884 103 44 22 4 6 12 3 6 12 

3 to 5 4,574 97 38 20 5 5 12 3 5 11 

≤5 7,818 88 31 16 4 7 10 2 6 10 

16 

16 

17 

17 

16 

18 

17 

17 

17 

Males 

6 to 9 787 110 47 26 4 5 16 5 5 11 

6 to 11 1,031 115 50 27 5 5 16 5 5 11 

12 to 19 737 176 85 44 6 6 28 12 3

b 10 

16 

18 

25 

Females 

6 to 9 704 110 42 22 5 4 14 6 5 13 

6 to 11 969 116 46 25 5 4 15 7 5 12 

12 to 19 732 145 61 31 9 4 18 12 4 8 

21 

22 

28 

Males and Females 

≤9 9,309 97 37 19 4 6 12 3 6 11 

≤19 11,287 125 53 27 6 6 17 7 5 10 

18 

22 a Based on data from 1994−1996, 1998 CSFII. b Estimate is not statistically reliable due to small samples size reporting intake. c Value less than 0.5, but greater than 0. 

Note: Consumption amounts shown are representative of the first day of each participant’s survey response. 

Source: USDA (1999a). 

Page Exposure Factors Handbook 9-34 September 2011 
 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-11. Percentage of Individuals Consuming Vegetables, by Sex and Age, for Children (%)a 

Age Group 

(years) Sample Size Total 

White Potatoes Dark Green 

Vegetables 

Deep Yellow 

Vegetables Tomatoes Lettuce, Lettucebased Salads 

Green 

Beans 

Corn, Green 

Peas, Lima 

Beans Total Fried 

Other 

Vegetables 

Males and Females 

Under 1 1,126 47.2 12.3 4.3 2.3 20.5 1.8 0.2b 7.8 8.5 

1 1,016 73.3 40.4 25.2 6.4 13.3 18.0 3.9 13.7 17.6 

2 1,102 78.4 46.7 34.5 7.6 10.5 30.8 7.5 11.5 15.0 

1 to 2 2,118 75.9 43.6 29.9 7.0 11.8 24.6 5.7 12.6 16.2 

3 1,831 80.5 46.7 34.7 7.0 10.7 34.1 8.3 10.1 14.6 

4 1,859 80.7 47.3 34.8 7.2 12.0 33.0 10.0 9.0 16.4 

5 884 83.0 50.7 38.3 4.6 13.3 36.5 13.4 10.4 16.1 

3 to 5 4,574 81.4 48.2 35.9 6.3 12.0 34.5 10.6 9.9 15.7 

≤5 7,818 75.4 42.3 30.1 6.1 13.0 27.2 7.6 10.5 15.0 

14.8 

19.4 

22.3 

20.9 

24.7 

26.5 

28.8 

26.7 

23.3 

Males 

6 to 9 787 78.8 47.9 38.0 6.3 12.5 38.2 13.1 7.8 15.0 

6 to 11 1,031 79.3 48.7 38.4 6.1 12.4 38.7 13.9 6.7 13.8 

12 to 19 737 78.2 49.5 38.6 3.6 8.0 43.0 23.8 3.5 7.4 

29.7 

30.8 

33.2 

Females 

6 to 9 704 80.5 48.2 36.3 5.9 11.9 33.8 15.8 8.4 15.9 

6 to 11 969 81.7 50.8 38.9 5.4 11.4 33.5 17.1 7.8 15.1 

12 to 19 732 79.5 46.4 34.6 7.0 10.6 35.3 25.1 4.4 7.4 

26.6 

29.2 

34.5 

Males and Females 

≤9 9,309 77.1 44.6 32.9 6.1 12.7 30.7 10.3 9.6 15.2 

≤19 11,287 78.3 46.8 35.3 5.6 11.2 34.6 16.6 7.0 11.9 

25.2 

29.4 a Based on data from 1994−1996, 1998 CSFII. b Estimate is not statistically reliable due to small samples size reporting intake. 

Note: Consumption amounts shown are representative of the first day of each participant’s survey response. 

Source: USDA (1999a). 

Exposure Factors Handbook PageSeptember 2011 9-35
Page 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Exposure Factors Handbook 

September 2011 9-36 

 

 

 

 

 

 

 

 

Table 9-12. Mean Quantities of Fruits Consumed Daily by Sex and Age, for Children, per Capita (g/day, as-consumed)a

Citrus Fruits and Juices Other Fruits, Mixtures, and Juices 

Age Group 

(years) Sample Size Total 

Total Juices 

Dried 

Fruits Total Apples Bananas Melons and 

Berries 

Other Fruits 

and Mixtures 

(mainly fruit) 

Non-Citrus 

Juices and 

Nectars 

Males and Females 

Under 1 1,126 131 4 4 -

b,c 126 14 10 1b 39 61 

1 1,016 267 47 42 2 216 22 23 8 29 134 

2 1,102 276 65 56 2 207 27 20 10 20 130 

1 to 2 2,118 271 56 49 2 212 24 22 9 24 132 

3 1,831 256 61 51 1 191 27 18 13 24 110 

4 

5 

1,859 

884 

243 

218 

62 

55 

52 

44 

1 

-

b,c 

177 

160 

31 

31 

17 

14 

14 

13 

22 

24 

92 

78 

3 to 5 4,574 239 59 49 1 176 30 16 13 23 93 

≤5 7,818 237 52 44 1 182 26 17 10 26 103 

Males 

6 to 9 787 194 58 51 -

b,c 133 32 11 21 20 50 

6 to 11 

12 to 19 

1,031 

737 

183 

174 

67 

102 

60 

94 

-

b,c 

1b 

113 

70 

28 

13 

11 

8 

16 

11b 

19 

10 

40 

29 

Females 

6 to 9 704 180 63 54 1b 113 23 10 10 25 46 

6 to 11 969 169 64 54 -

b,c 103 21 8 8 23 42 

12 to 19 732 157 72 67 -

b,c 83 13 5 15 14 35 

Males and Females 

≤9 9,309 217 55 47 1 159 27 15 12 24 81 

≤19 11,287 191 70 62 1 118 21 11 12 19 56 

a Based on data from 1994−1996, 1998 CSFII.
 b Estimate is not statistically reliable due to small samples size reporting intake.
 c Value less than 0.5, but greater than 0.
 

- Indicates value as not statistically significant or less than 0.5, but greater than 0.
 

Note: Consumption amounts shown are representative of the first day of each participant’s survey response.
 

Source: USDA (1999a).
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Page 

September 2011 9-37 

 

 

 

 

 

 

 

 

Table 9-13. Percentage of Individuals Consuming, Fruits by Sex and Age, for Children (%)a 

Age Group 

(years) Sample Size Total 

Citrus Fruits and Juices 

Dried 

Fruits 

Other Fruits, Mixtures, and Juices 

Total Juices Total Apples Bananas Melons and 

Berries 

Other Fruits 

and Mixtures 

(mainly fruit) 

Non-Citrus 

Juices and 

Nectars 

Males and Females 

Under 1 

1 

2 

1 to 2 

3 

4 

5 

3 to 5 

≤5 

1,126 

1,016 

1,102 

2,118 

1,831 

1,859 

884 

4,574 

7,818 

59.7 

81.0 

76.6 

78.8 

74.5 

72.6 

67.6 

71.6 

72.6 

3.6 

23.6 

30.6 

27.2 

27.9 

28.0 

26.9 

27.6 

24.6 

2.7 

19.0 

23.4 

21.3 

21.4 

21.8 

19.5 

20.9 

18.8 

0.4b 

5.9 

5.3 

5.6 

4.1 

3.0 

1.3b 

2.8 

3.5 

59.0 

73.0 

64.7 

68.8 

64.2 

62.1 

56.9 

61.0 

63.5 

15.7 

23.4 

24.0 

23.7 

22.4 

23.7 

21.9 

22.7 

22.2 

13.3 

25.1 

20.2 

22.6 

17.5 

15.7 

12.6 

15.3 

17.6 

1.8 

6.9 

8.5 

7.7 

7.8 

7.6 

7.4 

7.6 

6.9 

29.9 

26.5 

19.4 

22.9 

20.1 

20.0 

19.0 

19.7 

22.0 

33.0 

43.2 

37.0 

40.0 

33.3 

30.8 

24.5 

29.5 

33.5 

Males 

6 to 9 

6 to 11 

12 to 19 

787 

1,031 

737 

59.0 

56.5 

44.5 

24.8 

25.2 

24.7 

20.5 

21.6 

21.7 

0.8b 

1.1b 

1.0b 

49.1 

44.2 

27.1 

20.3 

18.2 

8.2 

8.7 

8.0 

6.0 

7.3 

6.6 

4.1 

16.8 

15.4 

7.1 

15.5 

12.7 

8.2 

Females 

6 to 9 

6 to 11 

12 to 19 

704 

969 

732 

64.9 

62.1 

45.6 

27.9 

27.7 

22.4 

22.3 

21.5 

18.1 

1.5b 

1.1b 

1.1b 

50.4 

47.2 

30.2 

17.3 

16.2 

8.2 

8.8 

7.3 

4.4 

7.4 

7.4 

6.0 

20.4 

19.0 

11.3 

17.3 

14.9 

9.7 

Males and Females 

≤9 

≤19 

9,309 

11,287 

68.3 

57.8 

25.2 

24.8 

19.8 

20.1 

2.5 

1.8 

58.0 

44.4 

20.9 

15.2 

14.0 

9.7 

7.1 

6.2 

20.6 

15.5 

26.7 

17.9 

a Based on data from 1994−1996, 1998 CSFII. b Estimate is not statistically reliable due to small sample size reporting intake. 

Note: Percentages shown are representative of the first day of each participant’s survey response. 

Source: USDA (1999a). 
Table 9-14. Per Capita Intake of Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

Population Group N Percent 

Consuming Mean SE 

Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Fruits 

Whole Population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

≥50 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian, Pacific Islander 

 American Indian, Alaskan 

 Native 

 Black 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 City Center 

 Suburban 

 Non-metropolitan 

20,607 

1,486 

2,096 

4,391 

2,089 

1,222 

4,677 

4,646 

4,687 

5,308 

5,890 

4,722 

557 

177 

2,740 

1,638 

15,495 

4,822 

3,692 

7,208 

4,885 

6,164 

9,598 

4,845 

80.0 

56.4 

89.5 

90.0 

88.3 

73.2 

75.3 

85.8 

79.6 

80.2 

78.3 

81.7 

78.8 

77.8 

71.3 

78.5 

81.5 

82.3 

83.4 

74.7 

82.7 

79.0 

82.5 

75.9 

1.6 

5.7 

6.2 

4.6 

2.4 

0.8 

0.9 

1.4 

1.5 

1.6 

1.5 

1.7 

2.1 

1.9 

1.2 

2.2 

1.6 

1.6 

1.7 

1.3 

2.0 

1.6 

1.7 

1.3 

0.0 

0.3 

0.2 

0.1 

0.1 

0.1 

0.0 

0.0 

0.1 

0.1 

0.1 

0.0 

0.2 

0.3 

0.1 

0.2 

0.0 

0.0 

0.1 

0.1 

0.1 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.5 

0.2 

0.1 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.5 

1.5 

4.7 

3.2 

1.3 

0.1 

0.2 

0.9 

0.5 

0.5 

0.4 

0.7 

1.1 

0.9 

0.1 

0.9 

0.6 

0.6 

0.8 

0.2 

0.9 

0.5 

0.7 

0.3 

2.0 

9.6 

9.4 

7.0 

3.3 

1.1 

1.3 

2.1 

2.0 

1.9 

1.9 

2.1 

3.2 

1.9 

1.2 

2.9 

2.0 

2.0 

2.2 

1.5 

2.6 

2.0 

2.1 

1.6 

4.2 

17.1 

14.6 

11.4 

6.4 

2.4 

2.7 

3.6 

4.2 

4.2 

4.0 

4.4 

6.0 

5.3 

3.6 

6.1 

4.1 

4.1 

4.2 

3.5 

5.2 

4.4 

4.5 

3.6 

6.5 

21.3 

18.5 

14.4 

8.8 

3.5 

3.9 

4.8 

6.4 

6.7 

6.2 

6.6 

7.4 

9.6 

5.6 

10.0 

6.3 

6.2 

6.3 

5.7 

8.0 

6.3 

6.9 

5.4 

14.0 

32.2 

26.4 

22.3 

14.3 

6.9 

6.2 

7.6 

13.3 

14.7 

12.8 

14.3 

14.7 

16.4 

13.3 

18.5 

13.4 

13.1 

14.1 

13.0 

15.3 

14.1 

14.5 

12.8 

73.8 

73.8 

44.0 

45.5 

25.0 

12.8 

16.7 

18.4 

43.8 

73.8 

53.2 

37.5 

43.5 

20.9 

40.0 

45.5 

73.8 

43.5 

40.0 

73.8 

45.5 

45.5 

43.8 

73.8 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 9-38 September 2011 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Page 

September 2011 9-39 

Table 9-14. Per Capita Intake of Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Percent 

Consuming Mean SE Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Vegetables 

Whole Population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 ≥50 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian, Pacific Islander 

 American Indian, Alaskan 

 Native 

 Black 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 City Center 

 Suburban 

 Non-metropolitan 

20,607 

1,486 

2,096 

4,391 

2,089 

1,222 

4,677 

4,646 

4,687 

5,308 

5,890 

4,722 

557 

177 

2,740 

1,638 

15,495 

4,822 

3,692 

7,208 

4,885 

6,164 

9,598 

4,845 

99.5 

72.1 

99.7 

100.0 

99.9 

100.0 

99.9 

99.9 

99.6 

99.5 

99.5 

99.5 

99.0 

99.7 

99.5 

98.8 

99.6 

99.6 

99.7 

99.5 

99.3 

99.5 

99.5 

99.6 

3.4 

4.5 

6.9 

5.9 

4.1 

2.9 

2.9 

3.1 

3.3 

3.4 

3.6 

3.2 

4.4 

3.9 

3.0 

4.1 

3.3 

3.4 

3.3 

3.2 

3.6 

3.3 

3.4 

3.3 

0.0 

0.2 

0.2 

0.1 

0.1 

0.1 

0.0 

0.0 

0.1 

0.1 

0.1 

0.1 

0.3 

0.3 

0.1 

0.2 

0.0 

0.1 

0.1 

0.1 

0.1 

0.1 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.4 

0.0 

0.7 

0.8 

0.6 

0.4 

0.5 

0.5 

0.5 

0.4 

0.4 

0.5 

0.8 

0.5 

0.2 

0.5 

0.5 

0.5 

0.4 

0.4 

0.5 

0.4 

0.5 

0.5 

0.8 

0.0 

1.5 

1.4 

1.0 

0.7 

0.8 

0.9 

0.8 

0.8 

0.8 

0.9 

1.3 

0.8 

0.5 

0.9 

0.8 

0.8 

0.7 

0.8 

0.9 

0.7 

0.9 

0.8 

1.6 

0.0 

3.2 

2.8 

1.8 

1.4 

1.5 

1.6 

1.6 

1.5 

1.6 

1.6 

2.3 

1.6 

1.2 

1.7 

1.6 

1.6 

1.5 

1.6 

1.7 

1.5 

1.6 

1.6 

2.7 

2.7 

5.6 

4.7 

3.2 

2.4 

2.5 

2.6 

2.7 

2.6 

2.9 

2.6 

3.9 

2.8 

2.1 

3.0 

2.7 

2.7 

2.6 

2.6 

2.9 

2.7 

2.7 

2.6 

4.3 

7.4 

9.3 

7.7 

5.3 

3.8 

3.8 

4.0 

4.3 

4.2 

4.6 

4.2 

5.6 

5.2 

3.9 

5.1 

4.3 

4.3 

4.3 

4.1 

4.6 

4.3 

4.3 

4.2 

6.4 

12.2 

13.9 

11.7 

7.8 

5.5 

5.4 

5.7 

6.2 

6.6 

7.2 

5.8 

8.2 

8.1 

6.2 

8.2 

6.2 

6.5 

6.2 

6.2 

7.0 

6.4 

6.5 

6.4 

8.3 

14.8 

17.1 

14.7 

9.9 

6.9 

6.8 

7.0 

7.6 

8.8 

9.5 

7.5 

10.2 

9.8 

8.4 

11.6 

8.0 

8.6 

8.2 

7.9 

8.8 

8.5 

8.3 

8.1 

14.8 

25.3 

26.5 

23.4 

17.4 

11.4 

10.0 

10.6 

13.0 

16.0 

15.8 

12.8 

15.9 

18.4 

16.1 

21.1 

13.5 

14.1 

14.4 

14.2 

15.5 

15.3 

14.0 

14.9 

58.2 

56.8 

58.2 

50.9 

53.7 

29.5 

42.7 

38.7 

58.2 

53.7 

50.9 

56.8 

32.3 

34.5 

56.8 

58.2 

50.9 

53.7 

42.7 

58.2 

50.9 

58.2 

53.7 

49.4 

N 

SE 

Source: 

= Sample size. 

= Standard error. 

U.S. EPA analysis of 1994−1996, 1998 CSFII. 
Table 9-15. Consumer-Only Intake of Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE 

Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Fruits 

Whole Population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 ≥50 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian, Pacific Islander 

 American Indian, Alaskan 

 Native 

 Black 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 City Center 

 Suburban 

 Non-metropolitan 

16,762 

830 

1,878 

3,957 

1,846 

898 

3,458 

3,895 

3,796 

4,289 

4,744 

3,933 

427 

146 

2,065 

1,323 

12,801 

4,023 

3,145 

5,531 

4,063 

4,985 

8,046 

3,731 

2.0 

10.1 

6.9 

5.1 

2.7 

1.1 

1.2 

1.6 

1.9 

2.0 

1.9 

2.0 

2.7 

2.4 

1.7 

2.9 

1.9 

1.9 

2.0 

1.7 

2.4 

2.0 

2.1 

1.7 

0.0 

0.4 

0.2 

0.1 

0.1 

0.1 

0.0 

0.0 

0.1 

0.1 

0.1 

0.1 

0.2 

0.4 

0.1 

0.2 

0.0 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.2 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

3.7 

2.2 

1.0 

0.3 

0.0 

0.1 

0.3 

0.1 

0.2 

0.1 

0.2 

0.5 

0.4 

0.0 

0.3 

0.2 

0.1 

0.2 

0.1 

0.3 

0.1 

0.2 

0.1 

1.0 

8.5 

5.4 

3.8 

1.7 

0.5 

0.7 

1.1 

0.9 

1.0 

0.9 

1.1 

1.7 

1.1 

0.6 

1.5 

1.0 

1.0 

1.1 

0.7 

1.3 

1.0 

1.1 

0.8 

2.5 

14.4 

10.1 

7.5 

3.7 

1.5 

1.7 

2.3 

2.4 

2.4 

2.4 

2.6 

3.8 

2.9 

2.0 

3.6 

2.4 

2.3 

2.6 

2.1 

3.0 

2.7 

2.5 

2.1 

4.9 

20.4 

15.3 

11.9 

6.7 

2.9 

3.2 

3.8 

4.9 

4.9 

4.7 

4.9 

6.6 

5.8 

4.6 

7.7 

4.7 

4.7 

4.6 

4.5 

5.8 

4.9 

5.1 

4.1 

7.3 

26.4 

19.0 

15.0 

9.3 

3.7 

4.4 

5.0 

7.1 

7.5 

7.1 

7.6 

7.8 

10.0 

6.7 

11.2 

7.0 

6.7 

6.9 

6.9 

8.9 

7.1 

7.7 

6.3 

15.0 

34.7 

27.1 

22.8 

14.8 

7.6 

6.6 

8.0 

14.4 

16.1 

14.5 

15.3 

14.7 

17.6 

15.7 

19.3 

14.5 

14.4 

14.8 

14.4 

16.4 

14.8 

15.6 

13.9 

73.8 

73.8 

44.0 

45.5 

25.0 

12.8 

16.7 

18.4 

43.8 

73.8 

53.2 

37.5 

43.5 

20.9 

40.0 

45.5 

73.8 

43.5 

40.0 

73.8 

45.5 

45.5 

43.8 

73.8 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 9-40 September 2011 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Page 

September 2011 9-41 

Table 9-15. Consumer-Only Intake of Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Percentiles 

Population Group N Mean SE

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Vegetables 

Whole Population 20,163 3.4 0.0 0.0 0.5 0.8 1.6 2.7 4.3 6.4 8.4 14.8 58.2 

Age Group 

 Birth to 1 year 1,062 6.2 0.3 0.0 0.1 0.1 2.0 4.9 9.4 13.4 16.1 26.4 56.8 

 1 to 2 years 2,090 6.9 0.2 0.0 0.7 1.5 3.2 5.6 9.3 13.9 17.1 26.5 58.2 

 3 to 5 years 4,389 5.9 0.1 0.0 0.8 1.4 2.8 4.7 7.7 11.7 14.7 23.4 50.9 

 6 to 12 years 2,087 4.1 0.1 0.1 0.6 1.0 1.8 3.2 5.3 7.8 9.9 17.4 53.7 

 13 to 19 years 1,222 2.9 0.1 0.0 0.4 0.7 1.4 2.4 3.8 5.5 6.9 11.4 29.5 

 20 to 49 years 4,673 2.9 0.0 0.1 0.5 0.8 1.5 2.5 3.8 5.4 6.8 10.0 42.7 

 ≥50 years 4,640 3.1 0.0 0.0 0.5 0.9 1.6 2.6 4.0 5.7 7.0 10.6 38.7 

Season 

 Fall 4,606 3.3 0.1 0.1 0.5 0.8 1.6 2.8 4.3 6.2 7.7 13.0 58.2 

 Spring 5,185 3.4 0.1 0.0 0.5 0.8 1.5 2.6 4.2 6.7 8.8 16.0 53.7 

 Summer 5,740 3.6 0.1 0.1 0.4 0.8 1.7 2.9 4.6 7.2 9.5 15.8 50.9 

 Winter 4,632 3.2 0.1 0.0 0.6 0.9 1.6 2.7 4.2 5.9 7.5 12.8 56.8 

Race 

 Asian, Pacific Islander 530 4.4 0.3 0.1 1.0 1.4 2.4 3.9 5.6 8.2 10.2 15.9 32.3 

 American Indian, Alaskan Native 174 3.9 0.3 0.0 0.5 0.9 1.7 2.9 5.2 8.1 9.8 18.4 34.5 

 Black 2,683 3.1 0.1 0.0 0.2 0.5 1.2 2.1 3.9 6.2 8.4 16.1 56.8 

 Other/NA 1,577 4.2 0.2 0.1 0.6 0.9 1.8 3.0 5.2 8.3 11.7 21.3 58.2 

 White 15,199 3.3 0.0 0.1 0.5 0.9 1.6 2.7 4.3 6.2 8.0 13.6 50.9 

Region 

 Midwest 4,721 3.4 0.1 0.1 0.5 0.8 1.6 2.7 4.3 6.5 8.6 14.2 53.7 

 Northeast 3,634 3.3 0.1 0.0 0.4 0.8 1.5 2.6 4.3 6.2 8.2 14.4 42.7 

 South 7,078 3.3 0.1 0.0 0.5 0.8 1.6 2.6 4.1 6.2 7.9 14.2 58.2 

 West 4,730 3.6 0.1 0.1 0.5 0.9 1.7 2.9 4.6 7.1 8.9 15.6 50.9 

Urbanization 

 City Center 6,029 3.4 0.1 0.0 0.4 0.8 1.5 2.7 4.3 6.4 8.6 15.4 58.2 

 Suburban 9,381 3.4 0.0 0.1 0.5 0.9 1.7 2.8 4.4 6.5 8.4 14.0 53.7 

 Non-metropolitan 4,753 3.3 0.1 0.0 0.5 0.9 1.6 2.7 4.2 6.4 8.1 14.9 49.4 

N = Sample size. 

SE = Standard error. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Apples Asparagus Bananas Beans 

Whole Population 20,607 

Age Group 

30.5 0.45 0.01 1.4 0.01 0.00 48.1 0.35 0.01 44.9 0.27 0.01 

Birth to 1 year 1,486 34.6 2.32 0.13 0.2 0.01 0.00 40.7 1.24 0.06 21.6 0.43 0.04 

1 to 2 years 2,096 44.8 1.79 0.09 0.8 0.02 0.01 62.8 1.77 0.09 46.8 0.76 0.04 

3 to 5 years 4,391 44.6 1.64 0.05 0.5 0.01 0.00 60.7 0.93 0.04 43.0 0.52 0.02 

6 to 12 years 2,089 38.2 0.83 0.05 0.7 0.01 0.00 57.7 0.38 0.03 38.8 0.32 0.02 

13 to 19 years 1,222 22.5 0.20 0.02 0.6 0.00 0.00 42.1 0.13 0.02 36.0 0.18 0.02 

20 to 49 years 4,677 25.7 0.21 0.01 1.3 0.01 0.00 41.7 0.21 0.01 45.5 0.22 0.01 

≥50 years 4,646 

Season 

34.5 0.32 0.02 2.5 0.02 0.00 54.1 0.35 0.01 51.4 0.26 0.01 

Fall 4,687 35.0 0.55 0.03 1.2 0.01 0.00 45.6 0.36 0.02 47.3 0.29 0.01 

Spring 5,308 29.6 0.45 0.02 1.9 0.02 0.00 49.8 0.35 0.02 43.3 0.25 0.01 

Summer 5,890 25.5 0.34 0.02 0.9 0.01 0.00 49.6 0.33 0.02 43.6 0.28 0.01 

Winter 4,722 

Race 

32.2 0.46 0.02 1.6 0.02 0.00 47.3 0.38 0.01 45.5 0.26 0.01 

Asian, Pacific Islander 557 33.5 0.53 0.06 1.0 0.01 0.00 45.4 0.43 0.04 52.0 0.25 0.02 

American Indian, Alaskan Native 177 31.0 0.60 0.12 2.5 0.02 0.01 44.1 0.39 0.05 37.8 0.26 0.06 

Black 2,740 22.0 0.36 0.02 0.4 0.00 0.00 45.4 0.43 0.04 45.2 0.32 0.02 

Other/NA 1,638 27.7 0.55 0.05 0.2 0.00 0.00 44.1 0.26 0.02 60.6 0.43 0.03 

White 15,495 

Region 

32.0 0.45 0.01 1.7 0.01 0.00 47.5 0.58 0.07 43.6 0.25 0.01 

Midwest 4,822 34.5 0.47 0.02 1.5 0.01 0.00 51.1 0.35 0.02 43.6 0.26 0.01 

Northeast 3,692 32.7 0.48 0.03 1.3 0.01 0.00 52.9 0.36 0.01 36.7 0.21 0.01 

South 7,208 25.3 0.36 0.01 1.1 0.01 0.00 42.4 0.30 0.02 48.8 0.33 0.01 

West 4,885 

Urbanization 

32.7 0.55 0.02 1.9 0.01 0.00 49.6 0.44 0.03 47.5 0.25 0.02 

City Center 6,164 28.9 0.42 0.02 1.7 0.01 0.00 48.4 0.36 0.02 46.2 0.29 0.01 

Suburban 9,598 33.2 0.49 0.02 1.1 0.01 0.00 50.5 0.38 0.01 42.4 0.25 0.01 

Non-metropolitan 4,845 27.0 0.39 0.02 1.5 0.01 0.00 42.3 0.28 0.03 48.7 0.30 0.02 

Page Exposure Factors Handbook 9-42 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Beets Berries and Small Fruit Broccoli Bulb Vegetables 

Whole Population 20,607 

Age Group 

2.2 0.01 0.00 58.7 0.23 0.01 13.9 0.11 0.01 95.3 0.20 0.00 

Birth to 1 year 1,486 0.4 0.01 0.01 16.5 0.13 0.02 3.5 0.07 0.02 33.4 0.07 0.01 

1 to 2 years 2,096 0.7 0.01 0.00 66.2 0.91 0.05 12.0 0.25 0.03 93.3 0.30 0.01 

3 to 5 years 4,391 0.8 0.01 0.00 72.7 0.72 0.03 10.7 0.18 0.01 95.8 0.27 0.01 

6 to 12 years 2,089 0.8 0.01 0.00 73.4 0.40 0.03 11.0 0.14 0.02 97.3 0.21 0.01 

13 to 19 years 1,222 0.7 0.00 0.00 55.4 0.15 0.02 8.3 0.06 0.01 97.7 0.19 0.01 

20 to 49 years 4,677 1.9 0.00 0.00 53.1 0.14 0.01 14.7 0.10 0.01 97.4 0.21 0.01 

≥50 years 4,646 

Season 

4.6 0.02 0.00 63.0 0.19 0.01 17.3 0.11 0.01 93.4 0.17 0.00 

Fall 4,687 2.0 0.01 0.00 57.4 0.18 0.01 14.6 0.12 0.01 95.8 0.21 0.01 

Spring 5,308 2.3 0.01 0.00 60.6 0.27 0.02 13.5 0.11 0.02 95.4 0.20 0.01 

Summer 5,890 2.3 0.01 0.00 60.4 0.29 0.02 13.7 0.11 0.01 94.3 0.19 0.01 

Winter 4,722 

Race 

2.3 0.01 0.00 56.6 0.20 0.01 13.7 0.10 0.01 95.5 0.21 0.01 

Asian, Pacific Islander 557 2.7 0.00 0.00 41.7 0.28 0.06 25.7 0.23 0.06 95.0 0.38 0.03 

American Indian, Alaskan Native 177 0.3 0.00 0.00 49.6 0.13 0.02 9.1 0.11 0.07 99.3 0.25 0.04 

Black 2,740 0.9 0.00 0.00 50.6 0.14 0.01 13.2 0.14 0.02 92.9 0.16 0.01 

Other/NA 1,638 1.3 0.01 0.00 47.5 0.21 0.03 8.2 0.09 0.02 95.0 0.31 0.02 

White 15,495 

Region 

2.5 0.01 0.00 61.6 0.25 0.01 14.0 0.10 0.01 95.6 0.19 0.00 

Midwest 4,822 2.3 0.01 0.00 63.1 0.25 0.02 13.0 0.09 0.01 96.2 0.19 0.01 

Northeast 3,692 2.4 0.01 0.00 63.2 0.24 0.02 15.3 0.13 0.01 94.5 0.19 0.01 

South 7,208 1.7 0.01 0.00 53.3 0.19 0.01 13.1 0.11 0.01 94.4 0.18 0.01 

West 4,885 

Urbanization 

2.8 0.01 0.00 58.7 0.28 0.03 14.6 0.12 0.02 96.3 0.25 0.01 

City Center 6,164 2.3 0.01 0.00 57.3 0.22 0.01 15.1 0.13 0.01 95.0 0.21 0.01 

Suburban 9,598 2.2 0.01 0.00 62.0 0.27 0.02 14.9 0.12 0.01 95.7 0.20 0.01 

Non-metropolitan 4,845 2.4 0.01 0.00 53.6 0.17 0.02 9.7 0.06 0.01 94.7 0.19 0.01 

Exposure Factors Handbook PageSeptember 2011 9-43
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Cabbage Carrots Citrus Fruits Corn 

Whole Population 20,607 

Age Group 

15.5 0.08 0.01 49.8 0.17 0.00 19.3 0.19 0.01 94.6 0.44 0.01 

Birth to 1 year 1,486 1.0 0.01 0.00 12.3 0.17 0.03 2.5 0.07 0.02 46.0 0.48 0.03 

1 to 2 years 2,096 8.0 0.06 0.01 46.8 0.41 0.02 15.5 0.47 0.05 96.5 1.13 0.05 

3 to 5 years 4,391 8.9 0.07 0.01 46.2 0.34 0.02 18.2 0.50 0.03 98.7 1.24 0.03 

6 to 12 years 2,089 9.5 0.06 0.01 44.4 0.22 0.01 16.0 0.26 0.02 98.9 0.87 0.03 

13 to 19 years 1,222 9.0 0.04 0.01 40.3 0.11 0.01 12.3 0.11 0.02 95.7 0.43 0.02 

20 to 49 years 4,677 16.0 0.07 0.01 50.2 0.14 0.01 18.1 0.12 0.01 94.7 0.32 0.01 

≥50 years 4,646 

Season 

22.8 0.12 0.01 58.1 0.17 0.01 27.1 0.23 0.01 94.2 0.26 0.01 

Fall 4,687 16.2 0.07 0.01 53.9 0.19 0.01 16.6 0.16 0.01 94.2 0.42 0.01 

Spring 5,308 15.1 0.08 0.01 46.5 0.17 0.01 20.3 0.20 0.01 94.5 0.44 0.02 

Summer 5,890 14.5 0.08 0.01 44.3 0.14 0.01 15.8 0.08 0.01 95.1 0.50 0.02 

Winter 4,722 

Race 

16.3 0.08 0.01 54.5 0.18 0.01 24.6 0.33 0.02 94.8 0.41 0.02 

Asian, Pacific Islander 557 33.9 0.24 0.04 59.4 0.28 0.04 23.4 0.35 0.07 85.6 0.32 0.04 

American Indian, Alaskan Native 177 15.8 0.05 0.04 47.3 0.12 0.02 20.4 0.33 0.13 93.6 0.51 0.06 

Black 2,740 15.9 0.14 0.03 36.6 0.10 0.01 13.0 0.15 0.02 93.7 0.49 0.02 

Other/NA 1,638 9.5 0.02 0.01 46.2 0.21 0.02 22.4 0.37 0.06 92.6 0.70 0.05 

White 15,495 

Region 

15.2 0.07 0.00 51.9 0.18 0.01 20.0 0.18 0.01 95.3 0.42 0.01 

Midwest 4,822 15.5 0.08 0.01 50.9 0.17 0.01 18.9 0.16 0.01 96.6 0.46 0.02 

Northeast 3,692 13.4 0.08 0.01 53.8 0.18 0.01 22.4 0.21 0.02 93.3 0.40 0.01 

South 7,208 16.8 0.09 0.01 44.9 0.14 0.01 15.1 0.14 0.01 94.4 0.44 0.01 

West 4,885 

Urbanization 

15.5 0.06 0.01 52.8 0.21 0.01 23.7 0.28 0.02 94.1 0.47 0.02 

City Center 6,164 16.4 0.09 0.01 48.8 0.16 0.01 19.8 0.20 0.01 93.8 0.44 0.01 

Suburban 9,598 16.0 0.07 0.00 52.3 0.19 0.01 20.0 0.19 0.01 94.8 0.45 0.01 

Non-metropolitan 4,845 13.4 0.06 0.01 45.7 0.15 0.01 17.0 0.17 0.01 95.5 0.43 0.02 

Page Exposure Factors Handbook 9-44 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Cucumbers Cucurbits Fruiting Vegetables Leafy Vegetables 

Whole Population 20,607 

Age Group 

40.1 0.10 0.01 48.9 0.40 0.02 93.8 0.82 0.01 90.1 0.59 0.01 

Birth to 1 year 1,486 1.7 0.00 0.00 14.0 0.45 0.04 25.5 0.32 0.04 44.2 0.29 0.05 

1 to 2 years 2,096 20.5 0.11 0.01 31.3 0.72 0.06 92.1 1.56 0.06 82.1 0.71 0.04 

3 to 5 years 4,391 29.3 0.16 0.02 38.7 0.83 0.07 95.4 1.46 0.03 86.9 0.67 0.02 

6 to 12 years 2,089 32.6 0.14 0.02 39.9 0.54 0.06 95.9 1.05 0.03 89.5 0.55 0.03 

13 to 19 years 1,222 41.3 0.11 0.03 46.7 0.32 0.08 96.1 0.79 0.03 90.3 0.43 0.02 

20 to 49 years 4,677 44.8 0.09 0.01 52.8 0.29 0.01 96.0 0.75 0.02 92.2 0.58 0.02 

≥50 years 4,646 

Season 

41.0 0.08 0.01 52.8 0.43 0.03 92.0 0.66 0.02 90.7 0.66 0.02 

Fall 4,687 36.7 0.08 0.01 45.4 0.21 0.01 92.6 0.81 0.03 89.7 0.59 0.02 

Spring 5,308 43.3 0.10 0.01 51.8 0.48 0.04 94.3 0.77 0.02 90.9 0.60 0.02 

Summer 5,890 43.2 0.14 0.02 55.6 0.73 0.06 94.5 0.88 0.02 90.1 0.56 0.02 

Winter 4,722 

Race 

37.2 0.07 0.01 43.0 0.16 0.01 93.7 0.80 0.02 89.6 0.59 0.02 

Asian, Pacific Islander 557 34.9 0.24 0.16 46.9 0.90 0.39 88.4 0.86 0.06 92.8 1.13 0.12 

American Indian, Alaskan Native 177 41.0 0.09 0.03 51.3 0.53 0.13 98.2 0.91 0.08 89.3 0.52 0.17 

Black 2,740 39.1 0.06 0.01 43.4 0.27 0.04 91.9 0.69 0.04 89.5 0.65 0.04 

Other/NA 1,638 33.4 0.10 0.01 46.1 0.53 0.09 93.6 1.25 0.05 85.3 0.50 0.03 

White 15,495 

Region 

40.9 0.10 0.01 50.1 0.39 0.02 94.3 0.80 0.01 90.4 0.56 0.01 

Midwest 4,822 42.1 0.10 0.01 49.6 0.37 0.03 94.8 0.81 0.02 92.1 0.55 0.03 

Northeast 3,692 39.4 0.10 0.01 50.7 0.43 0.05 92.3 0.82 0.02 87.4 0.62 0.03 

South 7,208 39.7 0.09 0.01 46.7 0.33 0.03 93.3 0.76 0.03 90.1 0.55 0.02 

West 4,885 

Urbanization 

39.3 0.11 0.03 50.1 0.50 0.06 94.9 0.91 0.03 90.3 0.64 0.03 

City Center 6,164 39.7 0.09 0.00 48.3 0.34 0.02 93.9 0.84 0.03 89.2 0.64 0.02 

Suburban 9,598 40.6 0.11 0.01 49.9 0.44 0.04 93.5 0.81 0.01 90.5 0.60 0.02 

Non-metropolitan 4,845 39.7 0.10 0.01 47.8 0.37 0.03 94.3 0.80 0.04 90.5 0.46 0.03 

Exposure Factors Handbook PageSeptember 2011 9-45
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Legumes Lettuce Okra Onions 

Whole Population 20,607 

Age Group 

95.5 0.43 0.01 52.2 0.24 0.01 1.4 0.01 0.00 94.9 0.19 0.00 

Birth to 1 year 1,486 51.7 1.21 0.06 1.1 0.00 0.00 0.2 0.00 0.00 32.8 0.07 0.01 

1 to 2 years 2,096 96.9 1.30 0.08 23.3 0.14 0.01 1.3 0.01 0.00 93.0 0.29 0.01 

3 to 5 years 4,391 98.3 0.85 0.06 33.4 0.21 0.01 0.8 0.01 0.00 95.6 0.26 0.01 

6 to 12 years 2,089 98.1 0.48 0.03 41.7 0.22 0.01 1.3 0.01 0.00 96.8 0.20 0.01 

13 to 19 years 1,222 94.9 0.27 0.02 55.2 0.22 0.02 0.8 0.00 0.00 97.3 0.18 0.01 

20 to 49 years 4,677 95.7 0.34 0.01 60.1 0.27 0.01 1.3 0.01 0.00 97.1 0.20 0.01 

≥50 years 4,646 

Season 

96.2 0.40 0.01 51.4 0.23 0.01 2.1 0.01 0.00 93.2 0.16 0.00 

Fall 4,687 96.0 0.44 0.02 50.6 0.23 0.01 1.7 0.01 0.00 95.5 0.20 0.01 

Spring 5,308 95.3 0.40 0.02 54.5 0.25 0.01 1.1 0.01 0.00 95.0 0.19 0.01 

Summer 5,890 95.2 0.43 0.02 51.7 0.23 0.01 1.7 0.01 0.00 94.0 0.18 0.00 

Winter 4,722 

Race 

95.5 0.44 0.02 52.1 0.24 0.01 1.0 0.01 0.00 95.3 0.20 0.01 

Asian, Pacific Islander 557 96.1 0.76 0.09 48.1 0.28 0.05 4.8 0.01 0.01 94.9 0.37 0.03 

American Indian, Alaskan Native 177 97.5 0.42 0.07 61.3 0.21 0.04 0.6 0.00 0.00 99.3 0.25 0.04 

Black 2,740 95.6 0.50 0.04 42.7 0.15 0.01 2.4 0.01 0.00 92.6 0.16 0.01 

Other/NA 1,638 93.5 0.55 0.04 52.1 0.25 0.02 0.6 0.00 0.00 95.0 0.30 0.02 

White 15,495 

Region 

95.6 0.40 0.01 53.8 0.25 0.01 1.2 0.01 0.00 95.3 0.18 0.00 

Midwest 4,822 96.9 0.40 0.02 53.3 0.25 0.02 0.4 0.00 0.00 96.0 0.18 0.01 

Northeast 3,692 93.4 0.38 0.02 49.3 0.24 0.01 0.8 0.00 0.00 94.0 0.18 0.01 

South 7,208 96.1 0.47 0.02 50.7 0.21 0.01 2.6 0.01 0.00 94.1 0.18 0.01 

West 4,885 

Urbanization 

95.0 0.44 0.02 56.0 0.27 0.01 1.2 0.00 0.00 96.1 0.24 0.01 

City Center 6,164 95.1 0.47 0.02 51.3 0.24 0.01 1.8 0.01 0.00 94.8 0.20 0.01 

Suburban 9,598 95.4 0.41 0.01 53.0 0.26 0.01 1.0 0.01 0.00 95.3 0.19 0.01 

Non-metropolitan 4,845 96.2 0.41 0.02 51.6 0.20 0.01 1.7 0.01 0.00 94.3 0.19 0.01 

Page Exposure Factors Handbook 9-46 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Peaches Pears Peas Peppers 

Whole Population 20,607 

Age Group 

40.8 0.11 0.00 8.2 0.09 0.00 22.3 0.11 0.01 83.0 0.06 0.00 

Birth to 1 year 1,486 24.4 0.85 0.08 15.9 0.73 0.07 29.5 0.47 0.04 15.6 0.01 0.00 

1 to 2 years 2,096 50.7 0.47 0.04 17.2 0.40 0.04 28.3 0.34 0.03 77.5 0.05 0.01 

3 to 5 years 4,391 55.4 0.26 0.02 16.6 0.26 0.03 20.5 0.21 0.02 84.6 0.05 0.00 

6 to 12 years 2,089 54.7 0.14 0.02 17.5 0.14 0.01 17.2 0.12 0.01 85.1 0.05 0.00 

13 to 19 years 1,222 39.1 0.06 0.01 5.9 0.03 0.01 14.0 0.07 0.01 84.8 0.04 0.00 

20 to 49 years 4,677 34.5 0.05 0.00 4.4 0.04 0.00 21.3 0.08 0.01 86.9 0.08 0.01 

≥50 years 4,646 

Season 

44.1 0.10 0.01 9.0 0.07 0.01 28.4 0.10 0.01 78.9 0.06 0.01 

Fall 4,687 35.9 0.07 0.01 9.6 0.11 0.01 24.1 0.10 0.01 81.3 0.07 0.01 

Spring 5,308 42.9 0.10 0.01 7.7 0.07 0.00 20.2 0.10 0.01 84.8 0.06 0.00 

Summer 5,890 46.6 0.17 0.01 6.8 0.07 0.01 19.8 0.10 0.01 83.1 0.06 0.00 

Winter 4,722 

Race 

37.9 0.09 0.01 8.7 0.10 0.01 24.9 0.13 0.01 83.0 0.06 0.00 

Asian, Pacific Islander 557 32.2 0.07 0.02 9.2 0.13 0.03 41.0 0.15 0.02 70.9 0.08 0.01 

American Indian, Alaskan Native 177 38.0 0.20 0.06 11.2 0.15 0.06 22.5 0.13 0.03 89.3 0.08 0.02 

Black 2,740 39.4 0.10 0.01 5.6 0.06 0.01 20.9 0.13 0.02 82.8 0.04 0.01 

Other/NA 1,638 35.2 0.13 0.02 8.3 0.11 0.02 19.8 0.07 0.01 81.7 0.12 0.01 

White 15,495 

Region 

41.8 0.11 0.01 8.6 0.09 0.00 21.9 0.10 0.01 83.6 0.06 0.00 

Midwest 4,822 45.3 0.11 0.01 9.1 0.09 0.01 22.1 0.10 0.01 85.6 0.06 0.01 

Northeast 3,692 44.0 0.10 0.01 9.4 0.10 0.01 24.7 0.13 0.02 79.0 0.07 0.01 

South 7,208 35.8 0.11 0.01 6.5 0.07 0.01 19.9 0.10 0.01 82.1 0.05 0.00 

West 4,885 

Urbanization 

41.1 0.11 0.01 8.9 0.10 0.01 24.0 0.10 0.01 85.4 0.08 0.01 

City Center 6,164 39.9 0.11 0.01 8.1 0.09 0.01 24.0 0.12 0.01 83.4 0.07 0.01 

Suburban 9,598 43.1 0.11 0.01 8.8 0.10 0.01 22.3 0.11 0.01 82.2 0.06 0.00 

Non-metropolitan 4,845 37.1 0.10 0.00 7.2 0.06 0.01 19.6 0.09 0.01 84.4 0.06 0.01 

Exposure Factors Handbook PageSeptember 2011 9-47
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Pome Fruit Pumpkins Root Tuber Vegetables Stalk, Stem Vegetables 

Whole Population 20,607 

Age Group 

34.7 0.54 0.01 1.8 0.01 0.00 99.2 1.42 0.02 19.4 0.05 0.00 

Birth to 1 year 1,486 40.0 3.04 0.17 0.3 0.00 0.00 61.7 2.60 0.15 1.9 0.01 0.00 

1 to 2 years 2,096 52.0 2.19 0.10 0.7 0.01 0.00 99.6 3.38 0.09 13.2 0.06 0.01 

3 to 5 years 4,391 51.7 1.90 0.06 0.9 0.01 0.00 100.0 2.96 0.07 10.9 0.04 0.00 

6 to 12 years 2,089 47.9 0.97 0.06 1.8 0.01 0.00 100.0 2.09 0.07 10.7 0.03 0.01 

13 to 19 years 1,222 26.5 0.23 0.02 1.3 0.01 0.00 99.9 1.36 0.06 16.6 0.03 0.01 

20 to 49 years 4,677 27.9 0.25 0.01 1.7 0.00 0.00 99.7 1.12 0.02 24.5 0.05 0.00 

≥50 years 4,646 

Season 

39.0 0.39 0.02 2.3 0.01 0.00 99.7 1.13 0.02 18.3 0.05 0.00 

Fall 4,687 39.5 0.66 0.04 4.9 0.01 0.00 99.4 1.49 0.04 18.5 0.04 0.00 

Spring 5,308 33.6 0.52 0.03 0.4 0.00 0.00 99.3 1.41 0.03 20.1 0.05 0.00 

Summer 5,890 29.1 0.41 0.02 0.7 0.00 0.00 99.2 1.34 0.03 17.0 0.03 0.00 

Winter 4,722 

Race 

36.7 0.56 0.03 1.0 0.00 0.00 99.0 1.45 0.04 21.8 0.06 0.01 

Asian, Pacific Islander 557 36.5 0.66 0.08 1.0 0.00 0.00 97.3 1.31 0.10 36.5 0.11 0.01 

American Indian, Alaskan Native 177 39.5 0.75 0.14 1.2 0.00 0.00 99.7 1.71 0.30 21.6 0.05 0.02 

Black 2,740 24.8 0.42 0.03 0.5 0.00 0.00 99.0 1.31 0.09 8.1 0.01 0.00 

Other/NA 1,638 32.7 0.67 0.06 3.5 0.01 0.00 98.0 1.47 0.05 14.5 0.03 0.00 

White 15,495 

Region 

36.4 0.54 0.01 1.9 0.01 0.00 99.4 1.44 0.02 20.9 0.05 0.00 

Midwest 4,822 38.9 0.55 0.03 2.4 0.01 0.00 99.5 1.57 0.05 22.1 0.05 0.00 

Northeast 3,692 37.3 0.57 0.02 2.0 0.01 0.00 99.4 1.33 0.05 17.2 0.05 0.01 

South 7,208 28.9 0.43 0.02 1.1 0.00 0.00 99.2 1.40 0.04 16.4 0.04 0.00 

West 4,885 

Urbanization 

37.2 0.65 0.03 1.9 0.01 0.00 98.8 1.38 0.05 23.1 0.06 0.00 

City Center 6,164 33.2 0.51 0.02 1.5 0.00 0.00 99.0 1.34 0.04 19.6 0.05 0.00 

Suburban 9,598 37.6 0.59 0.02 1.8 0.00 0.00 99.3 1.44 0.03 20.0 0.05 0.00 

Non-metropolitan 4,845 30.7 0.45 0.03 2.0 0.01 0.00 99.4 1.52 0.06 17.8 0.04 0.00 

Page Exposure Factors Handbook 9-48 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Strawberries Stone Fruit Tomatoes Tropical Fruits 

Whole Population 20,607 

Age Group 

32.4 0.06 0.00 44.5 0.17 0.01 84.4 0.74 0.01 58.3 0.43 0.01 

Birth to 1 year 1,486 6.8 0.02 0.00 29.2 1.15 0.10 21.5 0.30 0.03 42.2 1.31 0.07 

1 to 2 years 2,096 33.5 0.19 0.03 53.6 0.60 0.04 80.7 1.50 0.05 70.1 1.97 0.10 

3 to 5 years 4,391 37.1 0.14 0.01 57.5 0.38 0.02 85.7 1.40 0.03 69.7 1.10 0.04 

6 to 12 years 2,089 37.3 0.10 0.01 56.8 0.23 0.02 86.9 1.00 0.03 67.0 0.50 0.04 

13 to 19 years 1,222 26.8 0.05 0.01 41.1 0.09 0.01 90.2 0.74 0.03 54.5 0.19 0.02 

20 to 49 years 4,677 29.8 0.05 0.00 38.1 0.09 0.01 87.1 0.66 0.01 52.8 0.27 0.01 

≥50 years 4,646 

Season 

37.7 0.06 0.00 49.4 0.17 0.01 80.1 0.57 0.01 63.1 0.41 0.01 

Fall 4,687 26.8 0.03 0.00 39.3 0.11 0.01 83.5 0.73 0.03 56.5 0.42 0.02 

Spring 5,308 36.8 0.11 0.01 46.8 0.17 0.01 84.3 0.69 0.02 59.4 0.43 0.02 

Summer 5,890 36.1 0.06 0.01 50.3 0.28 0.02 85.1 0.80 0.02 58.2 0.41 0.02 

Winter 4,722 

Race 

29.9 0.05 0.01 41.6 0.12 0.01 84.5 0.72 0.02 58.9 0.45 0.02 

Asian, Pacific Islander 557 23.9 0.07 0.03 36.5 0.16 0.04 74.1 0.73 0.06 55.4 0.61 0.07 

American Indian, Alaskan Native 177 28.2 0.03 0.02 39.2 0.24 0.07 89.2 0.82 0.07 54.1 0.43 0.05 

Black 2,740 21.1 0.02 0.00 40.7 0.14 0.02 78.1 0.63 0.03 53.6 0.36 0.03 

Other/NA 1,638 22.3 0.05 0.01 38.2 0.19 0.03 89.6 1.11 0.05 60.9 0.77 0.09 

White 15,495 

Region 

35.3 0.07 0.00 45.9 0.17 0.01 85.4 0.73 0.01 59.0 0.41 0.01 

Midwest 4,822 34.9 0.07 0.01 49.9 0.18 0.01 85.5 0.74 0.02 60.1 0.40 0.03 

Northeast 3,692 37.1 0.06 0.01 47.5 0.15 0.01 83.4 0.73 0.02 62.4 0.47 0.02 

South 7,208 27.2 0.05 0.00 38.9 0.15 0.01 82.7 0.69 0.02 53.1 0.36 0.02 

West 4,885 

Urbanization 

33.9 0.08 0.01 44.8 0.20 0.01 86.6 0.81 0.02 60.8 0.53 0.03 

City Center 6,164 29.7 0.05 0.01 43.5 0.17 0.01 84.1 0.75 0.02 58.8 0.46 0.02 

Suburban 9,598 36.2 0.08 0.00 46.9 0.18 0.01 84.5 0.73 0.01 60.2 0.44 0.01 

Non-metropolitan 4,845 28.1 0.05 0.01 40.6 0.15 0.01 84.4 0.73 0.03 53.0 0.34 0.03 

Exposure Factors Handbook PageSeptember 2011 9-49
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-16. Per Capita Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

(continued) 

Population Group N Percent 

Consuming Mean SE 

White Potatoes 

Whole Population 20,607 

Age Group 

91.3 0.89 0.02 

Birth to 1 year 1,486 39.9 0.64 0.07 

1 to 2 years 2,096 91.2 1.95 0.08 

3 to 5 years 4,391 95.1 1.75 0.06 

6 to 12 years 2,089 93.9 1.21 0.06 

13 to 19 years 1,222 92.6 0.93 0.05 

20 to 49 years 4,677 91.5 0.74 0.02 

≥50 years 4,646 

Season 

91.7 0.72 0.02 

Fall 4,687 91.5 0.91 0.04 

Spring 5,308 91.3 0.87 0.03 

Summer 5,890 91.3 0.86 0.03 

Winter 4,722 

Race 

91.1 0.90 0.03 

Asian, Pacific Islander 557 82.3 0.72 0.09 

American Indian, Alaskan Native 177 92.7 1.29 0.32 

Black 2,740 88.5 0.81 0.07 

Other/NA 1,638 86.5 0.86 0.07 

White 15,495 

Region 

92.4 0.90 0.02 

Midwest 4,822 94.5 1.00 0.03 

Northeast 3,692 88.6 0.79 0.04 

South 7,208 91.8 0.90 0.04 

West 4,885 

Urbanization 

89.6 0.82 0.06 

City Center 6,164 89.5 0.81 0.04 

Suburban 9,598 91.2 0.87 0.02 

Non-metropolitan 4,845 94.2 1.02 0.06 

N = Sample size. 

SE = Standard error. 

Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and vegetables with higher 

percentages consuming. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Page Exposure Factors Handbook 9-50 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Apples Asparagus Bananas Beans Beets 

Whole Population 

Age Group 

7,193 1.47 0.03 233 0.85 0.04 10,734 0.73 0.02 9,086 0.60 0.01 374 0.35 0 

Birth to 1 year 496 6.71 0.31 3 2.59 1.16 605 3.04 0.12 313 2.00 0.16 6 1.42 0.9 

1 to 2 years 947 4.00 0.15 19 1.99 0.54 1,328 2.82 0.12 996 1.63 0.08 13 0.98 0.3 

3 to 5 years 1,978 3.68 0.08 23 1.37 0.32 2,746 1.54 0.06 1,909 1.22 0.04 36 0.9 0.2 

6 to 12 years 792 2.17 0.12 13 1.77 0.43 1,214 0.66 0.05 833 0.82 0.05 16 0.66 0.3 

13 to 19 years 271 0.90 0.06 4 0.56 0.08 511 0.30 0.04 472 0.49 0.03 9 0.2 0.1 

20 to 49 years 1,171 0.82 0.03 58 0.79 0.08 1,887 0.50 0.01 2,153 0.48 0.01 93 0.23 0 

≥ 50 years 

Season 

1,538 0.92 0.04 113 0.77 0.07 2,443 0.65 0.02 2,410 0.52 0.02 201 0.38 0 

Fall 1,841 1.57 0.06 44 0.80 0.13 2,292 0.79 0.04 2,122 0.60 0.02 90 0.25 0 

Spring 1,818 1.52 0.07 91 0.90 0.07 2,856 0.70 0.03 2,311 0.59 0.02 92 0.45 0.1 

Summer 1,801 1.32 0.06 36 0.66 0.12 3,124 0.66 0.03 2,539 0.65 0.02 104 0.34 0.1 

Winter 

Race 

1,733 1.44 0.05 62 0.94 0.10 2,462 0.80 0.03 2,114 0.57 0.02 88 0.33 0.1 

Asian, Pacific Islander 182 1.59 0.12 5 0.62 0.15 265 0.95 0.10 265 0.48 0.05 16 0.04 0 

American Indian, Alaskan Native 58 1.93 0.27 2 0.81 - 88 0.87 0.15 74 0.70 0.12 1 0.02 -

Black 762 1.62 0.12 8 1.01 0.64 1,288 0.59 0.05 1,205 0.71 0.04 18 0.29 0.1 

Other/NA 536 2.00 0.13 5 0.31 0.09 865 1.21 0.11 911 0.71 0.04 16 0.39 0.2 

White 

Region 

5,655 1.42 0.03 213 0.86 0.05 8,228 0.71 0.02 6,631 0.58 0.01 323 0.36 0 

Midwest 1,792 1.35 0.06 63 0.91 0.08 2,589 0.68 0.04 2,071 0.59 0.02 90 0.35 0.1 

Northeast 1,385 1.46 0.05 43 0.72 0.10 2,122 0.68 0.02 1,342 0.56 0.02 78 0.42 0.1 

South 2,201 1.44 0.05 64 1.07 0.09 3,356 0.70 0.04 3,465 0.68 0.02 99 0.29 0 

West 

Urbanization 

1,815 1.67 0.06 63 0.69 0.04 2,667 0.89 0.03 2,208 0.52 0.03 107 0.33 0.1 

City Center 2,091 1.46 0.05 81 0.85 0.07 3,182 0.75 0.03 2,840 0.62 0.02 110 0.28 0 

Suburban 3,647 1.49 0.05 97 0.78 0.07 5,303 0.75 0.02 3,957 0.58 0.01 171 0.39 0.1 

Non-metropolitan 1,455 1.45 0.03 55 0.98 0.11 2,249 0.67 0.04 2,289 0.61 0.01 93 0.35 0 

Exposure Factors Handbook PageSeptember 2011 9-51
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Berries and Small Fruits Broccoli Bulb Vegetables Cabbage Carrots 

Whole Population 

Age Group 

12,206 0.40 0.01 2,474 0.80 0.03 18,738 0.21 0.00 2,633 0.50 0.03 9,513 0.34 0.01 

Birth to 1 year 229 0.81 0.07 49 2.09 0.33 489 0.22 0.02 15 0.61 0.41 179 1.39 0.20 

1 to 2 years 1,396 1.38 0.06 242 2.11 0.16 1,957 0.32 0.01 160 0.73 0.11 999 0.87 0.05 

3 to 5 years 3,166 0.99 0.04 475 1.67 0.09 4,207 0.28 0.01 369 0.78 0.07 2,048 0.74 0.03 

6 to 12 years 1,523 0.54 0.04 213 1.29 0.16 2,040 0.22 0.01 190 0.63 0.11 904 0.50 0.03 

13 to 19 years 679 0.27 0.03 102 0.69 0.07 1,194 0.20 0.01 106 0.40 0.06 482 0.27 0.02 

20 to 49 years 2,393 0.27 0.02 640 0.68 0.04 4,546 0.22 0.01 746 0.45 0.03 2,289 0.28 0.01 

≥ 50 years 

Season 

2,820 0.31 0.01 753 0.63 0.03 4,305 0.18 0.00 1,047 0.52 0.02 2,612 0.29 0.01 

Fall 2,706 0.31 0.02 582 0.81 0.05 4,310 0.22 0.01 623 0.44 0.03 2,338 0.35 0.02 

Spring 3,202 0.45 0.03 651 0.82 0.07 4,835 0.21 0.01 684 0.52 0.03 2,345 0.36 0.02 

Summer 3,558 0.48 0.02 660 0.79 0.05 5,280 0.20 0.01 676 0.56 0.07 2,440 0.33 0.01 

Winter 

Race 

2,740 0.35 0.02 581 0.76 0.07 4,313 0.22 0.01 650 0.48 0.04 2,390 0.34 0.01 

Asian, Pacific Islander 252 0.66 0.13 118 0.89 0.12 481 0.40 0.03 152 0.69 0.09 329 0.47 0.05 

American Indian, Alaskan Native 85 0.26 0.04 16 1.18 0.43 169 0.25 0.04 18 0.34 0.13 82 0.26 0.03 

Black 1,430 0.27 0.02 286 1.06 0.12 2,438 0.18 0.01 359 0.87 0.11 958 0.28 0.02 

Other/NA 782 0.45 0.06 131 1.09 0.10 1,484 0.33 0.02 144 0.24 0.05 749 0.45 0.03 

White 

Region 

9,657 0.41 0.01 1,923 0.73 0.03 14,166 0.20 0.00 1,960 0.43 0.02 7,395 0.34 0.01 

Midwest 3,042 0.40 0.03 533 0.66 0.03 4,457 0.20 0.01 629 0.49 0.04 2,313 0.34 0.02 

Northeast 2,383 0.37 0.03 511 0.84 0.07 3,324 0.20 0.01 413 0.56 0.06 1,843 0.34 0.01 

South 3,896 0.35 0.02 810 0.83 0.04 6,497 0.19 0.01 978 0.52 0.06 2,981 0.31 0.01 

West 

Urbanization 

2,885 0.48 0.03 620 0.83 0.08 4,460 0.26 0.01 613 0.41 0.03 2,376 0.40 0.01 

City Center 3,525 0.38 0.02 741 0.83 0.06 5,547 0.22 0.01 794 0.58 0.07 2,759 0.34 0.01 

Suburban 6,039 0.44 0.02 1,283 0.81 0.03 8,768 0.21 0.01 1,251 0.45 0.02 4,690 0.36 0.01 

Non-metropolitan 2,642 0.31 0.03 450 0.64 0.05 4,423 0.20 0.01 588 0.48 0.04 2,064 0.32 0.01 

Page Exposure Factors Handbook 9-52 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Citrus Fruits Corn Cucumbers Cucurbits Fruiting Vegetables 

Whole Population 

Age Group 

3,656 0.99 0.03 19,059 0.47 0.01 6,779 0.24 0.02 8,763 0.81 0.04 18,407 0.87 0.01 

Birth to 1 year 37 2.79 0.53 671 1.05 0.07 25 0.28 0.11 213 3.19 0.29 371 1.24 0.11 

1 to 2 years 336 3.06 0.20 2,027 1.17 0.05 439 0.52 0.05 682 2.29 0.17 1,927 1.70 0.06 

3 to 5 years 751 2.75 0.15 4,334 1.26 0.03 1,266 0.56 0.05 1,694 2.15 0.17 4,180 1.53 0.03 

6 to 12 years 324 1.60 0.12 2,064 0.88 0.03 667 0.43 0.06 833 1.34 0.15 2,014 1.10 0.03 

13 to 19 years 157 0.90 0.15 1,176 0.45 0.01 500 0.26 0.06 563 0.69 0.16 1,176 0.82 0.03 

20 to 49 years 841 0.68 0.04 4,415 0.34 0.01 2,033 0.20 0.01 2,400 0.55 0.03 4,489 0.78 0.02 

≥ 50 years 

Season 

1,210 0.84 0.03 4,372 0.28 0.01 1,849 0.21 0.01 2,378 0.81 0.05 4,250 0.71 0.02 

Fall 761 0.93 0.06 4,342 0.44 0.01 1,374 0.22 0.02 1,778 0.46 0.03 4,186 0.87 0.03 

Spring 1,002 0.97 0.05 4,909 0.47 0.02 1,906 0.23 0.01 2,408 0.94 0.07 4,755 0.82 0.02 

Summer 815 0.53 0.04 5,423 0.52 0.02 2,070 0.32 0.05 2,855 1.32 0.10 5,262 0.93 0.02 

Winter 

Race 

1,078 1.32 0.06 4,385 0.44 0.02 1,429 0.20 0.02 1,722 0.36 0.03 4,204 0.85 0.03 

Asian, Pacific Islander 117 1.50 0.19 454 0.37 0.05 134 0.68 0.43 217 1.92 0.79 439 0.98 0.06 

American Indian, Alaskan Native 41 1.61 0.17 165 0.55 0.06 60 0.23 0.06 75 1.04 0.32 162 0.93 0.08 

Black 369 1.15 0.08 2,502 0.52 0.02 858 0.17 0.01 987 0.62 0.08 2,398 0.75 0.04 

Other/NA 347 1.66 0.16 1,475 0.76 0.05 413 0.30 0.03 633 1.14 0.19 1,447 1.34 0.05 

White 

Region 

2,782 0.89 0.03 14,463 0.44 0.01 5,314 0.24 0.01 6,851 0.77 0.03 13,961 0.85 0.01 

Midwest 842 0.84 0.06 4,562 0.48 0.02 1,693 0.23 0.02 2,091 0.75 0.05 4,379 0.85 0.02 

Northeast 754 0.94 0.06 3,377 0.43 0.01 1,191 0.25 0.02 1,614 0.85 0.08 3,254 0.88 0.02 

South 998 0.94 0.04 6,648 0.46 0.01 2,356 0.22 0.02 2,905 0.70 0.06 6,416 0.81 0.03 

West 

Urbanization 

1,062 1.20 0.07 4,472 0.49 0.02 1,539 0.29 0.07 2,153 0.99 0.12 4,358 0.96 0.03 

City Center 1,146 1.01 0.04 5,641 0.47 0.01 1,965 0.22 0.01 2,570 0.71 0.05 5,477 0.89 0.03 

Suburban 1,738 0.97 0.04 8,886 0.47 0.01 3,151 0.26 0.03 4,119 0.89 0.07 8,563 0.86 0.01 

Non-metropolitan 772 0.99 0.07 4,532 0.45 0.02 1,663 0.25 0.03 2,074 0.78 0.06 4,367 0.85 0.04 

Exposure Factors Handbook PageSeptember 2011 9-53
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Leafy Vegetables Legumes Lettuce Okra Onions 

Whole Population 

Age Group 

17,637 0.65 0.01 19,258 0.45 0.01 8,430 0.46 0.01 272 0.51 0.04 18,678 0.20 0.00 

Birth to 1 year 639 0.65 0.11 754 2.34 0.11 15 0.17 0.02 4 1.50 0.54 481 0.22 0.02 

1 to 2 years 1,729 0.87 0.05 2,037 1.34 0.08 481 0.58 0.04 29 0.64 0.19 1,948 0.31 0.01 

3 to 5 years 3,815 0.77 0.03 4,308 0.86 0.06 1,415 0.62 0.03 34 1.16 0.32 4,200 0.27 0.01 

6 to 12 years 1,860 0.62 0.03 2,045 0.49 0.03 858 0.53 0.02 21 0.62 0.15 2,030 0.21 0.01 

13 to 19 years 1,101 0.47 0.02 1,168 0.29 0.02 669 0.40 0.03 12 0.43 0.13 1,190 0.19 0.01 

20 to 49 years 4,308 0.63 0.02 4,477 0.36 0.01 2,693 0.45 0.01 62 0.44 0.06 4,533 0.21 0.01 

≥ 50 years 

Season 

4,185 0.72 0.02 4,469 0.41 0.01 2,299 0.45 0.01 110 0.50 0.05 4,296 0.17 0.00 

Fall 4,046 0.66 0.03 4,412 0.46 0.02 1,894 0.46 0.02 58 0.39 0.04 4,300 0.21 0.01 

Spring 4,579 0.66 0.02 4,952 0.42 0.02 2,279 0.46 0.02 66 0.47 0.09 4,815 0.20 0.01 

Summer 4,964 0.62 0.02 5,476 0.45 0.02 2,325 0.45 0.01 106 0.65 0.08 5,265 0.19 0.01 

Winter 

Race 

4,048 0.66 0.02 4,418 0.46 0.02 1,932 0.46 0.02 42 0.53 0.13 4,298 0.21 0.01 

Asian, Pacific Islander 469 1.22 0.12 503 0.79 0.09 191 0.58 0.09 15 0.20 0.06 480 0.39 0.03 

American Indian, Alaskan Native 151 0.59 0.19 170 0.44 0.08 88 0.34 0.04 2 0.40 - 169 0.25 0.04 

Black 2,367 0.73 0.04 2,563 0.52 0.04 884 0.35 0.02 67 0.63 0.08 2,431 0.17 0.01 

Other/NA 1,329 0.59 0.04 1,478 0.58 0.05 643 0.49 0.04 15 0.70 0.25 1,484 0.32 0.02 

White 

Region 

13,321 0.62 0.01 14,544 0.42 0.01 6,624 0.47 0.01 173 0.51 0.05 14,114 0.19 0.00 

Midwest 4,226 0.60 0.03 4,577 0.41 0.02 2,035 0.47 0.03 24 0.42 0.20 4,448 0.19 0.01 

Northeast 3,081 0.71 0.03 3,421 0.40 0.02 1,396 0.49 0.02 22 0.50 0.18 3,308 0.19 0.01 

South 6,174 0.61 0.02 6,771 0.49 0.02 2,830 0.41 0.02 178 0.58 0.05 6,479 0.19 0.01 

West 

Urbanization 

4,156 0.71 0.04 4,489 0.47 0.03 2,169 0.49 0.03 48 0.30 0.07 4,443 0.25 0.01 

City Center 5,232 0.72 0.03 5,735 0.50 0.02 2,414 0.46 0.02 96 0.49 0.07 5,531 0.21 0.01 

Suburban 8,220 0.67 0.02 8,950 0.43 0.02 3,999 0.49 0.01 102 0.59 0.07 8,739 0.20 0.01 

Non-metropolitan 4,185 0.51 0.03 4,573 0.43 0.02 2,017 0.39 0.02 74 0.42 0.04 4,408 0.20 0.01 

Page Exposure Factors Handbook 9-54 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Peaches Pears Peas Peppers Pome Fruit 

Whole Population 

Age Group 

9,069 0.26 0.01 2,355 1.06 0.04 4,661 0.48 0.02 16,093 0.08 0.00 8,316 1.55 0.03 

Birth to 1 year 344 3.47 0.28 217 4.55 0.28 417 1.60 0.09 224 0.05 0.01 572 7.60 0.34 

1 to 2 years 1,067 0.93 0.08 354 2.33 0.16 609 1.21 0.06 1,627 0.06 0.01 1,097 4.21 0.13 

3 to 5 years 2,461 0.48 0.03 711 1.59 0.12 888 1.02 0.07 3,706 0.06 0.00 2,291 3.68 0.08 

6 to 12 years 1,150 0.26 0.03 382 0.81 0.07 346 0.68 0.06 1,784 0.05 0.01 1,012 2.03 0.10 

13 to 19 years 480 0.15 0.03 72 0.45 0.09 168 0.48 0.06 1,041 0.05 0.00 320 0.87 0.06 

20 to 49 years 1,544 0.14 0.01 205 0.80 0.05 959 0.37 0.02 4,068 0.09 0.01 1,274 0.88 0.03 

≥ 50 years 

Season 

2,023 0.22 0.01 414 0.81 0.04 1,274 0.37 0.02 3,643 0.08 0.01 1,750 1.00 0.03 

Fall 1,841 0.20 0.02 596 1.15 0.08 1,172 0.43 0.02 3,643 0.08 0.01 2,102 1.67 0.07 

Spring 2,439 0.23 0.02 590 0.86 0.05 1,120 0.51 0.03 4,212 0.07 0.01 2,102 1.54 0.06 

Summer 2,815 0.37 0.02 585 1.05 0.06 1,213 0.48 0.02 4,568 0.08 0.01 2,092 1.40 0.06 

Winter 

Race 

1,974 0.22 0.02 584 1.14 0.09 1,156 0.52 0.04 3,670 0.07 0.01 2,020 1.53 0.06 

Asian, Pacific Islander 200 0.23 0.04 56 1.43 0.21 192 0.35 0.04 344 0.11 0.01 209 1.82 0.14 

American Indian, Alaskan Native 68 0.54 0.17 23 1.31 0.60 51 0.59 0.10 144 0.09 0.03 73 1.89 0.29 

Black 1,146 0.25 0.03 244 1.09 0.15 612 0.64 0.05 2,150 0.05 0.01 878 1.68 0.12 

Other/NA 590 0.38 0.07 171 1.39 0.22 323 0.38 0.04 1,233 0.15 0.01 624 2.05 0.14 

White 

Region 

7,065 0.26 0.01 1,861 1.02 0.04 3,483 0.48 0.02 12,222 0.07 0.00 6,532 1.48 0.03 

Midwest 2,283 0.25 0.02 625 0.96 0.06 1,108 0.46 0.02 3,920 0.07 0.01 2,094 1.42 0.07 

Northeast 1,778 0.22 0.02 470 1.04 0.06 923 0.52 0.05 2,711 0.08 0.01 1,598 1.54 0.05 

South 2,849 0.30 0.02 648 1.08 0.10 1,526 0.51 0.03 5,579 0.06 0.01 2,535 1.50 0.05 

West 

Urbanization 

2,159 0.26 0.02 612 1.17 0.08 1,104 0.43 0.04 3,883 0.10 0.01 2,089 1.74 0.07 

City Center 2,640 0.27 0.02 686 1.06 0.06 1,480 0.50 0.03 4,780 0.09 0.01 2,408 1.54 0.05 

Suburban 4,457 0.26 0.01 1,205 1.12 0.06 2,179 0.48 0.03 7,436 0.07 0.00 4,224 1.58 0.06 

Non-metropolitan 1,972 0.27 0.01 464 0.89 0.05 1,002 0.45 0.04 3,877 0.07 0.01 1,684 1.48 0.03 

Exposure Factors Handbook PageSeptember 2011 9-55
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE 

Pumpkins Root Tuber Vegetables Stalk, Stem Vegetables Strawberries Stone Fruit 

Whole Population 

Age Group 

299 0.30 0.02 19,997 1.44 0.02 3,095 0.24 0.01 6,675 0.20 0.01 9,786 0.38 0.01 

Birth to 1 year 3 1.06 0.71 916 4.21 0.19 24 0.56 0.22 96 0.26 0.06 418 3.95 0.25 

1 to 2 years 15 1.08 0.51 2,087 3.40 0.09 272 0.48 0.05 729 0.57 0.08 1,130 1.13 0.08 

3 to 5 years 36 0.56 0.10 4,388 2.96 0.07 502 0.38 0.03 1,710 0.38 0.03 2,556 0.66 0.03 

6 to 12 years 37 0.52 0.11 2,089 2.09 0.07 218 0.32 0.04 783 0.28 0.02 1,194 0.41 0.03 

13 to 19 years 14 0.42 0.16 1,221 1.36 0.06 190 0.20 0.03 326 0.18 0.03 508 0.21 0.03 

20 to 49 years 89 0.24 0.02 4,664 1.12 0.02 1,079 0.20 0.01 1,330 0.15 0.02 1,715 0.23 0.01 

≥ 50 years 

Season 

105 0.22 0.01 4,632 1.14 0.02 810 0.27 0.02 1,701 0.15 0.01 2,265 0.34 0.02 

Fall 193 0.29 0.02 4,565 1.50 0.04 720 0.22 0.02 1,250 0.13 0.01 1,987 0.27 0.02 

Spring 22 0.65 0.18 5,151 1.43 0.03 825 0.25 0.01 1,911 0.30 0.03 2,627 0.35 0.02 

Summer 40 0.22 0.06 5,690 1.35 0.03 796 0.20 0.01 2,060 0.17 0.02 3,029 0.56 0.03 

Winter 

Race 

44 0.25 0.04 4,591 1.46 0.03 754 0.26 0.02 1,454 0.16 0.02 2,143 0.29 0.02 

Asian, Pacific Islander 4 0.33 0.07 518 1.35 0.10 158 0.29 0.03 149 0.29 0.11 218 0.44 0.08 

American Indian, Alaskan Native 3 0.11 0.01 174 1.71 0.30 32 0.25 0.05 50 0.11 0.04 73 0.60 0.18 

Black 12 0.34 0.05 2,642 1.32 0.09 188 0.18 0.03 550 0.11 0.02 1,184 0.34 0.04 

Other/NA 43 0.21 0.08 1,561 1.50 0.05 172 0.21 0.02 367 0.22 0.06 649 0.50 0.08 

White 

Region 

237 0.31 0.02 15,102 1.45 0.02 2,545 0.24 0.01 5,559 0.20 0.01 7,662 0.38 0.01 

Midwest 87 0.31 0.01 4,709 1.58 0.05 883 0.22 0.02 1,668 0.20 0.01 2,469 0.36 0.02 

Northeast 62 0.30 0.09 3,598 1.34 0.05 467 0.26 0.03 1,381 0.16 0.02 1,912 0.32 0.02 

South 70 0.28 0.03 6,998 1.41 0.04 908 0.24 0.02 1,952 0.18 0.02 3,060 0.39 0.02 

West 

Urbanization 

80 0.30 0.05 4,692 1.40 0.05 837 0.24 0.02 1,674 0.23 0.03 2,345 0.45 0.03 

City Center 76 0.31 0.05 5,961 1.36 0.04 891 0.25 0.02 1,772 0.18 0.02 2,845 0.38 0.02 

Suburban 137 0.26 0.02 9,315 1.45 0.03 1,492 0.23 0.01 3,517 0.22 0.01 4,808 0.38 0.02 

Non-metropolitan 86 0.36 0.04 4,721 1.53 0.07 712 0.24 0.02 1,386 0.17 0.03 2,133 0.36 0.01 

Page Exposure Factors Handbook 9-56 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Table 9-17. Consumer-Only Intake of Individual Fruits and Vegetables Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Mean SE N Mean SE N Mean SE 

Tomatoes Tropical Fruits White Potatoes 

Whole Population 

Age Group 

16,403 0.87 0.01 12,539 0.73 0.02 18,261 0.97 0.02 

Birth to 1 year 315 1.42 0.13 630 3.09 0.12 577 1.60 0.15 

1 to 2 years 1,684 1.86 0.06 1,476 2.81 0.12 1,918 2.14 0.09 

3 to 5 years 3,764 1.63 0.03 3,106 1.57 0.05 4,147 1.84 0.06 

6 to 12 years 1,832 1.15 0.03 1,407 0.75 0.05 1,963 1.29 0.06 

13 to 19 years 1,098 0.82 0.03 652 0.35 0.04 4,271 0.81 0.02 

20 to 49 years 4,053 0.75 0.02 2,428 0.51 0.02 2,664 0.75 0.02 

≥ 50 years 

Season 

3,657 0.72 0.01 2,840 0.64 0.02 4,254 0.78 0.02 

Fall 3,732 0.87 0.03 2,748 0.75 0.03 4,205 1.00 0.04 

Spring 4,173 0.82 0.02 3,291 0.72 0.03 4,703 0.96 0.03 

Summer 4,731 0.94 0.02 3,595 0.70 0.02 5,190 0.94 0.03 

Winter 

Race 

3,767 0.86 0.03 2,905 0.77 0.03 4,163 0.99 0.03 

Asian, Pacific Islander 373 0.99 0.08 314 1.10 0.13 428 0.88 0.09 

American Indian, Alaskan Native 146 0.92 0.08 103 0.79 0.12 162 1.40 0.33 

Black 2,017 0.80 0.04 1,541 0.67 0.05 2,365 0.92 0.08 

Other/NA 1,369 1.24 0.05 1,034 1.26 0.10 1,353 1.00 0.06 

White 

Region 

12,498 0.85 0.01 9,547 0.69 0.02 13,953 0.98 0.02 

Midwest 3,915 0.87 0.02 2,989 0.67 0.04 4,436 1.06 0.04 

Northeast 2,906 0.88 0.02 2,412 0.75 0.02 3,199 0.90 0.03 

South 5,629 0.83 0.02 4,016 0.67 0.03 6,415 0.98 0.04 

West 

Urbanization 

3,953 0.93 0.02 3,122 0.87 0.03 4,211 0.92 0.06 

City Center 4,867 0.89 0.02 3,750 0.79 0.03 5,337 0.91 0.04 

Suburban 7,647 0.87 0.01 6,092 0.73 0.02 8,488 0.96 0.02 

Non-metropolitan 3,889 0.86 0.03 2,697 0.64 0.05 4,436 1.08 0.06 

N = Sample size. 

SE = Standard error. 

Note: Data for fruits and vegetables for which only small percentages of the population reported consumption may be less reliable than data for fruits and vegetables 

with higher percentages consuming. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook PageSeptember 2011 9-57
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 9-58 September 2011 

Table 9-18. Per Capita Intake of Exposed Fruits Based on 1994−1996 CSFII (g/kg-day, as-consumed) 

Population 

Group 

Percent 

consuming Mean SE 

Percentile 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 0 to 5 months 

 6 to 12 months 

 <1 years 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Urbanization 

 Central City 

 Non­

 Suburban 

Race 

 Asian 

 Black 

 Native American 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

39.9 

32.8 

79.9 

54.9 

69.2 

59.8 

50 

32.7 

29.6 

40 

51.6 

40.7 

40.4 

39.7 

38.6 

39.6 

33.6 

42.9 

41.6 

29 

33.2 

38.2 

41.7 

42.2 

45.3 

33.3 

42.9 

1.5 

6.4 

14.1 

10.0 

10.9 

5.6 

2.2 

0.87 

0.58 

0.69 

0.97 

1.6 

1.5 

1.5 

1.5 

1.6 

1.1 

1.6 

1.7 

1.3 

1.2 

1.9 

1.5 

1.5 

1.8 

1.3 

1.6 

0.06 

1.6 

1.2 

1.0 

0.47 

0.28 

0.14 

0.09 

0.05 

0.03 

0.06 

0.11 

0.10 

0.11 

0.12 

0.11 

0.10 

0.08 

0.35 

0.17 

0.57 

0.29 

0.06 

0.11 

0.13 

0.10 

0.12 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

4.5 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

11.8 

4.5 

5.7 

2.7 

0 

0 

0 

0 

0.11 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1.3 

6.9 

19.3 

16.5 

15.7 

8.1 

3.1 

1.1 

0.60 

0.94 

1.3 

1.4 

1.3 

1.3 

1.2 

1.4 

0.8 

1.4 

1.8 

0.67 

0.99 

1.4 

1.3 

1.4 

1.5 

0.86 

1.6 

3.8 

23.7 

32.7 

30.1 

29.4 

15.8 

6.3 

2.9 

2.0 

2.2 

2.8 

4.0 

3.8 

3.7 

3.4 

4.3 

2.8 

3.9 

5.0 

3.3 

3.8 

4.3 

3.7 

3.7 

4.5 

3.2 

4.2 

7.0 

40.2 

37.1 

38.8 

39.0 

22.2 

8.8 

4.9 

3.1 

3.3 

4.1 

7.0 

7.1 

6.9 

7.1 

7.3 

5.4 

7.5 

6.4 

6.3 

6.4 

8.8 

7.1 

6.7 

7.5 

6.4 

7.5 

22.6 

48.5 

63.7 

58.5 

65.8 

35.0 

17.6 

8.8 

6.2 

6.3 

7.5 

22.5 

20.9 

23.7 

21.2 

23.6 

16.5 

23.7 

22.1 

22.4 

14.0 

28.4 

21.6 

21.0 

24.6 

20.4 

22.1 

101.3 

63.4 

69.6 

69.6 

101.3 

77.1 

32.2 

14.9 

16.0 

18.6 

18.6 

101.3 

77.1 

81.1 

83.6 

83.6 

65.8 

101.3 

61.9 

101.3 

40.8 

69.6 

83.6 

101.3 

81.1 

81.3 

83.6 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994−1996 CSFII. 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Page 

September 2011 9-59 

Table 9-19. Per Capita Intake of Protected Fruits Based on 1994−1996 CSFII (g/kg-day, as-consumed) 

Population 

Group 

Percent 

consuming Mean SE 

Percentile 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 0 to 5 months 

 6 to 12 months 

 <1 years 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Urbanization 

 Central City 

 Non-metropolitan 

 Suburban 

Race 

 Asian 

 Black 

 Native American 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

53 

10.8 

49 

28.7 

61.8 

56.2 

50.7 

47.3 

48 

56.5 

68.7 

50.8 

53.5 

52.4 

55.4 

55.5 

45.6 

54.6 

62.3 

48.1 

44.1 

60.3 

53 

51 

62.5 

47.6 

55.3 

1.9 

0.5 

3.1 

1.7 

6.5 

4.4 

2.7 

1.8 

1.4 

1.4 

1.8 

1.8 

2.0 

2.0 

1.9 

2.1 

1.5 

2.0 

3.0 

1.8 

2.0 

2.8 

1.8 

1.8 

2.4 

1.6 

2.0 

0.04 

0.34 

0.58 

0.39 

0.31 

0.22 

0.17 

0.12 

0.07 

0.04 

0.07 

0.08 

0.08 

0.08 

0.07 

0.07 

0.08 

0.06 

0.30 

0.11 

0.65 

0.21 

0.04 

0.08 

0.09 

0.06 

0.09 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.38 

0 

0 

0 

3.6 

2.1 

0.17 

0 

0 

0.61 

1.3 

0.06 

0.46 

0.29 

0.61 

0.67 

0 

0.59 

1.5 

0 

0 

0.98 

0.37 

0.08 

1.1 

0 

0.61 

2.6 

0 

4.4 

2.0 

9.2 

6.7 

3.8 

2.6 

1.9 

2.2 

2.8 

2.3 

2.6 

2.7 

2.6 

2.8 

1.9 

2.7 

4.1 

2.2 

2.5 

3.9 

2.5 

2.4 

3.2 

2.1 

2.8 

5.4 

1.3 

8.3 

6.0 

17.8 

12.1 

8.1 

5.4 

4.3 

4.1 

4.7 

5.0 

5.4 

5.5 

5.5 

5.8 

4.4 

5.5 

8.1 

5.4 

6.8 

7.5 

5.1 

5.3 

6.2 

4.7 

5.8 

8.1 

4.3 

11.2 

8.3 

24.2 

17.2 

11.4 

8.4 

6.3 

5.5 

5.9 

7.3 

8.8 

8.4 

8.0 

8.5 

7.0 

8.3 

11.7 

8.1 

7.9 

10.8 

7.7 

7.8 

9.5 

7.1 

8.4 

16.3 

7.7 

26.8 

16.6 

39.0 

27.9 

19.8 

15.4 

11.8 

9.7 

9.2 

16.1 

18.7 

15.9 

15.1 

17.2 

14.9 

16.6 

18.7 

16.6 

17.0 

22.4 

15.7 

16.5 

19.5 

14.9 

15.3 

113.4 

12.5 

30.3 

30.3 

113.4 

66.5 

31.7 

27.0 

39.3 

45.8 

27.6 

75.7 

47.4 

113.4 

52.0 

66.5 

61.9 

113.4 

64.0 

50.1 

61.9 

113.4 

75.7 

75.7 

66.5 

65.7 

113.4 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994−1996 CSFII. 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 9-60 September 2011 

Table 9-20. Per Capita Intake of Exposed Vegetables (g/kg-day, as-consumed) 

Population 

Group 

Percent 

consuming Mean SE 

Percentile 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 0 to 5 months 

 6 to 12 months 

 <1 years 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Urbanization 

 Central City 

 Non-metropolitan 

 Suburban 

Race 

 Asian 

 Black 

 Native American 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

79.2 

6 

40.8 

22.3 

63.3 

67.8 

70.8 

77.4 

82.6 

84 

83.2 

79.6 

78.8 

81.2 

77.4 

79.5 

78 

79.6 

82.2 

76.3 

70.7 

73.8 

80.1 

80.2 

79.4 

79.6 

77.5 

1.3 

0.48 

2.0 

1.2 

2.0 

1.6 

1.2 

0.97 

1.3 

1.4 

1.5 

1.3 

1.3 

1.5 

1.2 

1.4 

1.2 

1.4 

2.1 

1.2 

1.3 

1.3 

1.3 

1.3 

1.4 

1.3 

1.3 

0.02 

0.62 

0.49 

0.37 

0.11 

0.08 

0.06 

0.04 

0.03 

0.02 

0.05 

0.03 

0.03 

0.03 

0.03 

0.03 

0.03 

0.02 

0.15 

0.04 

0.40 

0.08 

0.02 

0.03 

0.04 

0.03 

0.04 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.11 

0 

0 

0 

0 

0 

0 

0.06 

0.15 

0.28 

0.31 

0.12 

0.09 

0.16 

0.08 

0.12 

0.08 

0.12 

0.34 

0.04 

0 

0 

0.13 

0.12 

0.12 

0.12 

0.08 

0.80 

0 

0 

0 

0.59 

0.67 

0.60 

0.53 

0.81 

0.97 

1.09 

0.79 

0.79 

0.92 

0.74 

0.83 

0.69 

0.85 

1.39 

0.66 

0.45 

0.73 

0.82 

0.81 

0.91 

0.78 

0.78 

1.9 

0 

3.1 

0 

2.7 

2.2 

1.6 

1.3 

1.8 

2.0 

2.1 

1.9 

1.8 

2.1 

1.7 

2.0 

1.6 

1.9 

3.0 

1.7 

1.5 

1.8 

1.9 

1.8 

2.1 

1.8 

1.8 

3.4 

0 

5.8 

5.0 

5.8 

4.4 

3.4 

2.5 

3.2 

3.3 

3.6 

3.4 

3.3 

3.5 

3.2 

3.5 

2.9 

3.4 

4.9 

3.3 

2.0 

3.3 

3.3 

3.3 

3.5 

3.2 

3.4 

4.4 

4.6 

10.3 

7.4 

8.6 

6.4 

4.8 

3.6 

4.1 

4.3 

4.4 

4.4 

4.3 

4.8 

4.2 

4.5 

4.1 

4.5 

7.1 

4.1 

4.5 

4.7 

4.4 

4.4 

4.6 

4.2 

4.6 

7.6 

11.8 

14.7 

14.7 

14.9 

12.8 

8.1 

5.8 

6.9 

6.4 

7.2 

7.3 

7.9 

8.6 

7.0 

8.1 

6.9 

7.8 

13.0 

7.2 

9.5 

10.4 

7.2 

7.1 

7.9 

7.1 

8.9 

45.0 

12.5 

19.0 

19.0 

45.0 

25.1 

19.6 

13.0 

18.4 

16.4 

20.1 

45.0 

25.1 

25.1 

20.9 

25.1 

45.0 

25.1 

20.1 

20.9 

45.0 

24.8 

25.1 

24.8 

25.1 

25.1 

45.0 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994−1996 CSFII. 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Page 

September 2011 9-61 

Table 9-21. Per Capita Intake of Protected Vegetables Based on 1994−1996 CSFII (g/kg-day, as-consumed) 

Population 

Group 

Percent 

consuming Mean SE 

Percentile 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 0 to 5 months 

 6 to 12 months 

 <1 years 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Urbanization 

 Central City 

 Non-metropolitan 

 Suburban 

Race 

 Asian 

 Black 

 Native American 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

38.0 

10.3 

34.8 

21.8 

40.8 

38.2 

38.8 

30.4 

36.7 

41.2 

42.2 

37.9 

37.8 

39.3 

37.1 

38.9 

39.7 

36.6 

45.4 

36.2 

32.0 

50.4 

37.2 

36.3 

37.5 

38.5 

39.5 

0.63 

0.49 

2.2 

1.3 

1.5 

1.1 

0.78 

0.46 

0.53 

0.56 

0.65 

0.62 

0.62 

0.67 

0.61 

0.70 

0.62 

0.59 

0.85 

0.72 

0.34 

1.1 

0.57 

0.57 

0.61 

0.66 

0.67 

0.02 

0.41 

0.55 

0.37 

0.13 

0.09 

0.07 

0.06 

0.04 

0.03 

0.05 

0.04 

0.04 

0.04 

0.04 

0.04 

0.04 

0.03 

0.14 

0.07 

0.13 

0.10 

0.02 

0.04 

0.05 

0.03 

0.04 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.04 

0 

0 

0 

0 

0 

0.73 

0 

4.4 

0 

1.9 

1.4 

1.0 

0.44 

0.61 

0.73 

0.86 

0.71 

0.67 

0.85 

0.71 

0.78 

0.75 

0.68 

1.1 

0.77 

0.13 

1.5 

0.68 

0.62 

0.75 

0.78 

0.75 

2.0 

1.4 

7.3 

5.4 

4.4 

3.5 

2.6 

1.5 

1.7 

1.7 

2.0 

2.1 

1.8 

1.9 

1.9 

2.1 

1.9 

1.9 

2.7 

2.2 

1.6 

3.4 

1.8 

1.8 

1.8 

2.1 

2.1 

3.1 

3.9 

9.6 

7.8 

7.0 

5.4 

3.9 

2.4 

2.7 

2.6 

3.1 

3.2 

2.9 

3.1 

3.0 

3.4 

3.1 

2.9 

4.1 

3.5 

2.0 

5.2 

2.8 

2.9 

2.9 

3.1 

3.3 

6.6 

9.2 

19.5 

11.9 

14.2 

10.3 

7.5 

5.8 

5.5 

4.8 

5.7 

5.9 

7.6 

6.3 

6.9 

7.3 

6.0 

5.9 

7.8 

7.9 

3.5 

10.0 

5.9 

5.6 

6.3 

6.3 

7.8 

45.8 

11.0 

23.1 

23.1 

27.8 

18.0 

26.5 

21.6 

23.6 

45.8 

21.5 

21.6 

23.6 

45.8 

27.8 

45.8 

25.8 

27.8 

23.3 

45.8 

5.3 

26.5 

27.8 

21.5 

27.8 

45.8 

23.1 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994−1996 CSFII. 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 9-62 September 2011 

Table 9-22. Per Capita Intake of Root Vegetables Based on 1994−1996 CSFII (g/kg-day, as-consumed) 

Population 

Group 

Percent 

consuming Mean SE 

Percentile 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 0 to 5 months 

 6 to 12 months 

 <1 years 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Urbanization 

 Central City 

 Non-metropolitan 

 Suburban 

Race 

 Asian 

 Black 

 Native American 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

75.4 

12 

56.9 

33 

67.5 

71.9 

73.8 

76.4 

77.5 

77.2 

73.2 

77.3 

75.9 

74 

74.4 

71.9 

78.5 

76.4 

64.2 

68.9 

71.1 

67 

77.5 

79.4 

72.3 

77 

71.3 

1.2 

0.96 

2.8 

1.8 

2.6 

2.2 

1.6 

1.3 

1.1 

0.99 

1.1 

1.3 

1.2 

1.2 

1.2 

1.2 

1.4 

1.2 

0.97 

1.1 

1.4 

1.1 

1.3 

1.4 

1.1 

1.3 

1.1 

0.02 

0.61 

0.45 

0.36 

0.13 

0.09 

0.06 

0.05 

0.03 

0.02 

0.04 

0.04 

0.03 

0.03 

0.03 

0.03 

0.04 

0.02 

0.10 

0.05 

0.27 

0.10 

0.02 

0.04 

0.03 

0.03 

0.03 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.03 

0 

0 

0 

0 

0 

0 

0.09 

0.10 

0.08 

0 

0.09 

0.05 

0 

0 

0 

0.14 

0.07 

0 

0 

0 

0 

0.09 

0.16 

0 

0.09 

0 

0.75 

0 

0.80 

0 

1.5 

1.4 

1.0 

0.82 

0.73 

0.68 

0.70 

0.83 

0.73 

0.73 

0.74 

0.66 

0.89 

0.77 

0.37 

0.62 

1.0 

0.50 

0.81 

0.90 

0.64 

0.81 

0.61 

1.7 

0 

4.6 

2.3 

3.6 

3.2 

2.3 

1.8 

1.6 

1.5 

1.6 

1.8 

1.7 

1.6 

1.7 

1.6 

1.9 

1.7 

1.3 

1.4 

1.9 

1.4 

1.8 

2.0 

1.5 

1.8 

1.5 

3.0 

3.9 

8.0 

6.9 

6.8 

5.5 

4.2 

3.0 

2.7 

2.5 

2.7 

3.1 

3.1 

2.9 

3.0 

2.9 

3.2 

3.0 

2.8 

2.9 

2.8 

2.8 

3.1 

3.4 

2.9 

3.0 

2.8 

4.1 

8.3 

10.4 

9.6 

8.3 

7.1 

5.3 

4.0 

3.5 

3.2 

3.4 

4.2 

4.3 

3.9 

4.1 

4.2 

4.5 

4.0 

4.0 

4.2 

3.0 

3.7 

4.2 

4.6 

3.8 

4.1 

3.7 

7.6 

11.9 

16.6 

15.6 

16.8 

14.1 

9.5 

7.7 

6.0 

4.8 

5.3 

8.1 

7.7 

7.4 

7.4 

7.3 

9.5 

7.2 

7.1 

7.6 

11.2 

9.6 

7.5 

8.6 

7.1 

7.6 

6.9 

83.3 

21.9 

32.9 

32.9 

83.3 

32.1 

20.6 

22.5 

16.6 

15.1 

9.8 

83.3 

30.0 

25.8 

34.3 

83.3 

34.3 

26.1 

17.3 

32.9 

34.3 

83.3 

32.1 

26.1 

20.7 

83.3 

34.3 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994−1996 CSFII. 
 

Table 9-23. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and the Percentage of Individuals Consuming 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Page

September 2011 9-63

These Foods in Two Days 

Food category Percent 

Consuminga 

Quantity Consumed per 

Eating Occasion (gram) 

Average SE 5 

Consumer-Only Quantity Consumed per Eating Occasion 

at Specified Percentiles (gram)

a 

10 25 50 75 90 95 

Raw vegetables 

Cucumbers 10.8 48 3 7 14 16 29 54 100 157 

Lettuce 53.3 41 1 7 8 13 27 55 91 110 

Mixed lettuce-based salad 2.2 97 6 11 18 55 74 123 167 229 

Carrots 14.1 33 1 5 7 14 27 40 61 100 

Tomatoes 32.0 53 1 15 20 27 40 61 93 123 

Coleslaw 5.0 102 3 18 32 55 91 134 179 183 

Onions 14.4 23 1 3 7 10 15 28 41 60 

Cooked vegetables 

Broccoli 7.3 119 4 23 35 61 92 156 232 275 

Carrots 5.8 72 2 13 19 36 65 78 146 156 

Total tomato sauce 54.3 34 1 1 2 7 17 40 80 124 

String beans 13.2 90 2 17 31 52 68 125 136 202 

Peas 6.1 86 3 11 21 40 80 120 167 170 

Corn 15.1 101 2 20 33 55 82 123 171 228 

French-fried potatoes 25.5 83 1 28 35 57 70 112 125 140 

Home-fried and hash-browned potatoes 8.9 135 3 36 47 70 105 192 284 308 

Baked potatoes 12.4 120 2 48 61 92 106 143 184 217 

Boiled potatoes 5.3 157 5 34 52 91 123 197 308 368 

Mashed potatoes 15.0 188 3 46 61 105 156 207 397 413 

Dried beans and peas 8.0 133 3 22 33 64 101 173 259 345 

Baked beans 4.7 171 6 24 47 84 126 235 314 385 

Fruits 

Raw oranges 7.9 132 2 42 64 95 127 131 183 253 

Orange juice 27.2 268 4 124 124 187 249 311 447 498 

Raw apples 15.6 135 2 46 68 105 134 137 209 211 

Applesauce and cooked apples 4.6 134 4 31 59 85 121 142 249 254 

Apple juice 7.0 271 7 117 120 182 242 307 481 525 

Raw bananas 20.8 111 1 55 58 100 117 118 135 136 a = Percent consuming at least once in two days. 

SE = Standard error of the mean. 

Source: Smiciklas-Wright et al. (2002) (based on 1994−1996 CSFII data). 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 9-64 September 2011 

Table 9-24. Quantity (as-consumed) of Fruits and Vegetables Consumed per Eating Occasion and Percentage of Individuals 

Consuming These Foods in Two Days, by Food 

Food category 

Quantity consumed per eating occasion (grams) 

2 to 5 years 6 to 11 years 12 to 19 years 

Male and Female 

(N = 2,109) 

Male and Female Male 

(N = 1,432) (N = 696)

Female 

(N = 702)

PC Mean SEPC Mean SEPC Mean SEPC Mean SE 

Raw Vegetables 

Carrots 

Cucumbers 

Lettuce 

Onions 

Tomatoes 

10.4 

6.4 

34.0 

3.9 

14.8 

27 

32 

17 

9 

31 

2 

4 

1 

2 

2 

17.8 

6.6 

40.8 

4.5 

14.0 

32 

39 

26 

17 

42 

2 

6 

1 

2 

4 

9.2 

6.1 

56.0 

11.1 

25.7 

35 

71a 

32 

28 

49 

6 

22a 

3 

4 

5 

11.9 

6.8 

52.3 

7.9 

23.9 

32 

48 

34 

23 

44 

4 

11 

2 

4 

3 

Cooked Vegetables 

Beans (string)

Broccoli 

Carrots 

Corn 

Peas Potatoes (French-fried)

Potatoes (home-fried and hash-browned)

Potatoes (baked)

Potatoes (boiled)

Potatoes (mashed) 

16.8 

7.2 

6.0 

18.9 

8.4 

32.7 

9.3 

7.6 

4.8 

14.8 

50 

61 

48 

68 

48 

52 

85 

70 

81 

118 

2 

3 

4 

3 

3 

1 

5 

4 

9 

6 

12.1 

5.6 

3.8 

22.2 

6.8 

33.7 

10.1 

8.2 

2.7 

13.3 

71 

102 

46 

79 

72 

67 

93 

95 

103a 

162 

6 

16 

5 

4 

9 

2 

6 

6 

17a 

12 

8.3 

3.9 

2.8 

12.8 

3.6 

41.7 

10.1 

8.6 

2.0 

14.6 

85 

127a 

81a 

125 

115a 

97 

145 

152 

250a 

245 

9 

17a 

16a 

9 

15a 

3 

13 

15 

40a 

16 

7.6 

5.7 

2.1 

12.3 

2.4 

38.1 

6.1 

8.8 

3.2 

11.9 

78 

109a 

75a 

100 

93a 

81 

138 

115 

144a 

170 

5 

14a 

17a 

6 

17a 

4 

13 

10 

16a 

17 

Fruits 

Apples (raw)

Apples (cooked and applesauce)

Apple juice

Bananas (raw)

Oranges (raw)

Orange juice 

26.8 

10.1 

26.3 

25.0 

11.1 

34.4 

106 

118 

207 

95 

103 

190 

2 

5 

5 

2 

5 

4 

21.9 

9.0 

12.2 

16.5 

10.5 

30.9 

123 

130 

223 

105 

114 

224 

3 

7 

10 

3 

5 

6 

11.7 

2.3 

7.8 

10.3 

4.3 

30.8 

149 

153a 

346 

122 

187a 

354 

9 

19a 

22 

6 

38a 

16 

12.4 

2.6 

8.5 

8.4 

5.4 

29.5 

129 

200a 

360 

119 

109a 

305 

5 

47a 

44 

5 

8a 

11 
Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables Exposure Factors Handbook 

Page 

September 2011 9-65 

 

 

 

Table 9-24. Quantity (as-consumed) of Fruits and Vegetables Consumed Per Eating Occasion and Percentage of Individuals 

Consuming These Foods in Two Days, by Food (continued) 

Food category Quantity consumed per eating occasion (grams) 

20 to <40 years 40 to <60 years ≥60 years 

Male 

(N = 1,543) 

Female 

(N = 1,449) 

Male 

(N = 1,663) 

Female 

(N = 1,694) 

Male 

(N = 1,545) 

Female 

(N = 1,429) 

PC Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE 

Raw Vegetables 

Carrots 12.3 35 4 15.4 38 4 14.4 35 2 18.1 31 2 13.6 29 2 12.7 27 1 

Cucumbers 10.5 62 12 10.4 45 4 12.5 47 4 15.7 41 3 14.2 51 4 13.2 45 3 

Lettuce 63.4 40 2 57.6 44 2 55.5 48 2 59.1 48 1 48.1 47 2 46.1 42 2 

Onions 17.9 27 2 14.7 22 1 19.6 26 1 18.3 19 1 19.0 19 1 15.6 19 1 

Tomatoes 33.1 57 2 32.3 49 2 38.1 60 2 42.4 53 1 40.0 62 3 41.0 52 2 

Cooked Vegetables 

Beans (string) 10.6 111 5 12.5 89 6 13.7 114 6 13.4 93 4 18.3 99 4 19.7 78 3 

Broccoli 7.6 152 13 6.7 129 13 7.8 127 7 7.6 114 7 8.5 117 7 10.9 107 6 

Carrots 5.0 79 7 5.3 69 6 6.7 83 7 6.4 66 4 9.6 78 4 9.0 75 4 

Corn 12.7 122 5 15.3 98 5 17.1 133 6 13.5 90 3 14.2 109 4 13.0 83 5 

Peas 4.4 109 10 4.9 82 9 7.4 113 7 6.3 79 7 8.4 88 7 9.4 73 5 

Potatoes (French-fried) 35.3 107 2 23.9 79 3 20.6 89 2 16.8 72 3 11.2 76 3 8.1 58 3 

Potatoes (home-fried/hash-browned) 9.5 160 10 8.8 129 7 11. 174 10 6.4 119 7 10.4 152 8 7.1 110 9 

Potatoes (baked) 11.4 154 7 11.1 126 5 13.0 133 3 16.5 112 3 17.9 115 3 18.1 100 4 

Potatoes (boiled) 3.9 185 16 2.9 162 15 6.3 209 12 7.0 142 9 11.0 166 6 10.2 131 5 

Potatoes (mashed) 14.7 269 12 13.5 167 5 16.0 225 11 14.3 156 7 19.7 173 6 18.1 140 5 

Fruits 

Apples (raw) 6.6 153 8 6.3 126 6 7.4 148 8 8.3 132 5 8.9 133 5 11.2 129 4 

Apples (cooked and applesauce) 24.3 373 20 23.2 289 12 24.1 285 10 25.2 231 6 30.2 213 5 31.7 196 5 

Apple juice 12.1 161 6 12.9 134 3 14.1 145 3 16.2 136 4 17.6 145 8 16.1 128 3 

Bananas (raw) 1.3 153a 31a 2.4 155a 21a 3.1 142 12 3.9 125 10 8.1 135 10 9.2 121 7 

Oranges (raw) 4.2 345 20 4.7 302 19 4.7 358 33 3.2 259 21 4.8 233 11 5.0 225 13 

Orange juice 14.4 126 2 18.5 112 2 21.9 125 3 24.4 111 2 36.5 105 2 34.0 96 2 a Indicates a statistic that is potentially unreliable because of a small sample size and a large SE. PC = Percent consuming at least once in two days. 

SE = Standard error of the mean. 

N = Sample size. 

Source: Smiciklas-Wright et al. (2002) (based on 1994−1996 CSFII data). 
 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-25. Consumption of Major Food Groups: Median Servings (and ranges) by 

Demographic and Health Characteristics, for Older Adults 

Subject Characteristic N Fruits and Vegetables 

(servings per day) 

Sex 

Female 80 5.7 (1.5−8.1) 

Male 50 4.5 (0.8−8.8) 

Ethnicitya 

African American 44 4.5 (0.8−8.0) 

European American 47 6.0 (1.5−8.0) 

Native American 39 4.5 (1.6−8.8) 

Age 

70 to 74 years 42 4.5 (1.6−8.1) 

75 to 79 years 36 5.6 (0.8−8.0) 

80 to 84 years 36 5.6 (1.5−8.8) 

≥ 85 years 16 5.4 (1.8−8.0) 

Marital Status 

Married 49 4.5 (1.6−8.0) 

Not Married 81 5.6 (0.8−8.8) 

Education 

8th grade or less 37 5.0 (1.5−8.1) 

9th to 12th grades 47 4.5 (0.8−8.0) 

> High School 46 6.0 (1.5−8.8) 

Dentures 

Yes 83 5.4 (1.5−8.8) 

No 47 4.7 (0.8−8.0) 

Chronic Diseases 

0 7 7.0 (5.2−8.8) 

1 31 5.4 (1.5−8.0) 

2 56 5.4 (1.6−8.1) 

3 26 4.5 (2.0−8.0) 

4+ 10 5.5 (0.8−8.0) 

Weightb 

130 pounds 18 6.0 (1.8−8.0) 

131 to 150 pounds 32 5.5 (1.5−8.0) 

151 to 170 pounds 27 5.7 (1.7−8.1) 

171 to 190 pounds 22 5.6 (1.8−8.8) 

191 pounds 29 4.5 (0.8−8.0) a p < 0.05. b Two missing values. 

N = Number of individuals. 

Source: Vitolins et al. (2002). 

Page Exposure Factors Handbook 

9-66 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-26. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population 

Sample Size Percentage of Sample 

Sex 

Male 

Female 

1,549 

1,473 

51.3 

48.7 

Age of Child 

4 to 6 months 

7 to 8 months 

9 to 11 months 

12 to 14 months 

15 to 18 months 

19 to 24 months 

862 

483 

679 

374 

308 

316 

28.5 

16.0 

22.5 

12.4 

10.2 

10.4 

Child’s Ethnicity 

Hispanic or Latino 

Non-Hispanic or Latino 

Missing 

367 

2,641 

14 

12.1 

87.4 

0.5 

Child’s Race 

White 

Black 

Other 

2,417 

225 

380 

80.0 

7.4 

12.6 

Urbanicity 

Urban 

Suburban 

Rural 

Missing data 

1,389 

1,014 

577 

42 

46.0 

33.6 

19.1 

1.3 

Household Income 

Under $10,000 

$10,000 to $14,999 

$15,000 to $24,999 

$25,000 to $34,999 

$35,000 to $49,999 

$50,000 to $74,999 

$75,000 to $99,999 

$100,000 and Over 

Missing 

48 

48 

221 

359 

723 

588 

311 

272 

452 

1.6 

1.6 

7.3 

11.9 

23.9 

19.5 

10.3 

9.0 

14.9 

Receives WIC 

Yes 

No 

Missing 

821 

2,196 

5 

27.2 

72.6 

0.2 

Sample Size (Unweighted) 3,022 100.0 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Devaney et al. (2004). 

Exposure Factors Handbook Page
 

September 2011 9-67 
 

Table 9-27. Percentage of Infants and Toddlers Consuming Different Types of Vegetables 

Percentage of Infants and Toddlers Consuming at Least Once in a Day 

Food Group/Food 4 to 6 

months 

7 to 8 

months 

9 to 11 

months 

12 to 14 

months 

15 to 18 

months 

19 to 24 

months 

Any Vegetable 39.9 66.5 72.6 76.5 79.2 81.6 

Baby Food Vegetables 35.7 54.5 34.4 12.7 3.0 1.6 

Cooked Vegetables 5.2 17.4 45.9 66.3 72.9 75.6 

Raw Vegetables 0.5 1.6 5.5 7.9 14.3 18.6 

Types of Vegetablesa 

Dark Green Vegetablesb 0.1 2.9 4.2 5.0 10.4 7.8 

Deep Yellow Vegetablesc 26.5 39.3 29.0 24.0 13.6 13.4 

White Potatoes 3.6 12.4 24.1 33.2 42.0 40.6 

French Fries and Other Fried Potatoes 0.7 2.9 8.6 12.9 19.8 25.5 

Other Starchy Vegetablesd 6.5 10.9 16.9 17.3 20.8 24.2 

Other Vegetables 11.2 25.9 35.1 39.1 45.6 43.3 a Totals include commercial baby food, cooked vegetables, and raw vegetables. b Reported dark green vegetables include broccoli, spinach and other greens, and romaine lettuce. c Reported deep yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash. d Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried), cassava, and rutabaga. 

Source: Fox et al. (2004). 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 

9-68 September 2011 
 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-28. Top Five Vegetables Consumed by Infants and Toddlers 

Top Vegetables by Age Groupa Percentage Consuming at Least Once in a Day 

4 to 6 months 

Baby Food Carrots 9.6 

Baby Food Sweet Potatoes 9.1 

Baby Food Squash 8.1 

Baby Food Green Beans 7.2 

Baby Food Peas 5.0 

7 to 8 months 

Baby Food Carrots 14.2 

Baby Food Sweet Potatoes 12.9 

Baby Food Squash 12.9 

Baby Food Green Beans 11.2 

Baby Food Mixed/Garden Vegetables 10.1 

9 to 11 months 

Cooked Green Beans 9.7 

Mashed/Whipped Potatoes 9.0 

French Fries/Other Fried Potatoes 8.6 

Baby Food Mixed/Garden Vegetables 8.4 

Cooked Carrots 8.0 

12 to 14 months 

Cooked Green Beans 18.2 

French Fries/Other Fried Potatoes 12.9 

Cooked Carrots 11.5 

Mashed/Whipped Potatoes 10.3 

Cooked Peas 8.4 

15 to 18 months 

French Fries/Other Fried Potatoes 19.8 

Cooked Green Beans 16.7 

Cooked Peas 13.9 

Cooked Tomatoes/Tomato Sauce 13.7 

Mashed/Whipped Potatoes 12.4 

19 to 24 months 

French Fries/Other Fried Potatoes 25.5 

Cooked Green Beans 16.8 

Cooked Corn 15.2 

Cooked Peas 11.4 

Cooked Tomatoes/Tomato Sauce 9.4 

a Baby food vegetables include single vegetables (majority of vegetables reported) as well as mixtures with the named 

vegetables the predominant vegetable, e.g., broccoli and cauliflower or broccoli and carrots. 

Source: Fox et al. (2004). 

Exposure Factors Handbook Page
 

September 2011 9-69 
 

 

 

 

Table 9-29. Percentage of Infants and Toddlers Consuming Different Types of Fruits 

Percentage of Infants and Toddlers Consuming at Least Once in a Day 

Food Group/Food 4 to 6 months 7 to 8 months 9 to 11 months 12 to 14 months 15 to 18 months 19 to 24 months 

Any Fruit 41.9 75.5 75.8 77.2 71.8 67.3 

Baby Food Fruit 39.1 67.9 44.8 16.2 4.2 1.8 

Non-Baby Food Fruit 5.3 14.3 44.2 67.1 69.4 66.8 

Types of Non-Baby Food Fruit 

Canned Fruit 1.4 5.8 21.6 31.9 25.1 20.2 

Packed in Syrup 0.7 0.7 8.1 14.9 12.7 8.1 

Packed in Juice or Water 0.7 4.5 13.5 18.5 11.3 11.4 

Unknown Pack 0.0 0.7 1.5 1.2 3.1 1.2 

Fresh Fruit 4.4 9.5 29.5 52.1 55.0 54.6 

Dried Fruit 0.0 0.4 2.1 3.5 7.1 9.4 

Types of Fruit

a 

Apples 18.6 33.1 31.6 27.5 19.8 22.4 

Bananas 16.0 30.6 34.5 37.8 32.4 30.0 

Berries 0.1 0.6 5.3 6.6 11.3 7.7 

Citrus Fruits 0.2 0.4 1.6 4.9 7.3 5.1 

Melons 0.6 1.0 4.4 7.3 7.2 9.6 a Totals include all baby food and non-baby food fruits. 

Source: Fox et al. (2004). 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 

9-70 September 2011 
 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-30. Top Five Fruits Consumed by Infants and Toddlers 

Top Fruits by Age Groupa Percentage Consuming at Least Once in a Day 

4 to 6 months 

Baby Food Applesauce 17.5 

Baby Food Bananas 13.0 

Baby Food Pears 7.5 

Baby Food Peaches 7.4 

Fresh Banana 0.3 

7 to 8 months 

Baby Food Applesauce 29.0 

Baby Food Bananas 25.2 

Baby Food Pears 18.2 

Baby Food Peaches 13.1 

Fresh Banana 6.6 

9 to 11 months 

Fresh Banana 19.0 

Baby Food Applesauce 17.7 

Baby Food Bananas 16.8 

Baby Food Pears 12.4 

Canned Applesauce 11.1 

12 to 14 months 

Fresh Banana 33.0 

Canned Applesauce 15.2 

Fresh Grapes 9.0 

Fresh Apple 8.8 

Canned Peaches 7.2 

Canned Fruit Cocktail 7.2 

15 to 18 months 

Fresh Banana 30.5 

Fresh Grapes 13.2 

Fresh Apple 11.2 

Fresh Strawberries 10.6 

Canned Peaches 8.9 

19 to 24 months 

Fresh Banana 29.6 

Fresh Apple 15.0 

Fresh Grapes 11.2 

Raisins 9.0 

Fresh Strawberries 7.6 a Baby food fruits include single fruits (majority of fruits reported) as well as mixtures with the named fruit as the 

predominant fruit, e.g., pears and raspberries or prunes with pears. Baby food fruits with tapioca and other baby food 

dessert fruits were counted as desserts. 

Source: Fox et al. (2004). 

Exposure Factors Handbook Page
 

September 2011 9-71 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

c 

Table 9-31. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants

a 

(percentages) 

Infants 4 to 6 months Infants 7 to 11 months Toddlers 12 to 24 months 

WIC WIC WIC 

Participant Non-Participant Participant Non-Participant Participant Non-Participant 

Sex 

Male 55 54 55 51 57 52 

Female 45 46 45 49 43 48 

Child’s Ethnicity b b b 

Hispanic or Latino 20 11 24 8 22 10 

Non-Hispanic or Latino 80 89 76 92 78 89 

Child’s Race b b b 

White 63 84 63 86 67 84 

Black 15 4 17 5 13 5 

Other 22 11 20 9 20 11 

Child In Daycare b c 

Yes 39 38 34 46 43 53 

No 61 62 66 54 57 47 

Age of Mother b b b 

14 to 19 years 18 1 13 1 9 1 

20 to 24 years 33 13 38 11 33 14 

25 to 29 years 29 29 23 30 29 26 

30 to 34 years 9 33 15 36 18 34 

>35 years 9 23 11 21 11 26 

Missing 2 2 1 1 0 1 

Mother’s Education b b b 

11th Grade or Less 23 2 15 2 17 3 

Completed High School 35 19 42 20 42 19 

Some Postsecondary 33 26 32 27 31 28 

Completed College 7 53 9 51 9 48 

Missing 2 1 2 0 1 2 

Parent’s Marital Status b b b 

Married 49 93 57 93 58 88 

Not Married 50 7 42 7 41 11 

Missing 1 1 1 0 1 1 

Mother or Female Guardian Works b c 

Yes 46 51 45 60 55 61 

No 53 48 54 40 45 38 

Missing 1 1 1 0 0 1 

Urbanicity b b b 

Urban 34 55 37 50 35 48 

Suburban 36 31 31 34 35 35 

Rural 28 13 30 15 28 16 

Missing 2 1 2 1 2 2 

Sample Size (Unweighted) 265 597 351 808 205 791 a χ2 tests were conducted to test for statistical significance in the differences between WIC participants and non-participants within each 

age group for each variable. The results of the χ

2 tests are listed next to the variable under the column labeled non-participants for 

each of the three age groups. b p < 0.01 non-participants significantly different from WIC participants on the variable. 

p < 0.05 non-participants significantly different from WIC participants on the variable. 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Ponza et al. (2004). 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Page Exposure Factors Handbook 

9-72 September 2011 
 

 

 

 

Table 9-32. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC) 

Participation Status 

Infants 4 to 6 months Infants 7 to 11 months Toddlers 12 to 24 months 

WIC 

Participant 

NonParticipant WIC 

Participant 

NonParticipant WIC 

Participant 

NonParticipant 

Vegetables 

Any Vegetable 

Baby Food Vegetables 

Cooked Vegetables 

Raw Vegetables 

Dark Green Vegetables 

Deep Yellow Vegetables 

Other Starchy Vegetables 

Potatoes 

40.2 

32.9 

8.0 

1.4 

0.4 

23.2 

6.5 

6.0 

39.8 

37.0 

3.9a 

0.1b 

0.0 

28.1 

6.4 

2.4a 

68.2 

38.2 

33.8 

3.6 

2.9 

30.1 

12.9 

20.7 

70.7 

45.0 

33.8 

4.1 

4.0 

34.8 

15.2 

18.2 

77.5 

4.8 

73.1 

11.8 

6.3 

12.5 

21.1 

43.1 

80.2 

4.7 

72.3 

15.4 

8.4 

16.9 

21.5 

38.3 

Fruits 

Any Fruit 

Baby Food Fruits 

Non-Baby Food Fruit 

Fresh Fruit 

Canned Fruit 

47.8 

43.8 

8.1 

5.4 

3.4 

39.2a 

36.9 

4.0 

3.8 

0.5b 

64.7 

48.4 

22.9 

14.3 

10.3 

81.0b 

57.4a 

35.9b 

24.3b 

17.3b 

58.5 

3.8 

56.4 

43.6 

22.3 

74.6b 

6.5 

70.9b 

57.0b 

25.3 

Sample Size (unweighted) 265 597 351 808 205 791 a = p <0.05 non-participants significantly different from WIC participants. b = p <0.01 non-participants significantly different from WIC participants. 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Ponza et al. (2004). 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Exposure Factors Handbook Page
 

September 2011 9-73 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-33. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by 

Infants From the 2002 Feeding Infants and Toddlers Study 

Food Group 

Reference 

Unit 

4 to 5 months 

(N = 624) 

6 to 8 months 

(N = 708) 

Mean ± SE 

9 to 11 months 

(N = 687) 

Fruits and Juices 

All fruits tablespoon 3.6 ± 0.19 4.7 ± 0.11 5.8 ± 0.17 

Baby food fruit tablespoon 3.3 ± 0.16 4.6 ± 0.11 5.6 ± 0.17 

Baby food peaches tablespoon 3.6 ± 0.37 4.4 ± 0.26 5.3 ± 0.36 

Baby food pears tablespoon 3.5 ± 0.46 4.5 ± 0.21 6.0 ± 0.40 

Baby food bananas tablespoon 3.4 ± 0.23 5.0 ± 0.21 5.9 ± 0.35 

Baby food applesauce tablespoon 3.7 ± 0.29 4.6 ± 0.17 5.6 ± 0.25 

Canned fruit tablespoon - 4.5 ± 0.59 4.8 ± 0.25 

Fresh fruit tablespoon - 5.3 ± 0.52 6.4 ± 0.37 

100% juice fluid ounce 2.5 ± 0.17 2.8 ± 0.11 3.1 ± 0.09 

Apple/apple blends fluid ounce 2.7 ± 0.22 2.9 ± 0.13 3.2 ± 0.11 

Grape fluid ounce - 2.6 ± 0.19 3.1 ± 0.21 

Pear fluid ounce - 2.6 ± 0.29 3.1 ± 0.28 

Vegetables 

All vegetables tablespoon 3.8 ± 0.20 5.8 ± 0.16 5.6 ± 0.20 

Baby food vegetables tablespoon 4.0 ± 0.20 5.9 ± 0.16 6.6 ± 0.21 

Baby food green beans tablespoon 3.5 ± 0.33 5.1 ± 0.28 6.1 ± 0.50 

Baby food squash tablespoon 4.3 ± 0.47 5.6 ± 0.30 6.9 ± 0.41 

Baby food sweet tablespoon 4.3 ± 0.31 6.1 ± 0.34 7.2 ± 0.69 

Baby food carrots tablespoon 3.5 ± 0.33 5.6 ± 0.27 6.7 ± 0.48 

Cooked vegetables, excluding French fries tablespoon - 4.2 ± 0.47 3.8 ± 0.31 

Deep yellow vegetables tablespoon - 3.2 ± 0.59 3.2 ± 0.39 

Mashed potatoes tablespoon - 4.1 ± 0.67 2.8 ± 0.37 

Green beans tablespoon - 3.2 ± 0.62 5.0 ± 0.61 

- = Cell size was too small to generate a reliable estimate. 

N = Number of respondents. 

SE = Standard error. 

Source: Fox et al. (2006). 

Page Exposure Factors Handbook 

9-74 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 9-34. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly Consumed by 

Toddlers From the 2002 Feeding Infants and Toddlers Study 

Food Group 

Reference 

Unit 

12 to 14 months 

(N = 371) 

15 to 18 months 

(N = 312) 

19 to 24 months 

(N = 320) 

Mean ± SE 

Fruits and Juices 

All fruits cup 0.4 ± 0.02 0.5 ± 0.03 0.6 ± 0.03 

Canned fruit cup 0.3 ± 0.02 0.4 ± 0.03 0.4 ± 0.04 

Fresh fruit cup 0.4 ± 0.02 0.5 ± 0.03 0.6 ± 0.03 

Fresh apple cup, slice 0.4 ± 0.05 0.6 ± 0.07 0.8 ± 0.14 

1 medium 0.3 ± 0.04 0.5 ± 0.06 0.6 ± 0.11 

Fresh banana cup, slice 0.4 ± 0.02 0.5 ± 0.03 0.5 ± 0.03 

1 medium 0.6 ± 0.03 0.7 ± 0.03 0.7 ± 0.04 

Fresh grapes cup 0.2 ± 0.01 0.3 ± 0.03 0.3 ± 0.02 

100% juice fluid ounce 3.7 ± 0.15 5.0 ± 0.20 5.1 ± 0.18 

Orange/orange blends fluid ounce 3.3 ± 0.38 4.5 ± 0.33 5.2 ± 0.35 

Apple/apple blends fluid ounce 3.6 ± 0.21 4.5 ± 0.29 4.9 ± 0.27 

Grape fluid ounce 3.6 ± 0.38 5.6 ± 0.43 4.7 ± 0.31 

Vegetables 

All vegetables cup 0.4 ± 0.02 0.4 ± 0.03 0.4 ± 0.02 

Cooked vegetables, 

excluding French fries cup 0.3 ± 0.03 0.3 ± 0.03 0.3 ± 0.02 

Deep yellow vegetables cup 0.2 ± 0.03 0.3 ± 0.05 0.3 ± 0.05 

Corn cup 0.2 ± 0.03 0.2 ± 0.03 0.2 ± 0.03 

Peas cup 0.2 ± 0.02 0.2 ± 0.02 0.2 ± 0.02 

Green beans cup 0.4 ± 0.05 0.4 ± 0.05 0.3 ± 0.03 

Mashed potatoes cup 0.3 ± 0.05 0.4 ± 0.05 0.3 ± 0.05 

Baked/boiled potatoes cup 0.3 ± 0.05 0.4 ± 0.06 -

French fries cup 0.4 ± 0.05 0.6 ± 0.05 0.6 ± 0.05 

- Cell size too small to generate reliable estimate. 

N = Number of respondents. 

SE = Standard error of the mean. 

Source: Fox et al. (2006). 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Exposure Factors Handbook Page
 

September 2011 9-75 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 9-35. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of 

Fruits and Vegetables on a Given Day 

Age 4 to 5 months Age 6 to 11 months Age 12 to 24 months 

Hispanic 

(N = 84) 

Non-Hispanic 

(N = 538) 

Hispanic 

(N = 163) 

Non-Hispanic 

(N = 1,228) 

Hispanic 

(N = 124) 

Non-Hispanic 

(N = 871) 

Fruits 

Any Fruit or 100% Fruit Juice 

Any Fruit

a 

100% Fruit Juice 

Fruit Preparation 

Baby Food Fruit 

Non-Baby Food Fruit 

Canned Fruit 

Fresh Fruit 

45.0 

39.4 

19.3 

32.6 

9.1c 

2.3c 

9.1b,c 

35.9 

28.8 

15.3 

28.4 

1.3c 

-

-

86.2 

68.1 

57.8 

42.9b 

35.8 

8.8 

30.0d 

86.8 

76.0 

47.7 

58.1 

27.4 

13.7 

17.7 

84.6 

67.6 

64.1 

5.6c 

64.2 

12.1d 

59.3 

87.2 

71.5 

58.9 

6.3 

68.0 

26.2 

53.1 

Vegetables 

Any Vegetable or 100% Vegetable Juice

e 

Type of Preparation 

Baby Food Vegetables 

Cooked Vegetables 

Raw Vegetables 

Types of Vegetablese 

Dark Green Vegetablesf 

Deep Yellow Vegetablesg 

Starchy Vegetable: 

White Potatoes 

French Fries/Fried Potatoes 

Baked/Mashed 

Other Starchy Vegetablesh 

Other Non-Starchy Vegetablesi 

30.0 

25.7 

4.2c 

2.3c 

-

21.0 

1.4c 

-

-

5.0c 

8.1c 

27.3 

25.4 

2.4c 

-

-

18.2 

2.3c 

-

-

4.0 

8.0 

66.2 

34.4b 

33.2 

8.3c 

3.3c 

32.2 

20.7 

5.7c 

14.4c 

6.7d 

28.5 

70.3 

47.6 

29.4 

2.6 

3.1 

25.9 

17.4 

5.3 

10.7 

15.1 

29.0 

76.0 

4.1c 

71.4 

25.0 

11.4c 

20.0 

43.5 

23.4 

19.8 

16.6 

42.0 

80.5 

4.9 

72.9 

13.1 

7.5 

15.4 

39.0 

20.3 

17.7 

22.2 

43.4 

a Total includes all baby food and non-baby food fruits and excludes 100% fruit juices and juice drinks. b = Significantly different from non-Hispanic at the p < 0.05. c = Statistic is potentially unreliable because of a high coefficient of variation. d = Significantly different from non-Hispanic at the p < 0.01. e Total includes commercial baby food, cooked vegetables, raw vegetables, and 100% vegetable juices. f Reported dark green vegetables include broccoli, spinach, romaine lettuce, and other greens such as kale. g Reported yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash. h Reported starchy vegetables include corn, green peas, immature lima beans, black-eyed peas (not dried), cassava, and rutabaga. 

Corn is also shown as a subcategory of other starchy vegetables. i Reported non-starchy vegetables include asparagus, cauliflower, cabbage, onions, green beans, mixed vegetables, peppers, and 

tomatoes. 

- = Less than 1% of the group consumed this food on a given day. 

N = Sample size. 

Source: Mennella et al. (2006). 

Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

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Table 9-36. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants and 

Toddlers per Age Groupa 

Ethnicity 

Age (month) N Hispanic Non-Hispanic 

Top Fruits By Age Group 

4 to 5 84 Hispanic Bananas (16.3%) Apples (12.5%) 

538 non-Hispanic Apples (14.7%) Bananas (10.0%) 

Peaches (10.9%) Pears (5.9%) 

Melons (3.5%) Peaches (5.8%) 

Pears (2.5%) Prunes (1.6%) 

6 to 11 136 Hispanic Bananas (35.9%) Apples (32.9%) 

1,228 non-Hispanic Apples (29.7%) Bananas (31.5%) 

Pears (15.2%) 

Peaches (11.7%) 

Pears (17.5%) 

Peaches (13.9%) 

Melons (4.7%) Apricots (3.7%) 

12 to 24 124 Hispanic 

871 non-Hispanic 

Bananas (41.5%) 

Apples (25.7%) 

Bananas (30.9%) 

Apples (22.0%) 

Berries (8.5%) Grapes (12.3%) 

Melons (7.6%) 

Pears (7.3%) 

Peaches (9.6%) 

Berries (8.7%) 

Top Vegetables By Age Group 

4 to 5 84 Hispanic 

538 non-Hispanic 

Carrots (9.9%) 

Sweet Potatoes (6.8%) 

Sweet Potatoes (7.5%) 

Carrots (6.6%) 

Green Beans (5.8%) Green Beans (5.9%) 

Peas (5.0%) 

Squash (4.3%) 

Squash (5.4%) 

Peas (3.8%) 

6 to 11 136 Hispanic 

1,228 non-Hispanic 

Potatoes (20.7%) 

Carrots (19.0%) 

Mixed Vegetables (11.1%) 

Green Beans (11.0%) 

Sweet Potatoes (8.7%) 

Carrots (17.5%) 

Potatoes (16.4%) 

Green Beans (15.9%) 

Squash (11.8%) 

Sweet Potatoes (11.4%) 

12 to 24 124 Hispanic 

871 non-Hispanic 

Potatoes (43.5%) 

Tomatoes (23.1%) 

Carrots (18.6%) 

Onions (11.8%) 

Corn (10.2%) 

Potatoes (39.0%) 

Green Beans (19.6%) 

Peas (12.8%) 

Carrots (12.3%) 

Tomatoes (11.9%) a Percentage consuming at least one in a day is in parentheses. 

N = Sample size. 

Source: Mennella et al. (2006). 

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Chapter 9—Intake of Fruits and Vegetables 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of 

Edible Portions 

Food Moisture Content Comments 

Raw Cooked 

Fruits 

Apples—dried 31.76 84.13* sulfured; * without added sugar 

Apples 85.56* 

86.67** 

-

-

*with skin 

**without skin 

Apples—juice - 87.93 canned or bottled 

Applesauce - 88.35* *unsweetened 

Apricots 86.35 86.62* *canned juice pack with skin 

Apricots—dried 30.09 75.56* sulfured; *without added sugar 

Bananas 74.91 -

Blackberries 88.15 -

Blueberries 84.21 86.59* *frozen unsweetened 

Boysenberries 85.90 - frozen unsweetened 

Cantaloupes 90.15 -

Casabas 91.85 -

Cherries—sweet 82.25 84.95* *canned, juice pack 

Crabapples 78.94 -

Cranberries 87.13 -

Cranberries—juice cocktail 85.00 - Bottled 

Currants (red and white) 83.95 -

Elderberries 79.80 -

Grapefruit (pink, red and white) 90.89 -

Grapefruit—juice 90.00 90.10* *canned unsweetened 

Grapefruit—unspecified 90.89 - pink, red, white 

Grapes—fresh 81.30 - American type (slip skin) 

Grapes—juice 84.12 - canned or bottled 

Grapes—raisins 15.43 - Seedless 

Honeydew melons 89.82 -

Kiwi fruit 83.07 -

Kumquats 80.85 -

Lemons—juice 90.73 92.46* *canned or bottled 

Lemons—peel 81.60 -

Lemons—pulp 88.98 -

Limes 88.26 -

Limes—juice 90.79 92.52* *canned or bottled 

Loganberries 84.61* - *frozen 

Mulberries 87.68 -

Nectarines 87.59 -

Oranges—unspecified 86.75 - all varieties 

Peaches 88.87 87.49* *canned juice pack 

Pears—dried 26.69 64.44* sulfured; *without added sugar 

Pears—fresh 83.71 86.47* *canned juice pack 

Pineapple 86.00 83.51* *canned juice pack 

Pineapple—juice - 86.37 Canned 

Plums—dried (prunes) 30.92 -

Plums 87.23 84.02* *canned juice pack 

Quinces 83.80 -

Raspberries 85.75 -

Strawberries 90.95 89.97* *frozen unsweetened 

Tangerine—juice 88.90 87.00* *canned sweetened 

Tangerines 85.17 89.51* *canned juice pack 

Watermelon 91.45 -

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of 

Edible Portions (continued) 

Food Moisture Content Comments 

Raw Cooked 

Vegetables 

Alfalfa seeds—sprouted 92.82 

Artichokes—globe and French 84.94 84.08 boiled, drained 

Artichokes—Jerusalem 78.01 -

Asparagus 93.22 92.63 boiled, drained 

Bamboo shoots 91.00 95.92 boiled, drained 

Beans—dry—blackeyed peas (cowpeas) 77.20 75.48 boiled, drained 

Beans—dry—hyacinth (mature seeds) 87.87 86.90 boiled, drained 

Beans—dry—navy (mature seeds) 79.15 76.02 boiled, drained 

Beans—dry—pinto (mature seeds) 81.30 93.39 boiled, drained 

Beans—lima 70.24 67.17 boiled, drained 

Beans—snap—green—yellow 90.27 89.22 boiled, drained 

Beets 87.58 87.06 boiled, drained 

Beets—tops (greens) 91.02 89.13 boiled, drained 

Broccoli 90.69 89.25 boiled, drained 

Brussel sprouts 86.00 88.90 boiled, drained 

Cabbage—Chinese (pak-choi) 95.32 95.55 boiled, drained 

Cabbage—red 90.39 90.84 boiled, drained 

Cabbage—savoy 91.00 92.00 boiled, drained 

Carrots 88.29 90.17 boiled, drained 

Cassava (yucca blanca) 59.68 -

Cauliflower 91.91 93.00 boiled, drained 

Celeriac 88.00 92.30 boiled, drained 

Celery 95.43 94.11 boiled, drained 

Chives 90.65 -

Cole slaw 81.50 -

Collards 90.55 91.86 boiled, drained 

Corn—sweet 75.96 69.57 boiled, drained 

Cress—garden 89.40 92.50 boiled, drained 

Cucumbers—peeled 96.73 -

Dandelion—greens 85.60 89.80 boiled, drained 

Eggplant 92.41 89.67 boiled, drained 

Endive 93.79 -

Garlic 58.58 -

Kale 84.46 91.20 boiled, drained 

Kohlrabi 91.00 90.30 boiled, drained 

Lambsquarter 84.30 88.90 boiled, drained 

Leeks—bulb and lower leaf-portion 83.00 90.80 boiled, drained 

Lentils—sprouted 67.34 68.70 stir-fried 

Lettuce—iceberg 95.64 -

Lettuce—cos or romaine 94.61 -

Mung beans—mature seeds (sprouted) 90.40 93.39 boiled, drained 

Mushrooms—unspecified - 91.08 boiled, drained 

Mushrooms—oyster 88.80 -

Mushrooms—Maitake 90.53 -

Mushrooms—portabella 91.20 -

Mustard greens 90.80 94.46 boiled, drained 

Okra 90.17 92.57 boiled, drained 

Onions 89.11 87.86 boiled, drained 

Onions—dehydrated or dried 3.93 -

Parsley 87.71 -

Parsnips 79.53 80.24 boiled, drained 

Peas—edible-podded 88.89 88.91 boiled, drained 

Peppers—sweet—green 93.89 91.87 boiled, drained 

Peppers—hot chili-green 87.74 92.50* *canned solids and liquid 

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Exposure Factors Handbook 

Chapter 9—Intake of Fruits and Vegetables 

Table 9-37. Mean Moisture Content of Selected Food Groups Expressed as Percentages of 

Edible Portions (continued) 

Food Moisture Content Comments 

Raw Cooked 

Potatoes (white) 81.58 75.43 Baked 

Pumpkin 91.60 93.69 boiled, drained 

Radishes 95.27 -

Rutabagas—unspecified 89.66 88.88 boiled, drained 

Salsify (vegetable oyster) 77.00 81.00 boiled, drained 

Shallots 79.80 -

Soybeans—mature seeds—sprouted 69.05 79.45 Steamed 

Spinach 91.40 91.21 boiled, drained 

Squash—summer 94.64 93.70 all varieties; boiled, drained 

Squash—winter 89.76 89.02 all varieties; baked 

Sweet potatoes 77.28 75.78 baked in skin 

Swiss chard 92.66 92.65 boiled, drained 

Taro—leaves 85.66 92.15 Steamed 

Taro 70.64 63.80 

Tomatoes—juice - 93.90 Canned 

Tomatoes—paste - 73.50 Canned 

Tomatoes—puree - 87.88 Canned 

Tomatoes 93.95 -

Towel gourd 93.85 84.29 boiled, drained 

Turnips 91.87 93.60 boiled, drained 

Turnips—greens 89.67 93.20 boiled, drained 

Water chestnuts—Chinese 73.46 86.42* *canned solids and liquids 

Yambean—tuber 90.07 90.07 boiled, drained 

- Indicates data are not available for the fruit or vegetable under those conditions. 

* Number without added sugar. 

Source: USDA (2007). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

10. INTAKE OF FISH AND SHELLFISH 

10.1. INTRODUCTION 

Contaminated finfish and shellfish are potential 

sources of human exposure to toxic chemicals. 

Pollutants are carried in the surface waters but also 

may be stored and accumulated in the sediments as a 

result of complex physical and chemical processes. 

Finfish and shellfish are exposed to these pollutants 

and may become sources of contaminated food if the 

contaminants bioconcentrate in fish tissue or 

bioaccumulate through the food chain. Some 

chemicals (e.g., polychlorinated biphenyls and 

dioxins) are stored in fatty tissues, while others (e.g., 

mercury and arsenic) are typically found in the 

non-lipid components. 

Accurately estimating exposure to toxic 

chemicals in fish requires information about the 

nature of the exposed population (i.e., general 

population, recreational fishermen, subsistence 

fishers) and their intake rates. For example, general 

population intake rates may be appropriate for 

assessing contaminants that are widely distributed in 

commercially caught fish. However, these data may 

not be suitable to estimate exposure to contaminants 

in a particular water source among recreational or 

subsistence fishers. Because the catch of recreational 

and subsistence fishermen is not "diluted" by fish 

from other water bodies, these individuals and their 

families represent the population that is most 

vulnerable to exposure by intake of contaminated fish 

from a specific location. Subsistence fishermen are 

those individuals who consume fresh caught fish as a 

major source of food. Their intake rates are generally 

higher than those of the general population. It should 

be noted that, depending on the study, the data 

presented in this chapter for Native American 

populations may or may not reflect subsistence 

fishing. Harper and Harris (2008), and Donatuto and 

Harper (2008) describe some difficulties associated 

with evaluating fish intake rates among Native 

American subsistence populations. For example, 

Donatuto and Harper (2008) suggest that 

contemporary Native American subsistence intake 

rates may be lower (i.e., suppressed) compared to 

heritage rates. Also, the intake rates among certain 

subsets of the Native American populations may be 

higher than the rate for the average Native American 

(Donatuto and Harper, 2008; Harper and Harris, 

2008). 

This chapter focuses on intake rates of fish. Note 

that in this section the term fish refers to both finfish 

and shellfish, unless otherwise noted. Intake rates for 

the general population, and recreational and Native 

American fishing populations are addressed, and data 

are presented for intake rates for both marine and 

freshwater fish, when available. The general 

population studies in this chapter use the term 

consumer-only intake when referring to the quantity 

of fish and shellfish consumed by individuals during 

the survey period. These data are generated by 

averaging intake across only the individuals in the 

survey who consumed fish and shellfish. Per capita 

intake rates are generated by averaging 

consumer-only intakes over the entire survey 

population (including those individuals that reported 

no intake). In general, per capita intake rates are 

appropriate for use in exposure assessments for 

which average dose estimates are of interest because 

they represent both individuals who ate the foods 

during the survey period and individuals who may eat 

fish at some time but did not consume it during the 

survey period. Per capita intake, therefore, represents 

an average across the entire population of interest but 

does so at the expense of underestimating 

consumption for the population of fish consumers. 

Similarly, the discussions regarding recreationally 

caught fish consumption use the terms “all 

respondents” and “consuming anglers.” “All 

respondents” represents both survey 

individuals/anglers who ate recreationally caught fish 

during the survey period and those that did not but 

may eat recreationally caught fish during other 

periods. “Consuming anglers” refers only to the 

individuals who ate fish during the survey period. 

The determination to use consumer-only or per 

capita estimates of fish consumption in exposure 

assessments depends on the purpose of the 

assessment and on the source of the data. Both 

approaches can be a source of valuable insights on 

analyses of exposure and risk related to consumption 

of fish. This is because in the overall population, fish 

is not a frequently consumed item, and quantities 

may be relatively small, while in some populations, 

fish is consumed frequently and in large quantities. 

Nationwide surveys of food intake such as the 

Continuing Survey of Food Intake by Individuals 

(CSFII) or the National Health and Nutrition 

Examination Survey (NHANES) provide objective 

measures of food consumption that by design include 

overall, population-based estimates of fish 

consumption. The data from the CSFII or NHANES 

can be analyzed in terms of overall per capita 

consumption or consumers only. Although the CSFII 

and NHANES data are collected over short time 

periods, the large scale nature and design of such 

studies offer substantial advantages. In exposure 

analysis and risk assessment applications where fish 

intake is a concern, usually consumer-only data are of 

greater interest because of the relative infrequency of 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

fish consumption. Both approaches are a source of 

valuable insights and help to provide context for the 

results from specialized surveys that typically focus 

on fish consumption. Specialized surveys are done 

for a variety of reasons using different methodologies 

that typically focus on relatively small, high-fish 

consuming groups. It may be important to know how 

results based on small, high consuming groups 

compare to overall estimates of consumption based 

on per capita data and consumer-only data. The data 

presented in this chapter come from a variety of 

sources and were collected using various 

methodologies. Some data come from creel surveys 

where fishermen are usually asked, among other 

things, how much they have caught and the number 

of family members with which they will share their 

catch. These data will not represent usual behavior 

because one cannot assume that the angler will have 

the same luck over time. In all likelihood, there will 

be variation in the amounts caught and consumed by 

anglers that should be considered. Other data come 

from mail surveys or personal or phone interviews 

where participants are asked to recall how much fish 

each family member eats over a certain period of 

time. In some cases, data are recorded by survey 

participants in a food diary. Some surveys may ask 

about frequency of consumption, but not the amount. 

Frequency of consumption data can be combined 

with information on amount consumed per eating 

occasion to estimate consumption. The recall period 

determines if the survey characterizes long-term (i.e., 

usual intake) or short-term consumption. Exposure 

assessors are generally interested in estimates of 

long-term behaviors, but longer recall periods are 

associated with generally higher reporting error that 

should be considered. If the data come from a survey 

where long-term or usual intake is characterized (i.e., 

how often does someone eat fish in a year?), then 

consumer-only estimates may capture day-to-day 

variability in consumption. On the other hand, if the 

survey instrument used to collect the data 

characterizes short-term consumption (e.g., how 

much was eaten in a week, how much was consumed 

on a particular day), then a per capita estimate may 

account for the fact that individuals who are not 

consumers during the survey period may consume 

fish at some point over a longer time period. Using 

consumer-only data from short-term surveys may 

tend to overestimate consumption over the long term, 

especially at the high end, because it would not 

include days where respondents do not consume fish. 

Overestimates of consumption could, however, be 

considered conservative with regard to intake of 

contaminants and, thus, provide the basis for 

measures protective of human health. 

The U.S. Environmental Protection Agency (EPA) 

has prepared a review of and an evaluation of five 

different survey methods used for obtaining fish 

consumption data. They are 

 Recall-Telephone Survey, 

 Recall-Mail Survey, 

 Recall-Personal Interview, 

 Diary, and 

 Creel Census. 

Refer to U.S. EPA (1998) Guidance for 

Conducting Fish and Wildlife Consumption Surveys 

for more detail on these survey methods and their 

advantages and limitations. The type of survey used, 

its design, and any weighting factors used in 

estimating consumption should be considered when 

interpreting survey data for exposure assessment 

purposes. For surveys used in this handbook, 

respondents are typically adults who have reported on 

fish intake for themselves and for children living in 

their households. 

Generally, surveys are either "creel" studies in 

which fishermen are interviewed while fishing, or 

broader population surveys using either mailed 

questionnaires or phone interviews. Both types of 

data can be useful for exposure assessment purposes, 

but somewhat different applications and 

interpretations are needed. In fact, results from creel 

studies have often been misinterpreted, due to 

inadequate knowledge of survey principles. Below, 

some basic facts about survey design are presented, 

followed by an analysis of the differences between 

creel and population-based studies. 

Typical surveys seek to draw inferences about a 

larger population from a smaller sample of that 

population. This larger population, from which the 

survey sample is taken and to which the results of the 

survey are generalized, is denoted the target 

population of the survey. In order to generalize from 

the sample to the target population, the probability of 

being sampled must be known for each member of 

the target population. This probability is reflected in 

weights assigned to survey respondents, with weights 

being inversely proportional to sampling probability. 

When all members of the target population have the 

same probability of being sampled, all weights can be 

set to one and essentially ignored. For example, in a 

mail or phone study of licensed anglers, the target 

population is generally all licensed anglers in a 

particular area, and in the studies presented, the 

sampling probability is essentially equal for all target 

population members. 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

In a creel study (i.e., a study in which fishermen 

are interviewed while fishing), the target population 

is anyone who fishes at the locations being studied. 

Generally, in a creel study, the probability of being 

sampled is not the same for all members of the target 

population. For instance, if the survey is conducted 

for 1 day at a site, then it will include all persons who 

fish there daily, but only about 1/7 of the people who 

fish there weekly, 1/30 of the people who fish there 

monthly, etc. In this example, the probability of being 

sampled (or inverse weight) is seen to be proportional 

to the frequency of fishing. However, if the survey 

involves interviewers revisiting the same site on 

multiple days, and persons are only interviewed once 

for the survey, then the probability of being in the 

survey is not proportional to frequency; in fact, it 

increases less than proportionally with frequency. At 

the extreme of surveying the same site every day over 

the survey period with no re-interviewing, all 

members of the target population would have the 

same probability of being sampled regardless of 

fishing frequency, implying that the survey weights 

should all equal one. On the other hand, if the survey 

protocol calls for individuals to be interviewed each 

time an interviewer encounters them (i.e., without 

regard to whether they were previously interviewed), 

then the inverse weights will again be proportional to 

fishing frequency, no matter how many times 

interviewers revisit the same site. Note that when 

individuals can be interviewed multiple times, the 

results of each interview are included as separate 

records in the database and the survey weights should 

be inversely proportional to the expected number of 

times that an individual’s interviews are included in 

the database. 

In the published analyses of most creel studies, 

there is no mention of sampling weights; by default, 

all weights are set to one, implying equal probability 

of sampling. However, because the sampling 

probabilities in a creel study, even with repeated 

interviewing at a site, are highly dependent on fishing 

frequency, the fish intake distributions reported for 

these surveys are not reflective of the corresponding 

target populations. Instead, those individuals with 

high fishing frequencies are given too big a weight, 

and the distribution is skewed to the right, i.e., it 

overestimates the target population distribution. 

Price et al. (1994) explained this problem and set 

out to rectify it by adding weights to creel survey 

data; the authors used data from two creel studies 

(Puffer et al., 1982; Pierce et al., 1981) as examples. 

Price et al. (1994) used inverse fishing frequency as 

survey weights and produced revised estimates of 

median and 95th percentile intake for the above 

two studies. These revised estimates were 

dramatically lower than the original estimates. The 

approach of Price et al. (1994) is discussed in more 

detail in Section 10.4 where the Puffer et al. (1982) 

and Pierce et al. (1981) studies are summarized. 

When the correct weights are applied to survey 

data, the resulting percentiles reflect, on average, the 

distribution in the target population; thus, for 

example, an estimated 90% of the target population 

will have intake levels below the 90th percentile of the 

survey fish intake distribution. There is another way, 

however, of characterizing distributions in addition to 

the standard percentile approach; this approach is 

reflected in statements of the form “50% of the 

income is received by, for example, the top 10% of 

the population, which consists of individuals making 

more than $100,000.” Note that the 50th percentile 

(median) of the income distribution is well below 

$100,000. Here the $100,000 level can be thought of 

as, not the 50th percentile of the population income 

distribution, but as the 50th percentile of the “resource 

utilization distribution” (see Appendix 10A for 

technical discussion of this distribution). Other 

percentiles of the resource utilization distribution 

have similar interpretations; e.g., the 90th percentile 

of the resource utilization distribution (for income) 

would be that level of income such that 90% of total 

income is received by individuals with incomes 

below this level and 10% by individuals with income 

above this level. This alternative approach to 

characterizing distributions is of particular interest 

when a relatively small fraction of individuals 

consumes a relatively large fraction of a resource, 

which is the case with regards to recreational fish 

consumption. In the studies of recreational anglers, 

this alternative approach, based on resource 

utilization, will be presented, where possible, in 

addition to the primary approach of presenting the 

standard percentiles of the fish intake distribution. 

The recommendations for fish and shellfish 

ingestion rates are provided in the next section, along 

with summaries of the confidence ratings for these 

recommendations. The recommended values for the 

general population and for other subsets of the 

population are based on the key studies identified by 

U.S. EPA for this factor. Following the 

recommendations, the studies on fish ingestion 

among the general population (see Section 10.3), 

marine recreational angler populations (see 

Section 10.4), freshwater recreational populations 

(see Section 10.5), and Native American populations 

(see Section 10.6) are summarized. Information is 

provided on the key studies that form the basis for the 

fish and shellfish intake rate recommendations. 

Relevant data on ingestion of fish and shellfish are 

also provided. These studies are presented to provide 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

the reader with added perspective on the current 

state-of-knowledge pertaining to ingestion of fish and 

shellfish among children and adults. Information on 

other population studies (see Section 10.7), serving 

size (see Section 10.8), and other factors to consider 

(see Section 10.9) are also presented. 

10.2. RECOMMENDATIONS 

Considerable variation exists in the mean and 

upper percentile fish consumption rates obtained 

from the studies presented in this chapter. This can be 

attributed largely to the type of water body (i.e., 

marine, estuarine, freshwater) and the characteristics 

of the survey population (i.e., general population, 

recreational, Native American), but other factors such 

as study design, method of data collection, and 

geographic location also play a role. Based on these 

study variations, fish consumption studies were 

classified into the following categories: 

 General Population (finfish, shellfish, and 

total fish and shellfish combined); 

 Recreational Marine Intake; 

 Recreational Freshwater Intake; and 

 Native American Populations 

For exposure assessment purposes, the selection 

of intake rates for the appropriate category (or 

categories) will depend on the exposure scenario 

being evaluated. 

10.2.1. Recommendations—General Population 

Fish consumption rates are recommended for the 

general population, based on the key study presented 

in Section 10.3.1. The key study for estimating mean 

fish intake among the general population is the 

U.S. EPA analysis of data from the Centers for 

Disease Control and Prevention (CDC) NHANES 

2003–2006. 

Table 10-1 presents a summary of the 

recommended values for per capita and 

consumer-only intake of finfish, shellfish, and total 

finfish and shellfish combined. Table 10-2 provides 

confidence ratings for the fish intake 

recommendations for the general population. The 

U.S. EPA analysis of 2003–2006 NHANES data was 

conducted using childhood age groups that differed 

slightly from U.S. EPA’s Guidance on Selecting Age 

Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. 

EPA, 2005). However, for the purposes of the 

recommendations presented here, data were placed in 

the standardized age categories closest to those used 

in the analysis. 

Note that the fish intake values presented in Table 

10-1 are reported as uncooked fish weights. Recipe 

files were used to convert, for each fish-containing 

food, the as-eaten fish weight consumed into an 

uncooked equivalent weight of fish. This is important 

because the concentrations of the contaminants in 

fish are generally measured in the uncooked samples. 

Assuming that cooking results in some reductions in 

weight (e.g., loss of moisture), and the mass of the 

contaminant in the fish tissue remains constant, then 

the contaminant concentration in the cooked fish 

tissue will increase. 

In terms of calculating the dose (i.e., 

concentration times weight), actual consumption may 

be overestimated when intake is expressed on an 

uncooked basis, but the actual concentration may be 

underestimated when it is based on the uncooked 

sample. The net effect on the dose would depend on 

the magnitude of the opposing effects on these 

two exposure factors. On the other hand, if the 

"as-prepared" (i.e., as-consumed) intake rate and the 

uncooked concentration are used in the dose 

equation, dose may be underestimated because the 

concentration in the cooked fish is likely to be higher, 

if the mass of the contaminant remains constant after 

cooking. Reported weights are also more likely to 

reflect uncooked weight, and interpretation of 

advisories are likely to be in terms of uncooked 

weights. Although it is generally more conservative 

and appropriate to use uncooked fish intake rates, one 

should also be sure to use like measures. That is to 

say, avoid using raw fish concentrations and cooked 

weights to estimate the dose. For more information 

on cooking losses and conversions necessary to 

account for such losses, refer to Chapter 13 of this 

handbook. 

If concentration data can be adjusted to account 

for changes after cooking, then the "as-prepared" 

(i.e., as-consumed) intake rates are appropriate. 

However, data on the effects of cooking on 

contaminant concentrations are limited, and assessors 

generally make the conservative assumption that 

cooking has no effect on the contaminant mass. The 

key study on fish ingestion provides intake data 

based on uncooked fish weights. However, relevant 

data on both "as-prepared" (i.e., as-consumed) and 

uncooked general population fish intake are also 

presented in this handbook. The assessor should 

choose the intake data that best matches the 

concentration data that are being used. 

The NHANES data on which the general 

population recommendations are based, are 

short-term survey data and could not be used to 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

estimate the distribution over the long term. Also, it is 

important to note that a limitation associated with 

these data is that the total amount of fish reported by 

respondents included fish from all sources (e.g., 

fresh, frozen, canned, domestic, international origin). 

The analysis of NHANES survey data used to 

develop the recommended intake rates in this 

handbook did not consider the source of the fish 

consumed. This type of information may be relevant 

for some assessments. 

Recommended values should be selected that are 

relevant to the assessment, choosing the appropriate 

age groups and type of fish (i.e., finfish, shellfish, or 

total finfish, and shellfish). In some cases, a different 

study or studies may be particularly relevant to the 

needs of an assessment, in which case, results from 

that specific study or studies may be used instead of 

the recommended values provided here. For example, 

it may be advantageous to use estimates that target a 

particular region or geographical area, if relevant data 

are available. In addition, seasonal, sex, and fish 

species variations should be considered when 

appropriate, if data are available. Also, relevant data 

on general population fish intake in this chapter may 

be used if appropriate to the scenarios being assessed. 

For example, older data from the U.S. EPA’s analysis 

of data from the 1994–1996 and 1998 CSFII provide 

intake rates for freshwater/estuarine fish and 

shellfish, marine fish and shellfish, and total fish and 

shellfish that are not available from the more recent 

NHANES analysis. 

10.2.2.	 Recommendations—Recreational Marine 

Anglers 

Table 10-3 presents the recommended values for 

recreational marine anglers. These values are based 

on the surveys of the National Marine Fisheries 

Service (NMFS, 1993). The values from NMFS 

(1993) are assumed to represent intake of marine fish 

among adult recreational fishers. Values represent 

both individuals who ate recreational fish during the 

survey period and those that did not, but may eat 

recreationally caught fish during other periods. 

Age-specific values were not available from this 

source. However, recommendations for children were 

estimated based on the ratios of marine fish intake for 

general population children to that of adults using 

data from U.S. EPA’s analysis of CSFII data from 

1994–1996 and 1998 (U.S. EPA, 2002) (see 

Section 10.3.2.6), multiplied by the adult recreational 

marine fish intake rates for the Atlantic, Gulf, and 

Pacific regions, using data from NMFS (1993) (see 

Section 10.4.1.1). The ratios of each age group to 

adults >18 years were calculated separately for the 

means and 95th percentiles. Much of the other 

relevant data on recreational marine fish intake in this 

chapter are limited to certain geographic areas and 

cannot be generalized to the U.S. population as a 

whole. However, assessors may use the data from the 

relevant studies provided in this chapter if 

appropriate to the scenarios being assessed. Table 

10-4 presents the confidence ratings for 

recommended recreational marine fish intake rates. 

10.2.3.	 Recommendations—Recreational 

Freshwater Anglers 

Recommended values are not provided for 

recreational freshwater fish intake because the 

available data are limited to certain geographic areas 

and cannot be readily generalized to the U.S. 

population of freshwater recreational anglers as a 

whole (see Figure 10-1). For example, factors 

associated with water body, climate, fishing 

regulations, availability of alternate fishable water 

bodies, and water body productivity may affect 

recreational fish intake rates. However, data from 

several relevant recreational freshwater studies are 

provided in this chapter. Table 10-5 summarizes data 

from these studies. Assessors may use these data, if 

appropriate to the scenarios and locations being 

assessed. Although recommendations are not 

provided, some general observations can be made. 

Most of the studies in Table 10-5 represent state-wide 

surveys of recreational anglers. These include 

Alabama, Connecticut, Indiana, Maine, Michigan, 

Minnesota, North Dakota, and Wisconsin. 

Consumption data from these states would include 

freshwater fish from rivers, lakes, and ponds. The 

average range of consumption for all respondents 

from these states varies from 5 g/day to 51 g/day. 

Another two studies represent consumption of fish 

from specific rivers. These included Savannah River 

in Georgia and The Clinch River in Tennessee. The 

consumption rates for all respondents from these 

two rivers ranged from 20 g/day to 70 g/day. One of 

the studies in Table 10-5 represents the consumption 

of fish from three lakes in Washington, and another 

represents consumption of fish from Lake Ontario. 

The average consumption rate for all responding 

adults was 10 g/day for the three Washington lakes. It 

can also be noted that a large percentage of 

recreational anglers consumed fish and shellfish 

during the survey period. Thus, values for all 

respondents and consuming anglers are fairly similar. 

For Lake Ontario, the average consumption rate for 

adults was 5 g/day. 

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Chapter 10—Intake of Fish and Shellfish 

10.2.4.	 Recommendations—Native American 

Populations 

Recommended values are also not provided for 

Native American fish intake because the available 

data are limited to certain geographic areas and/or 

tribes and cannot be readily generalized to Native 

American tribes as a whole. However, data from 

several Native American studies are provided in this 

chapter and are summarized in Table 10-6. Assessors 

may use these data, if appropriate to the scenarios 

and populations being assessed. These studies were 

performed at various study locations among various 

tribes. 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-1. Recommended Per Capita and Consumer-Only Values for Fish Intake (g/kg-day), Uncooked Fish 

Weight, by Age 

Age 

Per Capita Consumers Only 

N 

% 

Consuming Mean 

95th 

percentile N Mean 

95th 

percentile Source 

Finfisha 

All 16,783 23 0.16 1.1 3,204 0.73 2.2 

U.S. EPA 

Analysis 

of 

NHANES 

2003– 

2006 data 

Birth to 1 year 865 2.6 0.03 0.0b 22 1.3 2.9b 

1 to <2 years 1,052 14 0.22 1.2b 143 1.6 4.9b 

2 to <3 years 1,052 14 0.22 1.2b 143 1.6 4.9b 

3 to <6 years 978 15 0.19 1.4 156 1.3 3.6b 

6 to <11 years 2,256 15 0.16 1.1 333 1.1 2.9b 

11 to <16 years 3,450 15 0.10 0.7 501 0.66 1.7 

16 to <21 years 3,450 15 0.10 0.7 501 0.66 1.7 

21 to <50 years 4,289 23 0.15 1.0 961 0.65 2.1 

Females 13 to 49 years 4,103 22 0.14 0.9 793 0.62 1.8 

50+ years 3,893 29 0.20 1.2 1,088 0.68 2.0 

Shellfisha 

All 16,783 11 0.06 0.4 1,563 0.57 1.9 

U.S. EPA 

Analysis 

of 

NHANES 

2003– 

2006 data 

Birth to 1 year 865 0.66 0.00 0.0b 11 0.42 2.3b 

1 to <2 years 1,052 4.4 0.04 0.0b 53 0.94 3.5b 

2 to <3 years 1,052 4.4 0.04 0.0b 53 0.94 3.5b 

3 to <6 years 978 4.6 0.05 0.0 56 1.0 2.9b 

6 to <11 years 2,256 7.0 0.05 0.2 158 0.72 2.0b 

11 to <16 years 3,450 5.1 0.03 0.0 245 0.61 1.9 

16 to <21 years 3,450 5.1 0.03 0.0 245 0.61 1.9 

21 to <50 years 4,289 13 0.08 0.5 605 0.63 2.2 

Females 13 to 49 years 4,103 11 0.06 0.3 474 0.53 1.8 

50+ years 3,893 13 0.05 0.4 435 0.41 1.2 

Total Finfish and Shellfisha 

All 16,783 29 0.22 1.3 4,206 0.78 2.4 

U.S. EPA 

Analysis 

of 

NHANES 

2003– 

2006 data 

Birth to 1 year 865 3.1 0.04 0.0b 30 1.2 2.9b 

1 to <2 years 1,052 17 0.26 1.6b 183 1.5 5.9b 

2 to <3 years 1,052 17 0.26 1.6b 183 1.5 5.9b 

3 to <6 years 978 18 0.24 1.6 196 1.3 3.6b 

6 to <11 years 2,256 22 0.21 1.4 461 0.99 2.7b 

11 to <16 years 3,450 18 0.13 1.0 685 0.69 1.8 

16 to <21 years 3,450 18 0.13 1.0 685 0.69 1.8 

21 to <50 years 4,289 31 0.23 1.3 1,332 0.76 2.5 

Females 13 to 49 years 4,103 28 0.19 1.2 1,109 0.68 1.9 

50+ years 3,893 36 0.25 1.4 1,319 0.71 2.1 a Analysis was conducted using slightly different childhood age groups than those recommended in Guidance on Selecting 

Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005). Data 

were placed in the standardized age categories closest to those used in the analysis. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance 

Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical 

Working Group Recommendations (NCHS, 1993). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-2. Confidence in Recommendations for General Population Fish Intake 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodology and the analysis of the survey 

data were adequate. Primary data were collected and 

used in a secondary analysis of the data. The sample 

size was large. 

The response rate was adequate. The survey data were 

based on recent recall. Data were collected over a short 

duration (i.e., 2 days). 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key study focused on the exposure factor of 

interest. 

The survey was conducted nationwide and was 

representative of the general U.S. population. 

Data were derived from 2003–2006 NHANES. 

Data were collected for 2 non-consecutive days. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The primary data are accessible through CDC. 

The methodology was clearly presented; enough 

information was available to allow for reproduction of 

the results. 

Quality assurance of NHANES data was good; quality 

control of secondary analysis was good. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were provided by the key study. 

The survey was not designed to capture long-term 

intake and was based on recall. 

Medium to high for 

averages; low for 

long-term upper 

percentiles 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The National Center for Health Statistics (NCHS) 

NHANES survey received a high level of peer review. 

The U.S. EPA analysis of these data has not been peer 

reviewed outside the Agency, but the methodology used 

has been peer reviewed in analysis of previous data. 

The number of studies is one. 

Medium 

Overall Rating Medium to High 

(mean) 

Medium (long-term 

upper percentiles) 

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Chapter 10—Intake of Fish and Shellfish 

Table 10-3. Recommended Values for Recreational Marine Fish Intake 

Age Group	 Intake Ratea 

Mean g/dayb	 95th Percentile g/dayb 

Atlantic 

3 to <6 years 2.5 8.8 

6 to <11 years 2.5 8.6 

11 to <16 years 3.4 13 

16 to <18 years 2.8 6.6 

>18 years 5.6 18 

Gulf 

3 to <6 years 3.2 13 

6 to <11 years 3.3 12 

11 to <16 years 4.4 18 

16 to <18 years 3.5 9.5 

>18 years 7.2 26 

Pacific 

3 to <6 years 0.9 3.3 

6 to <11 years 0.9 3.2 

11 to <16 years 1.2 4.8 

16 to <18 years 1.0 2.5 

>18 years 2.0 6.8 

a	 Represents intake for the recreational fishing population only. Data from U.S. EPA analysis of NMFS 

(1993) assumed to represent adults >18 years. Values represent both survey anglers who ate recreational 

fish during the survey period and those that did not, but may eat recreationally caught fish during other 

periods. b	 Recommendations for children were estimated based on the ratios of marine fish intake for general 

population children to that of adults using data from U.S. EPA’s analysis of CSFII data (see Table 10-31), 

multiplied by the adult recreational marine fish intake rates for the Atlantic, Gulf, and Pacific regions, 

using data from NMFS (1993) (see Table 10-50).The ratios of each age group to adults >18 years were 

calculated separately for the means and 95th percentiles. 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-4. Confidence in Recommendations for Recreational Marine Fish Intake 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodology and the analysis of the survey data 

were adequate. Primary data were collected and used in a 

secondary analysis of the data. The sample size was large. 

The response rate was adequate. The survey data were based 

on recent recall. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key study was not designed to estimate individual 

consumption of fish. U.S. EPA obtained the raw data and 

estimated intake distributions by employing assumptions 

derived from other data sources. 

The survey was conducted in coastal states in the Atlantic, 

Pacific, and Gulf regions and was representative of fishing 

populations in these regions of the United States. 

The data are from a survey conducted in 1993. 

Data were collected in telephone interviews and direct 

interviews of fishermen in the field over a short time frame. 

Low to Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The primary data are from NMFS. 

The methodology was clearly presented; enough information 

was available to allow for reproduction of the results. 

Quality assurance of the primary data was not described. 

Quality assurance of the secondary analysis was good. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Mean and 95th percentile values were provided. 

The survey was specifically designed to estimate individual 

intake rates. U.S. EPA estimated intake based on an analysis 

of the raw data, using assumptions about the number of 

individuals consuming fish meals from the fish caught. 

Estimates for children are based on additional assumptions 

regarding the proportion of intake relative to the amount 

eaten by adults. 

Low 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

Data from NMFS (1993) were reviewed by NMFS and 

U.S. EPA. U.S. EPA’s analysis was not peer reviewed outside 

of EPA. 

The number of studies is one. 

Medium 

Overall Rating Low to Medium (adults) 

Low (children) 

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Chapter 10—Intake of Fish and Shellfish 

Table 10-5. Summary of Relevant Studies on Freshwater Recreational Fish Intake 

Location Population Group Mean 95th Percentile Source 

g/day g/day 

Alabama All Respondents (Adults) 

Consuming Anglers 

44a 

53b 

-

-

ADEM (1994) 

Connecticut All Respondents 

Consuming Anglers 

51c 

53c,d 

-

-

Balcom et al. (1999) 

Georgia 

(Savannah 

River) 

All Respondents (Adult 

Whites) 

All Respondents (Adult 

Blacks) 

38e 

70e 

-

-

Burger et al. (1999) 

Indiana All Respondents 

Consuming Anglers 

16 

20 

61 

61 

Williams et al. (1999) 

Maine All Respondents 

Consuming Anglers 

5.0 

6.4 

21 

26 

ChemRisk (1992); 

Ebert et al. (1993) 

Michigan Consuming Anglers 

1 to 5 years 

6 to 10 years 

11 to 20 years 

21 to 80 years 

All ages 

5.6 

7.9 

7.3 

16f 

14 

-

-

-

-

39 

West et al. (1993; 

1989) 

Minnesota All Respondents 

0 to 14 years 

>14 years (male) 

15 to 44 (female) 

>44 (female) 

Consuming Anglers 

1.2 (50th percentile) 

4.5 (50th percentile) 

2.1 (50th percentile) 

3.6 (50th percentile) 

14 

14 

40 

25 

37 

37 

Benson et al. (2001) 

New York 

(Lake Ontario) 

All Respondents (Adults) 

Consuming Anglers 

4.9f 

5.8g 

18 

-

Connelly et al. (1996) 

North Dakota All Respondents 

0 to 14 years 

>14 years (male) 

15 to 44 (female) 

>44 (female) 

Consuming Anglers 

1.7 (50th percentile) 

2.3 (50th percentile) 

4.3 (50th percentile) 

4.2 (50th percentile) 

12 

22 

25 

30 

33 

43 

Benson et al. (2001) 

Tennessee 

(Clinch River) 

All Respondents 

Consuming Anglers 

20e,h 

38e,h 

-

-

Rouse Campbell et 

al. (2002) 

Washington All Respondents (Adults) 

Children of Respondents 

Consuming Anglers 

(Adults) 

10 

7 

15i 

42 

29 

-

Mayfield et al. (2007) 

Wisconsin All Respondents (Adults) 

Consuming Anglers 

11 

12 

37 

37 

Fiore et al. (1989) 

Summary (mean 

ranges) 

Statewide Surveysj 

Riversk 

Lakesl 

5–51 g/day 

20–70 g/day 

5–10 g/day 

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Chapter 10—Intake of Fish and Shellfish 

Table 10-5. Summary of Relevant Studies on Freshwater Recreational Fish Intake (continued) a 

b 

c 

d 

e 

f 

g 

h 

i 

j 

k 

l 

-

Note 

Based on the average of two methods. 

Value represents anglers who consumed recreationally caught fish during the survey period, calculated by 

dividing all respondents by the percent consuming of 83%. 

Values included consumption of both freshwater and saltwater fish. 

Value calculated by dividing all respondents by the percent consuming of 97%. 

Calculated as amount eaten per year divided by 365 days per year. 

Based on average of multiple adult age groups. 

Value calculated by dividing all respondents by the percent consuming of 84%. 

Values included consumption of both self-caught and store-bought fish. 

Value calculated by dividing all respondents by the percent consuming of 66%. 

Represents the range from the following states: Alabama, Connecticut, Indiana, Maine, Michigan, 

Minnesota, North Dakota, and Wisconsin. 

Represents the range from the following rivers: Savannah River in GA and The Clinch River in TN. 

Represents the range from three lakes in Washington and Lake Ontario. 

Estimate not available. 

All respondents represent both survey anglers who ate recreational fish during the survey period and those 

that did not, but may eat recreationally caught fish during other periods. 

Figure 10-1. Locations of Freshwater Fish Consumption Surveys in the United States. 

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Chapter 10—Intake of Fish and Shellfish 

Table 10-6. Summary of Relevant Studies on Native American Fish Intake 

Location/Tribe Population Group Mean a 95th Percentilea Source 

94 Alaska 

Communities 

All Respondents 

Lowest of 94 

Median of 94 

Highest of 94 

16 g/day 

81 g/day 

770 g/day 

-

-

-

Chippewa Indians 

(Wisconsin) 

All Respondents 

Adults 39 g/dayb -

4 Columbia River 

Tribes 

(Oregon) 

All Respondents 

Adults 

Children <5 years 

Consumers 

Adults 

59 g/day 

11 g/day (50th percentile) 

63 g/dayc 

170 g/day 

98 g/day 

183c 

Florida All Respondents 

Consumersd 

0.8 g/kg-day 

1.5 g/kg-day 

4.5 g/kg-day 

5.7 g/kg-day 

Minnesota All Respondents 

Consumersd 

2.8 g/kg-day 

2.8 g/kg-day 

-

-

Mohawk Tribe 

(New York and 

Canada) 

All Respondents 

Women 

Consuming Women 

13 g/daye 

16 g/daye 

-

-

Mohawk Tribe 

(New York and 

Canada) 

All Respondents

f 

Adults 

Children 2 yearsf 

Consumers 

Adultsf 

Children 2 yearsf 

25 g/day 

10 g/day 

29 g/day 

13 g/day 

131 g/day 

54 g/day 

135 g/day 

58 g/day 

North Dakota All Respondents 

Consumersb 

0.4 g/kg-day 

0.4 g/kg-day 

0.9g 

0.8 g 

Tulalip Tribe 

(Washington) 

Squaxin Island Tribe 

(Washington) 

All Respondents 

Adult 

Children birth <5 years 

All Respondents 

Adults 

Children 

0.9 g/kg-day 

0.2 g/kg-day 

0.9 g/kg-day 

0.8 g/kg-day 

2.9 g/kg-day 

0.7 g/kg-dayg 

3.0 g/kg-day 

2.1 g/kg-dayg 

Tulalip Tribe 

(Washington) 

Squaxin Island Tribe 

(Washington) 

Consumers 

Adults 

Children birth <5 years 

Consumers 

Adults 

Children birth <5 years 

1.0 g/kg-day 

0.4 g/kg-day 

1.0 g/kg-day 

2.9 g/kg-day 

2.6 g/kg-day 

0.8 g/kg-dayg 

3.4 g/kg-day 

7.7 g/kg-day 

Suquamish Tribe 

(Washington) 

All Respondents 

Adults 

Children <6 years 

Consumers 

Adults 

Children <6 years 

2.7 g/kg-day 

1.5 g/kg-day 

2.7 g/kg-day 

1.5 g/kg-day 

10 g/kg-day 

7.3 g/kg-day 

10 g/kg-day 

7.3 g/kg-day 

Wolfe and Walker 

(1987) 

Peterson et al. 

(1994) 

CRITFC (1994) 

Westat (2006) 

Westat (2006) 

Fitzgerald et al. 

(1995) 

Forti et al. (1995) 

Westat (2006) 

Toy et al. (1996) 

Polissar et al. 

(2006) 

Duncan (2000) 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-6. Summary of Relevant Studies on Native American Fish Intake (continued) 

a Results are reported in g/day or g/kg-day, depending on which was provided in the source material. b All respondents consumed fish caught in Northern Wisconsin lakes. 

Value calculated by dividing all respondents by the percent consuming of 93%. d Based on uncooked fish weight. e Value represents consumption by Mohawk women >1 year before pregnancy. Value estimated by 

multiplying number of fish meals/year by the 90th percentile meal size of 209 g/meal for general population 

females 20–39 years old from Smiciklas-Wright et al. (2002). f Based on 90th percentile general population meal size, based on Pao et al. (1982). g Value represents the 90th percentile. 

- Estimate not available. 

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Chapter 10—Intake of Fish and Shellfish 

10.3. GENERAL POPULATION STUDIES 

10.3.1. Key General Population Study 

10.3.1.1.	 U.S. EPA Analysis of Consumption Data 

From 2003–2006 NHANES 

The key source of recent information on 

consumption rates of fish and shellfish is the U.S. 

CDC’s NCHS’ NHANES. Data from NHANES 

2003–2006 have been used by the U.S. EPA, Office 

of Pesticide Programs (OPP) to generate per capita 

and consumer-only intake rates for finfish, shellfish, 

and total fish and shellfish combined. 

NHANES is designed to assess the health and 

nutritional status of adults and children in the United 

States. In 1999, the survey became a continuous 

program that interviews a nationally representative 

sample of approximately 7,000 persons each year and 

examines a nationally representative sample of about 

5,000 persons each year, located in counties across 

the country, 15 of which are visited each year. Data 

are released on a 2-year basis, thus, for example, the 

2003 data are combined with the 2004 data to 

produce NHANES 2003–2004. 

The dietary interview component of NHANES is 

called What We Eat in America and is conducted by 

the U.S. Department of Agriculture (USDA) and the 

U.S. Department of Health and Human Services 

(DHHS). DHHS’ NCHS is responsible for the sample 

design and data collection, and USDA’s Food 

Surveys Research Group is responsible for the dietary 

data collection methodology, maintenance of the 

databases used to code and process the data, and data 

review and processing. Beginning in 2003, 

2 non-consecutive days of 24-hour intake data were 

collected. The first day is collected in-person, and the 

second day is collected by telephone 3 to 10 days 

later. These data are collected using USDA’s dietary 

data collection instrument, the Automated Multiple 

Pass Method. This method provides an efficient and 

accurate means of collecting intakes for large-scale 

national surveys. It is fully computerized and uses a 

five-step interview. Details can be found at USDA’s 

Agriculture Research Service 

(http://www.ars.usda.gov/ba/bhnrc/fsrg). 

For NHANES 2003–2004, there were 

12,761 persons selected; of these, 9,643 were 

considered respondents to the mobile examination 

center (MEC) for examination and data collection. 

However, only 9,034 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,354 provided complete dietary intakes for Day 2. 

For NHANES 2005–2006, there were 12,862 persons 

selected; of these, 9,950 were considered respondents 

to the MEC examination and data collection. 

However, only 9,349 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,429 provided complete dietary intakes for Day 2. 

The 2003–2006 NHANES surveys are stratified, 

multistage probability samples of the civilian 

non-institutionalized U.S. population. The sampling 

frame was organized using 2000 U.S. population 

census estimates. NHANES oversamples low-income 

persons, adolescents 12–19 years, persons 60 years 

and older, African Americans, and Mexican 

Americans. Several sets of sampling weights are 

available for use with the intake data. By using 

appropriate weights, data for all 4 years of the 

surveys can be combined. Additional information on 

NHANES can be obtained at 

http://www.cdc.gov/nchs/nhanes.htm. 

In 2010, U.S. EPA’s OPP used NHANES 2003– 

2006 data to update the Food Commodity Intake 

Database (FCID) that was developed in earlier 

analyses of data from the U.S. Department of 

Agriculture’s (USDA’s) CSFII (U.S. EPA, 2002; 

USDA, 2000). NHANES data on the foods people 

reported eating were converted to the quantities of 

agricultural commodities eaten. "Agricultural 

commodity" is a term used by U.S. EPA to mean 

plant (or animal) parts consumed by humans as food; 

when such items are raw or unprocessed, they are 

referred to as "raw agricultural commodities." For 

example, clam chowder may contain the commodities 

clams, vegetables, and spices. FCID contains 

approximately 553 unique commodity names and 

eight-digit codes. The FCID commodity names and 

codes were selected and defined by U.S. EPA and 

were based on the U.S. EPA Food Commodity 

Vocabulary 

(http://www.epa.gov/pesticides/foodfeed/). 

Intake rates were generated for finfish, shellfish, 

and finfish and shellfish combined. These intake rates 

represent intake of all forms of the food (e.g., both 

self-caught and commercially caught) for individuals 

who provided data for 2 days of the survey. 

Individuals who did not provide information on body 

weight or for whom identifying information was 

unavailable were excluded from the analysis. Twoday average intake rates were calculated for all 

individuals in the database for each of the food 

items/groups. Note that if the person reported 

consuming fish on only one day of the survey, their 

2-day average would be half the amount reported for 

the one day of consumption. These average daily 

intake rates were divided by each individual's 

reported body weight to generate intake rates in units 

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Chapter 10—Intake of Fish and Shellfish 

day). The data were weighted according to the 4-year, 

2-day sample weights provided in NHANES 2003– 

2006 to adjust the data for the sample population to 

reflect the national population. 

Summary statistics were generated on a 

consumer-only and on a per capita basis. Summary 

statistics, including number of observations, 

percentage of the population consuming fish, mean 

intake rate, and standard error of the mean intake rate 

were calculated for finfish, shellfish, and finfish and 

shellfish combined, for both the entire population and 

consumers only (see Table 10-7 to Table 10-12). Data 

were provided for the following age groups: birth to 

<1 year, 1 to 2 years, 3 to 5 years, 6 to 12 years, 13 to 

19 years, 20 to 49 years, and ≥50 years. Because 

these data were developed for use in U.S. EPA’s 

pesticide registration program, the childhood age 

groups used are slightly different than those 

recommended in U.S. EPA’s Guidance on Selecting 

Age Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. 

EPA, 2005). 

The results are presented in units of g/kg-day 

(same as the CSFII data). Thus, use of these data in 

calculating potential dose does not require the 

body-weight factor to be included in the denominator 

of the average daily dose equation. It should be noted 

that converting these intake rates into units of g/day 

by multiplying by a single average body weight is 

inappropriate because individual intake rates were 

indexed to the reported body weights of the survey 

respondents. Also, it should be noted that the 

distribution of average daily intake rates generated 

using short-term data (e.g., 2-day) does not 

necessarily reflect the long-term distribution of 

average daily intake rates. The distributions 

generated from short-term and long-term data will 

differ to the extent that each individual’s intake varies 

from day to day; the distributions will be similar to 

the extent that individuals’ intakes are constant from 

day to day. Because of the increased variability of the 

short-term distribution, the short-term upper 

percentiles shown here may overestimate the 

corresponding percentiles of the long-term 

distribution. 

The advantages of using the U.S. EPA’s analysis 

of NHANES data are that it provides distributions of 

intake rates for various age groups of children and 

adults, normalized by body weight. The data set was 

designed to be representative of the U.S. population, 

and includes 4 years of intake data combined. 

Another advantage is the currency of the data. The 

NHANES data are from 2003–2006. However, 

short-term consumption data may not accurately 

reflect long-term eating patterns and may 

under-represent infrequent consumers of a given fish 

species. This is particularly true for the tails 

(extremes) of the distribution of food intake. Because 

these are 2-day averages, consumption estimates at 

the upper end of the intake distribution may be 

underestimated if these consumption values are used 

to assess acute (i.e., short-term) exposures. Also, the 

analysis was conducted using slightly different 

childhood age groups than those recommended in 

U.S. EPA’s Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

However, given the similarities in the age groups 

used, the data should provide suitable intake 

estimates for the age groups of interest. 

10.3.2. Relevant General Population Studies 

10.3.2.1. SRI (1980)—Seafood Consumption Study 

SRI (1980) utilized data that were originally 

collected in a study funded by the Tuna Research 

Foundation (TRF) to estimate fish intake rates. The 

TRF study of fish consumption was performed by the 

National Purchase Diary during the period of 

September, 1973 to August, 1974. The data tapes 

from this survey were obtained by the NMFS, which 

later, along with the Food and Drug Administration, 

USDA and TRF, conducted an intensive effort to 

identify and correct errors in the database. SRI (1980) 

summarized the TRF survey methodology and used 

the corrected tape to generate fish intake distributions 

for various population groups. 

The TRF survey sample included 9,590 families, 

of which 7,662 (25,162 individuals) completed the 

questionnaire, a response rate of 80%. The survey 

was weighted to represent the U.S. population. 

The population of fish consumers represented 

94% of the U.S. population. For this population of 

“fish consumers,” SRI (1980) calculated means and 

percentiles of fish consumption by demographic 

variables (age, sex, race, census region, and 

community type) and overall (see Table 10-13). The 

overall mean fish intake rate among fish consumers 

was calculated at 14.3 g/day and the 95th percentile at 

41.7 g/day. 

Table 10-14 presents the distribution of fish 

consumption for females and males, by age; this table 

give the percentages of females/males in a given age 

bracket with intake rates within various ranges. Table 

10-15 presents mean total fish consumption by fish 

species. 

The TRF survey data were also utilized by Rupp 

et al. (1980) to generate fish intake distributions for 

three age groups (1 to 11, 12 to 18, and 18 to 

98 years) within each of the 9 census regions and for 

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Chapter 10—Intake of Fish and Shellfish 

the entire United States. Separate distributions were 

derived for freshwater finfish, saltwater finfish, and 

shellfish. Ruffle et al. (1994) used the percentiles data 

of Rupp et al. (1980) to estimate the best-fitting 

lognormal parameters for each distribution. Table 

10-16 presents the optimal lognormal parameters, the 

mean (μ) and standard deviation (σ). These 

parameters can be used to determine percentiles of 

the corresponding distribution of average daily fish 

consumption rates through the relation 

(p) = exp[μ + z(p)σ] where DCR(p) is the pth 

percentile of the distribution of average daily fish 

consumption rates and z(p) is the z-score associated 

with the pth percentile (e.g., z(50) = 0). The mean 

average daily fish consumption rate is given by exp 

[μ + 0.5σ2

]. 

The advantages of the TRF data survey are that it 

was a large, nationally representative survey with a 

high response rate (80%) and was conducted over an 

entire year. In addition, consumption was recorded in 

a daily diary over a 1-month period; this format 

should be more reliable than one based on 1-month 

recall. The upper percentiles presented are derived 

from 1 month of data and are likely to overestimate 

the corresponding upper percentiles of the long-term 

(i.e., 1 year or more) average daily fish intake 

distribution. Similarly, the standard deviation of the 

fitted lognormal distribution probably overestimates 

the standard deviation of the long-term distribution. 

However, the period of this survey (1 month) is 

considerably longer than those of many other 

consumption studies, including the USDA National 

Food Consumption Surveys, CSFII, and NHANES, 

which report consumption over a 2-day to 1-week 

period. Another obvious limitation of this database is 

that it is now over 30 years out of date. Ruffle et al. 

(1994) considered this shortcoming and suggested 

that one may wish to shift the distribution upward to 

account for the recent increase in fish consumption, 

though CSFII has shown little change in g/day fish 

consumption from 1978 to 1996. Adding 

ln(1 + x/100) to the log mean μ will shift the 

distribution upward by x% (e.g., adding 

0.22 = ln(1.25) increases the distribution by 25%). 

Although the TRF survey distinguished between 

recreationally and commercially caught fish, SRI 

(1980), Rupp et al. (1980), and Ruffle et al. (1994) 

[which was based on Rupp et al. (1980)] did not 

present analyses by this variable. 

10.3.2.2.	 Pao et al. (1982)—Foods Commonly 

Eaten by Individuals: Amount per Day 

and per Eating Occasion 

The USDA 1977–1978 Nationwide Food 

Consumption Survey (NFCS) consisted of a 

household and individual component. For the 

individual component, all members of surveyed 

households were asked to provide three consecutive 

days of dietary data. For the first day’s data, 

participants supplied dietary recall information to an 

3rd in-home interviewer. Second and day dietary 

intakes were recorded by participants. A total of 

15,000 households were included in the 1977–1978 

NFCS, and about 38,000 individuals completed the 

3-day diet records. Fish intake was estimated based 

on consumption of fish products identified in the 

NFCS database according to NFCS-defined food 

codes. These products included fresh, breaded, 

floured, canned, raw, and dried fish, but not fish 

mixtures or frozen plate meals. 

Pao et al. (1982) used the data from this survey 

set to calculate per capita fish intake rates. However, 

because these data are now almost 30 years out of 

date, this analysis is not considered key with respect 

to assessing per capita intake (the average quantity of 

fish consumed per fish meal should be less subject to 

change over time than is per capita intake). In 

addition, fish mixtures and frozen plate meals were 

not included in the calculation of fish intake. The per 

capita fish intake rate reported by Pao et al. (1982) 

was 11.8 g/day. The 1977–1978 NFCS was a large 

and well-designed survey, and the data are 

representative of the U.S. population. 

10.3.2.3.	 USDA (1993)—Food and Nutrient Intakes 

by Individuals in the United States, 1 Day, 

1987–1988: Nationwide Food 

Consumption Survey 1987–1988 

The USDA 1987–1988 (NFCS) also consisted of 

a household and individual component. For the 

individual component, each member of a surveyed 

household was interviewed (in person) and asked to 

recall all foods eaten the previous day; the 

information from this interview made up the “1-day 

data” for the survey. In addition, members were 

instructed to fill out a detailed dietary record for the 

day of the interview and the following day. The data 

for this entire 3-day period made up the “3-day diet 

records.” A statistical sampling design was used to 

ensure that all seasons, geographic regions of the 

United States, and demographic and socioeconomic 

groups were represented. Sampling weights were 

used to match the population distribution of 

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Chapter 10—Intake of Fish and Shellfish 

13 demographic characteristics related to food intake 

(USDA, 1992). 

Total fish intake was estimated based on 

consumption of fish products identified in the NFCS 

database according to NFCS-defined food codes. 

These products included fresh, breaded, floured, 

canned, raw, and dried fish but not fish mixtures or 

frozen plate meals. 

A total of 4,500 households participated in the 

1987–1988 survey; the household response rate was 

38%. One-day data were obtained for 10,172 (81%) 

of the 12,522 individuals in participating households; 

8,468 (68%) individuals completed 3-day diet 

records. 

USDA (1992) used the 1-day data to derive per 

capita fish intake rate and intake rates for consumers 

of total fish. Table 10-17 shows these rates, 

calculated by sex and age group. Intake rates for 

consumers only were calculated by dividing the per 

capita intake rates by the fractions of the population 

consuming fish in 1 day. 

An advantage of analyses based on the 1987-1988 

USDA NFCS is that the data set is a large, 

geographically and seasonally balanced survey of a 

representative sample of the U.S. population. The 

survey response rate, however, was low, and an 

expert panel concluded that it was not possible to 

establish the presence or absence of non-response 

bias (USDA, 1992). In addition, the data from this 

survey have been superseded by more recent surveys. 

10.3.2.4.	 U.S. EPA (1996)—Descriptive Statistics 

From a Detailed Analysis of the National 

Human Activity Pattern Survey (NHAPS) 

Responses 

The U.S. EPA collected information for the 

general population on the duration and frequency of 

time spent in selected activities and time spent in 

selected microenvironments via 24-hour diaries (U.S. 

EPA, 1996). Over 9,000 individuals from 48 

contiguous states participated in NHAPS. 

Approximately 4,700 participants also provided 

information on seafood consumption. The survey was 

conducted between October 1992 and September 

1994. Data were collected on (1) the number of 

people that ate seafood in the last month, (2) the 

number of servings of seafood consumed, and 

(3) whether the seafood consumed was caught or 

purchased (U.S. EPA, 1996). The participant 

responses were weighted according to selected 

demographics such as age, sex, and race to ensure 

that results were representative of the U.S. 

population. Of those 4,700 respondents, 

2,980 (59.6%) ate seafood (including shellfish, eels, 

or squid) in the last month (see Table 10-18). The 

number of servings per month was categorized in 

ranges of 1–2, 3–5, 6–10, 11–19, and 20+ servings 

per month (see Table 10-19). The highest percentage 

(35%) of the respondent population had an intake of 

3–5 servings per month. Most (92%) of the 

respondents purchased the seafood they ate (see Table 

10-20). 

Intake data were not provided in the survey. 

However, intake of fish can be estimated using the 

information on the number of servings of fish eaten 

from this study and serving size data from other 

studies. Smiciklas-Wright et al. (2002) estimated that 

the mean value for fish serving size for all age groups 

combined is 114 g/serving based on the 1994–1996 

CSFII survey (see Section 10.8). The CSFII serving 

size data are based on all finfish, except canned, 

dried, and raw, whether reported separately or as part 

of a sandwich or other mixed food. Using this mean 

value for serving size and assuming that the average 

individual eats 3–5 servings per month, the amount of 

seafood eaten per month would range from 340 to 

570 g/month or 11.3 to 19.0 g/day for the highest 

percentage of the population. These values are within 

the range of per capita mean intake values for total 

fish (16.9 g/day, uncooked equivalent weight) 

calculated by U.S. EPA (2002) analysis of the USDA 

CSFII data. It should be noted that an all inclusive 

description for seafood was not presented in U.S. 

EPA (1996). It is not known if they included 

processed or canned seafood and seafood mixtures in 

the seafood category. 

The advantages of NHAPS are that the data were 

collected for a large number of individuals and are 

representative of the U.S. general population. 

However, evaluation of seafood intake was not the 

primary purpose of the study, and the data do not 

reflect the actual amount of seafood that was eaten. 

However, using the assumption described above, the 

estimated seafood intake from this study is 

comparable to that observed in the U.S. EPA CSFII 

analysis. 

10.3.2.5.	 Stern et al. (1996)—Estimation of Fish 

Consumption and Methylmercury Intake 

in the New Jersey Population 

Stern et al. (1996) reported on a 7-day fish 

consumption recall survey that was conducted in 

1993 as part of the New Jersey Household Fish 

Consumption Study. Households were contacted by 

telephone using the random-digit dialing technique, 

and the survey completion rate was 72% of 

households contacted. Respondents included 1 adult 

(i.e., >18 years) resident per household, for a total of 

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Chapter 10—Intake of Fish and Shellfish 

1,000 residents. The sample was “stratified to provide 

equal numbers of men and women and proportional 

representation by county” (Stern et al., 1996). Survey 

respondents provided data on consumption of all 

seafood consumed within the previous 7 days, 

including the number of fish meals, fish type, amount 

eaten at each meal, frequency of consumption, and 

whether the consumption patterns during the recall 

period were typical of their intake throughout the 

year. 

Stern et al. (1996) reported that “of the 

1,000 respondents, 933 reported that they normally 

consume fish at least a few times per year and 

686 reported that they consumed fish during the 

recall period” (Stern et al., 1996). Table 10-21 

presents the distribution of the number of meals for 

the 7-day recall period. The average portion size was 

168 grams. Approximately “4–5% of all fish meals 

consisted of fish obtained non-commercially, and 

only about 13% of these consisted of freshwater fish” 

(Stern et al., 1996). Tuna was consumed most 

frequently, followed by shrimp and flounder/fluke 

(see Table 10-22). 

Table 10-23 provides the average daily 

consumption rates (g/day) for all fish for all adults 

and for women of childbearing age (i.e., 18– 

40 years). The mean fish intake rate for all adult 

consumers was 50 g/day, and the 90th percentile was 

107 g/day. For women of childbearing age, the mean 

fish intake rate was 41 g/day, and the 90th percentile 

was 88 g/day. Table 10-24 provides information on 

the frequency of fish consumption. 

The advantages of this study are that it is based 

on a 7-day recall period and that data were collected 

for the frequency of eating fish. However, the data 

are based on fish consumers in New Jersey and may 

not be representative of the general population of the 

United States. 

10.3.2.6.	 U.S. EPA (2002)—Estimated Per Capita 

Fish Consumption in the United States 

U.S. EPA’s Office of Water used data from the 

1994–1996 CSFII and its 1998 Children’s 

Supplement (referred to collectively as CSFII 1994– 

1996, 1998) to generate fish intake estimates (U.S. 

EPA, 2002). Participants in the CSFII 1994–1996, 

1998 provided 2 non-consecutive days of dietary 

data. The Day 2 interview occurred 3 to 10 days after 

the Day 1 interview but not on the same day of the 

week. Data collection for the CSFII started in April 

of the given year and was completed in March of the 

following year. Respondents estimated the weight of 

each food that they consumed. Information on the 

consumption of food was classified using 11,345 

different food codes and stored in a database in units 

of grams consumed per day. A total of 831 of these 

food codes related to fish or shellfish; survey 

respondents reported consumption across 665 of 

these codes. The fish component (by weight) of the 

various foods was calculated using data from the 

recipe file for release seven of USDA’s Nutrient Data 

Base for Individual Food Intake Surveys. 

The amount of fish consumed by each individual 

was then calculated by summing, over all fish 

containing foods, the product of the weight of food 

consumed and the fish component (i.e., the 

percentage fish by weight) of the food. The recipe file 

also contains cooking loss factors associated with 

each food. These were used to convert, for each 

fish-containing food, the as-eaten fish weight 

consumed into an uncooked equivalent weight of 

fish. Analyses of fish intake were performed on both 

an “as-prepared” (i.e., as-consumed) and uncooked 

basis. 

Each fish-related food code was assigned, by 

U.S. EPA, to a habitat category. The habitat 

categories included freshwater/estuarine, or marine. 

Food codes were also designated as finfish or 

shellfish. Average daily individual consumption 

(g/day) was calculated, for a given fish 

type-by-habitat category (e.g., marine finfish), by 

summing the amount of fish consumed by the 

individual across the 2 reporting days for all 

fish-related food codes in the given fish-by-habitat 

category and then dividing by 2. Individual daily fish 

consumption (g/day) was calculated similarly except 

that total fish consumption was divided by the 

specific number of survey days the individual 

reported consuming fish; this was calculated for fish 

consumers only (i.e., those consuming fish on at least 

1 of the 2 survey days). The reported body weight of 

the individual was used to convert consumption in 

g/day to consumption in g/kg-day. 

There were a total of 20,607 respondents in the 

combined data set that had 2-day dietary intake data. 

Survey weights were assigned to this data set to make 

it representative of the U.S. population with respect 

to various demographic characteristics related to food 

intake. Survey weights were also adjusted for 

non-response. 

U.S. EPA (2002) reported means, medians, and 

estimates of the 90th, 95th, and 99th percentiles of fish 

intake. The 90% interval estimates are 

non-parametric estimates from bootstrap techniques. 

The bootstrap estimates result from the percentile 

method, which calculates the lower and upper bounds 

for the interval estimate by the 100α percentile and 

100 (1–α) percentile estimates from the 

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Chapter 10—Intake of Fish and Shellfish 

non-parametric distribution of the given point 

estimate (U.S. EPA, 2002). 

Analyses of fish intake were performed on an 

as-prepared as well as on an uncooked equivalent 

basis and on a g/day and mg/kg-day basis. Table 

10-25 gives the mean and various percentiles of the 

distribution of per capita finfish and shellfish intake 

rates (g/day), as prepared, by habitat and fish type, 

for the general population. Table 10-26 provides a 

list of the fish species categorized within each 

habitat. Table 10-26 also shows per capita 

consumption estimates by species. Table 10-27 

displays the mean and various percentiles of the 

distribution of per capita finfish and shellfish intake 

rates (g/day) by habitat and fish type, on an uncooked 

equivalent basis. Table 10-28 shows per capita 

consumption estimates by species on an uncooked 

equivalent basis. 

Table 10-29 through Table 10-36 present data for 

daily average fish consumption. These data are 

presented by selected age groupings (14 and under, 

15–44, 45 and older, all ages, children ages 3 to 17, 

and ages 18 and older) and sex. It should be noted the 

analysis predated the age groups recommended by 

U.S. EPA Guidelines on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposure to 

Environmental Contaminants (U.S. EPA, 2005). 

Table 10-29 through Table 10-32 present fish intake 

data (g/day and mg/kg-day; as prepared and 

uncooked) on a per capita basis, and Table 10-33 

through Table 10-36 provide data for consumers only. 

The advantages of this study are its large size and 

its representativeness. The survey was also designed 

and conducted to support unbiased estimation of food 

consumption across the population. In addition, 

through use of the USDA recipe files, the analysis 

identified all fish-related food codes and estimated 

the percent fish content of each of these codes. By 

contrast, some analyses of the USDA NFCSs, which 

reported per capita fish intake rates [e.g., Pao et al. 

(1982); USDA (1993)], excluded certain fishcontaining foods (e.g., fish mixtures, frozen plate 

meals) in their calculations. 

10.3.2.7. Westat (2006)—Fish Consumption in 

Connecticut, Florida, Minnesota, and 

North Dakota 

Westat (2006) analyzed the raw data from 

three fish consumption studies to derive fish 

consumption rates for various age, sex, and ethnic 

groups, and according to the source of fish consumed 

(i.e., bought or caught) and habitat (i.e., freshwater, 

estuarine, or marine). The studies represented data 

from four states: Connecticut, Florida, Minnesota, 

and North Dakota. 

The Connecticut data were collected in 1996/1997 

by the University of Connecticut to obtain estimates 

of fish consumption for the general population, sport 

fishing households, commercial fishing households, 

minority and limited income households, women of 

child-bearing years, and children. Data were obtained 

from 810 households, representing 2,080 individuals, 

using a combination of a mail questionnaire that 

included a 10-day diary, and personal interviews. The 

response rate for this survey was low (i.e., 6% for the 

general population and 10% for anglers) but was 

considered to be adequate by the study authors 

(Balcom et al., 1999). 

The Florida data were collected by telephone and 

in-person interviews by the University of Florida and 

represented a random sample of 8,000 households 

(telephone interviews) and 500 food stamp recipients 

(in-person interviews). The purpose of the survey was 

to obtain information on the quantity of fish and 

shellfish eaten, as well as the cooking method used. 

Additional information of the Florida survey can be 

found in Degner et al. (1994). 

The Minnesota and North Dakota data were 

collected by the University of North Dakota in 2000 

and represented 1,572 households and 

4,273 individuals. Data on purchased and caught fish 

were collected for the general population, anglers, 

new mothers, and Native American tribes. The survey 

also collected information on the species of fish 

eaten. Additional information on this study can be 

found in Benson et al. (2001). 

The primary difference in survey procedures 

among the three studies was the manner in which the 

fish consumption data were collected. In Connecticut, 

the survey requested information on how often each 

type of seafood was eaten, without a recall period 

specified. In Minnesota and North Dakota, the survey 

requested information on the rate of fish or shellfish 

consumption during the previous 12 months. In 

Florida, the survey requested information on fish 

consumption during the last 7 days prior to the 

telephone interview. In addition, for the Florida 

survey, information on away-from-home fish 

consumption was collected from a randomly selected 

adult from each participating household. Because this 

information was not collected from all household 

members, the study may tend to underestimate 

away-from-home consumption. The study notes that 

estimates of fish consumption using a shorter recall 

period will decrease the proportion of respondents 

that report eating fish or shellfish. This trend was 

observed in the Florida study (in which 

approximately half of respondents reported eating 

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Chapter 10—Intake of Fish and Shellfish 

fish/shellfish), compared with Connecticut, 

Minnesota, and North Dakota (in which 

approximately 90% of respondents reported eating 

fish or shellfish). 

Table 10-37 through Table 10-46 present key 

findings of the Westat (2006) consumption study. The 

tables show the fish and shellfish consumption rates 

for various groups classified by demographic 

characteristics and by the source of the fish and 

shellfish consumed (i.e., freshwater versus marine, 

and bought versus self-caught). Consumption rates 

are presented in grams per kilogram of body weight 

per day for the entire population (i.e., consumption 

per capita) and for just those that reported consuming 

fish and shellfish (consumption for consumers only). 

An advantage of this study is that it focused on 

individuals within the general population that may 

consume more fish and shellfish and, thus, may be at 

higher risk from exposure to contaminants in fish 

than other members of the population. Also, it 

provides distributions of fish consumption for 

different age cohorts, ethnic groups, socioeconomic 

status, types of fish (i.e., freshwater, marine, 

estuarine), and sources of fish (i.e., store-bought 

versus self-caught). However, the data were collected 

in four states and may not be representative of the 

U.S. population as a whole. 

10.3.2.8.	 Moya et al. (2008)—Estimates of Fish 

Consumption Rates for Consumers of 

Bought and Self-Caught Fish in 

Connecticut, Florida, Minnesota, and 

North Dakota 

Moya et al. (2008) summarized the analysis 

conducted by Westat (2006) described in 

Section 10.3.2.7. Moya et al. (2008) utilized the data 

to generate intake rates for 3 age groups of children 

(i.e., 1 to <6 years, 6 to <11 years, and 11 to 

<16 years) and 3 age groups of adults (16 to 

<30 years, 30 to <50 years, and >50 years), which are 

also listed by sex. These data represented the general 

population and angler population in the four states. 

Recreational fish intake rates were not provided for 

children, and data were not provided for children 

according to the source of intake (i.e., bought or 

caught) or habitat (i.e., freshwater, estuarine, or 

marine). Table 10-47 presents the intake rates for the 

general population who consumed fish and shellfish 

in g/kg-day, as-consumed. Table 10-47 also provides 

information on the fish intake among the sample 

populations from the four states, based on the source 

of the fish (i.e., caught or bought) and provides 

estimated fish intake rates among the general 

populations and angler populations from Connecticut, 

Minnesota, and North Dakota. 

This analysis is based on the data from Westat 

(2006). Therefore, the advantages and limitations are 

the same as those of the Westat (2006) study. Also, 

while data were provided for individuals who ate 

self-caught fish, it is not possible from this analysis 

to determine the proportion of self-caught fish 

represented by marine or freshwater habitats. 

10.3.2.9. Mahaffey et al. (2009)—Adult Women’s 

Blood Mercury Concentrations Vary 

Regionally in the United States: 

Association With Patterns of Fish 

Consumption (NHANES 1999–2004) 

Mahaffey et al. (2009) used NHANES 1999–2004 

data to evaluate relationships between fish intake and 

blood mercury levels. Mercury intake via fish 

ingestion was evaluated for four coastal populations 

(i.e., Atlantic, Pacific, Gulf of Mexico, and Great 

Lakes), and four non-coastal populations defined by 

U.S. census regions (i.e., Northeast, South, Midwest, 

and West) (Mahaffey et al., 2009). Serving size data, 

based on 24-hour dietary recall, were used with 

30-day food frequency data to estimate mercury 

intake from consumption of fish over a 30-day 

period. The frequency data used in the study 

indicated that people living on the Atlantic coast 

consumed fish most frequently (averaging 

6 meals/month), followed closely by those of the 

Gulf and Pacific coasts. People living in non-coastal 

areas or on the coasts of the Great Lakes consumed 

fish least often (averaging <4 meals/month). Figure 

10-2 illustrates these regional differences. 

The advantage of this study is that it is based on 

relatively recent NHANES data (i.e., 1999–2004), it 

uses data from the 30-day food frequency 

questionnaire, and it provides regional data that are 

not available elsewhere. However, because the study 

focused on mercury exposure, it did not provide 

non-chemical specific fish intake data (in g/day or 

g/kg-day) that can be used to support risk 

assessments for other chemicals (i.e., only frequency 

data were provided). It does, however, provide useful 

information on the relative differences in frequency 

of fish intake for regional populations. 

10.4. MARINE RECREATIONAL STUDIES 

10.4.1. Key Marine Recreational Study 

10.4.1.1.	 National Marine Fisheries Service (1993, 

1986a, b, c) 

The NMFS conducts systematic surveys, on a 

continuing basis, of marine recreational fishing. 

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These surveys are designed to estimate the size of the 

recreational marine finfish catch by location, species, 

and fishing mode. In addition, the surveys provide 

estimates for the total number of participants in 

marine recreational finfishing and the total number of 

fishing trips. 

The NMFS surveys involve two components: 

telephone surveys and direct interviewing of 

fishermen in the field. The telephone survey 

randomly samples residents of coastal regions, 

defined generally as counties within 25 miles of the 

nearest seacoast, and inquires about participation in 

marine recreational fishing in the resident’s home 

state in the past year, and more specifically, in the 

past 2 months. This component of the survey is used 

to estimate, for each coastal state, the total number of 

coastal region residents who participate in marine 

recreational fishing (for finfish) within the state, as 

well as the total number of (within state) fishing trips 

these residents take. To estimate the total number of 

participants and fishing trips in the state, by coastal 

residents and others, a ratio approach, based on the 

field interview data, was used. Thus, if the field 

survey data found that there was a 4:1 ratio of fishing 

trips taken by coastal residents as compared to trips 

taken by non-coastal and out-of-state residents, then 

an additional 25% would be added to the number of 

trips taken by coastal residents to generate an 

estimate of the total number of within-state trips. 

The surveys are not designed to estimate 

individual consumption of fish from marine 

recreational sources, primarily because they do not 

attempt to estimate the number of individuals 

consuming the recreational catch. Intake rates for 

marine recreational anglers can be estimated, 

however, by employing assumptions derived from 

other data sources about the number of consumers. 

The field intercept survey is essentially a creel 

type survey. The survey utilizes a national site 

register that details marine fishing locations in each 

state. Sites for field interviews are chosen in 

proportion to fishing frequency at the site. Anglers 

fishing on shore, private boat, and charter/party boat 

modes who had completed their fishing were 

interviewed. The field survey included questions 

about frequency of fishing, area of fishing, age, and 

place of residence. The fish catch was classified by 

the interviewer as either type A, type B1, or type B2 

catch. The type A catch denoted fish that were taken 

whole from the fishing site and were available for 

inspection. The type B1 and B2 catch were not 

available for inspection; the former consisted of fish 

used as bait, filleted, or discarded dead, while the 

latter was fish released alive. The type A catch was 

identified by species and weighed, with the weight 

reflecting total fish weight, including inedible parts. 

The type B1 catch was not weighed, but weights 

were estimated using the average weight derived 

from the type A catch for the given species, state, 

fishing mode, and season of the year. For both the 

type A and B1 catch, the intended disposition of the 

catch (e.g., plan to eat, plan to throw away, etc.) was 

ascertained. 

U.S. EPA obtained the raw data tapes from NMFS 

in order to generate intake distributions and other 

specialized analyses. Fish intake distributions were 

generated using the field survey tapes. Weights 

proportional to the inverse of the angler’s reported 

fishing frequency were employed to correct for the 

unequal probabilities of sampling; this was the same 

approach used by NMFS in deriving their estimates. 

Note that in the field survey, anglers were 

interviewed regardless of past interviewing 

experience; thus, the use of inverse fishing frequency 

as weights was justified (see Section 10.1). 

For each angler interviewed in the field survey, 

the yearly amount of fish caught that was intended to 

be eaten by the angler and his/her family or friends 

was estimated by U.S. EPA as follows: 

Y = [(wt of A catch) × IA + (wt of B1 catch) × IB] × 

[Fishing frequency] (Eqn. 10-1) 

where IA (IB) are indicator variables equal to one if 

the type A (B1) catch was intended to be eaten, and 

equal to 0 otherwise. To convert Y to a daily fish 

intake rate by the angler, it was necessary to convert 

amount of fish caught to edible amount of fish, divide 

by the number of intended consumers, and convert 

from yearly to daily rate. 

Although theoretically possible, U.S. EPA chose 

not to use species-specific edible fractions to convert 

overall weight to edible fish weight because edible 

fraction estimates were not readily available for many 

marine species. Instead, an average value of 0.5 was 

employed. For the number of intended consumers, 

U.S. EPA used an average value of 2.5, which was an 

average derived from the results of several studies of 

recreational fish consumption (ChemRisk, 1992; 

West et al., 1989; Puffer et al., 1982). Thus, the 

average daily intake rate (ADI) for each angler was 

calculated as 

ADI = Y × (0.5)/[2.5 × 365] (Eqn. 10-2) 

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Note that ADI will be 0 for those anglers who 

either did not intend to eat their catch or who did not 

catch any fish. The distribution of ADI among 

anglers was calculated by region and coastal status 

(i.e., coastal versus non-coastal counties). 

The results presented in Table 10-48 and Table 

10-49 are based on the results of the 1993 survey. 

Sample sizes were 200,000 for the telephone survey 

and 120,000 for the field surveys. All coastal states in 

the continental United States were included in the 

survey except Texas and Washington. 

Table 10-48 presents the estimated number of 

coastal, non-coastal, and out-of-state fishing 

participants by state and region of fishing. Florida 

had the greatest number of both Atlantic and Gulf 

participants. The total number of coastal residents 

who participated in marine finfishing in their home 

state was eight million; an additional 

750,000 non-coastal residents participated in marine 

finfishing in their home state. 

Table 10-49 presents the estimated total weight of 

the type A and B1 catch by region and time of year. 

For each region, the greatest catches were during the 

6-month period from May through October. This 

period accounted for about 90% of the North and 

Mid-Atlantic catch, about 80% of the Northern 

California and Oregon catch, about 70% of the 

Southern Atlantic and Southern California catch, and 

62% of the Gulf catch. Note that in the North and 

Mid-Atlantic regions, field surveys were not done in 

January and February due to very low fishing 

activity. For all regions, over half the catch occurred 

within 3 miles of the shore or in inland waterways. 

Table 10-50 presents the mean and 95th percentile 

of average daily intake (ADI) of recreationally caught 

marine finfish among anglers by region. The mean 

ADI values among all anglers were 5.6, 7.2, and 2.0 

g/day for the Atlantic, Gulf, and Pacific regions, 

respectively. Table 10-51 gives the distribution of 

catch, by species, for the Atlantic, Gulf, and Pacific 

regions. 

The NMFS surveys provide a large, 

geographically representative sample of marine 

angler activity in the United States. The major 

limitation of this database in terms of estimating fish 

intake is the lack of information regarding the 

intended number of consumers of each angler’s catch. 

In this analysis, it was assumed that every angler’s 

catch was consumed by the same number (2.5) of 

people; this number was derived from averaging the 

results of other studies. This assumption introduces a 

relatively low level of uncertainty in the estimated 

mean intake rates among anglers, but a somewhat 

higher level of uncertainty in the estimated intake 

distributions. 

Under the above assumption, the distributions 

shown here pertain not only to the population of 

anglers, but also to the entire population of 

recreational fish consumers, which is 2.5 times the 

number of anglers. If the number of consumers was 

changed, to, for instance, 2.0, then the distribution 

would be increased by a factor of 1.25 (2.5/2.0), but 

the estimated population of recreational fish 

consumers to which the distribution would apply, 

would decrease by a factor of 0.8 (2.0/2.5). 

Another uncertainty involves the use of 0.5 as an 

(average) edible fraction. This figure is assumed to be 

somewhat conservative (i.e., the true average edible 

fraction is probably lower); thus, the intake rates 

calculated here may be biased upward somewhat. 

The recreational fish intake distributions given 

refer only to marine finfish. In addition, the intake 

rates calculated are based only on the catch of anglers 

in their home state. Marine fishing performed 

out-of-state would not be included in these 

distributions. Therefore, these distributions give an 

estimate of consumption of locally caught marine 

fish. These data are approximately 2 decades old and 

may not be entirely representative of current intake 

rates. Also, data were not available for children. 

10.4.2. Relevant Marine Recreational Studies 

10.4.2.1. Pierce et al. (1981)—Commencement Bay 

Seafood Consumption Study 

Pierce et al. (1981) performed a local creel survey 

to examine seafood consumption patterns and 

demographics of sport fishermen in Commencement 

Bay, WA. The objectives of this survey included 

determining (1) the seafood consumption habits and 

demographics of non-commercial anglers catching 

seafood; (2) the extent to which resident fish were 

used as food; and (3) the method of preparation of the 

fish to be consumed. Salmon were excluded from the 

survey because it was believed that they had little 

potential for contamination. The first half of this 

survey was conducted from early July to 

mid-September, 1980 and the second half from 

mid-September through most of November. During 

the summer months, interviewers visited each of four 

sub-areas of Commencement Bay on five mornings 

and five evenings; in the fall, the areas were sampled 

on four complete survey days. Interviews were 

conducted only with persons who had caught fish. 

The anglers were interviewed only once during the 

survey period. Data were recorded for species, wet 

weight, size of the living group (family), place of 

residence, fishing frequency, planned uses of the fish, 

age, sex, and race (Pierce et al., 1981). The analysis 

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of Pierce et al. (1981) did not employ explicit 

sampling weights (i.e., all weights were set to one). 

There were 304 interviews in the summer and 204 

in the fall. About 60% of anglers were White, 

20% Black, and 19% Asian, and the rest were 

Hispanic or Native American. Table 10-52 gives the 

distribution of fishing frequency calculated by Pierce 

et al. (1981); for both the summer and fall, more than 

half of the fishermen caught and consumed fish 

weekly. The dominant (by weight) species caught 

were Pacific hake and walleye pollock. Pierce et al. 

(1981) did not present a distribution of fish intake or 

a mean fish intake rate. 

Price et al. (1994) obtained the raw data from this 

survey and performed a re-analysis using sampling 

weights proportional to inverse fishing frequency. 

The rationale for these weights is explained in 

Section 10.1 and in the discussion of the Puffer et al. 

(1982) study (see Section 10.4.2.2). In the 

re-analysis, Price et al. (1994) calculated a median 

intake rate of 1.0 g/day and a 90th percentile rate of 

13 g/day. The distribution of fishing frequency 

generated by Pierce et al. (1981) is shown in Table 

10-52. Note that when equal weights were used, Price 

et al. (1994) found a median rate of 19 g/day (Table 

10-53). 

The same limitations apply to interpreting the 

results presented here to those presented in the 

discussion of Puffer et al. (1982) (see 

Section 10.4.2.2). As with the Puffer et al. (1982) 

data described in the following section, these values 

(1.0 g/day and 19 g/day) are both probably 

underestimates because the sampling probabilities are 

less than proportional to fishing frequency; thus, the 

true target population median is probably somewhat 

above 1.0 g/day, and the true 50th percentile of the 

resource utilization distribution is probably somewhat 

higher than 19 g/day. The data from this survey 

provide an indication of consumption patterns for the 

time period around 1980 in the Commencement Bay 

area. However, the data may not reflect current 

consumption patterns because fishing advisories were 

instituted due to local contamination. Another 

limitation of these data is that fish consumption rates 

were estimated indirectly from a series of 

assumptions. 

10.4.2.2.	 Puffer et al. (1982)—Intake Rates of 

Potentially Hazardous Marine Fish 

Caught in the Metropolitan Los Angeles 

Area 

Puffer et al. (1982) conducted a creel survey with 

sport fishermen in the Los Angeles area in 1980. The 

survey was conducted at 12 sites in the harbor and 

coastal areas to evaluate intake rates of potentially 

hazardous marine fish and shellfish by local, 

non-professional fishermen. It was conducted for the 

full 1980 calendar year, although inclement weather 

in January, February, and March limited the interview 

days. Each site was surveyed an average of three 

times per month, on different days, and at a different 

time of the day. The survey questionnaire was 

designed to collect information on demographic 

characteristics, fishing patterns, species, number of 

fish caught, and fish consumption patterns. Scales 

were used to obtain fish weights. Interviews were 

conducted only with anglers who had caught fish, and 

the anglers were interviewed only once during the 

entire survey period. 

Puffer et al. (1982) estimated daily consumption 

rates (g/day) for each angler using the following 

equation: 

K × N × W × F)/[E × 365] (Eqn. 10-3) 

where: 

K = edible fraction of fish (0.25 to 0.5 

depending on species), 

N = number of fish in catch, 

W = average weight of (grams) fish in 

catch, 

F = frequency of fishing/year, and 

E = number of fish eaters in family/living 

group. 

No explicit survey weights were used in 

analyzing this survey; thus, each respondent’s data 

were given equal weight. 

A total of 1,059 anglers were interviewed for the 

survey. Table 10-54 shows the ethnic and age 

distribution of respondents; 88% of respondents were 

male. The median intake rate was higher for 

Asian/Samoan anglers (median 70.6 g/day) than for 

other ethnic groups and higher for those ages over 

65 years (median 113.0 g/day) than for other age 

groups. Puffer et al. (1982) found similar median 

intake rates for seasons: 36.3 g/day for November 

through March and 37.7 g/day for April through 

October. Puffer et al. (1982) also evaluated fish 

preparation methods; Appendix 10B presents these 

data. Table 10-55 presents the cumulative distribution 

of recreational fish (finfish and shellfish) 

consumption by survey respondents; this distribution 

was calculated only for those fishermen who 

indicated they eat the fish they catch. The median fish 

consumption rate was 37 g/day, and the 

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Chapter 10—Intake of Fish and Shellfish 

90th percentile rate was 225 g/day (Puffer et al., 

1982). Table 10-56 presents a description of catch 

patterns for primary fish species kept. 

As mentioned in the introduction to this chapter, 

intake distributions derived from analyses of creel 

surveys that did not employ weights reflective of 

sampling probabilities will overestimate the target 

population intake distribution and will, in fact, be 

more reflective of the “resource utilization 

distribution.” Therefore, the reported median level of 

37.3 g/day does not reflect the fact that 50% of the 

target population has intake above this level; instead, 

50% of recreational fish consumption is by 

individuals consuming at or above 37 g/day. In order 

to generate an intake distribution reflective of that in 

the target population, weights inversely proportional 

to sampling probability need to be employed. Price 

et al. (1994) made this attempt with the Puffer et al. 

(1982) survey data, using inverse fishing frequencies 

as the sampling weights. Price et al. (1994) was 

unable to get the raw data for this survey, but through 

the use of frequency tables and the average level of 

fish consumption per fishing trip provided in Puffer 

et al. (1982), generated an approximate revised intake 

distribution. This distribution was dramatically lower 

than that obtained by Puffer et al. (1982); the median 

was estimated at 2.9 g/day [compared with 37 from 

Puffer et al. (1982)] and the 90th percentile at 

35 g/day [compared to 225 g/day from Puffer et al. 

(1982)]. 

There are several limitations to the interpretation 

of the percentiles presented by both Puffer et al. 

(1982) and Price et al. (1994). As described in 

Appendix 10A, the interpretation of percentiles 

reported from creel surveys in terms of percentiles of 

the “resource utilization distribution” is approximate 

and depends on several assumptions. One of these 

assumptions is that sampling probability is 

proportional to inverse fishing frequency. In this 

survey, where interviewers revisited sites numerous 

times and anglers were not interviewed more than 

once, this assumption is not valid, though it is likely 

that the sampling probability is still highly dependent 

on fishing frequency, so that the assumption does 

hold in an approximate sense. The validity of this 

assumption also impacts the interpretation of 

percentiles reported by Price et al. (1994) because 

inverse frequency was used as sampling weights. It is 

likely that the value (2.9 g/day) of Price et al. (1994) 

underestimates somewhat the median intake in the 

target population but is much closer to the actual 

value than the Puffer et al. (1982) estimate of 

37.3 g/day. Similar statements would apply about the 

90th percentile. Similarly, the 37.3-g/day median 

value, if interpreted as the 50th percentile of the 

“resource utilization distribution,” is also somewhat 

of an underestimate. 

The fish intake distribution generated by Puffer et 

al. (1982) [and by Price et al. (1994)] was based only 

on fishermen who caught fish and ate the fish they 

caught. If all anglers were included, intake estimates 

would be somewhat lower. In contrast, the survey 

assumed that the number of fish caught at the time of 

the interview was all that would be caught that day. If 

it were possible to interview fishermen at the 

conclusion of their fishing day, intake estimates could 

be potentially higher. An additional factor potentially 

affecting intake rates is that fishing quarantines were 

imposed in early spring due to heavy sewage 

overflow (Puffer et al., 1982). These data are also 

over 20 years old and may not reflect current 

behaviors. 

10.4.2.3.	 Burger and Gochfeld (1991)—Fishing a 

Superfund Site: Dissonance and Risk 

Perception of Environmental Hazards by 

Fishermen in Puerto Rico 

Burger and Gochfeld (1991) examined fishing 

behavior, consumption patterns, and risk perceptions 

of fishermen and crabbers engaged in recreational 

and subsistence fishing in the Humacao Lagoons 

located in eastern Puerto Rico. For a 20-day period in 

February and March 1988, all persons encountered 

fishing and crabbing at the Humacao lagoons and at 

control sites were interviewed on fishing patterns, 

consumption patterns, cooking patterns, fishing and 

crabbing techniques, and consumption warnings. The 

control interviews were conducted at sites that were 

ecologically similar to the Humacao lagoons and 

contained the same species of fish and crabs. A total 

of 45 groups of people (3 to 4 people per group) 

fishing at the Humacao Lagoons and 17 control 

groups (3 to 4 people per group) were interviewed. 

Most people fished in the late afternoon or 

evenings, and on weekends. Eighty percent of the 

fishing groups from the lagoons were male. The 

breakdown according to age is as follows: 27% were 

younger than 20 years, 49% were 21–40 years old, 

24% were 41–60 years old, and 2% were over 60. 

The age groups for fishing were generally lower than 

the groups for crabbing. Caught fish were primarily 

tilapia and some tarpon. All crabs caught were blue 

crabs. 

On average, people at Humacao ate about 7 fish 

(N = 25) or 13 crabs (N = 20) each week, while 

people fishing at the control site ate about 2 fish 

(N = 9) and 14 crabs (N = 9) a week (see Table 

10-57). All of the crabbers (100%) and 96% of the 

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Chapter 10—Intake of Fish and Shellfish 

fisherman at the lagoons had heard of a 

contamination problem. 

All the interviewees that knew of a contamination 

problem knew that the contaminant was mercury. 

Most fisherman and crabbers believed that the water 

was clean and the catch was safe (fisherman—96% 

and crabbers—100%), and all fisherman and crabbers 

ate their catch. Seventy-two percent of the fisherman 

and crabbers from the lagoons lived within 3 km, 

18% lived 17–30 km away, and 1 group came from 

66 km away. Because many of the people interviewed 

had cars, researchers concluded that they were not 

impoverished and did not need the fish as a protein 

substitute. 

Burger and Gochfeld (1991) noted that fisherman 

and crabbers did not know of anyone who had gotten 

sick from eating catches from the lagoons, and the 

potential of chronic health effects did not enter into 

their consideration. The study concluded that 

fisherman and crabbers experienced an 

incompatibility between their own experiences, and 

the risk driven by media reports of pollution and the 

lack of governmental prohibition of fishing. 

One limitation of the study is that consumption 

rates were based on groups not individuals. In 

addition, rates were given in terms of fish per week 

and not mass consumed per time or body weight. 

10.4.2.4.	 Burger et al. (1992)—Exposure 

Assessment for Heavy Metal Ingestion 

From Sport Fish in Puerto Rico: 

Estimating Risk for Local Fishermen 

Burger et al. (1992) conducted another study in 

conjunction with the Burger and Gochfeld (1991) 

study. The study interviewed 45 groups of fishermen 

at Humacao and 14 groups at Boqueron in Puerto 

Rico. The respondents were 80% male, 50% were 21 

to 40 years old, most fished with pole or cast, and 

most fished for 1.5 hours. In Humacao, 96% claimed 

that they ate the entire fish besides the head. The fish 

were either fried or boiled in stews or soups. 

In February and March, 64% of the group caught 

only tilapia, but respondents stated that in June they 

caught mostly robalo and tarpon. Generally, the 

fisherman stated that they ate 2.1 fish (maximum of 

11 fish) from Boqueron and 6.8 fish (maximum of 

23) from Humacao per week. The study reported that 

adults ate 374 grams of fish per day, while children 

ate 127 grams per day. In order to calculate the daily 

mass intake of fish, the study assumed that an adult 

ate 4.4 robalos, each weighing 595 grams over a 

7-day period, and a child ate 1.5 robalos, each 

weighing 595 grams over a 7-day period. The study 

used a maximum consumption value of 200 g/day for 

fishermen to create various hazard indices. 

One limitation of this study is that the 

consumption rates were based on groups not 

individuals. In addition, consumption rates were 

calculated using the average fish weight and the 

number of meals per week reported by the 

respondents. 

10.4.2.5.	 Moya and Phillips (2001)—Analysis of 

Consumption of Home-Produced Foods 

The 1987–1988 NFCS was also utilized to 

estimate consumption of home-produced (i.e., 

self-caught) fish (as well as home-produced fruits, 

vegetables, meats, and dairy products) in the general 

U.S. population. The methodology for estimating 

home-produced intake rates was rather complex and 

involved combining the household and individual 

components of the NFCS; the methodology, as well 

as the estimated intake rates, are described in detail in 

Chapter 13. Some of the data on fish consumption 

from households who consumed self-caught fish are 

also provided in Moya and Phillips (2001). A total of 

2.1% of the total survey population reported 

self-caught fish consumption during the survey week. 

Among consumers, the mean intake rate was 

2.07 g/kg-day, and the 95th percentile was 

7.83 g/kg-day; the mean per capita intake rate was 

0.04 g/kg-day. Note that intake rates for 

home-produced foods were indexed to the weight of 

the survey respondent and reported in g/kg-day. 

The NFCS household component contains the 

question “Does anyone in your household fish?” For 

the population answering yes to this question (21% of 

households), the NFCS data show that 9% consumed 

home-produced fish in the week of the survey; the 

mean intake rate for fish consumers from fishing 

households was 2.2 g/kg-day (all ages combined, see 

Table 13-20) for the fishing population. Note that 

92% of individuals reporting home-produced fish 

consumption for the week of the survey indicated that 

a household member fishes; the overall mean intake 

rate among home-produced fish consumers, 

regardless of fishing status, was the above reported 

2.07 g/kg-day). The mean per capita intake rate 

among all those living in fishing household is then 

calculated as 0.2 g/kg-day (2.2 × 0.09). Using the 

estimated average weight of survey participants of 

59 kg, this translates into an average national per 

capita self-caught fish consumption rate of 11.8 g/day 

among the population of individuals who fish. 

However, this intake rate represents intake of both 

freshwater and saltwater fish combined. According to 

the data in Chapter 13 (see Table 13-68), 

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Chapter 10—Intake of Fish and Shellfish 

home-produced fish consumption accounted for 

32.5% of total fish consumption among households 

who fish. 

As discussed in Chapter 13 of this handbook, 

intake rates for home-produced foods, including fish, 

are based on the results of the household survey, and 

as such, reflect the weight of fish taken into the 

household. In most of the recreational fish surveys 

discussed later in this section, the weight of the fish 

catch (which generally corresponds to the weight 

taken into the household) is multiplied by an edible 

fraction to convert to an uncooked equivalent of the 

amount consumed. This fraction may be species 

specific, but some studies used an average value; 

these average values ranged from 0.3 to 0.5. Using a 

factor of 0.5 would convert the above 11.8 g/day rate 

to 5.9 g/day. 

The advantage of this study is that it provides a 

national perspective on the consumption of 

self-caught fish. A limitation of this study is that 

these values include both freshwater and saltwater 

fish. The proportion of freshwater to saltwater is 

unknown and will vary depending on geographical 

location. Intake data cannot be presented for various 

age groups due to sample size limitations. The 

unweighted number of households, who responded 

positively to the survey question “do you fish”? was 

also low (i.e., 220 households). 

10.4.2.6.	 KCA Research Division (1994)—Fish 

Consumption of Delaware Recreational 

Fishermen and Their Households 

In support of the Delaware Estuary Program, the 

State of Delaware’s Department of Natural Resources 

and Environmental Control conducted a survey of 

marine recreational fishermen along the coastal areas 

of Delaware between July 1992 and June 1993 (KCA 

Research Division, 1994). There were 

two components of the study: (1) a field survey of 

fishermen as they returned from their fishing trips, 

and (2) a telephone follow-up call. 

The purpose of the first component was to obtain 

information on their fishing trips and on their 

household composition. This information included 

the method and location of fishing, number of fish 

caught and kept by species, and weight of each fish 

kept. Household information included race, age, sex, 

and number of persons in the household. Information 

was also recorded as to the location of the angler 

intercept (i.e., where the angler was interviewed) and 

the location of the household. 

The purpose of the second component was to 

obtain information on the amount of fish caught and 

kept from the fishing trip and then eaten by the 

household. The methods used for preparing and 

cooking the fish were also documented. 

The field portion of the study was designed to 

interview 2,000 anglers. Data were obtained from 

1,901 anglers, representing 6,204 household 

members (KCA Research Division, 1994). While the 

primary goal of the study was to collect data on 

marine recreational fishing practices, the survey 

included some freshwater fishing and crabbing sites. 

Follow-up phone interviews typically occurred 

2 weeks after the field interview and were used to 

gather information about consumption. Interviewers 

aided respondents in their estimation of fish intake by 

describing the weight of ordinary products, for the 

purpose of comparison to the quantity of fish eaten. 

Information on the number of fishing trips a 

respondent had taken during the month was used to 

estimate average annual consumption rates. 

For all respondents, the average consumption was 

17.5 g/day. Males were found to have consumed 

more fish than women, and Caucasians consumed 

more fish per day than the other races surveyed (see 

Table 10-58). More than half of the study respondents 

reported that they skinned the fish that they ate (i.e., 

450 out of 807 who reported whether they skinned 

their catch); the majority ate filleted fish (i.e., 617 out 

of 794 who reported the preparation method used), 

and over half fried their fish (i.e., 506 out of 875 who 

reported the cooking method). Information on 

consumption relative to preparation method indicated 

a higher consumption level for skinned fish (0.627 

oz/day) than for un-skinned fish (0.517 oz/day). 

Although most respondents fried their catch (0.553 

oz/day), baking and broiling were also common 

(0.484 and 0.541 oz/day, respectively). 

One limitation of this study is that information on 

fish consumption is based on anglers’ recall of 

amount of fish eaten. While this study provides 

information on fish consumption of various ethnic 

groups, another limitation of this study is that the 

sample size for ethnic groups was very small. Also, 

the study was limited to one geographic area and may 

not be representative of the U.S. population. 

10.4.2.7.	 Santa Monica Bay Restoration Project 

(SMBRP) (1995)—Seafood Consumption 

Habits of Recreational Anglers in Santa 

Monica Bay, Los Angeles, CA 

The Santa Monica Bay Restoration Project 

(SMBRP) conducted a study on the seafood 

consumption habits of recreational anglers in Santa 

Monica Bay, CA. The study was conducted between 

September 1991 and August 1992. Surveys were 

conducted at 11 piers and jetties, three private boat 

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launches and hoists, 11 beach and intertidal sites, and 

five party boat landings. Information requested in the 

survey included fishing history, types of fish eaten, 

consumption habits, methods of preparing fish, and 

demographics. Consumption rates were calculated 

based on the anglers’ estimates of meal size relative 

to a model fish fillet that represented a 150-gram 

meal. Interviewers identified 67 species of fish, 

2 species of crustaceans, 2 species of mollusks, and 

1 species of echinoderms that had been caught from 

the study area by recreational anglers during the 

study period. The most abundant species caught were 

chub mackerel, barred sand bass, kelp bass, white 

croaker, Pacific barracuda, and Pacific bonito. 

A total of 2,376 anglers were censused during 

113 separate surveys. Of those anglers, 1,243 were 

successfully interviewed, and 554 provided sufficient 

information for calculation of consumption rates. The 

socio-demographics of the sample population were as 

follows: most anglers were male (93%), 21 to 

40 years old (54%), White (43%), and had an annual 

household income of $25,000 to $50,000 (39%). 

The results of the survey showed that the mean 

consumption rate was 50 g/day, while the 

90th percentile was over two times higher at 

107 g/day (see Table 10-59). Of the identified ethnic 

groups, Asians had the highest mean consumption 

rate (51 g/day) and the highest 90th percentile value 

for consumption rate (116 g/day). Anglers with 

annual household incomes greater than $50,000 had 

the highest mean consumption rate (59 g/day) and the 

highest 90th percentile consumption rate (129 g/day). 

Species of fish that were consumed in larger amounts 

than other species included barred sand bass, Pacific 

barracuda, kelp bass, rockfish species, Pacific bonito, 

and California halibut. 

About 77% of all anglers were aware of health 

warnings about consumption of fish from Santa 

Monica Bay. Of these anglers, 50% had altered their 

seafood consumption habits as a result of the 

warnings (46% stopped consuming some species, 

25% ate less of all species, 19% stopped consuming 

all fish, and 10% ate less of some species). Most 

anglers in the ethnic groups surveyed were aware of 

the health-risk warnings, but Asian and White anglers 

were more likely to alter their consumption behavior 

based on these warnings. 

One limitation of this study is the low numbers of 

anglers younger than 21 years of age. In this study, if 

several anglers from the same household were 

fishing, only the head of the household was 

interviewed. Hence, young individuals were 

frequently not interviewed and, therefore, are underrepresented in this study. 

It should also be noted that this study was not 

adjusted for avidity bias, but the California Office of 

Environmental Health Hazard Assessment has 

adjusted the distribution of fish consumption for 

avidity bias and other factors in the Air Toxics Hot 

Spots Program Risk Assessment Guidelines Part IV: 

Exposure Assessment and Stochastic Analysis 

Technical Support (see http://www.oehha.ca.gov/ 

air/hot_spots/finalStoc.html). 

10.4.2.8.	 Florida State Department of Health and 

Rehabilitative Services (1995)—Health 

Study to Assess the Human Health Effects 

of Mercury Exposure to Fish Consumed 

From the Everglades 

A health study was conducted in two phases in the 

Everglades, Florida for the U.S. Department of 

Health and Human Services (Florida State 

Department of Health and Rehabilitative Services, 

1995). The objectives of the first phase were to (a) 

describe the human populations at risk for mercury 

exposure through their consumption of fish and other 

contaminated animals from the Everglades and 

(b) evaluate the extent of mercury exposure in those 

persons consuming contaminated food and their 

compliance with the voluntary health advisory. The 

second phase of the study involved neurologic testing 

of all study participants who had total mercury levels 

in hair greater than 7.5 μg/g. 

Study participants were identified by using 

special targeted screenings, mailings to residents, 

postings and multi-media advertisements of the study 

throughout the Everglades region, and direct 

discussions with people fishing along the canals and 

waterways in the contaminated areas. The 

contaminated areas were identified by the 

interviewers and long-term Everglade residents. Of a 

total of 1,794 individuals sampled, 405 individuals 

were eligible to participate in the study because they 

had consumed fish or wildlife from the Everglades at 

least once per month in the last 3 months of the study 

period. The majority of the eligible participants 

(>93%) were either subsistence fishermen, Everglade 

residents, or both. Subsistence fishermen were 

defined in the survey as “people who rely on fish and 

the wildlife of the Everglades as a source of dietary 

protein for themselves and their families.” Of the 

total eligible participants, 55 individuals refused to 

participate in the survey. Useable data were obtained 

from 330 respondents ranging in age from 10–81 

years of age (mean age 39 years ± 18.8) (Florida 

State Department of Health and Rehabilitative 

Services, 1995). Respondents were administered a 

three-page questionnaire from which demographic 

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information, fishing and eating habits, and other 

variables were obtained (Florida State Department of 

Health and Rehabilitative Services, 1995). 

Table 10-60 shows the ranges, means, and 

standard deviations of selected characteristics by 

various groups of the survey population. Sixtytwo percent of the respondents were male with a 

slight preponderance of Black individuals (43% 

White, 46% Black non-Hispanic, and 11% Hispanic). 

Most of the respondents reported earning an annual 

income of $15,000 or less per family before taxes 

(Florida State Department of Health and 

Rehabilitative Services, 1995). The mean number of 

years fished along the canals by the respondents was 

15.8 years with a standard deviation of 15.8. The 

mean number of times per week fish consumers 

reported eating fish over the last 6 months and last 

month of the survey period were 1.8 and 1.5 per 

week with standard deviations of 2.5 and 1.4, 

respectively. Table 10-60 also indicates that 71% of 

the respondents reported knowing about the mercury 

health advisories. Of those who were aware, 26% 

reported that they had lowered their consumption of 

fish caught in the Everglades, while the rest (74%) 

reported no change in consumption patterns (Florida 

State Department of Health and Rehabilitative 

Services, 1995). 

A limitation of this study is that fish intake rates 

(g/day) were not reported. Another limitation is that 

the survey was site limited and, therefore, not 

representative of the U.S. population. An advantage 

of this study is that it is one of the few studies 

targeting populations expected to have higher 

consumption rates. 

10.4.2.9.	 Alcoa (1998)—Draft Report for the 

Finfish/Shellfish Consumption Study— 

Alcoa (Point Comfort)/Lavaca Bay 

Superfund Site 

The Texas Saltwater Angler Survey was 

conducted in 1996/1997 to evaluate the quantity and 

species of finfish and shellfish consumed by 

individuals who fish at Lavaca Bay (Alcoa, 1998). 

The target population for this study was residents of 

three Texas counties: Calhoun, Victoria, and Jackson 

(over 70% of the anglers who fish Lavaca Bay are 

from these three counties). The random sample 

design specified that the population percentages for 

the counties should be as follows: 50% from 

Calhoun, 30% from Victoria, and 20% from Jackson. 

Each individual in the sample population was sent 

an introductory note describing the study and then 

was contacted by telephone. People who agreed to 

participate and had taken fewer than six fishing trips 

to Lavaca Bay were interviewed by telephone. 

Persons who agreed to participate and had taken 

more than five fishing trips to Lavaca Bay were sent 

a mail survey with the same questions. A total of 

1,979 anglers participated in this survey, representing 

a response rate greater than 68%. Data were collected 

from the households for men, women, and children. 

The information collected as part of the survey 

included recreational fishing trip information for 

November 1996 (i.e., fishing site, site facilities, 

distance traveled, number and species caught), 

self-caught fish consumption (by the respondent, 

spouse and child, if applicable), opinions on different 

types of fishing experiences, and 

socio-demographics. Portion size for shellfish was 

determined by utilizing the number of shrimp, crabs, 

oysters, etc. that an individual consumed during a 

meal and the assumed tissue weight of the particular 

species of shellfish. 

Table 10-61 presents the results of the study. 

Adult men consumed 25 grams of self-caught finfish 

per day while women consumed an average of 

18 grams daily. Women of childbearing age 

consumed 19 grams per day, on average. Small 

children were found to consume 11 g/day, and youths 

consumed 16 g/day, on average. Less shellfish was 

consumed by all individuals than finfish. Men 

consumed an average of 2 g/day, women and youths 

an average of 1 g/day, and small children consumed 

less than 1 g/day of shellfish. 

The study results also showed the number of 

average meals and portion sizes for the respondents, 

(see Table 10-62). On average, members of each 

cohort consumed slightly more than 3 meals per 

month of finfish, although small children and youths 

consumed slightly less than 3 meals per month of 

finfish and less than 1 meal per month of shellfish. 

For finfish, adult men consumed an average, per 

meal, portion size of 8 ounces, while women and 

youths consumed 7 ounces, and small children 

consumed less than 5 ounces per meal. The average 

number of shellfish meals consumed per month for 

all cohorts was less than one. Adult men consumed 

an average shellfish portion size of 4 ounces, women 

and youth 3 ounces, and small children consumed 

2 ounces per meal. 

The study also discussed the species composition 

of self-caught fish consumed by source. 

Four different sources of fish were included: fish 

consumed from the closure area, fish consumed from 

Lavaca Bay, fish consumed from all waters, and all 

self-caught finfish and shellfish consumed, including 

preserved (i.e., frozen or smoked) fish where the 

location of the catch is not known. Red drum 

comprised the bulk of total finfish grams consumed 

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from any area, while black drum represented the 

smallest amount of finfish grams consumed. Overall, 

almost 40% of all self-caught finfish consumed were 

red drum, followed by speckled sea trout, flounder, 

all other finfish (all species were not specifically 

examined in this study), and black drum. Out of all 

self-caught shellfish, oysters accounted for 37%, blue 

crabs for 35%, and shrimp for 29% of the total. 

The study authors noted that because the survey 

relied on the anglers’ recall of meal frequency and 

portion, fish consumption may have been 

overestimated. There was evidence of overestimation 

when the data were validated, and approximately 

10% of anglers reported consuming more fish than 

what they caught and kept. Also, the study was 

conducted at one geographic location and may not be 

representative of the U.S. population. 

10.4.2.10. Burger et al. (1998)—Fishing, 

Consumption, and Risk Perception in 

Fisherfolk Along an East Coast Estuary 

Burger et al. (1998) examined fishing behavior, 

consumption patterns, and risk perceptions of 

515 people that were fishing and crabbing in 

Barnegat Bay, NJ. This research also tested the null 

hypotheses that there are no sex differences in fishing 

behavior and consumption patterns and no sex 

differences in the perception of fish and crab safety. 

The researchers interviewed 515 people who were 

fishing or crabbing on Barnegat Bay and Great Bay. 

Interviews were conducted from June 22 until 

September 27, 1996. Fifteen percent of the fishermen 

approached refused to be interviewed, usually 

because they did not have the time to participate. The 

questionnaire that researchers used to conduct the 

interviews contained questions about fishing 

behavior, consumption patterns, cooking patterns, 

warnings, and safety associated with the seafood, 

environmental problems, and changes in the Bay, and 

personal demographics. 

Eighty-four percent of those who were 

interviewed were men, 95% were White, and the rest 

were evenly divided between African American, 

Hispanic, and Asian. The age of interviewees ranged 

from 13 to 92 years. The subjects fished an average 

of seven times per month and crabbed three times per 

month (see Table 10-63). Bluefish (Pomatomus 

saltatrix), fluke or summer flounder (Paralichthys 

dentatus), and weakfish (Cynoscion regalis) were the 

most frequently caught fish. The researchers found 

that the average consumption rate for people fishing 

along the Barnegat Bay was 5 fish meals per month 

(eating just under 10 ounces per meal) for an 

approximate total of 1,450 grams of fish per month 

(48.3 g/day). Most of the subjects (80%) ate the fish 

they caught. 

The study found that there were significant 

differences in fishing behavior and consumption as a 

function of sex. Women had more children with them 

when fishing, and more women fished on foot along 

the Bay. The consumption by women included a 

significantly lower proportion of self-caught fish than 

men. Men ate significantly larger portions of fish per 

meal than did women, and men ate the whole fish 

more often. The study results showed that there were 

no sex differences with regard to the average number 

of fish caught or in fish size. Nearly 90% of the 

subjects believed the fish and crabs from Barnegat 

Bay were safe to eat, although approximately 40% of 

the subjects had heard warnings about their safety. 

The subjects generally did not have a clear 

understanding of the relationships between 

contaminants and fish size or trophic level. The 

researchers suggested that reducing the risk from 

contaminants does not necessarily involve a decrease 

in consumption rates but rather a change in the fish 

species and sizes consumed. 

While the study provides some useful information 

on sex difference in fishing behavior and 

consumption, the study is limited in that the majority 

of the people surveyed were White males. There were 

low numbers for women and ethnic groups. 

10.4.2.11. Chiang (1998)—A Seafood Consumption 

Survey of the Laotian Community of West 

Contra Costa County, CA 

A survey of members of the Laotian community 

of West Contra Costa, CA, was conducted to obtain 

data on the fishing and fish consumption activities of 

this community. A questionnaire was developed and 

translated by the survey staff into the many ethnic 

languages spoken by the members of the Laotian 

community. The survey questions covered the 

following topics: demographics, fishing and fish 

consumption habits back home, current fishing and 

fish consumption habits, fish preparation methods, 

fish species commonly caught, fishing locations, and 

awareness of the health advisory for this area. A total 

of 229 people were surveyed. 

Most respondents reported eating fish a few times 

per month, and the most common portion size was 

about 3 ounces. The mean amount of fish eaten per 

day was reported as 18.3 g/day, with a maximum of 

182.3 g/day (see Table 10-64). “Fish consumers” 

were considered to be people who ate fish at least 

once a month, and this group made up 86.9% of the 

people surveyed. The mean fish consumption rate for 

this group (“fish consumers”) averaged 21.4 g/day. 

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Catfish was most often mentioned when respondents 

were asked to name the fish they caught, but striped 

bass was the species reported caught most often by 

respondents. Soups/stews were reported as the most 

common preparation method of fish (86.4%) 

followed by frying (78.4%), and baking (63.6%). 

Of all survey respondents, 48.5% reported having 

heard of the health advisory about eating fish and 

shellfish from San Francisco Bay. Of those that had 

heard the advisory, 59.5% reported recalling its 

contents, and 60.3% said that it had influenced their 

fishing and fish consumption patterns. 

Some sectors of the Laotian community were not 

included in the survey such as the Lue, Hmong, and 

Lahu groups. However, it was noted that the groups 

excluded from the survey do not differ greatly from 

the sample population in terms of seafood 

consumption and fishing practices. The study authors 

also indicated that participants may have 

under-reported fishing and fish consumption 

practices due to recent publicity about contamination 

of the Bay, fear of losing disability benefits, and fear 

that the survey was linked to law enforcement actions 

about fishing from the Bay. Another limitation of the 

study involved the use of a 3-ounce fish fillet model 

to estimate portion size of fish consumed. The use of 

this small model may have biased respondents to 

choose a smaller portion size than what they actually 

eat. In addition, the study authors noted that the fillet 

model may not have been appropriate for estimating 

fish portions eaten by those respondents who eat 

“family style” meals. 

10.4.2.12. San Francisco Estuary Institute (SFEI) 

(2000)—Technical Report: San Francisco 

Bay Seafood Consumption Report 

A comprehensive study of 1,331 anglers was 

conducted by the California Department of Health 

Services between July 1998 and June 1999 at various 

recreational fishing locations in the San Francisco 

Bay area . The catching and consumption of 13 

finned fish species and 3 shellfish species were 

investigated to determine the number of meals eaten 

from recreational and other sources such as 

restaurants and grocery stores. The method of fish 

preparation, including the parts of the fish eaten, was 

also documented. Information was gathered on the 

amount of fish consumed per meal, as well as 

respondents’ ethnicity, age, income level, education, 

and the mode of fishing (e.g., pier, boat, and beach). 

Questions were also asked to ascertain the anglers’ 

knowledge and response to local fish advisories. 

Respondents were asked to recall their 

fishing/consumption experiences within the previous 

4 weeks. Anglers were not asked about the 

consumption habits of other members of their 

families. 

About 15% of the anglers reported that they do 

not eat San Francisco Bay fish (whether self-caught 

or commercial). Of those who did consume Bay fish, 

80% consumed about 1 fish meal per month or less; 

10% ate about 2 fish meals per month; and 10% ate 

more than 2 fish meals per month, which is above the 

advisory level for fish. (The advisory level was 

16 grams per day, or about two 8-ounce meals per 

4 weeks.) Two-thirds of those consuming fish at 

levels above the advisory limit consumed more than 

twice the advisory limit. Difference in income, 

education, or fishing mode did not markedly change 

anglers’ likelihood of eating in excess of the advisory 

limit. African Americans and Filipino anglers 

reported higher consumption levels than Caucasians 

(see Table 10-65). The overall mean consumption 

rate was 23 g/day. 

More than 50% of the finfish caught by anglers 

were striped bass, and about 25% were halibut. 

Approximately 15% of the anglers caught each of the 

following fish: jacksmelt, sturgeon, and white 

croaker. All other species were caught by less than 

10% of the anglers. For white croaker fish 

consumption: (1) lower income anglers consumed 

statistically more fish than mid- and upper-level 

income anglers, (2) anglers who did not have a high 

school education consumed more than those anglers 

with higher education levels, and (3) anglers of Asian 

descent consumed significantly more than anglers of 

other ethnic backgrounds. Asian anglers were more 

likely to eat fish skin, cooking juices, and raw fish 

than other anglers. These portions of the fish are 

believed to be more likely to contain higher levels of 

contamination. Likewise, skin consumption was 

higher for lower income and shore-based anglers. 

Anglers who had eaten Bay fish in the previous 

4 weeks indicated, in general, that they were likely to 

have eaten 1 fish meal from another source in the 

same time period. 

More than 60% of the anglers interviewed 

reported having knowledge of the health advisories. 

Of that 60%, only about one-third reported changing 

their fish-consumption behavior. 

A limitation of this study is that the sample size 

for ethnic groups was very small. Data are also 

specific to the San Francisco Bay area and may not 

be representative of anglers in other locations. 

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10.4.2.13. Burger (2002a)—Consumption Patterns 

and Why People Eat Fish 

Burger (2002a) evaluated fishing behavior and 

consumption patterns among 267 anglers who were 

interviewed at locations around Newark Bay and the 

New York-New Jersey Harbor estuary in 1999. 

Among the 267 study respondents, 13% were Asian, 

21% were Hispanic, 23% were Black, and 43% were 

White. Survey participants provided demographic 

information as well as information on their fish and 

crab consumption, knowledge of fishing advisories, 

and reasons for angling. Individual monthly fish 

consumption was estimated by multiplying the 

reported number of fish meals eaten per month by an 

average portion size, based on comparisons to a 

three-dimensional model of an 8-ounce fish fillet. 

Individual monthly crab consumption was estimated 

by multiplying the reported number of crabs eaten 

per month by the edible portion of crab, which was 

assumed to weigh 70 grams. Yearly fish and crab 

consumption was estimated by multiplying the 

monthly consumption rates by the number of months 

in a year over which the survey respondents reported 

eating self-caught fish or crabs. Intake rates were 

provided separately for those who fished only (44%), 

for those who crabbed only (44%), and for 

respondents who reported both fishing and crabbing 

(12%) (Burger, 2002a). Burger (2002a) also reported 

that more than 30% of the respondents reported that 

they did not eat the fish or crabs that they caught. 

Table 10-66 provides the average daily intake rates of 

fish and crab. U.S. EPA calculated these average 

daily intake rates by dividing the yearly intake rates 

provided by Burger (2002a) by 365 days/year. 

Burger (2002a) also evaluated potential 

differences in consumption based on age, income, 

and race/ethnicity. Consumption was found to be 

negatively correlated with mean income and 

positively correlated with age for fish, but not crabs. 

An evaluation of differences based on ethnicity 

indicated that Whites were the least likely to eat their 

catch than other groups; 49% of Whites, 40% of 

Hispanics, 24% of Asians, and 22% of Blacks 

reported that they did not eat the fish or crabs that 

they caught. Among all ethnicities most people 

indicated that they fished (63%) or crabbed (68%) for 

recreational purposes, and very few (4%) reported 

that they angled to obtain food. 

The advantages of this study are that it provides 

information for both fish and crab intake, and that it 

provides data on intake over a longer period of time 

than many of the other studies summarized in this 

chapter. However, the data are for individuals living 

in the Newark Bay area and may not be 

representative of the U.S. population as a whole. 

Also, there may be uncertainties in long-term intake 

estimates that are based on recall. 

10.4.2.14. Mayfield et al. (2007)—Survey of Fish 

Consumption Patterns of King County 

(Washington) Recreational Anglers 

Mayfield et al. (2007) conducted a series of fish 

consumption surveys among recreational anglers at 

marine and freshwater sites in King County, WA. The 

marine surveys were conducted between 1997 and 

2002 at public parks and boat launches throughout 

Elliot Bay and the Duwamish River, and at North 

King County marine locations. The numbers of 

individuals interviewed at these three locations were 

807, 152, and 228, respectively. The majority of 

participants were male, 15 years and older, and were 

either Caucasian or Asian and Pacific Islander. Data 

were collected on fishing location preferences, 

fishing frequency, consumption amounts, species 

preferences, cooking methods, and whether family 

members would also consume the catch. Respondent 

demographic data were also collected. Consumption 

rates were estimated using information on fishing 

frequency, weight of the catch, a cleaning factor, and 

the number of individuals consuming the catch. Mean 

recreational marine fish and shellfish consumption 

rates were 53 g/day and 25 g/day, respectively (see 

Table 10-67). Mayfield et al. (2007) also reported 

differences in intake according to ethnicity. Mean 

marine fish intake rates were 73, 60, 50, 43, and 

35 g/day for Native American, Caucasian, Asian and 

Pacific Islander, African American, and 

Hispanic/Latino respondents, respectively. 

The advantages of this study are that it provides 

additional perspective on recreational marine fish 

intake. However, the data are limited to a specific 

area of the United States and may not be 

representative of anglers in other locations. 

10.5. FRESHWATER RECREATIONAL 

STUDIES 

10.5.1.	 Fiore et al. (1989)—Sport Fish 

Consumption and Body Burden Levels of 

Chlorinated Hydrocarbons: A Study of 

Wisconsin Anglers 

This survey, reported by Fiore et al. (1989), was 

conducted to assess socio-demographic factors and 

sport-fishing habits of anglers, to evaluate anglers’ 

comprehension of and compliance with the 

Wisconsin Fish Consumption Advisory, to measure 

body burden levels of polychlorinated biphenyls 

(PCBs) and Dichlorodiphenyldichloroethylene 

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(DDE) through analysis of blood serum samples, and 

to examine the relationship between body burden 

levels and consumption of sport-caught fish. The 

survey targeted all Wisconsin residents who had 

purchased fishing or sporting licenses in 1984 in any 

of 10 pre-selected study counties. These counties 

were chosen in part based on their proximity to water 

bodies identified in Wisconsin fish advisories. A total 

of 1,600 anglers were sent survey questionnaires 

during the summer of 1985. 

The survey questionnaire included questions 

about fishing history, locations fished, species 

targeted, kilograms caught for consumption, overall 

fish consumption (including commercially caught), 

and knowledge of fish advisories. The recall period 

was 1 year. 

A total of 801 surveys were returned 

(50% response rate). Of these, 601 (75%) were from 

males and 200 from females; the mean age was 

37 years. Fiore et al. (1989) reported that the mean 

number of fish meals for 1984 for all respondents 

was 18 for sport-caught meals and 24 for 

non-sport-caught meals. Fiore et al. (1989) assumed 

that each fish meal consisted of 8 ounces (227 grams) 

of fish to generate means and percentiles of fish 

intake. The reported mean and 95th percentile intake 

rate of sport-caught fish for all respondents were 

11.2 g/day and 37.3 g/day, respectively. Among 

consumers, who comprised 91% of all respondents, 

the mean sport-caught fish intake rate was 12.3 g/day, 

and the 95th percentile was 37.3 g/day. The mean 

daily fish intake from all sources (both sport-caught 

and commercial) was 26.1 g/day, with a 95th 

percentile of 63.4 g/day. The 95th percentile of 37.3 

g/day of sport caught fish represents 60 fish meals 

per year; the 95th percentile of 63.4 g/day of total fish 

intake represents 102 fish meals per year. 

U.S. EPA obtained the raw data from this study 

and calculated the distribution of the number of 

sport-caught fish meals and the distribution of fish 

intake rates using the same meal size (227 g/meal) 

used by Fiore et al. (1989). This meal size is higher 

than the mean meal size of 114 g/meal, but similar to 

the 90th percentile meal size for general population 

adults (age 20–39 years) reported in a study by 

Smiciklas-Wright et al. (2002). However, because 

data for the general population may underestimate 

meal size for anglers, use of an upper percentile 

general population value may reflect higher intake 

among anglers. This is supported by data from other 

studies in the literature that have shown that the 

average meal size for sport fishing populations is 

higher than those of the general population. For 

example, Balcom et al. (1999) reported an average 

meal size for sport-caught fish for the angler 

population of 7.3 ounces (i.e., 207 grams), while the 

average meal size for the general population was 

5 ounces (142 grams). Other studies reported similar 

meal sizes for sport-caught fish. West et al. (1989) 

stated that the meal size most often reported in their 

survey was 8 ounces (i.e., 227 grams), and Connelly 

et al. (1996) estimated an average meal size of 

216 grams. Another study reported an average meal 

size of 376 grams (Burger et al., 1999). Therefore, the 

meal size used by Fiore et al. (1989) was deemed 

reasonable to represent a mean value for the 

population of sport anglers. Table 10-68 presents 

distributions of fish consumption using a meal size of 

227 grams. 

This study is limited in its ability to accurately 

estimate intake rates because of the absence of data 

on weight of fish consumed. Another limitation of 

this study is that the results are based on 1-year 

recall, which may tend to over-estimate the number 

of fishing trips (Ebert et al., 1993). In addition, the 

response rate was rather low (50%). 

10.5.2.	 West et al. (1989)—Michigan Sport 

Anglers Fish Consumption Survey 

The Michigan Sport Anglers Fish Consumption 

Survey (West et al., 1989) surveyed a stratified 

random sample of Michigan residents with fishing 

licenses. The sample was divided into 18 cohorts, 

with one cohort receiving a mail questionnaire each 

week between January and May 1989. The survey 

included both a short-term recall component, and a 

usual frequency component. For the short-term recall 

component, respondents were asked to identify all 

household members and list all fish meals consumed 

by each household member during the past 7 days. 

Information on the source of the fish for each meal 

was also requested (self-caught, gift, market, or 

restaurant). Respondents were asked to categorize 

serving size by comparison with pictures of 8-ounce 

fish portions; serving sizes could be designated as 

either “about the same size,” “less,” or “more” than 

the size pictured. Data on fish species, locations of 

self-caught fish, and methods of preparation and 

cooking were also obtained. 

The usual frequency component of the survey 

asked about the frequency of fish meals during each 

of the four seasons and requested respondents give 

the overall percentage of household fish meals that 

came from recreational sources. A sample of 

2,600 individuals was selected from state records to 

receive survey questionnaires. A total of 2,334 survey 

questionnaires were deliverable, and 1,104 were 

completed and returned, giving a response rate of 

47.3%. 

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In the analysis of the survey data by West et al. 

(1989), the authors did not attempt to generate the 

distribution of recreationally caught fish intake in the 

survey population. U.S. EPA obtained the raw data of 

this survey for the purpose of generating fish intake 

distributions and other specialized analyses. 

As described elsewhere in this handbook, 

percentiles of the distribution of average daily intake 

reflective of long-term consumption patterns cannot, 

in general, be estimated using short-term (e.g., 

1 week) data. Such data can be used to adequately 

estimate mean average daily intake rates (reflective 

of short- or long-term consumption); in addition, 

short-term data can serve to validate estimates of 

usual intake based on longer recall. 

U.S. EPA first analyzed the short-term data with 

the intent of estimating mean fish intake rates. In 

order to compare these results with those based on 

usual intake, only respondents with information on 

both short-term and usual intake were included in this 

analysis. For the analysis of the short-term data, 

U.S. EPA modified the serving size weights used by 

West et al. (1989), which were 5, 8, and 10-ounces, 

respectively, for portions that were less, about the 

same, and more than the 8-ounce picture. U.S. EPA 

examined the percentiles of the distribution of fish 

meal sizes reported in Pao et al. (1982) derived from 

the 1977–1978 USDA National Food Consumption 

Survey and observed that a lognormal distribution 

provided a good visual fit to the percentile data. 

Using this lognormal distribution, the mean values 

for serving sizes greater than 8 ounces and for 

serving sizes at least 10% greater than 8 ounces were 

determined. In both cases, a serving size of 12 ounces 

was consistent with the Pao et al. (1982) distribution. 

The weights used in the U.S. EPA analysis then were 

5, 8, and 12 ounces for fish meals described as less, 

about the same, and more than the 8-ounces picture, 

respectively. The mean serving size from Pao et al. 

(1982) was about 5 ounces, well below the value of 

8 ounces most commonly reported by respondents in 

the West et al. (1989) survey. 

Table 10-69 displays the mean number of total 

and recreational fish meals for each household 

member based on the 7-day recall data. Also shown 

are mean fish intake rates derived by applying the 

weights described above to each fish meal. Intake 

was calculated on both g/day and g/kg body weightday bases. This analysis was restricted to individuals 

who eat fish and who reside in households reporting 

some recreational fish consumption during the 

previous year. About 75% of survey respondents (i.e., 

licensed anglers) and about 84% of respondents who 

fished in the prior year reported some household 

recreational fish consumption. 

The U.S. EPA analysis next attempted to use the 

short-term data to validate the usual intake data. West 

et al. (1989) asked the main respondent in each 

household to provide estimates of their usual 

frequency of fishing and eating fish, by season, 

during the previous year. The survey provides a series 

of frequency categories for each season, and the 

respondent was asked to check the appropriate range. 

The ranges used for all questions were almost daily, 

2–4 times a week, once a week, 2–3 times a month, 

once a month, less often, none, and don’t know. For 

quantitative analysis of the data, it is necessary to 

convert this categorical information into numerical 

frequency values. As some of the ranges are 

relatively broad, the choice of conversion values can 

have some effect on intake estimates. In order to 

obtain optimal values, the usual fish eating frequency 

reported by respondents for the season during which 

the questionnaire was completed was compared to the 

number of fish meals reportedly consumed by 

respondents over the 7-day short-term recall period. 

The results of these comparisons are displayed in 

Table 10-70; it shows that, on average, there is 

general agreement between estimates made using 

1-year recall and estimates based on 7-day recall. The 

average number of meals (1.96/week) was at the 

bottom of the range for the most frequent 

consumption group with data (2–4 meals/week). In 

contrast, for the lower usual frequency categories, the 

average number of meals was at the top, or exceeded 

the top of category range. This suggests some 

tendency for relatively infrequent fish eaters to 

underestimate their usual frequency of fish 

consumption. The last column of the table shows the 

estimated fish eating frequency per week that was 

selected for use in making quantitative estimates of 

usual fish intake. These values were guided by the 

values in the second column, except that frequency 

values that were inconsistent with the ranges 

provided to respondents in the survey were avoided. 

Using the four seasonal fish-eating frequencies 

provided by respondents and the above conversions 

for reported intake frequency, U.S. EPA estimated the 

average number of fish meals per week for each 

respondent. This estimate, as well as the analysis 

above, pertains to the total number of fish meals 

eaten (in Michigan) regardless of the source of the 

fish. Respondents were not asked to provide a 

seasonal breakdown for eating frequency of 

recreationally caught fish; rather, they provided an 

overall estimate for the past year of the percent of 

fish they ate that was obtained from different sources. 

U.S. EPA estimated the annual frequency of 

recreationally caught fish meals by multiplying the 

estimated total number of fish meals by the reported 

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Chapter 10—Intake of Fish and Shellfish 

percent of fish meals obtained from recreational 

sources; recreational sources were defined as either 

self-caught or a gift from family or friends. 

The usual intake component of the survey did not 

include questions about the usual portion size for fish 

meals. In order to estimate usual fish intake, a portion 

size of 8 ounces was applied (the majority of 

respondents reported this meal size in the 7-day recall 

data). Individual body-weight data were used to 

estimate intake on a g/kg-day basis. Table 10-71 

displays the fish intake distribution estimated by U.S. 

EPA. 

The distribution shown in Table 10-71 is based on 

respondents who consumed recreational caught fish. 

As mentioned above, these represent 75% of all 

respondents and 84% of respondents who reported 

having fished in the prior year. Among this latter 

population, the mean recreational fish intake rate is 

14.4 × 0.84 = 12.1 g/day; the value of 38.7 g/day 

(95th percentile among consumers) corresponds to the 

95.8th percentile of the fish intake distribution in this 

(fishing) population. 

The advantages of this data set and analysis are 

that the survey was relatively large and contained 

both short-term and usual intake data. The presence 

of short-term data allowed validation of the usual 

intake data, which were based on long-term recall; 

thus, some of the problems associated with surveys 

relying on long-term recall are mitigated here. 

The response rate of this survey, 47%, was 

relatively low. In addition, the usual fish intake 

distribution generated here employed a constant fish 

meal size, 8 ounces. Although use of this value as an 

average meal size was validated by the short-term 

recall results, the use of a constant meal size, even if 

correct on average, may seriously reduce the 

variation in the estimated fish intake distribution. 

This study was conducted in the winter and spring 

months of 1988. This period does not include the 

summer months, when peak fishing activity can be 

anticipated, leading to the possibility that intake 

results based on the 7-day recall data may understate 

individuals’ usual (annual average) fish consumption. 

A second survey by West et al. (1993) gathered diary 

data on fish intake for respondents spaced over a full 

year. However, this later survey did not include 

questions about usual fish intake and has not been reanalyzed here. The mean recreational fish intake rates 

derived from the short-term and usual components 

were quite similar, however, 14.0 versus 14.4 g/day. 

10.5.3.	 ChemRisk (1992)—Consumption of 

Freshwater Fish by Maine Anglers 

ChemRisk conducted a study to characterize the 

rates of freshwater fish consumption among Maine 

residents (Ebert et al., 1993; ChemRisk, 1992). 

Because the only dietary source of local freshwater 

fish is recreational fish, the anglers in Maine were 

chosen as the survey population. The survey was 

designed to gather information on the consumption of 

fish caught by anglers from flowing (rivers and 

streams) and standing (lakes and ponds) water 

bodies. Respondents were asked to recall the 

frequency of fishing trips during the 1989–1990 

ice-fishing season, and the 1990 open water season, 

the number of fish species caught during both 

seasons, and to estimate the number of fish consumed 

from 15 fish species. The respondents were also 

asked to describe the number, species, and average 

length of each sport-caught fish consumed that had 

been gifts from other members of their households or 

other households. The weight of fish consumed by 

anglers was calculated by first multiplying the 

estimated weight of the fish by the edible fraction and 

then dividing this product by the number of intended 

consumers. Species-specific regression equations 

were utilized to estimate weight from the reported 

fish length. The edible fractions used were 0.4 for 

salmon, 0.78 for Atlantic smelt, and 0.3 for all other 

species (Ebert et al., 1993). 

A total of 2,500 prospective survey participants 

were randomly selected from a list of anglers 

licensed in Maine. The surveys were mailed in during 

October 1990. Because this was before the end of the 

open fishing season, respondents were also asked to 

predict how many more open water fishing trips they 

would undertake in 1990. 

ChemRisk (1992) and Ebert et al. (1993) 

calculated distributions of freshwater fish intake for 

two populations, “all anglers” and “consuming 

anglers.” All anglers were defined as licensed anglers 

who fished during either the 1989–1990 ice-fishing 

season or the 1990 open-water season (consumers 

and non-consumers) and licensed anglers who did not 

fish but consumed freshwater fish caught in Maine 

during these seasons. “Consuming anglers” were 

defined as those anglers who consumed freshwater 

fish obtained from Maine sources during the 

1989-1990 ice fishing or 1990 open water fishing 

season. In addition, the distribution of fish intake 

from rivers and streams was also calculated for 

two populations, those fishing on rivers and streams 

(“river anglers”), and those consuming fish from 

rivers and streams (“consuming river anglers”). 

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A total of 1,612 surveys were returned, giving a 

response rate of 64%; 1,369 (85%) of the 

1,612 respondents were included in the “all angler” 

population, and 1,053 (65%) were included in the 

“consuming angler” population. Table 10-72 presents 

freshwater fish intake distributions. The mean and 

95th percentile were 5.0 g/day and 21.0 g/day, 

respectively, for “all anglers,” and 6.4 g/day and 

26.0 g/day, respectively, for “consuming anglers.” 

Table 10-72 also presents intake distributions for fish 

caught from rivers and streams. Among “river 

anglers,” the mean and 95th percentile were 1.9 g/day 

and 6.2 g/day, respectively, while among “consuming 

river anglers,” the mean and the 95th percentile were 

3.7 g/day and 12.0 g/day, respectively. Table 10-73 

presents fish intake distributions by ethnic group for 

consuming anglers. The highest mean intake rates 

reported are for Native Americans (10 g/day) and 

French Canadians (7.4 g/day). Because there was a 

low number of respondents for Hispanics, 

Asian/Pacific Islanders, and African Americans, 

intake rates within these groups were not calculated 

(ChemRisk, 1992). 

Table 10-74 presents the consumption, by species, 

of freshwater fish caught. The largest species 

consumption was salmon from ice fishing 

(~292,000 grams); white perch (380,000 grams) for 

lakes and ponds; and Brook trout (420,000 grams) for 

rivers and streams (ChemRisk, 1992). 

U.S. EPA obtained the raw data tapes from the 

marine anglers survey and performed some 

specialized analyses. One analysis involved 

examining the percentiles of the “resource utilization 

distribution” (this distribution was defined in 

Section 10.1). The 50th, or more generally, the pth 

percentile of the resource utilization distribution, is 

defined as the consumption level such that p percent 

of the resource is consumed by individuals with 

consumptions below this level and 100–p percent by 

individuals with consumptions above this level. 

U.S. EPA found that 90% of recreational fish 

consumption was by individuals with intake rates 

above 3.1 g/day, and 50% was by individuals with 

intakes above 20 g/day. Those above 3.1 g/day make 

up about 30% of the “all angler” population, and 

those above 20 g/day make up about 5% of this 

population; thus, the top 5% of the angler population 

consumed 50% of the recreational fish catch. 

U.S. EPA also performed an analysis of fish 

consumption among anglers and their families. This 

analysis was possible because the survey included 

questions on the number, sex, and age of each 

individual in the household and whether the 

individual consumed recreationally caught fish. The 

total population of licensed anglers in this survey and 

their household members was 4,872; the average 

household size for the 1,612 anglers in the survey 

was thus 3.0 persons. Fifty-six percent of the 

population was male, and 30% was 18 or under. 

A total of 55% of this population was reported to 

consume freshwater recreationally caught fish in the 

year of the survey. The sex and ethnic distribution of 

the consumers was similar to that of the overall 

population. The distribution of fish intake among the 

overall household population, or among consumers in 

the household, can be calculated under the 

assumption that recreationally caught fish was shared 

equally among all members of the household 

reporting consumption of such fish (note this 

assumption was used above to calculate intake rates 

for anglers). With this assumption, the mean intake 

rate among consumers was 5.9 g/day, with a median 

of 1.8 g/day, and a 95th percentile of 23.1 g/day; for 

the overall population, the mean was 3.2 g/day and 

the 95th percentile was 14.1 g/day. 

The results of this survey can be put into the 

context of the overall Maine population. The 

1,612 anglers surveyed represent about 0.7% of the 

estimated 225,000 licensed anglers in Maine. It is 

reasonable to assume that licensed anglers and their 

families will have the highest exposure to 

recreationally caught freshwater fish. Thus, to 

estimate the number of persons in Maine with 

recreationally caught freshwater fish intake above, 

for instance, 6.5 g/day (the 80th percentile among 

household consumers in this survey), one can assume 

that virtually all persons came from the population of 

licensed anglers and their families. The number of 

persons above 6.5 g/day in the household survey 

population is calculated by taking 20% (i.e., 100– 

80%) of the consuming population in the survey; this 

number then is 0.2 × (0.55 × 4,872) = 536. Dividing 

this number by the sampling fraction of 0.007 (0.7%), 

gives about 77,000 persons above 6.5 g/day of 

recreational freshwater fish consumption statewide. 

The 1990 census showed the population of Maine to 

be 1.2 million people; thus, the 77,000 persons above 

6.5 g/day represent about 6% of the state’s 

population. 

ChemRisk (1992) reported that the fish 

consumption estimates were based upon the 

following assumptions: a 40% estimate as the edible 

portion of landlocked and Atlantic salmon; inclusion 

of the intended number of future fishing trips and an 

assumption that the average success and consumption 

rates for the individual angler during the trips already 

taken would continue through future trips. The data 

collected for this study were based on recall and 

self-reporting, which may have resulted in a biased 

estimate. The social desirability of the sport and 

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Chapter 10—Intake of Fish and Shellfish 

frequency of fishing are also bias-contributing 

factors; successful anglers are among the highest 

consumers of freshwater fish (ChemRisk, 1992). 

Additionally, fish advisories are in place in these 

areas and may affect the rate of fish consumption 

among anglers. The survey results showed that in 

1990, 23% of all anglers consumed no freshwater 

fish, and 55% of the river anglers ate no freshwater 

fish. An advantage of this study is that the sample 

size is rather large. 

10.5.4.	 Connelly et al. (1992)—Effects of Health 

Advisory and Advisory Changes on 

Fishing Habits and Fish Consumption in 

New York Sport Fisheries 

Connelly et al. (1992) conducted a study to assess 

the awareness and knowledge of New York anglers 

about fishing advisories and contaminants found in 

fish and their fishing and fish consuming behaviors. 

The survey sample consisted of 2,000 anglers with 

New York State fishing licenses for the year 

beginning October 1, 1990, through 

September 30, 1991. A questionnaire was mailed to 

the survey sample in January 1992. The questionnaire 

was designed to measure catch and consumption of 

fish, as well as methods of fish preparation and 

knowledge of and attitudes towards health advisories 

(Connelly et al., 1992). The survey-adjusted response 

rate was 52.8% (1,030 questionnaires were 

completed, and 51 were not deliverable). 

The average and median number of fishing days 

per year were 27 and 15 days, respectively (Connelly 

et al., 1992). The mean number of sport-caught fish 

meals was 11 meals/year. The maximum number of 

meals consumed was 757 meals/year. About 25% of 

anglers reported that they did not consume sportcaught fish. 

Connelly et al. (1992) found that 80% of anglers 

statewide did not eat listed species or ate them within 

advisory limits and followed the 1 sport-caught fish 

meal per week recommended maximum. The other 

20% of anglers exceeded the advisory 

recommendations in some way; 15% ate listed 

species above the limit, and 5% ate more than 

one sport-caught meal per week. 

Connelly et al. (1992) found that respondents 

eating more than 1 sport-caught meal per week were 

just as likely as those eating less than one meal per 

week to know the recommended level of sport-caught 

fish consumption, although less than 1/3 in each 

group knew the level. An estimated 85% of anglers 

were aware of the health advisory. Over 50% of 

respondents said that they made changes in their 

fishing or fish consumption behaviors in response to 

health advisories. 

The advisory included a section on methods that 

can be used to reduce contaminant exposure. 

Respondents were asked what methods they used for 

fish cleaning and cooking. 

A limitation of this study with respect to 

estimating fish intake rates is that only the number of 

sport-caught meals was ascertained, not the weight of 

fish consumed. The fish meal data can be converted 

to a mean intake rate (g/day) by assuming a meal size 

of 227 g/meal (i.e., 8 ounces). This value 

corresponds to the adult general population 90th 

percentile meal size derived from Smiciklas-Wright 

et al. (2002). The resulting mean intake rate among 

the angler population would be 6.8 g/day. However, 

about 25% of this population reported no 

sport-caught fish consumption. Therefore, the mean 

consumption rate among consuming anglers would 

be 27.4 g/day (i.e., 6.8 g/day divided by 0.25). 

The major focus of this study was not on 

consumption, per se, but on the knowledge of and 

impact of fish health advisories; Connelly et al. 

(1992) provides important information on these 

issues. 

10.5.5.	 Hudson River Sloop Clearwater, Inc. 

(1993)—Hudson River Angler Survey 

Hudson River Sloop Clearwater, Inc. (1993) 

conducted a survey of adherence to fish consumption 

health advisories among Hudson River anglers. All 

fishing has been banned on the upper Hudson River 

where high levels of PCB contamination are well 

documented; while voluntary recreational fish 

consumption advisories have been issued for areas 

south of the Troy Dam (Hudson River Sloop 

Clearwater, 1993). 

The survey consisted of direct interviews with 

336 shore-based anglers between the months of June 

and November 1991, and April and July 1992. Table 

10-75 presents socio-demographic characteristics of 

the respondents. The survey sites were selected based 

on observations of use by anglers, and legal 

accessibility. The selected sites included upper-, mid-, 

and lower- Hudson River sites located in both rural 

and urban settings. The interviews were conducted on 

weekends and weekdays during morning, midday, 

and evening periods. The anglers were asked specific 

questions concerning: fishing and fish consumption 

habits; perceptions of presence of contaminants in 

fish; perceptions of risks associated with 

consumption of recreationally caught fish; and 

awareness of, attitude toward, and response to fish 

consumption advisories or fishing bans. 

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Approximately 92% of the survey respondents 

were male. The following statistics were provided by 

Hudson River Sloop Clearwater, Inc. (1993). The 

most common reason given for fishing was for 

recreation or enjoyment. Over 58% of those surveyed 

indicated that they eat their catch. Of those anglers 

who eat their catch, 48% reported being aware of 

advisories. Approximately 24% of those who said 

they currently do not eat their catch have done so in 

the past. Anglers were more likely to eat their catch 

from the lower Hudson areas where health advisories, 

rather than fishing bans, have been issued. 

Approximately 94% of Hispanic Americans were 

likely to eat their catch, while 77% of African 

Americans and 47% of Caucasian Americans 

intended to eat their catch. Of those who eat their 

catch, 87% were likely to share their meal with others 

(including women of childbearing age, and children 

under the age of 15). 

For subsistence anglers, more low-income than 

upper-income anglers eat their catch (Hudson River 

Sloop Clearwater, 1993). Approximately 10% of the 

respondents stated that food was their primary reason 

for fishing; this group is more likely to be in the 

lowest per capita income group (Hudson River Sloop 

Clearwater, 1993). 

The average frequency of fish consumption 

reported was just under 1 (0.9) meal over the 

previous week, and 3 meals over the previous month. 

Approximately 35% of all anglers who eat their catch 

exceeded the amounts recommended by the New 

York State health advisories. Less than half (48%) of 

all the anglers interviewed were aware of the State 

health advisories or fishing bans. Only 42% of those 

anglers aware of the advisories have changed their 

fishing habits as a result. 

The advantages of this study include in-person 

interviews with 95% of all anglers approached; 

field-tested questions designed to minimize 

interviewer bias; and candid responses concerning 

consumption of fish from contaminated waters. The 

limitations of this study are that specific intake 

amounts are not indicated, and that only shore-based 

anglers were interviewed. 

10.5.6.	 West et al. (1993)—Michigan Sport 

Anglers Fish Consumption Study, 1991– 

1992 

West et al. (1993) conducted a survey financed by 

the Michigan Great Lakes Protection Fund, as a 

follow-up to the earlier 1989 Michigan survey 

described previously. The major purpose of 1991– 

1992 survey was to provide short-term recall data of 

recreational fish consumption over a full year period; 

the 1989 survey, in contrast, was conducted over only 

a half year period (West et al., 1993). 

This survey was similar in design to the 1989 

Michigan survey. A sample of 7,000 persons with 

Michigan fishing licenses was drawn, and surveys 

were mailed in 2-week cohorts over the period 

January 1991 to January 1992. Respondents were 

asked to report detailed fish consumption patterns 

during the preceding 7 days, as well as demographic 

information; they were also asked if they currently 

eat fish. Enclosed with the survey were pictures of 

about a half pound of fish. Respondents were asked 

to indicate whether reported consumption at each 

meal was more, less, or about the same as the picture. 

Based on responses to this question, respondents 

were assumed to have consumed ten, 5- or 8-ounce 

portions of fish, respectively. 

A total of 2,681 surveys were returned. West et al. 

(1993) calculated a response rate for the survey of 

46.8%; this was derived by removing from the 

sample those respondents who could not be located 

or who did not reside in Michigan for at least 

6 months. 

Of these 2,681 respondents, 2,475 (93%) reported 

that they currently eat fish; all subsequent analyses 

were restricted to the current fish eaters. The mean 

fish consumption rates were found to be 16.7 g/day 

for sport fish and 26.5 g/day for total fish (West et al., 

1993). Table 10-76 shows mean sport-fish 

consumption rates by demographic categories. Rates 

were higher among minorities, people with low 

income, and people residing in smaller communities. 

Consumption rates in g/day were also higher in males 

than in females; however, this difference would likely 

disappear if rates were computed on a g/kg-day basis. 

West et al. (1993) estimated the 80th percentile of 

the survey fish consumption distribution. More 

extensive percentile calculations were performed by 

U.S. EPA (1995) using the raw data from the West 

et al. (1993) survey. However, because this survey 

only measured fish consumption over a short 

(1 week) interval, the resulting distribution will not 

be indicative of the long-term fish consumption 

distribution, and the upper percentiles reported from 

the U.S. EPA analysis will likely considerably 

overestimate the corresponding long-term percentiles. 

The overall 95th percentile calculated by U.S. EPA 

(1995) was 77.9; this is about double the 

95th percentile estimated using yearlong consumption 

data from the 1989 Michigan survey. 

The limitations of this survey are the relatively 

low response rate and the fact that only 

three categories were used to assign fish portion size. 

The main study strengths were its relatively large size 

and its reliance on short-term recall. 

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10.5.7.	 Alabama Dept. of Environmental 

Management (ADEM) (1994)— 

Estimation of Daily Per Capita 

Freshwater Fish Consumption of 

Alabama Anglers 

The Alabama Department of Environmental 

Management (1994) conducted a fish consumption 

survey of sport-fishing Alabama anglers during the 

time period from August 1992 to August 1993. The 

target population included all anglers who were 

Alabama residents. The survey design consisted of 

personal interviews given to sport fishermen at the 

end of their fishing trips at 23 sampling sites. Each 

sampling site was surveyed once during each season 

(summer, fall, winter, and spring). The survey was 

conducted for 2 consecutive days, either a Friday and 

Saturday or a Sunday and Monday. This approach 

minimized single-day-type bias and maximized 

surveying the largest number of anglers because a 

large amount of fishing occurs on weekends. Anglers 

were asked about consumption of fish caught at the 

sampling site as well as consumption of fish caught 

from other lakes and rivers in Alabama. 

A total of 1,586 anglers were interviewed during 

the entire study period, of which, 83% reported 

eating fish they caught from the sampling sites 

(1,313 anglers). The number of anglers interviewed 

during each season was as follows: 488 during the 

summer, 363 during the fall, 224 during the winter, 

and 511 during the spring. Fish consumption rates 

were estimated using two methods: the 4-ounce 

Serving Method and the Harvest Method. The 

4-ounce Serving Method estimated consumption 

based on a typical 4-ounce serving size. The Harvest 

Method used the actual harvest of fish and dressing 

method reported. All of the 1,313 anglers were used 

in the mean estimates of daily consumption based on 

the 4-ounce Serving Method, while only 563 anglers 

were utilized in the calculations of mean estimates of 

daily consumption, based on the Harvest Method. 

Table 10-77 shows the results of the survey. 

Adults consumed an annual average of 32.6 g/day 

using the Harvest Method, calculated from study 

sites, and an annual average of 43.1 g/day using the 

Harvest Method, calculated from study sites plus 

other Alabama lakes and rivers. The survey also 

showed that adults consumed an annual average of 

30.3 g/day using the 4-ounce Serving Method, 

calculated from study sites, and an annual average of 

45.8 g/day using the 4-ounce Serving Method, 

calculated from study sites plus other Alabama lakes 

and rivers. When the entire sample was pooled, and a 

mean was taken over all respondents for the 4-ounce 

Serving Method, the average annual consumption 

was 44.8 g/day. 

The study also examined fish consumption in 

conjunction with socio-demographic factors. It was 

noted that fish consumption tended to increase with 

age. Anglers below the age of 20 years were not well 

represented in this study. However, based on 

estimates of consumption rates using the 4-ounce 

Serving Method, the study found that anglers 

between 20 and 30 years of age consumed an average 

of 16 g/day, anglers between 30 and 50 years old 

consumed 39 g/day, and anglers over 50 years old 

consumed 76 g/day. Trends also emerged when ethnic 

groups and income levels were examined together. 

Using the 4-ounce Serving Method, estimates of fish 

consumption for Blacks dropped from 60 g/day for 

poverty-level families to 15 g/day for upper-income 

families. For Whites, fish consumption rates dropped 

slightly from 41 g/day for poverty-level families to 

35 g/day for upper-income families. Similar trends 

were observed with the Harvest Method estimates. 

Averaging the results from the two estimation 

methods, there was a tendency for upper-income 

White anglers to eat roughly 30% less fish than 

poverty-level White anglers, while upper-income 

Black anglers ate about 80% less fish as povertylevel Black anglers. The analysis of seasonal intake 

showed that the highest consumption rates were 

consistently found to occur in the summer (see Table 

10-77). It was also found the lowest fish consumption 

rate occurred in the spring. 

The advantages of this study are that it compares 

estimates of intake using two different methods and 

provides some perspective on seasonal differences in 

intake. Data are not provided for children, and the 

number of observations for some race/ethnic groups 

is very small. 

10.5.8.	 Connelly et al. (1996)—Sportfish 

Consumption Patterns of Lake Ontario 

Anglers and the Relationship to Health 

Advisories, 1992 

The objectives of the Connelly et al. (1996) study 

were to provide accurate estimates of fish 

consumption (overall and sport caught) among Lake 

Ontario anglers and to evaluate the effect of Lake 

Ontario health advisory recommendations (Connelly 

et al., 1996). To target Lake Ontario anglers, a sample 

of 2,500 names was randomly drawn from 1990– 

1991 New York fishing license records for licenses 

purchased in six counties bordering Lake Ontario. 

Participation in the study was solicited by mail with 

potential participants encouraged to enroll in the 

study even if they fished infrequently or consumed 

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Chapter 10—Intake of Fish and Shellfish 

little or no sport-caught fish. The survey design 

involved three survey techniques including a mail 

questionnaire asking for 12-month recall of 1991 

fishing trips and fish consumption, self-recording 

information in a diary for 1992 fishing trips and fish 

consumption, periodic telephone interviews to gather 

information recorded in the diary, and a final 

telephone interview to determine awareness of health 

advisories (Connelly et al., 1996). 

Participants were instructed to record in the diary 

the species of fish eaten, meal size, method by which 

fish was acquired (sport-caught or other), fish 

preparation and cooking techniques used, and the 

number of household members eating the meal. Fish 

meals were defined as finfish only. Meal size was 

estimated by participants by comparing their meal 

size to pictures of 8-ounce fish steaks and fillets on 

dinner plates. An 8-ounce size was assumed unless 

participants noted their meal size was smaller than 

8 ounces, in which case, a 4-ounce size was assumed, 

or they noted it was larger than 8 ounces, in which 

case, a 12-ounce size was assumed. Participants were 

also asked to record information on fishing trips to 

Lake Ontario and species and length of any fish 

caught. 

From the initial sample of 2,500 license buyers, 

1,993 (80%) were reachable by phone or mail, and 

1,410 of these were eligible for the study, in that they 

intended to fish Lake Ontario in 1992. A total of 

1,202 of these 1,410, or 85%, agreed to participate in 

the study. Of the 1,202 participants, 853 either 

returned the diary or provided diary information by 

telephone. Due to changes in health advisories for 

Lake Ontario, which resulted in less Lake Ontario 

fishing in 1992, only 43%, or 366 of these 

853 persons indicated that they fished Lake Ontario 

during 1992. The study analyses summarized below 

concerning fish consumption and Lake Ontario 

fishing participation are based on these 366 persons. 

Anglers who fished Lake Ontario reported an 

average of 30.3 (standard error = 2.3) fish meals per 

person from all sources in 1992; of these meals, 28% 

were sport caught (Connelly et al., 1996). Less than 

1% ate no fish for the year, and 16% ate no sportcaught fish. The mean fish intake rate from all 

sources was 17.9 g/day, and from sport-caught 

sources was 4.9 g/day. Table 10-78 gives the 

distribution of fish intake rates from all sources and 

from sport-caught fish. The median rates were 

14.1 g/day for all sources and 2.2 g/day for sport 

caught; the 95th percentiles were 42.3 g/day and 

17.9 g/day for all sources and sport caught, 

respectively. As seen in Table 10-79, statistically 

significant differences in intake rates were seen 

across age and residence groups, with residents of 

large cities and younger people having lower intake 

rates, on average. 

The main advantage of this study is the diary 

format. This format provides more accurate 

information on fishing participation and fish 

consumption, than studies based on 1-year recall 

(Ebert et al., 1993). However, a considerable portion 

of diary respondents participated in the study for only 

a portion of the year, and some errors may have been 

generated in extrapolating these respondents’ results 

to the entire year (Connelly et al., 1996). In addition, 

the response rate for this study was relatively low— 

853 of 1,410 eligible respondents, or 60%—which 

may have engendered some non-response bias. 

The presence of health advisories should be taken 

into account when evaluating the intake rates 

observed in this study. Nearly all respondents (>95%) 

were aware of the Lake Ontario health advisory. This 

advisory counseled to eat none of nine fish species 

from Lake Ontario and to eat no more than one meal 

per month of another four species. In addition, New 

York State issues a general advisory to eat no more 

than 52 sport-caught fish meals per year. Among 

participants who fished Lake Ontario in 1992, 32% 

said they would eat more fish if health advisories did 

not exist. A significant fraction of respondents did not 

totally adhere to the fish advisory; however, 36% of 

respondents, and 72% of respondents reporting Lake 

Ontario fish consumption, ate at least one species of 

fish over the advisory limit. Interestingly, 90% of 

those violating the advisory reported that they 

believed they were eating within advisory limits. 

10.5.9.	 Balcom et al. (1999)—Quantification of 

Seafood Consumption Rates for 

Connecticut 

Balcom et al. (1999) conducted a seafood 

consumption study in Connecticut, utilizing a food 

frequency questionnaire along with portion size 

models. Follow-up telephone calls were made to 

encourage participation 7–10 days after mailing the 

questionnaires to improve response rates. Information 

requested in the survey included frequency of fish 

consumption, types of fish/seafood eaten, portion 

size, parts eaten, and the source of the fish/seafood 

eaten. A diary was also given to the sample 

populations to record fish and seafood consumption 

over a 10-day period, and to document where the 

fish/seafood was obtained and how it was prepared. 

The sample population size for this study was 

2,354 individuals (1,048 households). The study 

authors divided this overall population into various 

population groups including the general population 

(460 individuals/216 households), commercial 

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Chapter 10—Intake of Fish and Shellfish 

fishing population (178 individuals/73 households), 

sport fishing and cultural/subsistence fishing 

population (514 individuals/348 households), 

minority population 

(860 individuals/245 households), Southeast Asian 

(329 individuals/89 households), non-Southeast 

Asian (531 individuals/156 households), limited 

income population (937 individuals/276 households), 

women of childbearing age population 

(493 individuals/420 households), and children 

population (559 individuals/305 households). 

It is important to note that the nine population 

groups used in this study are not mutually exclusive. 

Many individuals were included in more than one 

population. For this reason, the authors did not 

attempt to make any statistical comparisons between 

the population groups. 

The survey showed that over 33% of the 

respondents ate 1–2 meals of fish or seafood per 

week, including 39% of the general population, 

35% of the sport fishing population, 38% of the 

commercial and minority populations, and 39% of 

the limited income population. A total of 36% of the 

Southeast Asian population consumed 2–3 meals per 

week with 2.1% consuming 5 or more meals per 

week, while 43% of non-Southeast Asians consumed 

1–2 meals of seafood per week. The general 

population consumed, on average, 4.2 ounces of fish 

per meal of purchased fish and 5.0 ounces per meal 

of caught fish. Individuals in the sport fishing 

population showed a marked difference, consuming 

4.7 ounces per meal of bought fish and 7.3 ounces 

per meal of caught fish. Southeast Asians consumed 

smaller portions of fish per meal, and children 

consumed the smallest portions of fish per meal. 

On average, the general population consumed 

27.7 g/day of fish and seafood while the sport fishing 

population consumed 51.1 g/day (see Table 10-80). 

The consumption of sport fish among consuming 

anglers can be estimated by dividing the consumption 

for all respondents by the percentage of consuming 

anglers reported by Balcom et al. (1999) of 97% to 

yield 52.7 g/day. The commercial fishing population 

had an average consumption rate of 47.4 g/day, while 

the limited income population’s rate was 43.1 g/day. 

The overall minority population consumption rate 

was 50.3 g/day, with Southeast Asians consuming an 

average of 59.2 g/day (the highest overall rate) and 

non-Southeast Asians consuming an average of 

45.0 g/day. Child-bearing age women consumed an 

average of 45.0 g/day, and children consumed an 

average of 18.3 g/day. 

The study also examined fish preparations and 

cooking practices for each population group. It was 

found that the sport fishing population was most 

likely to perform risk-reducing preparation methods 

compared to the other populations, while the minority 

population was least likely to use the same 

risk-reducing methods. Cooking information by 

specie was only available for the Southeast Asian 

population, but the most common cooking methods 

were boiling, poaching-boiling-steaming, sauté/stir 

fry, and deep frying. 

The authors noted that there were some 

limitations to this study. First, there was some 

association among household members in terms of 

the tendency to eat fish and seafood, but there was no 

dependence between households. Second, the study 

had a very low percent return rate for the general 

population mail survey, and it is questionable whether 

or not the responses accurately reflect the total 

population’s behavior. In addition, the proportion of 

intake that can be attributed to freshwater fish is not 

known. 

10.5.10. Burger et al. (1999)—Factors in Exposure 

Assessment: Ethnic and Socioeconomic 

Differences in Fishing and Consumption 

of Fish Caught Along the Savannah River 

Burger et al. (1999) examined the differences in 

fishing rates and fish consumption of people fishing 

along the Savannah River as a function of age, 

education, ethnicity, employment history, and 

income. A total of 258 people who were fishing on 

the Savannah River were interviewed. The interviews 

were conducted both on land and by boat from April 

to November 1997. Anglers were asked about fishing 

behavior, consumption patterns, cooking patterns, 

knowledge of warnings and safety of fish, and 

personal demographics. The authors used multiple 

regression procedures to examine the relative 

contribution of ethnicity, income, age, and education 

to parameters such as years fished, serving size, 

meals/month, and total ounces of fish consumed per 

year. 

Eighty-nine percent of people interviewed were 

men, 70% were White, 28% were African American, 

and 2% were of other ethnicity not specified in the 

study. The age of the interviewees ranged from 16 to 

82 years (mean = 43 ± 1 years). The study authors 

reported that the average fish intake for all survey 

respondents was 1.46 kg of fish per month 

(48.7 g/day). Although most of the respondents were 

men, they indicated that their wives and children 

consumed fish as often as they did, and children 

began to eat fish at 3 to 5 years of age. 

There were significant differences in fishing 

behavior and consumption as a function of ethnicity 

(see Table 10-81). African Americans fished more 

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Chapter 10—Intake of Fish and Shellfish 

often, consumed fish more frequently, and ate larger 

portions of fish than did Whites. Given the higher 

level of consumption by African Americans 

compared to consumption by Whites, the study 

authors suggested that the potential for exposure is 

higher for African Americans than for Whites, 

although the risks depend on the levels of 

contaminants in the fish. Income and education also 

contributed to variations in fishing and consumption 

behavior. Anglers with low incomes (less than or 

equal to $20,000) ate fish more often that those with 

higher incomes. Anglers who had not graduated from 

high school consumed fish more frequently, ate more 

fish per month and per year, and deep fried fish more 

often than anglers with more education. At all levels 

of education, African Americans consumed more fish 

than Whites. 

The authors acknowledged that there may have 

been sampling bias in the study because they only 

interviewed people who were fishing on the river and 

were, therefore, limited to those people they found. 

To reduce the bias, the authors conducted the survey 

at all times of the day, on all days of the week, and 

along different sections of the river. Another 

limitation noted by the study authors is that the 

survey asked questions about consumption of fish 

from two general sources: self-caught and bought. 

The study authors indicated that it would have been 

useful to distinguish between fish obtained directly 

from the wild by the anglers, their friends or family, 

and store-bought or restaurant fish. 

10.5.11. Williams et al. (1999)—Consumption of 

Indiana Sport-Caught Fish: Mail Survey 

of Resident License Holders 

In 1997, sport-caught fish consumption among 

licensed Indiana anglers was assessed using a mail 

survey (Williams et al., 1999). Anglers were asked 

about their consumption patterns during a 3-month 

recall, their fishing rates, species of fish consumed, 

awareness of advisory warnings, and associated 

behaviors. 

Average meal size among respondents was 

9.3 ounces per meal. Consumers indicated that, on 

average, they ate between 1 and 2 meals per month. 

The survey population was divided into active 

consumers (those who actively engage in consuming 

sport fish meals) and potential consumers (those who 

eat fish during other times of the year). The average 

consumption rate for active consumers was reported 

as 19.8 g/day. For both active and potential 

consumers, the rate was 16.4 g/day (see Table 10-82). 

The statewide mail survey of licensed Indiana 

anglers did not specifically address lower-income and 

minority anglers. The respondents to the mail survey 

were predominately White (94.5%). The recall period 

for this survey extended from the summer through 

the end of fall and early winter. No information was 

collected on consumption during spring or winter. 

Another limitation of the study was that only 

sport-caught fish consumption was measured among 

anglers. 

10.5.12. Burger (2000)—Gender Differences in 

Meal Patterns: Role of Self-Caught Fish 

and Wild Game in Meat and Fish Diets 

Burger (2000) used the hypothesis that there are 

sex differences in consumption patterns of 

self-caught fish and wild game in a meat and fish 

diet. A total of 457 people were randomly selected 

and interviewed while attending the Palmetto 

Sportsmen’s Classic in Columbia, SC in March 1998. 

The mean age of the respondents was 40 years and 

ranged from 15 to 74. The questionnaire requested 

information on two different categories: 

socio-demographics and number of meals consumed 

that included several types of fish and wild game. 

The demographics section contained questions 

dealing with ethnicity, sex, age, location of residence, 

occupation, and income. The section on consumption 

of wild game and fish included specific questions 

about the number of meals eaten and the source (i.e., 

self-caught fish, store-bought fish, and restaurant 

fish). 

The results of this study indicated that there were 

no sex differences in the percentage of people who 

ate commercial protein sources, but there were 

significant sex differences for the consumption of 

most wild-caught game and fish. A higher proportion 

of men (81.5%) ate wild-caught species than women 

(73.2%). There were also sex differences in mean 

monthly meals and mean serving sizes for 

wild-caught fish. Men ate more meals of wild-caught 

fish than woman, and men also ate larger portions 

than women. The mean number of wild-caught fish 

meals eaten per month was 2.24 for men and 1.52 for 

women. The mean serving size was 373 grams for 

men and 232 for women. The study authors also 

found that individuals who consumed a large number 

of fish meals per month consumed a higher 

percentage of wild-caught fish meals than individuals 

who consumed a small number of fish meals per 

month. 

This study provides information on sex 

differences with regard to consumption of 

wild-caught fish. Information on the number of 

monthly meals and meal size is provided. However, 

the study did not distinguish between marine and 

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Chapter 10—Intake of Fish and Shellfish 

freshwater fish. In addition, all subjects interviewed 

were White. 

10.5.13. Williams et al. (2000)—An Examination 

of Fish Consumption by Indiana 

Recreational Anglers: An Onsite Survey 

An on-site survey of Indiana anglers was 

conducted in the summer of 1998 (Williams et al., 

2000). A total of 946 surveys were completed. 

Minority anglers accounted for 31.8% of those 

surveyed, with African American anglers accounting 

for the majority of this group (25.1% of all 

respondents). Respondents reporting household 

incomes below $25,000 comprised 30.9% of the 

respondents. Anglers were asked to report their 

Indiana sport-caught fish consumption frequency for 

a 3-month recall period. Using the meal frequency 

and portion size reported by the anglers, the amount 

of fish consumed was calculated into a daily amount 

called grams per day consumption. Consumption 

rates were weighted to correct for participation bias. 

Consumption was reported as 27.2 g/day among 

minority consumers and 20.0 g/day among White 

consumers (see Table 10-83). Of the anglers 

surveyed, 75.4% of White active consumers reported 

being aware of the fish consumption advisory, while 

70.0% of the minority consumers reported awareness. 

The study authors also examined angler consumption 

rate based on the level of awareness of Indiana fish 

consumption advisories reported by the anglers. The 

consumption rate for those consumers who were very 

aware of the advisory was 35.2 g/day. For those with 

a general awareness of the advisory, the consumption 

rate was 14.1 g/day, and for those who were not 

aware of the advisory, the consumption rate was 

21.3 g/day. In terms of income, the study authors 

found that there was a significant difference in grams 

of Indiana sport-caught fish consumed per day. 

Anglers reporting a household income below $25,000 

had an average consumption rate of 18.9 g/day. 

Anglers with incomes between $25,000 and $34,999 

averaged 18.8 g/day, and anglers with incomes 

between $35,000 and $49,999 averaged 15.2 g/day. 

The highest income—those reporting an income 

$50,000 or above—consumed an average of 

48.9 g/day. 

The advantages of this study are that it was 

designed to determine the consumption rates of 

Indiana anglers, particularly those in minority and 

low-income groups, during a portion of the year. 

However, information was not collected for the 

period of September through January, so calculation 

of year-round consumption was not possible. 

10.5.14. Benson et al. (2001)—Fish Consumption 

Survey: Minnesota and North Dakota 

Benson et al. (2001) conducted a fish 

consumption survey among Minnesota and North 

Dakota residents. The target population included the 

general population, licensed anglers, and members of 

Native American tribes. The survey focused on 

obtaining the most recent year’s fish intake from all 

sources, including locally caught fish. Survey 

questionnaires were mailed to potential respondent 

households. Groups of interest were selected and 

allotted a portion of the total number of surveys to be 

distributed to each group as follows: a group 

categorized as the general population and anglers 

received 37.5% of the surveys, and new mothers and 

Native Americans each received 12.5% of the total 

surveys distributed. The survey distribution was split 

60/40 between Minnesota and North Dakota. For the 

entire survey population, a total of 1,565 surveys 

were returned completed (out of 7,835 that were 

mailed out), resulting in a total of 4,273 respondents. 

A target of 100 completed telephone interviews of 

non-respondents was set in order to characterize the 

non-respondent population. However, this target was 

not met. 

The Minnesota survey showed median total fish 

and sport fish consumption rates for the general 

population (2,312 respondents) of 12.3 and 2.8 g/day, 

respectively (see Table 10-84). The total number of 

Minnesota Bois Forte Tribe respondents was 232, and 

median total fish and sport fish consumption rates in 

g/day were 9.3 and 2.8, respectively. For Minnesota 

residents with fishing licenses (2,020 respondents), 

median total fish and sport fish consumption rates in 

g/day were 13.2 and 3.9, respectively. For Minnesota 

respondents without fishing licenses, median total 

fish and sport fish consumption rates in g/day were 

7.5 and 0, respectively. Table 10-84 also shows 

median intake rates for purchased fish, upper 

percentile intake rates for total fish, sport fish and 

purchased fish for various age groups. 

The North Dakota survey showed median total 

fish and sport fish consumption rates for the general 

population (1,406 respondents) of 12.6 and 3.0 g/day, 

respectively (see Table 10-84). The total number of 

North Dakota Spirit Lake Nation and Three Affiliated 

Tribes respondents was 105, and the median total fish 

and sport fish consumption rates in g/day were 1.4 

and 0, respectively. For North Dakota residents with 

fishing licenses (1,101 respondents), median total 

fish and sport fish consumption rates in g/day were 

14.0 and 4.5, respectively. For North Dakota 

respondents without fishing licenses, median total 

fish and sport fish consumption rates in g/day were 

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Chapter 10—Intake of Fish and Shellfish 

7.2 and 0, respectively. Table 10-84 also shows 

median intake rates for purchased fish, upper 

percentile intake rates for total fish, sport fish and 

purchased fish for various age groups. 

Westat (2006) analyzed the raw data from Benson 

et al. (2001) to derive fish consumption rates for 

various age, sex, and ethnic groups, and according to 

the source of fish consumed (i.e., bought or caught) 

and habitat (i.e., freshwater, estuarine, or marine). 

Westat (2006) calculated consumption rates of 

freshwater fish for consuming anglers. For Minnesota 

and North Dakota, these values are identical to the 

consumption rates estimated by Westat (2006) for 

consuming anglers of all self-caught fish (i.e., 

freshwater and saltwater). From this observation, it 

can be concluded that all the consumption of selfcaught fish comes from freshwater. The mean and 

95th percentile consumption rate for consuming 

anglers of freshwater fish reported by Westat (2006) 

are 14 g/day and 37 g/day, respectively, for 

Minnesota and 12 g/day and 43 g/day, respectively, 

for North Dakota. 

The authors noted that 80% of respondents in 

Minnesota and 72% of respondents in North Dakota 

lived in a household that included a licensed angler. 

They stated that this was a result of a direct intent to 

oversample the angling population in both states by 

sending 37.5% of surveys distributed to persons who 

purchased a fishing license in either Minnesota or 

North Dakota. The data were adjusted to incorporate 

overall licensed angler rates in both states (47.3% of 

households in Minnesota and 40.0% of households in 

North Dakota). 

An advantage of this study is its large overall 

sample size. A limitation of the study is the low 

numbers of Native Americans surveyed; thus, the 

survey may not be representative of overall Native 

American populations in Minnesota. In addition, the 

study did not include Asian Immigrants, African 

Americans, African immigrants, or Latino 

populations, and was limited to two states. Therefore, 

the results may not be representative of the U.S. 

population as a whole. 

10.5.15. Moya and Phillips (2001)—Analysis of 

Consumption of Home-Produced Foods 

As discussed in Section 10.4.2.5, some data on 

fish consumption from households who fish are 

provided in Chapter 13 and in Moya and Phillips 

(2001). This information is based on an analysis of 

data from the household component of the USDA’s 

1987–1988 NFCS. This analysis shows a mean 

consumer-only fish consumption of 2.2 g/kg-day (all 

ages combined, see Table 13-20) for the fishing 

population. This value can be converted to a per 

capita value by multiplying by the number of 

consumers and dividing by the total number of 

positive responses to the survey question “do you 

fish?” Assuming an average body weight of 59 kg for 

the survey population results in an average national 

per capita self-caught fish consumption rate of 

12 g/day among the population of individuals who 

fish. However, this mean intake rate represents intake 

of both freshwater and saltwater fish combined. 

Converting this number into the edible portion by 

multiplying by 0.5 as described in Section 10.4.2.5, 

the mean national per capita self-caught fish 

consumption rate is about 6 g/day. 

The advantage of this study is that it provides a 

national perspective on the consumption of 

self-caught fish. A limitation of this study is that 

these values include both freshwater and saltwater 

fish. The proportion of freshwater to saltwater is 

unknown and will vary depending on geographical 

location. Intake data cannot be presented for various 

age groups due to sample size limitations. The 

unweighted number of households, who responded 

positively to the survey question “do you fish?” was 

also low (i.e., 220 households). 

10.5.16. Rouse Campbell et al. (2002)—Fishing 

Along the Clinch River Arm of Watts Bar 

Reservoir Adjacent to the Oak Ridge 

Reservation, Tennessee: Behavior, 

Knowledge, and Risk Perception 

Rouse Campbell et al. (2002) examined 

consumption habits of anglers fishing along the 

Clinch River arm of Watts Bar Reservoir, adjacent to 

the U.S. Department of Energy’s Oak Ridge 

Reservation in East Tennessee. A total of 202 anglers 

were interviewed on 65 sampling days, which 

included 48 weekdays and 17 weekend days. Eightysix percent of fishermen interviewed were fishing 

from the shore, while 14% were fishing from a boat. 

The questionnaire utilized in the study included 

questions on demographics, fishing behavior, 

perceptions, cooking patterns, consumption patterns, 

and consumption warnings. Interviews were 

conducted by two people who were local to the area 

in order to promote participation in the study. 

Out of all anglers interviewed, approximately 

35% did not eat fish. Of the 65% who ate fish, only 

38% ate fish from the study area. This 38% 

(77 people) was considered useful to the study and, 

thus, were the main focus of the data analysis. These 

anglers averaged 2 meals of fish per month, with an 

average consumption rate of 37 grams per day or 

13.7 kilograms per year (see Table 10-85). They 

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Chapter 10—Intake of Fish and Shellfish 

caught almost 90% of the fish they ate, had a mean 

age of 42 years, and a mean income of $28,800. The 

species of fish most often mentioned by anglers who 

caught and ate fish from the study area were crappie, 

striped bass, white bass, sauger, and catfish. 

A limitation of this study is that the small size of 

the population does not allow for statistically 

significant analysis of the data. 

10.5.17. Burger (2002b)—Daily Consumption of 

Wild Fish and Game: Exposure of 

High-End Recreationists 

Burger (2002b) determined consumption patterns 

for a range of wild-caught fish and game in South 

Carolina. The population selected for dietary surveys 

were attendees at the Palmetto Sportsman’s Classic in 

Columbia, South Carolina. Individual dietary 

surveys were conducted at the show in March, 1998, 

on 458 participants who were randomly selected from 

an attending population of approximately 60,000 

people. Of the survey participants, 15% were Black, 

85% were White, and 33% were women. The age 

composition was similar for black and white 

respondents; however, Black participants had 

significantly lower mean incomes than White 

participants. 

The dietary survey took about 20 minutes to 

complete and was divided into three parts: a section 

on demographics; one on the number of meals 

consumed of different types of fish and meat for each 

of the past 12 months, and a section collecting 

information on serving size and cooking methods. 

The types of fish and meat inquired about included 

wild-caught fish, store-bought fish, restaurant fish, 

deer, wild-caught quail, restaurant quail, dove, duck, 

rabbit, squirrel, raccoon, wild turkey, beef, chicken, 

pork, and any wild game not listed in the 

questionnaire. Respondents were asked to provide 

information regarding serving/portion size and what 

percent of their meals they consumed as meat as 

opposed to stews. The average number of meals eaten 

as meat and stew were separately determined for each 

of the 12 months, then multiplied by the average 

serving size. Yearly consumption rates were then 

determined by summing across months for each type 

of fish or meat. Means and percentiles were 

computed using SAS. 

Mean daily consumption of wild-caught fish 

ranged from 32.6 g/kg-day for respondents less than 

32 years of age to 171.0 g/kg-day for Black 

respondents (see Table 10-86). The disparity in mean 

consumption was the greatest for ethnicity and 

income level, with black and low income respondents 

eating more than twice as much wild-caught fish as 

Whites or higher income respondents. Male fish 

consumption (mean of 55.2 g/kg-day) was higher 

than that of females (mean of 39.1 g/kg-day), while 

by age, fish consumption was highest among the 

33−45 year olds (mean intake of 71.3 g/kg-day). The 

author suggested that although the high consumption 

of wild-caught fish for this age group may reflect a 

more active lifestyle, it may also reflect exposure of 

women of child-bearing age. As shown in Table 

10-86, the differences between mean consumption 

rates and 99th percentile values were very large. For 

some population groups at the higher end of the 

distribution, fish consumption was ten times greater 

than that of the mean. 

This study provides useful comparisons on 

wild-caught fish intake among populations with 

differing ethnicity, sex, age, and income level. Data 

on fish consumption at the higher end of the 

distribution were also provided. A limitation of the 

study includes the fact that the study was based on 

dietary recall which is less reliable over time and may 

have recall bias. In addition, although the 

methodology indicated that information was collected 

and/or calculated for serving/portion size, the percent 

of meals consumed as meat versus stews, and yearly 

consumption rates, no data were provided for these 

parameters in the study. 

10.5.18. Mayfield et al. (2007)—Survey of Fish 

Consumption Patterns of King County 

(Washington) Recreational Anglers 

Mayfield et al. (2007) conducted a series of fish 

consumption surveys among recreational anglers at 

marine and freshwater sites in King County, WA. The 

freshwater surveys were conducted between 2002 

and 2003 at “freshwater locations around Lake 

Sammamish, Lake Washington, and Lake Union” 

(Mayfield et al., 2007). A total of 212 individuals 

were interviewed at these locations. The majority of 

participants were male, 18 years and older, and were 

either Caucasian or Asian and Pacific Islander. Data 

were collected on fishing location preferences, 

fishing frequency, consumption amounts, species 

preferences, cooking methods, and whether family 

members would also consume the catch. Respondent 

demographic data were also collected. Consumption 

rates were estimated using information on fish meal 

frequency and meal size. The mean recreational 

freshwater fish consumption rates were 10 g/day for 

all respondents and 7 g/day for the children of survey 

respondents (see Table 10-87). Mayfield et al. (2007) 

also reported differences in intake according to 

ethnicity. Mean freshwater fish intake rates were 40, 

38, 20, 19, and 2 g/day for Native American, African 

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Chapter 10—Intake of Fish and Shellfish 

American, Asian and Pacific Islander, Caucasian, and 

Hispanic/Latino respondents, respectively. 

The advantage of this study is that it provides 

additional perspective on recreational freshwater fish 

intake. However, the data are limited to a specific 

area of the United States and may not be 

representative of anglers in other locations. 

10.6. NATIVE AMERICAN STUDIES 

10.6.1.	 Wolfe and Walker (1987)—Subsistence 

Economies in Alaska: Productivity, 

Geography, and Development Impacts 

Wolfe and Walker (1987) analyzed a data set from 

98 communities for harvests of fish, land mammals, 

marine mammals, and other wild resources. The 

analysis was performed to evaluate the distribution 

and productivity of subsistence harvests in Alaska 

during the 1980s. Harvest levels were used as a 

measure of productivity. Wolfe and Walker (1987) 

defined harvest to represent a single year's production 

from a complete seasonal round. The harvest levels 

were derived primarily from a compilation of data 

from subsistence studies conducted between 1980 

and 1985 by various researchers in the Alaska 

Department of Fish and Game, Division of 

Subsistence. 

Of the 98 communities studied, four were large 

urban population centers, and 94 were small 

communities. The harvests for these latter 

94 communities were documented through detailed 

retrospective interviews with harvesters from a 

sample of households (Wolfe and Walker, 1987). 

Harvesters were asked to estimate the quantities of a 

particular species that were harvested and used by 

members of that household during the previous 

12-month period. Wolfe and Walker (1987) converted 

harvests to a common unit for comparison, pounds 

dressed weight per capita per year, by multiplying the 

harvests of households within each community by 

standard factors, converting total pounds to dressed 

weight, summing across households, and then 

dividing by the total number of household members 

in the household sample. Note average consumption 

by household member can be misleading because 

households include both children and adults whose 

intake rates may be very different. Dressed weight 

varied by species and community but, in general, was 

70% to 75% of total fish weight; dressed weight for 

fish represents that portion brought into the kitchen 

for use (Wolfe and Walker, 1987). 

Harvests for the four urban populations were 

developed from a statewide data set gathered by the 

Alaska Department of Fish and Game Divisions of 

Game and Sports Fish. Urban sport-fish harvest 

estimates were derived from a survey that was mailed 

to a randomly selected statewide sample of anglers 

(Wolfe and Walker, 1987). Sport-fish harvests were 

disaggregated by urban residency, and the data set 

was analyzed by converting the harvests into pounds 

and dividing by the 1983 urban population. 

For the overall analysis, each of the 

98 communities was treated as a single unit of 

analysis, and the entire group of communities was 

assumed to be a sample of all communities in Alaska 

(Wolfe and Walker, 1987). Each community was 

given equal weight, regardless of population size. 

Annual per capita harvests were calculated for each 

community. For the four urban centers, fish harvests 

ranged from 5 to 21 pounds per capita per year 

(6.2 g/day to 26.2 g/day). 

The range for the 94 small communities was 25 to 

1,239 pounds per capita per year (31 g/day to 

1,541 g/day). For these 94 communities, the median 

per capita fish harvest was 130 pounds per year 

(162 g/day). In most (68%) of the 98 communities 

analyzed, resource harvests for fish were greater than 

the harvests of the other wildlife categories (land 

mammal, marine mammal, and other) combined. 

The communities in this study were not made up 

entirely of Alaska Natives. For roughly half the 

communities, Alaska Natives comprised 80% or more 

of the population, but for about 40% of the 

communities, they comprised less than 50% of the 

population. Wolfe and Walker (1987) performed a 

regression analysis, which showed that the per capita 

harvest of a community tended to increase as a 

function of the percentage of Alaska Natives in the 

community. Although this analysis was done for total 

harvest (i.e., fish, land mammal, marine mammal, 

and others), the same result should hold for fish 

harvest because it is highly correlated with total 

harvest. 

A limitation of this report is that it presents per 

capita harvest rates as opposed to individual intake 

rates. Wolfe and Walker (1987) compared the per 

capita harvest rates reported to the results for the 

household component of the 1977–1978 USDA 

NFCS. The NFCS showed that about 222 pounds of 

meat, fish, and poultry were purchased and brought 

into the household kitchen for each person each year 

in the western region of the United States. This 

contrasts with a median total resource harvest of 

260 lbs/year in the 94 communities studied. This 

comparison, and the fact that Wolfe and Walker 

(1987) state that “harvests represent that portion 

brought into the kitchen for use,” suggest that the 

same factors used to convert household consumption 

rates in the NFCS to individual intake rates can be 

used to convert per capita harvest rates to individual 

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Chapter 10—Intake of Fish and Shellfish 

intake rates. In Section 10.3, a factor of 0.5 was used 

to convert fish consumption from household to 

individual intake rates. Applying this factor, the 

median per capita individual fish intake in the 

94 communities would be 81 g/day and the range 

15.5 to 770 g/day. 

A limitation of this study is that the data were 

based on 1-year recall from a mailed survey. An 

advantage of the study is that it is one of the few 

studies that present fish harvest patterns for 

subsistence populations. 

10.6.2.	 Columbia River Inter-Tribal Fish 

Commission (CRITFC) (1994)—A Fish 

Consumption Survey of the Umatilla, Nez 

Perce, Yakama, and Warm Springs 

Tribes of the Columbia River Basin 

The Columbia River Inter-Tribal Fish 

Commission (CRITFC) (1994) conducted a fish 

consumption survey among four Columbia River 

Basin Native American tribes during the fall and 

winter of 1991–1992. The target population included 

all adult tribal members who lived on or near the 

Yakama, Warm Springs, Umatilla, or Nez Perce 

reservations. The survey was based on a stratified 

random sampling design where respondents were 

selected from patient registration files at the Indian 

Health Service. Interviews were performed in person 

at a central location on the member’s reservation. 

The overall response rate was 69%, yielding a 

sample size of 513 tribal members, 18 years old and 

above. Of these, 58% were female, and 59% were 

under 40 years old. Each participating adult was 

asked if there were any children 5 years old or 

younger in his or her household. Those responding 

affirmatively were asked a set of survey questions 

about the fish consumption patterns of the youngest 

child in the household (CRITFC, 1994). Information 

for 204 children, 5 years old and younger, was 

provided by participating adult respondents. 

Consumption data were available for 194 of these 

children. 

Participants were asked to describe and quantify 

all food and drink consumed during the previous day. 

They were then asked to identify the months in which 

they ate the most and the least fish, and the number 

of fish meals consumed per week during each of 

those periods and an average value for the whole 

year. The typical portion size (in ounces) was 

determined with the aid of food models provided by 

the questioner. The next set of questions identified 

specific species of fish and addressed the number of 

times per month each was eaten, as well as what parts 

(e.g., fillet, skin, head, eggs, bones, other) were eaten. 

Respondents were then asked to identify the 

frequency with which they used various preparation 

methods, expressed as a percentage. Respondents 

sharing a household with a child, aged 5 years or less, 

were asked to repeat the serving size, eating 

frequency, and species questions for the child’s 

consumption behavior. All respondents were asked 

about the geographic origin of any fish they 

personally caught and consumed, and to identify the 

major sources of fish in their diet (e.g., self-caught, 

grocery store, tribe, etc.). Fish intake rates were 

calculated by multiplying the annual frequency of 

fish meals by the average serving size per fish meal. 

The population sizes of the four tribes were 

highly unequal, ranging from 818 to 

3,872 individuals (CRITFC, 1994). Nearly equal 

sample sizes were collected from each tribe. 

Weighting factors were applied to the pooled data (in 

proportion to tribal population size) so that the survey 

results would be representative of the overall 

population of the four tribes for adults only. Because 

the sample size for children was considered small, 

only an unweighted analysis was performed for this 

population. Based on a desired sample size of 

approximately 500 and an expected response rate of 

70%, 744 individuals were selected at random from 

lists of eligible patients; the numbers from each tribe 

were approximately equal. 

The results of the survey showed that adults 

consumed an average of 1.71 fish meals/week and 

had an average intake of 58.7 g/day (CRITFC, 1994). 

Table 10-88 shows the adult fish intake distribution; 

the median was between 29 and 32 g/day, and the 

95th percentile about 170 g/day. A small percentage 

(7%) of respondents indicated that they were not fish 

consumers. Table 10-89 shows that mean intake was 

slightly higher in males than females (63 g/day 

versus 56 g/day) and was higher in the over 60 years 

age group (74.4 g/day) than in the 18–39 years 

(57.6 g/day) or 40–59 years (55.8 g/day) age groups. 

Intake also tended to be higher among those living on 

the reservation. The mean intake for nursing 

mothers—59.1 g/day—was similar to the overall 

mean intake. Intake rates were calculated for children 

for which both the number of fish meals per week 

and serving size information were available. 

Appendix 10B presents the weighted percentage of 

adults consuming specific fish parts. 

A total of 49% of respondents of the total survey 

population reported that they caught fish from the 

Columbia River basin and its tributaries for personal 

use or for tribal ceremonies and distributions to other 

tribe members, and 88% reported that they obtained 

fish from either self-harvesting, family, or friends; at 

tribal ceremonies; or from tribal distributions. Of all 

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Chapter 10—Intake of Fish and Shellfish 

fish consumed, 41% came from self- or family 

harvesting, 11% from the harvest of friends, 35% 

from tribal ceremonies or distribution, 9% from 

stores, and 4% from other sources (CRITFC, 1994). 

Of the 204 children, the total number of 

respondents used in the analysis varied from 167 to 

202, depending on the topic (amount and species 

consumed, fish meals consumed/week, age 

consumption began, serving size, consumption of fish 

parts) of the analysis. The unweighted mean for the 

age when children begin eating fish was 13.1 months 

of age (N = 167). The unweighted mean number of 

fish meals consumed per week by children was 

1.2 meals per week (N = 195), and the unweighted 

mean serving size of fish for children aged 5 years 

old and less was 95 grams (i.e., 3.36 ounces) 

(N = 201). The unweighted percent of fish consumed 

by children by species was 82.7% for salmon, 

followed by 46.5% (N = 202) for trout. 

The analysis of seasonal intake showed that May 

and June tended to be high-consumption months and 

December and January, low consumption months. 

The mean adult intake rate for May and June was 

108 g/day, while the mean intake rate for December 

and January was 30.7 g/day. Salmon was the species 

eaten by the highest number of respondents (92%) 

followed by trout (70%), lamprey (54%), and smelt 

(52%). Table 10-90 gives the fish intake distribution 

for children under 5 years of age. The mean intake 

rate was 19.6 g/day, and the 95th percentile was 

approximately 70 g/day. These mean intake rates 

include both consumers and non-consumers. These 

values are based on survey questions involving 

estimated behavior throughout the year, which survey 

participants answered in terms of meals per week or 

per month and typical serving size per meal. Table 

10-91 presents consumption rates for children, who 

were reported to consume particular species of fish. 

The authors noted that some non-response bias 

may have occurred in the survey because respondents 

were more likely to be female and live near the 

reservation than non-respondents. In addition, they 

hypothesized that non-consumers may have been 

more likely to be non-respondents than fish 

consumers because non-consumers may have thought 

their contribution to the survey would be 

meaningless. If such were the case, this study would 

overestimate the mean per capita intake rate. It was 

also noted that the timing of the survey, which was 

conducted during low fish consumption months, may 

have led to underestimation of actual fish 

consumption. The authors conjectured that an 

individual may have reported higher annual 

consumption if interviewed during a relatively high 

consumption month and lower annual consumption if 

interviewed during a relatively low consumption 

month. Finally, with respect to children’s intake, it 

was observed that some of the respondents provided 

the same information for their children as for 

themselves; thereby, the reliability of some of these 

data is questioned (CRITFC, 1994). The combination 

of four different tribes’ survey responses into a single 

pooled data set is somewhat problematic. The data 

presented are unweighted and, therefore, contain a 

bias toward the smaller tribes, who were oversampled 

compared to the larger tribes. 

The limitations of this study, particularly with 

regard to the estimates of children’s consumption, 

result in a high degree of uncertainty in the estimated 

rates of consumption. Although the authors have 

noted these limitations, this study does present 

information on fish consumption patterns and habits 

for a Native American population. 

10.6.3.	 Peterson et al. (1994)—Fish Consumption 

Patterns and Blood Mercury Levels in 

Wisconsin Chippewa Indians 

Peterson et al. (1994) investigated the extent of 

exposure to methylmercury by Chippewa Indians 

living on a Northern Wisconsin reservation who 

consume fish caught in Northern Wisconsin lakes. 

Chippewa have a reputation for high fish 

consumption (Peterson et al., 1994). The Chippewa 

Indians fish by the traditional method of spearfishing. 

Spearfishing (for walleye) occurs for about 2 weeks 

each spring after the ice breaks, and although only a 

small number of tribal members participate in it, the 

spearfishing harvest is distributed widely within the 

tribe by an informal distribution network of family 

and friends and through traditional tribal feasts 

(Peterson et al., 1994). 

Potential survey participants, 465 adults, 18 years 

of age and older, were randomly selected from the 

tribal registries (Peterson et al., 1994). Participants 

were asked to complete a questionnaire describing 

their routine fish consumption and, more extensively, 

their fish consumption during the 2 previous months. 

The survey was carried out in May 1990. A follow-up 

survey was conducted for a random sample of 

75 non-respondents (80% were reachable), and their 

demographic and fish consumption patterns were 

obtained. Peterson et al. (1994) reported that the 

non-respondents' socioeconomic information and fish 

consumption were similar to the respondents. 

A total of 175 of the original random sample 

(38%) participated in the study. In addition, 

152 non-randomly selected participants were 

surveyed and included in the data analysis; these 

participants were reported by Peterson et al. (1994) to 

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Chapter 10—Intake of Fish and Shellfish 

have fish consumption rates similar to those of the 

randomly selected participants. Results from the 

survey showed that fish consumption varied 

seasonally, with 50% of the respondents reporting 

April and May (spearfishing season) as the highest 

fish consumption months (Peterson et al., 1994). 

Table 10-92 shows the number of fish meals 

consumed per week during the last 2 months (recent 

consumption) before the survey was conducted and 

during the respondents’ peak consumption months 

grouped by sex, age, education, and employment 

level. During peak consumption months, males 

consumed more fish (1.9 meals per week) than 

females (1.5 meals per week), respondents under 

35 years of age consumed more fish (1.8 meals per 

week) than respondents 35 years of age and over 

(1.6 meals per week), and the unemployed consumed 

more fish (1.9 meals per week) than the employed 

(1.6 meals per week). During the highest fish 

consumption season (April and May), 50% of 

respondents reported eating 1 or less fish meals per 

week, and only 2% reported daily fish consumption. 

A total of 72% of respondents reported Walleye 

consumption in the previous 2 months. Peterson et al. 

(1994) also reported that the mean number of fish 

meals usually consumed per week by the respondents 

was 1.2. 

The mean fish consumption rate reported (1.2 fish 

meals per week, or 62.4 meals per year) in this 

survey was compared with the rate reported in a 

previous survey of Wisconsin anglers (Fiore et al., 

1989) of 42 fish meals per year. These results indicate 

that the Chippewa Indians do not consume much 

more fish than the general Wisconsin angler 

population (Peterson et al., 1994). The differences in 

the two values may be attributed to differences in 

study methodology (Peterson et al., 1994). Note that 

this number (1.2 fish meals per week) includes fish 

from all sources. Peterson et al. (1994) noted that 

subsistence fishing, defined as fishing as a major 

food source, appears rare among the Chippewa. 

Using a meal size of 227 g/meal, the rate reported 

here of 1.2 fish meals per week translates into a mean 

fish intake rate of 39 g/day in this population. This 

meal size is similar to an adult general population 

90th percentile meal size derived from SmiciklasWright et al. (2002) (see Section 10.8.2). 

The advantages of this study are that it targeted a 

specific Native American population and provides 

some perspective on peak consumption and species 

of fish consumed. However, the data are more than 

2 decades old and may not be entirely representative 

of current intake patterns. 

10.6.4.	 Fitzgerald et al. (1995)—Fish PCB 

Concentrations and Consumption 

Patterns Among Mohawk Women at 

Akwesasne 

Akwesasne is a Native American community of 

10,000 plus persons located along the St. Lawrence 

River (Fitzgerald et al., 1995). Fitzgerald et al. (1995) 

conducted a recall study from 1986 to 1992 to 

determine the fish consumption patterns among 

nursing Mohawk women residing near 

three industrial sites. The study sample consisted of 

97 Mohawk women living on the Akwesasne 

Reservation and 154 nursing Caucasian controls 

living in Warren and Schoharie counties, which are 

primary rural like the Akwesasne. The Mohawk 

mothers were significantly younger (mean age: 24.9) 

than the controls (mean age: 26.4) and had 

significantly more years of education (mean: 13.1 for 

Mohawks versus 12.4 for controls). A total of 97 out 

of 119 Mohawk nursing women responded, a 

response rate of 78%; 154 out of 287 control nursing 

Caucasian women responded, a response rate of 54%. 

Statistical analysis focused upon socio-demographic, 

physical, reproductive, lifestyle, and dietary and 

consumption differences between the Mohawk and 

control women. 

Potential participants were identified prior to, or 

shortly after, delivery. The interviews were conducted 

at home within 1 month postpartum and were 

structured to collect information for sociodemographics, vital statistics, use of medications, 

occupational and residential histories, behavioral 

patterns (cigarette smoking and alcohol 

consumption), drinking water source, diet, and fish 

preparation methods (Fitzgerald et al., 1995). The 

dietary data collected were based on recall for food 

intake during the index pregnancy, the year before the 

pregnancy, and more than 1 year before the 

pregnancy. 

The dietary assessment involved the report by 

each participant on the consumption of various foods 

with emphasis on local species of fish and game 

(Fitzgerald et al., 1995). This method combined food 

frequency and dietary histories to estimate usual 

intake. Food frequency was evaluated with a 

checklist of foods for indicating the amount of 

consumption of a participant per week, month, or 

year. Information gathered for the dietary history 

included duration of consumption, changes in the 

diet, and food preparation method. 

Table 10-93 presents the number of local fish 

meals per year for both the Mohawk and control 

participants. The highest percentage of participants 

reported consuming between 1 and 9 local fish meals 

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Chapter 10—Intake of Fish and Shellfish 

per year. Table 10-93 indicates that Mohawk 

respondents consumed statistically significantly more 

local fish than did control respondents during the 

two time periods prior to pregnancy; for the time 

period during pregnancy, there was no significant 

difference in fish consumption between the 

two groups. Table 10-94 presents the mean number of 

local fish meals consumed per year by time period for 

all respondents and for those ever consuming 

(consumers only). A total of 82 (85%) Mohawk 

mothers and 72 (47%) control mothers reported ever 

consuming local fish. The mean number of local fish 

meals consumed per year by Mohawk respondents 

declined over time, from 23.4 (over 1 year before 

pregnancy) to 9.2 (less than 1 year before pregnancy) 

to 3.9 (during pregnancy); a similar decline was seen 

among consuming Mohawks only. There was also a 

decreasing trend over time in consumption among 

controls, though it was much less pronounced. 

Table 10-95 presents the mean number of fish 

meals consumed per year for all participants by time 

period and selected characteristics (age, education, 

cigarette smoking, and alcohol consumption). 

Pairwise contrasts indicated that control participants 

over 34 years of age had the highest fish consumption 

of local fish meals (22.1) (see Table 10-95). 

However, neither the overall nor pairwise differences 

by age among the Mohawk women over 34 years old 

were statistically significant, which may be due to the 

small sample size (N = 6) (Fitzgerald et al., 1995). 

The most common fish consumed by Mohawk 

mothers was yellow perch; for controls, the most 

common fish consumed was trout. 

An advantage of this study is that it presents data 

for fish consumption patterns for Native Americans 

as compared to a demographically similar group of 

Caucasians. Although the data are based on nursing 

mothers as participants, the study also captures 

consumption patterns prior to pregnancy (up to 1 year 

before and more than 1 year before). Fitzgerald et al. 

(1995) noted that dietary recall for a period more than 

1 year before pregnancy may be inaccurate, but these 

data were the best available measure of the more 

distant past. They also noted that the observed 

decrease in fish consumption among Mohawks from 

1 year before pregnancy to the period of pregnancy is 

due to a secular trend of declining fish consumption 

over time in Mohawks. This decrease, which was 

more pronounced than that seen in controls, may be 

due to health advisories promulgated by tribal, as 

well as state, officials. The authors noted that this 

decreasing secular trend in Mohawks is consistent 

with a survey from 1979–1980 that found an overall 

mean of 40 fish meals per year among male and 

female Mohawk adults. 

The data are presented as number of fish meals 

per year; the authors did not assign an average weight 

to fish meals. If assessors wanted to estimate the 

weight of fish consumed, some value of weight per 

fish meal would have to be assumed. 

Smiciklas-Wright et al. (2002) reported 209 grams as 

the 90th percentile weight of fish consumed per eating 

occasion for general population females 20–39 years 

old. Using this value, the rate reported of 27.6 fish 

meals per year for consumers only (over 1 year 

before pregnancy) translates into a mean fish intake 

rate of 15.8 g/day. 

A limitation of this study is that information on 

meal size was not available. It is not known whether 

the 90th percentile meal size from the general 

population is representative of the population of 

Mohawk women. 

10.6.5.	 Forti et al. (1995)—Health Risk 

Assessment for the Akwesasne Mohawk 

Population From Exposure to Chemical 

Contaminants in Fish and Wildlife 

Forti et al. (1995) estimated the potential 

exposure of residents of the Mohawk Nation at 

Akwesasne to PCBs through the ingestion of locally 

caught fish and wildlife, and human milk. The study 

was part of a remedial investigation/feasibility study 

(RI/FS) for a National Priorities List site near 

Massena, NY and the St. Lawrence River. Forti et al. 

(1995) used data collected in 1979–1980 on the 

source (store bought or locally caught), species, and 

frequency of fish consumption among 1,092 adult 

Mohawk Native Americans. The information on 

frequency of fish consumption was combined with an 

assumed meal size of 227 grams to estimate intake 

among the adult population. This meal size represents 

the 90th percentile meal size for fish consumers in the 

U.S. population as reported by Pao et al. (1982). 

Children were assumed to eat fish at the same 

frequency as adults but were assumed to have a meal 

size of 93 grams. 

Table 10-96 presents the mean and 95th percentile 

fish intake estimates for the Mohawk population, as 

reported by Forti et al. (1995). Mean intake of local 

fish was estimated to be 25 g/day for all adult fish 

consumers and 29 g/day for adult consumers only; 

95th percentile rates for these groups were 131 and 

135 g/day, respectively. Mean intake of local fish was 

estimated to be 10 g/day among all Mohawk children 

and 13 g/day among children consumers only; 

95th percentile estimates for these groups were 54 and 

58 g/day, respectively. 

The advantage of this study is that it provides 

additional perspective on intake among Native 

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Chapter 10—Intake of Fish and Shellfish 

American populations, especially those in the St. 

Lawrence River area. However, the fish intake survey 

data used in this analysis were collected more than 

3 decades ago and may not represent current intake 

patterns for this population. Also, the Forti et al. 

(1995) report provides limited details about the 

survey methodology and data used to estimate intake. 

It should also be noted that fish intake rates were 

estimated using a 90th percentile meal size. It is not 

known whether the 90th percentile meal size from the 

general population is representative of this population 

of Native Americans. 

10.6.6.	 Toy et al. (1996)—A Fish Consumption 

Survey of the Tulalip and Squaxin Island 

Tribes of the Puget Sound Region 

Toy et al. (1996) conducted a study to determine 

fish and shellfish consumption rates of the Tulalip 

and Squaxin Island tribes living in the Puget Sound 

region. These two Indian tribes were selected on the 

basis of judgment that they would be representative 

of the expected range of fishing and fish consumption 

activities of the 14 tribes in the region. Commercial 

fishing is a major source of income for members of 

both tribes; some members of the Squaxin Island 

tribe also participate in commercial shellfishing. Both 

tribes participate in subsistence fishing and 

shellfishing. 

A survey was conducted to describe fish 

consumption for Puget Sound tribal members over 

the age of 18 years, and their dependents, aged 

5 years and under, in terms of their consumption rate 

of anadromous, pelagic, bottom fish, and shellfish in 

grams per kilogram of body weight per day. The 

survey focused on the frequency of fish and shellfish 

consumption (number of fish meals eaten per day, per 

week, per month, or per year) over a 1-year period, 

and the portion size of each meal. Data were also 

collected on fish parts consumed, preparation 

methods, patterns of acquisition for all fish and 

shellfish consumption (including seasonal variations 

in consumption), and children’s consumption rates. 

Interviews were conducted between February 25 and 

May 15, 1994. A total of 190 tribal members, aged 

18 years old and older, and 69 children between birth 

and 5 years old, were surveyed on consumption of 

52 species. The response rate was 77% for the 

Squaxin Island tribe and 76% for the Tulalip tribes. 

The appropriate sample size was calculated based 

on the enrolled population of each tribe and a desired 

confidence interval of ±20% from the mean, with an 

additional 25% added to the total to allow for 

non-response or unusable data. The target population, 

derived from lists of enrolled tribal members 

provided by the tribes, consisted of enrolled tribal 

members aged 18 years and older and children aged 

5 years and younger living in the same household as 

an enrolled member. Only members living on or 

within 50 miles of the reservation were considered 

for the survey. Each eligible enrolled tribal member 

was assigned a number, and computer-generated 

random numbers were used to identify the survey 

participants. Children were not sampled directly but 

through adult members of their household; if one 

adult had more than one eligible child in his or her 

household, one of the children was selected at 

random. This indirect sampling method was 

necessitated by the available tribal records but may 

have introduced sampling bias to the process of 

selecting children for the study. A total of 190 adult 

tribal members (ages 18 years old and older) and 

69 children between birth and 5 years old (i.e., 0 to 

<6 years) were surveyed about their consumption of 

52 fish species in six categories: anadromous, 

pelagic, bottom, shellfish, canned tuna, and 

miscellaneous. 

Respondents described their consumption 

behavior for the past year in terms of frequency of 

fish meals eaten per week or per month, including 

seasonal variations in consumption rates. Portion 

sizes (in ounces) were estimated with the aid of 

model portions provided by the questioner. Data were 

also collected on fish parts consumed, preparation 

methods, patterns of acquisition for all fish and 

shellfish consumption, and children’s consumption 

rates. 

The adult mean and median consumption rates for 

all forms of fish combined were 0.89 and 

0.55 g/kg-day for the Tulalip tribes, and 0.89 and 

0.52 g/kg-day for the Squaxin Island tribe, 

respectively (see Table 10-97). As shown in Table 

10-98, consumption per body weight varied by sex 

(males consumed more as indicated by mean and 

median consumption). The median rates for the 

Tulalip Tribes were 53 g/day for males and 34 g/day 

for females, while the rates were 66 g/day for males 

and 25 g/day for females for the Squaxin Island tribe 

(see Table 10-99). Among adults, consumption 

generally followed a curvilinear pattern, with greater 

median consumption in the age range of 35 to 

64 years old, and lower consumption in the age range 

of 18 to 34 years old and 65 years old and over (see 

Table 10-100). No consistent pattern of consumption 

by income was found for either tribe (see Table 

10-101). 

The mean and median consumption rates for 

children 5 years and younger for both tribes 

combined, were 0.53 and 0.17 g/kg-day, respectively. 

These values were significantly lower than those of 

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Chapter 10—Intake of Fish and Shellfish 

adults, even when the consumption rate was adjusted 

for body weight (see Table 10-102). Squaxin Island 

children tended to consume more fish than Tulalip 

children (mean: 0.825 g/kg-day vs. 0.239 g/kg-day). 

The data were insufficient to allow re-analysis to fit 

the data to the standard U.S. EPA age categories used 

elsewhere in this handbook. A minority of consumers 

ate fish parts that are considered to have a higher 

concentration of toxins: skin, head, bones, eggs, and 

organs, and for the majority of consumers, fish were 

prepared (baking, boiling, broiling, roasting, and 

poaching) and eaten in a manner that tends to reduce 

intake of contaminants. Most anadromous fish and 

shellfish were obtained by harvesting in the Puget 

Sound area rather than by purchasing, though sources 

of harvesting varied between the tribes. 

The advantage of this study is that the data 

can be used to improve how exposure assessments 

are conducted for populations that include high 

consumers of fish and shellfish and to identify 

cultural characteristics that may place tribal members 

at disproportionate risk to chemical contamination. 

One limitation associated with this study is that 

although data from the Tulalip and Squaxin Island 

tribes may be representative of consumption rates of 

these specific tribes, fish consumption rates, habits, 

and patterns can vary among tribes and other 

population groups. As a result, the consumption rates 

of these two tribes may not be useful as a surrogate 

for consumption rates of other Native American 

tribes. There might also be a possible bias due to the 

time the survey was conducted; many species in the 

survey are seasonal, and although the survey was 

designed to solicit annual consumption rates, 

respondents may have weighted their responses 

toward the interview period. For example, because of 

the timing of the survey, respondents may have 

overestimated their annual consumption of shellfish 

and underestimated their annual consumption of 

salmon. Furthermore, there were differences in 

consumption patterns between the two tribes included 

in this study; the study provided data for each tribe 

and for the pooled data from both tribes, but the latter 

may not be a statistically valid measure for tribes in 

the region. 

10.6.7.	 Duncan (2000)—Fish Consumption 

Survey of the Suquamish Indian Tribe of 

the Port Madison Indian Reservation, 

Puget Sound Region 

The Suquamish Tribal Council conducted a study 

of the Suquamish tribal members living on and near 

the Port Madison Indian Reservation in the Puget 

Sound region (Duncan, 2000). The study was funded 

by the Agency for Toxic Substances and Disease 

Registry (ATSDR) through a grant to the Washington 

State Department of Health. The purpose of the study 

was to determine seafood consumption rates, 

patterns, and habits of the members of the Suquamish 

Tribe. The second objective was to identify cultural 

practices and attributes that affect consumption rates, 

patterns, and habits of members of the Suquamish 

Tribe. 

Adults, 16 years and older, were selected 

randomly from a Tribal enrollment roster. The study 

had a participation rate of 64.8%, which was 

calculated on the basis of 92 respondents out of a 

total of 142 potentially eligible adults on the list of 

those selected into the sample. Consumption data for 

children under 6 years of age were gathered through 

adult respondents who had children in this age group 

living in the household at the time of the survey. Data 

were collected for 31 children under 6 years old. 

A survey questionnaire was administered by 

personal interview. The survey included four parts: 

(1) 24-hour dietary recall; (2) identification, portions, 

frequency of consumption, preparation, harvest 

location of fish; (3) shellfish consumption, 

preparation, harvest location; and (4) changes in 

consumption over time, cultural information, physical 

information, and socioeconomic information. A 

display booklet was used to assist respondents in 

providing consumption data and identifying harvest 

locations of seafood consumed. Physical models of 

finfish and shellfish were constructed to assist 

respondents in determining typical food portions. 

Finfish and shellfish were grouped into categories 

based on similarities in life history as well as 

practices of Tribal members who fish for subsistence, 

ceremonial, and commercial purposes. 

Adult respondents reported a mean consumption 

rate of all finfish and all shellfish of 2.71 g/kg-day 

(see Table 10-103). Table 10-104, Table 10-105, and 

Table 10-106 provide consumption rates for adults by 

species, sex, and age, respectively. For children under 

6 years of age, the mean consumption rate of all 

finfish and shellfish was 1.48 g/kg-day (see Table 

10-107 and Table 10-108). The Suquamish Tribe's 

seafood consumption rates for adults and children 

under 6 years of age were higher than seafood 

consumption rates reported in studies conducted 

among the CRITFC, Tulalip Tribes, Squaxin Island 

Tribe, and the Asian Pacific Island population of 

King County (Duncan, 2000). This disparity 

illustrates the high degree of variability found 

between tribes even within a small geographic region 

(Puget Sound) and indicates that exposure and risk 

assessors should exercise care when imputing fish 

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Chapter 10—Intake of Fish and Shellfish 

consumption rates to a population of interest using 

data from tribal studies. 

An important attribute of this survey is that it 

provides consumption rates by individual type of fish 

and shellfish. It is important to note that the report 

indicates that increased levels of development as well 

as pollutants from residential, industrial, and 

commercial uses have resulted in degraded habitats 

and harvesting restrictions. Despite degraded water 

quality and habitat, tribal members continue to rely 

on fish and shellfish as a significant part of their diet. 

A limitation of this study is that the sample size for 

children was fairly small (31 children). 

10.6.8.	 Westat (2006)—Fish Consumption in 

Connecticut, Florida, Minnesota, and 

North Dakota 

As discussed in Section 10.3.2.7, Westat (2006) 

analyzed the raw data from three fish consumption 

studies to derive fish consumption rates for various 

age, sex, and ethnic groups, and according to the 

source of fish consumed (i.e., bought or caught) and 

habitat (i.e., freshwater, estuarine, or marine). The 

studies represented data from four states: 

Connecticut, Florida, Minnesota, and North Dakota. 

Consumption rates for individuals of Native 

American heritage were available for the states of 

Florida, Minnesota, and North Dakota. Fish intake 

distributions for these populations are presented in 

Table 10-41 for all respondents and Table 10-42 for 

consuming individuals. The mean and 95th percentile 

for all Native American respondents were 

0.8 g/kg-day and 4.5 g/kg-day for Florida, 

respectively. The mean fish intake rate for all Native 

American respondents for Minnesota was 

2.8 g/kg-day. The mean and 90th percentile fish intake 

rate for all Native American respondents for North 

Dakota were 0.4 g/kg-day and 0.9 g/kg-day, 

respectively. The mean and 95th percentile intake rate 

for Native American consumers only for Florida were 

1.5 g/kg-day and 5.7 g/kg-day, respectively. The 

mean fish intake rate for Native American consumers 

only for Minnesota was 2.8 g/kg-day. The mean and 

90th percentile fish intake rate for Native American 

consumers only for North Dakota were 0.4 g/kg-day 

and 0.8 g/kg-day, respectively (Westat, 2006). 

A limitation of this study is that sample sizes for 

these populations were small. Intake rates represent 

consumption of fish from all sources. Also, the study 

did not specifically target Native Americans, and it is 

not known whether the Native Americans included in 

the survey lived on reservations. 

10.6.9.	 Polissar et al. (2006)—A Fish 

Consumption Survey of the Tulalip and 

Squaxin Island Tribes of the Puget Sound 

Region—Consumption Rates for Fish 

Consumers Only 

Using fish consumption data from the Toy et al. 

(1996) survey of the Tulalip and Squaxin Island 

tribes of Puget Sound, Polissar et al. (2006) 

calculated consumption rates for various fish species 

groups, considering only the consumers of fish within 

each group. Weight-adjusted consumption rates were 

calculated by tribe, age, sex, and species groups. 

Species groups (anadromous, bottom, pelagic, and 

shellfish) were defined by life history and distribution 

in the water column. Data were available for 

69 children, birth to <6 years of age; 18 of these 

children had no reported fish consumption and were 

excluded from the analysis. Thus, estimated fish 

consumption rates are based on data for 51 children; 

15 from the Tulalip tribe and 36 from the Squaxin 

Island tribe. Both median and mean fish consumption 

rates for adults and children within each tribe were 

calculated in terms of grams per kilogram of body 

weight per day (g/kg-day). Anadromous fish and 

shellfish were the groups of fish most frequently 

consumed by both tribes and sexes. Consumption per 

body weight varied by sex (males consumed more) 

and age (those 35 to 64 years old consumed more 

than those younger and older). The consumption rates 

for groups of fish differed between the tribes. The 

distribution of consumption rates was skewed toward 

large values. In the Tulalip tribes, the estimated adult 

mean consumption rate for all forms of fish 

combined was 1.0 g/kg-day, and in the Squaxin 

Island tribe, the estimated mean rate was also 

1.0 g/kg-day (see Table 10-109). Table 10-110 

presents consumption rates for adults by species and 

sex. Table 10-111 and Table 10-112 show 

consumption rates for adults by species and age for 

the Squaxin Island and Tulalip tribes, respectively. 

The mean consumption rate for the Tulalip children 

was 0.45 g/kg-day, and 2.9 g/kg-day for the Squaxin 

Island children (see Table 10-113). Table 10-114 

presents consumption rates for children by species 

and sex. 

Because this study used the data originally 

generated by Toy et al. (1996), the advantages and 

limitations associated with the Toy et al. (1996) 

study, as described in Section 10.6.6, also apply to 

this study. However, an advantage of this study is that 

the consumption rates are based only on individuals 

who consumed fish within the selected categories. 

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Chapter 10—Intake of Fish and Shellfish 

10.7. OTHER POPULATION STUDIES 

10.7.1.	 U.S. EPA (1999)—Asian and Pacific 

Islander Seafood Consumption Study in 

King County, WA 

This study was conducted to obtain seafood 

consumption rates, species, and seafood parts 

consumed, and cooking methods used by the Asian 

and Pacific Islander (API) community. Participants 

were seafood consumers who were first or 

second generation members of the API ethnic group, 

18 years of age or older, and lived in King County, 

WA. APIs represent one of the most diverse and 

rapidly growing immigrant populations in the United 

States. In 1997, APIs (166,000) accounted for 10% of 

King County’s population, an increase from 8% in 

1990. Between 1990 and 1997, the total population of 

King Country increased by 9%, while the population 

of APIs increased by 43% (U.S. EPA, 1999). 

This study was conducted in three phases. Phase I 

focused on identifying target ethnic groups and 

developing appropriate questionnaires in the 

language required for each ethnic group. Phase II 

focused on characterizing seafood consumption 

patterns for 10 API ethnic groups (Cambodian, 

Chinese, Filipino, Hmong, Japanese, Korean, 

Laotian, Mien, Samoan, and Vietnamese) within the 

study area. Phase III focused on developing culturally 

appropriate health messages on risks related to 

seafood consumption and disseminating this 

information for the API community. The majority of 

the 202 respondents (89%) were first generation (i.e., 

born outside the United States). There were slightly 

more women (53%) than men (47%), and 35% lived 

under the 1997 Federal Poverty Level (FPL). 

In general, it was found that API members 

consumed seafood at a very high rate. As shown in 

Table 10-115, the mean overall consumption rate for 

all seafood combined was 1.9 g/kg body weight-day 

(g/kg-day), with a median consumption rate of 

1.4 g/kg-day. The predominant seafood consumed 

was shellfish (46% of all seafood). The API 

community consumed more shellfish (average 

consumption rate of 0.87 g/kg-day) than all finfish 

combined (an average consumption rate of 

0.82 g/kg-day). Within the category of finfish, 

pelagic fish were consumed most by the API 

members, mean consumption rate of 0.38 g/kg-day 

(median: 0.22 g/kg-day), followed by anadromous 

fish with a mean consumption rate of 0.20 g/kg-day 

(median: 0.09 g/kg-day). The mean consumption for 

freshwater fish was 0.11 g/kg-day (median: 

0.04 g/kg-day), and bottom fish was 0.13 g/kg-day 

(median: 0.05 g/kg-day). Individuals in the lowest 

income level (under the FPL) consumed more 

seafood than those in higher income levels (1–2, 2–3, 

and >3 times the FPL), but the difference was not 

statistically significant. 

In an effort to capture the participants consuming 

large quantities of seafood, the survey participants 

were classified as higher (N = 44) or lower (N = 158) 

consumers of shellfish or finfish based on their 

consumption rates being ≥75th (higher) or 

≤75th (lower) percentile. Table 10-116 shows that 

people in the >55-years-old-category had the greatest 

percentage for high consumers of finfish; they had 

approximately the same percentage as other age 

groups for shellfish. The Japanese had a greater 

percentage (52%) for higher finfish consumers, and 

Vietnamese (50%) were in the higher shellfish 

consumer category. 

Table 10-117 presents seafood consumption rates 

by ethnicity. In general, members of the Vietnamese 

and Japanese communities had the highest overall 

consumption rate, averaging 2.6 g/kg-day (median 

2.4 g/kg-day) and 2.2 g/kg-day (median 

1.8 g/kg day), respectively. 

Table 10-118 presents consumption rates by sex. 

The mean consumption rate for all seafood for 

women was 1.8 g/kg-day (median: 1.4 g/kg-day) and 

1.7 g/kg-day (median: 1.3 g/kg-day) for men. 

Salmon and tuna were the most frequently 

consumed finfish. More than 75% of the respondents 

consumed shrimp, crab, and squid. Table 10-119 

presents these data. For all survey participants, the 

head, bones, eggs, and other organs were consumed 

20% of the time. Fillet without skin was consumed 

45% of the time, and fillet with skin, 55% of the 

time. Consumption patterns of shellfish parts varied 

depending on the type of shellfish. 

Preparation methods were also surveyed in the 

API community. The survey covered two categories 

of preparation methods: (1) baked, broiled, roasted, 

or poached and (2) canned, fried, raw, smoked, or 

dried. The respondents most frequently prepared their 

finfish and shellfish using the baked, boiled, broiled, 

roasted, or poached method, averaging 65% and 

78%, respectively. 

The benefit of this research is that it can be used 

to improve API-specific risk assessments. API 

community members consume greater amounts of 

seafood than the general population, and these 

consumption patterns may pose a health risk if the 

consumed seafood is contaminated with toxic 

chemicals. Because the survey was based on recall, 

the authors selected 20 respondents for a follow-up 

re-interview. Its purpose was to assess the reliability 

of the responses. The results of the re-interview 

suggest that, based on the difference in means 

between the original and re-interview responses, the 

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Chapter 10—Intake of Fish and Shellfish 

estimated consumption rates from this study are 

reliable. One limitation associated with this study is 

that it is based on a relatively small number of 

respondents within each ethnic group. Caution should 

be used to avoid extrapolation of data to other ethnic 

groups that have potentially significant cultural 

differences. Further study of the consumption 

patterns and preparation methods for the Hmong, 

Laotian, Mien, and Vietnamese communities is also 

needed because of potential health risks from 

contaminated seafood. 

10.7.2	 Shilling et al. (2010)—Contaminated Fish 

Consumption in California’s Central 

Valley Delta 

Shilling et al. (2010) conducted a survey of 

373 anglers and 137 community members between 

September 2005 and June 2008, in a region of the 

Sacramento-San Joaquin River Delta where 

subsistence fishing rates are high. This area was also 

chosen as an area where mercury concentrations in 

fish tissues were likely to be high. Anglers were 

selected for interviews as they were encountered in 

order to reduce bias, however, approximately 5% of 

the anglers approached did not speak English and 

were unable to be interviewed. Community members 

were chosen for interviews based on knowledge that 

an extended family member fished in this area. The 

interviews were conducted primarily in the early 

morning and late afternoon, and all days of the week 

were represented. Subjects were told at the beginning 

of the interview that the study was about fishing 

activity along the river, but not that it was related to 

fish contamination. Anglers and community members 

were grouped according to ethnicity, and fish 

consumption rates were calculated based on each 

individual’s 30-day recall of how much and how 

often types of fish were eaten. Mean, median and 

95th percentile fish consumption rates were calculated 

for study participants according to ethnicity, age, and 

sex. In addition, fish intake was determined for 

households containing women of child-bearing age, 

children, and for respondents whose awareness of 

warnings about fish contamination in the area ranged 

from no awareness to high awareness. 

Regardless of ethnicity, the fish species that were 

primarily targeted by anglers in this study were 

striped bass, salmon, shad, and catfish, similar to 

those identified in creel survey data for this region 

from the California Department of Fish and Game. 

Consumption rates for locally caught and 

commercially obtained fish are shown in Table 

10-120. Mean intake of locally caught fish among all 

ethnic groups ranged from 6.5 g/day for Native 

American anglers to 57.6 g/day for Southeast 

Asian/Lao anglers. For all anglers, the mean and 

median consumption rates of locally caught fish were 

27.4 and 19.7 g/day, respectively. These values 

increased to 40.6 g/day (mean) and 26.1 g/day 

(median) when commercially obtained fish were 

included. The 95th percentile intake rates for all 

anglers were 126.6 g/day for local fish consumption 

and 147.3 g/day for total fish consumption. Fish 

consumption rates were not significantly different 

among age groups, but were higher for anglers from 

households with either children or women of 

child-bearing age. 

No significant trend (p = 0.78) was observed 

across the 3-year study period for the consumption of 

locally caught fish. Peak consumption rates occurred 

during the fall, when striped bass and salmon return 

to the area to spawn and fishing activity is the 

highest. Fish consumption rates were significantly 

different for anglers and community members, with 

the exception of Southeast Asians. No significant 

difference was observed between the day of the week 

when surveying was conducted and ethnic group or 

fish consumption rates, or between anglers with 

higher or lower awareness of warnings about fish 

contamination in the area. 

The advantages of this study are that the sample 

size was fairly large and that a number of ethnic 

groups were included. Limitations of the study 

include the fact that information on fish consumption 

was based on 30-day recall data and that the study 

was limited to one geographic area and may not be 

representative of the U.S. general population. 

10.8. SERVING SIZE STUDIES 

10.8.1.	 Pao et al. (1982)—Foods Commonly 

Eaten in the United States: Amount per 

Day and per Eating Occasion 

Pao et al. (1982) used the 1977–1978 NFCS to 

examine the quantity of fish consumed per eating 

occasion. For each individual consuming fish in the 

3-day survey period, the quantity of fish consumed 

per eating occasion was derived by dividing the total 

reported fish intake over the 3-day period by the 

number of occasions the individual reported eating 

fish. Table 10-121 displays the distributions, by age 

and sex, for the quantity of fish consumed per eating 

occasion (Pao et al., 1982). For the general 

population, the average quantity of fish consumed per 

fish meal was 117 grams, with a 95th percentile of 

284 grams. Males in the age groups 19–34, 35–64, 

and 65–74 years had the highest average and 

95th percentile quantities among the age-sex groups 

presented. It should be noted that the serving size 

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Chapter 10—Intake of Fish and Shellfish 

data from this analysis has been superseded by the 

analysis of the 1994–1996 USDA CSFII data 

conducted by Smiciklas-Wright et al. (2002). 

10.8.2.	 Smiciklas-Wright et al. (2002)—Foods 

Commonly Eaten in the United States: 

Quantities Consumed per Eating 

Occasion and in a Day, 1994–1996 

Using data gathered in the 1994–1996 USDA 

CSFII, Smiciklas-Wright et al. (2002) calculated 

distributions for the quantities of canned tuna and 

other finfish consumed per eating occasion by 

members of the U.S. population (i.e., serving sizes), 

over a 2-day period. The estimates of serving size are 

based on data obtained from 14,262 respondents, 

ages 2 years and above, who provided 2 days of 

dietary intake information. Only dietary intake data 

from users of the specified food were used in the 

analysis (i.e., consumer-only data). 

Table 10-122 and Table 10-123 present serving 

size data for canned tuna and other finfish, 

respectively. These data are presented on an 

as-consumed basis (grams) and represent the quantity 

of fish consumed per eating occasion. These 

estimates may be useful for assessing acute exposures 

to contaminants in specific foods, or other 

assessments where the amount consumed per eating 

occasion is necessary. The average meal size for 

finfish (other than tuna) for adults 20 years and older 

was 114 g/meal (see Table 10-122). It should be 

noted that this value represents fish eaten in any form 

(e.g., as an ingredient in a meal) and not just fish 

eaten as a meal (e.g., fish fillet). 

The advantages of using these data are that they 

were derived from the USDA CSFII and are 

representative of the U.S. population. The analysis 

conducted by Smiciklas-Wright et al. (2002) 

accounted for individual foods consumed as 

ingredients of mixed foods. Mixed foods were 

disaggregated via recipe files so that the individual 

ingredients could be grouped together with similar 

foods that were reported separately. Thus, weights of 

foods consumed as ingredients were combined with 

weights of foods reported separately to provide a 

more thorough representation of consumption. 

However, it should be noted that because the recipes 

for the mixed foods consumed by respondents were 

not provided by the respondents, standard recipes 

were used. As a result, the estimates of the quantity 

of some food types are based on assumptions about 

the types and quantities of ingredients consumed as 

part of mixed foods. 

10.9. OTHER FACTORS TO CONSIDER FOR 

FISH CONSUMPTION 

Other factors to consider when using the available 

survey data include location, climate, season, and 

ethnicity of the angler or consumer population, as 

well as the parts of fish consumed and the methods of 

preparation. Some contaminants (for example, 

persistent, bioaccumulative, and toxic contaminants 

such as dioxins and polychlorinated biphenyls) have 

the affinity to accumulate more in certain tissues, 

such as the fatty tissue, as well as in certain internal 

organs. The effects of cooking methods for various 

food products on the levels of dioxin-like compounds 

have been addressed by evaluating a number of 

studies in U.S. EPA (2003). These studies showed 

various results for contamination losses based on the 

methodology of the study and the method of food 

preparation. Refer to U.S. EPA (2003) for a detailed 

review of these studies. 

In addition, some studies suggest that there is a 

significant decrease of contaminants in cooked fish 

when compared with raw fish (San Diego County, 

1990). Several studies cited in this section have 

addressed fish preparation methods and parts of fish 

consumed. Table 10-124 provides summary results 

from these studies on fish preparation methods; 

Appendix 10B presents further details on preparation 

methods, as well as results from some studies on 

parts of fish consumed. 

Users of the data presented in this chapter should 

ensure that consistent units are used for intake rate 

and concentration of contaminants in fish. The 

following sections provide information on converting 

between wet weight and dry weight, and between wet 

weight and lipid weight. 

10.9.1.	 Conversion Between Wet and Dry Weight 

The intake data presented in this chapter are 

reported in units of wet weight (i.e., as-consumed or 

uncooked weight of fish consumed per day or per 

eating occasion). However, data on the concentration 

of contaminants in fish may be reported in units of 

either wet or dry weight (e.g., milligram of 

contaminant per gram-dry-weight of fish). It is 

essential that exposure assessors be aware of this 

difference so that they may ensure consistency 

between the units used for intake rates and those used 

for concentration data (i.e., if the contaminant 

concentration is measured in dry weight of fish, then 

the dry-weight units should be used for fish intake 

values). 

If necessary, wet-weight (e.g., as-consumed) 

intake rates may be converted to dry-weight intake 

rates using the moisture content percentages 

Page Exposure Factors Handbook 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

presented in Table 10-125 and the following 

equation: 

IRdw = IR ww 



 



 −

100 

100 W (Eqn. 10-4) 

where: 

IRdw = dry-weight intake rate, 

IRww = wet-weight intake rate, and 

W = percent water content. 

Alternately, dry-weight residue levels in fish may 

be converted to wet-weight residue levels for use 

with wet-weight (e.g., as-consumed) intake rates, as 

follows: 

C 100 −W  ww = Cdw (Eqn. 10-5) 

 100 

where: 

Cww = wet-weight concentration, 

Cdw = dry-weight concentration, and 

W = percent water content. 

The moisture content data presented in Table 

10-125 are for selected fish taken from USDA 

(2007). The moisture content is based on the percent 

of water present. 

10.9.2.	 Conversion Between Wet-Weight and 

Lipid-Weight Intake Rates 

In some cases, the residue levels of contaminants 

in fish are reported as the concentration of 

contaminant per gram of fat. This may be particularly 

true for lipophilic compounds. When using these 

residue levels, the assessor should ensure consistency 

in the exposure-assessment calculations by using 

consumption rates that are based on the amount of fat 

consumed for the fish product of interest. 

The total fat content (percent) measured and/or 

calculated in various fish forms (i.e., raw, cooked, 

smoked, etc.) for selected fish species is presented in 

Table 10-125, based on data from USDA (2007). The 

total percent fat content is based on the sum of 

saturated, monounsaturated, and polyunsaturated fat. 

If necessary, wet-weight (e.g., as-consumed) 

intake rates may be converted to lipid-weight intake 

rates using the fat content percentages presented in 

Table 10-125 and the following equation: 

 L  IRlw = IR ww (Eqn. 10-6) 

100

where: 

IRlw = lipid-weight intake rate, 

IRww = wet-weight intake rate, and 

L = percent lipid (fat) content. 

Alternately, wet-weight residue levels in fish may 

be estimated by multiplying the levels based on fat by 

the fraction of fat per product as follows: 

C  L  ww = Clw (Eqn. 10-7) 

100

where: 

Cww = wet-weight concentration,
 

Clw = lipid-weight concentration, and
 

L = percent lipid (fat) content.
 

The resulting residue levels may then be used in 

conjunction with wet-weight (e.g., as-consumed) 

consumption rates. The total fat content data 

presented in Table 10-125 are for selected fish taken 

from USDA (2007). 

10.10. REFERENCES FOR CHAPTER 10 

ADEM (Alabama Department of Environmental 

Management). (1994). Estimation of daily 

per capita freshwater fish consumption of 

Alabama anglers. Montgomery, AL. 

Alcoa (Aluminum Corporation of America). (1998). 

Draft report for the finfish/shellfish 

consumption study Alcoa (Point 

Comfort)/Lavaca Bay Superfund Site, 

Volume B7b: Bay System Investigation 

Phase 2. Point Comfort, TX: Aluminum 

Company of America. 

Balcom, N; Capacchione, C; DW, H. (1999). 

Quantification of seafood consumption rates 

for Connecticut. (Contract No. CWF-332­

R). Hartford, CT: Connecticut Department 

of Environmental Protection, Office of Long 

Island Sound Programs. 

Exposure Factors Handbook Page
 

September 2011 10-57 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Benson, S; Crocker, C; Erjavec, J; Jensen, RR; 

Nyberg, CM; Wixo, CY; Zola, JM. (2001). 

Fish consumption survey: Minnesota and 

North Dakota. Washington, DC: U.S. 

Department of Energy. 

Burger, J. (2000). Gender differences in meal 

patterns: role of self-caught fish and wild 

game in meat and fish diets. Environ Res 83: 

140-149. 

http://dx.doi.org/10.1006/enrs.2000.4060. 

Burger, J. (2002a). Consumption patterns and why 

people fish. Environ Res 90: 125-135. 

Burger, J. (2002b). Daily consumption of wild fish 

and game: Exposures of high end 

recreationists. Int J Environ Health Res 12: 

343-354. 

http://dx.doi.org/10.1080/096031202100005 

6393. 

Burger, J; Cooper, K; Gochfeld, M. (1992). Exposure 

assessment for heavy metal ingestion from a 

sport fish in Puerto Rico: estimating risk for 

local fishermen. J Toxicol Environ Health 

36: 36:355-365. 

Burger, J; Gochfeld, M. (1991). Fishing a superfund 

site: Dissonance and risk perception of 

environmental hazards by fishermen in 

Puerto Rico. Risk Anal 11: 269-277. 

Burger, J; Sanchez, J; Gochfeld, M. (1998). Fishing, 

consumption, and risk perception in 

fisherfolk along an east coast estuary. 

Environ Res 77: 25-35. 

http://dx.doi.org/10.1006/enrs.1997.3819. 

Burger, J; Stephens, WL; Boring, CS; Kuklinski, M; 

Gibbons, JW; Gochfeld, M. (1999). Factors 

in exposure assessment: ethnic and 

socioeconomic differences in fishing and 

consumption of fish caught along the 

Savannah River. Risk Anal 19: 427-438. 

ChemRisk. (1992). Consumption of freshwater fish 

by Maine anglers. ChemRisk, a division of 

Mclaren/Hart. 

Chiang, A. (1998). A seafood consumption survey of 

the Laotian community of West Contra 

Costa County, CA. Oakland, CA: Asian 

Pacific Environmental Network. 

Connelly, NA; Knuth, BA; Bisogni, CA. (1992). 

Effects of the health advisory and advisory 

changes on fishing habits and fish 

consumption in New York sport fisheries. 

(Report for the New York Sea Grant Institute 

Project No. R/FHD-2-PD.). Ithaca, NY: 

Cornell University. 

Connelly, NA; Knuth, BA; Brown, TL. (1996). 

Sportfish consumption patterns of Lake 

Ontario anglers and the relationship to 

health advisories. North American Journal of 

Fisheries Management 16: 90-101. 

CRITFC (Columbia River Inter-Tribal Fish 

Commission). (1994). A fish consumption 

survey of the Umatilla, Nez Perce, Yakama, 

and Warm Springs Tribes of the Columbia 

River Basin. 

Degner, RL; Adams, CM; Moss, SD; Mack, SK. 

(1994). Per capita fish and shellfish 

consumption in Florida. Gainesville, FL: 

University of Florida. 

Donatuto, J; Harper, BL. (2008). Issues in evaluating 

fish consumption rates for Native American 

tribes. 28: 1497-1506. 

http://dx.doi.org/10.1111/j.1539­

6924.2008.01113.x. 

Duncan, M. (2000). Fish consumption survey of the 

Suquamish Indian Tribe of the Port Madison 

Indian Reservation, Puget Sound Region. 

Suquamish, WA: The Suquamish Tribe, Port 

Madison Indian Reservation. 

http://www.deq.state.or.us/wq/standards/doc 

s/toxics/suquamish2000report.pdf. 

Ebert, ES; Harrington, NW; Boyle, KJ; Knight, JW; 

Keenan, RE. (1993). Estimating 

consumption of freshwater fish among 

Maine anglers. North American Journal of 

Fisheries Management 13: 737-745. 

FASEB/LSRO (Federation of American Societies for 

Experimental Biology, Life Sciences 

Research Office). (1995). Third report on 

nutrition monitoring in the United States: 

Volume 1. Washington, DC: Interagency 

Board for Nutrition Monitoring and Related 

Research. 

Fiore, BJ; Anderson, HA; Hanrahan, LP; Olson, LJ; 

Sonzogni, WC. (1989). Sport fish 

consumption and body burden levels of 

chlorinated hydrocarbons: A study of 

Wisconsin anglers. Arch Environ Health 44: 

82-88. 

Fitzgerald, EF; Hwang, SA; Brix, KA; Bush, B; 

Cook, K; Worswick, P. (1995). Fish PCB 

concentrations and consumption patterns 

among Mohawk women at Akwesasne. J 

Expo Anal Environ Epidemiol 5: 1-19. 

Florida State Department of Health and 

Rehabilitative Services. (1995). Health study 

to assess the human health effects of 

mercury exposure to fish consumed from the 

Everglades: Final report. 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB95167276. 

Forti, A; Bogdan, KG; Horn, E. (1995). Health risk 

assessment for the Akwesasne Mohawk 

Page Exposure Factors Handbook 

10-58 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

population from exposure to chemical 

contaminants in fish and wildlife. Massena, 

NY: New York State Dept. of Health, Center 

for Environmental Health, Bureau of Toxic 

Substance Assessment. 

Harper, BL; Harris, SG. (2008). A possible approach 

for setting a mercury risk-based action level 

based on tribal fish ingestion rates. Environ 

Res 107: 60-68. 

http://dx.doi.org/10.1016/j.envres.2007.05.0 

08. 

Hudson River Sloop Clearwater, Inc., . (1993). 

Hudson River angler survey. Poughkeepsie, 

NY. 

KCA Research Division. (1994). Fish consumption 

pattern of Delaware recreational fishermen 

and their households. Dover, DE: Delaware 

Department of Natural Resources. 

Mahaffey, KR; Clickner, RP; Jeffries, RA. (2009). 

Adult women's blood mercury 

concentrations vary regionally in the United 

States: Association with patterns of fish 

consumption (NHANES 1999-2004). 

Environ Health Perspect 117: 47-53. 

http://dx.doi.org/10.1289/ehp.11674. 

Mayfield, DB; Robinson, S; Simmonds, J. (2007). 

Survey of fish consumption patterns of King 

County (Washington) recreational anglers. J 

Expo Sci Environ Epidemiol 17: 604-612. 

http://dx.doi.org/10.1038/sj.jes.7500559. 

Moya, J; Itkin, C; Selevan, SG; Rogers, JW; 

Clickner, RP. (2008). Estimates of fish 

consumption rates for consumers of bought 

and self-caught fish in Connecticut, Florida, 

Minnesota, and North Dakota. Sci Total 

Environ 403: 89-98. 

http://dx.doi.org/10.1016/j.scitotenv.2008.05 

.023. 

Moya, J; Phillips, L. (2001). Analysis of consumption 

of home-produced foods. J Expo Anal 

Environ Epidemiol 11: 398-406. 

http://dx.doi.org/10.1038/sj.jea.7500181. 

NCHS (National Center for Health Statistics). (1993). 

Joint policy on variance estimation and 

statistical reporting standards on NHANES 

III and CSFII reports: HNIS/NCHS Analytic 

Working Group recommendations. 

Riverdale, MD: Human Nutrition 

Information Service (HNIS)/Analytic 

Working Group. Agricultural Research 

Service, Survey Systems/Food Consumption 

Laboratory. 

NMFS (National Marine Fisheries Service). (1986a). 

Fisheries of the United States, 1985. Current 

Fisheries Statistics No. 8368. Washington, 

DC: National Oceanic and Atmospheric 

Administration, National Environmental 

Satellite, Data and Information Service. 

NMFS (National Marine Fisheries Service). (1986b). 

Marine Recreational Fishery Statistics 

Survey, Atlantic and Gulf Coasts, 1985. 

Current Fisheries Statistics No. 8327. 

Washington, DC: National Oceanic and 

Atmospheric Administration, National 

Environmental Satellite, Data and 

Information Service. 

NMFS (National Marine Fisheries Service). (1986c). 

Marine Recreational Fishery Statistics 

Survey, Pacific Coast. Current Fisheries 

Statistics No. 8328. Washington, DC: 

National Oceanic and Atmospheric 

Administration, National Environmental 

Satellite, Data and Information Service. 

NMFS (National Marine Fisheries Service). (1993). 

Data tapes for the 1993 NMFS provided to 

U.S. EPA. Washington, DC: U.S. 

Environmental Protection Agency.
 

Pao, EM; Fleming, KH; Guenther, PM; Mickle, SJ. 

(1982). Foods commonly eaten by 

individuals: Amount per day and per eating 

occasion. (Home Economic Report No. 44). 

Washington, DC: U.S. Department of 

Agriculture. 

Peterson, DE; Kanarek, MS; Kuykendall, MA; 

Diedrich, JM; Anderson, HA; Remington, 

PL; Sheffy, TB. (1994). Fish consumption 

patterns and blood mercury levels in 

Wisconsin Chippewa Indians. Arch Environ 

Health 49: 53-58. 

http://dx.doi.org/10.1080/00039896.1994.99 

34415. 

Pierce, D; Noviello, DT; Rogers, SH. (1981). 

Commencement Bay seafood consumption 

study: preliminary report. 

Polissar, NL; Neradilek, B; Liao, S; Toy, KA; 

Mittelstaedt, GD. (2006). A fish 

consumption survey of the Tulalip and 

Squaxin Island tribes of the Puget Sound 

region – Consumption rates for fish 

consumers only. Seattle, WA: MountainWhisper-Light Statistical Consulting. 

Price, P; Su, S; Gray, M. (1994). The effects of 

sampling bias on estimates of angler 

consumption rates in creel surveys. J Expo 

Anal Environ Epidemiol 4: 355-371. 

Puffer, HW; Azen, SP; Duda, MJ; Young, DR. 

(1982). Consumption rates of potentially 

hazardous marine fish caught in the 

metropolitan Los Angeles area. (EPA-600/3­

82-070). Los Angeles: University of 

Exposure Factors Handbook Page
 

September 2011 10-59 
 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Southern California. 

Rouse Campbell, K; Dickey, RJ; Sexton, R; Burger, 

J. (2002). Fishing along the Clinch River 

arm of Watts Bar reservoir adjacent to the 

Oak Ridge Reservation, Tennessee: 

behavior, knowledge and risk perception. 

Sci Total Environ 299: 145-161. 

Ruffle, B; Burmaster, DE; Anderson, PD; Gordon, 

HD. (1994). Lognormal distributions for fish 

consumption by the general US population. 

Risk Anal 14: 395-404. 

Rupp, EM; Miller, FI; Baes, CF. (1980). Some results 

of recent surveys of fish and shellfish 

consumption by age and region of U.S. 

residents. Health Phys 39: 165-175. 

San Diego County. (1990). San Diego Bay health risk 

study. San Diego, CA: San Diego County 

Department of Health Services. 

SFEI (San Francisco Estuary Institute). (2000). San 

Francisco Bay seafood consumption report. 

Richmond, CA. 

http://www.sfei.org/node/2022. 

Shilling, F; White, A; Lippert, L; Lubell, M. (2010). 

Contaminated fish consumption in 

California's Central Valley Delta. Environ 

Res 110: 334-344. 

http://dx.doi.org/10.1016/j.envres.2010.02.0 

02. 

SMBRP (Santa Monica Bay Restoration Project). 

(1995). Seafood consumption habits of 

recreational anglers in Santa Monica Bay. In 

Southern California Coastal Water Research 

Project 1993-94 annual report (pp. 55-62). 

Westminster, CA: Southern California 

Coastal Water Research Project. 

ftp://ftp.sccwrp.org/pub/download/DOCUM 

ENTS/AnnualReports/1993_94AnnualRepor 

t/ar07.pdf. 

Smiciklas-Wright, H; Mitchell, DC; Mickle, SJ; 

Cook, AJ; Goldman, JD. (2002). Foods 

commonly eaten in the United States: 

Quantities consumed per eating occasion 

and in a day, 1994−96 [pre-publication 

version]. (NFS Report No. 96-5). Beltsville, 

MD: U.S. Department of Agriculture. 

http://www.ars.usda.gov/sp2userfiles/place/1 

2355000/pdf/portion.pdf. 

SRI (SRI Consulting). (1980). Seafood consumption 

data analysis [EPA Report]. Washington, 

DC: U.S. Environmental Protection Agency. 

Stern, AH; Korn, LR; Ruppel, BE. (1996). Estimation 

of fish consumption and methylmercury 

intake in the New Jersey population. J Expo 

Anal Environ Epidemiol 6: 503-525. 

Toy, KA; Polissar, NL; Liao, S; Mittelstaedt, GD. 

(1996). A fish consumption survey of the 

Tulalip and Squaxin Island tribes of the 

Puget Sound region. Marysville, WA: 

Tulalip Tribes, Department of Environment. 

http://www.deq.state.or.us/wq/standards/doc 

s/toxics/tulalipsquaxin1996.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1984). Ambient water quality criteria for 2, 

3, 7, 8 - Tetrachloro-dibenzo - p - dioxin. 

(EPA-440/5-84-007). 

U.S. EPA (U.S. Environmental Protection Agency). 

(1995). Fish consumption estimates based 

on the 1991-1992 Michigan sport anglers 

fish consumption study: Final report. 

Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1996). Descriptive statistics from a detailed 

analysis of the National Human Activity 

Pattern Survey (NHAPS) responses. 

(EPA/600/R-96/148). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1998). Guidance for conducting fish and 

wildlife consumption surveys. (EPA-823­

B/98/007). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1999). Asian and Pacific Islander seafood 

consumption study in King County, WA. 

(EPA/910/R-99-003). Seattle, WA. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2002). Estimated per capita fish 

consumption in the United States. 

(EPA/821/C-02/003). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2003). Exposure and human health 

reassessment of 2,3,7,8 tetrachlorodibenzo-p 

dioxin (TCDD) and related compounds 

[NAS review draft]. (EPA/600/P-00/001). 

Washington, DC: U.S. Environmental 

Protection Agency, National Center for 

Environmental Assessment. 

http://www.epa.gov/nceawww1/pdfs/dioxin/ 

nas-review/. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum. 

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

USDA (U.S. Department of Agriculture). (1992). 

Changes in food consumption and 

expenditures in American households during 

the 1980s. Statistical Bulletin No. 849. 

Page Exposure Factors Handbook 

10-60 September 2011 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Washington, DC. 

USDA (U.S. Department of Agriculture). (1993). 

Food and nutrient intakes by individuals in 

the United States, 1 day, 1987–88. 

Nationwide Food Consumption Survey 

1987-88: Report no. 87-I-1. (87-I-1). 

Washington, DC. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/8788/nfcs8788_rep_87-i1.pdf. 

USDA (U.S. Department of Agriculture). (2000). 

1994-1996, 1998 continuing survey of food 

intakes by individuals (CSFII). Beltsville, 

MD: Agricultural Research Service, 

Beltsville Human Nutrition Research Center. 

USDA (U.S. Department of Agriculture). (2007). 

USDA nutrient database for standard 

reference, release 20. Riverdale, MD. 

http://www.ars.usda.gov/main/site_main.htm 

?modecode=12-35-45-00. 

West, PC; Fly, JM; Marans, R; Larkin, F. (1989). 

1991-1992 Michigan sport anglers fish 

consumption study. Ann Arbor, MI: 

Michigan Department of Natural Resources. 

West, PC; Fly, JM; Marans, R; Larkin, F; Rosenblatt, 

D. (1993). 1991-1992 Michigan sport 

anglers fish consumption study. Ann Arbor, 

MI: Michigan Department of Natural 

Resources. 

Westat. (2006). Fish consumption in Connecticut, 

Florida, Minnesota, and North Dakota. 

Rockville, MD. 

Williams, R; O’Leary, J; Sheaffer, A; Mason, D. 

(1999). Consumption of Indiana sport 

caught fish: Mail survey of resident license 

holders. (Technical Report 99-D-HDFW-1). 

West Lafayette, IN: Indiana Department of 

Forestry and Natural Resources. 

Williams, R; O’Leary, J; Sheaffer, A; Mason, D. 

(2000). An examination of fish consumption 

by Indiana recreational anglers: An onsite 

survey. (Technical Report 99-D-HDFW-2). 

West Lafayette, IN: Indiana Department of 

Forestry and Natural Resources. 

Wolfe, RJ; Walker, RJ. (1987). Subsistence 

economies in Alaska: productivity, 

geography, and development impacts. Arctic 

Anthropology56-81. 

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Table 10-7. Per Capita Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight 

Percentiles 

% Lower Upper 

1st 5th 10th 25th 50th 75th 90th 95th 99th Population Group N Consuming Mean SE 95% CL 95%CL Min Max 

Whole Population 16,783 23 0.16 0.01 0.14 0.18 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.6 1.1 2.3 13.4b 

Age Group (years) 

0 to 1 865 2.6 0.03 0.01 0.01 0.06 0.0b 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.0b 1.5b 3.7b 

1 to 2 1,052 14 0.22 0.05 0.12 0.32 0.0b 0.0b 0.0b 0.0 0.0 0.0 0.0 0.5 1.2b 4.3b 13.4b 

3 to 5 978 15 0.19 0.03 0.13 0.25 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.7 1.4 2.7b 7.0b 

6 to 12 2,256 15 0.16 0.04 0.08 0.24 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.5 1.1 2.6b 6.7b 

13 to 19 3,450 15 0.10 0.01 0.08 0.11 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.7 1.7 6.9b 

20 to 49 4,289 23 0.15 0.01 0.13 0.17 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.0 2.2 8.5b 

Females 13 to 49 4,103 22 0.14 0.01 0.11 0.16 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.9 1.8 8.5b 

50+ 3,893 29 0.20 0.02 0.16 0.23 0.0b 0.0 0.0 0.0 0.0 0.0 0.1 0.7 1.2 2.4 6.1b 

Race 

Mexican American 4,450 16 0.15 0.02 0.11 0.18 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.1 2.6 8.5b 

Non-Hispanic Black 4,265 24 0.18 0.02 0.15 0.22 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.6 1.1 2.4 8.8b 

Non-Hispanic White 6,757 22 0.15 0.01 0.13 0.17 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.0 2.0 13.4b 

Other Hispanic 562 22 0.18 0.03 0.11 0.24 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.5 1.0 2.7b 7.3b 

Other a 749 33 0.31 0.05 0.20 0.42 0.0b 0.0b 0.0 0.0 0.0 0.0 0.2 1.1 2.0 4.0b 6.5b 

a Other: Other Race - including Multiple Races. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III 

and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

N = Sample size.
 

SE = Standard error.
 

CL = Confidence limit.
 

Min = Minimum value.
 

Max = Maximum value.
 

Source: U.S. EPA analysis of NHANES 2003–2006.
 

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Table 10-8. Consumer-Only Intake of Finfish (g/kg-day), Edible Portion, Uncooked Fish Weight 

Lower Upper Percentiles 

1st 5th Population Group N Mean SE 95%CL 95% CL Min 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 3,204 0.73 0.03 0.67 0.78 0.0b 0.0 0.0 0.0 0.2 0.5 1.0 1.6 2.2 4.0 13.4b 

Age Group (years) 

0 to 1 22 1.31 0.31 0.68 1.94 0.1b 0.1b 0.2b 0.2b 0.4b 0.8b 2.0b 2.8b 2.9b 3.7b 3.7b 

1 to 2 143 1.61 0.27 1.06 2.16 0.0b 0.0b 0.1b 0.2b 0.5b 0.8b 1.7b 3.6b 4.9b 13.4b 13.4b 

3 to 5 156 1.28 0.13 1.01 1.55 0.0b 0.0b 0.0b 0.2b 0.5 1.0 1.7 2.7b 3.6b 5.6b 7.0b 

6 to 12 333 1.05 0.12 0.81 1.29 0.0b 0.0b 0.0b 0.1b 0.3 0.7 1.4 2.1b 2.9b 6.5b 6.7b 

13 to 19 501 0.66 0.03 0.59 0.73 0.0b 0.0b 0.0 0.0 0.2 0.5 0.9 1.4 1.7 2.6b 6.9b 

20 to 49 961 0.65 0.02 0.60 0.70 0.0b 0.0b 0.0 0.0 0.2 0.4 0.9 1.5 2.1 3.9b 8.5b 

Females 13 to 49 793 0.62 0.04 0.54 0.69 0.0b 0.0 0.0 0.0 0.1 0.4 0.9 1.4 1.8 2.9 8.5b 

50+ 1,088 0.68 0.04 0.61 0.76 0.0b 0.0b 0.0 0.0 0.2 0.5 0.9 1.5 2.0 3.2b 6.1b 

Race 0.0b 

Mexican American 584 0.93 0.04 0.84 1.03 0.0b 0.0b 0.0 0.0 0.3 0.7 1.3 1.9 2.8 4.7b 8.5b 

Non-Hispanic Black 906 0.77 0.05 0.66 0.88 0.0b 0.0 0.0 0.1 0.2 0.5 1.0 1.7 2.1 4.9 8.8b 

Non-Hispanic White 1,405 0.67 0.03 0.62 0.72 0.0b 0.0b 0.0 0.0 0.2 0.5 0.9 1.5 1.9 3.2b 13.4b 

Other Hispanic 101 0.82 0.10 0.61 1.03 0.0b 0.0b 0.0b 0.1b 0.3 0.5 1.0 2.0b 2.7b 4.9b 7.3b 

Other a 208 0.96 0.14 0.68 1.23 0.0b 0.0b 0.0b 0.0 0.2 0.5 1.3 2.2 3.6b 5.3b 6.5b 

a Other: Other Race - including Multiple Races. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on 

NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

N = Sample size.
 

SE = Standard error.
 

CL = Confidence limit.
 

Min = Minimum value.
 

Max = Maximum value.
 

Source: U.S. EPA analysis of NHANES 2003–2006. 

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Exposure Factors Handbook Page September 2011 10-63 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-9. Per Capita Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight 

Percentiles 

% Lower Upper 

1st 5th 10th 25th 50th 75th 90th 95th 99th Population Group N Consuming Mean SE 95% CL 95% CL Min Max 

Whole Population 16,783 11 0.06 0.01 0.05 0.07 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 1.4 6.6b 

Age Group (years) 

0 to 1 865 0.66 0.00 0.00 0.00 0.01 0.0b 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.0b 0.0b 2.3b 

1 to 2 1,052 4.4 0.04 0.01 0.02 0.06 0.0b 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.0b 1.0b 6.6b 

3 to 5 978 4.6 0.05 0.01 0.02 0.08 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.4b 4.0b 

6 to 12 2,256 7.0 0.05 0.01 0.02 0.08 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.2 1.4b 4.9b 

13 to 19 3,450 5.1 0.03 0.01 0.02 0.04 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 4.5b 

20 to 49 4,289 13 0.08 0.01 0.06 0.10 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.5 1.9 5.4b 

Females 13 to 49 4,103 11 0.06 0.01 0.04 0.07 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 1.3 5.3b 

50+ 3,893 13 0.05 0.01 0.04 0.07 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.4 1.0 5.2b 

Race 

Mexican American 4,450 9.5 0.08 0.01 0.05 0.11 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 1.8 6.6b 

Non-Hispanic Black 4,265 12 0.06 0.01 0.04 0.07 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3 1.1 4.9b 

Non-Hispanic White 6,757 10 0.05 0.01 0.04 0.07 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 1.2 5.4b 

Other Hispanic 562 15 0.09 0.02 0.05 0.14 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.4 0.7 2.1b 2.6b 

Othera 749 20 0.13 0.02 0.10 0.17 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.4 0.9 2.6b 4.5b 

a Other: Other Race - including Multiple Races. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III and 

CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

N = Sample size.
 

SE = Standard error.
 

CL = Confidence limit.
 

Min = Minimum value.
 

Max =Maximum value.
 

Source: U.S. EPA analysis of NHANES 2003–2006.
 

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Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 10-64 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-10. Consumer-Only Intake of Shellfish (g/kg-day), Edible Portion, Uncooked Fish Weight 

Lower Upper Percentiles 

1st 5th Population Group N Mean SE 95%CL 95% CL Min 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 1,563 0.57 0.03 0.50 0.63 0.0b 0.0b 0.0 0.0 0.1 0.3 0.7 1.3 1.9 3.0b 6.6b 

Age Group (years) 

0 to 1 11 0.42 0.21 0.00 0.85 0.0b 0.0b 0.0b 0.0b 0.0b 0.2b 0.2b 1.3b 2.3b 2.3b 2.3b 

1 to 2 53 0.94 0.18 0.56 1.31 0.0b 0.0b 0.0b 0.1b 0.2b 0.6b 1.0b 1.6b 3.5b 6.6b 6.6b 

3 to 5 56 1.00 0.18 0.63 1.36 0.0b 0.0b 0.0b 0.1b 0.4b 0.7b 1.4b 2.9b 2.9b 4.0b 4.0b 

6 to 12 158 0.72 0.12 0.47 0.97 0.0b 0.0b 0.1b 0.1b 0.2 0.5 1.1 1.7b 2.0b 4.5b 4.9b 

13 to 19 245 0.61 0.06 0.49 0.74 0.0b 0.0b 0.0 0.0 0.1 0.4 0.9 1.5 1.9 2.7b 4.5b 

20 to 49 605 0.63 0.06 0.52 0.75 0.0b 0.0b 0.0 0.0 0.1 0.4 0.8 1.8 2.2 4.3b 5.4b 

Females 13 to 49 474 0.53 0.06 0.40 0.66 0.0b 0.0b 0.0 0.0 0.1 0.3 0.6 1.2 1.8 4.5b 5.3b 

50+ 435 0.41 0.02 0.36 0.46 0.0b 0.0b 0.0 0.0 0.1 0.3 0.5 0.9 1.2 1.8b 5.2b 

Race 

Mexican American 331 0.83 0.10 0.62 1.04 0.0b 0.0b 0.0 0.1 0.2 0.5 1.1 1.9 2.8 4.3b 6.6b 

Non-Hispanic Black 449 0.48 0.03 0.41 0.54 0.0b 0.0b 0.0 0.0 0.1 0.3 0.6 1.1 1.7 2.5b 4.9b 

Non-Hispanic White 617 0.53 0.05 0.44 0.63 0.0b 0.0b 0.0 0.0 0.1 0.3 0.6 1.2 1.9 3.0b 5.4b 

Other Hispanic 49 0.64 0.07 0.49 0.79 0.0b 0.0b 0.0b 0.1b 0.3b 0.4 0.9b 1.3b 2.1b 2.6b 2.6b 

Other a 117 0.67 0.06 0.55 0.80 0.0b 0.0b 0.1b 0.1b 0.2 0.4 0.9 1.4b 2.6b 2.6b 4.5b 

a Other: Other Race - including Multiple Races. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III 

and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

N = Sample size.
 

SE = Standard error.
 

CL = Confidence limit.
 

Min = Minimum value.
 

Max = Maximum value.
 

Source: U.S. EPA analysis of NHANES 2003–2006. 

Chapter 10—Exposure Factors Handbook 

Intake of Fish and Shellfish 

Exposure Factors Handbook Page September 2011 10-65 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-11. Per Capita Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible Portion, Uncooked Fish Weight 

Percentiles 

% Lower Upper 

1st 5th 99th Population Group N Consuming Mean SE 95%CL 95% CL Min 10th 25th 50th 75th 90th 95th Max 

Whole Population 16,783 29 0.22 0.014 0.20 0.25 0.0b 0.0 0.0 0.0 0.0 0.0 0.1 0.8 1.3 2.7 13.4b 

Age Group (years) 

0 to 1 865 3.1 0.04 0.01 0.02 0.06 0.0b 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.0b 1.5b 5.1b 

1 to 2 1,052 17 0.26 0.06 0.15 0.38 0.0b 0.0b 0.0b 0.0 0.0 0.0 0.0 0.7 1.6b 4.7b 13.4b 

3 to 5 978 18 0.24 0.03 0.17 0.31 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.9 1.6 3.4b 7.0b 

6 to 12 2,256 22 0.21 0.05 0.12 0.31 0.0b 0.0b 0.0 0.0 0.0 0.0 0.0 0.8 1.4 2.7b 6.7b 

13 to 19 3,450 18 0.13 0.01 0.10 0.15 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.4 1.0 1.7 6.9b 

20 to 49 4,289 31 0.23 0.02 0.20 0.27 0.0b 0.0 0.0 0.0 0.0 0.0 0.1 0.8 1.3 2.7 8.6b 

Females 13 to 49 4,103 28 0.19 0.02 0.16 0.22 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.7 1.2 2.4 8.6b 

50+ 3,893 36 0.25 0.02 0.21 0.29 0.0b 0.0 0.0 0.0 0.0 0.0 0.3 0.9 1.4 2.6 6.1b 

Race 

Mexican American 4,450 22 0.23 0.03 0.17 0.28 0.0b 0.0 0.0 0.0 0.0 0.0 0.0 0.9 1.4 3.5 8.6b 

Non-Hispanic Black 4,265 32 0.24 0.02 0.20 0.28 0.0b 0.0 0.0 0.0 0.0 0.0 0.2 0.8 1.3 2.7 8.9b 

Non-Hispanic White 6,757 28 0.20 0.01 0.17 0.23 0.0b 0.0 0.0 0.0 0.0 0.0 0.1 0.7 1.2 2.4 13.4b 

Other Hispanic 562 32 0.27 0.05 0.17 0.37 0.0b 0.0b 0.0 0.0 0.0 0.0 0.2 0.9 1.7 3.1b 7.3b 

Other a 749 43 0.45 0.06 0.32 0.58 0.0b 0.0b 0.0 0.0 0.0 0.0 0.4 1.5 2.5 4.1b 6.5b 

a Other: Other Race - including Multiple Races. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III 

and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

N = Sample size.
 

SE = Standard error.
 

CL = Confidence limit.
 

Min = Minimum value.
 

Max = Maximum value.
 

Source: U.S. EPA analysis of NHANES 2003–2006. 

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Page Exposure Factors Handbook 10-66 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-12. Consumer-Only Intake of Total Finfish and Shellfish Combined (g/kg-day), Edible Portion, Uncooked Fish Weight 

Lower Upper Percentiles 

1st 5th Population Group N Mean SE 95%CL 95% CL Min 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 4,206 0.78 0.03 0.73 0.83 0.0b 0.0 0.0 0.1 0.2 0.5 1.1 1.8 2.4 4.2 13.4b 

Age Group (years) 0.0b 

0 to 1 30 1.18 0.29 0.59 1.76 0.0b 0.0b 0.0b 0.1b 0.2b 0.7b 1.6b 2.8b 2.9b 5.1b 5.1b 

1 to 2 183 1.54 0.25 1.04 2.04 0.0b 0.0b 0.1b 0.2b 0.4b 0.8 1.7b 3.5b 5.9b 13.4b 13.4b 

3 to 5 196 1.31 0.14 1.04 1.59 0.0b 0.0b 0.1b 0.2b 0.5 1.0 1.7 2.9b 3.6b 6.2b 7.0b 

6 to 12 461 0.99 0.08 0.82 1.15 0.0b 0.0b 0.1b 0.1 0.3 0.7 1.4 2.0 2.7b 5.2b 6.7b 

13 to 19 685 0.69 0.03 0.63 0.76 0.0b 0.0 0.0 0.0 0.2 0.5 1.0 1.5 1.8 3.0 6.9b 

20 to 49 1,332 0.76 0.04 0.68 0.83 0.0b 0.0b 0.0 0.0 0.2 0.5 1.0 1.8 2.5 4.2b 8.6b 

Females 13 to 49 1,109 0.68 0.04 0.60 0.76 0.0b 0.0 0.0 0.0 0.2 0.4 0.9 1.5 1.9 4.0 8.6b 

50+ 1,319 0.71 0.03 0.64 0.77 0.0b 0.0b 0.0 0.1 0.2 0.5 1.0 1.6 2.1 3.3b 6.1b 

Race 0.0b 

Mexican American 831 1.01 0.06 0.88 1.14 0.0b 0.0b 0.0 0.1 0.3 0.8 1.3 2.1 3.2 5.6b 8.6b 

Non-Hispanic Black 1,212 0.76 0.04 0.67 0.85 0.0b 0.0 0.0 0.1 0.2 0.5 1.0 1.8 2.2 4.9 8.9b 

Non-Hispanic White 1,753 0.73 0.03 0.67 0.78 0.0b 0.0b 0.0 0.0 0.2 0.5 1.0 1.6 2.1 3.4b 13.4b 

Other Hispanic 136 0.86 0.11 0.63 1.09 0.0b 0.0b 0.0b 0.1b 0.3 0.5 1.2 2.0b 2.6b 5.2b 7.3b 

Other a 274 1.03 0.13 0.77 1.29 0.0b 0.0b 0.0b 0.1 0.2 0.6 1.4 2.5 2.9b 6.1b 6.5b 

a Other: Other Race - including Multiple Races. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on NHANES III and 

CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

N = Sample size.
 

SE = Standard error.
 

CL = Confidence limit.
 

Min = Minimum value.
 

Max = Maximum value.
 

Source: U.S. EPA analysis of NHANES 2003–2006. 

Chapter 10—Exposure Factors Handbook 

Intake of Fish and Shellfish 

Exposure Factors Handbook Page September 2011 10-67 
 

 

a Table 10-13. Total Fish Consumption, Consumers Only, by Demographic Variables

Demographic Category 

Intake (g/person-day) 

Mean 95th Percentile 

Overall (all fish consumers) 

Race 

 Caucasian 

 Black 

 Asian 

 Other 

Sex 

 Female 

 Male 

Age (years) 

 0 to 9 

 10 to 19 

 20 to 29 

 30 to 39 

 40 to 49 

 50 to 59 

 60 to 69 

 ≥70 

Sex and Age (years) 

 Female 

 0 to 9 

 10 to 19 

 20 to 29 

 30 to 39 

 40 to 49 

 50 to 59 

 60 to 69 

 ≥70 

 Male 

 0 to 9 

 10 to 19 

 20 to 29 

 30 to 39 

 40 to 49 

 50 to 59 

 60 to 69 

 ≥70 

Census Region 

 New England 

 Middle Atlantic 

 East North Central 

 West North Central 

 South Atlantic 

 East South Central 

 West South Central 

 Mountain 

 Pacific 

14.3 

14.2 

16.0 

21.0 

13.2 

13.2 

15.6 

6.2 

10.1 

14.5 

15.8 

17.4 

20.9 

21.7 

13.3 

6.1 

9.0 

13.4 

14.9 

16.7 

19.5 

19.0 

10.7 

6.3 

11.2 

16.1 

17.0 

18.2 

22.8 

24.4 

15.8 

16.3 

16.2 

12.9 

12.0 

15.2 

13.0 

14.4 

12.1 

14.2 

41.7 

41.2 

45.2 

67.3 

29.4 

38.4 

44.8 

16.5 

26.8 

38.3 

42.9 

48.1 

53.4 

55.4 

39.8 

17.3 

25.0 

34.5 

41.8 

49.6 

50.1 

46.3 

31.7 

15.8 

29.1 

43.7 

45.6 

47.7 

57.5 

61.1 

45.7 

46.5 

47.8 

36.9 

35.2 

44.1 

38.4 

43.6 

32.1 

39.6 

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Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-68 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-13. Total Fish Consumption, Consumers Only, by Demographic Variablesa (continued) 

Intake (g/person-day) 

Demographic Category Mean 95th Percentile 

Community Type 

Rural, non-SMSA 

Central city, 2M or more 

Outside central city, 2M or more 

Central city, 1M–2M 

Outside central city, 1M–2M 

Central city, 500K–1M 

Outside central city, 500K–1M 

Outside central city, 250K–500K 

Central city, 250K–500K 

Central city, 50K–250K 

Outside central city, 50K–250K 

Other urban 

13.0 38.3 

19.0 55.6 

15.9 47.3 

15.4 41.7 

14.5 41.5 

14.2 41.0 

14.0 39.7 

12.2 32.1 

14.1 40.5 

13.8 43.4 

11.3 31.7 

13.5 39.2 a	 The calculations in this table are based on respondents who consumed fish during the survey month. These 

respondents are estimated to represent 94% of the U.S. population. 

SMSA	 = Standard metropolitan statistical area. 

Source:	 SRI (1980). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-69 
a Table 10-14. Percent Distribution of Total Fish Consumption for Females and Males by Age

Age 

(years) 

Consumption Category (g/day) 

0.0–5.0 5.1–10.0 10.1–15.0 15.1–20.0 20.1–25.0 25.1–30.0 30.1–37.5 37.6–47.5 47.6–60.0 60.1–122.5 over 122.5 

Females 

 0to 9 

 10 to 19 

 20 to 29 

 30 to 39 

 40 to 49 

 50 to 59 

 60 to 69 

 ≥70 

 Overall 

Males 

 0to 9 

 10 to 19 

 20 to 29 

 30 to 39 

 40 to 49 

 50 to 59 

 60 to 69 

 ≥70 

 Overall 

55.5 

17.8 

28.1 

22.4 

17.5 

17.0 

11.5 

41.9 

28.9 

52.1 

27.8 

16.7 

16.6 

11.9 

9.9 

7.4 

24.5 

22.6 

26.8 

31.4 

26.1 

23.6 

21.9 

17.4 

16.9 

22.1 

24.0 

30.1 

29.3 

22.9 

21.2 

22.3 

15.2 

15.0 

21.7 

23.1 

11.0 

15.4 

20.4 

18.0 

20.7 

16.8 

20.6 

12.3 

16.8 

11.9 

19.0 

19.6 

19.2 

18.6 

15.4 

15.6 

15.7 

17.0 

3.7 

6.9 

11.8 

12.7 

13.2 

15.5 

15.9 

9.7 

10.7 

3.1 

10.4 

14.5 

13.2 

14.7 

14.4 

12.8 

9.9 

11.3 

1.0 

3.5 

6.7 

8.3 

9.3 

10.5 

9.1 

5.2 

6.4 

1.2 

6.0 

8.8 

9.5 

8.4 

10.4 

11.4 

9.8 

7.7 

1.1 

2.4 

3.5 

4.8 

4.5 

8.5 

9.2 

2.9 

4.3 

0.6 

3.2 

6.2 

7.3 

8.5 

9.7 

8.5 

5.3 

5.7 

0.7 

1.2 

4.4 

3.8 

4.6 

6.8 

6.0 

2.6 

3.5 

0.7 

1.7 

4.4 

5.2 

5.3 

8.7 

9.9 

5.4 

4.6 

0.3 

0.7 

2.2 

2.8 

2.8 

5.2 

6.1 

1.2 

2.4 

0.1 

1.7 

3.1 

3.2 

5.2 

7.6 

8.3 

3.1 

3.6 

0.0 

0.2 

0.9 

1.9 

3.4 

4.2 

2.4 

0.8 

1.6 

0.2 

0.4 

1.9 

1.3 

3.3 

4.3 

5.5 

1.7 

2.2 

0.0 

0.4 

0.9 

1.7 

2.1 

2.0 

2.1 

1.2 

1.2 

0.1 

0.5 

1.9 

2.2 

1.7 

4.1 

5.5 

2.8 

2.1 

0.0 

0.0 

0.0 

0.1 

0.2 

0.2 

0.2 

0.1 

0.1 

0.0 

0.0 

0.1 

0.0 

0.1 

0.2 

0.1 

0.1 

0.1 a The percentage of females in an age bracket whose average daily fish consumption is within the specified range. The calculations in this table are 

based upon the respondents who consumed fish during the month of the survey. These respondents are estimated to represent 94% of the U.S. 

population. 

Source: SRI (1980). 

Page Exposure Factors Handbook 10-70 September 2011

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-15. Mean Total Fish Consumption by Speciesa 

Species 

Mean Consumption 

(g/day) Species 

Mean Consumption 

(g/day) 

Not reported 

Abalone 

Anchovies 

Bassb 

Bluefish 

Bluegillsb 

Bonitob 

Buffalofish 

Butterfish 

Carpb 

Catfish (Freshwater)b 

Catfish (Marine)b 

Clamsb 

Cod 

Crab, King 

Crab, other than Kingb 

Crappieb 

Croakerb 

Dolphinb 

Drums 

Floundersb 

Groupers 

Haddock 

Hake 

Halibutb 

Herring 

Kingfish 

Lobster (Northern)b 

Lobster (Spiny) 

Mackerel, Jack 

Mackerel, other than Jack 

1.173 

0.014 

0.010 

0.258 

0.070 

0.089 

0.035 

0.022 

0.010 

0.016 

0.292 

0.014 

0.442 

0.407 

0.030 

0.254 

0.076 

0.028 

0.012 

0.019 

1.179 

0.026 

0.399 

0.117 

0.170 

0.224 

0.009 

0.162 

0.074 

0.002 

0.172 

Mulletb 

Oystersb 

Perch (Freshwater)b 

Perch (Marine) 

Pike (Marine)b 

Pollock 

Pompano 

Rockfish 

Sablefish 

Salmonb 

Scallopsb 

Scupb 

Sharks 

Shrimpb 

Smeltb 

Snapper 

Snookb 

Spotb 

Squid and Octopi 

Sunfish 

Swordfish 

Tilefish 

Trout (Freshwater)b 

Trout (Marine)b 

Tuna, light 

Tuna, White Albacore 

Whitefishb 

Other finfishb 

Other shellfishb 

0.029 

0.291 

0.062 

0.773 

0.154 

0.266 

0.004 

0.027 

0.002 

0.533 

0.127 

0.014 

0.001 

1.464 

0.057 

0.146 

0.005 

0.046 

0.016 

0.020 

0.012 

0.003 

0.294 

0.070 

3.491 

0.008 

0.141 

0.403 

0.013 

a The calculations in this table are based upon respondents who consumed fish during the month of the 

survey. These respondents are estimated to represent 94% of the U.S. population. b Designated as freshwater or estuarine species. 

Source: SRI (1980). 

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September 2011 10-71 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-16. Best Fits of Lognormal Distributions Using the Non-Linear Optimization Method 

Adults Teenagers Children 

Shellfish 

μ 

σ

Finfish (freshwater) 

μ 

σ

Finfish (saltwater) 

μ 

σ

1.370 

0.858 

0.334 

1.183 

2.311 

0.72 

–0.183 

1.092 

0.578 

0.822 

1.691 

0.830 

0.854 

0.730 

–0.559 

1.141 

0.881 

0.970 

The following equations may be used with the appropriate μ and σ values to obtain an average Daily 

Consumption Rate (DCR), in grams, and percentiles of the DCR distribution. 

DCR50 = exp (μ) 

DCR90 = exp [μ + z(0.90) × σ] 

DCR99 = exp [μ + z(0.99) × σ] 

DCRavg = exp [μ + 0.5 × σ2

] 

Source: Ruffle et al. (1994). 

Table 10-17. Mean Fish Intake in a Day, by Sex and Agea 

Sex 

Age (years) 

Per Capita Intake 

(g/day) 

Percent of Population 

Consuming Fish in 1 Day 

Mean Intake (g/day) for 

Consumers Onlyb 

Males or Females 

5 and under 4 6.0 67 

Males 

6 to 11 

12 to 19 

20 and over 

3 

3 

15 

3.7 

2.2 

10.9 

79 

136 

138 

Females 

6 to 11 

12 to 19 

20 and over 

7 

9 

12 

7.1 

9.0 

10.9 

99 

100 

110 

All individuals 11 9.4 117 a Based on USDA Nationwide Food Consumption Survey 1987–1988 data for 1 day. b Intake for users only was calculated by dividing the per capita consumption rate by the fraction of the 

population consuming fish in 1 day. 

Source: USDA (1992). 

Page Exposure Factors Handbook 

10-72 September 2011 
 

Table 10-18. Percent of Respondents That Responded Yes, No, or Don’t Know to Eating Seafood in 1 Month 

(including shellfish, eels, or squid) 

No 

Response 

Yes DK 

Population Group Total N N % N % N % 

Overall 

Sex 

 * 

 Male 

 Female 

Age (years) 

 * 

 1 to 4 

 5 to 11 

 12 to 17 

 18 to 64 

 >64 

Race 

 * 

 White 

 Black 

 Asian 

 Some Others 

 Hispanic 

Hispanic 

 * 

 No 

 Yes 

 DK 

Employment 

 * 

 Full Time 

 Part Time 

 Not Employed 

Education 

 * 

 <High School 

 High School Graduate 

 <College 

 College Graduate 

 Post-Graduate 

4,663 

2 

2,163 

2,498 

84 

263 

348 

326 

2,972 

670 

60 

3,774 

463 

77 

96 

193 

46 

4,243 

348 

26 

958 

2,017 

379 

1,309 

1,021 

399 

1,253 

895 

650 

445 

1,811 

1 

821 

989 

25 

160 

177 

179 

997 

273 

20 

1,475 

156 

21 

39 

100 

10 

1,625 

165 

11 

518 

630 

134 

529 

550 

196 

501 

304 

159 

101 

38.8 

50.0 

38.0 

39.6 

29.8 

60.8 

50.9 

54.9 

33.5 

40.7 

33.3 

39.1 

33.7 

27.3 

40.6 

51.8 

21.7 

31.2 

35.4 

40.4 

54.1 

31.2 

35.4 

40.4 

53.9 

49.1 

40.0 

34.0 

24.5 

22.7 

2,780 

1 

1,311 

1,468 

42 

102 

166 

137 

1,946 

387 

22 

2,249 

304 

56 

56 

93 

412 

1,366 

236 

766 

412 

1,366 

236 

766 

434 

198 

739 

584 

484 

341 

59.6 

50.0 

60.6 

58.8 

50.0 

38.8 

47.7 

42.0 

65.5 

57.8 

36.7 

59.6 

65.7 

72.7 

58.3 

48.2 

43.0 

67.7 

62.3 

58.5 

43.0 

67.7 

62.3 

58.5 

42.5 

49.6 

59.0 

65.3 

74.5 

76.6 

72 

* 

31 

41 

17 

1 

5 

10 

29 

10 

18 

50 

3 

* 

1 

* 

28 

21 

9 

14 

28 

21 

9 

14 

37 

45 

13 

7 

7 

3 

1.5 

* 

1.4 

1.6 

20.2 

0.4 

1.4 

3.1 

1.0 

1.5 

30.0 

1.3 

0.6 

* 

1.0 

* 

41.3 

1.2 

* 

* 

2.9 

1.0 

2.4 

1.1 

3.6 

1.3 

1.0 

0.8 

1.1 

0.7 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-73 
 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-74 September 2011 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-18. Percent of Respondents That Responded Yes, No, or Don’t Know to Eating Seafood in 1 Month 

(including shellfish, eels, or squid) (continued) 

Response 

No Yes DK 

Population Group Total N N % N % N % 

Census Region 

Northeast 

Midwest 

South 

West 

1,048 

1,036 

1,601 

978 

370 

449 

590 

402 

35.3 

43.3 

36.9 

41.1 

655 

575 

989 

561 

62.5 

55.5 

61.8 

57.4 

23 

12 

22 

15 

2.2 

1.2 

1.4 

1.5 

Day of Week 

Weekday 

Weekend 

3,156 

1,507 

1,254 

557 

39.7 

37.0 

1,848 

932 

58.6 

61.8 

54 

18 

1.7 

1.2 

Season 

Winter 

Spring 

Summer 

Fall 

1,264 

1,181 

1,275 

943 

462 

469 

506 

374 

36.6 

39.7 

39.7 

39.7 

780 

691 

745 

564 

61.7 

58.5 

58.4 

59.8 

22 

21 

24 

5 

1.7 

1.8 

1.9 

0.5 

Asthma 

No 

Yes 

DK 

4,287 

341 

35 

1,674 

131 

6 

39.0 

38.4 

17.7 

2,563 

207 

10 

59.8 

60.7 

28.6 

50 

3 

19 

1.2 

0.9 

54.3 

Angina 

No 

Yes 

DK 

4,500 

125 

38 

1,750 

56 

50 

38.9 

44.8 

13.2 

2,698 

68 

14 

60.0 

54.4 

36.8 

52 

1 

19 

1.2 

0.8 

50.0 

Bronchitis/Emphysema 

No 

Yes 

DK 

4,424 

203 

36 

1,726 

80 

5 

9.0 

39.4 

13.9 

2,648 

121 

11 

59.6 

59.6 

30.6 

50 

2 

20 

1.1 

1.0 

55.6 

* = Missing data. 

DK = Don’t know. 

% = Row percentage. 

N = Sample size. 

Source: U.S. EPA (1996). 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-19. Number of Respondents Reporting Consumption of a Specified Number of Servings of Seafood in 

1 Month 

Number of Servings in a Month 

Population Group Total N 1–2 3–5 6–10 11–19 20+ DK 

Overall 2,780 918 990 519 191 98 64 

Sex 

* 1,311 405 458 261 101 57 29 

Male 1,468 512 532 258 90 41 35 

Female 1 1 * * * * * 

Age (years) 

* 42 13 16 5 4 1 3 

1 to 4 102 55 29 12 2 * 4 

5 to 11 166 72 57 21 6 4 6 

12 to 17 137 68 54 9 2 1 3 

18 to 64 1,946 603 679 408 145 79 32 

>64 387 107 155 64 32 13 16 

Race 

* 2,249 731 818 428 155 76 41 

White 304 105 103 56 16 10 14 

Black 56 15 17 11 5 5 3 

Asian 56 22 18 6 5 3 2 

Some Others 93 41 25 14 9 2 2 

Hispanic 22 4 9 4 1 2 2 

Hispanic 

* 2,566 844 922 480 175 88 57 

No 182 68 52 34 15 8 5 

Yes 15 5 8 2 * * * 

DK 17 1 8 3 1 2 2 

Employment 

* 399 190 140 40 11 5 13 

Full Time 1,366 407 466 307 107 57 22 

Part Time 236 70 95 46 14 8 3 

Not Employed 766 249 285 124 57 26 25 

Refused 13 2 4 2 2 2 1 

Education 

* 434 205 149 47 12 7 14 

<High School 198 88 62 20 6 10 12 

High School Graduate 739 267 266 119 46 21 20 

<College 584 161 219 122 48 26 8 

College Graduate 484 115 183 121 43 17 5 

Post-Graduate 341 82 111 90 36 17 5 

Census Region 

Northeast 655 191 241 137 62 12 12 

Midwest 575 199 221 102 17 22 14 

South 989 336 339 175 70 41 28 

West 561 192 189 105 42 23 10 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-75 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-19. Number of Respondents Reporting Consumption of a Specified Number of Servings of Seafood 

in 1 Month (continued) 

Number of Servings in a Month 

Population Group Total N 1–2 3–5 6–10 11–19 20+ DK 

Day of Week 

Weekday 1,848 602 661 346 129 70 40 

Weekend 932 316 329 173 62 28 24 

Season 

Winter 780 262 284 131 60 28 15 

Spring 691 240 244 123 45 25 14 

Summer 745 220 249 160 59 31 26 

Fall 564 196 213 105 27 14 9 

Asthma 

No 2,563 846 917 475 180 88 57 

Yes 207 69 71 42 11 9 5 

DK 10 3 2 2 * 1 2 

Angina 

No 2,698 896 960 509 183 95 55 

Yes 68 19 27 8 7 1 6 

DK 14 3 3 2 1 2 3 

Bronchitis/Emphysema 

No 2,648 877 940 495 185 91 60 

Yes 121 37 47 23 6 6 2 

DK 11 4 3 1 * 1 2 

* = Missing data.
 

DK = Don’t know.
 

% = Row percentage.
 

N = Sample size.
 

Refused = Respondent refused to answer.
 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-76 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-20. Number of Respondents Reporting Monthly Consumption of Seafood That Was Purchased or 

Caught by Someone They Knew 

Population Group Total N * 

Mostly 

Purchased Mostly Caught DK 

Overall 2,780 3 2,584 154 39 

Sex 

* 

Male 

Female 

1,311 

1,468 

1 

1 

2 

* 

1,206 

1,377 

1 

85 

69 

* 

19 

20 

* 

Age (years) 

* 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

42 

102 

166 

137 

1,946 

387 

* 

* 

* 

* 

3 

* 

39 

94 

153 

129 

1,810 

359 

3 

8 

9 

6 

106 

22 

* 

* 

4 

2 

27 

6 

Race 

* 

White 

Black 

Asian 

Some Others 

Hispanic 

2,249 

304 

56 

56 

93 

22 

1 

1 

* 

* 

* 

1 

2,092 

280 

50 

55 

86 

21 

124 

19 

4 

* 

7 

* 

32 

4 

2 

1 

* 

* 

Hispanic 

* 

No 

Yes 

DK 

2,566 

182 

15 

17 

2 

* 

* 

1 

2,387 

169 

12 

16 

140 

13 

1 

* 

37 

* 

2 

* 

Employment 

* 

Full Time 

Part Time 

Not Employed 

Refused 

399 

1,366 

236 

766 

13 

* 

2 

1 

* 

* 

368 

1,285 

217 

701 

13 

25 

64 

15 

50 

* 

6 

15 

3 

15 

* 

Education 

* 

<High School 

High School Graduate 

<College 

College Graduate 

Post-Graduate 

434 

198 

739 

584 

484 

341 

* 

* 

* 

2 

* 

1 

401 

174 

680 

547 

460 

322 

26 

20 

48 

28 

19 

13 

7 

4 

11 

7 

5 

5 

Census Region 

Northeast 

Midwest 

South 

West 

655 

575 

989 

561 

2 

* 

1 

* 

627 

547 

897 

513 

21 

20 

73 

40 

5 

8 

18 

8 

Exposure Factors Handbook Page
 

September 2011 10-77 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-20. Number of Respondents Reporting Monthly Consumption of Seafood That Was Purchased or 

Caught by Someone They Knew (continued) 

Population Group Total N * 

Mostly 

Purchased Mostly Caught DK 

Day of Week 

Weekday 

Weekend 

1,848 

932 

2 

1 

1,724 

860 

100 

54 

22 

17 

Season 

Winter 

Spring 

Summer 

Fall 

780 

691 

745 

564 

* 

* 

2 

1 

741 

655 

674 

514 

35 

27 

54 

38 

4 

9 

15 

11 

Asthma 

No 

Yes 

DK 

2,563 

207 

10 

2 

1 

* 

2,384 

190 

10 

142 

12 

* 

35 

4 

* 

Angina 

No 

Yes 

DK 

2,698 

68 

14 

3 

* 

* 

2,507 

63 

14 

151 

3 

* 

37 

2 

* 

Bronchitis/Emphysema 

No 

Yes 

DK 

2,648 

121 

11 

3 

* 

* 

2,457 

116 

11 

149 

5 

* 

39 

* 

* 

* = Missing data. 

DK = Don’t know. 

N = Sample size. 

Refused = Respondent refused to answer. 

Source: U.S. EPA (1996). 

Table 10-21. Distribution of Fish Meals Reported by NJ Consumers During the Recall Period 

Meals N % of Total Cumulative % 

1 288 41.9 41.9 

2 204 29.7 71.7 

3 118 17.2 88.9 

4 34 5.0 93.9 

5 16 2.3 96.2 

6 13 1.9 98.1 

7 7 1.0 99.1 

≥7 6 0.9 100.0 

Total 686 99.9 -­

N = Number of respondents. 

Source: Stern et al. (1996). 

Page Exposure Factors Handbook 

10-78 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-22. Selected Species Among All Reported Meals by NJ Consumers During 

the Recall Period 

Species % of total reported meals (N = 1,447) 

Tunaa 19.2 

Shrimp 13.5 

Founder/fluke 11.9 

Shellfish/clams, etc. 

b 8.2 

Finfish (unidentified) 7.5 

Salmon 5.3 

Swordfish 1.5 

Shark 0.3 

Total 67.4 a Includes fresh and canned tuna, as fillets, sandwiches, and salads. b Includes soups and stews. 

N = Number of meals. 

Source: Stern et al. (1996). 

Table 10-23. Cumulative Probability Distribution of Average Daily Fish Consumption (g/day) 

Percentile All Adult Fish Consumers 

(≥18 years) 

Fish Consuming Women 

(18 to 40 years) 

Arithmetic mean 

Geometric mean 

Percentiles 

5th 

10th 

25th 

40th 

50th 

60th 

75th 

90th 

95th 

99th 

50.2 

36.6 

9.1 

12.2 

24.3 

28.4 

32.4 

42.6 

62.1 

107.4 

137.7 

210.6 

41.0 

30.8 

7.0 

10.3 

20.3 

24.3 

28.0 

33.4 

48.6 

88.1 

106.8 

142.3 

Source: Stern et al. (1996). 

Table 10-24. Distribution of the Usual Frequency of Fish Consumptiona 

Usual Frequency All Fish 

Consumers 

N = 933 

% of Total Consumers 

During Recall 

Period 

N = 686 

% of Total 

>2 times/week 63 6.8 59 8.6 

1 to 2 times/week 365 39.1 335 48.8 

2 times/month 173 18.5 136 19.8 

1 time/month 206 22.0 121 17.6 

Few times/year 126 13.5 35 5.1 a Based on survey respondents and household members. 

N = Sample size. 

Source: Stern et al. (1996). 

Exposure Factors Handbook Page
 

September 2011 10-79 
 

 

 

 

 

 

 

 

 

 

 

 

Table 10-25. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type 

for the U.S. Population, as Prepared 

Estimate (90% Interval) 

Habitat Statistic Finfish Shellfish 

Fresh/Estuarine	 Mean 

50th percentile 

90th percentile 

95th percentile 

99th percentile 

Marine	 Mean 

50th percentile 

90th percentile 

95th percentile 

99th percentile 

All Fish	 Mean 

50th percentile 

90th percentile 

95th percentile 

99th percentile 

2.6 (2.3–2.8) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

6.7 (5.3–9.3) 

67.2 (63.5–75.5) 

6.6 (6.1–7.0) 

0.0 (0.0–0.0) 

26.3 (24.3–27.4) 

46.1 (43.1–47.5) 

94.7 (89.8–100.4) 

9.1 (8.6–9.7) 

0.0 (0.0–0.0) 

34.8 (31.4–36.6) 

59.8 (57.5–61.6) 

126.3 (120.6–130.1) 

2.0 (1.8–2.3) 

0.0 (0.0–0.0) 

0.0 (0.0–0.2) 

9.6 (7.9–10.6) 

59.3 (51.5–64.0) 

1.7 (1.3–2.0) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

67.9 (51.6–84.5) 

3.7 (3.2–4.2) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

22.6 (17.2–26.3) 

90.6 (82.9–95.7) 

Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 

replications. Estimates are projected from a sample of 20,607 individuals to the 

U.S. population of 261,897,236 using 4-year combined survey weights. 

Source:	 U.S. EPA (2002). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-80 September 2011 
 

 

 

Table 10-26. Daily Average Per Capita Estimates of Fish Consumption: U.S. Population—Mean Consumption by Species Within Habitat, as 

Prepared 

Estimated Mean Estimated Mean Estimated Mean Habitat Species Habitat Species	 Habitat Species g/Person/Day g/Person/Day	 g/Person/Day 

Estuarine Shrimp 1.63012 Marine (Cont) Lobster 0.15725 All Species Perch (Freshwater) 0.12882 

Flounder 0.45769 Scallop (Marine) 0.14813 (Cont) Squid 0.12121 

Catfish (Estuarine) 0.34065 Squid 0.12121 Oyster 0.11615 

Flatfish (Estuarine) 0.27860 Ocean Perch 0.11135 Ocean Perch 0.11135 

Crab (Estuarine) 0.17971 Sea Bass 0.09766 Sea Bass 0.09766 

Perch (Estuarine) 0.12882 Mackerel 0.08780 Carp 0.09584 

Oyster 0.11615 Swordfish 0.07790 Herring 0.09409 

Herring 0.09409 Sardine 0.07642 Croaker 0.08798 

Croaker 0.08798 Pompano 0.07134 Mackerel 0.08780 

Trout, mixed sp. 0.08582 Flatfish (Marine) 0.05216 Trout (Estuarine) 0.08582 

Salmon (Estuarine) 0.05059 Mussels 0.05177 Trout (Freshwater) 0.08582 

Rockfish 0.03437 Octopus 0.04978 Swordfish 0.07790 

Anchovy 0.02976 Halibut 0.02649 Sardine 0.07642 

Clam (Estuarine) 0.02692 Snapper 0.02405 Pompano 0.07134 

Mullet 0.02483 Whitefish (Marine) 0.00988 Flatfish (Marine) 0.05216 

Smelts (Estuarine) 0.00415 Smelts (Marine) 0.00415 Mussels 0.05177 

Eel 0.00255 Shark 0.00335 Salmon (Estuarine) 0.05059 

Scallop (Estuarine) 0.00100 Snails (Marine) 0.00198 Octopus 0.04978 

Smelts, Rainbow 0.00037 Conch 0.00155 Rockfish 0.03437 

Sturgeon (Estuarine) 0.00013 Roe 0.00081 Anchovy 0.02976 

Unknown Pike 0.02958 

Freshwater Catfish (Freshwater) 0.34065 Fish 0.23047 Clam (Estuarine) 0.02692 

Trout 0.15832 Seafood 0.00203 Halibut 0.02649 

Perch (Freshwater) 0.12882 All Species Mullet 0.02483 

Carp 0.09584 Tuna 2.62988 Snapper 0.02405 

Trout, mixed sp. 0.08582 Shrimp 1.63012 Whitefish (Freshwater) 0.00988 

Pike 0.02958 Cod 1.12504 Whitefish (Marine) 0.00988 

Whitefish (Freshwater) 0.00988 Salmon (Marine) 1.01842 Crayfish 0.00575 

Crayfish 0.00575 Clam (Marine) 1.00458 Smelts (Estuarine) 0.00415 

Snails (Freshwater) 0.00198 Flounder 0.45769 Smelts (Marine) 0.00415 

Cisco 0.00160 Catfish (Estuarine) 0.34065 Shark 0.00335 

Salmon (Freshwater) 0.00053 Catfish (Freshwater) 0.34065 Eel 0.00255 

Smelts, Rainbow 0.00037 Flatfish (Estuarine) 0.27860 Seafood 0.00203 

Sturgeon (Freshwater) 0.00013 Pollock 0.27685 Snails (Freshwater) 0.00198 

Porgy 0.27346 Snails (Marine) 0.00198 

Marine Tuna 2.62988 Haddock 0.25358 Cisco 0.00160 

Cod 1.12504 Fish 0.23047 Conch 0.00155 

Salmon (Marine) 1.01842 Crab (Marine) 0.20404 Scallop (Estuarine) 0.00100 

Clam (Marine) 1.00458 Whiting 0.20120 Roe 0.00081 

Pollock 0.27685 Crab (Estuarine) 0.17971 Salmon (Freshwater) 0.00053 

Porgy 0.27346 Trout 0.15832 Smelts, Rainbow (Estuarine) 0.00037 

Haddock 0.25358 Lobster 0.15725 Smelts, Rainbow 0.00037 

Crab (Marine) 0.20404 Scallop (Marine) 0.14813 Sturgeon (Estuarine) 0.00013 

Whiting 0.20120 Perch (Estuarine) 0.12882 Sturgeon (Freshwater) 0.00013 

Notes: Estimates are projected from a sample of 20,607 individuals to the U.S. population of 261,897,236 using 4-year combined survey weights. Source of individual consumption data: USDA Combined 

1994–1996, 1998 CSFII. The fish component of foods containing fish was calculated using data from the recipe file of the USDA’s Nutrient Data Base for Individual Food Intake Surveys. 

Source:	 U.S. EPA (2002). 

Chapter 10—Exposure Factors Handbook 

Intake of Fish and Shellfish 

Exposure Factors Handbook Page September 2011 10-81 
 

 

Table 10-27. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type 

for the U.S. Population, Uncooked Fish Weight 

Estimate (90% Interval) 

Habitat Statistic Finfish Shellfish 

Fresh/Estuarine	 Mean 

50th percentile 

90th percentile 

95th percentile 

99th percentile 

Marine	 Mean 

50th percentile 

90th percentile 

95th percentile 

99th percentile 

All Fish	 Mean 

50th percentile 

90th percentile 

95th percentile 

99th percentile 

3.6 (3.2–4.0) 

0.0 (0.0–0.0) 

0.0 (0.00–0.7) 

14.1 (10.0–16.8) 

95.3 (80.7–100.8) 

9.0 (8.4–9.6) 

0.0 (0.0–0.0) 

37.5 (35.7–37.6) 

62.9 (61.3–65.5) 

128.4 (119.3–135.8) 

12.6 (11.9–13.3) 

0.0 (0.0–0.0) 

48.7 (45.3–50.4) 

81.8 (79.5–85.0) 

173.6 (168.0–183.4) 

2.7 (2.4–3.1) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

12.8 (10.5–13.8) 

77.0 (69.7–84.1) 

1.6 (1.2–2.0) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

54.8 (33.1–80.6) 

4.3 (3.7–4.9) 

0.0 (0.0–0.0) 

0.0 (0.0–0.0) 

23.2 (18.3–28.3) 

110.5 (93.1–112.9) 

Note:	 Percentile confidence intervals estimated using the bootstrap method with 1,000 

replications. Estimates are projected from a sample of 20,607 individuals to the 

U.S. population of 261,897,236 using 4-year combined survey weights. 

Source:	 U.S. EPA (2002). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-82 September 2011 
 

 

Chapter 10—Exposure Factors Handbook 

Intake of Fish and Shellfish 

Exposure Factors Handbook PageSeptember 2011 10-83

Table 10-28. Daily Average Per Capita Estimates of Fish Consumption U.S. Population—Mean Consumption by Species Within Habitat, Uncooked Fish Weight 

Habitat Species Estimated Mean 

g/Person/Day Habitat Species Estimated Mean g/Person/Day Habitat Species Estimated Mean g/Person/Day 

Estuarine 

Freshwater 

Marine 

Shrimp 

Flounder 

Catfish (Estuarine) 

Flatfish (Estuarine) 

Crab (Estuarine) 

Perch (Estuarine) 

Oyster 

Croaker 

Herring 

Trout, mixed sp. 

Salmon (Estuarine) 

Rockfish 

Anchovy 

Mullet 

Clam (Estuarine) 

Smelts (Estuarine) 

Eel 

Scallop (Estuarine) 

Smelts, Rainbow 

Sturgeon (Estuarine) 

Catfish (Freshwater) 

Trout 

Perch (Freshwater) 

Carp 

Trout, mixed sp. 

Pike 

Whitefish (Freshwater) 

Crayfish 

Snails (Freshwater) 

Cisco 

Salmon (Freshwater) 

Smelts, Rainbow 

Sturgeon (Freshwater) 

Tuna 

Cod 

Salmon (Marine) 

Clam (Marine) 

Porgy 

Pollock 

Haddock 

Crab (Marine) 

Whiting 

2.20926 

0.58273 

0.48928 

0.33365 

0.25382 

0.18148 

0.13963 

0.13730 

0.13298 

0.11908 

0.06898 

0.04448 

0.04334 

0.03617 

0.01799 

0.00611 

0.00324 

0.00128 

0.00052 

0.00013 

0.48928 

0.19917 

0.18148 

0.13406 

0.11908 

0.03260 

0.00995 

0.00746 

0.00249 

0.00234 

0.00073 

0.00052 

0.00013 

3.61778 

1.47734 

1.38873 

0.67135 

0.40148 

0.32878 

0.32461 

0.28818 

0.25725 

Marine (Cont.) 

Unknown 

All Species 

Lobster 

Scallop (Marine) 

Squid 

Ocean Perch 

Sea Bass 

Mackerel 

Sardine 

Swordfish 

Pompano 

Mussels 

Octopus 

Flatfish (Marine) 

Halibut 

Snapper 

Whitefish (Marine) 

Smelts (Marine) 

Shark 

Snails (Marine) 

Conch 

Roe 

Fish 

Seafood 

Tuna 

Shrimp 

Cod 

Salmon (Marine) 

Clam (Marine) 

Flounder 

Catfish (Estuarine) 

Catfish (Freshwater) 

Porgy 

Flatfish (Estuarine) 

Pollock 

Haddock 

Fish 

Crab (Marine) 

Whiting 

Crab (Estuarine) 

Trout 

Lobster 

Scallop (Marine) 

Perch (Estuarine) 

0.21290 

0.18951 

0.15438 

0.14074 

0.12907 

0.11468 

0.10565 

0.10193 

0.09905 

0.07432 

0.06430 

0.06247 

0.03226 

0.02739 

0.00995 

0.00611 

0.00424 

0.00249 

0.00207 

0.00102 

0.60608 

0.00326 

3.61778 

2.20926 

1.47734 

1.38873 

0.67135 

0.60608 

0.58273 

0.48928 

0.48928 

0.40148 

0.33365 

0.32878 

0.32461 

0.28818 

0.25725 

0.25382 

0.21290 

0.19917 

0.18951 

0.18148 

All 

Species 

(Cont.) 

Perch (Freshwater) 

Squid 

Ocean Perch 

Oyster 

Croaker 

Carp 

Herring 

Sea Bass 

Trout (Estuarine) 

Trout (Freshwater) 

Mackerel 

Sardine 

Swordfish 

Pompano 

Mussels 

Salmon (Estuarine) 

Octopus 

Flatfish (Marine) 

Rockfish 

Anchovy 

Mullet 

Pike 

Halibut 

Snapper 

Clam (Estuarine) 

Whitefish (Freshwater) 

Whitefish (Marine) 

Crayfish 

Smelts (Estuarine) 

Smelts (Marine) 

Shark 

Seafood 

Eel 

Snails (Freshwater) 

Snails (Marine) 

Cisco 

Conch 

Scallop (Estuarine) 

Roe 

Salmon (Freshwater) 

Smelts, Rainbow (Estuarine) 

Smelts, Rainbow 

Sturgeon (Estuarine) 

Sturgeon (Freshwater) 

0.18148 

0.15438 

0.14074 

0.13963 

0.13730 

0.13406 

0.13298 

0.12907 

0.11908 

0.11908 

0.11468 

0.10565 

0.10193 

0.09905 

0.07432 

0.06898 

0.06430 

0.06247 

0.04448 

0.04334 

0.03617 

0.03260 

0.03226 

0.02739 

0.01799 

0.00995 

0.00995 

0.00746 

0.00611 

0.00611 

0.00424 

0.00326 

0.00324 

0.00249 

0.00249 

0.00234 

0.00207 

0.00128 

0.00102 

0.00073 

0.00052 

0.00052 

0.00013 

0.00013 

Notes: Estimates are projected from a sample of 20,607 individuals to the U.S. population of 261,897,236 using 4-year combined survey weights. Source of individual consumption data: USDA Combined 

1994–1996, 1998 CSFII. Amount of consumed fish recorded by survey respondents was converted to uncooked fish quantities using data from the recipe file of USDA’s Nutrient Data Base for 

Individual Food Intake Survey. Fish component of foods containing fish was calculated using data from the recipe file of the USDA’s Nutrient Data Base for Individual Food Intake Surveys. 

Source: U.S. EPA (2002). 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-29. Per Capita Distributions of Fish (finfish and shellfish) Intake (g/day), as Prepareda 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

5,182 

2,332 

2,654 

10,168 

1.6 (1.2–1.9) 

4.3 (3.4–5.1) 

4.8 (4.0–5.6) 

3.9 (3.3–4.4) 

0.0 (0.0–0.5) 

5.1 (2.8–7.9) 

11.8 (5.7–16.8) 

4.9 (2.6–6.3) 

5.8 (4.4–10.2) 

23.9 (21.8–28.6) 

32.7 (26.7–40.1) 

23.8 (22.1–27.5) 

40.0 (33.7–52.0) 

82.9 (75.2–111.2) 

79.4 (74.2–87.0) 

77.1 (74.3–85.2) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

5,277 

2,382 

2,780 

10,439 

2.1 (1.6–2.6) 

5.7 (4.8–6.6) 

7.4 (6.3–8.5) 

5.3 (4.7–6.0) 

0.0 (0.0–0.6) 

10.4 (9.2–12.4) 

23.6 (19.7–28.1) 

9.3 (7.1–10.9) 

6.6 (4.4–10.4) 

38.6 (33.7–49.0) 

56.6 (52.3–57.2) 

37.1 (32.1–40.3) 

60.8 (42.7–74.2) 

112.7 (91.5–125.1) 

112.3 (107.5–130.1) 

107.1 (97.1–125.1) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,391 

1,670 

1,005 

363 

9,596 

10,459 

4,714 

5,434 

20,607 

1.5 (1.2–1.8) 

2.1 (1.4–2.9) 

3.0 (2.2–3.8) 

3.4 (1.6–5.3) 

5.5 (4.9–6.0) 

1.8 (1.5–2.1) 

5.0 (4.4–5.6) 

6.0 (5.2–6.7) 

4.6 (4.2–5.0) 

0.1 (0.00–1.0) 

0.0 (0.0–0.6) 

1.4 (0.5–5.5) 

0.0 (0.0–1.5) 

11.7 (9.9–14.7) 

0.0 (0.0–0.0) 

8.6 (5.3–10.4) 

17.4 (13.9–22.1) 

6.6 (5.3–8.5) 

5.1 (4.1–6.2) 

5.9 (3.2–12.7) 

18.2 (14.8–21.1) 

31.1* (5.2–29.2) 

38.0 (34.7–43.0) 

6.0 (5.5–9.5) 

31.7 (28.6–36.8) 

42.7 (37.1–52.8) 

29.7 (28.1–31.6) 

38.7 (32.9–43.6) 

60.9* (51.0–86.0) 

69.5* (56.0–75.1) 

81.2* (42.0–117.0) 

105.1 (91.5–113.5) 

51.7 (39.4–61.2) 

98.9 (85.5–125.1) 

104.2 (91.0–112.0) 

91.0 (82.6–100.1) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

5,182 

2,332 

2,654 

10,168 

3.6 (3.0–4.2) 

7.0 (6.1–7.9) 

10.9 (9.6–12.1) 

7.6 (6.9–8.3) 

10.8 (8.1–13.5) 

27.9 (24.3–28.2) 

42.0 (38.4–42.5) 

28.1 (27.9–29.2) 

28.1 (24.3–31.0) 

48.1 (42.6–53.7) 

63.3 (57.8–66.3) 

49.6 (46.6–52.4) 

61.3 (51.2–70.5) 

97.0 (86.6–137.6) 

128.5 (120.5–138.3) 

106.6 (95.2–119.2) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

5,277 

2,382 

2,780 

10,439 

4.3 (3.6–5.1) 

9.4 (8.2–10.6) 

11.9 (10.5–13.2) 

8.9 (8.1–9.8) 

11.8 (8.4–14.0) 

36.6 (28.0–43.1) 

47.1 (42.2–54.5) 

34.2 (28.2–38.5) 

29.1 (26.7–31.4) 

72.8 (58.8–82.8) 

71.4 (64.4–81.3) 

63.3 (59.0–73.2) 

84.4 (77.0–113.3) 

127.4 (116.3–153.6) 

140.1 (114.9–149.6) 

122.8 (109.4–139.6) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,391 

1,670 

1,005 

363 

9,596 

10,459 

4,714 

5,434 

20,607 

3.7 (3.2–4.3) 

4.2 (3.5–4.9) 

5.5 (4.2–6.7) 

4.7 (2.9–6.4) 

9.8 (9.0–10.6) 

4.0 (3.5–4.5) 

8.2 (7.4–9.1) 

11.3 (10.3–12.3) 

8.3 (7.6–8.9) 

11.1 (10.4–12.6) 

13.1 (9.7–17.0) 

13.9 (9.8–20.6) 

0.0 (0.0–6.9) 

38.6 (36.6–41.5) 

10.8 (10.1–13.5) 

28.2 (27.9–34.3) 

42.7 (42.0–45.7) 

29.2 (28.2–32.1) 

27.9 (24.4–29.1) 

28.7 (27.6–33.8) 

38.5 (30.8–50.3) 

24.2* (7.8–71.5) 

63.8 (58.8–68.8) 

28.2 (27.9–29.8) 

56.6 (54.5–68.9) 

65.1 (63.9–68.0) 

55.8 (54.7–56.9) 

59.8 (52.4–71.3) 

78.6* (49.2–84.4) 

102.3* (84.4–113.6) 

107.8* (68.4–118.9) 

126.3 (117.3–140.1) 

79.0 (63.0–98.8) 

115.7 (98.5–143.8) 

136.9 (125.6–140.3) 

114.6 (108.9–120.8) 

Page Exposure Factors Handbook 

10-84 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-29. Per Capita Distributions of Fish (finfish and shellfish) Intake (g/day), as Prepareda (continued) 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

5,182 

2,332 

2,654 

10,168 

5.2 (4.4–5.9) 

11.3 (10.0–12.7) 

15.6 (14.0–17.3) 

11.4 (10.5–12.4) 

18.9 (15.3–21.1) 

41.2 (36.6–46.2) 

56.2 (52.7–60.6) 

42.2 (39.0–45.7) 

37.5 (30.0–41.7) 

66.3 (61.0–73.0) 

82.9 (75.6–88.0) 

66.8 (63.2–71.4) 

80.2 (72.6–83.0) 

143.4 (128.0–148.4) 

158.9 (141.6–170.6) 

140.8 (128.5–148.4) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

5,277 

2,382 

2,780 

10,439 

6.4 (5.5–7.3) 

15.1 (13.6–16.6) 

19.2 (17.6–20.9) 

14.3 (13.4–15.2) 

21.1 (15.7–24.9) 

58.4 (51.0–70.3) 

67.7 (65.0–72.2) 

55.9 (51.0–59.4) 

42.2 (34.0–52.5) 

89.1 (85.6–97.5) 

98.6 (92.7–105.1) 

86.1 (84.3–89.7) 

114.3 (98.4–130.6) 

177.2 (163.0–185.3) 

167.5 (157.0–193.3) 

162.6 (155.8–178.7) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,391 

1,670 

1,005 

363 

9,596 

10,459 

4,714 

5,434 

20,607 

5.2 (4.6–5.8) 

6.3 (5.3–7.3) 

8.5 (6.9–10.0) 

8.1 (5.4–10.8) 

15.3 (14.3–16.2) 

5.8 (5.2–6.5) 

13.2 (12.2–14.2) 

17.3 (16.0–18.6) 

12.8 (12.1–13.6) 

18.9 (15.3–21.3) 

23.9 (21.1–27.0) 

28.1 (24.9–31.4) 

18.6 (7.0–40.9) 

56.2 (55.4–58.3) 

19.4 (17.2–21.2) 

50.0 (45.3–56.2) 

61.1 (56.6–64.2) 

48.2 (46.2–49.9) 

35.3 (31.1–39.5) 

39.6 (34.3–51.5) 

60.3 (53.4–74.2) 

73.8* (29.2–89.8) 

86.1 (84.3–87.5) 

38.2 (36.6–42.1) 

82.9 (76.2–86.1) 

90.5 (86.5–93.2) 

79.0 (74.6–83.3) 

72.2 (66.7–81.4) 

107.8* (91.6–130.6) 

122.2* (106.8–131.9) 

142.3* (107.9–200.4) 

162.6 (155.8–171.0) 

96.5 (83.0–114.3) 

162.6 (147.2–176.2) 

162.7 (158.4–170.6) 

153.2 (145.9–160.9) a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval (BI); percentile intervals were estimated using the percentile bootstrap method with 

1,000 bootstrap replications. 

* The sample size does not meet minimum reporting requirements as described in the “Third Report on 

Nutrition Monitoring in the United States” (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-85 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-30. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepareda 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

4,879 

2,275 

2,569 

9,723 

56 (46–66) 

67 (53–81) 

72 (58–85) 

66 (58–75) 

0.0 (0.0–3.4) 

75 (40–107) 

184 (75–247) 

80 (44–104) 

208 (162–268) 

380 (306–435) 

491 (369.3–606.2) 

398 (364–435) 

1,516 (1,305–1,801) 

1,329 (1,238–2,021) 

1,339 (1,133–1,462) 

1,352 (1,222–1,528) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

4,994 

2,369 

2,764 

10,127 

65 (52–78) 

72 (60–83) 

88 (75–101) 

75 (67–84) 

0.0 (0.0–17) 

131 (101–170) 

272 (212–321) 

131 (107–181) 

279 (179–384) 

481 (425–574) 

666 (540–712) 

504 (455–560) 

1,767 (1,470–1,888) 

1,350 (1,228–1,729) 

1,378 (1,260–1,508) 

1,470 (1,378–1,568) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,112 

1,553 

975 

360 

9,432 

9,873 

4,644 

5,333 

19,850 

82.9(67–99) 

59.3 (39–79) 

53.3 (42–64) 

49.5(23–76) 

74 (67–82) 

61 (52–70) 

69 (61–78) 

79 (69–90) 

71 (65–77) 

0.0 (0.0–56) 

0.0 (0.0–5.3) 

0.0 (0.0–78) 

0.0 (0.0–33) 

158 (125–198) 

0.0 (0.0–0.0) 

104 (72–139) 

236 (188–284) 

106 (87–128) 

284 (240–353) 

178 (88–402) 

312 (253–390) 

213* (106–390) 

502 (452–567) 

230 (187–283) 

431 (390–476) 

557 (493.7–666) 

451 (424–484) 

2,317 (1,736–2,463) 

1,662* (1,433–2,335) 

1,237* (950–1,521) 

1,186* (600–2,096) 

1,353 (1,238–1,511) 

1,689 (1,470–1,805) 

1,335 (1,238–1,684) 

1,351 (1,260–1,462) 

1,432 (1,325–1,521) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

4,879 

2,275 

2,569 

9,723 

147 (125–168) 

114 (98–129) 

166 (147–185) 

139 (127–150) 

381 (324–506) 

423 (365–485) 

620 (567–658) 

501 (465–534) 

1,028 (908–1,149) 

768 (650–881) 

950 (900–1,042) 

892 (847–923) 

2,819 (2,481–2,908) 

1,648 (1,428–2,177) 

2,022 (1,899–2,683) 

2,151 (1,858–2,484) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

4,994 

2,369 

2,764 

10,127 

154 (132–176) 

118 (104–132) 

149 (133–166) 

136 (125–147) 

426 (357–494) 

444 (368–547) 

568 (504–673) 

494 (445–543) 

1,081 (975–1,293) 

880 (760–954) 

889 (831–990) 

908 (868–954) 

2,678 (2,383–3,073) 

1,643 (1,454–1,819) 

1,859 (1,725–2,011) 

1,965 (1,817–2,247) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,112 

1,553 

975 

360 

9,432 

9,873 

4,644 

5,333 

19,850 

209 (181–237) 

150 (123–177) 

109 (84–133) 

75 (46–103) 

137 (126–147) 

150 (134–167) 

116 (104–128) 

158 (144–173) 

137 (128–147) 

614 (525–696) 

416 (326–546) 

338 (179–413) 

0.0 (0.0–124) 

527 (501–575) 

413 (366–476) 

440 (389–488) 

601 (562–642) 

497 (480–517) 

1,537 (1,340–1,670) 

1,055 (969–1,275) 

821 (629–1,034) 

381* (132–951) 

881 (840–945) 

1,037(1,002–1,163) 

830 (750–920) 

921 (882–977) 

903 (869–938) 

3,447 (3,274–3,716) 

2,800* (2,021–3,298) 

1,902* (1,537–2,366) 

1,785* (1,226–2,342) 

1,798 (1,708–1,971) 

2,692 (2,481–2,823) 

1,651.83 (1,487–1,793) 

1,975.67 (1,785–2,118) 

2,014.52 (1,947–2,158) 

Page Exposure Factors Handbook 

10-86 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-30. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepareda 

(continued) 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

4,879 

2,275 

2,569 

9,723 

203 (178–227) 

181 (158–204) 

238 (212–263) 

205 (188–221) 

693 (929–1,408) 

641 (641–879) 

812 (797–956) 

731 (797–912) 

1,344 (1,224–1,489) 

1,040 (910–1,226) 

1,265 (1,165–1,353) 

1,211 (1,128–1,256) 

3,297 (2,823–3,680) 

2,292 (2,096–2,494) 

2,696 (2,247–2,974) 

2,651 (2,358–2,823) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

4,994 

2,369 

2,764 

10,127 

219 (252–356) 

190 (219–263) 

237 (225–277) 

211 (240–279) 

745 (583–881) 

756 (689–851) 

849 (812–920) 

792 (727–884) 

1,470 (1,282–1,775) 

1,165 (1,060–1,239) 

1,253 (1,183–1,282) 

1,239 (1,201–1,282) 

3,392 (2,893–3,954) 

2,238 (2,045–2,492) 

2,310 (2,079–2,438) 

2,537 (2,324–2,679) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,112 

1,553 

975 

360 

9,432 

9,873 

4,644 

5,333 

19,850 

292 (260–326) 

209 (176–242) 

162 (133–191) 

124 (83–165) 

211 (197–225) 

211 (191–231) 

185 (170–200) 

238 (219–256) 

208 (196–220) 

1,057 (931–1,232) 

780 (644–842) 

570 (476–664) 

261 (110–600) 

779 (743–816) 

713 (652–780) 

714 (645–803) 

836 (767–883) 

762 (737–790) 

1,988 (1,813–2,147) 

1,357 (1,173–1,451) 

1,051 (991–1,313) 

1,029* (390–1,239) 

1,198 (1,165–1,238) 

1,429 (1,344–1,499) 

1,139 (1,014–1,228) 

1,261 (1,185–1,314) 

1,227 (1,198–1,251) 

4,089 (3,733–4,508) 

3,350* (2,725–4,408) 

2,305* (1,908–2,767) 

2,359* (2,096–2,676) 

2,327 (2,198–2,438) 

3,354 (3,224–3,458) 

2,290 (2,082–2,476) 

2,386 (2,158–2,672) 

2,539 (2,476–2,679) a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 

1,000 bootstrap replications. 

* The sample size does not meet minimum reporting requirements as described in the Third Report on 

Nutrition Monitoring in the United States (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-87 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-31. Per Capita Distribution of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish Weighta 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

5,182 

2,332 

2,654 

10,168 

2.3 (1.8–2.8) 

5.8 (4.6–6.9) 

6.4 (5.3–7.4) 

5.2 (4.5–5.9) 

0.0 (0.0–0.2) 

6.3 (4.7–11.4) 

17.7 (8.9–23.6) 

7.3 (3.8–11.9) 

13.1 (9.9–16.4) 

32.4 (27.7–38.0) 

44.9 (37.4–55.4) 

31.9 (28.3–37.4) 

58.8 (45.8–86.4) 

109.8 (100.4–154.5) 

108.8 (95.4–123.9) 

102.1(95.5–114.0) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

5,277 

2,382 

2,780 

10,439 

3.0 (2.3–3.7) 

7.9 (6.7–9.1) 

10.2 (8.6–11.7) 

7.4 (6.6–8.3) 

0.0 (0.0–0.2) 

15.6 (13.2–19.8) 

32.5 (27.3–37.2) 

14.6 (12.6–17.7) 

13.5 (10.2–17.0) 

49.7 (45.7–66.4) 

73.5 (66.2–77.1) 

49.3 (45.6–53.2) 

79.0 (55.2–97.9) 

151.2 (126.4–183.4) 

165.9 (147.7–190.7) 

147.8 (132.3–183.4) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,391 

1,670 

1,005 

363 

9,596 

10,459 

4,714 

5,434 

20,607 

2.2 (1.8–2.6) 

3.0 (1.9–4.1) 

4.3 (3.2–5.4) 

4.6 (2.2–6.9) 

7.5 (6.8–8.3) 

2.6 (2.2–3.1) 

6.8 (6.0–7.6) 

8.1 (7.1–9.2) 

6.3 (5.7–6.9) 

0.1 (0.0–1.5) 

0.0 (0.0–0.5) 

2.3 (0.1–7.7) 

0.0 (0.0–1.9) 

17.4 (14.3–21.6) 

0.0 (0.0–0.0) 

13.0 (8.6–15.6) 

24.8 (18.8–28.6) 

11.7 (8.4–13.7) 

12.2 (10.3–14.1) 

13.1 (4.8–20.1) 

25.8 (21.0–28.9) 

19.3* (13.3–36.8) 

49.6 (46.9–55.4) 

13.1 (11.9–14.8) 

43.6 (37.8–47.4) 

56.5 (48.9–69.7) 

41.1 (37.9–43.7) 

52.5 (45.6–61.5) 

78.5* (63.8–110.5) 

94.8* (83.1–109.5) 

109.2* (57.7–154.5) 

143.4 (125.3–156.8) 

73.7 (51.5–86.4) 

135.9 (121.0–167.0) 

144.3 (121.7–156.8) 

123.9 (114.0–138.8) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

5,182 

2,332 

2,654 

10,168 

5.2 (4.5–6.0) 

9.0 (7.8–10.1) 

13.7 (12.0–15.4) 

9.8 (8.9–10.6) 

18.8 (13.5–21.9) 

37.5 (31.0–37.9) 

51.4 (49.0–55.4) 

37.8 (37.3–40.2) 

40.1 (37.9–47.7) 

61.7 (55.8–71.2) 

80.4 (76.9–82.6) 

64.7 (59.2–67.7) 

81.3 (67.0–98.4) 

120.6 (116.5–132.5) 

155.6 (148.7–179.2) 

128.5 (119.4–142.9) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

5,277 

2,382 

2,780 

10,439 

6.0 (4.9–7.0) 

12.0 (10.5–13.5) 

15.0 (13.3–16.7) 

11.5 (10.4–12.5) 

17.0 (13.0–21.4) 

41.7 (37.8–56.3) 

58.0 (53.5–68.3) 

41.3 (37.8–49.7) 

39.7 (35.9–41.1) 

90.2 (75.7–106.7) 

90.7 (85.4–97.3) 

82.9 (75.7–96.8) 

113.3 (106.3–140.3) 

151.5 (134.9–192.5) 

168.8 (157.1–186.9) 

152.3 (136.6–166.9) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,391 

1,670 

1,005 

363 

9,596 

10,459 

4,714 

5,434 

20,607 

5.5 (4.8–6.2) 

5.6 (4.6–6.5) 

7.6 (5.9–9.4) 

6.1 (3.7–8.4) 

12.4 (11.5–13.4) 

5.59 (4.9–6.3) 

10.5 (9.4–11.6) 

14.3 (13.0–15.6) 

10.6 (9.8–11.4) 

19.8 (16.6–23.1) 

18.9 (14.2–24.3) 

25.3 (16.4–34.5) 

0.0 (0.0–9.3) 

48.9 (47.1–51.2) 

18.7 (16.1–19.7) 

37.9 (37.5–41.3) 

55.7 (53.1–57.9) 

38.4 (37.8–40.6) 

39.4 (37.7–41.4) 

38.4 (37.9–41.6) 

56.5 (45.3–67.1) 

29.5* (11.6–90.7) 

80.7 (77.8–83.5) 

40.2 (39.6–40.4) 

75.3 (67.3–83.5) 

83.4 (80.7–85.8) 

74.9 (69.9–75.6) 

82.3 (73.0–95.4) 

99.8* (62.8–111.4) 

131.8* (110.3–148.7) 

135.6* (92.0–177.1) 

150.8 (139.7–164.3) 

103.4 (82.6–123.5) 

137.1 (122.0–151.0) 

166.0 (155.5–178.0) 

139.2 (131.3–148.3) 

Page Exposure Factors Handbook 

10-88 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-31. Per Capita Distribution of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish Weighta 

(continued) 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

5,182 

2,332 

2,654 

10,168 

7.5 (6.5–8.5) 

14.7 (13.0–16.5) 

20.1 (17.9–22.2) 

15.0 (13.7–16.2) 

28.5 (25.4–34.0) 

53.6 (46.6–58.8) 

73.4 (67.7–77.3) 

56.2 (51.0–59.2) 

55.2 (49.0–59.2) 

85.2 (77.3–94.6) 

104.0 (96.7–112.1) 

86.3 (81.2–93.2) 

103.9 (95.1–126.2) 

189.9 (165.1–197.1) 

213.7 (190.1–221.6) 

185.7 (162.6–187.2) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

5,277 

2,382 

2,780 

10,439 

9.0 (7.6–10.3) 

19.9 (18.0–21.7) 

25.2 (23.0–27.3) 

18.9 (17.7–20.1) 

31.5 (24.6–37.5) 

77.0 (65.8–88.8) 

89.7 (86.5–94.2) 

73.5 (66.6–80.5) 

56.5 (49.0–69.9) 

118.6 (110.7–127.1) 

130.7 (125.8–135.5) 

113.4 (110.7–118.6) 

165.2 (141.6–177.4) 

242.7 (224.3–254.9) 

226.5 (207.3–278.3) 

219.3 (204.8–236.5) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,391 

1,670 

1,005 

363 

9,596 

10,459 

4,714 

5,434 

20,607 

7.7 (6.9–8.6) 

8.5 (7.1–10.0) 

12.0 (9.7–14.2) 

10.6 (7.0–14.2) 

19.9 (18.7–21.1) 

8.2 (7.3–9.2) 

17.3 (15.9–18.7) 

22.4 (20.7–24.1) 

16.9 (15.9–17.9) 

32.6 (27.6–34.0) 

32.6 (27.0–37.9) 

43.4 (36.7–50.8) 

29.3 (9.4–48.7) 

74.8 (71.7–75.7) 

29.0 (27.6–32.6) 

64.6 (57.0–73.5) 

80.6 (75.0–85.3) 

63.5 (59.5–66.2) 

51.0 (46.3–56.7) 

56.4 (49.6–69.8) 

87.4 (69.6–102.6) 

83.5* (42.3–114.5) 

111.4 (110.0–114.0) 

56.3 (52.2–56.7) 

107.7 (99.2–113.6) 

115.3 (111.7–122.2) 

102.3 (97.9–107.6) 

100.5 (89.1–111.4) 

144.4* (117.4–183.4) 

170.7* (147.9–176.8) 

192.5* (120.5–266.0) 

215.7 (197.1–228.5) 

127.2 (118.2–149.5) 

211.3 (197.1–242.3) 

215.7 (208.3–227.6) 

198.2 (190.7–208.8) a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 

1,000 bootstrap replications. 

* The sample size does not meet minimum reporting requirements as described in the Third Report on 

Nutrition Monitoring in the United States (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-89 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-32. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish Weighta 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

4,879 

2,275 

2,569 

9,723 

83 (69–96) 

91 (71–110) 

96 (78–113) 

91 (79–103) 

0.0 (0.0–1.6) 

107 (57–145) 

250 (123–322) 

117 (63–165) 

443 (269–572) 

482 (403–538) 

655 (485–776) 

535 (485–613) 

2,179 (1,866–2,345) 

1,818 (1,633–2,767) 

1,822 (1,515–1,909) 

1,871 (1,629–2,025) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

4,994 

2,369 

2,764 

10,127 

95 (76–113) 

99 (84–115) 

121 (102–140) 

106 (94–117) 

0.0 (0.0–1.7) 

201 (151–254) 

378 (317–429) 

208 (165–272) 

534 (371–605) 

623 (558–810) 

891 (754–974) 

697 (629–782) 

2,351 (1,920–2,501) 

1,910 (1,760–2,221) 

1,963 (1,731–2,132) 

2,034 (1,856–2,221) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,112 

1,553 

975 

360 

9,432 

9,873 

4,644 

5,333 

19,850 

124 (102–146) 

84 (55–112) 

77 (60–94) 

65 (30–100) 

102 (92–112) 

89 (76–101) 

95 (83–107) 

108 (94–122) 

98 (90–107) 

0.0 (0.0–83) 

0.0 (0.0–1.4) 

20 (0.0–116) 

0.0 (0.0–23) 

236 (183–277) 

0.0 (0.0–0.0) 

150 (115–195) 

322 (250–379) 

159 (131–198) 

712 (599–784) 

354 (116–685) 

477 (411–618) 

285* (167–491) 

669 (597–749) 

485 (411–557) 

558 (506–623) 

751 (653.97–870) 

631 (590–675) 

3,091 (2,495–3,475) 

2,322* (1,856–2,994) 

1,610* (1,358–2,203) 

1,542* (760–2,767) 

1,886 (1,700–2,049) 

2,246 (1,987–2,495) 

1,893 (1,683–2,221) 

1,868 (1,709–1,941) 

1,943 (1,816–2,086) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

4,879 

2,275 

2,569 

9,723 

212 (183–242) 

146 (126–166) 

209 (185–233) 

181 (167–196) 

592 (508–785) 

557 (463–632) 

802 (757–844) 

657 (601–718) 

1,532 (1,418–1,703) 

995 (874–1,078) 

1,184 (1,132–1,281) 

1,158 (1,094–1,216) 

3,708 (3,276–4,295) 

2,056 (1,848–2,330) 

2,464 (2,282–2,820) 

2,716 (2,382–3,051) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

4,994 

2,369 

2,764 

10,127 

214 (183–244) 

150 (132–168) 

187 (167–208) 

175 (161–189) 

609 (480–808) 

576 (461–675) 

713 (658–851) 

649 (575–711) 

1,542 (1,380–1,887) 

1,113 (963–1,226) 

1,138 (1,103–1,213) 

1,205 (1,127–1,233) 

3,603 (3,212–4,131) 

1,990 (1,782–2,317) 

2,275 (1,993–2,495) 

2,545 (2,314–2,705) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

4,112 

1,553 

975 

360 

9,432 

9,873 

4,644 

5,333 

19,850 

309 (270–348) 

198 (161–235) 

153 (117–189) 

98 (58–137) 

173 (160–186) 

213 (190–237) 

148 (132–163) 

199 (181–217) 

178 (167–190) 

1,108 (984–1,332) 

600 (474–733) 

481 (361–609) 

0.0 (0.0–177) 

672 (651–732) 

606 (517–688) 

568 (502–630) 

767 (718–828) 

651 (620–675) 

2,314 (2,097–2,481) 

1,481 (1,310–1,549) 

1,251 (808–1,390) 

460* (197–1,079) 

1,115 (1,078–1,182) 

1,543 (1,491–1,670) 

1,052 (973–1,184) 

1,156 (1,115–1,214) 

1,178 (1,134–1,226) 

4,608 (4,301–5,354) 

3,684* (2,458–4,353) 

2,381* (2,162–3,207) 

2,148* (1,648–3,901) 

2,157 (2,024–2,412) 

3,694 (3,318–4,065) 

2,023 (1,925–2,197) 

2,389 (2,273–2,546) 

2,587 (2,454–2,705) 

Page Exposure Factors Handbook 

10-90 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-32. Per Capita Distribution of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish 

Weighta (continued) 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

4,879 

2,275 

2,569 

9,723 

295 (261–330) 

237 (206–267) 

305 (272–338) 

272 (251–294) 

1,046 (885–1,262) 

834.58 (771–981) 

1,065.15 (98–1,200) 

970.64 (906–1,040) 

2,03,8 (1,853–2,251) 

1,362 (1,181–1,556) 

1,568 (1,472–1,671) 

1,566 (1,511–1,633) 

4,548 (4,117–4,977) 

3,113 (2,767,–3,361) 

3,071 (2,716–3,941) 

3,566 (3,270–3,782) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

4,994 

2,369 

2,764 

10,127 

308 (273–344) 

249 (226–272) 

309 (282–335) 

281 (264–297) 

1,122 (774–1,310) 

982 (908–1,154) 

1,128 (1,078–1,206) 

1,058 (962–1,201) 

2,136 (1,856–2,371) 

1,533 (1,407–1,619) 

1,605 (1,534–1,731) 

1,644 (1,559–1,731) 

4,518 (4,055–5,465) 

3,011 (2,820–3,349) 

2,821 (2,587–3,204) 

3,369 (3,204–3,680) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

4,112 

1,553 

975 

360 

9,432 

433 (385–482) 

282 (235–328) 

231 (186–275) 

163 (107–219) 

275 (258–292) 

1,842 (1,555–1,957) 

1,045 (744.58–1,219) 

824 (657–952) 

406 (145–756) 

1,017 (975–1,065) 

2,964 (2,790–3,194) 

1,854 (1,638–2,175) 

1,531 (1,362–1,850) 

1,272* (558–1,500) 

1,549 (1,481–1,591) 

5,604 (5,231–6,135) 

4,371* (3,433–5,814) 

3,651* (2,745–3,795) 

3,544* (2,767–3,946) 

3,060 (2,771–3,204) 

14 and under 

15 to 44 

45 and older 

All ages 

9,873 

4,644 

5,333 

19,850 

302 (274–330) 

243 (223–262) 

307 (283–331) 

276 (261–292) 

1,072 (961–1,162) 

938 (878–1,019) 

1,112 (1,002–1,168) 

1,013 (976–1,052) 

2,089 (1,987–2,207) 

1,451 (1,342–1,602) 

1,591 (1,517–1,685) 

1,613 (1,561–1,651) 

4,539 (4,391–5,108) 

3,094 (2,788–3,349) 

3,014 (2,714–3,226) 

3,457 (3,349–3,680) a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 

1,000 bootstrap replications. 

* The sample size does not meet minimum reporting requirements as described in the Third Report on 

Nutrition Monitoring in the United States (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-91 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-33. Consumer-Only Distribution of Fish (finfish and shellfish) Intake (g/day), as Prepareda 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

445 

325 

449 

1,219 

32.7 (26.8–36.6) 

55.4 (45.9–64.8) 

49.0 (44.3–53.6) 

49.4 (44.5–54.3) 

79.9 (77.1–103.9) 

125.9 (117.0–157.8) 

122.8 (118.7–128.0) 

122.7 (117.0–126.6) 

111.0 (103.0–163.5) 

189.4 (154.2–259.9) 

158.3 (151.3–165.8) 

163.2 (151.5–193.8) 

185.4 (163.5–384.3) 

341.4 (260.2–853.4) 

284.7 (241.2–308.5) 

320.6 (260.2–345.2) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

442 

361 

553 

1,356 

41.7 (34.9–48.4) 

66.6 (59.7–73.6) 

65.8 (59.0–72.6) 

62.9 (57.8–67.9) 

121.5 (85.3–148.4) 

165.0 (158.8–171.0) 

154.3 (148.1–174.0) 

158.2(148.4–165.8) 

161.9 (138.6–229.2) 

226.3 (194.2–250.2) 

214.4 (200.2–222.3) 

215.4 (202.4–226.5) 

260.8 (260.2–292.5) 

336.9 (327.0–402.9) 

400.2 (300.8–571.0) 

335.9 (316.5–437.1) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

442 

147 

107 

28 

1,633 

887 

686 

1,002 

2,575 

27.1 (23.2–31.1) 

43.5 (31.8–55.2) 

49.0 (39.4–58.5) 

75.8* (58.9–92.7) 

59.2 (54.9–63.4) 

36.8 (32.5–41.1) 

61.3 (56.4–66.2) 

57.3 (51.9–62.7) 

56.3 (52.5–60.0) 

72.6 (65.0–79.0) 

121.6* (82.5–187.3) 

126.6* (103.9–148.4) 

158.5* (151.1–171.0) 

150.2 (141.8–154.2) 

103.1 (75.5–120.7) 

157.8 (150.3–163.5) 

141.1 (127.6–151.0) 

145.3 (138.6–151.3) 

95.6 (87.2–109.6) 

186.7* (114.8–260.2) 

149.9* (134.6–192.7) 

167.8* (158.8–484.4) 

201.0 (181.9–216.6) 

146.8 (114.8–167.4) 

217.1 (181.8–253.2) 

182.5 (170.5–200.1) 

188.8 (178.5–211.9) 

159.0* (136.1–260.2) 

260.4* (172.1–261.3) 

307.1* (192.7–384.3) 

371.6* (171.0–484.4) 

338.2 (308.5–345.2) 

260.0 (250.2–292.5) 

342.6 (321.1–484.4) 

306.9 (261.8–345.5) 

332.9 (308.5–361.3) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

670 

412 

588 

1,670 

48.7 (43.7–53.7) 

71.0 (66.2–75.7) 

82.3 (75.9–88.6) 

72.2 (68.6–75.8) 

98.1 (93.3–112.6) 

158.5 (128.0–170.8) 

153.3 (140.1–166.1) 

146.3 (140.3–158.7) 

135.9 (112.6–162.2) 

181.5 (167.4–202.8) 

203.5 (181.2–252.5) 

181.6 (169.0–201.6) 

196.2 (162.2–238.4) 

286.7 (234.6–293.2) 

362.3 (275.4–485.4) 

286.6 (269.5–293.2) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

677 

412 

623 

1,712 

59.5 (51.3–67.7) 

99.1 (91.3–106.9) 

90.0 (84.9–95.1) 

88.7 (83.7–93.7) 

144.6 (113.3–168.7) 

186.1 (174.7–199.5) 

179.8 (167.3–200.1) 

178.2 (170.0–181.2) 

168.8 (167.0–227.2) 

232.5 (214.0–254.4) 

224.4 (207.2–280.1) 

226.1 (214.4–232.7) 

265.1 (170.0–291.6) 

403.8 (321.5–407.2) 

306.3 (292.5–380.9) 

354.2 (315.3–403.6) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

682 

217 

122 

37 

1.978 

1,347 

824 

1,211 

3,382 

44.5 (40.6–48.5) 

59.4 (52.6–66.1) 

72.4 (59.9–84.9) 

96.9* (65.3–128.5) 

85.1 (81.3–88.9) 

54.1 (48.4–59.9) 

85.0 (79.5–90.4) 

85.8 (81.5–90.2) 

80.2 (76.6–83.8) 

90.6 (84.3–104.8) 

128.7 (111.6–158.4) 

165.3* (157.6–202.8) 

218.9* (179.6–237.8) 

168.9 (168.9–174.6) 

119.1 (112.3–144.8) 

172.0 (168.8–179.6) 

168.4 (158.7–181.2) 

168.9 (165.6–169.0) 

119.1 (102.0–142.8) 

159.2* (134.9–219.05) 

203.6* (168.8–227.2) 

237.5* (179.6–292.5) 

214.1 (195.9–227.2) 

162.3 (141.9–168.7) 

213.7 (194.3–229.7) 

218.7 (207.3–229.8) 

207.6 (197.0–214.4) 

227.6* (168.7–292.5) 

242.5* (219.0–291.6) 

245.6* (213.6–268.6) 

365.3* (229.8–428.0) 

337.2 (306.4–380.9) 

238.2 (219.0–269.4) 

343.7 (304.9–404.2) 

320.1 (299.2–485.4) 

310.2 (299.2–383.5) 

Page Exposure Factors Handbook 

10-92 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-33. Consumer-Only Distribution of Fish (finfish and shellfish) Intake (g/day), as Prepareda (continued) 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

836 

554 

751 

2,141 

54.2 (49.3–59.0) 

82.5 (74.8–90.2) 

90.5 (85.3–95.7) 

81.5 (77.3–85.7) 

112.5 (97.2–136.9) 

170.8 (151.0–184.7) 

170.5 (158.7–181.7) 

163.6 (151.3–171.0) 

155.4 (128.5–162.2) 

221.7 (197.9–260.2) 

219.8 (197.0–242.5) 

208.2 (193.8–238.4) 

237.5 (197.9–285.6) 

336.5 (294.3–345.2) 

326.0 (308.5–612.9) 

327.0 (285.6–359.6) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

836 

565 

849 

2,250 

69.1 (61.9–76.3) 

111.9 (106.0–117.9) 

106.5 (101.5–111.5) 

102.9 (99.0–106.8) 

157.0 (136.1–168.8) 

210.6 (195.0–242.5) 

210.3 (193.3–229.8) 

206.0 (192.7–219.0) 

227.5 (168.7–260.2) 

296.1 (249.7–316.5) 

271.1 (241.4–292.5) 

262.0 (251.3–285.8) 

276.0 (269.4–292.5) 

427.9 (403.6–465.6) 

392.5 (330.6–535.5) 

404.1 (380.9–428.4) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

834 

270 

172 

52 

2,634 

1,672 

1,119 

1,600 

4,391 

50.2 (46.3–54.0) 

70.6 (63.8–77.4) 

79.6 (70.4–88.7) 

104.1* (75.0–133.1) 

97.56 (93.7–101.4) 

61.7 (56.6–66.8) 

97.2 (92.1–102.4) 

98.1 (93.6–102.6) 

92.0 (88.5–95.5) 

103.1 (94.5–124.9) 

154.7 (130.0–183.2) 

167.1* (154.0–192.7) 

200.5* (167.4–242.5) 

191.8 (184.7–197.9) 

138.4 (125.1–150.1) 

195.1 (183.2–206.0) 

187.0 (184.1–198.0) 

184.5 (179.6–195.0) 

133.9 (120.7–151.8) 

218.2* (197.9–261.3) 

208.8* (205.9–257.0 

241.9* (215.7–484.4) 

253.2 (243.6–261.8) 

168.7 (162.4–232.8) 

256.0 (240.2–283.9) 

248.5 (238.00–260.2) 

249.3 (234.3–259.8) 

260.0* (195.3–293.3) 

280.9* (260.2–291.6) 

285.2* (263.8–327.0) 

451.0* (292.5–484.4) 

399.5 (359.1–407.2) 

271.4 (260.2–291.6) 

404.0 (352.4–450.4) 

381.4 (300.6–413.0) 

379.0 (340.2–413.0) a Estimates were projected from sample size to the U.S. population using 4–year combined survey weights; 

consumers only are those individuals who consumed fish at least once during the 2-day reporting period. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 

1,000 bootstrap replications. 

* The sample size does not meet minimum reporting requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-93 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-34. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepareda 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

410 

315 

432 

1,157 

1,198 (1,029–1,367) 

872 (7,13–1,032) 

736 (658–813) 

859 (776–943) 

3,167 (2,626–3,601) 

2,702 (1,777–2,484) 

1,943 (1,803–2,128) 

2,151 (1,941–2,476) 

4,921 (3,601–6,563) 

3,153 (2,484–4,067) 

2,487 (2,249–2,706) 

3,004 (2,602–3,368) 

9,106 (6,875–10,967) 

5,738 (4,584–15,930) 

3,169 (3,027–7,078) 

6,102 (5,475–7,078) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

419 

358 

548 

1,325 

1,299 (1,106–1,492) 

841 (751–931) 

782 (701–862) 

882 (814–950) 

3,556 (3,068–3,830) 

2,182 (2,057–2,318) 

1,804 (1,696–1,903) 

2,148 (2,045–2,318) 

4,495 (3,830–4,982) 

2,819 (2,539–3,241) 

2,511 (2,175–2,652) 

3,021 (2,867–3,241) 

8,714 (6,266–11,276) 

4,379 (4,057–4,931) 

4,812 (4,036–6,987) 

5,333 (4,548–6,775) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

416 

132 

101 

28 

1,599 

829 

673 

980 

2,482 

1,532 (1,320–1,743) 

1,296 (1,004–1,588) 

869 (724.60–1,013) 

1,063* (781–1,346) 

805 (748–861) 

1,251 (1,135–1,367) 

855 (778–933) 

759 (694–824) 

871 (816–926) 

4,307 (3,472–4,624) 

3,453* (2,626–4,671) 

2,030* (1,628–2,104) 

2,293* (2,096–2,577) 

2,025 (1,888–2,072) 

3,456 (3,136–3,597) 

2,136 (2,057–2,371) 

1,896 (1,739–1,983) 

2,152 (2,063–2,295) 

5,257 (4,926–5,746) 

4,675* (3,459–8,816) 

3,162* (2,104–3,601) 

2,505* (2,096–6,466) 

2,679 (2,539–2,947) 

4,681 (4,084–5,247) 

3,071 (2,675–3,478) 

2,512 (2,262–2,706) 

3,019 (2,924–3,101) 

10,644* (9,083–12,735) 

8,314* (4,684–9,172) 

4,665* (3,597–7,361) 

5,067* (2,295–6,466) 

4,930 (4,285–5,849) 

8,792 (7,361–10,967) 

5,795 (4,066–6,096) 

4,261 (3,117–6,419) 

5,839 (4,926–7,078) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

629 

403 

568 

1,600 

1,988 (1,827–2,148) 

1,147 (1,061–1,234) 

1,259 (1,159–1,360) 

1,323 (1,260–1,385) 

4,378 (3,927–4,962) 

2,404 (2,014–2,660) 

2,430 (2,258–2,627) 

2,680 (2,477–2,977) 

5,767 (5,041–6,519) 

3,151 (2,621–3,325) 

3,274 (2,699–4,029) 

3,644 (3,381–4,305) 

8,185 (6,907–8,842) 

4,774 (4,523–5,510) 

5,798 (5,365–9,297) 

5,895 (5,750–6,956) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

643 

409 

621 

1,673 

2,084 (1,842–2,326) 

1,242 (1,151–1,333) 

1,129 (1,063–1,195) 

1,337 (1,267–1,408) 

4,734 (3,911–5,307) 

2,448 (2,349–2,773) 

2,294 (2,106–2,452) 

2,745 (2,513–2,858) 

5,490 (4,944–6,628) 

2,985 (2,870–3,265) 

2,942 (2,809–3,526) 

3,636 (3,450–3,922) 

9,004 (7,432–10,962) 

4,674 (3,637–5,926) 

4,622 (4,094–4,936) 

5,908 (5,359–6,366) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

640 

203 

120 

37 

1,944 

1,272 

812 

1,189 

3,273 

2,492 (2,275–2,709) 

2,120 (1,880–2,361) 

1,427 (1,203–1,651) 

1,534* (1,063–2,004) 

1,187 (1,137–1,238) 

2,037 (1,880–2,195) 

1,195 (1,127–1,263) 

1,198 (1,135–1,261) 

1,330 (1,278–1,382) 

5,303 (4,873–5,930) 

4,950 (4,043–5,384) 

2,971* (2,858–3,741) 

3,602* (2,974–4,649) 

2,386 (2,265–2,450) 

4,646 (4,213–4,892) 

2,442 (2,349–2,660) 

2,394 (2,205–2,534) 

2,710 (2,618–2,870) 

6,762 (6,097–7,168) 

5,817* (5,333–6,596) 

4,278* (3,026–4,766) 

4,475* (3,068–4,685) 

2,998 (2,907–3,191) 

5,664 (5,384–6,093) 

3,046 (2,856–3,309) 

3,100 (2,933–3,500) 

3,637 (3,544–3,927) 

11,457* (7,432–14,391) 

8,092* (6,146–9,184) 

5,214* (4,647–5,646) 

4,982* (3,467–5,238) 

4,961 (4,523–5,510) 

8,611 (7,755–9,184) 

4,817 (3,932–5,238) 

5,436 (4,655–7,504) 

5,910 (5,646–6,711) 

Page Exposure Factors Handbook 

10-94 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-34. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), as Prepareda 

(continued) 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

779 

541 

725 

2,045 

2,183 (2,021–2,344) 

1,317 (1,184–1,451) 

1,380 (1,299–1,460) 

1,469 (1,400–1,539) 

4,786 (4,422–5,138) 

2,636 (2,385–3,051) 

2,639 (2,406–2,950) 

3,008 (2,752–3,169) 

6,218 (5,766–6,738) 

3,611 (3,225–4,584) 

3,560 (3,008–3,967) 

4,088 (3,649–4,544) 

10,395 (8,680–10,967) 

5,712 (4,952–5,849) 

5,929 (5,452–9,905) 

7,074 (6,519–8,761) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

788 

561 

842 

2,191 

2,355 (2,164–2,545) 

1,409 (1,339–1,478) 

1,311 (1,250–1,373 

1,518 (1,461–1,575) 

5,097 (4,680–5,535) 

2,770 (2,570–3,241) 

2,564 (2,501–2,801) 

3,043 (2,867–3,159) 

6,712 (6,146–7,432) 

3,490 (3,092–3,725) 

3,133 (3,050–3,584) 

4,029 (3,779–4,477) 

9,182 (8,816–11,276) 

5,612 (5,163–5,926) 

4,935 (4,548–6,987) 

6,736 (6,096–7,117) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

779 

250 

164 

52 

2,585 

1,567 

1,102 

1,567 

4,236 

2,828 (2,608–3,049) 

2,375 (2,199–2,551) 

1,533 (1,384–1,682) 

1,578*(1,187–1,969) 

1,349 (1,297–1,401) 

2,271 (2,130–2,412) 

1,363 (1,292–1,435) 

1,347 (1,288–1,406) 

1,494 (1,440–1,548) 

5,734 (5,268–6,706) 

5,135 (4,684–5,816) 

3,207* (2,945–3,485) 

3,468* (2,676–4,752) 

2,641 (2,539–2,773) 

4,959 (4,647–5,450) 

2,728 (2,570–2,974) 

2,619 (2,546–2,752) 

3,021 (2,941–3,082) 

7,422 (6,907–8,393) 

6,561* (5,404–8,816) 

3,924.64* (3,485–4,764) 

4,504.25* (3,709–6,466) 

3,493 (3,258–3,628) 

6,531 (5,887–6,929) 

3,583 (3,275–3,999) 

3,265 (3,115–3,569) 

4,055 (3,816–4,218) 

13,829* (11,349–14,391) 

9,179* (8,130–10,485) 

5,624* (4,764–6,929) 

5,738* (4,752–6,466) 

5,708 (5,085–5,926) 

10,389 (8,982–10,967) 

5,694 (4,987–5,849) 

5,807 (5,073–6,987) 

6,920 (6,466–7,527) 

a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights; consumers 

only are those individuals who consumed fish at least once during the 2-day reporting period.. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 1,000 bootstrap 

replications. 

* The sample size does not meet minimum reporting requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-95 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-35. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish 

Weighta 

Age (years) N Mean (90% CI) 

90th Percentile (90% 

BI) 

95th Percentile (90% 

BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

445 

325 

449 

1,219 

47 (40–54) 

75 (62–88) 

66 (59–72) 

67 (60–74) 

117 (104–142) 

173 (155–204) 

163 (153–168) 

163 (154–170) 

172 (150–204) 

274 (204–331) 

204 (192–226) 

219 (199–267) 

243 (220–514) 

503 (381–1,144) 

394 (303–431) 

461 (381–508) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

442 

361 

553 

1,356 

60 (50–70) 

93 (82.33–103) 

91 (81.11–100) 

87 (80–95) 

158 (110–196) 

236 (226–246) 

221 (204–236) 

220 (200–232) 

199 (189–296) 

305 (272–367) 

295 (264–332) 

296 (289–333) 

381 (381–401) 

495 (444–643) 

562 (402–764) 

490 (444–595) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

442 

147 

107 

28 

1,633 

887 

686 

1,002 

2,575 

40 (35–46) 

61 (44–79) 

71 (58–83) 

100* (80–121) 

81 (75–87) 

53 (47–59) 

84 (77–91) 

78 (70–86) 

78 (72–83) 

95 (86–102) 

157* (117–250) 

173* (166–196) 

203* (197–248) 

200 (190–206) 

144 (101–173) 

205 (197–226) 

191 (170–202) 

196 (189–202) 

129 (120–142) 

248* (150–381) 

199* (173–296) 

242* (206–643) 

279 (253–301) 

196 (173–220) 

295 (253–345) 

245 (230–264) 

258 (243–289) 

205* (200–381) 

386* (221–401) 

392* (296–514) 

501* (241–643) 

506 (444–508) 

381 (367–401) 

504 (438–818) 

413 (382–505) 

468 (431–531) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

670 

412 

588 

1,670 

71 (65–77) 

91 (85–96) 

104 (94–113) 

93 (88–98) 

134 (124–155) 

188 (163–210) 

189 (170–213) 

183 (174–192) 

183 (151–205) 

241 (227–265) 

239 (222–283) 

232 (227–250) 

240 (209–379) 

376 (347–391) 

441 (359–647) 

385 (354–397) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

677 

412 

623 

1,712 

81 (69–93) 

127 (116–137) 

113 (107–120) 

114 (107–120) 

198 (162–227) 

240 (227–258) 

223 (205–252) 

227 (223–236) 

231 (225–307) 

279 (271–370) 

285 (250–324) 

277 (270–297) 

353 (244–392) 

568 (488–647) 

384 (359–480) 

483 (390–501) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

682 

217 

122 

37 

1,978 

1,347 

824 

1,211 

3,382 

66 (60–71) 

78 (67–89) 

102 (85–118) 

126* (80–171) 

108 (103–113) 

76 (68–85) 

109 (101–116) 

108 (102–114) 

103 (98–108) 

125 (114–150) 

150 (129–201) 

220* (205–265) 

281* (241–354) 

217 (213–223) 

161 (149–201) 

225 (213–233) 

206 (195–224) 

215 (207–217) 

165 (139–190) 

202* (165–317) 

262* (227–307) 

353* (241–390) 

270 (251–283) 

220 (183–227) 

270 (247–279) 

272 (250–293) 

258 (247–270) 

316* (227–390) 

350* (223–392) 

320* (277–379) 

530* (291–650) 

464 (391–487) 

335 (307–379) 

483 (390–634) 

407 (374–647) 

395 (390–487) 

Page Exposure Factors Handbook 

10-96 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-35. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (g/day), Uncooked Fish 

Weighta (continued) 

Age (years) N Mean (90% CI) 

90th Percentile (90% 

BI) 

95th Percentile (90% 

BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

836 

554 

751 

2,141 

79 (73–85) 

108 (97–118) 

117 (109–124) 

107 (101–113) 

158 (142–198) 

221 (197–236) 

215 (200–228) 

207 (196–227) 

205 (180–218) 

315 (246–378) 

270 (236–286) 

275 (246–300) 

372 (254–381) 

495 (394–508) 

444 (428–817) 

453 (394–508) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

836 

565 

849 

2,250 

96 (85–107) 

148 (139–156) 

139 (132–146) 

136 (130–142) 

225 (195–254) 

272 (253–334) 

274 (285–304) 

266 (248–289) 

336 (286–353) 

381 (323–431) 

348 (320–374) 

354 (315–379) 

390 (381–401) 

636 (595–647) 

505 (439–693) 

595 (505–643) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

834 

270 

172 

52 

2,634 

1,672 

1,119 

1,600 

4,391 

74 (69–79) 

95 (85–106) 

113 (99–127) 

136* (97–174) 

127 (122–133) 

88 (80–95) 

128 (121–135) 

127 (120–134) 

121 (116–126) 

149 (136–165) 

200 (177–235) 

227* (205–296) 

242* (206–358) 

248 (236–264) 

191 (173–201) 

255 (241–271) 

244 (230–258) 

241 (233–255) 

184 (172–223) 

313* (254–381) 

308* (271–348) 

357* (266–643) 

334 (321–349) 

249 (214–330) 

358 (330–381) 

317 (304–330) 

329 (314–343) 

363* (310–391) 

387* (381–401) 

380* (353–409) 

645* (390–650) 

519 (508–634) 

381 (367–392) 

609 (508–647) 

476 (439–593) 

507 (486–593) a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights; 

consumers only are those individuals who consumed fish at least once during the 2-day reporting period.. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 

1,000 bootstrap replications. 

* The sample size does not meet minimum reporting requirements as described in the Third Report on 

Nutrition Monitoring in the United States (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-97 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-36. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish 

Weighta 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

Freshwater and Estuarine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

410 

315 

432 

1,157 

1,776 (1,543–2,009) 

1,185 (962–1,408) 

986 (880–1,093) 

1,185 (1,071–1,299) 

4,397 (3,635–4,535) 

2,922 (2,294–3,314) 

2,655 (2,313–2,875) 

2,875 (2,654–3,266) 

6,855 (4,881–9,166) 

4,260 (3,266–5,973) 

3,263 (2,944–3,716) 

4,033 (3,516–4,406) 

11,544 (9,166–16,108) 

8,154 (6,721–20,620) 

4,630 (4,037–9,900) 

8,608 (7,087–9,900) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

419 

358 

548 

1,325 

1,895 (1,618–2,172) 

1,167 (1,034–1,299) 

1,076 (963–1,190) 

1,238 (1,140–1,336) 

4,707 (3,992–4,990) 

2,998 (2,724–3,349) 

2,467 (2,378–2,597) 

3,052 (2,735–3,221) 

5,905 (5,522–6,103) 

4,015 (3,712–4,635) 

3,447 (3,093–3,849) 

4,257 (4,039–4,473) 

12,628 (8,111–15,495) 

6,534 (5,511–8,577) 

6,574 (5,557–9,351) 

7,998 (6,539–9,351) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

416 

132 

101 

28 

1,599 

829 

673 

980 

2,482 

2,292 (2,012–2,572) 

1,830 (1,416–2,245) 

1,273 (1,082–1,464) 

1,401* (10,588–1,744) 

1,102 (1,023–1,181) 

1,834 (1,680–1,987) 

1,175 (1,067–1,282) 

1,032 (941–1,123) 

1,213 (1,136–1,291) 

5,852 (4,703–6,068) 

4,688* (3,673–5,987) 

2,777* (2,091–3,026) 

2,971* (2,743–3,692) 

2,693 (2,507–2,820) 

4,512 (4,045–4,780) 

2,978 (2,739–3,221) 

2,508 (2,383–2,797) 

2,947 (2,808–3,118) 

7,160 (6,950–7,442) 

6,207* (4,767–12,926) 

4,419* (3,026–5,522) 

3,279* (2,767–8,577) 

3,744 (3,520–4,037) 

5,986 (5,531–6,867) 

4,125 (3,815–4,841) 

3,319 (3,034–3,716) 

4,135 (4,037–4,287) 

15,600* (11,877–18,670) 

12,365* (6,763–12,926) 

5,717* (5,457–9,852) 

6,819* (3,221–8,577) 

7,140 (6,388–8,604) 

12,389 (9,852–15,495) 

8,580 (5,973–9,477) 

6,122 (4,422–8,254) 

8,587 (6,950–9,900) 

Marine 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

629 

403 

568 

1,600 

2,893 (2,679–3,107) 

1,475 (1,366–1,584) 

1,579 (1,439–1,719) 

1,732 (1,649–1,815) 

6,279 (5,286–6,554) 

3,102 (2,580–3,378) 

3,028 (2,676–3,239) 

3,558 (3,335–3,880) 

7,899 (7,033–8,478) 

3,927 (3,440–4,929) 

3,917 (3,584–4,560) 

4,878 (4,560–5,640) 

10,514 (9,322–11,981) 

6,491 (5,931–7,802) 

7,416 (6,021–12,395) 

8,618 (7,802–9,322) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

643 

409 

621 

2,885 (2,540–3,230) 

1,579 (1,458–1,701) 

1,412 (1,328–1,496) 

6,244 (5,390–6,931) 

3,063 (2,855–3,481) 

2,812 (2,589–3,072) 

8,068 (6,577–8,707) 

3,736 (3,554–4,048) 

3,724 (3,386–3,987) 

11,871 (10,365–14,194) 

7,103 (4,634–7,701) 

5,504 (5,134–6,321) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

640 

203 

120 

37 

1,944 

1,272 

812 

1,189 

3,689 (3,395–3,982) 

2,787 (2,417–3,157) 

2,020 (1,741–2,327) 

2,007* (1,302–2,712) 

1,501 (1,440–1,562) 

2,892 (2,674–3,111) 

1,527 (1,441–1,614) 

1,501 (1,416–1,586) 

7,253 (6,777–8,504) 

5,910 (4,813–7,365) 

4,224* (3,744–4,781) 

4,468* (3,880–7,802) 

2,971 (2,740–3,098) 

6,290 (5,748–6,448) 

3,093 (2,855–3,318) 

2,948 (2,664–3,232) 

9,270 (8,415–9,991) 

8,001* (6,375–8,707) 

5,195* (3,859–6,448) 

6,537* (3,991–7,802) 

3,749 (3,579–3,962) 

8,047 (7,365–8,564) 

3,872 (3,564–4,131) 

3,889 (3,494–4,030) 

16,100* (11,980–17,989) 

10,754* (8,707–12,055) 

6,839* (6,076–8,970) 

7,886* (4,661–7,958) 

6,345 (5,653–7,224) 

11,507 (10,124–12,054) 

6,898 (5,287–7,701) 

6,229 (5,409–9,759) 

Page Exposure Factors Handbook 

10-98 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-36. Consumer-Only Distributions of Fish (finfish and shellfish) Intake (mg/kg-day), Uncooked Fish 

Weighta (continued) 

Age (years) N Mean (90% CI) 

90th Percentile 

(90% BI) 

95th Percentile 

(90% BI) 

99th Percentile 

(90% BI) 

All Fish 

Females 

14 and under 

15 to 44 

45 and older 

All ages 

779 

541 

725 

2,045 

3,202 (2,983–3,421) 

1,728 (1,547–1,909) 

1,774 (1,657–1,890) 

1,962 (1,864–2,061) 

6,854 (6,596–7,365) 

3,437 (3,153–3,925) 

3,422 (3,098–3,767) 

4,005 (3,831–4,278) 

8,808 (8,451–9,408) 

5,045 (4,221–6,122) 

4,098 (3,870–4,853) 

5,792 (5,097–6,059) 

13,907 (11,461–16,108) 

8,011 (6,721–8,604) 

7,996 (6,121–15,117) 

9,878 (8,970–12,235) 

Males 

14 and under 

15 to 44 

45 and older 

All ages 

788 

561 

842 

3,314 (3,022–3,607) 

1,851 (1,754–1,947) 

1,703 (1,616–1,791) 

7,402 (6,241–7,626) 

3,599 (3,232–4,197) 

3,395 (3,118–3,638) 

8,720 (8,323–10,591) 

4,461 (3,991–5,063) 

4,253 (3,912–4,685) 

13,025 (12,278–16,803) 

7,621 (7,361–8,473) 

6,376 (5,514–9,351) 

Both Sexes 

3 to 5 

6 to 10 

11 to 15 

16 to 17 

18 and older 

14 and under 

15 to 44 

45 and older 

All ages 

779 

250 

164 

52 

2,585 

1,567 

1,102 

1,567 

4,198 (3,894–4,502) 

3,188 (2,923–3,452) 

2,199 (1,950–2,449) 

2,066* (1,529–2,603) 

1,758 (1,687–1,829) 

3,260 (3,062–3,457) 

1,790 (1,696–1,884) 

1,740 (1,650–1,830) 

8,061 (7,366–9,223) 

6,544 (6,013–8,707) 

4,387* (3,785–5,522) 

3,902* (3,536–7,892) 

3,438 (3,303–3,584) 

7,120 (6,533–7,859) 

3,549 (3,318–3,833) 

3,416 (3,227–3,572) 

10,444 (9,475–12,261) 

8,654* (7,086–11,756) 

6,234* (4,420–7,589) 

6,594* (4,661–8,577) 

4,492 (4,271–4,810) 

8,758 (8,487–9,362) 

4,806 (4,214–5,422) 

4,261 (4,017–4,497) 

17,874* (15,290–18,670) 

12,785* (10,930–13,979) 

8,345* (6,076–8,970) 

8,210* (7,892–8,577) 

7,510 (6,679–8,604) 

13,955 (12,926–15,495) 

7,839 (7,361–8,604) 

6,704 (6,195–9,351) 

a Estimates were projected from sample size to the U.S. population using 4-year combined survey weights; consumers 

only are those individuals who consumed fish at least once during the 2-day reporting period.. 

N = Sample size. 

CI = Confidence interval. 

BI = Bootstrap interval; percentile intervals (BI) were estimated using the percentile bootstrap method with 1,000 

bootstrap replications. 

* The sample size does not meet minimum reporting requirements as described in the Third Report on Nutrition 

Monitoring in the United States (FASEB/LSRO, 1995). 

Source: U.S. EPA (2002). 

Exposure Factors Handbook Page
 

September 2011 10-99 
 

 

Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics (g/kg-day, as-consumed) 

Percentiles 

State Demographic Sample Arithmetic Percent 

Characteristic Size Mean Eating 10th 50th 90th 95th 

Fish 

Connecticut 

All 420 0.41 85.1 0.00 0.25 1.00 1.32 

Sex 

Male 201 0.39 86.2 0.00 0.24 1.05 1.34 

Female 219 0.43 84.0 0.00 0.28 0.95 1.30 

Age (years)-Sex 

Category 

Child 1 to 5 26 0.32 51.7 0.00 0.05 0.95 1.47 

Child 6 to 10 26 0.51 86.7 0.00 0.35 1.13 1.29 

Child 11 to 15 21 0.27 85.6 0.00 0.19 0.52 0.89 

Female 16 to 29 17 0.67 79.9 0.00 0.31 1.06 4.02 

Female 30 to 49 85 0.46 86.7 0.00 0.28 1.00 1.36 

Female 50+ 77 0.43 90.6 0.01 0.33 0.96 1.33 

Male 16 to 29 14 0.16 70.5 0.00 0.14 0.41 0.53 

Male 30 to 49 80 0.47 92.8 0.03 0.29 1.13 1.44 

Male 50+ 63 0.35 90.5 0.02 0.22 0.86 1.11 

Unknown 11 0.09 76.1 0.00 0.02 0.37 0.45 

Race/Ethnicity 

White, Non-Hispanic 370 0.41 88.7 0.00 0.27 0.98 1.27 

Black, Non-Hispanic 9 0.05 33.5 0.00 0.00 0.17 * 

Hispanic 20 0.48 70.9 0.00 0.21 1.53 2.29 

Asian 19 0.61 59.2 0.00 0.14 1.33 3.80 

Unknown 2 0.01 43.4 0.00 0.00 * * 

Respondent 

Education 

0 to 11 years 13 0.33 100.0 0.05 0.15 1.04 1.39 

High School 87 0.38 85.3 0.00 0.22 1.00 1.14 

Some College 62 0.41 88.7 0.00 0.30 0.80 1.41 

College Grad 258 0.43 83.4 0.00 0.25 1.03 1.32 

Household Income 

($) 

0 to 20,000 40 0.39 86.4 0.00 0.26 0.96 1.45 

20,000 to 50,000 150 0.47 87.4 0.00 0.28 1.04 1.43 

>50,000 214 0.38 84.1 0.00 0.24 0.99 1.27 

Unknown 16 0.32 73.4 0.00 0.30 0.75 1.00 

Florida 

All 15,367 0.47 50.5 0.00 0.06 1.27 1.91 

Sexes 

Male 7,911 0.44 49.2 0.00 0.00 1.22 1.84 

Female 7,426 0.50 51.9 0.00 0.10 1.32 1.98 

Unknown 30 0.41 48.0 0.00 0.00 1.41 2.38 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-100 September 2011 
 

Exposure Factors Handbook Page 

September 2011 10-101 

Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics (g/kg-day, as-consumed) (continued) 

Percentiles 

State Demographic 

Characteristic 

Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating Fish 10th 50th 90th 95th 

Florida (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 1,102 0.89 37.8 0.00 0.00 2.75 3.97 

Child 6 to 10 938 0.44 39.4 0.00 0.00 1.37 2.03 

Child 11 to 15 864 0.37 42.9 0.00 0.00 1.02 1.44 

Female 16 to 29 1,537 0.44 49.1 0.00 0.00 1.10 1.75 

Female 30 to 49 2,264 0.53 56.6 0.00 0.20 1.38 1.98 

Female 50+ 2,080 0.41 56.5 0.00 0.20 1.14 1.62 

Male 16 to 29 1,638 0.44 46.1 0.00 0.00 1.11 1.72 

Male 30 to 49 2,540 0.43 53.0 0.00 0.11 1.17 1.77 

Male 50+ 2,206 0.38 54.5 0.00 0.15 0.98 1.46 

Unknown 198 0.35 54.7 0.00 0.20 0.88 1.22 

Race/Ethnicity 

White, Non-Hispanic 11,607 0.46 51.6 0.00 0.09 1.24 1.84 

Black, Non-Hispanic 1,603 0.54 48.3 0.00 0.00 1.49 2.24 

Hispanic 1,556 0.46 45.9 0.00 0.00 1.20 1.96 

Asian 223 0.58 49.5 0.00 0.00 1.33 1.78 

American Indian 104 0.63 53.4 0.00 0.15 1.95 3.61 

Unknown 274 0.43 45.9 0.00 0.00 1.17 1.71 

Respondent 

Education 

0 to 11 years 1,481 0.40 41.5 0.00 0.00 1.16 1.69 

High School 4,992 0.46 48.5 0.00 0.00 1.26 1.96 

Some College 4,791 0.49 52.3 0.00 0.11 1.30 1.98 

College Grad 4,012 0.47 54.2 0.00 0.15 1.30 1.85 

Unknown 91 0.46 41.2 0.00 0.00 1.57 2.61 

Household Income 

($) 

0 to 20,000 3,314 0.47 45.9 0.00 0.00 1.21 2.11 

20,000 to 50,000 6,678 0.48 50.4 0.00 0.06 1.28 1.92 

>50,000 3,136 0.51 57.5 0.00 0.21 1.38 1.99 

Unknown 2,239 0.35 47.6 0.00 0.00 1.09 1.57 

Minnesota 

All 837 0.31 94.4 0.02 0.18 0.62 1.07 

Sexes 

Male 419 0.26 95.3 0.02 0.16 0.58 1.06 

Female 418 0.36 93.4 0.02 0.21 0.65 1.10 

Age (years)-Sex 

Category 

Child 1 to 5 47 0.57 97.4 0.05 0.45 1.09 1.74 

Child 6 to 10 46 0.33 88.4 0.00 0.21 0.82 1.34 

Child 11 to 15 68 0.22 92.8 0.02 0.19 0.54 0.59 

Female 16 to 29 47 0.67 96.0 0.02 0.15 0.61 4.48 

Female 30 to 49 132 0.24 95.0 0.02 0.22 0.50 0.58 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 
 

 

Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics (g/kg-day, as-consumed) (continued) 

Percentiles 

State Demographic Sample Arithmetic Percent 10th 50th 90th 95th 

Characteristic Size Mean Eating Fish 

Minnesota (continued) 

Age (years)-Sex 

Category 

Female 50+ 162 0.34 94.9 0.03 0.21 0.90 1.35 

Male 16 to 29 55 0.10 92.3 0.01 0.07 0.26 0.33 

Male 30 to 49 120 0.24 96.0 0.04 0.16 0.42 0.64 

Male 50+ 155 0.24 99.8 0.05 0.19 0.53 0.68 

Unknown 5 0.00 1.6 0.00 0.00 0.00 0.00 

Race/Ethnicity 

White, Non-Hispanic 775 0.27 93.8 0.02 0.17 0.59 0.90 

Black, Non-Hispanic 1 0.00 * * * * * 

Hispanic 3 0.65 100.0 * 0.27 * * 

Asian 7 0.53 100.0 0.13 0.47 * * 

American Indian 12 2.08 100.0 0.09 0.16 * * 

Unknown 39 0.32 100.0 0.10 0.24 0.79 1.02 

Respondent 

Education 

0 to 11 years 46 0.34 86.2 0.00 0.19 1.23 1.56 

High School 234 0.29 92.9 0.02 0.17 0.65 1.11 

Some College 259 0.41 95.3 0.03 0.20 0.65 0.95 

College Grad 255 0.26 95.0 0.02 0.17 0.57 1.05 

Unknown 43 0.24 99.7 0.09 0.23 0.41 0.51 

Household Income 

($) 

0 to 20,000 87 0.40 91.0 0.03 0.20 1.20 1.61 

20,000 to 50,000 326 0.34 91.3 0.01 0.17 0.62 0.90 

>50,000 327 0.29 97.9 0.03 0.18 0.62 1.09 

Unknown 97 0.24 92.9 0.03 0.21 0.56 0.68 

North Dakota 

All 575 0.32 95.2 0.03 0.18 0.71 1.18 

Sexes 

Male 276 0.32 96.2 0.04 0.19 0.68 1.20 

Female 299 0.32 94.2 0.03 0.17 0.73 1.16 

Age (years)-Sex 

Category 

Child 1 to 5 30 0.67 94.4 0.04 0.22 1.56 3.83 

Child 6 to 10 44 0.51 92.0 0.07 0.29 1.14 1.49 

Child 11 to 15 55 0.40 97.1 0.06 0.21 1.01 1.24 

Female 16 to 29 42 0.18 89.9 0.00 0.11 0.39 0.63 

Female 30 to 49 95 0.28 98.3 0.04 0.18 0.55 0.86 

Female 50+ 99 0.38 93.4 0.02 0.16 0.99 1.47 

Male 16 to 29 36 0.22 100.0 0.04 0.13 0.45 0.56 

Male 30 to 49 90 0.22 97.8 0.04 0.18 0.45 0.54 

Male 50+ 81 0.29 94.0 0.01 0.18 0.67 1.16 

Unknown 3 0.11 31.5 0.00 0.00 * * 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-102 September 2011 
 

 

Table 10-37. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics (g/kg-day, as-consumed) (continued) 

Percentiles 

State Demographic Sample Arithmetic Percent 10th 50th 90th 95th 

Characteristic Size Mean Eating Fish 

North Dakota (continued) 

Race/Ethnicity 

White, Non-Hispanic 528 0.33 95.1 0.03 0.18 0.72 1.21 

Black, Non-Hispanic 2 0.25 100.0 * 0.25 * * 

Asian 4 0.20 100.0 * 0.18 * * 

American Indian 9 0.30 100.0 0.08 0.25 0.69 * 

Unknown 32 0.30 93.5 0.05 0.13 0.71 0.94 

Respondent 

Education 

0 to 11 years 29 0.23 86.6 0.00 0.11 0.65 0.86 

High School 138 0.42 97.3 0.04 0.20 0.89 1.56 

Some College 183 0.28 95.2 0.03 0.18 0.63 0.99 

College Grad 188 0.31 96.7 0.04 0.18 0.69 1.26 

Unknown 37 0.35 87.2 0.00 0.10 0.73 1.32 

Household Income 

($) 

0 to 20,000 51 0.52 93.7 0.02 0.17 1.79 2.55 

20,000 to 50,000 235 0.27 94.2 0.02 0.14 0.70 1.13 

>50,000 233 0.31 97.1 0.05 0.22 0.63 1.02 

Unknown 56 0.42 92.7 0.04 0.18 0.79 1.21 

*	 Percentiles cannot be estimated due to small sample size. 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-103 
 

 

Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected
 

Demographic Characteristics (g/kg-day, as-consumed)
 

State Demographic 

Characteristic 

Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating 

Fish 

Percentiles 

10th 50th 90th 95th 

Connecticut 

All 

Sex 

Age (years)-Sex 

Category 

Race/Ethnicity 

Respondent 

Education 

Household 

Income ($) 

Florida 

All 

Sexes 

Male 

Female 

Child 1 to 5 

Child 6 to 10 

Child 11 to 15 

Female 16 to 29 

Female 30 to 49 

Female 50+ 

Male 16 to 29 

Male 30 to 49 

Male 50+ 

Unknown 

White, NonHispanic 

Black, NonHispanic 

Hispanic 

Asian 

Unknown 

0 to 11 years 

High School 

Some College 

College Grad 

0 to 20,000 

20,000 to 50,000 

>50,000 

Unknown 

Male 

Female 

Unknown 

362 

175 

187 

14 

22 

18 

14 

74 

70 

10 

74 

57 

9 

331 

3 

15 

12 

1 

13 

76 

56 

217 

35 

133 

182 

12 

7,757 

3,880 

3,861 

16 

0.48 

0.45 

0.52 

0.61 

0.59 

0.32 

0.84 

0.53 

0.48 

0.23 

0.51 

0.38 

0.12 

0.46 

0.15 

0.68 

1.03 

0.01 

0.32 

0.44 

0.46 

0.51 

0.45 

0.54 

0.45 

0.44 

0.93 

0.90 

0.95 

0.85 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

0.07 

0.08 

0.05 

0.16 

0.14 

0.07 

0.11 

0.05 

0.05 

0.08 

0.11 

0.10 

0.01 

0.07 

* 

0.12 

0.09 

* 

0.05 

0.05 

0.10 

0.08 

0.08 

0.07 

0.07 

0.10 

0.19 

0.18 

0.19 

0.12 

0.32 

0.29 

0.34 

0.55 

0.47 

0.19 

0.35 

0.34 

0.37 

0.21 

0.35 

0.26 

0.04 

0.32 

0.15 

0.30 

0.48 

* 

0.15 

0.27 

0.34 

0.33 

0.32 

0.33 

0.30 

0.41 

0.58 

0.55 

0.62 

0.69 

1.09 

1.11 

1.03 

1.42 

1.15 

0.52 

1.12 

1.12 

1.03 

0.47 

1.15 

0.93 

0.39 

1.05 

* 

1.86 

1.95 

* 

0.97 

1.04 

0.85 

1.12 

1.13 

1.12 

1.06 

0.84 

1.89 

1.85 

1.94 

2.37 

1.37 

1.40 

1.35 

1.56 

1.30 

0.84 

3.10 

1.48 

1.36 

0.56 

1.46 

1.12 

* 

1.31 

* 

2.47 

4.78 

* 

1.37 

1.15 

1.43 

1.39 

1.47 

1.45 

1.31 

1.03 

2.73 

2.65 

2.78 

2.61 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-104 September 2011 
 

Exposure Factors Handbook 

September 2011 

Page 

10-105 

Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected 

Demographic Characteristics (g/kg-day, as-consumed) (continued)
 

State Demographic 

Characteristic 

Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating 

Fish 

Percentiles 

10th 50th 90th 95th 

Florida (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 

Child 6 to 10 

Child 11 to 15 

Female 16 to 29 

Female 30 to 49 

Female 50+ 

Male 16 to 29 

Male 30 to 49 

Male 50+ 

Unknown 

Race/Ethnicity 

White, NonHispanic 

Black, NonHispanic 

Hispanic 

Asian 

American Indian 

Unknown 

Respondent 

Education 

0 to 11 years 

High School 

Some College 

College Grad 

Unknown 

Household 

Income ($) 

0 to 20,000 

20,000 to 50,000 

>50,000 

Unknown 

Minnesota 

All 

Sexes 

Male 

Female 

Age (years)-Sex 

Category 

Child 1 to 5 

Child 6 to 10 

Child 11 to 15 

420 

375 

365 

753 

1,287 

1,171 

754 

1,334 

1,192 

106 

5,957 

785 

721 

110 

57 

127 

613 

2,405 

2,511 

2,190 

38 

1,534 

3,370 

1,806 

1,047 

793 

401 

392 

46 

42 

63 

2.34 

1.10 

0.85 

0.89 

0.94 

0.73 

0.96 

0.81 

0.70 

0.64 

0.88 

1.11 

1.01 

1.16 

1.17 

0.94 

0.96 

0.96 

0.93 

0.87 

1.13 

1.03 

0.95 

0.89 

0.74 

0.33 

0.28 

0.38 

0.58 

0.38 

0.24 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

0.50 

0.28 

0.20 

0.16 

0.18 

0.19 

0.16 

0.17 

0.17 

0.21 

0.18 

0.23 

0.17 

0.27 

0.21 

0.19 

0.22 

0.18 

0.18 

0.19 

0.25 

0.19 

0.19 

0.17 

0.17 

0.04 

0.04 

0.05 

0.07 

0.05 

0.03 

1.74 

0.81 

0.63 

0.55 

0.63 

0.52 

0.52 

0.53 

0.50 

0.49 

0.56 

0.73 

0.60 

0.67 

0.69 

0.67 

0.60 

0.58 

0.58 

0.57 

0.85 

0.61 

0.60 

0.56 

0.51 

0.2 

0.17 

0.22 

0.46 

0.25 

0.21 

4.67 

2.23 

1.62 

1.77 

1.86 

1.52 

1.77 

1.69 

1.41 

1.15 

1.82 

2.27 

2.08 

1.78 

3.13 

1.73 

1.86 

1.98 

1.91 

1.79 

2.69 

2.22 

1.91 

1.87 

1.61 

0.65 

0.62 

0.7 

1.1 

1.01 

0.55 

6.80 

2.97 

2.16 

2.42 

2.68 

2.05 

2.65 

2.44 

1.93 

1.55 

2.61 

3.21 

2.81 

3.29 

4.70 

2.43 

2.81 

2.83 

2.70 

2.47 

2.74 

2.99 

2.78 

2.73 

2.09 

1.08 

1.07 

1.22 

1.75 

1.36 

0.59 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 
 

Page Exposure Factors Handbook 

10-106 September 2011 

Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected 

Demographic Characteristics (g/kg-day, as-consumed) (continued)
 

State Demographic 

Characteristic 

Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating 

Fish 

Percentiles 

10th 50th 90th 95th 

Minnesota (continued) 

Age (years)-Sex 

Category 

Female 16 to 29 

Female 30 to 49 

Female 50+ 

Male 16 to 29 

Male 30 to 49 

Male 50+ 

Unknown 

Race/Ethnicity 

White, NonHispanic 

Black, NonHispanic 

Hispanic 

Asian 

American Indian 

Unknown 

Respondent 

Education 

0 to 11 years 

High School 

Some College 

College Grad 

Unknown 

Household 

Income ($) 

0 to 20,000 

20,000 to 50,000 

>50,000 

Unknown 

North Dakota 

All 

Sexes 

Male 

Female 

Age (years)-Sex 

Category 

Child 1 to 5 

Child 6 to 10 

Child 11 to 15 

Female 16 to 29 

Female 30 to 49 

Female 50+ 

Male 16 to 29 

44 

127 

150 

52 

115 

153 

1 

732 

* 

3 

7 

12 

39 

41 

219 

249 

242 

42 

77 

301 

321 

94 

546 

265 

281 

28 

41 

53 

38 

93 

92 

36 

0.69 

0.25 

0.36 

0.11 

0.25 

0.24 

0.18 

0.29 

* 

0.65 

0.53 

2.08 

0.32 

0.39 

0.31 

0.43 

0.27 

0.24 

0.44 

0.37 

0.29 

0.26 

0.34 

0.33 

0.34 

0.70 

0.56 

0.41 

0.20 

0.29 

0.40 

0.22 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

0.02 

0.04 

0.05 

0.02 

0.07 

0.05 

* 

0.04 

* 

* 

0.13 

0.09 

0.10 

0.07 

0.04 

0.04 

0.04 

0.09 

0.09 

0.05 

0.03 

0.05 

0.05 

0.04 

0.05 

0.05 

0.11 

0.06 

0.04 

0.05 

0.06 

0.04 

0.16 

0.23 

0.22 

0.08 

0.17 

0.19 

* 

0.19 

* 

0.27 

0.46 

0.15 

0.24 

0.20 

0.18 

0.22 

0.19 

0.23 

0.20 

0.18 

0.19 

0.23 

0.19 

0.20 

0.18 

0.23 

0.30 

0.22 

0.15 

0.18 

0.17 

0.13 

0.66 

0.51 

0.93 

0.27 

0.42 

0.53 

* 

0.60 

* 

* 

* 

* 

0.79 

1.37 

0.68 

0.65 

0.58 

0.41 

1.30 

0.65 

0.62 

0.57 

0.74 

0.74 

0.74 

1.58 

1.17 

1.04 

0.41 

0.56 

1.14 

0.45 

2.95 

0.58 

1.37 

0.33 

0.64 

0.68 

* 

0.98 

* 

* 

* 

* 

1.01 

1.56 

1.13 

0.98 

1.05 

0.50 

1.63 

0.96 

1.10 

0.69 

1.21 

1.22 

1.20 

3.82 

1.51 

1.26 

0.67 

0.87 

1.52 

0.56 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 
 

 

Table 10-38. Fish Consumption per kg Body Weight, Consumers Only, by Selected 

Demographic Characteristics (g/kg-day, as-consumed) (continued)
 

Percentiles 

50th 95th State Demographic Sample Arithmetic Percent 10th 90th 

Characteristic Size Mean Eating 

Fish 

North Dakota (continued) 

Age (years)-Sex 

Category 

Male 30 to 49 88 0.22 100 0.05 0.18 0.45 0.54 

Male 50+ 76 0.31 100 0.04 0.19 0.74 1.20 

Unknown 1 0.34 100 * * * * 

Race/Ethnicity 

White, Non- 501 0.34 100 0.05 0.19 0.74 1.23 

Hispanic 

Black, Non- 2 0.25 100 * 0.25 * * 

Hispanic 

Asian 4 0.20 100 * 0.14 * * 

American Indian 9 0.30 100 0.08 0.25 0.61 * 

Unknown 30 0.32 100 0.05 0.16 0.73 0.95 

Respondent 

Education 

0 to 11 years 25 0.26 100 0.07 0.12 0.73 0.90 

High School 134 0.43 100 0.05 0.20 0.98 1.62 

Some College 174 0.29 100 0.05 0.20 0.65 1.02 

College Grad 181 0.32 100 0.05 0.19 0.72 1.30 

Unknown 32 0.40 100 0.04 0.13 0.84 1.43 

Household 

Income ($) 

0 to 20,000 48 0.55 100 0.07 0.19 1.80 2.62 

20,000 to 50,000 221 0.29 100 0.04 0.15 0.73 1.17 

>50,000 225 0.32 100 0.06 0.23 0.64 1.04 

Unknown 52 0.45 100 0.05 0.20 0.82 1.28 

*	 Percentiles cannot be estimated due to small sample size. 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on 

rate of consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-107 
 

 

Table 10-39. Fish Consumption per kg Body Weight, All Respondents by State, Acquisition Method, 

(g/kg-day, as-consumed) 

State Category Sample Arithmetic Percent Percentiles 

Size Mean Eating 10th 50th 90th 95th 

Fish 

Connecticut 

All 420 0.41 85.1 0.00 0.25 1.00 1.32 

Acquisition Method 

Bought 420 0.40 84.8 0.00 0.25 0.96 1.30 

Caught 420 0.01 16.3 0.00 0.00 0.01 0.03 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 40 0.38 86.4 0.00 0.26 0.96 1.45 

Bought; 20,000 to 50,000 150 0.46 86.6 0.00 0.27 0.93 1.42 

Bought; >50,000 214 0.38 84.1 0.00 0.24 0.99 1.27 

Bought; Unknown 16 0.32 73.4 0.00 0.30 0.75 1.00 

Caught; 0 to 20,000 40 0.01 11.0 0.00 0.00 0.00 0.05 

Caught; 20,000 to 50,000 150 0.01 18.1 0.00 0.00 0.02 0.06 

Caught; >50,000 214 0.01 16.8 0.00 0.00 0.01 0.02 

Caught; Unknown 16 0.00 6.2 0.00 0.00 0.00 0.01 

Habitat 

Freshwater 420 0.01 36.4 0.00 0.00 0.03 0.07 

Estuarine 420 0.10 76.0 0.00 0.04 0.23 0.43 

Marine 420 0.29 84.8 0.00 0.17 0.67 0.97 

Fish/Shellfish Type 

Shellfish 420 0.13 74.6 0.00 0.06 0.30 0.55 

Finfish 420 0.27 82.7 0.00 0.14 0.69 0.95 

Florida 

All 15,367 0.47 50.5 0.00 0.06 1.27 1.91 

Acquisition Method 

Bought 15,367 0.41 47.5 0.00 0.00 1.12 1.70 

Caught 15,367 0.06 7.4 0.00 0.00 0.00 0.34 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 3,314 0.41 42.5 0.00 0.00 1.10 1.84 

Bought; 20,000 to 50,000 6,678 0.41 47.4 0.00 0.00 1.11 1.68 

Bought; >50,000 3,136 0.45 54.2 0.00 0.14 1.27 1.79 

Bought; Unknown 2,239 0.32 45.3 0.00 0.00 0.99 1.45 

Caught; 0 to 20,000 3,314 0.06 6.7 0.00 0.00 0.00 0.32 

Caught; 20,000 to 50,000 6,678 0.07 7.8 0.00 0.00 0.00 0.38 

Caught; >50,000 3,136 0.06 8.4 0.00 0.00 0.00 0.42 

Caught; Unknown 2,239 0.03 5.5 0.00 0.00 0.00 0.16 

Habitat 

Freshwater 15,367 0.04 9.1 0.00 0.00 0.00 0.26 

Estuarine 15,367 0.10 26.5 0.00 0.00 0.32 0.54 

Marine 15,367 0.33 40.3 0.00 0.00 0.90 1.43 

Fish/Shellfish Type 

Shellfish 15,367 0.07 21.1 0.00 0.00 0.22 0.43 

Finfish 15,367 0.39 41.9 0.00 0.00 1.10 1.67 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-108 September 2011 
 

Table 10-39. Fish Consumption per kg Body Weight, All Respondents by State, Acquisition Method, 

(g/kg-day, as-consumed) (continued) 

State Category Sample Arithmetic Percent Percentiles 

Size Mean Eating 10th 50th 90th 95th 

Fish 

Minnesota 

All 837 0.31 94.4 0.02 0.18 0.62 1.07 

Acquisition Method 

Bought 837 0.20 89.9 0.00 0.10 0.51 0.76 

Caught 837 0.11 60.6 0.00 0.03 0.22 0.37 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 87 0.26 90.7 0.02 0.12 0.61 1.06 

Bought; 20,000 to 50,000 326 0.18 84.4 0.00 0.10 0.45 0.58 

Bought; >50,000 327 0.20 93.9 0.02 0.10 0.55 0.86 

Bought; Unknown 97 0.21 91.3 0.01 0.18 0.54 0.65 

Caught; 0 to 20,000 87 0.14 70.4 0.00 0.03 0.28 1.00 

Caught; 20,000 to 50,000 326 0.15 66.0 0.00 0.04 0.25 0.36 

Caught; >50,000 327 0.09 55.5 0.00 0.02 0.24 0.39 

Caught; Unknown 97 0.04 56.7 0.00 0.02 0.12 0.14 

Habitat 

Freshwater 837 0.11 60.6 0.00 0.03 0.22 0.37 

Estuarine 837 0.02 67.5 0.00 0.01 0.05 0.09 

Marine 837 0.18 89.9 0.00 0.09 0.46 0.68 

Fish/Shellfish Type 

Shellfish 837 0.04 67.5 0.00 0.01 0.10 0.18 

Finfish 837 0.27 94.0 0.01 0.15 0.57 0.83 

North Dakota 

All 575 0.32 95.2 0.03 0.18 0.71 1.18 

Acquisition Method 

Bought 575 0.23 89.9 0.00 0.10 0.52 0.93 

Caught 575 0.09 68.3 0.00 0.04 0.24 0.40 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 51 0.41 88.0 0.00 0.12 1.34 2.03 

Bought; 20,000 to 50,000 235 0.21 90.6 0.01 0.09 0.48 1.01 

Bought; >50,000 233 0.19 90.7 0.01 0.10 0.48 0.77 

Bought; Unknown 56 0.30 85.5 0.00 0.10 0.66 0.91 

Caught; 0 to 20,000 51 0.10 53.9 0.00 0.01 0.23 0.45 

Caught; 20,000 to 50,000 235 0.07 59.4 0.00 0.02 0.18 0.30 

Caught; >50,000 233 0.12 76.2 0.00 0.06 0.34 0.46 

Caught; Unknown 56 0.11 85.7 0.00 0.05 0.22 0.23 

Habitat 

Freshwater 575 0.09 68.3 0.00 0.04 0.24 0.40 

Estuarine 575 0.02 71.3 0.00 0.01 0.05 0.08 

Marine 575 0.21 89.9 0.00 0.09 0.45 0.80 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-109 
 

 

Table 10-39. Fish Consumption per kg Body Weight, All Respondents by State, Acquisition 

Method,g/kg-day, as-consumed) (continued)
 

Percentiles 

50th 95th State Category Sample Arithmetic Percent 10th 90th 

Size Mean Eating 

Fish 

North Dakota (continued) 

Fish/Shellfish Type 

Shellfish 575 0.04 71.3 0.00 0.02 0.09 0.15 

Finfish 575 0.28 94.3 0.02 0.14 0.63 1.01 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

A respondent can be represented in more than one row. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-110 September 2011 
 

Exposure Factors Handbook Page 

September 2011 10-111 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method (g/kgday, as-consumed) 

Percentiles 

State Category Sample Arithmetic Percent 10th 50th 90th 95th 

Size Mean Eating 

Fish 

Connecticut 

All 362 0.48 100 0.07 0.32 1.09 1.37 

Acquisition Method 

Bought 361 0.47 100 0.07 0.31 1.05 1.38 

Caught 71 0.05 100 0.00 0.02 0.13 0.18 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 35 0.44 100 0.08 0.30 1.13 1.47 

Bought; 20,000 to 50,000 132 0.53 100 0.07 0.32 1.03 1.46 

Bought; >50,000 182 0.45 100 0.06 0.30 1.04 1.29 

Bought; Unknown 12 0.44 100 0.10 0.41 0.84 1.03 

Caught; 0 to 20,000 4 0.05 100 * 0.01 * * 

Caught; 20,000 to 50,000 30 0.08 100 0.00 0.02 0.23 0.46 

Caught; >50,000 36 0.03 100 0.00 0.02 0.08 0.11 

Caught; Unknown 1 0.01 100 * * * * 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 1 0.01 100 * * * * 

Eats Caught and Bought 70 0.49 100 0.10 0.34 1.10 1.33 

Eats Bought Only 291 0.48 100 0.06 0.32 1.06 1.39 

Habitat 

Freshwater 157 0.04 100 0.00 0.02 0.07 0.15 

Estuarine 327 0.14 100 0.01 0.06 0.30 0.51 

Marine 361 0.34 100 0.04 0.23 0.78 1.09 

Eats Freshwater/Estuarine Caught Fish 

Sometimes 50 0.46 100 0.09 0.29 1.10 1.25 

Never 312 0.49 100 0.07 0.32 1.06 1.41 

Fish/Shellfish Type 

Shellfish 320 0.18 100 0.02 0.09 0.37 0.68 

Finfish 353 0.32 100 0.02 0.20 0.77 1.08 

Florida 

All 7,757 0.93 100 0.19 0.58 1.89 2.73 

Acquisition Method 

Bought 7,246 0.86 100 0.17 0.54 1.77 2.55 

Caught 1,212 0.83 100 0.15 0.52 1.74 2.36 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 1,418 0.97 100 0.19 0.58 2.10 2.78 

Bought; 20,000 to 50,000 3,141 0.87 100 0.18 0.56 1.74 2.50 

Bought; >50,000 1,695 0.83 100 0.16 0.53 1.75 2.54 

Bought; Unknown 992 0.71 100 0.16 0.48 1.55 2.06 

Caught; 0 to 20,000 246 0.89 100 0.19 0.60 1.94 2.77 

Caught; 20,000 to 50,000 563 0.90 100 0.15 0.53 1.79 2.38 

Caught; >50,000 274 0.76 100 0.11 0.49 1.63 2.42 

Caught; Unknown 129 0.58 100 0.16 0.41 1.07 1.52 
 

 

Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,(g/kgday, as-consumed) (continued) 

Category Sample Arithmetic Percent Percentiles 

State Size Mean Eating 10th 50th 90th 95th 

Fish 

Florida (continued) 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 511 0.76 100 0.15 0.50 1.67 2.34 

Eats Caught and Bought 701 1.81 100 0.50 1.15 3.35 5.09 

Eats Bought Only 6,545 0.85 100 0.18 0.54 1.75 2.49 

Habitat 

Freshwater 1,426 0.47 100 0.07 0.30 1.09 1.51 

Estuarine 4,124 0.37 100 0.07 0.23 0.80 1.14 

Marine 6,124 0.81 100 0.15 0.50 1.64 2.40 

Eats Freshwater/Estuarine Caught Fish 

Exclusively 235 0.71 100 0.10 0.42 1.60 2.16 

Sometimes 458 1.73 100 0.43 1.10 3.44 4.96 

Never 7,064 0.88 100 0.18 0.56 1.81 2.60 

Fish/Shellfish Type 

Shellfish 3,260 0.35 100 0.07 0.21 0.74 1.02 

Finfish 6,428 0.94 100 0.24 0.60 1.85 2.72 

Minnesota 

All 793 0.33 100 0.04 0.20 0.65 1.08 

Acquisition Method 

Bought 755 0.22 100 0.03 0.12 0.55 0.83 

Caught 593 0.18 100 0.02 0.07 0.30 0.57 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 76 0.29 100 0.04 0.13 0.64 1.08 

Bought; 20,000 to 50,000 284 0.22 100 0.03 0.13 0.47 0.74 

Bought; >50,000 312 0.21 100 0.03 0.11 0.57 0.97 

Bought; Unknown 83 0.23 100 0.02 0.2 0.54 0.65 

Caught; 0 to 20,000 56 0.19 100 0.02 0.05 0.49 1.09 

Caught; 20,000 to 50,000 232 0.23 100 0.02 0.08 0.30 0.46 

Caught; >50,000 235 0.16 100 0.02 0.08 0.37 0.65 

Caught; Unknown 70 0.07 100 0.02 0.03 0.14 0.16 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 38 0.16 100 0.02 0.08 0.37 0.51 

Eats Caught and Bought 555 0.40 100 0.08 0.23 0.70 1.32 

Eats Bought Only 200 0.23 100 0.02 0.14 0.56 0.91 

Habitat 

Freshwater 593 0.18 100 0.02 0.07 0.30 0.57 

Estuarine 559 0.03 100 0.00 0.01 0.07 0.12 

Marine 755 0.20 100 0.02 0.10 0.50 0.73 

Eats Freshwater/Estuarine Caught Fish 

Exclusively 38 0.16 100 0.02 0.08 0.37 0.51 

Sometimes 555 0.40 100 0.08 0.23 0.70 1.32 

Never 200 0.23 100 0.02 0.14 0.56 0.91 

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Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-112 September 2011 
 

Table 10-40. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method,(g/kgday, as-consumed) (continued) 

Category Sample Arithmetic Percent Percentiles 

State Size Mean Eating 10th 50th 90th 95th 

Fish 

Minnesota (continued) 

Fish/Shellfish Type 

Shellfish 559 0.06 100 0.01 0.02 0.14 0.24 

Finfish 791 0.28 100 0.03 0.16 0.57 0.86 

North Dakota 

All	 546 0.34 100 0.05 0.19 0.74 1.21 

Acquisition Method 

Bought 516 0.25 100 0.03 0.12 0.61 1.02 

Caught 389 0.14 100 0.02 0.07 0.34 0.46 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 45 0.47 100 0.05 0.14 1.54 2.22 

Bought; 20,000 to 50,000 213 0.23 100 0.03 0.11 0.52 1.03 

Bought; >50,000 210 0.21 100 0.03 0.11 0.48 0.79 

Bought; Unknown 48 0.35 100 0.03 0.14 0.70 1.08 

Caught; 0 to 20,000 27 0.19 100 0.01 0.08 0.42 0.64 

Caught; 20,000 to 50,000 142 0.11 100 0.02 0.05 0.25 0.40 

Caught; >50,000 173 0.15 100 0.02 0.08 0.38 0.53 

Caught; Unknown 47 0.13 100 0.03 0.06 0.23 0.24 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 30 0.21 100 0.05 0.14 0.33 0.51 

Eats Caught and Bought 359 0.39 100 0.07 0.23 0.82 1.25 

Eats Bought Only 157 0.25 100 0.03 0.10 0.53 0.97 

Habitat 

Freshwater 389 0.14 100 0.02 0.07 0.34 0.46 

Estuarine 407 0.03 100 0.00 0.01 0.06 0.10 

Marine 516 0.23 100 0.02 0.10 0.54 0.86 

Eats Freshwater/Estuarine Caught Fish 

Exclusively 30 0.21 100 0.05 0.14 0.33 0.51 

Sometimes 359 0.39 100 0.07 0.23 0.82 1.25 

Never 157 0.25 100 0.03 0.10 0.53 0.97 

Fish/Shellfish Type 

Shellfish 407 0.05 100 0.01 0.02 0.13 0.21 

Finfish 541 0.30 100 0.04 0.16 0.67 1.08 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

A respondent can be represented in more than one row. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-113
 
 

Page Exposure Factors Handbook 

10-114 September 2011 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) 

Percentiles 

State Demographic Sample Arithmetic Percent 10th 50th 90th 95th 

Characteristic Size Mean Eating 

Fish 

Connecticut 

All 420 0.56 85.1 0.00 0.35 1.37 1.76 

Sex 

Male 201 0.53 86.2 0.00 0.34 1.48 1.78 

Female 219 0.59 84.0 0.00 0.39 1.29 1.73 

Age (years)-Sex 

Category 

Child 1 to 5 26 0.43 51.7 0.00 0.07 1.25 1.95 

Child 6 to 10 26 0.71 86.7 0.00 0.48 1.55 1.74 

Child 11 to 15 21 0.37 85.6 0.00 0.25 0.71 1.20 

Female 16 to 29 17 0.88 79.9 0.00 0.43 1.41 5.25 

Female 30 to 49 85 0.64 86.7 0.00 0.39 1.39 1.80 

Female 50+ 77 0.59 90.6 0.01 0.45 1.28 1.74 

Male 16 to 29 14 0.23 70.5 0.00 0.21 0.55 0.74 

Male 30 to 49 80 0.64 92.8 0.04 0.43 1.56 1.97 

Male 50+ 63 0.47 90.5 0.03 0.36 1.15 1.55 

Unknown 11 0.12 76.1 0.00 0.03 0.52 0.62 

Race/Ethnicity 

White, Non­ 370 0.56 88.7 0.00 0.38 1.32 1.69 

Hispanic 

Black, Non­ 9 0.07 33.5 0.00 0.00 0.23 * 

Hispanic 

Hispanic 20 0.67 70.9 0.00 0.29 2.14 3.43 

Asian 19 0.81 59.2 0.00 0.18 1.74 4.96 

Unknown 2 0.01 43.4 0.00 0.00 * * 

Respondent 

Education 

0 to 11 years 13 0.43 100.0 0.07 0.20 1.34 1.74 

High School 87 0.51 85.3 0.00 0.30 1.40 1.55 

Some College 62 0.56 88.7 0.00 0.41 1.09 1.87 

College Grad 258 0.58 83.4 0.00 0.36 1.40 1.78 

Household Income 

($) 

0 to 20,000 40 0.52 86.4 0.00 0.34 1.28 1.86 

20,000 to 50,000 150 0.64 87.4 0.00 0.39 1.40 1.93 

>50,000 214 0.52 84.1 0.00 0.34 1.37 1.69 

Unknown 16 0.45 73.4 0.00 0.42 1.02 1.36 

Florida 

All 15,367 0.59 50.5 0.00 0.08 1.59 2.39 

Sexes 

Male 7,911 0.55 49.2 0.00 0.00 1.51 2.32 

Female 7,426 0.62 51.9 0.00 0.14 1.66 2.48 

Unknown 30 0.51 48.0 0.00 0.00 1.73 2.90 
 

Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) (continued) 

Percentiles 

State Demographic Sample Arithmetic Percent 10th 50th 90th 95th 

Characteristic Size Mean Eating 

Fish 

Florida (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 1,102 1.10 37.8 0.00 0.00 3.41 4.85 

Child 6 to 10 938 0.54 39.4 0.00 0.00 1.69 2.55 

Child 11 to 15 864 0.46 42.9 0.00 0.00 1.27 1.92 

Female 16 to 29 1,537 0.55 49.1 0.00 0.00 1.42 2.20 

Female 30 to 49 2,264 0.67 56.6 0.00 0.27 1.73 2.56 

Female 50+ 2,080 0.52 56.5 0.00 0.27 1.44 2.04 

Male 16 to 29 1,638 0.55 46.1 0.00 0.00 1.41 2.20 

Male 30 to 49 2,540 0.54 53.0 0.00 0.16 1.49 2.21 

Male 50+ 2,206 0.49 54.5 0.00 0.20 1.24 1.86 

Unknown 198 0.45 54.7 0.00 0.27 1.07 1.53 

Race/Ethnicity 

White, Non­ 11,607 0.57 51.6 0.00 0.12 1.56 2.33 

Hispanic 

Black, Non­ 1,603 0.67 48.3 0.00 0.00 1.87 2.77 

Hispanic 

Hispanic 1,556 0.57 45.9 0.00 0.00 1.52 2.46 

Asian 223 0.72 49.5 0.00 0.00 1.65 2.34 

American Indian 104 0.78 53.4 0.00 0.20 2.46 4.52 

Unknown 274 0.53 45.9 0.00 0.00 1.45 2.14 

Respondent 

Education 

0 to 11 years 1,481 0.50 41.5 0.00 0.00 1.45 2.16 

High School 4,992 0.58 48.5 0.00 0.00 1.59 2.45 

Some College 4,791 0.61 52.3 0.00 0.15 1.59 2.47 

College Grad 4,012 0.60 54.2 0.00 0.20 1.64 2.34 

Unknown 91 0.58 41.2 0.00 0.00 2.04 3.05 

Household Income 

($) 

0 to 20,000 3,314 0.59 45.9 0.00 0.00 1.55 2.61 

20,000 to 50,000 6,678 0.61 50.4 0.00 0.08 1.61 2.42 

>50,000 3,136 0.65 57.5 0.00 0.27 1.77 2.53 

Unknown 2,239 0.45 47.6 0.00 0.00 1.36 1.99 

Minnesota 

All 837 0.41 94.4 0.03 0.24 0.83 1.43 

Sexes 

Male 419 0.35 95.3 0.03 0.22 0.77 1.41 

Female 418 0.48 93.4 0.02 0.27 0.87 1.46 

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Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-115
 
 

 

Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) (continued) 

Percentiles 

10th 50th 90th 95th State Demographic Sample Arithmetic Percent 

Characteristic Size Mean Eating 

Fish 

Minnesota (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 47 0.76 97.4 0.06 0.60 1.46 2.32 

Child 6 to 10 46 0.44 88.4 0.00 0.28 1.09 1.79 

Child 11 to 15 68 0.29 92.8 0.02 0.25 0.72 0.78 

Female 16 to 29 47 0.89 96.0 0.03 0.20 0.81 5.97 

Female 30 to 49 132 0.32 95.0 0.03 0.29 0.67 0.77 

Female 50+ 162 0.46 94.9 0.04 0.28 1.19 1.80 

Male 16 to 29 55 0.13 92.3 0.01 0.09 0.35 0.44 

Male 30 to 49 120 0.32 96.0 0.06 0.22 0.56 0.85 

Male 50+ 155 0.32 99.8 0.06 0.25 0.70 0.91 

Unknown 5 0.00 1.6 0.00 0.00 0.00 0.00 

Race/Ethnicity 

White, Non- 775 0.36 93.8 0.02 0.23 0.79 1.19 

Hispanic 

Black, Non- 1 0.00 * * * * * 

Hispanic 

Hispanic 3 0.86 100 * 0.36 * * 

Asian 7 0.71 100 0.18 0.63 * * 

American Indian 12 2.77 100 0.12 0.21 * * 

Unknown 39 0.43 100 0.14 0.31 1.05 1.36 

Respondent 

Education 

0 to 11 years 46 0.45 86.2 0.00 0.25 1.64 2.08 

High School 234 0.39 92.9 0.02 0.22 0.86 1.48 

Some College 259 0.54 95.3 0.04 0.27 0.86 1.27 

College Grad 255 0.34 95.0 0.03 0.23 0.76 1.40 

Unknown 43 0.32 99.7 0.12 0.30 0.55 0.68 

Household Income 

($) 

0 to 20,000 87 0.53 91.0 0.04 0.27 1.60 2.14 

20,000 to 50,000 326 0.45 91.3 0.02 0.23 0.83 1.20 

>50,000 327 0.38 97.9 0.04 0.24 0.82 1.46 

Unknown 97 0.33 92.9 0.04 0.29 0.74 0.91 

North Dakota 

All 575 0.43 95.2 0.05 0.24 0.95 1.58 

Sexes 

Male 276 0.43 96.2 0.05 0.25 0.91 1.60 

Female 299 0.43 94.2 0.04 0.23 0.97 1.55 

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Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-116 September 2011 
 

 

Table 10-41. Fish Consumption per kg Body Weight, All Respondents, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) (continued) 

Percentiles 

10th 50th 90th 95th State Demographic Sample Arithmetic Percent 

Characteristic Size Mean Eating 

Fish 

North Dakota (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 30 0.89 94.4 0.05 0.30 2.08 5.10 

Child 6 to 10 44 0.68 92.0 0.09 0.39 1.52 1.99 

Child 11 to 15 55 0.53 97.1 0.07 0.28 1.35 1.65 

Female 16 to 29 42 0.24 89.9 0.00 0.15 0.52 0.84 

Female 30 to 49 95 0.38 98.3 0.05 0.24 0.74 1.14 

Female 50+ 99 0.50 93.4 0.03 0.21 1.32 1.95 

Male 16 to 29 36 0.29 100.0 0.05 0.17 0.61 0.75 

Male 30 to 49 90 0.29 97.8 0.05 0.23 0.59 0.71 

Male 50+ 81 0.38 94.0 0.02 0.23 0.90 1.54 

Unknown 3 0.14 31.5 0.00 0.00 * * 

Race/Ethnicity 

White, Non- 528 0.43 95.1 0.04 0.24 0.96 1.62 

Hispanic 

Black, Non- 2 0.33 100.0 * 0.33 * * 

Hispanic 

Asian 4 0.26 100.0 * 0.24 * * 

American Indian 9 0.40 100.0 0.11 0.33 0.92 * 

Unknown 32 0.40 93.5 0.06 0.18 0.95 1.25 

Respondent 

Education 

0 to 11 years 29 0.30 86.6 0.00 0.15 0.86 1.15 

High School 138 0.56 97.3 0.06 0.26 1.19 2.08 

Some College 183 0.37 95.2 0.04 0.25 0.84 1.32 

College Grad 188 0.41 96.7 0.05 0.25 0.92 1.69 

Unknown 37 0.46 87.2 0.00 0.13 0.98 1.76 

Household Income 

($) 

0 to 20,000 51 0.69 93.7 0.03 0.23 2.39 3.40 

20,000 to 50,000 235 0.36 94.2 0.03 0.18 0.93 1.51 

>50,000 233 0.41 97.1 0.06 0.30 0.84 1.36 

Unknown 56 0.55 92.7 0.05 0.24 1.05 1.62 

*	 Percentiles cannot be estimated due to small sample size. 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-117
 
 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) 

Percentiles 

State Demographic 

Characteristic 

Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating 

Fish 

10th 50th 90th 95th 

Connecticut 

All 362 0.66 100 0.10 0.43 1.51 1.80 

Sex 

Male 175 0.61 100 0.11 0.41 1.54 1.85 

Female 187 0.70 100 0.09 0.47 1.40 1.77 

Age (years)-Sex 

Category 

Child 1 to 5 14 0.83 100 0.21 0.74 1.88 2.07 

Child 6 to 10 22 0.81 100 0.21 0.74 1.57 1.76 

Child 11 to 15 18 0.43 100 0.12 0.30 0.72 1.14 

Female 16 to 29 14 1.10 100 0.15 0.47 1.50 4.07 

Female 30 to 49 74 0.73 100 0.08 0.47 1.60 1.97 

Female 50+ 70 0.65 100 0.07 0.50 1.39 1.76 

Male 16 to 29 10 0.32 100 0.11 0.30 0.63 0.78 

Male 30 to 49 74 0.69 100 0.15 0.48 1.58 1.98 

Male 50+ 57 0.52 100 0.14 0.38 1.25 1.55 

Unknown 9 0.16 100 0.01 0.05 0.54 * 

Race/Ethnicity 

White, NonHispanic 331 0.63 100 0.10 0.43 1.41 1.75 

Black, NonHispanic 3 0.20 100 * 0.20 * * 

Hispanic 15 0.95 100 0.16 0.39 2.95 3.52 

Asian 12 1.36 100 0.12 0.69 2.57 6.24 

Unknown 1 0.03 100 * * * * 

Respondent 

Education 

0 to 11 years 13 0.43 100 0.07 0.20 1.27 1.72 

High School 76 0.60 100 0.06 0.37 1.47 1.56 

Some College 56 0.63 100 0.16 0.46 1.16 1.89 

College Grad 217 0.70 100 0.11 0.45 1.53 1.85 

Household Income 

($) 

0 to 20,000 35 0.60 100 0.10 0.43 1.53 1.90 

20,000 to 50,000 133 0.73 100 0.12 0.46 1.55 1.98 

>50,000 182 0.62 100 0.09 0.41 1.49 1.75 

Unknown 12 0.61 100 0.13 0.57 1.14 1.41 

Florida 

All 7,757 1.16 100 0.24 0.73 2.39 3.37 

Sexes 

Male 3,880 1.12 100 0.23 0.69 2.33 3.32 

Female 3,861 1.20 100 0.25 0.77 2.42 3.48 

Unknown 16 1.05 100 0.15 0.91 2.90 3.19 

Page Exposure Factors Handbook 

10-118 September 2011 
 

Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) (continued) 

Percentiles 

State Demographic Sample Arithmetic Percent 10th 50th 90th 95th 

Characteristic Size Mean Eating 

Fish 

Florida (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 420 2.92 100 0.63 2.16 5.73 8.37 

Child 6 to 10 375 1.37 100 0.38 1.01 2.72 3.45 

Child 11 to 15 365 1.06 100 0.28 0.79 2.02 2.78 

Female 16 to 29 753 1.12 100 0.23 0.71 2.22 3.10 

Female 30 to 49 1,287 1.18 100 0.24 0.78 2.39 3.31 

Female 50+ 1,171 0.91 100 0.24 0.66 1.92 2.53 

Male 16 to 29 754 1.19 100 0.22 0.66 2.26 3.30 

Male 30 to 49 1,334 1.02 100 0.22 0.67 2.18 3.05 

Male 50+ 1,192 0.89 100 0.22 0.62 1.75 2.51 

Unknown 106 0.81 100 0.27 0.61 1.50 2.02 

Race/Ethnicity 

White, Non­ 5,957 1.11 100 0.24 0.71 2.30 3.28 

Hispanic 

Black, Non­ 785 1.39 100 0.30 0.91 2.81 3.92 

Hispanic 

Hispanic 721 1.25 100 0.23 0.75 2.53 3.57 

Asian 110 1.46 100 0.35 0.84 2.34 4.08 

American Indian 57 1.45 100 0.28 0.90 4.02 5.73 

Unknown 127 1.16 100 0.24 0.81 2.23 3.10 

Respondent 

Education 

0 to 11 years 613 1.20 100 0.27 0.74 2.38 3.53 

High School 2,405 1.20 100 0.23 0.73 2.49 3.58 

Some College 2,511 1.16 100 0.24 0.72 2.39 3.39 

College Grad 2,190 1.10 100 0.24 0.73 2.25 3.17 

Unknown 38 1.40 100 0.32 1.06 3.08 3.17 

Household Income 

($) 

0 to 20,000 1,534 1.28 100 0.25 0.77 2.77 3.66 

20,000 to 50,000 3,370 1.20 100 0.25 0.75 2.41 3.45 

>50,000 1,806 1.13 100 0.22 0.71 2.39 3.37 

Unknown 1,047 0.93 100 0.23 0.64 2.06 2.52 

Minnesota 

All 793 0.44 100 0.06 0.26 0.86 1.44 

Sexes 

Male 401 0.37 100 0.05 0.23 0.82 1.43 

Female 392 0.51 100 0.06 0.29 0.93 1.62 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-119
 
 

 

Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) (continued) 

Percentiles 

State Demographic Sample Arithmetic Percent 10th 50th 90th 95th 

Characteristic Size Mean Eating 

Fish 

Minnesota (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 46 0.78 100 0.09 0.62 1.47 2.33 

Child 6 to 10 42 0.50 100 0.06 0.33 1.35 1.81 

Child 11 to 15 63 0.32 100 0.04 0.28 0.73 0.78 

Female 16 to 29 44 0.92 100 0.03 0.21 0.88 3.93 

Female 30 to 49 127 0.34 100 0.05 0.30 0.68 0.78 

Female 50+ 150 0.48 100 0.07 0.29 1.24 1.82 

Male 16 to 29 52 0.14 100 0.02 0.11 0.36 0.44 

Male 30 to 49 115 0.33 100 0.09 0.23 0.56 0.86 

Male 50+ 153 0.33 100 0.06 0.25 0.70 0.91 

Unknown 1 0.24 100 * * * * 

Race/Ethnicity 

White, Non­ 732 0.38 100 0.05 0.25 0.81 1.31 

Hispanic 

Black, Non­ * * 100 * * * * 

Hispanic 

Hispanic 3 0.86 100 * 0.36 * * 

Asian 7 0.71 100 0.18 0.62 * * 

American Indian 12 2.77 100 0.12 0.21 * * 

Unknown 39 0.43 100 0.14 0.31 1.05 1.34 

Respondent 

Education 

0 to 11 years 41 0.53 100 0.10 0.26 1.83 2.08 

High School 219 0.42 100 0.06 0.24 0.90 1.51 

Some College 249 0.57 100 0.05 0.29 0.86 1.31 

College Grad 242 0.36 100 0.05 0.25 0.78 1.41 

Unknown 42 0.32 100 0.12 0.31 0.55 0.67 

Household Income 

($) 

0 to 20,000 77 0.59 100 0.12 0.27 1.73 2.17 

20,000 to 50,000 301 0.49 100 0.07 0.24 0.86 1.28 

>50,000 321 0.39 100 0.04 0.25 0.83 1.46 

Unknown 94 0.35 100 0.07 0.30 0.76 0.92 

North Dakota 

All 546 0.45 100 0.07 0.25 0.99 1.62 

Sexes 

Male 265 0.44 100 0.06 0.27 0.99 1.62 

Female 281 0.46 100 0.07 0.24 0.99 1.60 

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Table 10-42. Fish Consumption per kg Body Weight, Consumers Only, by Selected Demographic 

Characteristics, Uncooked (g/kg-day) (continued) 

Percentiles 

State Demographic Sample Arithmetic Percent 10th 50th 90th 95th 

Characteristic Size Mean Eating 

Fish 

North Dakota (continued) 

Age (years)-Sex 

Category 

Child 1 to 5 28 0.94 100 0.07 0.31 2.11 5.09 

Child 6 to 10 41 0.74 100 0.14 0.40 1.56 2.02 

Child 11 to 15 53 0.54 100 0.08 0.29 1.39 1.68 

Female 16 to 29 38 0.27 100 0.05 0.19 0.54 0.89 

Female 30 to 49 93 0.38 100 0.06 0.24 0.75 1.16 

Female 50+ 92 0.54 100 0.08 0.23 1.53 2.02 

Male 16 to 29 36 0.29 100 0.05 0.17 0.60 0.75 

Male 30 to 49 88 0.29 100 0.06 0.25 0.60 0.72 

Male 50+ 76 0.41 100 0.05 0.25 0.99 1.60 

Unknown 1 0.45 100 * * * * 

Race/Ethnicity 

White, Non- 501 0.45 100 0.06 0.25 0.99 1.64 

Hispanic 

Black, Non- 2 0.33 100 * 0.33 * * 

Hispanic 

Asian 4 0.26 100 * 0.18 * * 

American Indian 9 0.40 100 0.11 0.33 0.82 * 

Unknown 30 0.42 100 0.07 0.21 0.98 1.27 

Respondent 

Education 

0 to 11 years 25 0.35 100 0.09 0.16 0.97 1.20 

High School 134 0.57 100 0.07 0.27 1.30 2.16 

Some College 174 0.38 100 0.06 0.26 0.87 1.36 

College Grad 181 0.43 100 0.07 0.25 0.95 1.73 

Unknown 32 0.53 100 0.05 0.17 1.12 1.91 

Household Income 

($) 

0 to 20,000 48 0.74 100 0.09 0.25 2.40 3.49 

20,000 to 50,000 221 0.39 100 0.05 0.20 0.97 1.55 

>50,000 225 0.42 100 0.08 0.31 0.85 1.39 

Unknown 52 0.60 100 0.06 0.27 1.10 1.71 

*	 Percentiles cannot be estimated due to small sample size. 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate 

of consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-121 
 

 

Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition Method, 

Uncooked (g/kg-day) 

State Characteristic Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating Fish 

Percentiles 

10th 50th 90th 95th 

Connecticut 

All 420 

Acquisition Method 

Bought 420 

Caught 420 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 40 

Bought; 20,000 to 50,000 150 

Bought; >50,000 214 

Bought; Unknown 16 

Caught; 0 to 20,000 40 

Caught; 20,000 to 50,000 150 

Caught; >50,000 214 

Caught; Unknown 16 

Habitat 

Freshwater 420 

Estuarine 420 

Marine 420 

Fish/Shellfish Type 

Shellfish 420 

Finfish 420 

Florida 

All 15,367 

Acquisition Method 

Bought 15,367 

Caught 15,367 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 3,314 

Bought; 20,000 to 50,000 6,678 

Bought; >50,000 3,136 

Bought; Unknown 2,239 

Caught; 0 to 20,000 3,314 

Caught; 20,000 to 50,000 6,678 

Caught; >50,000 3,136 

Caught; Unknown 2,239 

Habitat 

Freshwater 15,367 

Estuarine 15,367 

Marine 15,367 

Fish/Shellfish Type 

Shellfish 15,367 

Finfish 15,367 

0.56 

0.55 

0.01 

0.51 

0.62 

0.52 

0.45 

0.01 

0.02 

0.01 

0.00 

0.02 

0.15 

0.40 

0.19 

0.36 

0.59 

0.51 

0.08 

0.51 

0.52 

0.57 

0.40 

0.08 

0.09 

0.08 

0.04 

0.05 

0.13 

0.40 

0.11 

0.48 

85.1 

84.8 

16.3 

86.4 

86.6 

84.1 

73.4 

11.0 

18.1 

16.8 

6.2 

36.4 

76.0 

84.8 

74.6 

82.7 

50.5 

47.5 

7.40 

42.5 

47.4 

54.2 

45.3 

6.7 

7.8 

8.4 

5.5 

9.1 

26.5 

40.3 

21.1 

41.9 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.35 

0.34 

0.00 

0.34 

0.37 

0.33 

0.42 

0.00 

0.00 

0.00 

0.00 

0.00 

0.06 

0.23 

0.09 

0.19 

0.08 

0.00 

0.00 

0.00 

0.00 

0.19 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

1.37 

1.30 

0.02 

1.28 

1.22 

1.34 

1.02 

0.00 

0.03 

0.01 

0.00 

0.05 

0.36 

0.90 

0.43 

0.94 

1.59 

1.41 

0.00 

1.34 

1.40 

1.58 

1.21 

0.00 

0.00 

0.00 

0.00 

0.00 

0.43 

1.11 

0.32 

1.35 

1.76 

1.76 

0.04 

1.86 

1.93 

1.64 

1.36 

0.06 

0.08 

0.03 

0.01 

0.09 

0.59 

1.29 

0.76 

1.28 

2.39 

2.16 

0.45 

2.32 

2.12 

2.27 

1.82 

0.42 

0.48 

0.53 

0.21 

0.33 

0.73 

1.76 

0.61 

2.08 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-122 September 2011 
 

Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition 

MethodUncooked (g/kg-day) (continued) 

State Characteristic Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating Fish 

Percentiles 

10th 50th 90th 95th

Minnesota 

All 837 

Acquisition Method 

Bought 837 

Caught 837 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 87 

Bought; 20,000 to 50,000 326 

Bought; >50,000 327 

Bought; Unknown 97 

Caught; 0 to 20,000 87 

Caught; 20,000 to 50,000 326 

Caught; >50,000 327 

Caught; Unknown 97 

Habitat 

Freshwater 837 

Estuarine 837 

Marine 837 

Fish/Shellfish Type 

Shellfish 837 

Finfish 837 

North Dakota 

All 575 

Acquisition Method 

Bought 575 

Caught 575 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 51 

Bought; 20,000 to 50,000 235 

Bought; >50,000 233 

Bought; Unknown 56 

Caught; 0 to 20,000 51 

Caught; 20,000 to 50,000 235 

Caught; >50,000 233 

Caught; Unknown 56 

Habitat 

Freshwater 575 

Estuarine 575 

Marine 575 

0.41 

0.27 

0.15 

0.35 

0.25 

0.27 

0.28 

0.18 

0.20 

0.12 

0.05 

0.15 

0.03 

0.24 

0.06 

0.36 

0.43 

0.30 

0.13 

0.55 

0.28 

0.26 

0.41 

0.14 

0.09 

0.15 

0.15 

0.13 

0.03 

0.28 

94.4 

89.9 

60.6 

90.7 

84.4 

93.9 

91.3 

70.4 

66.0 

55.5 

56.7 

60.6 

67.5 

89.9 

67.5 

94.0 

95.2 

89.9 

68.3 

88.0 

90.6 

90.7 

85.5 

53.9 

59.4 

76.2 

85.7 

68.3 

71.3 

89.9 

0.03 

0.00 

0.00 

0.02 

0.00 

0.02 

0.02 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.02 

0.05 

0.00 

0.00 

0.00 

0.01 

0.01 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.24 

0.14 

0.03 

0.15 

0.13 

0.14 

0.23 

0.04 

0.06 

0.03 

0.02 

0.03 

0.01 

0.12 

0.02 

0.19 

0.24 

0.13 

0.05 

0.15 

0.13 

0.13 

0.14 

0.01 

0.03 

0.08 

0.07 

0.05 

0.01 

0.11 

0.83 

0.68 

0.30 

0.82 

0.60 

0.74 

0.72 

0.38 

0.33 

0.31 

0.16 

0.30 

0.06 

0.61 

0.13 

0.76 

0.95 

0.69 

0.31 

1.79 

0.65 

0.64 

0.88 

0.31 

0.23 

0.45 

0.29 

0.31 

0.06 

0.60 

1.43 

1.01 

0.49 

1.42 

0.77 

1.15 

0.86 

1.33 

0.48 

0.53 

0.19 

0.49 

0.12 

0.91 

0.24 

1.11 

1.58 

1.24 

0.53 

2.71 

1.35 

1.02 

1.21 

0.61 

0.40 

0.61 

0.31 

0.53 

0.10 

1.07 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-123 
 

 

Table 10-43. Fish Consumption per kg Body Weight, All Respondents, by State, Acquisition 

MethodUncooked (g/kg-day) (continued)
 

Percentiles 

50th 95th State Characteristic Sample Arithmetic Percent 10th 90th 

Size Mean Eating Fish 

North Dakota (continued) 

Fish/Shellfish Type 

Shellfish 575 0.05 71.3 0.00 0.02 0.12 0.20 

Finfish 575 0.38 94.3 0.03 0.19 0.84 1.35 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

A respondent can be represented in more than one row. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-124 September 2011 
 

Exposure Factors Handbook Page 

September 2011 10-125 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-44. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method, 

Uncooked (g/kg-day) 

State Category Sample Arithmetic Percent Percentiles 

Size Mean Eating 10th 50th 90th 95th 

Fish 

Connecticut 

All 362 0.66 100 0.10 0.43 1.51 1.80 

Acquisition Method 

Bought 361 0.65 100 0.10 0.43 1.43 1.80 

Caught 71 0.07 100 0.00 0.02 0.17 0.23 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 35 0.59 100 0.10 0.41 1.53 1.90 

Bought; 20,000 to 50,000 132 0.71 100 0.11 0.45 1.40 1.98 

Bought; >50,000 182 0.62 100 0.08 0.41 1.45 1.75 

Bought; Unknown 12 0.61 100 0.13 0.57 1.14 1.41 

Caught; 0 to 20,000 4 0.07 100 * 0.02 * * 

Caught; 20,000 to 50,000 30 0.11 100 0.01 0.03 0.30 0.62 

Caught; >50,000 36 0.04 100 0.00 0.02 0.11 3.15 

Caught; Unknown 1 0.01 100 * * * * 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 1 0.03 100 * * * * 

Eats Caught and Bought 70 0.67 100 0.13 0.46 1.54 1.71 

Eats Bought Only 291 0.66 100 0.09 0.43 1.50 1.82 

Habitat 

Freshwater 157 0.05 100 0.00 0.03 0.10 0.21 

Estuarine 327 0.19 100 0.01 0.09 0.40 0.69 

Marine 361 0.47 100 0.06 0.31 1.03 1.45 

Eats Freshwater/Estuarine Caught Fish 

Sometimes 50 0.64 100 0.12 0.39 1.53 1.68 

Never 312 0.66 100 0.10 0.44 1.50 1.83 

Fish/Shellfish Type 

Shellfish 320 0.26 100 0.03 0.14 0.56 0.91 

Finfish 353 0.43 100 0.03 0.26 1.03 1.45 

Florida 

All 7,757 1.16 100 0.24 0.73 2.39 3.37 

Acquisition Method 

Bought 7,246 1.07 100 0.23 0.68 2.22 3.18 

Caught 1,212 1.05 100 0.20 0.64 2.18 3.03 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 1,418 1.20 100 0.24 0.72 2.54 3.44 

Bought; 20,000 to 50,000 3,141 1.09 100 0.24 0.70 2.18 3.21 

Bought; >50,000 1,695 1.05 100 0.22 0.67 2.18 3.17 

Bought; Unknown 992 0.89 100 0.22 0.60 1.96 2.50 

Caught; 0 to 20,000 246 1.14 100 0.26 0.76 2.40 3.72 

Caught; 20,000 to 50,000 563 1.14 100 0.20 0.67 2.31 3.13 

Caught; >50,000 274 0.95 100 0.16 0.61 2.09 3.06 

Caught; Unknown 129 0.74 100 0.22 0.54 1.36 2.03 
 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-44. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method, 

Uncooked (g/kg-day) (continued) 

Percentiles 

State Category Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating 

Fish 

10th 50th 90th 95th 

Florida (continued) 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 511 0.97 100 0.20 0.64 2.14 2.89 

Eats Caught and Bought 701 2.28 100 0.65 1.48 4.38 6.37 

Eats Bought Only 6,545 1.06 100 0.23 0.68 2.20 3.08 

Habitat 

Freshwater 1,426 0.59 100 0.09 0.37 1.36 1.89 

Estuarine 4,124 0.50 100 0.10 0.31 1.05 1.46 

Marine 6,124 0.99 100 0.20 0.62 2.01 2.94 

Eats Freshwater/Estuarine Caught Fish 

Exclusively 235 0.91 100 0.13 0.56 2.14 2.7 

Sometimes 458 2.21 100 0.56 1.40 4.54 6.17 

Never 7,064 1.11 100 0.24 0.71 2.27 3.24 

Fish/Shellfish Type 

Shellfish 3,260 0.50 100 0.10 0.30 1.07 1.42 

Finfish 6,428 1.15 100 0.29 0.73 2.28 3.32 

Minnesota 

All 793 0.44 100 0.06 0.26 0.86 1.44 

Acquisition Method 

Bought 755 0.30 100 0.04 0.16 0.73 1.10 

Caught 593 0.24 100 0.02 0.09 0.40 0.76 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 76 0.39 100 0.05 0.18 0.85 1.44 

Bought; 20,000 to 50,000 284 0.29 100 0.04 0.17 0.63 0.99 

Bought; >50,000 312 0.28 100 0.03 0.15 0.76 1.30 

Bought; Unknown 83 0.30 100 0.03 0.26 0.73 0.87 

Caught; 0 to 20,000 56 0.26 100 0.02 0.07 0.65 1.45 

Caught; 20,000 to 50,000 232 0.31 100 0.03 0.10 0.41 0.61 

Caught; >50,000 235 0.21 100 0.03 0.11 0.5 0.86 

Caught; Unknown 70 0.09 100 0.02 0.04 0.19 0.21 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 38 0.21 100 0.02 0.11 0.49 0.68 

Eats Caught and Bought 555 0.53 100 0.11 0.31 0.93 1.76 

Eats Bought Only 200 0.31 100 0.03 0.18 0.75 1.21 

Habitat 

Freshwater 593 0.24 100 0.02 0.09 0.4 0.76 

Estuarine 559 0.04 100 0.00 0.02 0.09 0.16 

Marine 755 0.26 100 0.03 0.14 0.67 0.97 

Eats Freshwater/Estuarine Caught Fish 

Exclusively 38 0.21 100 0.02 0.11 0.49 0.68 

Sometimes 555 0.53 100 0.11 0.31 0.93 1.76 

Never 200 0.31 100 0.03 0.18 0.75 1.21 

Page Exposure Factors Handbook 

10-126 September 2011 
 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-44. Fish Consumption per kg Body Weight, Consumers Only, by State, Acquisition Method, 

Uncooked (g/kg-day) (continued) 

Percentiles 

State Category Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating 

Fish 

10th 50th 90th 95th 

Minnesota (continued) 

Fish/Shellfish Type 

Shellfish 559 0.08 100 0.01 0.03 0.19 0.32 

Finfish 791 0.38 100 0.04 0.21 0.77 1.15 

North Dakota 

All 546 0.45 100 0.07 0.25 0.99 1.62 

Acquisition Method 

Bought 516 0.34 100 0.04 0.15 0.81 1.36 

Caught 389 0.18 100 0.02 0.09 0.46 0.61 

Acquisition Method-Household Income ($) Group 

Bought; 0 to 20,000 45 0.63 100 0.06 0.19 2.06 2.97 

Bought; 20,000 to 50,000 213 0.30 100 0.04 0.15 0.69 1.37 

Bought; >50,000 210 0.28 100 0.04 0.15 0.64 1.05 

Bought; Unknown 48 0.47 100 0.04 0.19 0.93 1.44 

Caught; 0 to 20,000 27 0.25 100 0.02 0.10 0.56 0.86 

Caught; 20,000 to 50,000 142 0.15 100 0.02 0.07 0.33 0.54 

Caught; >50,000 173 0.20 100 0.03 0.11 0.51 0.71 

Caught; Unknown 47 0.17 100 0.04 0.08 0.30 0.32 

Acquisition Method of Fish/Shellfish Eaten 

Eats Caught Only 30 0.28 100 0.07 0.18 0.43 0.68 

Eats Caught and Bought 359 0.52 100 0.10 0.31 1.10 1.66 

Eats Bought Only 157 0.33 100 0.03 0.13 0.71 1.29 

Habitat 

Freshwater 389 0.18 100 0.02 0.09 0.46 0.61 

Estuarine 407 0.04 100 0.01 0.01 0.08 0.14 

Marine 516 0.31 100 0.03 0.13 0.72 1.15 

Eats Freshwater/Estuarine Caught Fish 

Exclusively 30 0.28 100 0.07 0.18 0.43 0.68 

Sometimes 359 0.52 100 0.10 0.31 1.10 1.66 

Never 157 0.33 100 0.03 0.13 0.71 1.29 

Fish/Shellfish Type 

Shellfish 407 0.07 100 0.01 0.03 0.17 0.27 

Finfish 541 0.40 100 0.05 0.21 0.89 1.44 

* Percentiles cannot be estimated due to small sample size. 

Notes: FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. 

A respondent can be represented in more than one row. 

Source: Westat (2006). 

Exposure Factors Handbook Page
 

September 2011 10-127 
 

 

Table 10-45. Fish Consumption per kg Body Weight, All Respondents, by State, Subpopulation, and Sex 

(g/kg-day, as-consumed) 

Percentiles 

State Category Sample Arithmetic Percent 10th 50th 90th 95th 

Size Mean Eating 

Fish 

Connecticut 

Population for Sample Selection 

Anglers 250 0.64 97.6 0.08 0.40 1.51 2.07 

Aquaculture Students 25 0.22 76.0 0.00 0.07 0.65 0.89 

Asians 396 1.15 99.2 0.30 0.91 2.28 3.15 

Commercial Fishermen 173 0.65 96.0 0.05 0.44 1.51 1.63 

EFNEP Participants 67 1.00 86.6 0.00 0.31 2.46 3.50 

General 420 0.41 85.1 0.00 0.25 1.00 1.32 

WIC Participants 699 0.80 79.1 0.00 0.42 1.93 3.02 

Population for Sample Selection and Sex Group 

Angler; Males 197 0.68 97.5 0.08 0.41 1.68 2.16 

Angler; Females 53 0.49 98.1 0.10 0.30 1.06 1.45 

Aquaculture Students; Males 10 0.21 90.0 0.00 0.09 0.75 0.85 

Aquaculture Students; Females 15 0.24 66.7 0.00 0.03 0.62 0.91 

Asians; Males 188 1.06 99.5 0.27 0.88 1.99 2.44 

Asians; Females 208 1.24 99.0 0.36 0.92 2.85 3.33 

Commercial Fishermen; Males 94 0.67 92.6 0.05 0.46 1.54 1.62 

Commercial Fishermen; Females 79 0.63 100 0.06 0.42 1.40 1.93 

EFNEP Participants; Males 25 1.05 88.0 0.00 0.33 2.83 3.80 

EFNEP Participants; Females 42 0.96 85.7 0.00 0.26 2.02 3.95 

General; Males 201 0.39 86.2 0.00 0.24 1.05 1.34 

General; Females 219 0.43 84.0 0.00 0.28 0.95 1.30 

WIC Participants; Males 312 0.94 79.2 0.00 0.45 2.30 3.52 

WIC Participants; Females 387 0.69 79.1 0.00 0.40 1.64 2.43 

Florida 

Population for Sample Selection 

General 15,367 0.47 50.5 0.00 0.06 1.27 1.91 

Population for Sample Selection and Sex Group 

General; Males 7,911 0.44 49.2 0.00 0.00 1.22 1.84 

General; Females 7,426 0.50 51.9 0.00 0.10 1.32 1.98 

Unknown 30 0.41 48.0 0.00 0.00 1.41 2.38 

Minnesota 

Population for Sample Selection 

American Indians 216 0.21 88.9 0.00 0.13 0.52 0.64 

Anglers 1,152 0.31 96.3 0.04 0.17 0.66 0.97 

General 837 0.31 94.4 0.02 0.18 0.62 1.07 

New Mothers 401 0.33 85.0 0.00 0.15 0.80 1.21 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-128 September 2011 
 

Table 10-45. Fish Consumption per kg Body Weight, All Respondents, by State, Subpopulation, and Sex 

(g/kg-day, as-consumed) (continued) 

Percentiles 

50th 95th State Category Sample Arithmetic Percent 10th 90th 

Size Mean Eating 

Fish 

Minnesota (continued) 

Population for Sample Selection and Sex Group 

American Indians; Males 108 0.19 89.8 0.00 0.14 0.46 0.55 

American Indians; Females 108 0.23 88.0 0.00 0.12 0.57 0.93 

Anglers; Males 606 0.30 96.9 0.04 0.18 0.63 0.93 

Anglers; Females 546 0.31 95.6 0.04 0.17 0.70 1.04 

General; Males 419 0.26 95.3 0.02 0.16 0.58 1.06 

General; Females 418 0.36 93.4 0.02 0.21 0.65 1.10 

New Mothers; Males 205 0.27 86.3 0.00 0.15 0.67 0.93 

New Mothers; Females 196 0.39 83.7 0.00 0.14 0.95 1.42 

North Dakota 

Population for Sample Selection 

American Indians 106 0.35 60.4 0.00 0.04 1.10 2.27 

Anglers 854 0.32 94.6 0.04 0.19 0.77 1.14 

General 575 0.32 95.2 0.03 0.18 0.71 1.18 

Population for Sample Selection and Sex Group 

American Indians; Males 50 0.35 58.0 0.00 0.04 0.76 1.39 

American Indians; Females 56 0.36 62.5 0.00 0.05 1.34 2.32 

Anglers; Males 467 0.32 95.3 0.04 0.19 0.77 1.14 

Anglers; Females 387 0.33 93.8 0.03 0.19 0.77 1.18 

General; Males 276 0.32 96.2 0.04 0.19 0.68 1.20 

General; Females 299 0.32 94.2 0.03 0.17 0.73 1.16 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. Subpopulations statistics are 

unweighted. 

EFNEP = Expanded Food and Nutrition Education Program. 

WIC = USDA’s Women, Infants, and Children Program. 

Source:	 Westat (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-129 
 

 

Table 10-46. Fish Consumption per kg, Consumers Only, by State, Subpopulation, and Sex 

(g/kg-day, as-consumed) 

State Category Sample 

Size 

Arithmetic 

Mean 

Percent 

Eating 

Fish 

Percentiles 

10th 50th 90th 95th 

Connecticut 

Population for Sample Selection 

Angler 244 0.66 100 

Aquaculture Students 19 0.30 100 

Asians 393 1.16 100 

Commercial Fisherman 166 0.68 100 

EFNEP Participants 58 1.15 100 

General 362 0.48 100 

WIC Participants 553 1.01 100 

Population for Sample Selection and Sex Group 

Angler; Male 192 0.70 100 

Angler; Female 52 0.50 100 

Aquaculture Students; Male 9 0.23 100 

Aquaculture Students; Female 10 0.36 100 

Asians; Male 187 1.06 100 

Asians; Female 206 1.25 100 

Commercial Fishermen; Male 87 0.72 100 

Commercial Fishermen; Female 79 0.63 100 

EFNEP Participants; Male 22 1.20 100 

EFNEP Participants; Female 36 1.12 100 

General; Male 175 0.45 100 

General; Female 187 0.52 100 

WIC Participants; Male 247 1.18 100 

WIC Participants; Female 306 0.87 100 

Population for Sample Selection and Eats Freshwater/Estuarine Caught Fish Group 

Angler; Exclusively 1 0.04 100 

Angler; Sometimes 190 0.74 100 

Angler; Never 53 0.38 100 

Aquaculture Students; Sometimes 2 0.34 100 

Aquaculture Students; Never 17 0.29 100 

Asians; Sometimes 199 1.23 100 

Asians; Never 194 1.09 100 

Commercial Fishermen; Sometimes 120 0.78 100 

Commercial Fishermen; Never 46 0.41 100 

EFNEP Participants; Sometimes 8 0.25 100 

EFNEP Participants; Never 50 1.29 100 

General; Sometimes 50 0.46 100 

General; Never 312 0.49 100 

WIC Participants; Sometimes 67 1.49 100 

WIC Participants; Never 486 0.95 100 

0.10 

0.02 

0.31 

0.09 

0.11 

0.07 

0.12 

0.10 

0.11 

0.01 

0.03 

0.28 

0.37 

0.12 

0.06 

0.14 

0.07 

0.08 

0.05 

0.12 

0.12 

* 

0.14 

0.05 

* 

0.02 

0.30 

0.34 

0.18 

0.03 

0.14 

0.09 

0.09 

0.07 

0.28 

0.10 

0.40 

0.14 

0.91 

0.46 

0.39 

0.32 

0.61 

0.42 

0.33 

0.11 

0.31 

0.88 

0.93 

0.54 

0.42 

0.42 

0.39 

0.29 

0.34 

0.69 

0.59 

* 

0.44 

0.27 

0.21 

0.14 

0.93 

0.87 

0.54 

0.30 

0.22 

0.52 

0.29 

0.32 

0.91 

0.60 

1.55 

0.75 

2.28 

1.53 

2.69 

1.09 

2.30 

1.69 

1.07 

0.74 

0.75 

1.99 

2.86 

1.57 

1.40 

2.89 

2.38 

1.11 

1.03 

2.89 

1.87 

* 

1.69 

0.89 

* 

0.80 

2.94 

2.03 

1.58 

0.89 

0.40 

2.82 

1.10 

1.06 

3.43 

2.02 

2.07 

0.91 

3.16 

1.65 

4.51 

1.37 

3.39 

2.17 

1.45 

* 

1.00 

2.44 

3.34 

1.63 

1.91 

3.75 

4.50 

1.40 

1.35 

3.78 

2.73 

* 

2.18 

1.00 

* 

0.93 

3.50 

2.39 

1.98 

1.36 

* 

6.09 

1.25 

1.41 

5.12 

3.12 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-130 September 2011 
 

Table 10-46. Fish Consumption per kg, Consumers Only, by State, Subpopulation, and Sex 

(g/kg-day, as-consumed) (continued) 

Percentiles 

State Category Sample Arithmetic Percent 10th 50th 90th 95th 

Size Mean Eating 

Fish 

Florida 

Population for Sample Selection 

General 7,757 0.93 100 0.19 0.58 1.89 2.73 

Population for Sample Selection and Sex Group 

General; Male 3,880 0.90 100 0.18 0.55 1.85 2.65 

General; Female 3,861 0.95 100 0.19 0.62 1.94 2.78 

Unknown 16 0.85 100 0.12 0.69 2.37 2.61 

Population for Sample Selection and Eats Freshwater/Estuarine Caught Fish Group 

General; Exclusively 235 0.71 100 0.10 0.42 1.60 2.16 

General; Sometimes 458 1.73 100 0.43 1.10 3.44 4.96 

General; Never 7,064 0.88 100 0.18 0.56 1.81 2.60 

Minnesota 

Population for Sample Selection 

American Indian 192 0.24 100 0.02 0.15 0.53 0.70 

Anglers 1,109 0.32 100 0.05 0.18 0.67 0.99 

General 793 0.33 100 0.04 0.20 0.65 1.08 

New Mothers 341 0.38 100 0.04 0.20 0.89 1.30 

Population for Sample Selection and Sex Group 

American Indians; Male 97 0.21 100 0.03 0.15 0.49 0.55 

American Indians; Female 95 0.26 100 0.02 0.16 0.59 0.95 

Anglers; Male 587 0.31 100 0.05 0.18 0.63 0.93 

Anglers; Female 522 0.33 100 0.05 0.18 0.72 1.05 

General; Male 401 0.28 100 0.04 0.17 0.62 1.07 

General; Female 392 0.38 100 0.05 0.22 0.70 1.22 

New Mothers; Male 177 0.31 100 0.04 0.19 0.75 1.06 

New Mothers; Female 164 0.46 100 0.05 0.21 1.04 1.83 

Population for Sample Selection and Eats Freshwater/Estuarine Caught Fish Group 

American Indians; Exclusively 31 0.18 100 0.01 0.07 0.42 0.55 

American Indians; Sometimes 136 0.28 100 0.05 0.18 0.57 0.92 

American Indians; Never 25 0.05 100 0.01 0.04 0.12 0.15 

Anglers; Exclusively 57 0.35 100 0.02 0.16 0.89 1.93 

Anglers; Sometimes 879 0.34 100 0.07 0.20 0.71 1.05 

Anglers; Never 173 0.20 100 0.03 0.10 0.46 0.66 

General; Exclusively 38 0.16 100 0.02 0.08 0.37 0.51 

General; Sometimes 555 0.40 100 0.08 0.23 0.70 1.32 

General; Never 200 0.23 100 0.02 0.14 0.56 0.91 

New Mothers; Exclusively 17 0.06 100 0.02 0.09 0.20 0.25 

New Mothers; Sometimes 189 0.47 100 0.07 0.27 1.00 1.32 

New Mothers; Never 135 0.30 100 0.03 0.12 0.74 1.35 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-131 
 

 

 

 

Table 10-46. Fish Consumption per kg, Consumers Only, by State, Subpopulation, and Sex 

(g/kg-day, as-consumed) (continued) 

Percentiles 

State Category Sample Arithmetic Percent 10th 50th 90th 95th 

Size Mean Eating 

Fish 

North Dakota 

Population for Sample Selection 

American Indians 64 0.58 100 0.03 0.19 1.75 2.65 

Anglers 808 0.34 100 0.05 0.20 0.81 1.17 

General 546 0.34 100 0.05 0.19 0.74 1.21 

Population for Sample Selection and Sex Group 

American Indians; Male 29 0.60 100 0.03 0.18 1.31 3.67 

American Indians; Female 35 0.57 100 0.02 0.19 2.25 2.55 

Anglers; Male 445 0.33 100 0.05 0.20 0.78 1.14 

Anglers; Female 363 0.35 100 0.05 0.21 0.83 1.29 

General; Male 265 0.33 100 0.04 0.20 0.74 1.22 

General; Female 281 0.34 100 0.05 0.18 0.74 1.20 

Population for Sample Selection and Eats Freshwater/Estuarine Caught Fish Group 

American Indians; Exclusively 4 0.05 100 * 0.05 * * 

American Indians; Sometimes 30 1.08 100 0.13 0.60 2.65 3.62 

American Indians; Never 30 0.16 100 0.02 0.07 0.36 0.66 

Anglers; Exclusively 47 0.19 100 0.01 0.07 0.61 1.02 

Anglers; Sometimes 660 0.38 100 0.07 0.23 0.84 1.29 

Anglers; Never 101 0.18 100 0.02 0.10 0.41 0.53 

General; Exclusively 30 0.21 100 0.05 0.14 0.33 0.51 

General; Sometimes 359 0.39 100 0.07 0.23 0.82 1.25 

General; Never 157 0.25 100 0.03 0.10 0.53 0.97 

* Percentiles cannot be estimated due to small sample size. 

Notes:	 FL consumption is based on a 7-day recall; CT, MN, and ND consumptions are based on rate of 

consumption. 

FL consumption excludes away-from-home consumption by children <18. 

Statistics are weighted to represent the general population in the states. Subpopulations statistics are 

unweighted. 

Source:	 Westat (2006). 

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Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-132 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-47. Fish Consumption Among General Population in Four States, Consumers Only 

(g/kg-day, as-consumed) 

N Mean CI Percentiles Maximum 

10th 25th 50th 75th 90th 95th 

Connecticut 

1 to <6 years 14 0.61 0.42–0.81 0.16 0.26 0.55 0.83 1.4 1.6 1.6 

6 to <11 years 22 0.59 0.040–0.77 0.14 0.23 0.47 0.96 1.2 1.3 1.5 

11 to <16 years 18 0.32 0.17–0.46 0.07 0.14 0.19 0.38 0.52 0.84 1.3 

16 to <30 years 

Females 

Males 

14 

10 

0.84 

0.23 

0.10–1.58 

0.14–0.32 

0.11 

0.08 

0.30 

0.13 

0.35 

0.21 

0.87 

0.25 

1.1 

0.47 

3.1 

0.56 

7.0 

0.58 

30 to <50 years 

Females 

Males 

74 

74 

0.53 

0.51 

0.37–0.70 

0.40–0.61 

0.05 

0.11 

0.15 

0.18 

0.34 

0.35 

0.67 

0.70 

1.1 

1.2 

1.5 

1.5 

4.5 

2.2 

>50 years 

Females 

Males 

70 

57 

0.48 

0.38 

0.37–0.59 

0.30–0.46 

0.05 

0.10 

0.13 

0.17 

0.37 

0.26 

0.72 

0.50 

1.0 

0.93 

1.4 

1.1 

2.7 

1.4 

Eats Caught Only 

Eats Caught and Bought 

Eats Bought Only 

1 

70 

291 

0.01 

0.49 

0.48 

-

0.36–0.61 

0.40–0.57 

-

0.10 

0.06 

-

0.17 

0.16 

-

0.34 

0.32 

-

0.75 

0.61 

-

1.1 

1.1 

-

1.3 

1.4 

0.01 

2.2 

7.0 

Anglers 

General Population 

244 

362 

0.66 

0.48 

-

-

0.10 

0.07 

0.20 

0.16 

0.40 

0.32 

0.80 

0.63 

1.6 

1.1 

2.1 

1.4 

3.5 

2.4 

Florida 

1 to <6 years 420 2.3 2.05–2.63 0.5 1.0 1.7 2.8 4.7 6.8 14.6 

6 to <11 years 375 1.1 0.98–1.22 0.28 0.52 0.81 1.4 2.2 3.0 9.4 

11 to <16 years 365 0.85 0.73–0.98 0.20 0.36 0.63 0.99 1.6 2.2 11.0 

16 to <30 years 

Females 

Males 

753 

754 

0.89 

0.96 

0.74–1.04 

0.80–1.12 

0.16 

0.16 

0.31 

0.28 

0.55 

0.52 

0.95 

0.99 

1.8 

1.8 

2.4 

2.7 

25 

34 

30 to <50 years 

Females 

Males 

1,287 

1,334 

0.94 

0.81 

0.87–1.00 

0.74–0.88 

0.18 

0.17 

0.33 

0.28 

0.63 

0.53 

1.0 

0.95 

1.9 

1.7 

2.7 

2.4 

20 

23 

>50 years 

Females 

Males 

1,171 

1,192 

0.73 

0.70 

0.69–0.77 

0.66–0.75 

0.19 

0.17 

0.31 

0.27 

0.52 

0.50 

0.94 

0.84 

1.5 

1.4 

2.1 

1.9 

7.4 

14 

Eats Caught Only 

Eats Caught and Bought 

Eats Bought Only 

511 

701 

6,545 

0.76 

1.8 

0.85 

0.66–0.86 

1.6–2.1 

0.81–0.89 

0.15 

0.50 

0.18 

0.30 

0.76 

0.30 

0.50 

1.2 

0.54 

0.90 

2.0 

0.98 

1.7 

3.4 

1.8 

2.3 

5.1 

2.5 

7.4 

34 

24 

Exposure Factors Handbook Page
 

September 2011 10-133 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-47. Fish Consumption Among General Population Children in Four States, Consumers Only 

(g/kg-day, as-consumed) (continued) 

N Mean CI 

Percentiles Maximum 

10th 25th 50th 75th 90th 95th 

Minnesota 

1 to <6 years 46 0.58 0.32–0.85 0.07 0.15 0.46 0.73 1.1 1.8 8.0 

6 to <11 years 42 0.38 0.21–0.54 0.05 0.07 0.25 0.47 1.0 1.4 5.3 

11 to <16 years 63 0.24 0.16–0.31 0.03 0.06 0.21 0.32 0.55 0.59 1.4 

16 to <30 years 

Females 

Males 

44 

52 

0.69 

0.11 

–0.21–1.59 

0.07–0.15 

0.02 

0.02 

0.08 

0.02 

0.16 

0.08 

0.29 

0.14 

0.66 

0.27 

3.0 

0.33 

9.2 

0.74 

30 to <50 years 

Females 

Males 

127 

115 

0.25 

0.25 

0.21–0.30 

0.17–0.32 

0.04 

0.07 

0.10 

0.11 

0.23 

0.17 

0.32 

0.30 

0.51 

0.42 

0.58 

0.64 

1.3 

1.9 

>50 years 

Females 

Males 

150 

153 

0.36 

0.24 

0.26–0.46 

0.20–0.29 

0.05 

0.05 

0.11 

0.11 

0.22 

0.19 

0.38 

0.28 

0.93 

0.53 

1.4 

0.68 

1.9 

1.3 

Eats Caught Only 

Eats Caught and Bought 

Eats Bought Only 

38 

555 

200 

0.16 

0.40 

0.23 

0.05–0.26 

0.27–0.52 

0.18–0.28 

0.02 

0.08 

0.02 

0.03 

0.11 

0.05 

0.08 

0.23 

0.14 

0.25 

0.49 

0.26 

0.37 

0.70 

0.56 

0.51 

1.3 

0.91 

0.57 

9.2 

8.0 

Anglers 

General Population 

1,109 

793 

0.32 

0.33 

-

-

0.05 

0.04 

0.10 

0.10 

0.18 

0.20 

0.34 

0.34 

0.67 

0.65 

0.99 

1.1 

2.2 

1.8 

North Dakota 

1 to <6 years 28 0.70 0.24–1.17 0.05 0.12 0.23 0.68 1.6 3.8 6.8 

6 to <11 years 41 0.56 0.31–0.81 0.11 0.21 0.30 0.66 1.2 1.5 4.3 

11 to <16 years 53 0.41 0.23–0.59 0.06 0.12 0.22 0.54 1.0 1.3 2.3 

16 to <30 years 

Females 

Males 

38 

36 

0.20 

0.22 

0.14–0.26 

0.13–0.31 

0.04 

0.04 

0.06 

0.07 

0.15 

0.13 

0.26 

0.23 

0.41 

0.45 

0.67 

0.56 

0.80 

1.9 

30 to <50 years 

Females 

Males 

93 

88 

0.29 

0.22 

0.22–0.36 

0.17–0.27 

0.05 

0.05 

0.10 

0.08 

0.18 

0.18 

0.36 

0.26 

0.56 

0.45 

0.87 

0.54 

2.6 

1.3 

>50 years 

Females 

Males 

92 

76 

0.40 

0.31 

0.27–0.54 

0.20–0.41 

0.06 

0.04 

0.10 

0.08 

0.17 

0.19 

0.52 

0.33 

1.1 

0.74 

1.5 

1.2 

4.2 

1.8 

Eats Caught Only 

Eats Caught and Bought 

Eats Bought Only 

30 

359 

157 

0.21 

0.39 

0.25 

0.09–0.32 

0.29–0.49 

0.13–0.36 

0.05 

0.07 

0.03 

0.09 

0.13 

0.05 

0.14 

0.23 

0.10 

0.22 

0.43 

0.24 

0.33 

0.82 

0.53 

0.51 

1.3 

0.97 

1.8 

4.3 

6.8 

Anglers 

General Population 

808 

546 

0.34 

0.34 

-

-

0.05 

0.05 

0.10 

0.09 

0.20 

0.19 

0.39 

0.35 

0.81 

0.74 

1.2 

1.2 

2.0 

2.2 

N = Sample size. 

CI = Confidence interval. 

- Not reported. 

Source: Moya et al. (2008). 

Page Exposure Factors Handbook 

10-134 September 2011 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-48. Estimated Number of Participants in Marine Recreational Fishing by State and Subregion 

Subregion State 

Coastal 

Participants 

Non-Coastal 

Participants Out of Statea 

Total 

Participantsa 

Pacific Southern California 

Northern California 

Oregon 

TOTAL 

902 

534 

265 

1,701 

8 

99 

19 

126 

159 

63 

78 

910 

633 

284 

North Atlantic Connecticut 

Maine 

Massachusetts 

New Hampshire 

Rhode Island 

TOTAL 

186 

93 

377 

34 

97 

787 

*b 

9 

69 

10 

* 

88 

47 

100 

273 

32 

157 

186 

102 

446 

44 

97 

Mid-Atlantic Delaware 

Maryland 

New Jersey 

New York 

Virginia 

TOTAL 

90 

540 

583 

539 

294 

1,046 

* 

32 

9 

13 

29 

83 

159 

268 

433 

70 

131 

90 

572 

592 

552 

323 

South Atlantic Florida 

Georgia 

North Carolina 

South Carolina 

TOTAL 

1,201 

89 

398 

131 

1,819 

* 

61 

224 

77 

362 

741 

29 

745 

304 

1,201 

150 

622 

208 

Gulf of Mexico Alabama 

Florida 

Louisiana 

Mississippi 

TOTAL 

95 

1,053 

394 

157 

1,699 

9 

* 

48 

42 

99 

101 

1,349 

63 

51 

104 

1,053 

442 

200 

GRAND TOTAL 8,053 760 a Not additive across states. One person can be counted as "OUT OF STATE" for more than one state. b An asterisk (*) denotes no non-coastal counties in state. 

Source: NMFS (1993). 

Exposure Factors Handbook Page
 

September 2011 10-135 
 

 

 

 

 

 

 

 

 

Table 10-49. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine Recreational Fishermen, 

by Wave and Subregion 

Atlantic and Gulf Pacific 

Region Weight (1,000 kg) Region Weight (1,000 kg) 

Jan/Feb 

Mar/Apr 

May/Jun 

Jul/Aug 

Sep/Oct 

Nov/Dec 

South Atlantic 

Gulf 

TOTAL 

North Atlantic 

Mid-Atlantic 

South Atlantic 

Gulf 

TOTAL 

North Atlantic 

Mid-Atlantic 

South Atlantic 

Gulf 

TOTAL 

North Atlantic 

Mid-Atlantic 

South Atlantic 

Gulf 

TOTAL 

North Atlantic 

Mid-Atlantic 

South Atlantic 

Gulf 

TOTAL 

North Atlantic 

Mid-Atlantic 

South Atlantic 

Gulf 

TOTAL 

GRAND TOTAL 

1,060 So. California 418 

3,683 N. California 101 

4,743 Oregon 165 

TOTAL 684 

310 So. California 590 

1,030 N. California 346 

1,913 Oregon 144 

3,703 TOTAL 1,080 

6,956 

3,272 So. California 1,195 

4,815 N. California 563 

4,234 Oregon 581 

5,936 TOTAL 2,339 

18,257 

4,003 So. California 1,566 

9,693 N. California 1,101 

4,032 Oregon 39 

5,964 TOTAL 2,706 

23,692 

2,980 So. California 859 

7,798 N. California 1,032 

3,296 Oregon 724 

7,516 TOTAL 2,615 

21,590 

456 So. California 447 

1,649 N. California 417 

2,404 Oregon 65 

4,278 TOTAL 929 

8,787 

84,025 GRAND TOTAL 10,353 

Source: NMFS (1993). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-136 September 2011 
 

 

 

 

 

Table 10-50. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status 

Intake Among Anglers 

Regiona Mean 95th Percentile 

North Atlantic 6.2 20.1 

Mid-Atlantic 6.3 18.9 

South Atlantic 4.7 15.9 

All Atlantic 5.6 18.0 

Gulf 7.2 26.1 

Southern California 2.0 5.5 

Northern California 2.0 5.7 

Oregon 2.2 8.9 

All Pacific 2.0 6.8 a	 North Atlantic—ME, NH, MA, RI, and CT; Mid-Atlantic—NY, NJ, MD, DE, and VA; South Atlantic— 

NC, SC, GA, and FL (Atlantic Coast); Gulf—AL, MS, LA, and FL (Gulf Coast). 

Source:	 NMFS (1993). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-137 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-51. Estimated Weight of Fish Caught (Catch Type A and B1)a by Marine Recreational Fishermen, by Species 

Group and Subregion 

North Atlantic 

(1,000 kg) 

Mid-Atlantic 

(1,000 kg) 

South Atlantic 

(1,000 kg) 

Gulf 

(1,000 kg) 

All Atlantic and Gulf 

(1,000 kg) 

Cartilaginous Fishes 

Eels 

Herrings 

Catfishes 

Toadfishes 

Cods and Hakes 

Searobins 

Sculpins 

Temperate Basses 

Sea Basses 

Bluefish 

Jacks 

Dolphins 

Snappers 

Grunts 

Porgies 

Drums 

Mullets 

Barracudas 

Wrasses 

Mackerels and Tunas 

Flounders 

Triggerfishes/Filefishes 

Puffers 

Other fishes 

66 

14 

118 

0 

0 

2,404 

2 

1 

837 

22 

4,177 

0 

65 

0 

0 

132 

3 

1 

0 

783 

878 

512 

0 

* 

105 

1,673 

9 

69 

306 

7 

988 

68 

* 

2,166 

2,166 

3,962 

138 

809 

* 

9 

417 

2,458 

43 

* 

1,953 

3,348 

4,259 

48 

16 

72 

162 

*b 

1 

138 

0 

4 

* 

0 

22 

644 

1,065 

760 

2,435 

508 

239 

1,082 

2,953 

382 

356 

46 

4,738 

532 

109 

56 

709 

318 

0c 

89 

535 

* 

0 

* 

0 

4 

2,477 

158 

2,477 

1,599 

3,219 

816 

2,629 

9,866 

658 

244 

113 

4,036 

377 

544 

4 

915 

2,219 

23 

177 

979 

7 

1,396 

70 

1 

2,229 

5,309 

5,362 

3,375 

4,908 

3,727 

1,064 

4,160 

15,280 

1,084 

600 

2,895 

13,000 

5,680 

701 

76 

1,801 

Species Group 

Southern California 

(1,000 kg) 

Northern California 

(1,000 kg) 

Oregon 

(1,000 kg) All Pacific 

Cartilaginous fish 

Sturgeons 

Herrings 

Anchovies 

Smelts 

Cods and Hakes 

Silversides 

Striped Bass 

Sea Basses 

Jacks 

Croakers 

Sea Chubs 

Surfperches 

Pacific Barracuda 

Wrasses 

Tunas and Mackerels 

Rockfishes 

California Scorpionfish 

Sablefishes 

Greenlings 

Sculpins 

Flatfishes 

Other fishes 

35 

0b 

10 

*c 

0 

0 

58 

0 

1,319 

469 

141 

53 

74 

866 

73 

1,260 

409 

86 

0 

22 

6 

106 

89 

162 

89 

15 

7 

71 

0 

148 

51 

17 

17 

136 

1 

221 

10 

5 

36 

1,713 

0 

0 

492 

81 

251 

36 

1 

13 

40 

0 

0 

0 

0 

0 

0 

1 

0 

0 

47 

0 

0 

1 

890 

0 

5 

363 

44 

5 

307 

198 

102 

65 

7 

71 

0 

206 

51 

1,336 

487 

277 

54 

342 

876 

78 

1,297 

3,012 

86 

5 

877 

131 

362 

432 a For Catch Type A and B1, the fish were not thrown back. b An asterisk (*) denotes data not reported. c Zero (0) = <1,000 kg. 

Source: NMFS (1993). 

Page Exposure Factors Handbook 

10-138 September 2011 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-52. Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement Bay, 

Washington 

Fishing Frequency 

Frequency Percent 

in the Summera 

Frequency Percent 

in the Fallb 

Frequency Percent 

in the Fallc 

Daily 

Weekly 

Monthly 

Bimonthly 

Biyearly 

Yearly 

10.4 

50.3 

20.1 

6.7 

4.4 

8.1 

8.3 

52.3 

15.9 

3.8 

6.1 

13.6 

5.8 

51.0 

21.1 

4.2 

6.3 

11.6 a Summer—July through September, includes 5 survey days and 4 survey areas (i.e., Areas #1, #2, #3, and 

#4) b Fall—September through November, includes 4 survey days and 4 survey areas (i.e., Areas #1, #2, #3, and 

#4) c Fall—September through November, includes 4 survey days described in footnote b plus an additional 

survey area (5 survey areas) (i.e., Areas #1, #2, #3, #4, and #5) 

Source: Pierce et al. (1981). 

Table 10-53. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler Populations 

Based on the Re-Analysis of the Puffer et al. (1982) and Pierce et al. (1981) Data 

50th Percentile 90th Percentile 

Survey Population 

Puffer et al. (1982) 

Pierce et al. (1981) 

37 

19 

225 

155 

Average 28 190 

Total Angler Population 

Puffer et al. (1982) 

Pierce et al. (1981) 

2.9a 

1.0 

35b 

13 

Average 2.0 24 a Estimated based on the average intake for the 0–90th percentile anglers. b Estimated based on the average intake for the 91st

–96th percentile anglers. 

Source: Price et al. (1994). 

Exposure Factors Handbook Page
 

September 2011 10-139 
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-54. Median Intake Rates Based on Demographic Data of Sport Fishermen and Their Family/Living 

Group 

Percent of Total Interviewed 

Median Intake Rates 

(g/person-day) 

Ethnic Group 

Caucasian 

Black 

Mexican American 

Asian/Samoan 

Other 

Age (years) 

<17 

18 to 40 

41 to 65 

>65 

42 

24 

16 

13 

5 

11 

52 

28 

9 

46.0 

24.2 

33.0 

70.6 

-

a 

27.2 

32.5 

39.0 

113.0 a Not reported. 

Source: Puffer et al. (1982). 

Table 10-55. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed Sport Fishermen 

in the Metropolitan Los Angeles Area 

Percentile Intake Rate (g/person-day) 

5 

10 

20 

30 

40 

50 

60 

70 

80 

90 

95 

2.3 

4.0 

8.3 

15.5 

23.9 

36.9 

53.2 

79.8 

120.8 

224.8 

338.8 

Source: Puffer et al. (1982). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-56. Catch Information for Primary Fish Species Kept 

by Sport Fishermen (N = 1,059) 

Species Average Weight (Grams) 

Percent of Fishermen 

who Caught 

White Croaker 

Pacific Mackerel 

Pacific Bonito 

Queenfish 

Jacksmelt 

Walleye Perch 

Shiner Perch 

Opaleye 

Black Perch 

Kelp Bass 

California Halibut 

Shellfisha 

153 

334 

717 

143 

223 

115 

54 

307 

196 

440 

1,752 

421 

34 

25 

18 

17 

13 

10 

7 

6 

5 

5 

4 

3 a Crab, mussels, lobster, abalone. 

Source: Modified from Puffer et al. (1982). 

Table 10-57. Fishing and Crabbing Behavior of Fishermen at Humacao, 

Puerto Rico 

Mean ± Standard Error 

Crabbing 

Number of interviews 

Number of people in group 

Number of adults (>21 years) 

Visits to site/month 

No. crabs caught per season 

Crabs/hour 

Crabs eaten/week 

Range in no. eaten/week 

20 

3.5 ± 0.4 

2.3 ± 0.3 

3.8 ± 0.7 

21.4 ± 4.7 

21.6 ± 4.9 

13.3 ± 2.3 

0–25 

Fishing 

Number of interviews 

Number of people in group 

Number of adults (>21 years) 

Visits to site/month 

No. fish caught per season 

Fish/hour 

Fish eaten/week 

Range in no. eaten/week 

25 

2.9 ± 0.3 

2.3 ± 0.2 

2.8 ± 0.4 

16.9 ± 3.5 

11.3 ± 2.5 

6.8 ± 0.7 

3–30 

Source: Burger and Gochfeld (1991). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-58. Fish Consumption of Delaware Recreational Fishermen and Their Households 

N 

Mean Consumption 

(g/day) SE (%) 

All respondents 867 17.5 5.3 

Sex 

Males 

Females 

496 

369 

18.6 

15.9 

6.6 

8.7 

Age (years) 

0 to 9 

10 to 19 

20 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 69 

70 to 79 

80 to 89 

73 

102 

95 

148 

144 

149 

124 

28 

4 

6.0 

11.4 

11.7 

18.1 

12.6 

28.6 

23.0 

21.8 

53.9 

13.4 

16.8 

10.9 

13.9 

8.5 

11.1 

12.4 

33.4 

68.3 

Race 

African American 

Asian 

Hispanic 

Caucasian 

81 

12 

12 

748 

14.9 

5.6 

3.0 

18.2 

27.1 

31.2 

35.2 

5.3 

N = Sample size. 

SE = Standard error. 

Source: KCA Research Division (1994). 

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Table 10-59. Seafood Consumption Rates of All Fish by Ethnic and Income Groups of Santa
 

Monica Bay 

Consumption (g/day) 

Category N Mean 95% CI 50th 90th 

All respondents 555 49.6 9.3 21.4 107.1 

Ethnicity 

White 217 58.1 19.1 21.4 112.5 

Hispanic 137 28.2 5.9 16.1 64.3 

Black 57 48.6 18.9 24.1 85.7 

Asian 122 51.1 18.7 21.4 115.7 

Other 14 137.3 92.2 85.7 173.6 

Income 

<$5,000 20 42.1 18.0 32.1 64.3 

$5,000 to $10,000 27 40.5 29.1 21.4 48.2 

$10,000 to $25,000 90 40.4 9.3 21.4 80.4 

$25,000 to $50,000 149 46.9 10.5 21.4 113.0 

>$50,000 130 58.9 20.6 21.4 128.6 

N = Sample size. 

CI = Confidence interval. 

Source: Santa Monica Bay Restoration Project (1995). 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-60. Means and Standard Deviations of Selected Characteristics by Population Groups in 

Everglades, Florida 

Variables 

(Na = 330) Mean ± SDb Range 

Age (years) 38.6 ± 18.8 2 to 81 

Sex 

Female 

Male 

38% 

62% 

-

-

Race/ethnicity 

Black 

White 

Hispanic 

46% 

43% 

11% 

-

-

-

Number of Years Fished 15.8 ± 15.8 0–70 

Number Per Week Fished in Past 6 Months of Survey Period 1.8 ± 2.5 0–20 

Number Per Week Fished in Last Month of Survey Period 1.5 ± 1.4 0–12 

Aware of Health Advisories 71% - a N = Number of respondents who reported consuming fish. b SD = Standard deviation. 

- Not reported. 

Source: Florida State Department of Health and Rehabilitative Services (1995). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-61. Grams per Day of Self-Caught Fish Consumed by Recreational Anglers—Alcoa/Lavaca 

Bay 

Cohort Mean 

95% Upper Confidence 

Limit on Mean 

90th or 95th Percentile of 

Distributiona 

Finfish 

Adult men 24.8 27.7 68.1 

Adult women 17.9 19.7 47.8 

Women of childbearing age 18.8 22.1 45.4 

Small children 11.4 14.2 30.3 

Youths 15.6 17.8 45.4 

Shellfish 

Adult men 1.2 1.6 5.1 

Adult women 0.8 1.1 2.4 

Women of childbearing age 0.9 1.2 4.0 

Small children 0.4 0.6 2.0 

Youths 0.7 1.0 4.5 a For shellfish, the 95th percentile value is provided because less than 90% of the individuals 

consumed shellfish, resulting in a 90th percentile of zero. 

Source: Alcoa (1998). 

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Table 10-62. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational Anglers 

Lavaca Bay, Texas 

Portion Size 

Number of Meals (ounces)a 

Age Group 95% Upper 95% Upper 

Mean Confidence Limit Confidence Limit on 

on Mean Mean Mean 

Finfish 

Adult Men 3.2 3.5 8.0 8.2 

Adult Women 2.6 3.0 6.8 7.1 

Women of Childbearing Age 2.8 3.2 6.8 7.3 

Small children (<6 years) 2.6 3.1 4.5 4.7 

Youths (6 to 19 years) 2.4 2.7 6.6 6.9 

Shellfish 

Adult Men 0.3 0.4 3.7 4.3 

Adult Women 0.3 0.4 2.9 3.4 

Women of Childbearing Age 0.3 0.5 3.3 4.3 

Small children (<6 years) 0.3 0.5 2.0 2.4 

Youths (6 to 19 years) 0.3 0.4 2.5 2.9 a Converted from ounces; 1 ounce = 28.35 grams. 

Source: Alcoa (1998). 

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Chapter 10—Intake of Fish and Shellfish 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-63. Consumption Patterns of People Fishing and Crabbing in Barnegat Bay, New Jersey 

Males Females 

N 434 81 

% Eat fish 84.1 78.05 

% Give away fish 55.0 41.2 

% Eat crabs 87.9 94.7 

% Give away crabs 48.2 53.1 

Number of times fish eaten/month 5.21 ± 0.33 5.21 ± 0.33 

% Eaten that are self-caught 48.7 ± 2.15 48.7 ± 2.15 

Number of times crabs eaten/month 2.14 ± 0.32 2.14 ± 0.32 

Average serving size (ounces) 10.12 ± 0.32 10.12 ± 0.32 

Average consumption (males and females) (g/day) 48.3 

N = Sample size. 

Source: Burger et al. (1998). 

Table 10-64. Fish Intake Rates of Members of the Laotian Community of West Contra Costa County, 

California 

Group Sample Size 

Consumption (g/day) 

Mean Percentile Max Min 50th 90th 95th 

All respondents 

Fish consumersa 

229 

199 

18.3 

21.4 

9.1 

9.1 

42.5 

42.5 

85.1 

85.1 

182.3 

-­

-­

1.5 a “Fish consumers” were those who reported consumption of fish at least once a month. 

Max = Maximum. 

Min = Minimum. 

Source: Chiang (1998). 

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Table 10-65. Consumption Rates (g/day) Among Recent Consumersa by Demographic Factor 

Percentiles 

10th 50th 90th 95th N Mean SD 

Overall 465 23.0 32.1 4.0 16.0 48.0 80.0 

Sex 

Male 410 22.7 32.3 4.0 16.0 48.0 72.0
 

Female 35 22.3 26.8 6.0 16.0 53.2 84.0
 

Age (years) 

18 to 45 256 24.2 32.2 5.3 12.0 48.0 84.0 

46 to 65 148 21.0 32.9 4.0 16.0 32.0 64.0 

65 and older 43 21.8 24.4 4.0 16.0 64.0 72.0 

Ethnicity 

African American 41 26.7 38.3 8.0 16.0 48.0 6.04 

Asian-Chinese 26 27.8 34.8 4.0 12.0 80.0 128.0 

Asian-Filipino 70 32.7 48.8 5.3 16.0 72.0 176.0 

Asian-Other 31 22.0 27.6 4.0 8.0 72.0 72.0 

Asian-Pacific Islander 12 38.0 44.2 4.0 24.0 96.0 184.0 

Asian-Vietnamese 51 21.8 20.7 4.0 16.0 48.0 72.0 

Hispanic 52 22.0 29.5 4.0 16.0 48.0 84.0 

Caucasian 158 18.9 27.0 4.0 10.7 36.0 56.0 

Education 

<12th Grade 73 24.2 28.7 4.0 16.0 48.0 64.0 

HS/GED 142 21.5 28.0 4.0 12.0 48.0 72.0 

Some college 126 22.7 29.0 5.3 16.0 45.0 84.0 

>4 years college 94 25.0 42.1 4.0 12.0 53.2 96.0 

Annual income 

<$20,000 101 21.9 27.8 4.0 8.0 48.0 72.0 

$20,000 to $45,000 119 21.7 32.9 4.0 8.0 40.0 56.0 

>$45,000 180 25.3 35.3 5.3 8.0 56.0 108.0 

Season 

Winter 70 19.4 28.2 4.0 8.0 48.0 80.0 

Spring 76 22.1 37.6 4.0 8.0 40.0 144.0 

Summer 189 23.9 30.6 7.9 16.0 48.0 72.0 

Fall 130 24.4 32.1 5.4 16.0 64.0 96.0 a	 Recent consumers are defined in the study as anglers who report consuming fish caught from San 

Francisco Bay in the 4 weeks prior to the date they were interviewed. Recent consumers are a subset 

of the overall consumer group. 

N = Sample size.
 

SD = Standard deviation.
 

HS/GED= High school/general education development.
 

Source:	 SFEI (2000).
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

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Table 10-66. Mean + SD Consumption Rates for Individuals Who Fish or Crab in the Newark Bay Area 

People that People that People that both crab and fish 

crab fish Crab values Fish values 

Sample size 110 111 33 33 

Number of times per month consuming 3.39 + 0.42 4.06 + 0.76 2.96 + 0.45 3.56 + 0.66 

Serving size 

Number of crabs 6.15 + 0.85 - 7.27 + 0.91 -

Fish or crabs (grams) (crabs assumed to weigh 439 + 61.2 331 + 42.1 509 + 63.8 428 + 57.6 

70 grams each) 

Monthly consumption (g/month) 1,980 + 561 1,410 + 266 1,620 + 330 1,630 + 358 

Number of months per year fishing and/or 3.31 + 0.13 4.92 + 0.33 3.5 + 0.37 7.24 + 0.74 

crabbing 

Yearly consumption (g/year) 5,760 + 1,360 8,120 + 2,040 6,230 + 1,790 13,600 + 3,480 

Average daily consumption (g/day)a 15.8 + 3.7 22.2 + 5.6 17.1 + 4.9 37.3 + 9.5 a Estimated by U.S. EPA by dividing yearly consumption rate by 365 days/year. 

SD = Standard deviation. 

Note: Sample size is slightly different from that reported in the text of Burger (2002a). 

Source: Burger (2002a). 

 

 

 

 

 

 

 

 

 

 

 

Table 10-67. Consumption Rates (g/day) for Marine Recreational Anglers in
 

King County, WA
 

Location 

Sample 

Size Mean SD SE 

Percentiles 

50th 90th 95th 

Marine Fish Consumption 

Duwamish Rivera 50 8 13 2 2 23 42 

Elliott Bay 377 63 91 5 31 145 221 

North King County 67 32 40 5 17 85 102 

All Locations 494 53 83 4 21 121 181 

Shellfish Consumption 

Duwamish Rivera 16 20 33 8 4 77 123 

Elliott Bay 49 28 33 5 14 74 119 

North King County 31 22 33 6 12 62 132 

All Locations 96 25 33 3 11 60 119 a The Duwamish River is tidally influenced by Elliott Bay, and anglers caught marine 

species; therefore, data for these locations were considered to represent marine locations. 

SD = Standard deviation. 

SE = Standard error. 

Source: Mayfield et al. (2007). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-68. Percentile and Mean Intake Rates for Wisconsin Sport Anglers (all respondents) 

Percentile Annual Number of Sport-Caught Meals Intake Rate of Sport-Caught Meals (g/day) 

25th 

50th 

75th 

90th 

95th 

98th 

100th 

Mean 

4 

10 

25 

50 

60 

100 

365 

18 

2.6 

6.2 

15.5 

31.3 

37.2 

62.1 

227 

11.2 

Source: Raw data on sport-caught meals from Fiore et al. (1989). U.S. EPA calculated distributions of intake rates 

using a value of 227 grams per fish meal. 

Table 10-69. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households With 

Recreational Fish Consumption 

Group 

All Fish 

meals/week 

Recreational 

Fish 

meals/week N 

Total 

Fish 

g/day 

Recreational 

Fish g/day 

Total Fish 

g/kg-day 

Recreational 

Fish g/kg-day 

All household members 0.686 0.332 2,196 21.9 11.0 0.356 0.178 

Respondents (i.e., licensed 

anglers) 

0.873 0.398 748 29.4 14.0 0.364 0.168 

Age groups (years) 

1 to 5 0.463 0.223 121 11.4 5.63 0.737 0.369 

6 to 10 0.49 0.278 151 13.6 7.94 0.481 0.276 

11 to 20 0.407 0.229 349 12.3 7.27 0.219 0.123 

21 to 40 0.651 0.291 793 22 10.2 0.306 0.139 

41 to 60 0.923 0.42 547 29.3 14.2 0.387 0.186 

61 to 70 0.856 0.431 160 28.2 14.5 0.377 0.193 

71 to 80 1.0 0.622 45 32.3 20.1 0.441 0.271 

80+ 0.8 0.6 10 26.5 20 0.437 0.345 

N = Sample size. 

Source: U.S. EPA analysis using data from West et al. (1989). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-70. Comparison of 7-Day Recall and Estimated Seasonal Frequency for Fish Consumption 

Usual Fish Consumption 

Frequency Category 

Mean Fish Meals/Week 

7-day Recall Data 

Usual Frequency Value Selected 

for Data Analysis (times/week) 

Almost daily 

2 to 4 times a week 

Once a week 

2 to 3 times a month 

Once a month 

Less often 

no data 

1.96 

1.19 

0.840 (3.6 times/month) 

0.459 (1.9 times/month) 

0.306 (1.3 times/month) 

4 (if needed) 

2 

1.2 

0.7 (3 times/month) 

0.4 (1.7 times/month) 

0.2 (0.9 times/month) 

Source: U.S. EPA analysis using data from West et al. (1989). 

Table 10-71. Distribution of Usual Fish Intake Among Survey Main Respondents Who Fished and Consumed 

Recreationally Caught Fish 

All Fish 

Meals/Week 

Recreational Fish 

Meals/Week 

All Fish Intake 

g/day 

Recreational 

Fish Intake 

g/day 

All Fish Intake 

g/kg-day 

Recreational 

Fish Intake 

g/kg-day 

N 

Mean 

10% 

25% 

50% 

75% 

90% 

95% 

738 

0.859 

0.300 

0.475 

0.750 

1.200 

1.400 

1.800 

738 

0.447 

0.040 

0.125 

0.338 

0.672 

1.050 

1.200 

738 

27.74 

9.69 

15.34 

24.21 

38.74 

45.20 

58.11 

738 

14.42 

1.29 

4.04 

10.90 

21.71 

33.90 

38.74 

726 

0.353 

0.119 

0.187 

0.315 

0.478 

0.634 

0.747 

726 

0.1806 

0.0159 

0.0504 

0.1357 

0.2676 

0.4146 

0.4920 

N = Sample size. 

Source: U.S. EPA analysis using data from West et al. (1989). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-72. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the 1989–1990 Ice 

Fishing or 1990 Open-Water Seasonsa 

Intake Rates (g/day) 

Percentile Rankings 

All Watersb Rivers and Streams 

All Anglersc 

(N = 1,369) 

Consuming Anglersd 

(N = 1,053) 

River Anglerse 

(N = 741) 

Consuming Anglersd 

(N = 464) 

50th (median) 

66th 

75th 

90th 

95th 

Arithmetic Meanf 

1.1 

2.6 

4.2 

11.0 

21.0 

5.0 [79] 

2.0 

4.0 

5.8 

13.0 

26.0 

6.4 [77] 

0.19 

0.71 

1.3 

3.7 

6.2 

1.9 [82] 

0.99 

1.8 

2.5 

6.1 

12.0 

3.7 [81] a Estimates are based on rank except for those of arithmetic mean. b All waters based on fish obtained from all lakes, ponds, streams, and rivers in Maine, from other household 

sources, and from other non-household sources. c Licensed anglers who fished during the seasons studied and did or did not consume freshwater fish, and 

licensed anglers who did not fish but ate freshwater fish caught in Maine during those seasons. d Licensed anglers who consumed freshwater fish caught in Maine during the seasons studied. e Those of the "all anglers" who fished on rivers or streams (consumers and non-consumers). f Values in brackets [ ] are percentiles at the mean consumption rates. 

Source: ChemRisk (1992); Ebert et al. (1993). 

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c 

Table 10-73. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day)a 

Consuming Anglersb 

French Native Other White 

Canadian Irish Italian American Non-Hispanic Scandinavian 

Heritage Heritage Heritage Heritage Heritage Heritage 

N of Cases 201 138 27 96 533 37 

Median (50th percentile)c,d 

66th percentilec,d 

75th percentilec,d 

2.3 

4.1 

6.2 

2.4 

4.4 

6.0 

1.8 

2.6 

5.0 

2.3 

4.7 

6.2 

1.9 

3.8 

5.7 

1.3 

2.6 

4.9 

Arithmetic meanc 7.4 5.2 4.5 10 6.0 5.3 

Percentile at the meand 80 70 74 83 76 78 

90th percentilec,d 

95th percentilec,d 

Percentile at 6.5 g/dayd,e 

15 

27 

77 

12 

20 

75 

12 

21 

81 

16 

51 

77 

13 

24 

77 

9.4 

25 

84 a	 "All Waters" based on fish obtained from all lakes, ponds, streams, and rivers in Maine, from other 

household sources, and from other non-household sources. b	 "Consuming Anglers" refers to only those anglers who consumed freshwater fish obtained from Maine 

sources during the 1989–1990 ice fishing or 1990 open water fishing seasons. 

The average consumption per day by freshwater fish consumers in the household. d Calculated by rank without any assumption of statistical distribution. e Fish consumption rate recommended by U.S. EPA (1984) for use in establishing ambient water quality 

standards. 

Source:	 ChemRisk (1992). 

 

Table 10-74. Total Consumption of Freshwater Fish Caught by All Survey Respondents During the 1990 

Season 

Ice Fishing Lakes and Ponds Rivers and Streams 

Quantity 

Consumed 

Grams 

(×103) Quantity Grams (×103) Quantity Grams (×103) 

Species (#) Consumed Consumed (#) Consumed Consumed (#) Consumed 

Landlocked salmon 832 290 928 340 305 120 

Atlantic salmon 3 1.1 33 9.9 17 11 

Togue (lake trout) 483 200 459 160 33 2.7 

Brook trout 1,309 100 3,294 210 10,185 420 

Brown trout 275 54 375 56 338 23 

Yellow perch 235 9.1 1,649 52 188 7.4 

White perch 2,544 160 6,540 380 3,013 180 

Bass (smallmouth and largemouth) 474 120 73 5.9 787 130 

Pickerel 1,091 180 553 91 303 45 

Lake whitefish 111 20 558 13 55 2.7 

Hornpout (catfish and bullheads) 47 8.2 1,291 100 180 7.8 

Bottom fish (suckers, carp, and sturgeon) 50 81 62 22 100 6.7 

Chub 0 0 252 35 219 130 

Smelt 7,808 150 428 4.9 4,269 37 

Other 201 210 90 110 54 45 

TOTALS 15,463 1,583.4 16,587 1,590 20,046 1,168 

Source: ChemRisk (1992). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-75. Socio-Demographic Characteristics of Respondents 

Category Subcategory Percent of Totala 

Geographic Distribution Upper Hudson 

Mid Hudson 

Lower Hudson 

Age Distribution (years) <14 

15 to 29 

30 to 44 

45 to 59 

>60 

Annual Household Income <$10,000 

$10,000 to 29,999 

$30,000 to 49,999 

$50,000 to 69,999 

$70,000 to 89,999 

>$90,000 

Ethnic Background Caucasian American 

African American 

Hispanic American 

Asian American 

Native American 

18% 

35% 

48% 

3% 

26% 

35% 

23% 

12% 

16% 

41% 

29% 

10% 

2% 

3% 

67% 

21% 

10% 

1% 

1% a A total of 336 shore-based anglers were interviewed. 

Source: Hudson River Sloop Clearwater, Inc. (1993). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-76. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport Anglers Fish 

Consumption Study, 1991–1992 

N Mean (g/day) 95% CI 

Incomea 

<$15,000 

$15,000 to $24,999 

$25,000 to $39,999 

>$40,000 

290 

369 

662 

871 

21.0 

20.6 

17.5 

14.7 

16.3–25.8 

15.5–25.7 

15.0–20.1 

12.8–16.7 

Education 

Some High School 

High School Degree 

Some College-College Degree 

Post-Graduate 

299 

1,074 

825 

231 

16.5 

17.0 

17.6 

14.5 

12.9–20.1 

14.9–19.1 

14.9–20.2 

10.5–18.6 

Residence Sizeb 

Large City/Suburb (>100,000) 

Small City (20,000 to 100,000) 

Town (2,000 to 20,000) 

Small Town (100 to 2,000) 

Rural, Non-Farm 

Farm 

487 

464 

475 

272 

598 

140 

14.6 

12.9 

19.4 

22.8 

17.7 

15.1 

11.8–17.3 

10.7–15.0 

15.5–23.3 

16.8–28.8 

15.1–20.3 

10.3–20.0 

Age (years) 

16 to 29 

30 to 39 

40 to 49 

50 to 59 

60+ 

266 

583 

556 

419 

596 

18.9 

16.6 

16.5 

16.5 

16.2 

13.9–23.9 

13.5–19.7 

13.4–19.6 

13.6–19.4 

13.8–18.6 

Sexa 

Male 

Female 

299 

1,074 

17.5 

13.7 

15.8–19.1 

11.2–16.3 

Race/Ethnicityb 

Minority 

White 

160 

2,289 

23.2 

16.3 

13.4–33.1 

14.9–17.6 a p < 0.01, F test. b p < 0.05, F test. 

N = Sample size. 

CI = Confidence interval. 

Source: West et al. (1993). 

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Table 10-77. Mean Per Capita Freshwater Fish Intake of Alabama Anglers 

Mean Consumption (g/day) 

Harvest Methoda 4-Ounce Serving Methodb 

N Site meals All meals N Site Meals All Meals 

All respondents 563 32.6 43.1 1,303 30.3 45.8 

All respondents; all - - - - - 44.8 

meals; 4-ounce 

serving method 

Age (years) 16 

20 to 30 - - - - - 39 

31 to 50 - - - - - 76 

51 and over - - - - -

Race/Ethnicity 

African American 113 35.4 49.6 232 33.4 50.7 

Native American 0 0 0 2 22.7 22.7 

Asian 2 74.7 74.7 3 44.1 44.1 

Hispanic 2 0 0 2 0 0 

Caucasian 413 33.9 48.6 925 29.4 49.7 

Seasons 

Fall 130 29.7 43.4 303 32.0 49.4 

Winter 56 26.2 34.2 177 30.8 43.9 

Spring 185 21.5 29.3 414 20.5 33.6c 

Summer 192 46.7 57.0 417 36.4 53.0c 

a The Harvest Method used the actual harvest of fish and dressing method reported to calculate 

consumption rates. b The 4-ounce Serving Method estimated consumption based on a typical 4-ounce serving size. c Statistical difference at p < 0.05. 

N = Number of respondents. 

Source: Alabama Department of Environmental Management (ADEM) (1994). 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-78. Distribution of Fish Intake Rates (from all sources and from sport-caught sources) for 1992 Lake 

Ontario Anglers 

Percentile of Lake Ontario Anglers Fish From All Sources (g/day) Sport-Caught Fish (g/day) 

25% 

50% 

75% 

90% 

95% 

99% 

8.8 

14.1 

23.2 

34.2 

42.3 

56.6 

0.6 

2.2 

6.6 

13.2 

17.9 

39.8 

Source. Connelly et al. (1996). 

Exposure Factors Handbook Page
 

September 2011 10-155 
 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-79. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by Socio-Demographic 

Characteristics 

Mean Consumption 

Demographic Group Fish From All Sources Sport-Caught Fish 

Overall 17.9 4.9 

Residence 

Rural 17.6 5.1 

Small City 20.8 6.3 

City (25 to 100,000) 19.8 5.8 

City (>100,000) 13.1 2.2 

Income 

<$20,000 20.5 4.9 

$21,000 to 34,000 17.5 4.7 

$35,000 to 50,000 16.5 4.8 

>$50,000 20.7 6.1 

Age (years) 

<30 13.0 4.1 

30 to 39 16.6 4.3 

40 to 49 18.6 5.1 

50+ 21.9 6.4 

Education 

<High School 17.3 7.1 

High School Graduate 17.8 4.7 

Some College 18.8 5.5 

College Graduate 17.4 4.2 

Some Post-Grad. 20.5 5.9 

Note	 Scheffe’s test showed statistically significant differences between residence types (for all sources and sport 

caught) and age groups (all sources). 

Source:	 Connelly et al. (1996). 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-80. Seafood Consumption Rates of Nine Connecticut Population Groups 

(cooked, edible meat, g/day) 

N Mean SD Minimum Maximum 

General population 437 27.7 42.7 0 

Sport-fishing households 502 51.1 66.1 0 

Commercial fishing households 178 47.4 58.5 0 

Minority 

South East Asians 

Non-Asians 

861 

329 

532 

50.3 

59.2 

44.8 

57.5 

49.3 

61.5 

0 

0.13 

0 

Limited income households 937 43.1 60.4 0 

Women aged 15 to 45 years 497 46.5 57.4 0 

Children ≤15 years old 559 18.3 29.8 0 

494.8 

586.0 

504.3 

430.0 

245.6 

430.0 

571.9 

494.8 

324.8 

N = Sample size. 

SD = Standard deviation. 

Source: Balcom et al. (1999). 

Page Exposure Factors Handbook 

10-156 September 2011 
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-81. Fishing Patterns and Consumption Rates of People Fishing Along the Savannah River (Mean ± SE) 

N 

Age 

(years) 

Years 

Fished 

Years 

Fished 

Savannah 

River 

Distance 

Traveled 

(km) 

How 

Often Eat 

Fish/Month 

Serving Size 

(grams) 

Fish/Month 

(kg) 

Fish/Year 

(kg) 

Ethnicity 

White 

Black 

180 

72 

42 ± 1 

47 ± 2 

31 ± 1 

34 ± 2 

24 ± 1 

24 ± 2 

42 ± 9 

15 ± 1 

2.88 ± 0.30 

5.37 ± 0.57 

370 ± 6.60 

387 ± 10.2 

1.17 ± 0.14 

2.13 ± 0.24 

14.0 ± 1.70 

25.6 ± 2.92 

Income 

≤$20,000 

>$20,000 

138 

99 

43 ± 1 

42 ± 1 

32± 2 

30± 1 

24 ± 2 

22 ± 2 

31 ± 4 

32 ± 9 

3.39 ± 0.52 

3.97 ± 0.36 

379 ± 7.27 

375 ± 8.10 

1.44 ± 0.24 

1.58 ± 0.16 

17.3 ± 2.82 

18.9 ± 1.88 

Education 

Not high school graduate 

High school graduate 

College or technical 

training 

45 

154 

59 

49 ± 2 

43 ± 1 

41 ± 2 

36 ± 2 

31 ± 1 

28 ± 2 

23 ± 3 

26 ± 1 

17 ± 2 

24 ± 4 

36 ± 9 

54 ± 24 

5.93 ± 0.85 

3.02 ± 0.27 

3.36 ± 0.67 

383 ± 13.3 

366 ± 6.81 

398 ± 11.8 

2.61 ± 0.44 

1.15 ± 0.11 

1.52 ± 0.31 

31.3 ± 5.26 

13.8 ± 1.36 

18.2 ± 3.66 

Overall mean (all respondents) 48.7 g/day 

N = Sample size. 

SE = Standard error. 

Source: Burger et al. (1999). 

Exposure Factors Handbook Page
 

September 2011 10-157 
 

 

Table 10-82. Fish Consumption Rates for Indiana Anglers—Mail Survey (g/day) 

Percentile 

N Mean 50th 80th 90th 95th 

Active Consumers 1,045 19.8 9.5 28.4 37.8 60.5 

Potential and Active Consumers 1,261 16.4 7.6 23.6 37.8 60.5 

N = Sample size. 

Source: Williams et al. (1999). 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-83. Fish Consumption Rates for Indiana Anglers—On-Site Survey (g/day) 

Percentile 

50th 80th 90th 95th N Mean 

Active Consumers 

White 177 20.0 7.6 23.6 37.8 113.4 

Minority 143 27.2 7.6 30.2 90.7 136.1 

Income 

<$25,000 101 18.9 7.5 18.9 37.8 136.1 

$25,000 to $34,999 62 18.8 7.6 23.6 60.5 90.7 

$35,000 to $49,999 55 15.2 5.7 23.6 23.6 45.4 

>$50,000 60 48.9 11.3 113.4 181.4 181.4 

Potential and Active Consumers 

White 361 6.8 0 5.7 15.1 37.8 

Minority 217 15.3 3.8 13.2 37.8 90.7 

Income 

<$25,000 180 10.2 3.8 9.5 23.6 37.8 

$25,000 to $34,999 117 7.4 0 7.6 15.1 37.8 

$35,000 to $49,999 91 6.8 0 5.7 22.7 23.6 

>$50,000 126 13.6 0 7.6 37.8 113.4 

N = Sample size. 

Source: Williams et al. (2000). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-158 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-84. Consumption of Sport-Caught and Purchased Fish by Minnesota and North 

Dakota Residents (g/day) 

Percentile 

N 50th 75th 90th 95th 99th 

Minnesota 

Sport-caught fish only 

Age in years (sex) 

0 to 14 582 1.2 4.2 9.0 13.7 26.7 

14 and over (males) 996 4.5 10.6 23.7 39.8 113.9 

15 to 44 (females) 505 2.1 5.8 14.0 24.9 75.9 

44 and over (females) 460 3.6 8.2 20.8 37.2 101.3 

General population 2,312 2.8 7.9 17.3 28.9 78.0 

Bois Forte Tribe 232 2.8 6.6 12.0 19.6 120.6 

With fishing license 2,020 3.9 9.2 18.9 30.4 94.5 

Without fishing license 490 0.0 2.0 4.5 7.0 51.1 

Purchased Fish Only 

Age in years (sex) 

0 to 14 582 3.6 9.3 18.0 31.3 61.2 

14 and over (males) 996 7.4 15.4 30.3 47.5 91.6 

15 to 44 (females) 505 6.1 14.0 29.2 50.3 103.7 

44 and over (females) 460 7.1 14.6 25.3 42.5 89.4 

General population 2,312 6.6 14.4 27.7 43.2 91.3 

Bois Forte Tribe 232 3.4 9.0 14.4 24.1 71.9 

With fishing license 2,020 6.4 14.0 25.9 39.7 88.7 

Without fishing license 490 5.6 12.7 29.6 55.4 98.7 

Total 

Age in years (sex) 

0 to 14 582 6.9 14.0 25.6 38.1 78.2 

14 and over (males) 996 15.1 27.2 50.3 72.3 155.6 

15 to 44 (females) 505 10.1 19.1 39.5 69.2 147.7 

44 and over (females) 460 13.8 22.8 45.2 64.1 139.3 

General population 2,312 12.3 22.6 42.8 64.5 128.7 

Bois Forte Tribe 232 9.3 14.5 26.0 38.4 123.0 

With fishing license 2,020 13.2 23.1 42.3 64.5 133.5 

Without fishing license 490 7.5 15.2 30.4 58.7 110.0 

North Dakota 

Sport-Caught Fish Only 

Age in years (sex) 

0 to 14 343 1.7 6.0 13.3 21.6 44.3 

14 and over (males) 579 2.3 6.8 15.1 24.6 79.8 

15 to 44 (females) 311 4.3 10.7 23.8 30.1 89.8 

44 and over (females) 278 4.2 11.5 21.8 32.5 87.5 

General population 1,406 3.0 9.2 16.4 27.4 80.9 

Spirit Lake Nation Tribes 105 0.0 2.9 20.3 36.3 97.6 

With fishing license 1,101 4.5 11.2 21.2 30.8 87.2 

Without fishing license 391 0.0 1.5 4.8 7.9 23.1 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-159 
 

 

 

 

 

 

 

 

 

 

 

Table 10-84. Consumption of Sport-Caught and Purchased Fish by Minnesota and North 

Dakota Residents (g/day) (continued) 

Percentile 

N 50th 75th 90th 95th 99th 

Purchased Fish Only 

Age in years (sex) 

0 to 14 343 4.7 14.3 23.1 32.9 90.7 

14 and over (males) 579 7.4 15.4 30.3 47.5 91.6 

15 to 44 (females) 311 7.1 16.1 33.5 50.6 90.9 

44 and over (females) 278 6.1 15.4 30.3 47.0 90.7 

General population 1,406 6.4 15.4 29.1 47.8 95.6 

Spirit Lake Nation Tribes 105 1.2 16.5 30.0 40.7 143.5 

With fishing license 1,101 6.8 15.9 29.5 47.0 95.6 

Without fishing license 391 5.7 15.1 30.2 52.8 112.2 

Total 

Age in years (sex) 

0 to 14 343 9.2 20.4 35.7 57.1 97.4 

14 and over (males) 579 7.4 15.4 30.3 47.5 91.6 

15 to 44 (females) 311 14.1 27.3 49.8 80.5 137.5 

44 and over (females) 278 13.5 25.4 49.3 78.8 144.5 

General population 1,406 12.6 24.1 46.7 71.4 126.3 

Spirit Lake Nation Tribes 105 1.4 21.2 50.7 80.8 179.8 

With fishing license 1,101 14.0 25.3 49.2 76.2 131.4 

Without fishing license 391 7.2 15.9 33.5 54.1 116.1 

N = Sample size. 

Source: Benson et al. (2001). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-160 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-86. Daily Consumption of Wild-Caught Fish, Consumers Only (g/kg-day, as-consumed) 

g/person/day 

Population N Consumers (%) Mean Range Median 75th 90th 95th 99th 

Ethnicity 

Black 39 79 171.0 1.88–590.0 137.0 240.0 446.0 557.0 590.0 

White 415 78 38.8 0.35–902.0 15.3 37.6 93.0 129.0 286.0 

All 458 78 50.2 0.35–902.0 17.6 47.8 123.0 216.0 538.0 

Sex 

Female 149 72 39.1 0.35–412.0 11.6 32.8 123.0 172.0 373.0 

Male 308 80 55.2 0.63–902.0 21.3 56.4 127.0 235.0 557.0 

All 458 73 50.2 0.35–902.0 17.6 47.8 123.0 216.0 538.0 

Age (years) 

<32 145 77 32.6 0.63–412.0 14.2 37.6 66.5 123.0 216.0 

33 to 45 159 77 71.3 7.52–902.0 18.8 67.6 177.0 354.0 590.0 

>45 150 78 44.0 0.35–538.0 20.0 44.4 100.0 164.0 286.0 

Income 

$0 to <20K 98 82 104.0 31.9–590.0 31.9 151.0 285.0 429.0 590.0 

$20 to 30K 95 82 32.7 0.35–460.0 15.0 37.2 93.0 120.0 460.0 

>$30K 172 76 40.9 0.47–902.0 19.4 45.8 87.9 127.0 216.0 

N = Sample size. 

Source: Burger (2002b). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-85. Fishing Patterns and Consumption Rates of Anglers Along the Clinch River Arm of Watts Bar 

Reservoir (Mean ± SE) 

N 

Age 

(years) 

Years 

Fished 

Years 

Fished, 

Clinch 

River 

Distance 

Traveled 

(km) 

How 

Often Eat 

fish/month 

Serving 

Size 

(grams) 

Fish/Month 

(kg) 

Fish/Year 

(kg) 

All anglers 

Anglers who catch and eat fish 

from study area 

202 

77 

39.2± 1 

41.8 ± 2 

31 ± 1 

34 ± 2 

11 ± 1 

12 ± 2 

61 ± 5 

57 ± 6 

1.28 ± 0.12 

2.06 ± 0.22 

283 ± 20.9 

486 ± 32.7 

0.62 ± 0.08 

1.14 ± 0.19 

7.40 ± 1.01 

13.7 ± 2.17 

Ethnicity 

White 

Black 

71 

6 

42 ± 2 

43 ± 6 

34 ± 2 

33 ± 7 

12 ± 2 

20 ± 5 

59 ± 6 

44 ± 20 

2.14 ± 0.23 

0.94 ± 0.78 

501 ± 33.6 

307 ± 116 

1.21 ± 0.20 

0.34 ± 0.68 

14.5 ± 2.36 

4.14 ± 8.11 

Income 

≤$20,000 

$20,000 to $29,000 

$30,000 to $39,000 

>$40,000 

22 

19 

18 

15 

42 ± 3 

35 ± 3 

43 ± 3 

47 ± 4 

33 ± 4 

29 ± 4 

37 ± 4 

38 ± 4 

16 ± 3 

8.8 ± 3 

8.9 ± 3 

13.9 ± 3 

49 ± 10 

37 ± 12 

69 ± 11 

81 ± 12 

1.37 ±0.40 

1.84 ± 0.44 

2.13 ± 0.45 

3.01 ± 0.49 

392 ± 41.7 

548 ± 44.9 

482 ± 46.1 

452 ± 50.5 

0.52 ± 0.29 

1.19 ± 0.32 

1.11 ± 0.33 

1.56 ± 0.36 

6.29 ± 3.58 

14.3 ± 3.85 

13.3 ± 3.95 

18.8 ± 4.33 

Education 

Not high school graduate 

High school graduate 

Some college, associates, trade 

school 

College, at least a bachelors 

degree 

18 

28 

20 

10 

44 ± 4 

40 ± 3 

40 ± 3 

42 ± 5 

35 ± 4 

32 ± 3 

35 ± 4 

36 ± 5 

13 ± 3 

14 ± 3 

9.0 ± 3 

10 ± 4 

57 ± 12 

55 ± 10 

61 ± 11 

59 ± 16 

1.67 ± 0.46 

2.12 ± 0.37 

2.05 ± 0.44 

2.33 ± 0.62 

439 ± 67.7 

551 ± 54.2 

486 ± 64.2 

414 ± 90.8 

0.83 ± 0.39 

1.45 ± 0.32 

1.11 ± 0.38 

0.92 ± 0.53 

9.99 ± 4.77 

17.4 ± 3.82 

13.4 ± 4.52 

11.0 ± 6.39 

N = Sample size. 

Source: Rouse Campbell et al. (2002). 

Exposure Factors Handbook Page
 

September 2011 10-161 
 

 

 

 

 

Table 10-87. Consumption Rates (g/day) for Freshwater Recreational Anglers in King County, WA 

Location 

Sample 

Size Mean SD SE 50th 

Percentiles 

90th 95th 

Freshwater Fish Consumption 

King County Lakes (all respondents) 128 10 24 2 0 23 42 

King County Lakes (children of 

respondents) 81 7 20 2 0 17 29 

SD = Standard deviation. 

SE = Standard error. 

Source: Mayfield et al. (2007). 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-88. Number of Grams per Day of Fish Consumed by All Adult Respondents (consumers and 

non-consumers combined)—Throughout the Year 

Number of g/day Cumulative Percent Number of g/Day Cumulative Percent 

0.00 

1.6 

3.2 

4.0 

4.9 

6.5 

7.3 

8.1 

9.7 

12.2 

13.0 

16.2 

19.4 

20.2 

24.3 

29.2 

32.4 

38.9 

40.5 

48.6 

8.9% 

9.0% 

10.4% 

10.8% 

10.9% 

12.8% 

12.9% 

13.7% 

14.4% 

14.9% 

16.3% 

22.8% 

24.0% 

24.1% 

27.9% 

28.1% 

52.5% 

52.9% 

56.5% 

67.6% 

64.8 

72.9 

77.0 

81.0 

97.2 

130 

146 

162 

170 

194 

243 

259 

292 

324 

340 

389 

486 

648 

778 

972 

80.6% 

81.2% 

81.4% 

83.3% 

89.3% 

92.2% 

93.7% 

94.4% 

94.8% 

97.2% 

97.3% 

97.4% 

97.6% 

98.3% 

98.7% 

99.0% 

99.6% 

99.7% 

99.9% 

100% 

N = 500; N = sample size. 

Weighted Mean = 58.7 g/day. 

Weighted SE = 3.64; SE = standard error. 

90th Percentile 97.2 g/day < (90th) < 130 g/day. 

95th Percentile = 170 g/day. 

99th Percentile = 389 g/day. 

Source: CRITFC (1994). 

Page Exposure Factors Handbook 

10-162 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-89. Fish Intake Throughout the Year by Sex, Age, and Location by All Adult Respondents 

N Weighted Mean (g/day) Weighted SE 

Sex 

Female 

Male 

Total 

Age (years) 

18 to 39 

40 to 59 

60 and Older 

Total 

Location 

On Reservation 

Off Reservation 

Total 

278 

222 

500 

287 

155 

58 

500 

440 

60 

500 

55.8 

62.6 

58.7 

57.6 

55.8 

74.4 

58.7 

60.2 

47.9 

58.7 

4.78 

5.60 

3.64 

4.87 

4.88 

15.3 

3.64 

3.98 

8.25 

3.64 

Source: CRITFC (1994). 

Table 10-90. Fish Consumption Rates Among Native American Children (age 5 years and under)a 

g/day Unweighted Cumulative Percent 

0.0 

0.4 

0.8 

1.6 

2.4 

3.2 

4.1 

4.9 

6.5 

8.1 

9.7 

12.2 

13.0 

16.2 

19.4 

20.3 

24.3 

32.4 

48.6 

64.8 

72.9 

81.0 

97.2 

162.0 

21.1 

21.6 

22.2 

24.7 

25.3 

28.4 

32.0 

33.5 

35.6 

47.4 

48.5 

51.0 

51.5 

72.7 

73.2 

74.2 

76.3 

87.1 

91.2 

94.3 

96.4 

97.4 

98.5 

100 a Sample size = 194; unweighted mean = 19.6 g/day; unweighted standard error = 1.94. 

Note: Data are compiled from the Umatilla, Nez Perce, Yakama, and Warm Springs tribes of the Columbia River 

Basin. 

Source: CRITFC (1994). 

Exposure Factors Handbook Page
 

September 2011 10-163 
 

 

Table 10-91. Number of Fish Meals Eaten per Month and Fish Intake Among Native American Children Who 

Consume Particular Species 

Fish Meals/Month Intake (g/day) Species N Unweighted Mean Unweighted SE Unweighted Mean Unweighted SE 

Salmon 164 2.3 0.16 19 1.5 

Lamprey 37 0.89 0.27 8.1 2.8 

Trout 89 0.96 0.12 8.8 1.4 

Smelt 39 0.40 0.09 3.8 0.99 

Whitefish 21 3.5 2.83 21 16 

Sturgeon 21 0.43 0.12 4.0 1.3 

Walleye 5 0.22 0.20 2.0 1.5 

Squawfish 2 0.00 - 0.0 -

Sucker 4 0.35 0.22 2.6 1.7 

Shad 3 0.10 0.06 1.1 0.57 

- Not applicable. 

SE = Standard error. 

Source: CRITFC (1994). 

 

 

 

 

 

 

 

 

 

 

c 

Table 10-92. Socio-Demographic Factors and Recent Fish Consumption 

Peak Consumptiona Recent Consumptionb 

Average ≥3 meals/weekd 

Meals/Weekc (%) Walleye N. Pike Muskellunge Bass 

All participants 

(N = 323) 1.7 20 4.2 0.3 0.3 0.5 

Sex 

Male (N = 148) 1.9 26 5.1 0.5a 0.5 0.7a 

Female (N = 175) 1.5 15 3.4 0.2 0.1 0.3 

Age (years) 

<35 (N = 150) 1.8 23 5.3a 0.3 0.2 0.7 

≥35 (N = 173) 1.6 17 3.2 0.4 0.3 0.3 

High School Graduate 

No (N = 105) 1.6 18 3.6 0.2 0.4 0.7 

Yes (N = 218) 1.7 21 4.4 0.4 0.2 0.4 

Unemployed 

Yes (N = 78) 1.9 27 4.8 0.6 0.6 1.1 

No (N = 245) 1.6 18 4.0 0.3 0.2 0.3 a Highest number of fish meals consumed/week. b Number of meals of each species in the previous 2 months. 

Average peak fish consumption. d Percentage of population reporting peak fish consumption of ≥3 fish meals/week. 

Source: Peterson et al. (1994). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-164 September 2011 
 

 

 

 

 

 

 

 

 

 

Table 10-93. Number of Local Fish Meals Consumed per Year by Time Period for All Respondents 

Time Period 

Number of During Pregnancy ≤1 Year Before Pregnancya >1 Year Before Pregnancyb 

Local Fish Meals Mohawk Control Mohawk Control Mohawk Control 

Consumed Per Year N % N % N % N % N % N % 

None 63 64.9 109 70.8 42 43.3 99 64.3 20 20.6 93 60.4 

1 to 9 24 24.7 24 15.6 40 41.2 31 20.1 42 43.3 35 22.7 

10 to 19 5 5.2 7 4.5 4 4.1 6 3.9 6 6.2 8 5.2 

20 to 29 1 1.0 5 3.3 3 3.1 3 1.9 9 9.3 5 3.3 

30 to 39 0 0.0 2 1.3 0 0.0 3 1.9 1 1.0 1 0.6 

40 to 49 0 0.0 1 0.6 1 1.0 1 0.6 1 1.0 1 0.6 

50+ 4 4.1 6 3.9 7 7.2 11 7.1 18 18.6 11 7.1 

Total 97 100.0 154 100.0 97 100.0 154 100.0 97 100.0 154 100.0 a p < 0.05 for Mohawk vs. Control. b p < 0.001 for Mohawk vs. Control. 

N = Number of respondents. 

Source: Fitzgerald et al. (1995). 

 

 

Table 10-94. Mean Number of Local Fish Meals Consumed per Year by Time Period for All Respondents and 

Consumers Only
 

All Respondents Consumers Only 

(N = 97 Mohawks and 154 Controls) (N = 82 Mohawks and 72 Controls) 

During ≤1 Year Before >1 Year Before During ≤1 Year Before >1 Year Before 

Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy 

Mohawk 3.9 (1.2) 9.2 (2.3) 23.4 (4.3)a 4.6 (1.3) 10.9 (2.7) 27.6 (4.9) 

Control 7.3 (2.1) 10.7 (2.6) 10.9 (2.7) 15.5 (4.2)a 23.0 (5.1)b 23.0 (5.5) a p < 0.001 for Mohawk vs. Controls. b p < 0.05 for Mohawk vs. Controls. 

( ) = Standard error. 

Test for linear trend: 

p < 0.001 for Mohawk (All participants and consumers only); 

p = 0.07 for Controls (All participants and consumers only). 

Source: Fitzgerald et al. (1995). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-165 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-95. Mean Number of Local Fish Meals Consumed per Year by Time Period and Selected 

Characteristics for All Respondents (Mohawk, N = 97; Control, N = 154) 

Time Period 

During Pregnancy ≤1 Year Before Pregnancy >1 Year Before Pregnancy 

Variable Mohawk Control Mohawk Control Mohawk Control 

Age (years) 

<20 

20 to 24 

25 to 29 

30 to 34 

>34 

Education (Years) 

<12 

12 

13 to 15 

>15 

Cigarette Smoking 

Yes 

No 

Alcohol Consumption 

Yes 

No 

7.7 

1.3 

3.9 

12.0 

1.8 

6.3 

7.3 

1.7 

0.9 

3.8 

3.9 

4.2 

3.8 

0.8 

5.9 

9.9 

7.6 

11.2 

7.9 

5.4 

10.1 

6.8 

8.8 

6.4 

9.9 

6.3b 

13.5 

5.7 

15.5 

9.5 

1.8 

14.8 

8.1 

8.0 

10.7 

10.4 

8.4 

6.8 

12.1 

13.9 

14.5 

6.2 

2.9 

26.2 

12.4 

8.4 

15.4 

0.8 

13.0 

8.3 

13.8 

4.7c 

27.4 

20.4 

25.1 

12.0 

52.3 

24.7 

15.3 

29.2 

18.7 

31.6 

18.1 

18.0 

29.8 

10.4 

15.9 

5.4 

5.6 

22.1a 

8.6 

11.4 

13.3 

2.1 

10.9 

10.8 

14.8 

2.9d 

a F (4,149) = 2.66, p = 0.035 for Age Among Controls. b F (1,152) = 3.77, p = 0.054 for Alcohol Among Controls. c F (1,152) = 5.20, p = 0.024 for Alcohol Among Controls. d F (1,152) = 6.42, p = 0.012 for Alcohol Among Controls. 

Note: F (r1, r2) = F statistic with r1 and r2 degrees of freedom. 

Source: Fitzgerald et al. (1995). 

Table 10-96. Fish Consumption Rates for Mohawk Native Americans (g/day) 

Population Group Sample Size Fish Intake Rate % Consuming Mean 95th Percentile 

Adults—alla 

All fish 

Local fish 

1,092 

1,092 

28 

25 

132 

131 

90% 

90% 

Adults—consumers onlya 

All fish 

Local fish 

983 

972 

31 

29 

142 

135 

90% 

90% 

Children—allb 

Local fish -­ 10 54 -­

Children—consumers onlyb 

Local fish -­ 13 58 -­ a Value based on assumption that 1 fish meal = 227 grams (1/2 pound) [based on data from Pao et al. (1982)]. b Value for 2-year old child, based on assumption that children consume fish at the same frequency as adults 

but have a smaller meal size (93 grams). 

Source: Forti et al. (1995). 

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10-166 September 2011 
 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-97. Percentiles and Mean of Adult Tribal Member Consumption Rates (g/kg-day) 

5% 50% 90% 95% SE Mean 95% CI 

Tulalip Tribes (N = 73) 

Anadromous fish 0.006 0.190 1.429 2.114 0.068 0.426 (0.297, 0.555) 

Pelagic fish 0.000 0.004 0.156 0.234 0.008 0.036 (0.021, 0.051) 

Bottom fisha 0.000 0.008 0.111 0.186 0.007 0.033 (0.020, 0.046) 

Shellfisha 0.000 0.153 1.241 1.5296 0.059 0.362 (0.250, 0.474) 

Total finfish 0.010 0.284 1.779 2.149 0.072 0.495 (0.359, 0.631) 

Other fishb 0.000 0.000 0.113 0.264 0.008 0.031 (0.016, 0.046) 

Total fish 0.046 0.552 2.466 2.876 0.111 0.889 (0.679, 1.099) 

Squaxin Island Tribe (N = 117) 

Anadromous fish 0.016 0.308 1.639 2.182 0.069 0.590 (0.485, 0.695) 

Pelagic fish 0.000 0.003 0.106 0.248 0.009 0.043 (0.029, 0.057) 

Bottom fisha 0.000 0.026 0.176 0.345 0.010 0.063 (0.048, 0.078) 

Shellfisha 0.000 0.065 0.579 0.849 0.027 0.181 (0.140, 0.222) 

Total finfish 0.027 0.383 1.828 2.538 0.075 0.697 (0.583, 0.811) 

Other fishb 0.000 0.000 0.037 0.123 0.003 0.014 (0.009, 0.019) 

Total fish 0.045 0.524 2.348 3.016 0.088 0.891 (0.757, 1.025) 

Both Tribes Combined (weighted) 

Anadromous fish 0.010 0.239 1.433 2.085 0.042 0.508 (0.425, 0.591) 

Pelagic fish 0.000 0.004 0.112 0.226 0.005 0.040 (0.029, 0.050) 

Bottom fish** 0.000 0.015 0.118 0.118 0.005 0.048 (0.038, 0.058) 

Shellfish** 0.000 0.115 0.840 1.308 0.030 0.272 (0.212, 0.331) 

Total finfish 0.017 0.317 1.751 2.188 0.045 0.596 (0.507, 0.685) 

Other fish* 0.000 0.000 0.049 0.145 0.004 0.023 (0.015, 0.030) 

Total fish 0.047 0.531 2.312 2.936 0.064 0.890 (0.765, 1.015) a p < 0.01 comparing two tribes (Wilcoxon-Mann-Whitney test). b p < 0.05 

N = Sample size. 

SE = Standard error. 

CI = Confidence interval. 

Source: Toy et al. (1996). 

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September 2011 10-167 
 

 

 

 

Table 10-98. Median and Mean Consumption Rates by Sex (g/kg-day) within Each Tribe 

Tulalip Tribe Squaxin Island Tribe 

N Median Mean 95% CI N Median Mean 95% CI 

Shellfish 

Male 42 0.158 0.370 (0.215, 

0.525) 

65 0.100 0.202 (0.149, 

0.255) 

Female 31 0.153 0.353 (0.192, 0.514) 52 0.038 0.155 (0.093, 

0.217) 

Total finfish 

Male 42 0.414 0.559 (0.370, 0.748) 65 0.500 0.707 (0.576, 

0.838) 

Female 31 0.236 0.409 (0.218, 0.600) 52 0.272 0.684 (0.486, 

0.882) 

Total fisha 

Male 42 0.623 0.959 (0.666, 1.252) 65 0.775b 0.926 (0.771, 

1.081) 

Female 31 0.472 0.794 (0.499, 1.089) 52 0.353 0.847 (0.614, 

1.080) a Total fish includes anadromous, pelagic, bottom shellfish, finfish, and other fish. b p < 0.05 for difference in consumption rate by sex within a tribe (Wilcoxon-Mann-Whitney test). 

N = Sample size. 

CI = Confidence interval. 

Source: Toy et al. (1996). 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-99. Median Consumption Rate for Total Fish by Sex and Tribe (g/day) 

Tulalip Tribe Squaxin Island Tribe 

Male 53 66 

Female 34 25 

Source: Toy et al. (1996). 

Page Exposure Factors Handbook 

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Table 10-100. Percentiles of Adult Consumption Rates by Age (g/kg-day) 

Tulalip Tribes Squaxin Island Tribe 

Ages (years) 5% 50% 90% 95% 50% 90% 95% 

Shellfish 

18 to 34 0.00 0.181 1.163 1.676 0.073 0.690 1.141 

35 to 49 0.00 0.161 1.827 1.836 0.073 0.547 1.094 

50 to 64 0.00 0.173 0.549 0.549 0.000 0.671 0.671 

65+ 0.00 0.034 0.088 0.088 0.035 0.188 0.188 

Total finfish 

18 to 34 0.013 0.156 1.129 1.956 0.289 1.618 2.963 

35 to 49 0.002 0.533 2.188 2.388 0.383 2.052 2.495 

50 to 64 0.156 0.301 1.211 1.211 0.909 3.439 3.439 

65+ 0.006 0.176 0.531 0.531 0.601 2.049 2.049 

Total fisha 

18 to 34 0.044 0.571 2.034 2.615 0.500 2.385 3.147 

35 to 49 0.006 0.968 3.666 4.204 0.483 2.577 3.053 

50 to 64 0.190 0.476 11.586 1.586 1.106 3.589 3.589 

65+ 0.050 0.195 0.623 0.623 0.775 2.153 2.153 a Total fish includes anadromous, pelagic, bottom, shellfish, finfish, and other fish. 

Source: Toy et al. (1996). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-169 
 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-101. Median Consumption Rates by Income (g/kg-day) Within Each Tribe 

Income Tulalip Tribes Squaxin Island Tribe 

Shellfish 

≤ $10,000 0.143 0.078 

$10,001 to $15,000 0.071 0.121 

$15,001 to $20,000 0.144 0.072 

$20,001 to $25,000 0.202 0.000 

$25,001 to $35,000 0.416 0.030 

$35,001+ 0.175 0.090 

Total finfish 

≤ $10,000 0.235 0.272 

$10,001 to $15,000 0.095 0.254 

$15,001 to $20,000 0.490 0.915 

$20,001 to $25,000 0.421 0.196 

$25,001 to $35,000 0.236 0.387 

$35,001+ 0.286 0.785 

Total fish 

≤$10,000 0.521 0.476 

$10,001 to $15,000 0.266 0.432 

$15,001 to $20,000 0.640 0.961 

$20,001 to $25,000 0.921 0.233 

$25,001 to $35,000 0.930 0.426 

$35,001+ 0.607 1.085 

Source: Toy et al. (1996). 

Page Exposure Factors Handbook 

10-170 September 2011 
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-102. Mean, 50th, and 90th Percentiles of Consumption Rates for Children 

Age Birth to 5 Years (g/kg-day) 

Mean (SE) 95% CI 50% 90% 

Tulalip Tribes (N = 21) 

Shellfish 0.125 (0.056) (0.014, 0.236) 0.000 0.597 

Total finfish 0.114 (0.030) (0.056, 0.173) 0.060 0.290 

Total, all fish 0.239 (0.077) (0.088, 0.390) 0.078 0.738 

Squaxin Island Tribe (N = 48) 

Shellfish 0.228 (0.053) (0.126, 0.374) 0.045 0.574 

Total finfish 0.250 (0.063) (0.126, 0.374) 0.061 0.826 

Total, all fish 0.825 (0.143) (0.546, 1.105) 0.508 2.056 

Both Tribes Combined (weighted) 

Shellfish 0.177 (0.039) (0.101, 0.253) 0.012 0.574 

Total finfish 0.182 (0.035) (0.104, 0.251) 0.064 0.615 

Total, all fish 0.532 (0.081) (0.373, 0.691) 0.173 1.357 

N = Sample size. 

SE = Standard error. 

CI = Confidence interval. 

Source: Toy et al. (1996). 

Exposure Factors Handbook Page
 

September 2011 10-171 
 

 

 

Table 10-103. Adult Consumption Rate (g/kg-day): Individual Finfish and Shellfish and Fish Groups 

All Adult Respondents (Including Non-Consumers) Consumers Only 

Species/Group 95% 95% Percentiles 

N Mean SE Max N % GM MSE LCL UCL 5th 50th 75th 90th 95th 

Group G 

Abalone 92 0.001 0.001 0.000 0.002 0.000 0.000 0.000 0.000 0.000 0.063 3 3 0.007 3.139
 

Lobster 92 0.022 0.007 0.008 0.036 0.000 0.000 0.000 0.085 0.139 0.549 22 24 0.052 1.266
 

Octopus 92 0.019 0.006 0.008 0.030 0.000 0.000 0.015 0.069 0.128 0.407 25 27 0.042 1.231
 

Limpets 92 0.010 0.009 0.000 0.027 0.000 0.000 0.000 0.000 0.000 0.795 2 2 0.261 3.047
 

Miscellaneous 92 0.0003 0.0003 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.023 1 1 0.023
 

Group A 92 0.618 0.074 0.473 0.763 0.021 0.350 1.002 1.680 2.177 3.469 92 100 0.274 1.167
 

Group B 92 0.051 0.016 0.019 0.082 0.000 0.003 0.019 0.128 0.270 1.149 49 53 0.025 1.262
 

Group C 92 0.136 0.025 0.087 0.185 0.000 0.055 0.141 0.369 0.526 1.716 87 95 0.064 1.147
 

Group D 92 0.097 0.021 0.056 0.138 0.000 0.029 0.076 0.206 0.613 1.069 76 83 0.045 1.168
 

Group E 92 1.629 0.262 1.115 2.143 0.063 0.740 1.688 4.555 7.749 15.886 91 99 0.703 1.160
 

Group F 92 0.124 0.016 0.092 0.156 0.000 0.068 0.144 0.352 0.533 0.778 85 92 0.070 1.139
 

Group G 92 0.052 0.017 0.019 0.084 0.000 0.000 0.038 0.128 0.262 1.344 42 46 0.043 1.240
 

All Finfish 92 1.026 0.113 1.153 2.208 0.087 0.639 1.499 2.526 3.412 5.516 92 100 0.590 1.128
 

All Shellfish 92 1.680 0.269 2.049 3.364 0.063 0.796 1.825 4.590 7.754 15.976 91 99 0.727 1.160
 

All Seafood 92 2.707 0.336 0.000 0.000 0.236 1.672 3.598 6.190 10.087 18.400 92 100 1.530 1.123
 

N = Sample size.
 

SE = Standard error.
 

LCL = Lower confidence limit.
 

UCL = Upper confidence limit.
 

GM = Geometric mean.
 

MSE = Multiplicative standard error.
 

Note: The minimum consumption for all species and groups was zero, except for "Group A," "All Finfish," and "All Seafood". The minimum 

rate for "Group A” was 0.005, for "All Finfish" was 0.018, and for "All Seafood" was 0.080. 

Source: Duncan (2000). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors 10-172 Sept
 

Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only 

Group Species N 

Consumers Only 

Mean SE Median 75th 

Percentile 

90th 

Percentile 

Group A King 

Sockeye 

Coho 

Chum 

Pink 

Other or Unspecified 

Salmon 

Steelhead 

Salmon (gatherings) 

63 

59 

50 

42 

17 

32 

26 

85 

0.200 

0.169 

0.191 

0.242 

0.035 

0.159 

0.102 

0.074 

0.031 

0.026 

0.033 

0.046 

0.007 

0.070 

0.035 

.0.012 

0.092 

0.070 

0.084 

0.147 

0.034 

0.043 

0.027 

0.031 

0.322 

0.293 

0.247 

0.280 

0.057 

0.172 

0.103 

0.079 

0.581 

0.493 

0.584 

0.768 

0.077 

0.261 

0.398 

0.205 

Group B Smelt 

Herring 

49 

14 

0.078 

0.059 

0.024 

0.020 

0.016 

0.034 

0.078 

0.093 

0.247 

0.197 

Group C Cod 

Perch 

Pollock 

Sturgeon 

Sable Fish 

Spiny Dogfish 

Greenling 

Bull Cod 

78 

2 

40 

8 

5 

1 

2 

1 

0.126 

0.012 

0.054 

0.041 

0.018 

0.004 

0.013 

0.016 

0.024 

0.002 

0.020 

0.021 

0.009 

--­

0.002 

--­

0.051 

0.012 

0.013 

0.021 

0.014 

--­

0.013 

--­

0.140 

--­

0.060 

0.053 

0.034 

--­

--­

--­

0.319 

--­

0.139 

--­

--­

--­

--­

--­

Group D Halibut 

Sole/Flounder 

Rock Fish 

74 

20 

12 

0.080 

0.052 

0.169 

0.018 

0.015 

0.072 

0.029 

0.022 

0.066 

0.069 

0.067 

0.231 

0.213 

0.201 

0.728 

Group E Manila/Littleneck Clams 

Horse Clams 

Butter Clams 

Geoduck 

Cockles 

Oysters 

Mussels 

Moon Snails 

Shrimp 

Dungeness Crab 

84 

52 

72 

83 

61 

60 

25 

0 

86 

81 

0.481 

0.073 

0.263 

0.184 

0.233 

0.164 

0.059 

--­

0.174 

0.164 

0.154 

0.016 

0.062 

0.039 

0.055 

0.034 

0.020 

--­

0.027 

0.028 

0.088 

0.025 

0.123 

0.052 

0.099 

0.068 

0.015 

--­

0.088 

0.071 

0.284 

0.070 

0.184 

0.167 

0.202 

0.184 

0.085 

--­

0.196 

0.185 

1.190 

0.261 

0.599 

0.441 

0.530 

0.567 

0.155 

--­

0.549 

0.425 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-173 
 

Table 10-104. Adult Consumption Rate (g/kg-day) for Consumers Only (continued) 

Group Species N 

Consumers Only 

Mean SE Median 75th 

Percentile 

90th 

Percentile 

Group E 

(cont’d) 

Red Rock Crab 

Scallops 

Squid 

Sea Urchin 

Sea Cucumber 

Oyster (gatherings) 

Clams (gatherings) 

Crab (gatherings) 

Clams (razor, 

unspecified) 

Crab (king/snow) 

19 

54 

23 

6 

5 

40 

61 

43 

35 

1 

0.037 

0.037 

0.041 

0.025 

0.056 

0.061 

0.071 

0.056 

0.124 

0.017 

0.010 

0.009 

0.017 

0.008 

0.031 

0.014 

0.016 

0.019 

0.036 

--­

0.012 

0.011 

0.009 

0.019 

0.008 

0.031 

0.029 

0.027 

0.062 

--­

0.057 

0.040 

0:032 

0.048 

0.130 

0.088 

0.064 

0.042 

0.138 

--­

0.117 

0.110 

0.188 

--­

--­

0.152 

0.165 

0.100 

0.284 

--­

Group F Cabazon 

Blue Back (sockeye) 

Trout/Cutthroat 

Tuna (fresh/canned) 

Groupers 

Sardine 

Grunter 

Mackerel 

Shark 

1 

2 

3 

83 

1 

1 

4 

1 

1 

0.080 

0.006 

0.112 

0.129 

0.025 

0.049 

0.056 

0.008 

0.002 

--­

0.004 

0.035 

0.017 

--­

--­

0.026 

--­

--­

--­

0.006 

0.129 

0.071 

--­

--­

0.047 

--­

--­

--­

--­

--­

0.145 

--­

--­

0.110 

--­

--­

--­

--­

--­

0.346 

--­

--­

--­

--­

--­

Group G Abalone 

Lobster 

Octopus 

Limpets 

Miscellaneous 

3 

22 

25 

2 

1 

0.022 

0.092 

0.071 

0.440 

0.023 

0.020 

0.025 

0.017 

0.355 

--­

0.003 

0.057 

0.044 

0.440 

--­

--­

0.130 

0.123 

--­

--­

--­

0.172 

0.149 

--­

--­

Group A 

Group B 

Group C 

Group D 

Group E 

Group F 

Group G 

All Finfish 

92 

49 

87 

76 

91 

85 

42 

92 

0.618 

0.095 

0.144 

0.118 

1.647 

0.134 

0.113 

1.026 

0.074 

0.029 

0.026 

0.025 

0.265 

0.017 

0.034 

0.113 

0.350 

0.017 

0.068 

0.042 

0.750 

0.076 

0.042 

0.639 

1.002 

0.098 

0.141 

0.091 

1.691 

0.163 

0.118 

1.499 

1.680 

0.261 

0.403 

0.392 

4.577 

0.372 

0.270 

2.526 

All Shellfish 

All Seafood 

91 

92 

1.699 

2.707 

0.271 

0.336 

0.819 

1.672 

1.837 

3.598 

4.600 

6.190 

N 

SE 

--­

= Sample size. 

= Standard error. 

Not reported. 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-174 September 2011 
Table 10-105. Adult Consumption Rate (g/kg-day) by Sex 

Species/Group 

All Adult Respondents ( Including Non-Consumers) Consumers Only 

N Mean 95% 95% Percentiles SE N % GMa MSEb 

5th 50th 75th LCL UCL 90th 95th 

Group A (p = 0.02) 

Male 

Female 

Group B (p = 0.04) 

Male 

Female 

Group C ( p = 0.03) 

Male 

Female 

Group D (p = 0.08) 

Male 

Female 

Group E ( p = 0.03) 

Male 

Female 

Group F (p = 0.6)

Male 

Female 

Group G (p = 0.2)

Male 

Female 

All Finfish (p = 0.007) 

Male 

Female 

All Shellfish (p = 0.03) 

Male 

Female 

All Seafood (p = 0.008) 

Male 

Female 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

46 

0.817 

0.419 

0.089 

0.013 

0.170 

0.102 

0.135 

0.060 

1.865 

1.392 

0.141 

0.107 

0.081 

0.023 

1.351 

0.701 

1.946 

1.415 

3.297 

2.116 

0.120 

0.077 

0.031 

0.004 

0.043 

0.025 

0.037 

0.018 

0.316 

0.419 

0.026 

0.020 

0.032 

0.007 

0.193 

0.100 

0.335 

0.421 

0.458 

0.480 

0.582 

0.268 

0.028 

0.005 

0.086 

0.053 

0.062 

0.025 

1.246 

0.571 

0.090 

0.068 

0.018 

0.009 

0.973 

0.505 

1.289 

0.590 

2.399 

1.175 

1.052 

0.570 

0.150 

0.021 

0.254 

0.151 

0.208 

0.095 

2.484 

2.213 

0.192 

0.146 

0.144 

0.037 

1.729 

0.897 

2.603 

2.240 

4.195 

3.057 

0.021 

0.018 

0.000 

0.000 

0.007 

0.000 

0.000 

0.000 

0.068 

0.029 

0.000 

0.005 

0.000 

0.000 

0.115 

0.083 

0.068 

0.029 

0.232 

0.236 

0.459 

0.294 

0.008 

0.000 

0.078 

0.047 

0.045 

0.026 

1.101 

0.644 

0.072 

0.052 

0.001 

0.000 

0.905 

0.465 

1.121 

0.678 

2.473 

0.965 

1.463 

0.521 

0.076 

0.013 

0.148 

0.102 

0.133 

0.056 

2.608 

0.936 

0.195 

0.126 

0.070 

0.016 

1.871 

0.943 

2.628 

1.007 

4.518 

2.219 

2.033 

1.028 

0.269 

0.044 

0.432 

0.277 

0.546 

0.105 

4.980 

2.462 

0.413 

0.322 

0.261 

0.093 

3.341 

1.751 

5.146 

2.462 

8.563 

4.898 

 

2.236 

1.813 

0.623 

0.099 

0.847 

0.496 

0.948 

0.453 

7.453 

9.184 

0.597 

0.451 

0.476 

0.162 

4.540 

2.508 

7.453 

9.231 

10.008 

10.400 

46 

46 

27 

22 

46 

41 

39 

37 

46 

45 

40 

45 

23 

19 

46 

46 

46 

45 

46 

46 

100 

100 

59 

48 

100 

89 

85 

80 

100 

98 

87 

98 

50 

41 

100 

100 

100 

98 

100 

100 

0.385 

0.195 

0.046 

0.012 

0.075 

0.053 

0.057 

0.035 

0.879 

0.559 

0.089 

0.056 

0.057 

0.031 

0.800 

0.434 

0.909 

0.579 

1.971 

1.188 

1.245 

1.232 

1.378 

1.309 

1.210 

1.215 

1.274 

1.204 

1.238 

1.224 

1.199 

1.198 

1.395 

1.272 

1.191 

1.169 

1.240 

1.221 

1.188 

1.158 

N 

SE 

LCL 

UCL 

GM 

MSE 

Note 

Source: 

= Sample size. 

= Standard error. 

= Lower confidence interval. 

= Upper confidence interval. 

= Geometric m ean. 

= Multiplicative standard error. 

p-value is 2-sided and based upon Mann-Whitney test. The 95% CL is based on the normal distribution. The 5th 

than 20 respondents. 

Duncan (2000). 

and 95th percentile are not reported for groups with less 

Exposure Factors Handbook Page September 2011 10-175 

Chapter 10—Intake of Fish and Exposure Factors Handbook 

Shellfish 
 

 

 

 

Table 10-106. Adult Consumption Rate (g/kg-day) by Age 

All Adult Respondents (Including Non-Consumers) Consumers Only 

Species/Age Group N Mean SE 95% 

LCL 

95% 

UCL 

5th 50th 

Percentiles 

75th 90th 95th N % GMa MSEb 

Group A (p = 0.04) 

16 to 42 Years 58 0.512 0.083 0.349 0.675 0.015 0.294 0.660 1.544 2.105 58 100 0.215 1.219 

43 to 54 Years 15 1.021 0.233 0.564 1.478 1.020 1.596 2.468 15 100 0.645 1.337 

55 Years and Over 19 0.623 0.159 0.311 0.935 0.394 0.868 2.170 19 100 0.294 1.402 

Group B (p = 0.001) 

16 to 42 Years 58 0.042 0.022 0.000 0.085 0.000 0.000 0.009 0.098 0.295 22 38 0.023 1.447 

43 to 54 Years 15 0.097 0.047 0.005 0.189 0.019 0.124 0.421 12 80 0.049 1.503 

55 Years and Over 19 0.041 0.017 0.008 0.074 0.010 0.054 0.182 15 79 0.017 1.503 

Group C (p = 0.6) 

16 to 42 Years 58 0.122 0.026 0.071 0.173 0.000 0.055 0.134 0.301 0.578 54 93 0.061 1.186 

43 to 54 Years 15 0.117 0.029 0.060 0.174 0.078 0.146 0.339 15 100 0.072 1.335 

55 Years and Over 19 0.193 0.091 0.015 0.371 0.050 0.141 0.503 18 95 0.066 1.429 

Group D (p = 0.2) 

16 to 42 Years 58 0.079 0.023 0.034 0.124 0.000 0.026 0.072 0.164 0.610 44 76 0.043 1.218 

43 to 54 Years 15 0.164 0.079 0.009 0.319 0.049 0.094 0.862 15 100 0.056 1.435 

55 Years and Over 19 0.102 0.038 0.028 0.176 0.033 0.088 0.513 17 89 0.041 1.434 

Group E (p = 0.1) 

16 to 42 Years 58 1.537 0.289 0.971 2.103 0.059 0.740 1.715 3.513 8.259 57 98 0.707 1.199 

43 to 54 Years 15 2.241 0.571 1.122 3.360 1.679 4.403 6.115 15 100 1.188 1.419 

55 Years and Over 19 1.425 0.811 0.000 3.015 0.678 1.159 1.662 19 100 0.456 1.415 

Group F (p = 0.5) 

16 to 42 Years 58 0.119 0.021 0.078 0.160 0.000 0.044 0.123 0.387 0.563 53 91 0.065 1.180 

43 to 54 Years 15 0.154 0.050 0.056 0.252 0.109 0.217 0.472 14 93 0.098 1.339 

55 Years and Over 19 0.115 0.029 0.058 0.172 0.072 0.145 0.302 18 95 0.066 1.350 

Group G (p = 0.6) 

16 to 42 Years 58 0.052 0.024 0.005 0.099 0.000 0.006 0.035 0.126 0.241 30 52 0.037 1.259 

43 to 54 Years 15 0.088 0.043 0.004 0.172 0.000 0.116 0.420 5 33 0.207 1.447 

55 Years and Over 19 0.023 0.011 0.001 0.045 0.000 0.018 0.091 7 37 0.028 1.875 

All Finfish (p = 0.03) 

16 to 42 Years 58 0.874 0.136 0.607 1.141 0.087 0.536 1.062 2.471 2.754 58 100 0.489 1.163 

43 to 54 Years 15 1.554 0.304 0.958 2.150 1.422 2.005 3.578 15 100 1.146 1.249 

55 Years and Over 19 1.074 0.247 0.590 1.558 0.861 1.525 2.424 19 100 0.619 1.329 

All Shellfish (p = 0.1) 

16 to 42 Years 58 1.589 0.301 3.626 2.179 0.059 0.799 1.834 3.626 8.305 57 98 0.736 1.197 

43 to 54 Years 15 2.330 0.586 1.181 3.479 1.724 4.519 6.447 15 100 1.225 1.426 

55 Years and Over 19 1.447 0.815 0.000 3.044 0.688 1.160 1.837 19 100 0.464 1.417 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 10-176 September 2011
Table 10-106. Adult Consumption Rate (g/kg-day) by Age (continued) 

Species/Age Group 

All Adult Respondents ( Including Non-Consumers) Consumers Only 

N Mean 95% 95% Percentiles SE N % GM MSE 5th 50th 75th LCL UCL 90th 95th 

All Seafood (p = 0.09) 

 16to 42 Years 

 43to 54 Years 

55 Years and 

Over 

58 

15 

19 

2.463 

3.884 

2.522 

0.387 

0.781 

0.927 

1.704 

2.353 

0.705 

3.222 

5.415 

4.339 

0.247 1.270 

3.869 

1.393 

3.410 

4.942 

2.574 

6.206 

9.725 

5.220 

 

9.954 

 

 

58 

15 

19 

100 

100 

100 

1.384 

2.665 

1.340 

1.156 

1.295 

1.293 

N 

SE 

LCL 

UCL 

GM 

MSE 

Note 

Source: 

= Sample size. 

= Standard error. 

= Lower confidence interval. 

= Upper confidence interval. 

= Geometric m ean. 

= Multiplicative standard error. 

p-value is 2-sided and based upon Kruskul-Wallis test. The 95% CL is based on the normal distribution. The 5 th 

less than 20 respondents. 

Duncan (2000). 

and 95th percentiles are not reported for groups with 

Chapter 10—Intake of Fish and Exposure Factors Handbook 

Shellfish 

Exposure Factors Handbook PageSeptember 2011 10-177
 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 10-178 September 2011

Table 10-107. Consumption Rates for Native American Children (g/kg-day), All Children (including non-consumers): 

Individual Finfish and Shellfish and Fish Groups 

Group Species N Mean SE 95% LCL 95% UCL p5 Median p75 p90 p95 Maximum 

Group E 

Manila/Littleneck clams 

Horse clams 

Butter clams 

Geoduck 

Cockles 

Oysters 

Mussels 

Moon snails 

Shrimp 

Dungeness crab 

Red rock crab 

Scallops 

Squid 

Sea urchin 

Sea cucumber 

31 

31 

31 

31 

31 

31 

31 

31 

31 

31 

31 

31 

31 

31 

31 

0.095 

0.022 

0.021 

0.112 

0.117 

0.019 

0.001 

0.000 

0.093 

0.300 

0.007 

0.011 

0.002 

0.000 

0.000 

0.051 

0.013 

0.014 

0.041 

0.079 

0.012 

0.001 

-

0.038 

0.126 

0.003 

0.006 

0.002 

-

-

0.000 

0.000 

0.000 

0.033 

0.000 

0.000 

0.000 

-

0.019 

0.053 

0.001 

0.000 

0.000 

-

-

0.195 

0.048 

0.048 

0.191 

0.271 

0.043 

0.002 

-

0.168 

0.547 

0.014 

0.022 

0.005 

-

-

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.000 

0.031 

0.000 

0.000 

0.027 

0.000 

0.000 

0.000 

0.000 

0.004 

0.047 

0.000 

0.000 

0.000 

0.000 

0.000 

0.063 

0.006 

0.000 

0.116 

0.054 

0.056 

0.000 

0.000 

0.059 

0.166 

0.000 

0.005 

0.000 

0.000 

0.000 

0.181 

0.048 

0.041 

0.252 

0.240 

0.058 

0.000 

0.000 

0.394 

1.251 

0.046 

0.031 

0.000 

0.000 

0.000 

0.763 

0.269 

0.247 

0.841 

1.217 

0.205 

0.011 

0.000 

0.712 

2.689 

0.064 

0.089 

0.000 

0.000 

0.000 

1.597 

0.348 

0.422 

1.075 

2.433 

0.362 

0.026 

0.000 

0.982 

2.833 

0.082 

0.174 

0.411 

0.000 

0.000 

Group Aa 

Group Bb 

Group Cc 

Group Dd 

Group Fe 

31 

31 

31 

31 

31 

0.271 

0.004 

0.131 

0.030 

0.240 

0.117 

0.002 

0.040 

0.011 

0.075 

0.043 

0.000 

0.052 

0.008 

0.094 

0.499 

0.008 

0.210 

0.053 

0.387 

0.000 

0.000 

0.000 

0.000 

0.000 

0.063 

0.000 

0.036 

0.010 

0.092 

0.216 

0.000 

0.205 

0.037 

0.254 

0.532 

0.015 

0.339 

0.081 

0.684 

2.064 

0.038 

0.838 

0.191 

1.571 

3.559 

0.069 

1.014 

0.342 

1.901 

All Finfish 

All Shellfish 

All Seafood 

31 

31 

31 

0.677 

0.801 

1.477 

0.168 

0.274 

0.346 

0.346 

0.265 

0.799 

1.007 

1.337 

2.155 

0.026 

0.000 

0.042 

0.306 

0.287 

0.724 

0.740 

0.799 

1.983 

2.110 

2.319 

3.374 

3.549 

4.994 

7.272 

4.101 

7.948 

9.063 

a Group A is salmon, including king, sockeye, coho, chum, pink, and steelhead. b Group B is finfish, including smelt and herring. c Group C is finfish, including cod, perch, pollock, sturgeon, sablefish, spiny dogfish, and greenling. d Group D is finfish, including halibut, sole, flounder, and rockfish. e Group F includes tuna, other finfish, and all others not included in Groups A, B, C, and D. 

- = Not applicable. 

N = Sample size. 

SE = Standard error 

LCL = Lower confidence limit 

UCL = Upper confidence limit 

p5...p95 = Percentile value. 

Note: The minimum consumption for all species and groups was zero, except for “All Finfish” and “All Seafood.” The minimum rate for “All Finfish” was 0.023, and for “All 

Seafood” was 0.035. 

Source: Duncan (2000). 
 

c 

Table 10-108. Consumption Rates for Native American Children (g/kg-day), 

Consumers Only: Individual Finfish and Shellfish and Fish Groups 

Percentiles Group Species N Mean SE Median 75th 90th 

Group E Manila/Littleneck clams 23 0.128 0.068 0.043 0.066 0.200 

Horse clams 12 0.058 0.032 0.009 0.046 0.308 

Butter clams 6 0.106 0.066 0.032 0.203 -

Geoduck 22 0.158 0.054 0.053 0.230 0.554 

Cockles 10 0.361 0.233 0.078 0.291 2.230 

Oysters 10 0.060 0.035 0.015 0.074 0.336 

Mussels 1 0.026 - - - -

Moon snails 0 - - - - -

Shrimp 17 0.170 0.064 0.035 0.299 0.621 

Dungeness crab 21 0.443 0.179 0.082 0.305 2.348 

Red rock crab 5 0.046 0.011 0.051 0.067 -

Scallops 8 0.042 0.019 0.027 0.032 -

Squid 2 0.033 0.008 0.033 - -

Sea urchin 0 - - - - -

Sea cucumber 0 - - - - -

Group Aa 28 0.300 0.128 0.112 0.246 0.599 

Group Bb 5 0.023 0.012 0.017 0.043 -

Group Cc 25 0.163 0.048 0.048 0.236 0.493 

Group Dd 17 0.055 0.019 0.033 0.064 0.140 

Group Fe (tuna/other finfish) 24 0.311 0.092 0.177 0.336 1.035 

All finfish 31 0.677 0.168 0.306 0.740 2.110 

All shellfish 28 0.886 0.299 0.363 0.847 2.466 

All seafood 31 1.477 0.346 0.724 1.983 3.374 a Group A is salmon, including king, sockeye, coho, chum, pink, and steelhead. b Group B is finfish, including smelt and herring. 

Group C is finfish, including cod, perch, pollock, sturgeon, sablefish, spiny dogfish, and greenling. d Group D is finfish, including halibut, sole, flounder, and rockfish. e Group F includes tuna, other finfish, and all others not included in Groups A, B, C, and D. 

N = Sample size. 

SE = Standard error. 

- = No data. 

Source: Duncan (2000). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-179 
 

 

Table 10-109. Percentiles and Mean of Consumption Rates for Adult Consumers Only (g/kg-day) 

Species N Mean 

 

SD 95% CI 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 

Squaxin Island Tribe 

Anadromous 

fish 117 0.672 1.174 (0.522–1.034) 0.016 0.028 0.093 0.308 0.802 1.563 2.086 

Pelagic fish 62 0.099 0.203 (0.064–0.181) 0.004 0.007 0.014 0.035 0.086 0.226 0.349 

Bottom fish 94 0.093 0.180 (0.065–0.140) 0.006 0.007 0.016 0.037 0.079 0.223 0.370 

Shellfish 86 0.282 0.511 (0.208–0.500) 0.006 0.015 0.051 0.126 0.291 0.659 1.020 

Other fish 39 0.046 0.066 (0.031–0.073) 0.002 0.005 0.006 0.019 0.046 0.129 0.161 

All finfish 117 0.799 1.263 (0.615–1.136) 0.031 0.056 0.139 0.383 1.004 1.826 2.537 

All fish 117 1.021 1.407 (0.826–1.368) 0.050 0.097 0.233 0.543 1.151 2.510 3.417 

Tulalip Tribe 

Anadromous 

fish 72 0.451 0.671 (0.321–0.648) 0.010 0.020 0.065 0.194 0.529 1.372 1.990 

Pelagic fish 38 0.077 0.100 (0.051–0.118) 0.005 0.011 0.015 0.030 0.088 0.216 0.266 

Bottom fish 44 0.062 0.092 (0.043–0.107) 0.006 0.007 0.011 0.030 0.077 0.142 0.207 

Shellfish 61 0.559 1.087 (0.382–1.037) 0.037 0.047 0.104 0.196 0.570 1.315 1.824 

Other fish 36 0.075 0.119 (0.044–0.130) 0.004 0.004 0.011 0.022 0.054 0.239 0.372 

All finfish 72 0.530 0.707 (0.391–0.724) 0.017 0.026 0.119 0.286 0.603 1.642 2.132 

All fish 73 1.026 1.563 (0.772–1.635) 0.049 0.074 0.238 0.560 1.134 2.363 2.641 

N = Sample size. 

SD = Standard deviation. 

CI = Confidence interval. 

Source: Polissar et al. (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-180 September 2011 
Exposure Factors Handbook Page 

September 2011 10-181 Table 10-110. Percentiles and Mean of Consumption Rates by Sex for Adult Consumers Only (g/kg-day

Species Sex N Mean SD 95% CI Percentiles 5th 10th 25th 50th 75th 

Squaxin Island Tribe Anadromous fish Pelagic fish Bottom fish Shellfish Other fish All finfish All fish Male Female Male Female Male Female Male Female Male Female Male Female Male Female 65 52 39 23 55 39 52 34 27 12 65 52 65 52 0.596 0.766 0.104 0.091 0.091 0.096 0.305 0.245 0.047 0.045 0.735 0.878 0.999 1.049 0.629 1.618 0.235 0.136 0.185 0.175 0.586 0.372 0.066 0.068 0.784 1.686 0.991 1.808 (0.465–0.770) (0.463–1.458) (0.055–0.219) (0.050–0.160) (0.060–0.185) (0.058–0.177) (0.215–0.645) (0.149–0.407) (0.029–0.085) (0.016–0.100) (0.586–0.980) (0.546–1.652) (0.794–1.291) (0.712–1.793) 0.026 0.016 0.003 0.005 0.005 0.006 0.006 0.007 0.003 - 0.044 0.026 0.082 0.041 0.039 0.023 0.008 0.007 0.007 0.007 0.014 0.018 0.005 0.004 0.079 0.039 0.157 0.061 0.163 0.068 0.013 0.017 0.017 0.014 0.052 0.047 0.006 0.008 0.226 0.115 0.335 0.183 0.388 0.184 0.037 0.030 0.041 0.034 0.136 0.119 0.020 0.015 0.500 0.272 0.775 0.353 0.816 0.656 0.074 0.096 0.077 0.089 0.337 0.250 0.061 0.037 1.045 0.840 1.196 1.083 

Tulalip Tribe Anadromous fish Pelagic fish Bottom fish Male Female Male Female Male Female 41 31 24 14 24 20 0.546 0.327 0.066 0.096 0.061 0.063 0.754 0.528 0.099 0.103 0.106 0.073 (0.373–0.856) (0.189–0.578) (0.037–0.119) (0.046–0.153) (0.035–0.147) (0.039–0.103) 0.011 0.014 0.013 - 0.006 0.007 0.020 0.028 0.014 0.005 0.006 0.008 0.066 0.066 0.016 0.016 0.009 0.014 0.408 0.134 0.030 0.053 0.030 0.029 0.570 0.290 0.064 0.156 0.070 0.093 
Table 10-110. Percentiles and Mean of Consumption Rates by Sex for Adult Consumers Only (g/kg-day) (continued) 

Species 

 

Sex N Mean 

 

SD 95% CI 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 

Shellfish 

Other fish 

All finfish 

All fish 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

35 

26 

24 

12 

41 

31 

42 

31 

0.599 

0.505 

0.064 

0.097 

0.620 

0.411 

1.140 

0.872 

1.261 

0.818 

0.114 

0.131 

0.795 

0.561 

1.805 

1.168 

(0.343–1.499) 

(0.292–1.018) 

(0.029–0.134) 

(0.041–0.190) 

(0.438–0.966) 

(0.265–0.678) 

(0.785–2.047) 

(0.615–1.453) 

0.036 

0.043 

0.004 

-

0.017 

0.025 

0.049 

0.066 

0.048 

0.047 

0.004 

0.011 

0.020 

0.036 

0.068 

0.144 

0.098 

0.117 

0.007 

0.015 

0.098 

0.126 

0.208 

0.305 

0.183 

0.215 

0.026 

0.022 

0.421 

0.236 

0.623 

0.510 

0.505 

0.582 

0.043 

0.142 

0.706 

0.404 

1.142 

0.963 

1.329 

1.074 

0.174 

0.254 

1.995 

0.924 

2.496 

1.938 

1.826 

1.357 

0.334 

-

2.185 

1.769 

2.638 

2.317 

N = Sample size. 

SD = Standard deviation. 

CI = Confidence interval. 

- = No data. 

Source: Polissar et al. (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 10-182 September 2011
Table 10-111. Percentiles and Mean of Consumption Rates by Age for Adult Consume rs Only—Squaxin Island Tribe (g/kg-day) 

Species 

Age Group 

(years) N Mean SD 95% CI 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 

Anadromous fish 

Pelagic fish 

Bottom fish 

Shellfish 

Other fish 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

54 

41 

11 

11 

22 

30 

4 

6 

41 

35 

9 

9 

44 

27 

5 

10 

20 

10 

2 

7 

0.664 

0.563 

1.126 

0.662 

0.067 

0.128 

0.154 

0.036 

0.063 

0.126 

0.159 

0.035 

0.335 

0.264 

0.321 

0.076 

0.079 

0.014 

0.007 

0.010 

1.392 

0.820 

1.511 

0.681 

0.086 

0.269 

0.239 

0.023 

0.102 

0.225 

0.302 

0.031 

0.657 

0.321 

0.275 

0.079 

0.079 

0.008 

0.003 

0.007 

(0.430–1.438) 

(0.376–0.914) 

(0.595–2.791) 

(0.321–1.097) 

(0.040–0.114) 

(0.063–0.272) 

(0.027–0.396) 

(0.020–0.053) 

(0.043–0.120) 

(0.076–0.276) 

(0.029–0.460) 

(0.020–0.065) 

(0.211–0.729) 

(0.171–0.422) 

(0.137–0.589) 

(0.033–0.124) 

(0.053–0.122) 

(0.009–0.019) 

(0.005–0.009) 

(0.006–0.015) 

0.019 

0.023 

-

-

0.006 

0.003 

-

-

0.004 

0.010 

-

-

0.014 

0.016 

-

-

0.004 

-

-

-

0.026 

0.031 

0.212 

0.015 

0.007 

0.005 

-

-

0.006 

0.013 

0.009 

0.006 

0.019 

0.054 

-

0.005 

0.005 

0.005 

-

-

0.078 

0.073 

0.278 

0.107 

0.014 

0.014 

0.033 

0.017 

0.012 

0.023 

0.014 

0.018 

0.041 

0.082 

0.100 

0.007 

0.025 

0.007 

-

0.006 

0.233 

0.292 

0.771 

0.522 

0.035 

0.029 

0.045 

0.038 

0.034 

0.051 

0.029 

0.034 

0.127 

0.146 

0.335 

0.042 

0.046 

0.015 

0.007 

0.008 

0.863 

0.590 

0.948 

0.924 

0.081 

0.101 

0.166 

0.047 

0.069 

0.111 

0.067 

0.043 

0.327 

0.277 

0.364 

0.155 

0.124 

0.020 

-

0.014 

1.236 

1.354 

2.160 

1.636 

0.186 

0.248 

-

-

0.115 

0.273 

0.451 

0.060 

0.698 

0.582 

-

0.180 

0.161 

0.022 

-

-

1.969 

2.062 

-

-

0.228 

0.626 

-

-

0.221 

0.446 

-

-

1.046 

0.984 

-

-

0.218 

-

-

-

Exposure Factors Handbook Page September 2011 10-183 

Chapter 10—Exposure Factors Handbook 

Intake of Fish and Shellfish 
Table 10-111. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only —Squaxin Island Tribe (g/kg-day) 

(continued) 

Species 

Age Group 

(years) N Mean SD 95% CI 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 

All finfish 18 to 34 54 0.739 1.417 (0.508–1.372) 0.025 0.039 0.105 0.289 0.887 1.466 2.296 

35 to 49 41 0.764 1.001 (0.527–1.173) 0.046 0.082 0.226 0.383 0.816 1.859 2.423 

50 to 64 11 1.312 1.744 (0.690–3.219) - 0.212 0.297 0.909 1.119 2.188 -

≥65 11 0.711 0.699 (0.386–1.259) - 0.027 0.119 0.601 0.986 1.637 -

All fish 18 to 34 54 1.041 1.570 (0.729–1.741) 0.052 0.107 0.217 0.500 1.117 2.669 3.557 

35 to 49 41 0.941 1.217 (0.652–1.453) 0.051 0.136 0.248 0.483 0.975 2.227 3.009 

50 to 64 11 1.459 1.773 (0.770–3.258) - 0.317 0.327 1.106 1.301 2.936 -

≥65 11 0.786 0.727 (0.446–1.242) - 0.058 0.122 0.775 1.091 1.687 -

N = Sample size. 

SD = Standard deviation. 

CI = Confidence interval. 

- = No data. 

Source: Polissar et al. (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 10-184 September 2011
Table 10-112. Percentiles and Mean of Consumption Rates by Age for Adult Consumers Only —Tulalip Tribe 

(g/kg-day) 

Species 

Age Group 

(years) N Mean SD 95% CI 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 

Anadromous 

fish 

Pelagic fish 

Bottom fish 

Shellfish 

Other fish 

All finfish 

All fish 

18 to 34 

35 to 49 

50 to 64 

 ≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

18 to 34 

35 to 49 

50 to 64 

≥65 

27 0.298 

23 0.725 

16 0.393 

6 0.251

12 0.092 

15 0.077 

8 0.077

3 0.008

14 0.075 

16 0.066 

11 0.051

3 0.015

23 0.440 

19 1.065 

14 0.245 

5 0.062

15 0.097 

13 0.057 

6 0.075

2 0.024

27 0.378 

23 0.821 

16 0.467 

6 0.263

27 0.806 

24 1.661 

16 0.710 

6 0.322

0.456 

0.928 

0.550 

0.283 

0.099 

0.118 

0.085 

0.009 

0.138 

0.069 

0.056 

0.005 

0.487 

1.784 

0.216 

0.064 

0.146 

0.085 

0.138 

0.015 

0.548 

0.951 

0.535 

0.293 

0.747 

2.466 

0.591 

0.344 

(0.169–0.524) 

(0.436–1.202) 

(0.225–0.854) 

(0.065–0.475) 

(0.051–0.173) 

(0.039–0.206) 

(0.037–0.160) 

(0.002–0.014) 

(0.033–0.205) 

(0.041–0.112) 

(0.026–0.098) 

(0.008–0.018) 

(0.289–0.702) 

(0.536–2.461) 

(0.158–0.406) 

(0.027–0.135) 

(0.043–0.197) 

(0.022–0.123) 

(0.015–0.215) 

(0.014–0.024) 

(0.222–0.680) 

(0.532–1.315) 

(0.311–0.925) 

(0.091–0.518) 

(0.575–1.182) 

(0.974–3.179) 

(0.513–1.144) 

(0.107–0.642) 

0.011 

0.010 

-

-

-

-

-

-

-

-

-

-

0.049 

0.049 

-

-

-

-

-

-

0.018 

0.020 

-

-

0.071 

0.017 

-

-

0.016 

0.032 

0.059 

-

0.016 

0.013 

-

-

0.007 

0.007 

0.007 

-

0.053 

0.074 

0.048 

-

0.010 

0.004 

-

-

0.022 

0.047 

0.186 

-

0.136 

0.069 

0.278 

-

0.061 

0.078 

0.164 

0.022 

0.021 

0.015 

0.027 

0.003 

0.010 

0.023 

0.011 

0.013 

0.131 

0.123 

0.117 

0.023 

0.017 

0.006 

0.012 

-

0.080 

0.116 

0.227 

0.030 

0.231 

0.177 

0.370 

0.062 

0.120 

0.431 

0.228 

0.164 

0.054 

0.021 

0.034 

0.004 

0.020 

0.053 

0.036 

0.017 

0.196 

0.250 

0.224 

0.046 

0.033 

0.014 

0.018 

0.024 

0.156 

0.602 

0.301 

0.176 

0.617 

0.968 

0.495 

0.195 

0.315 

0.719 

0.420 

0.425 

0.124 

0.087 

0.090 

0.011 

0.078 

0.077 

0.069 

0.018 

0.582 

1.222 

0.282 

0.060 

0.102 

0.049 

0.038 

-

0.438 

0.898 

0.503 

0.430 

1.126 

2.005 

0.944 

0.475 

0.713 

2.001 

0.599 

-

0.218 

0.189 

-

-

0.142 

0.152 

0.119 

-

1.076 

2.265 

0.417 

-

0.319 

0.187 

-

-

0.840 

2.035 

0.615 

-

1.960 

3.147 

1.070 

-

1.281 

2.171 

-

-

-

-

-

-

-

-

-

-

1.410 

4.351 

-

-

-

-

-

-

1.677 

2.268 

-

-

2.457 

5.707 

-

-

- = No data. 

Source: Polissar et al. (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-185 
 

 

Table 10-113. Percentiles and Mean of Consumption Rates for Child Consumers Only (g/kg-day) 

Species N Mean SD 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 

Squaxin Island Tribe 

Anadromous fish 

Pelagic fish 

Bottom fish 

Shellfish 

Other fish 

All finfish 

All fish 

33 

21 

18 

31 

30 

35 

36 

0.392 

0.157 

0.167 

2.311 

0.577 

0.538 

2.890 

1.295 

0.245 

0.362 

8.605 

0.584 

1.340 

8.433 

0.005 

0.010 

-

0.006 

0.012 

0.005 

0.012 

0.006 

0.014 

0.006 

0.025 

0.051 

0.007 

0.019 

0.030 

0.019 

0.014 

0.050 

0.111 

0.046 

0.244 

0.049 

0.044 

0.026 

0.262 

0.400 

0.062 

0.704 

0.130 

0.107 

0.050 

0.404 

0.566 

0.216 

1.495 

0.686 

0.547 

0.482 

0.769 

1.620 

1.698 

2.831 

0.786 

0.712 

-

4.479 

1.628 

2.334 

7.668 

Tulalip Tribe 

Anadromous fish 

Pelagic fish 

Bottom fish 

Shellfish 

Other fish 

All finfish 

All fish 

14 

7 

2 

11 

1 

15 

15 

0.148 

0.152 

0.044 

0.311 

0.115 

0.310 

0.449 

0.229 -

0.178 -

0.005 -

0.392 -

0.115 -

0.332 -

0.529 -

 0.012

 -

 -

 0.012

 -

 0.027

 0.066

0.026 

0.027 

-

0.034 

-

0.082 

0.088 

0.045 

0.053 

0.041 

0.036 

-

0.133 

0.215 

0.136 

0.165 

-

0.518 

-

0.431 

0.601 

0.334 

-

-

0.803 

-

0.734 

0.884 

-

-

-

-

-

-

-

N = Sample size. 

SD = Standard deviation. 

- = No data. 

Source: Polissar et al. (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-186 September 2011 
Table 10-114. Percentiles and Mean of Consumption Rates by Sex for Child Consumers Only (g/kg-day) 

Species Sex N Mean SD 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 

Squaxin Island Tribe 

Anadromous fish 

Pelagic fish 

Bottom fish 

Shellfish 

Other fish 

All finfish 

All fish 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

15 

18 

8 

13 

6 

12 

13 

18 

13 

17 

15 

20 

15 

21 

0.702 

0.155 

0.102 

0.179 

0.038 

0.244 

0.275 

3.799 

0.836 

0.400 

0.787 

0.372 

1.700 

3.655 

1.937 

0.253 

0.138 

0.280 

0.057 

0.442 

0.244 

11.212 

0.663 

0.463 

1.940 

0.719 

1.965 

10.738 

-

-

-

-

-

-

-

-

-

-

-

0.005 

-

0.008 

0.009 

0.005 

-

0.015 

-

0.005 

0.036 

0.008 

0.106 

0.013 

0.009 

0.005 

0.061 

0.014 

0.026 

0.025 

0.015 

0.020 

0.016 

0.010 

0.047 

0.050 

0.232 

0.096 

0.038 

0.037 

0.476 

0.160 

0.062 

0.046 

0.058 

0.040 

0.020 

0.028 

0.241 

0.229 

0.448 

0.311 

0.062 

0.071 

1.184 

0.599 

0.331 

0.090 

0.099 

0.109 

0.026 

0.105 

0.353 

0.490 

1.530 

0.486 

0.521 

0.179 

1.937 

0.916 

1.082 

0.600 

-

0.681 

-

0.736 

0.462 

1.333 

1.625 

0.610 

1.500 

1.408 

2.444 

2.764 

-

-

-

-

-

-

-

-

-

-

-

2.119 

-

16.374 

Tulalip Tribe 

Anadromous fish 

Pelagic fish 

Bottom fish 

Shellfish 

Other fish 

All finfish 

All fish 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

Male 

Female 

7 

7 

5 

2 

0 

2 

5 

6 

0 

1 

8 

7 

8 

7 

0.061 

0.237 

0.106 

0.265 

-

0.044 

0.141 

0.431 

-

0.115 

0.208 

0.433 

0.202 

0.745 

0.052 -

0.306 -

0.081 -

0.350 -

- -

0.005 -

0.221 -

0.459 -

- -

0.115 -

0.176 -

0.440 -

0.169 -

0.670 -

- 0.023 

- 0.032 

- 0.044 

- -

- -

- -

- 0.012 

- 0.034 

- -

- -

- 0.087 

- 0.045 

- 0.071 

- 0.155 

0.034 

0.080 

0.053 

0.017 

-

0.041 

0.027 

0.219 

-

-

0.133 

0.165 

0.122 

0.488 

0.067 - -

0.198 - -

0.128 - -

- - -

- - -

- - -

0.110 - -

0.651 - -

- - -

- - -

0.322 - -

0.652 - -

0.233 - -

0.835 - -

N 

SD 

-

Source: 

= Sample size. 

= Standard deviation. 

= No data. 

Polissar et al. (2006). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-187 
 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-115. Consumption Rates of API Community Members 

Category N 

Median 

(g/kg-day) 

Mean 

(g/kg-day) 

Percentage of 

Consumptiona SE 

95% LCI 

(g/kg-day) 

95% UCI 

(g/kg-day) 

90th Percentile 

(g/kg-day) 

Anadromous 

Fish 

202 0.093 0.201 10.6% 0.008 0.187 0.216 0.509 

Pelagic Fish 202 0.215 0.382 20.2% 0.013 0.357 0.407 0.829 

Freshwater Fish 202 0.043 0.110 5.8% 0.005 0.101 0.119 0.271 

Bottom Fish 202 0.047 0.125 6.6% 0.006 0.113 0.137 0.272 

Shellfish Fish 202 0.498 0.867 45.9% 0.023 0.821 0.913 1.727 

Seaweed/Kelp 202 0.014 0.084 4.4% 0.005 0.075 0.093 0.294 

Miscellaneous 

Seafood 

202 0.056 0.121 6.4% 0.004 0.112 0.130 0.296 

All Finfish 202 0.515 0.818 43.3% 0.023 0.774 0.863 1.638 

All Fish 202 1.363 1.807 95.6% 0.042 1.724 1.889 3.909 

All Seafood 202 1.439 1.891 100.0% 0.043 1.805 1.976 3.928 

a Percentage of consumption = the percent of each category that makes up the total (i.e., 10.6% of total 

fish eaten was anadromous fish). 

N = Sample size. 

SE = Standard error. 

LCI = 95% lower confidence interval. 

UCI = 95% upper confidence interval. 

Note: Confidence intervals were computed based on the Student's t-distribution. Rates were weighted across 

ethnic groups. 

Source: U.S. EPA (1999). 

Page Exposure Factors Handbook 

10-188 September 2011 
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-116. Demographic Characteristics of “Higher” and “Lower” Seafood Consumers 

All Finfish Shellfish 

N 

Lower Consumers 

(%) 

Higher Consumersa 

(%) 

Lower Consumers 

(%) 

Higher Consumersb 

(%) 

Female 107 76 24 71 29 

Male 95 81 19 79 21 

18 to 29 years 78 85 15 73 27 

30 to 54 years 85 79 21 78 22 

55+ 39 64 36 72 28 

Cambodian 20 90 10 70 30 

Chinese 30 83 17 70 30 

Filipino 30 80 20 87 13 

Japanese 29 48 52 79 21 

Korean 22 91 9 68 32 

Laotian 20 75 25 75 25 

Mien 10 90 10 90 10 

Hmong 5 100 0 100 0 

Samoan 10 100 0 100 0 

Vietnamese 26 69 31 50 50 

Non-fishermen 136 82 18 76 24 

Fishermen 66 71 29 73 27 

a Higher Consumer: >75 percentile = 1.144 g/kg-day. b Higher Consumer: >75 percentile = 1.072g/kg-day. 

N = Sample size. 

Source: U.S. EPA (1999). 

Exposure Factors Handbook Page
 

September 2011 10-189 
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 10-190 September 2011

Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community (g/kg-day)

a 

Category Ethnicity N Mean SE 10 

Percentile Median 90 

Percentile 

% With 

Non-Zero 

Consumption 

Consumers 

(%) 

95% 

LCI 

95% 

UCI 

Anadromous fish 

(p < 0.001) 

Pelagic Fish 

(p < 0.001) 

Freshwater Fish 

(p < 0.001) 

Cambodian 20 0.118 0.050 0.000 0.030 0.453 18 90 

Chinese 30 0.193 0.052 0.012 0.066 0.587 30 100 

Filipino 30 0.152 0.027 0.025 0.100 0.384 29 96.7 

Japanese 29 0.374 0.056 0.086 0.251 0.921 29 100 

Korean 22 0.091 0.026 0.007 0.048 0.248 22 100 

Laotian 20 0.187 0.064 0.002 0.069 0.603 18 90 

Mien 10 0.018 0.008 0.000 0.011 0.080 7 70 

Hmong 5 0.059 0.013 n/a 0.071 n/a 5 100 

Samoan 10 0.067 0.017 0.012 0.054 0.185 10 100 

Vietnamese 26 0.124 0.026 0.017 0.072 0.349 26 100 

All Ethnicity (1) 202 0.201 0.008 0.016 0.093 0.509 194 96 

Cambodian 20 0.088 0.021 0.000 0.061 0.293 17 85 

Chinese 30 0.325 0.068 0.022 0.171 0.824 30 100 

Filipino 30 0.317 0.081 0.051 0.132 0.729 30 100 

Japanese 29 0.576 0.079 0.132 0.429 1.072 29 100 

Korean 22 0.313 0.056 0.073 0.186 0.843 22 100 

Laotian 20 0.412 0.138 0.005 0.115 1.061 20 100 

Mien 10 0.107 0.076 0.000 0.09 0.716 7 70 

Hmong 5 0.093 0.028 n/a 0.090 n/a 5 100 

Samoan 10 0.499 0.060 0.128 0.535 0.792 10 100 

Vietnamese 26 0.377 0.086 0.059 0.208 0.956 26 100 

All Ethnicity (1) 202 0.382 0.013 0.046 0.215 0.829 196 97 

Cambodian 20 0.139 0.045 0.000 0.045 0.565 18 90 

Chinese 30 0.084 0.023 0.000 0.015 0.327 24 80 

Filipino 30 0.132 0.034 0.018 0.086 0.273 30 100 

Japanese 29 0.021 0.006 0.000 0.007 0.071 20 69 

Korean 22 0.032 0.015 0.000 0.008 0.160 13 59.1 

Laotian 20 0.282 0.077 0.002 0.099 1.006 18 90 

Mien 10 0.097 0.039 0.007 0.070 0.407 10 100 

Hmong 5 0.133 0.051 n/a 0.081 n/a 5 100 

Samoan 10 0.026 0.007 0.000 0.025 0.061 9 90 

Vietnamese 26 0.341 0.064 0.068 0.191 1.036 26 100 

All Ethnicity (1) 202 0.110 0.005 0.000 0.043 0.271 173 85.6 

0.014 

0.086 

0.098 

0.261 

0.037 

0.054 

0.000 

0.026 

0.030 

0.071 

0.187 

0.044 

0.187 

0.151 

0.415 

0.196 

0.124 

–0.064 

0.021 

0.365 

0.201 

0.357 

0.045 

0.037 

0.062 

0.010 

0.002 

0.122 

0.010 

0.002 

0.011 

0.209 

0.101 

0.223 

0.300 

0.206 

0.488 

0.146 

0.321 

0.036 

0.091 

0.104 

0.176 

0.216 

0.131 

0.463 

0.482 

0.737 

0.429 

0.700 

0.277 

0.164 

0.633 

0.553 

0.407 

0.232 

0.131 

0.202 

0.032 

0.062 

0.442 

0.184 

0.263 

0.041 

0.472 

0.119 
 

Chapter 10—Exposure Factors Handbook 

Intake of Fish and Shellfish 

Exposure Factors Handbook PageSeptember 2011 10-191

Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community (g/kg-day)

a (continued) 

Category Ethnicity N Mean SE 10 

Percentile Median 90 

Percentile 

% With 

Non-Zero 

Consumption 

Consumers 

(%) 

95% 

LCI 

95% 

UCI 

Bottom Fish Cambodian 20 0.045 0.025 0.000 0.003 0.114 10 50 –0.006 

(p < 0.001) Chinese 30 0.082 0.026 0.004 0.033 0.212 28 93.3 0.028 

Filipino 30 0.165 0.043 0.001 0.103 0.560 27 90 0.078 

Japanese 29 0.173 0.044 0.023 0.098 0.554 28 96.6 0.083 

Korean 22 0.119 0.026 0.000 0.062 0.270 19 86.4 0.064 

Laotian 20 0.066 0.031 0.000 0.006 0.173 13 65 0.000 

Mien 10 0.006 0.003 0.000 0.00 0.026 4 40 –0.001 

Hmong 5 0.036 0.021 n/a 0.024 n/a 3 60 –0.017 

Samoan 10 0.029 0.005 0.008 0.026 0.058 10 100 0.018 

Vietnamese 26 0.102 0.044 0.000 0.030 0.388 21 80.8 0.013 

All Ethnicity (1) 202 0.125 0.006 0.000 0.047 0.272 163 80.7 0.113 

Shellfish Fish Cambodian 20 0.919 0.216 0.085 0.695 2.003 20 100 0.467 

(p < 0.001) Chinese 30 0.985 0.168 0.176 0.569 2.804 30 100 0.643 

Filipino 30 0.613 0.067 0.188 0.505 1.206 30 100 0.477 

Japanese 29 0.602 0.089 0.116 0.401 1.428 29 100 0.419 

Korean 22 1.045 0.251 0.251 0.466 2.808 22 100 0.524 

Laotian 20 0.898 0.259 0.041 0.424 2.990 19 95 0.357 

Mien 10 0.338 0.113 0.015 0.201 1.058 10 100 0.086 

Hmong 5 0.248 0.014 n/a 0.252 n/a 5 100 0.212 

Samoan 10 0.154 0.024 0.086 0.138 0.336 10 100 0.100 

Vietnamese 26 1.577 0.260 0.247 1.196 4.029 26 100 1.044 

All Ethnicity (1) 202 0.867 0.023 0.168 0.498 1.727 201 99.5 0.821 

Seaweed/Kelp Cambodian 20 0.002 0.001 0.000 0.000 0.008 7 35 0.000 

(p < 0.001) Chinese 30 0.062 0.022 0.001 0.017 0.314 29 96.7 0.016 

Filipino 30 0.009 0.004 0.000 0.000 0.025 15 50 0.002 

Japanese 29 0.190 0.043 0.019 0.082 0.752 29 100 0.101 

Korean 22 0.200 0.050 0.011 0.087 0.686 21 95.5 0.096 

Laotian 20 0.004 0.003 0.000 0.000 0.013 6 30 –0.001 

Mien 10 0.000 0.000 0.000 0.000 0.000 0 0 0.000 

Hmong 5 0.002 0.001 n/a 0.001 n/a 3 60 0.000 

Samoan 10 0.000 0.000 0.000 0.000 0.000 0 0 0.000 

Vietnamese 26 0.017 0.012 0.000 0.000 0.050 6 23.1 –0.008 

All Ethnicity (1) 202 0.084 0.005 0.000 0.014 0.294 116 57.4 0.075 

0.097 

0.135 

0.253 

0.263 

0.173 

0.131 

0.013 

0.088 

0.040 

0.192 

0.137 

1.370 

1.327 

0.750 

0.784 

1.566 

1.439 

0.590 

0.283 

0.208 

2.110 

0.913 

0.004 

0.107 

0.016 

0.279 

0.304 

0.009 

0.000 

0.004 

0.000 

0.043 

0.093 
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 10-192 September 2011

Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community (g/kg-day)

a (continued) 

Category Ethnicity N Mean SE 10 

Percentile Median 90 

Percentile 

% With 

Non-Zero 

Consumption 

Consumers 

(%) 

95% 

LCI 

95% 

UCI 

Miscellaneous 

Fish 

Cambodian 20 0.113 0.026 0.000 0.087 0.345 18 90 0.058 

(p < 0.001) Chinese 30 0.081 0.021 0.003 0.030 0.201 30 100 0.038 

Filipino 30 0.083 0.025 0.016 0.043 0.182 30 100 0.032 

Japanese 29 0.246 0.036 0.032 0.206 0.620 29 100 0.173 

Korean 22 0.092 0.031 0.004 0.047 0.307 21 95.5 0.028 

Laotian 20 0.074 0.021 0.000 0.025 0.225 15 75 0.029 

Mien 10 0.015 0.008 0.000 0.002 0.063 7 70 0.003 

Hmong 5 0.019 0.014 n/a 0.008 n/a 4 80 0.018 

Samoan 10 0.076 0.028 0.003 0.045 0.276 10 100 0.014 

Vietnamese 26 0.089 0.013 0.013 0.087 0.184 25 96.2 0.062 

All Ethnicity (1) 202 0.121 0.004 0.005 0.056 0.296 189 93.6 0.112 

All Finfish Cambodian 20 0.390 0.098 0.061 0.223 1.379 20 100 0.185 

(p < 0.001) Chinese 30 0.683 0.133 0.114 0.338 2.024 30 100 0.412 

Filipino 30 0.766 0.148 0.268 0.452 1.348 30 100 0.464 

Japanese 29 1.144 0.124 0.194 1.151 2.170 29 100 0.890 

Korean 22 0.555 0.079 0.180 0.392 1.204 22 100 0.391 

Laotian 20 0.947 0.204 0.117 0.722 2.646 20 100 0.523 

Mien 10 0.228 0.117 0.034 0.097 1.160 10 100 –0.032 

Hmong 5 0.319 0.073 n/a 0.268 n/a 5 100 0.131 

Samoan 10 0.621 0.059 0.225 0.682 0.842 10 100 0.490 

Vietnamese 26 0.944 0.171 0.188 0.543 2.568 26 100 0.593 

All Ethnicity (1) 202 0.818 0.023 0.166 0.515 1.638 202 100 0.774 

0.168 

0.123 

0.134 

0.139 

0.156 

0.118 

0.033 

0.055 

0.138 

0.115 

0.130 

0.594 

0.954 

1.067 

1.398 

0.719 

1.372 

0.488 

0.507 

0.751 

1.296 

0.863 
 

 

Chapter 10—Exposure Factors Handbook 

Intake of Fish and Shellfish 

Exposure Factors Handbook PageSeptember 2011 10-193

Table 10-117. Seafood Consumption Rates by Ethnicity for Asian and Pacific Islander Community (g/kg-day)

a (continued) 

Category Ethnicity N Mean SE 10 

Percentile Median 90 

Percentile 

% With 

Non-Zero 

Consumption 

Consumers 

(%) 

95% 

LCI 

95% 

UCI 

All Fish Cambodian 20 1.421 0.274 0.245 1.043 3.757 20 100 0.850 

(p < 0.001) Chinese 30 1.749 0.283 0.441 1.337 4.206 30 100 1.172 

Filipino 30 1.462 0.206 0.660 1.137 2.423 30 100 1.041 

Japanese 29 1.992 0.214 0.524 1.723 3.704 29 100 1.555 

Korean 22 1.692 0.275 0.561 1.122 3.672 22 100 1.122 

Laotian 20 1.919 0.356 0.358 1.467 4.147 20 100 1.176 

Mien 10 0.580 0.194 0.114 0.288 1.967 10 100 0.149 

Hmong 5 0.585 0.069 n/a 0.521 n/a 5 100 0.407 

Samoan 10 0.850 0.078 0.363 0.879 1.188 10 100 0.676 

Vietnamese 26 2.610 0.377 0.653 2.230 6.542 26 100 1.835 

All Ethnicity (1) 202 1.807 0.042 0.480 1.363 3.909 202 100 1.724 

All Seafood Cambodian 20 1.423 0.274 0.245 1.043 3.759 20 100 0.851 

(p < 0.001) Chinese 30 1.811 0.294 0.452 1.354 4.249 30 100 1.210 

Filipino 30 1.471 0.206 0.660 1.135 2.425 30 100 1.050 

Japanese 29 2.182 0.229 0.552 1.830 3.843 29 100 1.714 

Korean 22 1.892 0.294 0.608 1.380 4.038 22 100 1.281 

Laotian 20 1.923 0.356 0.400 1.467 4.147 20 100 1.181 

Mien 10 0.580 0.194 0.114 0.288 1.967 10 100 0.149 

Hmong 5 0.587 0.069 n/a 0.521 n/a 5 100 0.410 

Samoan 10 0.850 0.078 0.363 0.879 1.188 10 100 0.676 

Vietnamese 26 2.627 0.378 0.670 2.384 6.613 26 100 1.851 

All Ethnicity (1) 202 1.891 0.043 0.521 1.439 3.928 202 100 1.805 

1 

2.326 

1.883 

2.429 

2.262 

2.663 

1.012 

0.764 

1.025 

3.385 

1.889 

1.995 

2.411 

1.892 

2.650 

2.503 

2.665 

1.012 

0.765 

1.025 

3.404 

1.976 a All consumption rates in g/kg body weight/day. Weighted by population percentage. 

N = Sample size. 

SE = Standard error. 

LCI = Lower confidence interval. 

UCI = Upper confidence interval. 

Note: p-values are based on Kruskal-Wallis test. 

Source: U.S. EPA (1999). 
 

 

Table 10-118. Consumption Rates by Sex for All Asian and Pacific Islander Community 

Female Male 

Mean Median Mean Median 

Category N (g/kg-day) SE (g/kg-day) N (g/kg-day) SE (g/kg-day) 

Anadromous Fish (p = 0.8) 107 0.165 0.022 0.076 95 0.169 0.024 0.080 

Pelagic Fish (p = 0.4) 107 0.349 0.037 0.215 95 0.334 0.045 0.148 

Freshwater Fish (p = 1.0) 107 0.131 0.021 0.054 95 0.137 0.023 0.054 

Bottom Fish (p = 0. 6) 107 0.115 0.019 0.040 95 0.087 0.017 0.034 

Shellfish (p = 0.8) 107 0.864 0.086 0.432 95 0.836 0.104 0.490 

Seaweed/Kelp (p = 0.5) 107 0.079 0.018 0.005 95 0.044 0.010 0.002 

Miscellaneous Seafood (p = 0.5) 107 0.105 0.013 0.061 95 0.104 0.015 0.055 

All Finfish (p = 0.8) 107 0.759 0.071 0.512 95 0.726 0.072 0.458 

All Fish (p = 0.5) 107 1.728 0.135 1.328 95 1.666 0.149 1.202 

All Seafood (p = 0.4) 107 1.807 0.139 1.417 95 1.710 0.152 1.257 

N = Sample size. 

SE = Standard error.
 

Note: p-values are based on Mann-Whitney test.
 

Source: U.S. EPA (1999).
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Page Exposure Factors Handbook 

10-194 September 2011 
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-119. Types of Seafood Consumed/Respondents Who Consumed (%) 

Type of Seafood (%) 

Anadromous Fish 

Salmon 93 

Trout 61 

Smelt 45 

Salmon Eggs 27 

Pelagic Fish 

Tuna 86 

Cod 66 

Mackerel 62 

Snapper 50 

Rockfish 34 

Herring 21 

Dogfish 7 

Snowfish 6 

Freshwater Fish 

Catfish 58 

Tilapia 45 

Perch 39 

Bass 28 

Carp 22 

Crappie 17 

Bottom Fish 

Halibut 65 

Sole/Flounder 42 

Sturgeon 13 

Suckers 4 

Shellfish 

Shrimp 98 

Crab 96 

Squid 82 

Oysters 71 

Manila/Littleneck Clams 72 

Lobster 65 

Mussel 62 

Scallops 57 

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September 2011 10-195 
 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-119. Types of Seafood Consumed/Respondents Who Consumed (%) 

(continued) 

Type of Seafood (%) 

Butter Clams 39 

Geoduck 34 

Cockles 21 

Abalone 15 

Razor Clams 16 

Sea Cucumber 15 

Sea Urchin 14 

Horse Clams 13 

Macoma Clams 9 

Moonsnail 4 

Seaweed/Kelp 

Seaweed 57 

Kelp 29 

Source: U.S. EPA (1999). 

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10-196 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-120. Mean, Median and 95th Percentile Fish Intake Rates for Different Groups (g/day) 

Sample Group 

Sample 

Size 

Local Fish Intakea 

Mean Median 95th Mean 

Total Fish Intakeb 

Median 95th 

Ethnicity 

African American 32 31.2 21.3 242.3 48.3 21.3 252.0 

Southeast Asian 152 32.3 17.0 129.4 42.8 24.1 180.2 

Hmong 67 17.8 14.9 89.6 22.3 19.1 89.6 

Lao 30 57.6 21.3 310.4 65.2 24.1 317.5 

Vietnamese 33 27.1 21.7 152.4 55.4 36.1 249.3 

Asian/Pacific Islander 38 23.8 15.6 148.3 46.1 35.0 156.4 

Hispanic 45 25.8 19.1 155.9 36.3 14.2 169.5 

Native American 6 6.5 NDc ND 69.9 108.4 ND 

White 57 23.6 21.3 138.9 34.7 28.4 139.2 

Russian 17 23.7 17.7 ND 36.1 35.5 ND 

All Anglers 373 27.4 19.7 126.6 40.6 26.1 147.3 

Southeast Asiand 286 40.8 17.0 128.5 50.3 25.5 144.5 

Hmongd 130 21.3 14.9 102.1 26.5 17.0 119.7 

Laod 54 47.2 17.0 265.8 54.4 28.4 267.0 

Age 

18 to 34 143 32.0 24.6 138.9 44.9 25.5 151.5 

35 to 49 130 22.7 14.2 120.5 36.8 24.0 143.9 

>49 87 30.6 17.0 207.0 44.3 24.1 217.2 

Sex 

Female 35 38.2 22.5 226.8 53.9 24.6 263.1 

Male 336 26.4 19.5 129.3 39.3 26.1 146.6 

Household Contains 

Women 18 to 49 years 217 33.0 21.2 142.2 46.6 25.5 158.1 

Children 174 35.1 22.2 142.8 49.2 27.1 171.9 

Awareness

e 

0 172 24.7 18.2 121.6 35.5 23.0 143.5 

1 44 42.8 28.0 361.1 52.9 28.5 361.1 

2 115 28.4 21.3 139.6 45.8 28.0 151.7 

3 35 12.2 13.8 62.4 28.1 20.8 95.6 

4 7 57.1 36.1 ND 65.0 39.0 ND a Locally caught fish. b Locally caught and commercially obtained fish. c Not determined because of insufficient data. d All data shown are for angler surveying, except for these groups which are rates from combined 

angler and community surveys. e Respondent responses when asked about their awareness of warnings about fish contamination 

ranged from 0 = no awareness to 4 = high awareness. 

Source: Shilling et al. (2010). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Exposure Factors Handbook Page
 

September 2011 10-197 
 

 

Table 10-121. Distribution of Quantity of Fish Consumed (in grams) per Eating Occasion, by Age and Sex 

Percentiles 

25th 50th 75th 90th 95th 99th Age (years)-Sex Group Mean SD 5th 

1 to 2 Male-Female 52 38 8 28 43 58 112 125 168 

3 to 5 Male-Female 70 51 12 36 57 85 113 170 240 

6 to 8 Male-Female 81 58 19 40 72 112 160 170 288 

9 to 14 Male 101 78 28 56 84 113 170 255 425 

9 to 14 Female 86 62 19 45 79 112 168 206 288 

15 to 18 Male 117 115 20 57 85 142 200 252 454 

15 to 18 Female 111 102 24 56 85 130 225 270 568 

19 to 34 Male 149 125 28 64 113 196 284 362 643 

19 to 34 Female 104 74 20 57 85 135 184 227 394 

35 to 64 Male 147 116 28 80 113 180 258 360 577 

35 to 64 Female 119 98 20 57 85 152 227 280 480 

65 to 74 Male 145 109 35 75 113 180 270 392 480 

65 to 74 Female 123 87 24 61 103 168 227 304 448 

≥75 Male 124 68 36 80 106 170 227 227 336 

≥75 Female 112 69 20 61 112 151 196 225 360 

Overall 117 98 20 57 85 152 227 284 456 

Source: Pao et al. (1982). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

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10-198 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-122. Distribution of Quantity of Canned Tuna Consumed (grams) per Eating Occasion, by Age and 

Sex 

Percentiles Age (years)-Sex Group Mean SE 5th 10th 25th 50th 75th 90th 95th 

2 to 5 

Male-Female 37 3 5* 8 14 29 56 73 85* 

6 to 11 

Male-Female 58 8 14* 20* 28 49 60 99* 157* 

12 to 19 

Male 98* 16* - 18* 49* 84 162* 170* 186* 

Female 64 6 14* 18* 28* 56 77* 105* 156* 

20 to 39 

Male 84 7 15* 27* 49 57 113 160* 168* 

Female 61 5 14* 14* 34 56 74 110* 142* 

40 to 59 

Male 72 4 14* 27 37 57 96 127 168* 

Female 60 4 13* 15 28 56 74 112 144 

60 and older 

Male 64 5 12* 17* 37 56 81 114* 150* 

Female 67 4 12* 23 42 57 85 112 153* 

SE = Standard error. 

* Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of 

variation. 

- Indicates a percentage that could not be estimated. 

Source: Smiciklas-Wright et al. (2002) (based on 1994–1996 CSFII data). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

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September 2011 10-199 
 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10-123. Distribution of Quantity of Other Finfish Consumed (grams) per Eating Occasion, by Age and 

Sex 

Percentiles Age (years)-Sex Group Mean SE 5th 10th 25th 50th 75th 90th 95th 

2 to 5 

Male-Female 64 4 8* 16 33 58 77 124 128* 

6 to 11 

Male-Female 93 8 17* 31* 50 77 119 171* 232* 

12 to 19 

Male 119* 11* 40* 50* 64* 89 170* 185* 249* 

Female 89* 13* 20* 26* 47* 67 124* 164* 199* 

20 to 39 

Male 117 8 37* 47 68 100 138 205 256* 

Female 111 10 26* 36* 50 85 129 209* 289* 

40 to 59 

Male 130 7 29* 47 75 110 153 243 287* 

Female 107 9 29* 42 51 85 123 174 244* 

60 and older 

Male 111 6 37* 45 57 90 133 220 261* 

Female 108 6 33* 42 57 90 130 200 229* 

SE	 = Standard error. 

* Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of 

variation. 

Source:	 Smiciklas-Wright et al. (2002) (based on 1994–1996 CSFII data). 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

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10-200 September 2011 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-124. Percentage of Individuals Using Various Cooking Methods at Specified Frequencies 

Study 

Use 

Frequency Bake 

Pan Fry Deep 

Fry 

Broil or 

Grill Poach Boil Smoke Raw Other 

Connelly et al. (1992) Always 

Ever 

24a 

75a 

51 

88 

13 

59 

24a 

75a 

Connelly et al. (1996) Always 

Ever 

13 

84 

4 

72 

4 

42 

CRITFC (1994) At Least 

Monthly 

79 51 14 27 11 46 31 1 34b 

29c 

49d 

Ever 98 80 25 39 17 73 66 3 67b 71c 

75d 

Fitzgerald et al. (1995) Not Specified 94e,f 71e,g 

Puffer et al. (1982) As Primary 

Method 

16.3 52.5 12 0.25 19h 

a 24 and 75 listed as bake, BBQ, or poach. b Dried. c Roasted. d Canned. e Not specified whether deep or pan fried. f Mohawk women. g Control population. h Boil, stew, soup, or steam. 

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September 2011 10-201 
 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

FINFISH 

Anchovy, European 73.37 

50.30 

4.84 

9.71 

Raw 

Canned in oil, drained solids 

Bass, Freshwater 75.66 

68.79 

3.69 

4,73 

Raw 

Cooked, dry heat 

Bass, Striped 79.22 

73.36 

2.33 

2.99 

Raw 

Cooked, dry heat 

Bluefish 70.86 

62.64 

4.24 

5.44 

Raw 

Cooked, dry heat 

Burbot 79.26 

73.41 

0.81 

1.04 

Raw 

Cooked, dry heat 

Butterfish 74.13 

66.83 

8.02 

10.28 

Raw 

Cooked, dry heat 

Carp 76.31 

69.63 

5.60 

7.17 

Raw 

Cooked, dry heat 

Catfish, Channel, Farmed 75.38 

71.58 

7.59 

8.02 

Raw 

Cooked, dry heat 

Catfish, Channel, Wild 80.36 

77.67 

2.82 

2.85 

Raw 

Cooked, dry heat 

Caviar, Black and Red 47.50 17.90 --

Cisco 78.93 

1.91 

69.80 

11.90 

Raw 

Smoked 

Cod, Atlantic 81.22 

75.61 

75.92 

16.14 

0.67 

0.86 

0.86 

2.37 

Raw 

Canned, solids and liquids 

Cooked, dry heat 

Dried and salted 

Cod, Pacific 81.28 

76.00 

0.63 

0.81 

Raw 

Cooked, dry heat 

Croaker, Atlantic 78.03 

59.76 

3.17 

12.67 

Raw 

Cooked, breaded and fried 

Cusk 76.35 

69,68 

0.69 

0.88 

Raw 

Cooked, dry heat 

Dolphinfish 77.55 

71.22 

0.70 

0.90 

Raw 

Cooked, dry heat 

Drum, Freshwater 77.33 

70.94 

4.93 

6.32 

Raw 

Cooked, dry heat 

Eel 69.26 

59.31 

11.66 

14.95 

Raw 

Cooked, dry heat 

Flatfish, Flounder, and Sole 79.06 

73.16 

1.19 

1.53 

Raw 

Cooked, dry heat 

Grouper 79.22 

73.36 

1.02 

1.30 

Raw, mixed species 

Cooked, dry heat 

Haddock 79.92 

74.25 

71.48 

0.72 

0.93 

0.96 

Raw 

Cooked, dry heat 

Smoked 

Halibut, Atlantic and Pacific 77.92 

71.69 

2.29 

2.94 

Raw 

Cooked, dry heat 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species (continued) 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

Halibut, Greenland 70.27 

61.88 

13.84 

17.74 

Raw 

Cooked, dry heat 

Herring, Atlantic 72.05 

64.16 

59.70 

55.22 

9.04 

11.59 

12.37 

18.00 

Raw 

Cooked, dry heat 

Kippered 

Pickled 

Herring, Pacific 71.52 

63.49 

13.88 

17.79 

Raw 

Cooked, dry heat 

Ling 79.63 

73,88 

0.64 

0.82 

Raw 

Cooked, dry heat 

Lingcod 81.03 

75.68 

1.06 

1.36 

Raw 

Cooked, dry heat 

Mackerel, Atlantic 63.55 

53.27 

13.89 

17.81 

Raw 

Cooked, dry heat 

Mackerel, Jack 69.17 6.30 Canned, drained solids 

Mackerel, King 75.85 

69.04 

2.00 

2.56 

Raw 

Cooked, dry heat 

Mackerel, Pacific and Jack 70.15 

61.73 

7.89 

10.12 

Raw 

Cooked, dry heat 

Mackerel, Spanish 71.67 

68.46 

6.30 

6.32 

Raw 

Cooked, dry heat 

Milkfish 70.85 

62.63 

6.73 

8.63 

Raw 

Cooked, dry heat 

Monkfish 83.24 

78.51 

1.52 

1.95 

Raw 

Cooked, dry heat 

Mullet, Striped 77.01 

70.52 

3.79 

4.86 

Raw 

Cooked, dry heat 

Ocean Perch, Atlantic 78.70 

72.69 

1.63 

2.09 

Raw 

Cooked, dry heat 

Perch 79.13 

73.25 

0.92 

1.18 

Raw 

Cooked, dry heat 

Pike, Northern 78.92 

72.97 

0.69 

0.88 

Raw 

Cooked, dry heat 

Pike, Walleye 79.31 

73.47 

1.22 

1.56 

Raw 

Cooked, dry heat 

Pollock, Atlantic 78.18 

72.03 

0.98 

1.26 

Raw 

Cooked, dry heat 

Pollock, Walleye 81.56 

74.06 

0.80 

1.12 

Raw 

Cooked, dry heat 

Pompano, Florida 71.12 

62.97 

9.47 

12.14 

Raw 

Cooked, dry heat 

Pout, Ocean 81.36 

76.10 

0.91 

1.17 

Raw 

Cooked, dry heat 

Rockfish, Pacific 79.26 

73.41 

1.57 

2.01 

Raw 

Cooked, dry heat 

Roe 67.73 

58.63 

6.42 

8.23 

Raw 

Cooked, dry heat 

Roughy, Orange 75.67 

66.97 

0.70 

0.90 

Raw 

Cooked, dry heat 

Sablefish 71.02 

62.85 

60.14 

15.30 

19.62 

20.14 

Raw 

Cooked, dry heat 

Smoked 

Salmon, Atlantic, Farmed 68.90 

64.75 

10.85 

12.35 

Raw 

Cooked, dry heat 

Salmon, Atlantic, Wild 68.50 

59.62 

6.34 

8.13 

Raw 

Cooked, dry heat 

Salmon, Chinook 71.64 

65.60 

72.00 

10.43 

13.38 

4.32 

Raw 

Cooked, dry heat 

Smoked 

Salmon, Chum 75.38 

68.44 

70.77 

3.77 

4.83 

5.50 

Raw 

Cooked, dry heat 

Drained solids with bone 

Salmon, Coho, Farmed 70.47 

67.00 

7.67 

8.23 

Raw 

Cooked, dry heat 

Salmon, Coho, Wild 72.66 5.93 Raw 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species (continued) 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

71.50 

65.39 

4.30 

7.50 

Cooked, dry heat 

Cooked, moist heat 

Salmon, Pink 76.35 

69.68 

68.81 

3.45 

4.42 

6.05 

Raw 

Cooked, dry heat 

Canned, solids with bone and liquid 

Salmon, Sockeye 70.24 

61.84 

67.51 

8.56 

10.97 

7.31 

Raw 

Cooked, dry heat 

Canned, drained solids with bone 

Sardine, Atlantic 59.61 11.45 Canned in oil, drained solids with bone 

Sardine, Pacific 66.65 10.46 Canned in tomato sauce, drained solids with bone 

Scup 75.37 

68.42 

2.73 

3.50 

Raw 

Cooked, dry heat 

Sea Bass 78.27 

72.14 

2.00 

2.56 

Raw 

Cooked, dry heat 

Seatrout 78.09 

71.91 

3.61 

4.63 

Raw 

Cooked, dry heat 

Shad, American 68.19 

59.22 

13.77 

17.65 

Raw 

Cooked, dry heat 

Shark, mixed species 73.58 

60.09 

4.51 

13.82 

Raw 

Cooked, batter-dipped and fried 

Sheepshead 77.97 

69.04 

2.41 

1.63 

Raw 

Cooked, dry heat 

Smelt, Rainbow 78.77 

72.79 

2.42 

3.10 

Raw 

Cooked, dry heat 

Snapper 76.87 

70.35 

1.34 

1.72 

Raw 

Cooked, dry heat 

Spot 75.95 

69.17 

4.90 

6.28 

Raw 

Cooked, dry heat 

Sturgeon 76.55 

69.94 

62.50 

4.04 

5.18 

4.40 

Raw 

Cooked, dry heat 

Smoked 

Sucker, white 79.71 

73.99 

2.32 

2.97 

Raw 

Cooked, dry heat 

Sunfish, Pumpkinseed 79.50 

73.72 

0.70 

0.90 

Raw 

Cooked, dry heat 

Surimi 76.34 0.90 -

Swordfish 75.62 

68.75 

4.01 

5.14 

Raw 

Cooked, dry heat 

Tilapia 78.08 

71.59 

1.70 

2.65 

Raw 

Cooked, dry heat 

Tilefish 78.90 

70.24 

2.31 

4.69 

Raw 

Cooked, dry heat 

Trout, Mixed Species 71.42 

63.36 

6.61 

8.47 

Raw 

Cooked, dry heat 

Trout, Rainbow, Farmed 72.73 

67.53 

5.40 

7.20 

Raw 

Cooked, dry heat 

Trout, Rainbow, Wild 71.87 

70.50 

3.46 

5.82 

Raw 

Cooked, dry heat 

Tuna, Fresh, Bluefin 68.09 

59.09 

4.90 

6.28 

Raw 

Cooked, dry heat 

Tuna, Fresh, Skipjack 70.58 

62.28 

1.01 

1.29 

Raw 

Cooked, dry heat 

Tuna, Fresh, Yellowfin 70.99 

62.81 

0.95 

1.22 

Raw 

Cooked, dry heat 

Tuna, Light 59.83 

74.51 

8.21 

0.82 

Canned in oil, drained solids 

Canned in water, drained solids 

Tuna, White 64.02 

73.19 

8.08 

2.97 

Canned in oil, drained solids 

Canned in water, drained solids 

Turbot, European 76.95 

70.45 

2.95 

3.78 

Raw 

Cooked, dry heat 

Whitefish, mixed species 72.77 

65.09 

70.83 

5.86 

7.51 

0.93 

Raw 

Cooked, dry heat 

Smoked 

Whiting, mixed species 80.27 

74.71 

1.31 

1.69 

Raw 

Cooked, dry heat 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10-125. Mean Percent Moisture and Total Fat Content for Selected Species (continued) 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

Wolffish, Atlantic 79.90 

74.23 

2.39 

3.06 

Raw 

Cooked, dry heat 

Yellowtail, mixed species 74.52 

67.33 

5.24 

6.72 

Raw 

Cooked, dry heat 

SHELLFISH 

Abalone 74.56 

60.10 

0.76 

6.78 

Raw 

Cooked, fried 

Clam 81.82 

63.64 

97.70 

61.55 

63.64 

0.97 

1.95 

0.02 

11.15 

1.95 

Raw 

Canned, drained solids 

Canned, liquid 

Cooked, breaded and fried 

Cooked, moist heat 

Crab, Alaska King 79.57 

77.55 

74.66 

0.60 

1.54 

0.46 

Raw 

Cooked, moist heat 

Imitation, made from surimi 

Crab, Blue 79.02 

79.16 

77.43 

71.00 

1.08 

1.23 

1.77 

7.52 

Raw 

Canned 

Cooked, moist heat 

Crab cakes 

Crab, Dungeness 79.18 

73.31 

0.97 

1.24 

Raw 

Cooked, moist heat 

Crab, Queen 80.58 

75.10 

1.18 

1.51 

Raw 

Cooked, moist heat 

Crayfish, Farmed 84.05 

80.80 

0.97 

1.30 

Raw 

Cooked, moist heat 

Crayfish, Wild 82.24 

79.37 

0.95 

1.20 

Raw 

Cooked, moist heat 

Cuttlefish 80.56 

61.12 

0.70 

1.40 

Raw 

Cooked, moist heat 

Lobster, Northern 76.76 

76.03 

0.90 

0.59 

Raw 

Cooked, moist heat 

Lobster, Spiny 74.07 

66.76 

1.51 

1.94 

Raw 

Cooked, moist heat 

Mussel, Blue 80.58 

61.15 

2.24 

4.48 

Raw 

Cooked, moist heat 

Octopus 80.25 

60.50 

1.04 

2.08 

Raw 

Cooked, moist heat 

Oyster, Eastern 86.20 

85.16 

85.14 

64.72 

81.95 

83.30 

70.32 

1.55 

2.46 

2.47 

12.58 

2.12 

1.90 

4.91 

Raw, farmed 

Raw, wild 

Canned 

Cooked, breaded and fried 

Cooked, farmed, dry heat 

Cooked, wild, dry heat 

Cooked, wild, moist heat 

Oyster, Pacific 82.06 

64.12 

2.30 

4.60 

Raw 

Cooked, moist heat 

Scallop, mixed species 78.57 

58.44 

73.10 

0.76 

10.94 

1.40 

Raw 

Cooked, breaded and fried 

Steamed 

Shrimp 75.86 

75.85 

52.86 

77.28 

1.73 

1.36 

12.28 

1.08 

Raw 

Canned 

Cooked, breaded and fried 

Cooked, moist heat 

Squid 78.55 

64.54 

1.38 

7.48 

Raw 

Cooked, fried 

Source: USDA (2007). 

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Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Figure 10-2. Species and Frequency of Meals Consumed by Geographic Residence. 

Source: Mahaffey et al. (2009). 

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10-206 September 2011 
 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

APPENDIX 10A:
 

RESOURCE UTILIZATION DISTRIBUTION
 

Exposure Factors Handbook Page
 

September 2011 10A-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

10A.1.	 RESOURCE UTILIZATION 

DISTRIBUTION 

The percentiles of the resource utilization 

distribution of Y are to be distinguished from the 

percentiles of the (standard) distribution of Y. The 

latter percentiles show what percentage of 

individuals in the population are consuming below a 

given level. Thus, the 50th percentile of the 

distribution of Y is that level such that 50% of 

individuals consume below it; on the other hand, the 

50th percentile of the resource utilization distribution 

is that level such that 50% of the overall 

consumption in the population is done by individuals 

consuming below it. 

The percentiles of the resource utilization 

distribution of Y will always be greater than or equal 

to the corresponding percentiles of the (standard) 

distribution of Y, and, in the case of recreational fish 

consumption, usually considerably exceed the 

standard percentiles. 

To generate the resource utilization 

distribution, one simply weights each observation in 

the data set by the Y level for that observation and 

performs a standard percentile analysis of weighted 

data. If the data already have weights, then one 

multiplies the original weights by the Y level for that 

observation, and then performs the percentile 

analysis. 

Under certain assumptions, the resource 

utilization percentiles of fish consumption may be 

related (approximately) to the (standard) percentiles 

of fish consumption derived from the analysis of 

creel studies. In this instance, it is assumed that the 

creel survey data analysis did not employ sampling 

weights (i.e., weights were implicitly set to one); this 

is the case for many of the published analyses of 

creel survey data. In creel studies, the fish 

consumption rate for the i

th individual is usually 

derived by multiplying the amount of fish 

consumption per fishing trip (say Ci) by the 

frequency of fishing (say fi). If it is assumed that the 

probability of sampling an angler is proportional to 

fishing frequency, then sampling weights of inverse 

fishing frequency (1/fi) should be employed in the 

analysis of the survey data. Above it was stated that 

for data that are already weighted, the resource 

utilization distribution is generated by multiplying 

the original weights by the individual’s fish 

consumption level to create new weights. Thus, to 

generate the resource utilization distribution from the 

data with weights of (1/fi), one multiplies (1/fi) by the 

fish consumption level of fi Ci to get new weights of 

Ci. 

Now if Ci (amount of consumption per fishing 

trip) is constant over the population, then these new 

weights are constant and can be taken to be one. But 

weights of one is what (it is assumed) were used in 

the original creel survey data analysis. Hence, the 

resource utilization distribution is exactly the same 

as the original (standard) distribution derived from 

the creel survey using constant weights. 

The accuracy of this approximation of the 

resource utilization distribution of fish by the 

(standard) distribution of fish consumption derived 

from an unweighted analysis of creel survey data 

depends then on two factors, how approximately 

constant the Ci’s are in the population and how 

approximately proportional the relationship between 

sampling probability and fishing frequency is. 

Sampling probability will be roughly proportional to 

frequency if repeated sampling at the same site is 

limited or if re-interviewing is performed 

independent of past interviewing status. 

Note: For any quantity Y that is 

consumed by individuals in a population, the 

percentiles of the “resource utilization distribution” 

of Y can be formally defined as follows: Yp (R) is the 

pth percentile of the resource utilization distribution 

if p percent of the overall consumption of Y in the 

population is done by individuals with consumption 

below Yp (R) and 100-p percent is done by 

individuals with consumption above Yp(R). 

Page Exposure Factors Handbook 

10A-2 September 2011 
 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

APPENDIX 10B:
 

FISH PREPARATION AND COOKING METHODS
 

Exposure Factors Handbook Page
 

September 2011 10B-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10B-1. Percent of Fish Meals Prepared Using Various Cooking Methods by Residence Sizea 

Residence Size 

Large 

City/Suburb Small City Town Small Town Rural Non-Farm Farm 

Total Fish 

Cooking Method 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Don't Know 

Total (N) 

32.7 

19.6 

6.0 

23.6 

12.4 

2.5 

3.2 

0 

393 

31.0 

24.0 

3.0 

20.8 

12.4 

6.0 

2.8 

0 

317 

36.0 

23.3 

3.4 

13.8 

10.0 

8.3 

5.2 

0 

388 

32.4 

24.7 

3.7 

21.4 

10.3 

5.0 

1.9 

0.5 

256 

38.6 

26.2 

3.4 

13.7 

12.7 

2.3 

2.9 

0.2 

483 

51.6 

15.7 

3.5 

13.1 

6.4 

7.0 

1.8 

-­

94 

Sport Fish 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (smoked, etc.) 

Don't Know 

Total (N) 

45.8 

12.2 

2.8 

20.2 

11.8 

2.7 

4.5 

0 

205 

45.7 

14.5 

2.3 

17.6 

8.8 

8.5 

2.7 

0 

171 

47.6 

17.5 

2.9 

10.6 

6.3 

10.4 

4.9 

0 

257 

41.4 

15.2 

0.5 

25.3 

8.7 

6.7 

1.5 

0.7 

176 

51.2 

21.9 

3.6 

8.2 

9.7 

1.9 

3.5 

0 

314 

63.3 

7.3 

0 

10.4 

6.9 

9.3 

2.8 

0 

62 a Large City = over 100,000; Small City = 20,000–100,000; Town = 2,000–20,000; Small Town = 

100-2,000. 

N = Total number of respondents. 

Source: West et al. (1993). 

Page Exposure Factors Handbook 

10B-2 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10B-2. Percent of Fish Meals Prepared Using Various Cooking Methods by Age 

Age (years) 17–30 31–40 41–50 51–64 >64 Overall 

Total Fish 

Cooking Method 

Pan Fried 

Deep Fried 

Boiled 

Grilled or Boiled 

Baked 

Combination 

Other (Smoked, etc.) 

Don't Know 

Total (N) 

45.9 

23.0 

0.0000 

15.6 

10.8 

3.1 

1.6 

0.0 

246 

31.7 

24.7 

6.0 

15.2 

13.0 

5.2 

4.2 

0.0 

448 

30.5 

26.9 

3.6 

24.3 

8.7 

2.2 

3.5 

0.3 

417 

33.9 

23.7 

3.9 

16.1 

12.8 

6.5 

2.7 

0.4 

502 

40.7 

14.0 

4.3 

18.8 

11.5 

6.8 

4.0 

0.0 

287 

35.3 

23.5 

3.9 

17.8 

11.4 

4.7 

3.2 

0.2 

1,946 

Sport Fish 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Don't Know 

Total (N) 

57.6 

18.2 

0.0000 

15.0 

3.6 

3.8 

1.7 

0.0 

174 

42.6 

21.0 

4.4 

10.1 

10.4 

7.2 

4.3 

0.0 

287 

43.4 

17.3 

0.8 

25.9 

6.4 

3.0 

3.2 

0.0 

246 

46.6 

14.8 

3.2 

12.2 

11.7 

7.5 

3.5 

0.4 

294 

54.1 

7.7 

3.1 

12.2 

9.9 

8.2 

4.8 

0.0 

163 

47.9 

16.5 

2.4 

14.8 

8.9 

5.9 

3.5 

0.1 

1,187 

N = Total number of respondents. 

Source: West et al. (1993). 

Exposure Factors Handbook Page
 

September 2011 10B-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10B-3. Percent of Fish Meals Prepared Using Various Cooking Methods by Ethnicity 

Ethnicity Black Native American Hispanic White Other 

Total Fish 

Cooking Method 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Don't Know 

Total (N) 

40.5 

27.0 

0 

19.4 

1.9 

9.5 

1.6 

0 

52 

37.5 

22.0 

1.1 

9.8 

16.3 

6.2 

4.2 

0 

84 

16.1 

83.9 

0 

0 

0 

0 

3.5 

0.3 

12 

35.8 

22.7 

4.3 

17.7 

11.7 

4.5 

2.7 

0.4 

1,744 

18.5 

18.4 

0 

57.6 

5.4 

0 

4.0 

0 

33 

Sport Fish 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Total (N) 

44.9 

36.2 

0 

0 

5.3 

13.6 

0 

19 

47.9 

20.2 

0 

1.5 

18.2 

8.6 

3.6 

60 

52.1 

47.9 

0 

0 

0 

0 

0 

4 

48.8 

15.7 

2.7 

14.7 

8.6 

5.6 

3.7 

39 

22.0 

9.6 

0 

61.9 

6.4 

0 

0 

0 

N = Total number of respondents. 

Source: West et al. (1993). 

Page Exposure Factors Handbook 

10B-4 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10B-4. Percent of Fish Meals Prepared Using Various Cooking Methods by Education 

Ethnicity Through Some H.S. H.S. Degree College Degree Post-Graduate 

Education 

Total Fish 

Cooking Method 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Don't Know 

Total (N) 

44.7 

23.6 

2.2 

8.9 

8.1 

10.0 

2.1 

0.5 

236 

41.8 

23.6 

2.8 

10.9 

12.1 

5.1 

3.4 

0.3 

775 

28.8 

23.8 

5.1 

23.8 

11.6 

3.0 

4.0 

0 

704 

22.9 

19.4 

5.8 

34.1 

12.8 

3.8 

1.3 

0 

211 

Sport Fish 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Total (N) 

56.1 

13.6 

2.8 

6.3 

7.4 

10.1 

2.8 

0.8 

146 

52.4 

15.8 

2.4 

9.4 

10.6 

6.3 

3.3 

0 

524 

41.8 

18.6 

3.0 

21.7 

6.1 

3.9 

4.6 

0 

421 

36.3 

12.9 

0 

28.3 

14.9 

6.5 

1.0 

0 

91 

N = Total number of respondents. 

Source: West et al. (1993). 

Exposure Factors Handbook Page
 

September 2011 10B-5 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10B-5. Percent of Fish Meals Prepared Using Various Cooking Methods by Income 

Ethnicity 0–$24,999 $25,000–$39,999 $40,000–or more 

Total Fish 

Cooking Method 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Don't Know 

Total (N) 

44.8 

21.7 

2.1 

11.3 

9.1 

8.7 

2.4 

0 

544 

39.1 

22.2 

3.5 

15.8 

12.3 

2.9 

4.0 

0.2 

518 

26.5 

23.4 

5.6 

25.0 

13.3 

2.5 

3.5 

0.3 

714 

Sport Fish 

Pan Fried 

Deep Fried 

Boiled 

Grilled/Broiled 

Baked 

Combination 

Other (Smoked, etc.) 

Total (N) 

51.5 

15.8 

1.8 

12.0 

7.2 

9.1 

2.7 

0 

387 

51.4 

15.8 

2.1 

12.2 

10.0 

3.8 

4.6 

0 

344 

42.0 

17.2 

3.7 

19.4 

10.0 

3.5 

3.8 

0.3 

369 

N = Total number of respondents. 

Source: West et al. (1993). 

Page Exposure Factors Handbook 

10B-6 September 2011 
 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

Table 10B-6. Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by Demographic 

Variables 

Total Fish Sport Fish 

Population Trimmed Fat (%) Skin Off (%) Trimmed Fat (%) Skin Off (%) 

Total Fish 

Residence Size 

Large City/Suburb 

Small City 

Town 

Small Town 

Rural Non-Farm 

Farm 

Age (years) 

17–30 

31–40 

41–50 

51–65 

Over 65 

Ethnicity 

Black 

Native American 

Hispanic 

White 

Other 

Education 

Some High School 

High School Degree 

College Degree 

Post-Graduate 

Income 

<$25,000 

$25,000–$39,999 

$40,000 or more 

Overall 

51.7 

56.9 

50.3 

52.6 

42.4 

37.3 

50.6 

49.7 

53.0 

48.1 

41.6 

25.8 

50.0 

59.5 

49.3 

77.1 

50.8 

47.2 

51.9 

47.6 

50.5 

47.8 

50.2 

49.0 

31.6 

34.1 

33.4 

45.2 

32.4 

38.1 

36.5 

29.7 

32.2 

35.6 

43.1 

37.1 

41.4 

7.1 

34.0 

61.6 

43.9 

37.1 

31.9 

26.6 

43.8 

34.0 

28.6 

34.7 

56.7 

59.3 

51.7 

55.8 

46.2 

39.4 

53.9 

51.6 

58.8 

48.8 

43.0 

16.0 

56.3 

50.0 

51.8 

75.7 

49.7 

49.5 

55.9 

53.4 

50.6 

54.9 

51.7 

52.1 

28.9 

36.2 

33.7 

51.3 

34.6 

42.1 

39.3 

29.9 

37.0 

37.2 

42.9 

40.1 

36.7 

23.0 

35.6 

65.5 

47.1 

37.6 

33.8 

38.7 

47.3 

34.6 

27.7 

36.5 

Source: Modified from West et al. (1993). 

Exposure Factors Handbook Page
 

September 2011 10B-7 
 

 

 

Table 10B-7. Method of Cooking of Most Common Species Kept by Sportfishermen 

Use as Primary Cooking Method (%) Percent of Anglers Species Deep Fried Pan Fry Bake and Charcoal Raw Other

b 

Catching Species Broil 

White Croaker 34 19 64 12 0 5 

Pacific Mackerel 25 10 41 28 0 21 

Pacific Bonito 18 5 33 43 2 17 

Queenfish 17 15 70 6 1 8 

Jacksmelt 13 17 57 19 0 7 

Walleye Perch 10 12 69 6 0 13 

Shiner Perch 7 11 72 8 0 11 

Opaleye 6 16 56 14 0 14 

Black Perch 5 18 53 14 0 15 

Kelp Bass 5 12 55 21 0 12 

California Halibut 4 13 60 24 0 3 

Shellfisha 3 0 0 0 0 100 a Crab, mussels, lobster, abalone. b Boil, soup, steam, stew. 

N = 1,059. 

Source: Modified from Puffer et al. (1982). 

 

Table 10B-8. Adult Consumption of Fish Parts 

Number Species Consuming 

Salmon 473 95.1 55.8 42.7 42.8 12.1 3.7 

Lamprey 249 86.4 89.3 18.1 4.6 5.2 3.2 

Trout 365 89.4 68.5 13.7 8.7 7.1 2.3 

Smelt 209 78.8 88.9 37.4 46.4 28.4 27.9 

Whitefish 125 93.8 53.8 15.4 20.6 6.0 0.0 

Sturgeon 121 94.6 18.2 6.2 11.9 2.6 0.3 

Walleye 46 100 20.7 6.2 9.8 2.4 0.9 

Squawfish 15 89.7 34.1 8.1 11.1 5.9 0.0 

Sucker 42 89.3 50.0 19.4 30.4 9.8 2.1 

Shad 16 93.5 15.7 0.0 0.0 3.3 0.0 

Source: CRITFC (1994). 

Weighted Percent Consuming Specific Parts 

Fillet Skin Head Eggs Bones Organs 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 10—Intake of Fish and Shellfish 

10B.1. REFERENCES FOR APPENDIX 10B 

CRITFC (Columbia River Inter-Tribal Fish 

Commission). (1994). A fish consumption 

survey of the Umatilla, Nez Perce, Yakama, 

and Warm Springs Tribes of the Columbia 

River Basin. 

Puffer, HW; Azen, SP; Duda, MJ; Young, DR. 

(1982). Consumption rates of potentially 

hazardous marine fish caught in the 

metropolitan Los Angeles area. (EPA-600/3­

82-070). Los Angeles: University of 

Southern California. 

West, PC; Fly, JM; Marans, R; Larkin, F; Rosenblatt, 

D. (1993). 1991-1992 Michigan sport 

anglers fish consumption study. Ann Arbor, 

MI: Michigan Department of Natural 

Resources. 

Page Exposure Factors Handbook 

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Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

11.	 INTAKE OF MEATS, DAIRY 

PRODUCTS, AND FATS 

11.1. INTRODUCTION 

The American food supply is generally 

considered to be one of the safest in the world. 

Nevertheless, meats, dairy products, and fats may 

become contaminated with toxic chemicals by 

several pathways. These foods sources can become 

contaminated if animals are exposed to contaminated 

media (i.e., soil, water, or feed crops). To assess 

exposure through this pathway, information on meat, 

dairy, and fat ingestion rates are needed. 

A variety of terms may be used to define intake of 

meats, dairy products, and fats (e.g., consumer-only 

intake, per capita intake, total meat, dairy product, or 

fat intake, as-consumed intake, uncooked edible 

portion intake, dry-weight intake). As described in 

Chapter 9, Intake of Fruits and Vegetables, 

consumer-only intake is defined as the quantity of 

meats, dairy products, or fats consumed by 

individuals during the survey period averaged across 

only the individuals who consumed these food items 

during the survey period. Per capita intake rates are 

generated by averaging consumer-only intakes over 

the entire population In general, per capita intake 

rates are appropriate for use in exposure assessment 

for which average dose estimates are of interest 

because they represent both individuals who ate the 

foods during the survey period and individuals who 

may eat the food items at some time, but did not 

consume them during the survey period. Per capita 

intake, therefore, represents an average across the 

entire population of interest, but does so at the 

expense of underestimating consumption for the 

subset of the population that consumes the food in 

question. Total intake refers to the sum of all meats, 

dairy products, or fats consumed in a day. 

Intake rates may be expressed on the basis of the 

as-consumed weight (e.g., cooked or prepared) or on 

the uncooked or unprepared weight. As-consumed 

intake rates are based on the weight of the food in the 

form that it is consumed and should be used in 

assessments where the basis for the contaminant 

concentrations in foods is also indexed to the 

as-consumed weight. Some of the food ingestion 

values provided in this chapter are expressed as 

as-consumed intake rates because this is the fashion 

in which data were reported by survey respondents. 

Others are provided as uncooked weights based on 

analyses of survey data that account for weight 

changes that occur during cooking. This is of 

importance because concentration data to be used in 

the dose equation are often measured in uncooked 

food samples. It should be recognized that cooking 

can either increase or decrease food weight. 

Similarly, cooking can increase the mass of 

contaminant in food (due to formation reactions, or 

absorption from cooking oils or water) or decrease 

the mass of contaminant in food (due to vaporization, 

fat loss, or leaching). The combined effects of 

changes in weight and changes in contaminant mass 

can result in either an increase or decrease in 

contaminant concentration in cooked food. Therefore, 

if the as-consumed ingestion rate and the uncooked 

concentration are used in the dose equation, dose may 

be under-estimated or over-estimated. It is important 

for the assessor to be aware of these issues and 

choose intake rate data that best match the 

concentration data that are being used. For more 

information on cooking losses and conversions 

necessary to account for such losses, refer to 

Chapter 13 of this handbook. 

Sometimes contaminant concentrations in food 

are reported on a dry-weight basis. When these data 

are used in an exposure assessment, it is 

recommended that dry-weight intake rates also be 

used. Dry-weight food concentrations and intake 

rates are based on the weight of the food consumed 

after the moisture content has been removed. 

Similarly, when contaminant concentrations in food 

are reported on a lipid-weight basis, lipid-weight 

intake rates should be used. For information on 

converting the intake rates presented in this chapter 

to dry-weight or lipid-weight intake rates, refer to 

Sections 11.5 and 11.6 of this chapter. 

The purpose of this chapter is to provide intake 

data for meats, dairy products, and fats. The 

recommendations for ingestion rates of meats, dairy 

products, and fats are provided in the next section, 

along with a summary of the confidence ratings for 

these recommendations. The recommended values 

are based on the key study identified by 

U.S. Environmental Protection Agency (EPA) for this 

factor. Following the recommendations, the key study 

on ingestion of meats, dairy products, and fats are 

summarized. Relevant data on ingestion of meats, 

dairy products, and fats are also provided. These 

studies are presented to provide the reader with added 

perspective on the current state-of-knowledge 

pertaining to ingestion of meats, dairy products, and 

fats. 

11.2. RECOMMENDATIONS 

Table 11-1 presents a summary of the 

recommended values for per capita and 

consumer-only intake of meats, dairy products, and 

fats. Table 11-2 provides confidence ratings for these 

recommendations. 

Exposure Factors Handbook Page
 

September 2011 11-1
 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-2 September 2011 

U.S. EPA analyses of data from the 2003−2006 

National Health and Nutrition Examination Survey 

(NHANES) were used in selecting recommended 

intake rates for intake of meats and dairy products by 

the general population. The U.S. EPA analysis of 

meat and dairy products was conducted using 

childhood age groups that differed slightly from 

U.S. EPA’s Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

However, for the purposes of the recommendations 

for children presented here, data were placed in the 

standardized age categories closest to those used in 

the analysis. The U.S. EPA analysis of fat intake data 

from the U.S. Department of Agriculture’s (USDA’s) 

Continuing Survey of Food Intake by Individuals 

[CSFII, U.S. EPA (2007)] were used in selecting 

recommended intake rates for fats. This study used 

the childhood age groups recommended by U.S. EPA 

(2005). 

The NHANES data on which the

recommendations for meats and dairy products are 

based, and the CSFII data on which the 

recommendations for fats are based are short-term 

survey data and may not necessarily reflect the 

long-term distribution of average daily intake rates. 

However, since these broad categories of food (i.e., 

total meats and dairy products), are eaten on a daily 

basis throughout the year with minimal seasonality, 

the short term distribution may be a reasonable 

approximation of the long-term distribution, although 

it will display somewhat increased variability. This 

implies that the upper percentiles shown here will 

tend to overestimate the corresponding percentiles of 

the true long-term distribution. In general, the 

recommended values based on U.S. EPA’s analyses of 

NHANES data and CSFII data represent the 

uncooked weight of the edible portion of meat, dairy, 

and fats. It should be noted that because the 

recommendations for fat intake are based on 

1994−1996 and 1998 CSFII data, they may not 

reflect the most recent changes that may have 

occurred in consumption patterns. 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, Edible Portion, 

Uncooked 

Age Group 

(years) 

Per Capita Consumers Only Multiple 

Percentiles Mean 95 Source th Percentile Mean 95th Percentile 

g/kg-day g/kg-day g/kg-day g/kg-day 

Total Meata 

Birth to 1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <50 

≥50 

1.2 5.4b 2.7 8.1b 

See Table 11-3 

and Table 11-4 

U.S. EPA 

Analysis of 

NHANES 

2003−2006 

4.0 10.0b 4.1 10.1b 

4.0 10.0 b 4.1 10.1 b 

3.9 8.5 3.9 8.6 

2.8 6.4 2.8 6.4 

2.0 4.7 2.0 4.7 

2.0 4.7 2.0 4.7 

1.8 4.1 1.8 4.1 

1.4 3.1 1.4 3.1 

Total Dairy Products

a 

Birth to 1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 to <50 

≥50 

10.1 43.2b 11.7 44.7b 

See Table 11-3 

and Table 11-4 

U.S. EPA 

Analysis of 

NHANES 

2003−2006 

43.2 94.7b 43.2 94.7b 

43.2 94.7 b 43.2 94.7 b 

24.0 51.1 24.0 51.1 

12.9 31.8 12.9 31.8 

5.5 16.4 5.5 16.4 

5.5 16.4 5.5 16.4 

3.5 10.3 3.5 10.3 

3.3 9.6 3.3 9.6 

Individual Meat and Dairy Products―See Table 11-5 and Table 11-6 

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Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, Edible Portion, 

Uncooked (continued) 

Age Group 

Per Capita Consumers Only Multiple 

Percentiles Mean 95 Source th Percentile Mean 95th Percentile 

g/kg-day g/kg-day g/kg-day g/kg-day 

Total Fat 

Birth to <1 month 5.2 16 7.8 16 

See Table 

11-31 and 

Table 11-33 

U.S. EPA 

(2007) 

1 to <3 months 4.5 12 6.0 12 

3 to <6 months 4.1 8.2 4.4 8.3 

6 to <12 months 3.7 7.0 3.7 7.0 

1 to <2 years 4.0 7.1 4.0 7.1 

2 to <3 years 3.6 6.4 3.6 6.4 

3 to <6 years 3.4 5.8 3.4 5.8 

6 to <11 years 2.6 4.2 2.6 4.2 

11 to <16 years 1.6 3.0 1.6 3.0 

16 to <21 years 1.3 2.7 1.3 2.7 

21 to <31 years 1.2 2.3 1.2 2.3 

31 to <41 years 1.1 2.1 1.1 2.1 

41 to <51 years 1.0 1.9 1.0 1.9 

51 to <61 years 0.9 1.7 0.9 1.7 

61 to <71 years 0.9 1.7 0.9 1.7 

71 to <81 years 0.8 1.5 0.8 1.5 

≥81 years 0.9 1.5 0.9 1.5 a Analysis was conducted using slightly different childhood age groups than those recommended in Guidance on 

Selecting Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. 

EPA, 2005). Data were placed in the standardized age categories closest to those used in the analysis. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation 

and Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group 

Recommendations (NCHS, 1993). 

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Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-2. Confidence in Recommendations for Intake of Meats, Dairy Products, and Fats 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodology and data analysis were adequate. 

The surveys sampled approximately 16,000 for meats and 

dairy products and 20,000 individuals for fats. Analyses of 

primary data were conducted. 

No physical measurements were taken. The method relied 

on recent recall of meats and dairy products eaten. 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key studies were directly relevant to meat, dairy, and fat 

intake. 

The data were demographically representative of the U.S. 

population (based on stratified random sample). 

Data were collected between 2003 and 2006 for meat and 

dairy products and between 1994 and 1998 for fats. 

Data were collected for two non-consecutive days. 

High for meats and dairy 

products; medium for fats 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The NHANES and CSFII data are publicly available. 

The methodology used was clearly described; enough 

information was included to reproduce the results. 

NHANES and CSFII follow strict QA/QC procedures. 

U.S. EPA analysis of NHANES data has only been reviewed 

internally. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were provided for total meats, total dairy 

products, and total fats. Means were provided for 

individual meats and dairy products. 

Data collection was based on recall of consumption for a 

2-day period; the accuracy of using these data to estimate 

long-term intake (especially at the upper percentiles) is 

uncertain. However, use of short-term data to estimate 

chronic ingestion can be assumed for broad categories of 

foods such as total meats, total dairy products, and total fats. 

Uncertainty is likely to be greater for individual meats and 

dairy products. 

Medium to high for averages, 

low for long-term upper 

percentiles; low for individual 

foods 

Evaluation and Review 

Peer Review 

Number and Agreement of 

Studies 

Both the NCHS NHANES and the USDA CSFII survey 

received high levels of peer review. The U.S. EPA analysis 

of the NHANES data has not been peer reviewed outside 

the Agency, but methodology has been used in analysis of 

previous data. 

There was one key study for intake of meat and dairy 

products (2003−2006 NHANES) and 1 key study for fat 

intake [U.S. EPA (2007), based on 1994−1996, 1998 

CSFII]. 

Medium 

Overall Rating Medium to high confidence in 

the averages; Low confidence in 

the long-term upper percentiles 

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Chapter 11—Intake of Meats, Dairy Products, and Fats 

11.3.	 INTAKE OF MEAT AND DAIRY 

PRODUCTS 

11.3.1.	 Key Meat and Dairy Intake Studies 

11.3.1.1.	 U.S. EPA Analysis of Consumption Data 

From 2003−2006 National Health and 

Nutrition Examination Survey 

(NHANES) 

The key source of recent information on 

consumption rates of meat and dairy products is the 

U.S. Centers for Disease Control and Prevention’s 

(CDC) National Center for Health Statistics’ (NCHS) 

NHANES. Data from NHANES have been used by 

the U.S. EPA, Office of Pesticide Programs (OPP) to 

generate per capita and consumer-only intake rates 

for both individual meat and dairy products and total 

meat and dairy products. 

NHANES is designed to assess the health and 

nutritional status of adults and children in the United 

States. In 1999, the survey became a continuous 

program that interviews a nationally representative 

sample of approximately 7,000 persons each year and 

examines a nationally representative sample of about 

5,000 persons each year, located in counties across 

the country, 15 of which are visited each year. Data 

are released on a 2 year basis, thus, for example, the 

2003 data are combined with the 2004 data to 

produce NHANES 2003−2004. 

The dietary interview component of NHANES is 

called What We Eat in America and is conducted by 

the U.S. Department of Agriculture (USDA) and the 

U.S. Department of Health and Human Services 

(DHHS). DHHS’ NCHS is responsible for the sample 

design and data collection and USDA’s Food Surveys 

Research Group is responsible for the dietary data 

collection methodology, maintenance of the databases 

used to code and process the data, and data review 

and processing. Beginning in 2003, 

2 non-consecutive days of 24-hour intake data were 

collected. The first day is collected in-person, and the 

second day is collected by telephone 3 to 10 days 

later. These data are collected using USDA’s dietary 

data collection instrument, the Automated Multiple 

Pass Method. This method provides an efficient and 

accurate means of collecting intakes for large-scale 

national surveys. It is fully computerized and uses a 

5-step interview. Details can be found at USDA’s 

Agriculture Research Service 

(http://www.ars.usda.gov/ba/bhnrc/fsrg). 

For NHANES 2003−2004, there were 

12,761 persons selected; of these, 9,643 were 

considered respondents to the mobile examination 

center (MEC) examination and data collection. 

However, only 9,034 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,354 provided complete dietary intakes for Day 2. 

For NHANES 2005−2006, there were 12,862 persons 

selected; of these 9,950 were considered respondents 

to the MEC examination and data collection. 

However, only 9,349 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,429 provided complete dietary intakes for Day 2. 

The 2003−2006 NHANES surveys are stratified, 

multistage probability samples of the civilian noninstitutionalized U.S. population. The sampling frame 

was organized using 2000 U.S. population census 

estimates. NHANES oversamples low income 

persons, adolescents 12 to 19 years, persons 60 years 

and older, African Americans, and Mexican 

Americans. Several sets of sampling weights are 

available for use with the intake data. By using 

appropriate weights, data for all 4 years of the 

surveys can be combined. Additional information on 

NHANES can be obtained at 

http://www.cdc.gov/nchs/nhanes.htm. 

In 2010, OPP used NHANES 2003−2006 data to 

update the Food Commodity Intake Database (FCID) 

that was developed in earlier analyses of data from 

the U.S. Department of Agriculture’s (USDA’s) 

CSFII (U.S. EPA, 2000; USDA, 2000) (see 

Section 11.3.2.3), NHANES data on the foods people 

reported eating were converted to the quantities of 

agricultural commodities eaten. “Agricultural 

commodity” is a term used by U.S. EPA to mean 

plant (or animal) parts consumed by humans as food; 

when such items are raw or unprocessed, they are 

referred to as “raw agricultural commodities.” For 

example, beef stew may contain the commodities 

beef, potatoes, carrots, and other vegetables. FCID 

contains approximately 558 unique commodity 

names and 8-digit codes. The FCID commodity 

names and codes were selected and defined by 

U.S. EPA and were based on the U.S. EPA Food 

Commodity Vocabulary 

(http://www.epa.gov/pesticides/foodfeed/). 

Intake rates were generated for a variety of food 

items/groups based on the agricultural commodities 

included in the FCID. These intake rates represent 

intake of all forms of the product (e.g., both home 

produced and commercially produced) for individuals 

who provided data for 2 days of the survey. Note that 

if the person reported consuming food for only one 

day, their 2-day average would be half the amount 

reported for the one day of consumption. Individuals 

who did not provide information on body weight or 

for whom identifying information was unavailable 

were excluded from the analysis. Two-day average 

intake rates were calculated for all individuals in the 

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Chapter 11—Intake of Meats, Dairy Products, and Fats 

database for each of the food items/groups. These 

average daily intake rates were divided by each 

individual's reported body weight to generate intake 

rates in units of grams per kilogram of body weight 

per day (g/kg-day). The data were weighted 

according to the 4-year, 2-day sample weights 

provided in NHANES 2003−2006 to adjust the data 

for the sample population to reflect the national 

population. Summary statistics were generated on a 

consumer-only and on a per capita basis. Summary 

statistics, including number of observations, 

percentage of the population consuming the meats 

and dairy products being analyzed, mean intake rate, 

and standard error of the mean intake rate were 

calculated for total meats, total dairy products, and 

selected individual meats and dairy products. 

Percentiles of the intake rate distribution (i.e., 1st, 5th, 

10th, 25th, 50th, 75th, 90th, 95th, 99th, and the maximum 

value) were also provided for total meats and dairy 

products. Data were provided for the following age 

groups: birth to 1 year, 1 to 2 years, 3 to 5 years, 6 to 

12 years, 13 to 19 years, 20 to 49 years, and 

≥50 years. Data on females 13 to 49 years were also 

provided. Because these data were developed for use 

in U.S. EPA’s pesticide registration program, the 

childhood age groups used are slightly different than 

those recommended in U.S. EPA’s Guidance on 

Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005). 

Table 11-3 presents per capita intake data for total 

meats and dairy products in g/kg-day; Table 11-4 

provides consumer-only intake data for total meats 

and total dairy products in g/kg-day. Table 11-5 

provides per capita intake data for individual meats 

and dairy products, and Table 11-6 provides 

consumer-only intake data for individual meats and 

dairy products. In general, these data represent intake 

of the edible portions of uncooked foods. 

The results are presented in units of g/kg-day. 

Thus, the use of these data in calculating potential 

dose does not require the body-weight factor to be 

included in the denominator of the average daily dose 

(ADD) equation. It should be noted that converting 

these intake rates into units of g/day by multiplying 

by a single average body weight is inappropriate 

because individual intake rates were indexed to the 

reported body weights of the survey respondents. 

Also, it should be noted that the distribution of 

average daily intake rates generated using short-term 

data (e.g., 2-day) do not necessarily reflect the 

long-term distribution of average daily intake rates. 

The distributions generated from short-term and 

long-term data will differ to the extent that each 

individual’s intake varies from day to day; the 

distributions will be similar to the extent that 

individuals’ intakes are constant from day to day. 

However, for broad categories of foods (e.g., total 

meats and total dairy) that are eaten on a daily basis 

throughout the year, the short-term distribution may 

be a reasonable approximation of the true long-term 

distribution, although it will show somewhat more 

variability. In this chapter, distributions are provided 

only for broad categories of meats and dairy (i.e., 

total meats and total dairy). Because of the increased 

variability of the short-term distribution, the 

short-term upper percentiles shown here may 

overestimate the corresponding percentiles of the 

long-term distribution. For individual foods, only the 

mean, standard error, and percent consuming are 

provided. 

An advantage of using the U.S. EPA’s analysis of 

NHANES data is that it provides distributions of 

intake rates for various age groups of children and 

adults, normalized by body weight. The data set was 

designed to be representative of the U.S. population 

and includes 4 years of intake data combined. 

Another advantage is the currency of the data; the 

NHANES data are from 2003−2006. However, 

short-term dietary data may not accurately reflect 

long-term eating patterns and may under-represent 

infrequent consumers of a given food. This is 

particularly true for the tails (extremes) of the 

distribution of food intake. Because these are 2-day 

averages, consumption estimates at the upper end of 

the intake distribution may be underestimated if these 

consumption values are used to assess acute (i.e., 

short-term) exposures. Also, the analysis was 

conducted using slightly different childhood age 

groups than those recommended in U.S. EPA’s 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

However, given the similarities in the age groups 

used, the data should provide suitable intake 

estimates for the age groups of interest. 

11.3.2. Relevant Meat and Dairy Intake Studies 

11.3.2.1.	 USDA (1996a, b, 1993, 1980)―Food and 

Nutrient Intakes of Individuals in 1 Day 

in the United States 

USDA calculated mean per capita intake rates for 

meat and dairy products using Nationwide Food 

Consumption Survey (NFCS) data from 1977−1978 

and 1987−1988 (USDA, 1993, 1980) and CSFII data 

from 1994 and 1995 (USDA, 1996a, b). The mean 

per capita intake rates for meat are presented in Table 

11-7 through Table 11-9 based on intake data for 

1 day from the 1977−1978 (see Table 11-7) and 

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1987−1988 NFCSs (see Table 11-8), and 1994 and 

1995 CSFII (see Table 11-9). Table 11-10 through 

Table 11-12 present similar data for dairy products. 

Note that the age classifications used in the later 

surveys were slightly different than those used in the 

1977−1978 NFCS. 

The advantages of using these data are that they 

provide mean intake estimates for all meat, poultry, 

and dairy products. The consumption estimates are 

based on short-term (i.e., 1-day) dietary data, which 

may not reflect long-term consumption. These data 

are based on older surveys and may not be entirely 

representative of current eating patterns. 

11.3.2.2.	 USDA (1999a)―Food and Nutrient 

Intakes by Children 1994−1996, 1998, 

Table Set 17 

USDA (1999a) calculated national probability 

estimates of food and nutrient intake by children 

based on 4 years of the CSFII (1994−1996 and 1998) 

for children age 9 years and under and on CSFII 

1994−1996 only for individuals age 10 years and 

over. The CSFII was a series of surveys designed to 

measure the kinds and amounts of foods eaten by 

Americans. Intake data, based on 24-hour dietary 

recall, were collected through in-person interviews on 

2 non-consecutive days. Section 11.3.2.3 provides 

additional information on these surveys. 

USDA (1999a) used sample weights to adjust for 

non-response, to match the sample to the U.S. 

population in terms of demographic characteristics, 

and to equalize intakes over the 4 quarters of the year 

and the 7 days of the week. A total of 503 breast-fed 

children were excluded from the estimates, but both 

consumers and non-consumers were included in the 

analysis. 

USDA (1999a) provided data on the mean per 

capita quantities (grams) of various food 

products/groups consumed per individual for 1 day, 

and the percent of individuals consuming those foods 

in 1 day of the survey. Table 11-13 and Table 11-14 

present data on the mean quantities (grams) of meat 

and eggs consumed per individual for 1 day, and the 

percentage of survey individuals consuming meats 

and eggs on that survey day. Table 11-15 and Table 

11-16 present similar data for dairy products. Data on 

mean intakes or mean percentages are based on 

respondents’ Day-1 intakes. 

The advantage of the USDA (1999a) study is that 

it uses the 1994−1996, 1998 CSFII data set, which 

includes 4 years of intake data, combined, and 

includes the supplemental data on children. These 

data are expected to be generally representative of the 

U.S. population, and they include data on a wide 

variety of meats and dairy products. The data set is 

one of a series of USDA data sets that are publicly 

available. One limitation of this data set is that it is 

based on 1 day, and short-term dietary data may not 

accurately reflect long-term eating patterns. Other 

limitations of this study are that it only provides 

mean values of food intake rates, consumption is not 

normalized by body weight, and presentation of 

results is not consistent with U.S. EPA’s 

recommended age groups. These data are based on 

older surveys and may not be entirely representative 

of current eating patterns. 

11.3.2.3.	 U.S. EPA Analysis of CSFII 1994−1996, 

1998 Based on USDA (2000) and 

U.S. EPA (2000) 

U.S. EPA/OPP, in cooperation with USDA’s 

Agricultural Research Service, used data from the 

1994−1996, 1998 CSFII to develop the FCID (U.S. 

EPA, 2000; USDA, 2000), as described in 

Section 11.3.1.1. The CSFII 1994−1996 was 

conducted between January 1994 and January 1997 

with a target population of non-institutionalized 

individuals in all 50 states and Washington, DC. In 

each of the 3 survey years, data were collected for a 

nationally representative sample of individuals of all 

ages. The CSFII 1998 was conducted between 

December 1997 and December 1998 and surveyed 

children 9 years of age and younger. It used the same 

sample design as the CSFII 1994−1996 and was 

intended to be merged with CSFII 1994−1996 to 

increase the sample size for children. The merged 

surveys are designated as CSFII 1994−1996, 1998 

(USDA, 2000). Additional information on the CSFII 

can be obtained at 

http://www.ars.usda.gov/Services/docs.htm?docid=14 

531. 

The CSFII 1994−1996, 1998 collected dietary 

intake data through in-person interviews on 

2 non-consecutive days. The data were based on 

24-hour recall. A total of 21,662 individuals provided 

data for the first day; of those individuals, 20,607 

provided data for a second day. The 2-day response 

rate for the 1994−1996 CSFII was approximately 

76%. The 2-day response rate for CSFII 1998 was 

82%. The CSFII 1994−1996, 1998 surveys were 

based on a complex multistage area probability 

sample design. The sampling frame was organized 

using 1990 U.S. population census estimates, and the 

stratification plan took into account geographic 

location, degree of urbanization, and socioeconomic 

characteristics. Several sets of sampling weights are 

available for use with the intake data. By using 

appropriate weights, data for all 4 years of the 

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surveys can be combined. USDA recommends that 

all 4 years be combined in order to provide an 

adequate sample size for children. 

The meats and dairy items/groups selected for the 

U.S. EPA analysis included total meats and total dairy 

products, and individual meats and dairy such as 

beef, pork, poultry, and eggs. CSFII data on the foods 

people reported eating were converted to the 

quantities of agricultural commodities eaten. Intake 

rates for these food items/groups were calculated, and 

summary statistics were generated on both a per 

capita and a consumer-only basis using the same 

general methodology as in the U.S. EPA analysis of 

2003−2006 NHANES data, as described in 

Section 11.3.1.1. Because these data were developed 

for use in U.S. EPA’s pesticide registration program, 

the childhood age groups used are slightly different 

than those recommended in U.S. EPA’s Guidance on 

Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005). 

Table 11-17 presents per capita intake data for 

total meat and total dairy products in g/kg-day; Table 

11-18 provides consumer-only intake data for total 

meat and total dairy products in g/kg-day. Table 

11-19 provides per capita intake data for certain 

individual meats and dairy products, and Table 11-20 

provides consumer-only intake data for these 

individual meats and dairy products. In general, these 

data represent intake of the edible portions of 

uncooked foods. 

The results are presented in units of g/kg-day. 

Thus, use of these data in calculating potential dose 

does not require the body-weight factor to be 

included in the denominator of the average daily dose 

equation. The cautions concerning converting these 

intake rates into units of g/day by multiplying by a 

single average body weight and the discussion of the 

use of short term data in the NHANES description in 

Section 11.3.1.1 apply to the CSFII estimates as well. 

A strength of U.S. EPA’s analysis is that it 

provides distributions of intake rates for various age 

groups, normalized by body weight. The analysis 

uses the 1994−1996, 1998 CSFII data set, which was 

designed to be representative of the U.S. population. 

The data set includes 4 years of intake data combined 

and is based on a 2-day survey period. As discussed 

above, short-term dietary data may not accurately 

reflect long-term eating patterns and may 

under-represent infrequent consumers of a given 

food. This is particularly true for the tails (extremes) 

of the distribution of food intake. Although the 

analysis as conducted used slightly different age 

groups than those recommended in U.S. EPA’s 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005), 

given the similarities in the age groups used, the data 

should provide suitable intake estimates for the 

childhood age groups of interest. While the CSFII 

data are older than the NHANES data, they provide 

relevant information on consumption by season, 

region of the United States, and urbanization, cohorts 

that are not available in the publicly released 

NHANES data. 

11.3.2.4.	 Smiciklas-Wright et al. (2002)―Foods 

Commonly Eaten in the United States: 

Quantities Consumed per Eating 

Occasion and in a Day, 1994−1996 

Using data gathered in the 1994−1996 USDA 

CSFII, Smiciklas-Wright et al. (2002) calculated 

distributions for the quantities of meat, poultry, and 

dairy products consumed per eating occasion by 

members of the U.S. population (i.e., serving sizes). 

The estimates of serving size are based on data 

obtained from 14,262 respondents, ages two years 

and above, who provided 2 days of dietary intake 

information. Only dietary intake data from users of 

the specified food were used in the analysis (i.e., 

consumer-only data). 

Table 11-21 presents serving size data for meats 

and dairy products. These data are presented on an 

as-consumed basis (grams) and represent the quantity 

of meats and dairy products consumed per eating 

occasion. These estimates may be useful for assessing 

acute exposures to contaminants in specific foods, or 

other assessments where the amount consumed per 

eating occasion is necessary. Only the mean and 

standard deviation serving size data and percent of 

the population consuming the food during the 2-day 

survey period are presented in this handbook. 

Percentiles of serving sizes of the foods consumed by 

these age groups of the U.S. population can be found 

in Smiciklas-Wright et al. (2002). 

The advantages of using these data are that they 

were derived from the USDA CSFII and are 

representative of the U.S. population. The analysis 

conducted by Smiciklas-Wright et al. (2002) 

accounted for individual foods consumed as 

ingredients of mixed foods. Mixed foods were 

disaggregated via recipe files so that the individual 

ingredients could be grouped together with similar 

foods that were reported separately. Thus, weights of 

foods consumed as ingredients were combined with 

weights of foods reported separately to provide a 

more thorough representation of consumption. 

However, it should be noted that since the recipes for 

the mixed foods consumed were not provided by the 

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Chapter 11—Intake of Meats, Dairy Products, and Fats 

respondents, standard recipes were used. As a result, 

the estimates of quantity consumed for some food 

types are based on assumptions about the types and 

quantities of ingredients consumed as part of mixed 

foods. This study used data from the 1994−1996 

CSFII; data from the 1998 children’s supplement 

were not included. 

11.3.2.5.	 Vitolins et al. (2002)―Quality of Diets 

Consumed by Older Rural Adults 

Vitolins et al. (2002) conducted a survey to 

evaluate the dietary intake, by food groups, of older 

(>70 years) rural adults. The sample consisted of 

130 community dwelling residents from two rural 

counties in North Carolina. Data on dietary intake 

over the preceding year were obtained in face-to-face 

interviews conducted in participants’ homes, or in a 

few cases, a senior center. The food frequency 

questionnaire used in the survey was a modified 

version of the National Cancer Institute Health Habits 

and History Questionnaire; this modified version 

included an expanded food list containing a greater 

number of ethnic foods than the original food 

frequency form. Demographic and personal data 

collected included sex, ethnicity, age, education, 

denture use, marital status, chronic disease, and 

weight. 

Food items reported in the survey were grouped 

into food groups similar to the USDA Food Guide 

Pyramid and the National Cancer Institute’s 5 A Day 

for Better Health program. These groups are: (1) 

fruits and vegetables; (2) bread, cereal, rice, and 

pasta; (3) milk, yogurt, and cheese; (4) meat, fish, 

poultry, beans, and eggs; and (5) fats, oils, sweets, 

and snacks. Medians, ranges, frequencies, and 

percentages were used to summarize intake of each 

food group, broken down by demographic and health 

characteristics. In addition, multiple regression 

models were used to determine which demographic 

and health factors were jointly predictive of intake of 

each of the five food groups. 

Thirty-four percent of the survey participants 

were African American, 36% were European 

American, and 30% were Native American. 

Sixty-two percent were female, 62% were not 

married at the time of the interview, and 65% had 

some high school education or were high school 

graduates. Almost all of the participants (95%) had 

one or more chronic diseases. Sixty percent of the 

respondents were between 70 and 79 years of age; the 

median age was 78 years old. Table 11-22 presents 

the median servings of milk, yogurt, and cheese 

broken down by demographic and health 

characteristics. None of the demographic 

characteristics were significantly associated with 

milk intake, and only ethnicity was found to be 

borderline (p = 0.13). In addition, none of the 

demographic characteristics were jointly predictive of 

milk, yogurt, and cheese consumption. 

One limitation of the study, as noted by the study 

authors, is that the study did not collect information 

on the length of time the participants had been 

practicing the dietary behaviors reported in the 

survey. The questionnaire asked participants to report 

the frequency of food consumption during the past 

year. The study authors noted that, currently, there are 

no dietary assessment tools that allow the collection 

of comprehensive dietary data over years of food 

consumption. Another limitation of the study is the 

small sample size used, which makes associations by 

sex and ethnicity difficult. 

11.3.2.6.	 Fox et al. (2004)―Feeding Infants and 

Toddlers Study: What Foods Are Infants 

and Toddlers Eating 

Fox et al. (2004) used data from the Feeding 

Infants and Toddlers study (FITS) to assess food 

consumption patterns in infants and toddlers. The 

FITS was sponsored by Gerber Products Company 

and was conducted to obtain current information on 

food and nutrient intakes of children, ages 4 to 

24 months old, in the 50 states and the District of 

Columbia. The FITS is described in detail in 

Devaney et al. (2004). FITS was based on a random 

sample of 3,022 infants and toddlers for which 

dietary intake data were collected by telephone from 

their parents or caregivers between March and July 

2002. An initial recruitment and household interview 

was conducted, followed by an interview to obtain 

information on intake based on 24-hour recall. The 

interview also addressed growth, development, and 

feeding patterns. A second dietary recall interview 

was conducted for a subset of 703 randomly selected 

respondents. The study over-sampled children in the 

4 to 6 and 9 to 11-months age groups; sample weights 

were adjusted for non-response, over-sampling, and 

under-coverage of some subgroups. The response rate 

for the FITS was 73% for the recruitment interview. 

Of the recruited households, there was a response rate 

of 94% for the dietary recall interviews (Devaney et 

al., 2004). Table 11-23 shows the characteristics of 

the FITS study population. 

Fox et al. (2004) analyzed the first set of 24-hour 

recall data collected from all study participants. For 

this analysis, children were grouped into six age 

categories: 4 to 6 months, 7 to 8 months, 9 to 

11 months, 12 to 14 months, 15 to 18 months, and 19 

to 24 months. Table 11-24 provides the percentage of 

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infants and toddlers consuming milk, meats, or other 

protein sources at least once in a day. The percentage 

of children consuming any type of meat or protein 

source ranged from 14.2% for 4 to 6-month olds to 

97.2% for 19 to 24-month olds (see Table 11-24). 

The advantages of this study are that the study 

population represented the U.S. population and the 

sample size was large. One limitation of the analysis 

done by Fox et al. (2004) was that only frequency 

data were provided; no information on actual intake 

rates was included. In addition, Devaney et al. (2004) 

noted several limitations associated with the FITS 

data. For the FITS, a commercial list of infants and 

toddlers was used to obtain the sample used in the 

study. Since many of the households could not be 

located and did not have children in the target 

population, a lower response rate than would have 

occurred in a true national sample was obtained 

(Devaney et al., 2004). In addition, the sample was 

likely from a higher socioeconomic status when 

compared with all U.S. infants in this age group (4 to 

24 months old), and the use of a telephone survey 

may have omitted lower-income households without 

telephones (Devaney et al., 2004). 

11.3.2.7.	 Ponza et al. (2004)―Nutrient Food 

Intakes and Food Choices of Infants and 

Toddlers Participating in WIC 

Ponza et al. (2004) conducted a study using 

selected data from FITS to assess feeding patterns, 

food choices, and nutrient intake of infants and 

toddlers participating in the Special Supplemental 

Nutrition Program for Women, Infants, and Children 

(WIC). Ponza et al. (2004) evaluated FITS data for 

the following age groups: 4 to 6 months (N = 862), 

7 to 11 months (N = 1,159), and 12 to 24 months 

(N = 996). Table 11-25 shows the total sample size 

described by WIC participants and non-participants. 

The foods consumed were analyzed by tabulating 

the percentage of infants who consumed specific 

foods/food groups per day (Ponza et al., 2004). 

Weighted data were used in all of the analyses used in 

the study (Ponza et al., 2004). Table 11-25 presents 

the demographic data for WIC participants and 

non-participants. Table 11-26 provides the food 

choices for infants and toddlers. In general, there was 

little difference in food choices among WIC 

participants and non-participants, except for 

consumption of yogurt by infants 7 to 11 months of 

age and toddlers 12 to 24 months of age (see Table 

11-26). Non-participants, 7 to 24 months of age, were 

more likely to eat yogurt than WIC participants 

(Ponza et al., 2004). 

An advantage of this study is that it had a 

relatively large sample size and was representative of 

the U.S. general population of infants and children. A 

limitation of the study is that intake values for foods 

were not provided. Other limitations are associated 

with the FITS data and are described previously in 

Section 11.3.2.6. 

11.3.2.8.	 Mennella et al. (2006)―Feeding Infants 

and Toddlers Study: The Types of Foods 

Fed to Hispanic Infants and Toddlers 

Mennella et al. (2006) investigated the types of 

food and beverages consumed by Hispanic infants 

and toddlers in comparison to the non-Hispanic 

infants and toddlers in the United States. The FITS 

2002 data for children between 4 and 24 months old 

were used for the study. The data represent a random 

sample of 371 Hispanic and 2,367 non-Hispanic 

infants and toddlers (Mennella et al., 2006). Mennella 

et al. (2006) grouped the infants as follows: 4 to 

5 months (N = 84 Hispanic; 538 non-Hispanic), 6 to 

11 months (N = 163 Hispanic; 1,228 non-Hispanic), 

and 12 to 24 months (N = 124 Hispanic; 

871 non-Hispanic) of age. 

Table 11-27 provides the percentages of Hispanic 

and non-Hispanic infants and toddlers consuming 

milk, meats, or other protein sources on a given day. 

In most instances, the percentages consuming the 

different types of meats and protein sources were 

similar (Mennella et al., 2006). 

The advantage of the study is that it provides 

information on food preferences for Hispanic and 

non-Hispanic infants and toddlers. A limitation is that 

the study did not provide food intake data, but 

provided frequency of use data instead. Other 

limitations are those noted previously in 

Section 11.3.2.6 for the FITS data. 

11.3.2.9.	 Fox et al. (2006)―Average Portion of 

Foods Commonly Eaten by Infants and 

Toddlers in the United States 

Fox et al. (2006) estimated average portion sizes 

consumed per eating occasion by children 4 to 

24 months of age who participated in the FITS. The 

FITS is a cross-sectional study designed to collect 

and analyze data on feeding practices, food 

consumption, and usual nutrient intake of U.S. 

infants and toddlers and is described in 

Section 11.3.2.6 of this chapter. It included a 

stratified random sample of 3,022 children between 4 

and 24 months of age. 

Using the 24-hour recall data, Fox et al. (2006) 

derived average portion sizes for six major food 

groups, including meats and other protein sources. 

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Average portion sizes for select individual foods 

within these major groups were also estimated. For 

this analysis, children were grouped into six age 

categories: 4 to 5 months, 6 to 8 months, 9 to 

11 months, 12 to 14 months, 15 to 18 months, and 19 

to 24 months. Table 11-28 and Table 11-29 present 

the average portion sizes of meats and dairy products 

for infants and toddlers, respectively. 

11.4. INTAKE OFFAT 

11.4.1. Key Fat Intake Study 

11.4.1.1.	 U.S. EPA (2007)―Analysis of Fat Intake 

Based on the U.S. Department of 

Agriculture’s 1994–1996, 1998 

Continuing Survey of Food Intakes by 

Individuals (CSFII) 

U.S. EPA conducted an analysis to evaluate the 

dietary intake of fats by individuals in the United 

States using data from the USDA’s 1994–1996, 1998 

CSFII (USDA, 2000). Intakes of CSFII foods were 

converted to U.S. EPA food commodity codes using 

data provided in U.S. EPA’s FCID (U.S. EPA, 2000). 

The FCID contains a “translation file” that was used 

to break down the USDA CSFII food codes into 

548 U.S. EPA commodity codes. The method used to 

translate USDA food codes into U.S. EPA commodity 

codes is discussed in detail in U.S. EPA (2000). 

Each of the 548 U.S. EPA commodity codes was 

assigned a value between zero and one that indicated 

the mass fraction of fat in that food item. For many 

sources of fat, a commodity code existed solely for 

the nutrient fat portion of the food. For example, beef 

is represented in the FCID database by 10 different 

commodity codes; several of these codes specifically 

exclude fat, and one code is described as “nutrient fat 

only.” In these cases, the fat fraction could be 

expressed as 0 or 1, as appropriate. Most animal food 

products and food oils were broken down in this way. 

The fat contents of other foods in the U.S. EPA 

commodity code list were determined using the 

USDA Nutrient Database for Standard Reference, 

Release 13 (USDA, 1999b). For each food item in the 

U.S. EPA code list, the best available match in the 

USDA Nutrient Database was used. If multiple 

values were available for different varieties of the 

same food item (e.g., green, white, and red grapes), a 

mean value was calculated. If multiple values were 

available for different cooking methods (i.e., fried vs. 

dry cooked), the method least likely to introduce 

other substances, such as oil or butter, was preferred. 

In some cases, not all of the items that fall under a 

given food commodity code could be assigned a fat 

content. For example, the food commodity code list 

identified “turkey, meat byproducts” as including 

gizzard, heart, neck, and tail. Fat contents could be 

determined only for the gizzard and heart. Because 

the relative amounts of the different items in the food 

commodity code were unknown, the mean fat content 

of these two items was assumed to be the best 

approximation of the fat content for the food code as 

a whole. 

The analysis was based on respondents who had 

provided body weights and who had completed both 

days of the 2-day survey process. These individuals 

were grouped according to various age categories. 

The mean, standard error, and a range of percentiles 

of fat intake were calculated for 12 food categories 

(i.e., all fats, animal fats, meat and meat products, 

beef, pork, poultry, organ meats, milk and dairy 

products, fish, oils, nuts/seeds/beans/legumes/tubers, 

and others) and 98 demographic cohorts. Fat intake 

was calculated as a 2-day average consumption 

across both survey days in units of grams per day and 

grams per kilogram of body weight per day for the 

whole survey population and for consumers only. 

A secondary objective of the study was to 

evaluate fat consumption patterns of individuals who 

consume high levels of animal fats. The entire data 

analysis was repeated for a subset of individuals who 

were identified as high consumers of animal fats. The 

selection of the high-consumption group was done 

for each age category individually, rather than on the 

whole population, because fat intake on a per bodyweight basis is heavily skewed towards young 

children, and an analysis across the entire American 

population was desired. For infants, the “less-than-1­

year-old” group was used instead of the smaller 

infant groups (<1 month, 1 to <3 months, etc.). 

Within each of the age categories, individuals that 

ranked at or above the 90th percentile of consumption 

of all animal fats on a per unit body-weight basis 

were identified. Because of the sample weighting 

factors, the high consumer group was not necessarily 

10% of each age group. The selected individuals 

made up a survey population of 2,134 individuals. 

Fat intake of individuals in this group was calculated 

in g/day and g/kg-day for the whole population (i.e., 

per capita) and for consumers only. 

The analysis presented in U.S. EPA (2007) was 

conducted before U.S. EPA published the guidance 

entitled Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

Therefore, the age groups used for children in 

U.S. EPA (2007) were not entirely consistent with the 

age groups recommended in the 2005 guidance. A 

re-analysis of the some of the data was conducted to 

conform with U.S. EPA’s recommended age groups 

for children. The results of this re-analysis are 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

included in Table 11-30 through Table 11-35 for all 

individuals. Only intake rates of all fats are provided 

in these tables; refer to U.S. EPA (2007) for fat intake 

rates from individual food sources. Table 11-30 and 

Table 11-31 present intake rates of all fats for the 

whole population (i.e., per capita) in g/day and 

g/kg-day, respectively. Table 11-32 and Table 11-33 

present intake rates of all fats for consumers only in 

g/day and g/kg-day, respectively. Fat intake rates of 

all fats for the top decile of animal fat consumers 

from the consumers only group are presented in Table 

11-34 in g/day and in Table 11-35 in g/kg-day (per 

capita total fat intake rates for the top decile of 

animal fat consumers are not provided because they 

are the same as those for consumers only). 

11.4.2.	 Relevant Fat Intake Studies 

11.4.2.1.	 Cresanta et al. (1988)/Nicklas et al. 

(1993)/Frank et al. (1986)―Bogalusa 

Heart Study 

Cresanta et al. (1988), Nicklas et al. (1993), and 

Frank et al. (1986) analyzed dietary fat intake data as 

part of the Bogalusa heart study. The Bogalusa study, 

an epidemiologic investigation of cardiovascular 

risk-factor variables and environmental determinants, 

collected dietary data on subjects residing in 

Bogalusa, LA, beginning in 1973. Among other 

research, the study collected fat intake data for 

children, adolescents, and young adults. Researchers 

examined various cohorts of subjects, including (1) 

six cohorts of 10-year olds, (2) two cohorts of 

13-year olds, (3) one cohort of subjects from 

6 months to 4 years of age, and (4) one cohort of 

subjects from 10 to 17 years of age (Nicklas, 1995). 

To collect the data, interviewers used the 24-hour 

dietary recall method. According to Nicklas (1995), 

“the diets of children in the Bogalusa study are 

similar to those reported in national studies of 

children.” Thus, these data are useful in evaluating 

the variability of fat intake among the general 

population. Table 11-36 and Table 11-37 present data 

for 6-month-old to 17-year-old individuals collected 

during 1973 to 1982 (Frank et al., 1986). Data are 

presented for total fats, animal fats, vegetable fats, 

and fish fats in units of g/day (see Table 11-36) and 

g/kg-day (see Table 11-37). 

11.5.	 CONVERSION BETWEEN WET- AND 

DRY-WEIGHT INTAKE RATES 

The intake rates presented in this chapter are 

reported in units of wet weight (i.e., as-consumed or 

uncooked weight of meats and dairy products 

consumed per day or per eating occasion). However, 

data on the concentration of contaminants in meats 

and dairy products may be reported in units of either 

wet or dry weight (e.g., mg contaminant per gram 

dry-weight of meats and dairy products). It is 

essential that exposure assessors be aware of this 

difference so that they may ensure consistency 

between the units used for intake rates and those used 

for concentration data (i.e., if the contaminant 

concentration is measured in dry weight of meats and 

dairy products, then the dry-weight units should be 

used for their intake values). 

If necessary, wet weight (e.g., as-consumed) 

intake rates may be converted to dry-weight intake 

rates using the moisture content percentages 

presented in Table 11-38 and the following equation: 

100 −W  IRdw = IRww (Eqn. 11-1) 

 100 

where: 

IRdw = dry-weight intake rate, 

IRww = wet-weight intake rate, and 

W = percent water content. 

Alternatively, dry-weight residue levels in meat 

and dairy products may be converted to wet-weight 

residue levels for use with wet-weight (e.g., 

as-consumed) intake rates as follows: 

C 100 −W  ww = Cdw (Eqn. 11-2) 

 100 

where: 

Cww = wet-weight concentration, 

Cdw = dry-weight concentration, and 

W = percent water content. 

The moisture content data presented in Table 

11-38 are for selected meats and dairy products taken 

from USDA (2007). 

11.6.	 CONVERSION BETWEEN 

WET-WEIGHT AND LIPID-WEIGHT 

INTAKE RATES 

In some cases, the residue levels of contaminants 

in meat and dairy products may be reported as the 

concentration of contaminant per gram of fat. This 

may be particularly true for lipophilic compounds. 

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When using these residue levels, the assessor should 

ensure consistency in the exposure assessment 

calculations by using consumption rates that are 

based on the amount of lipids consumed for the meat 

or dairy product of interest. 

If necessary, wet-weight (e.g., as-consumed) 

intake rates may be converted to lipid-weight intake 

rates using the fat content percentages presented in 

Table 11-38 and the following equation: 

IR  L  lw = IR ww (Eqn. 11-3)   100

where: 

IRlw = lipid-weight intake rate,
 

IRww = wet-weight intake rate, and
 

L = percent lipid (fat) content.
 

Alternately, wet-weight residue levels in meat and 

dairy products may be estimated by multiplying the 

levels based on fat by the fraction of fat per product 

as follows: 

C = C  L  ww lw (Eqn. 11-4)   100

where: 

Cww = wet-weight concentration,
 

Clw = lipid-weight concentration, and
 

L = percent lipid (fat) content.
 

The resulting residue levels may then be used in 

conjunction with wet-weight (e.g., as-consumed) 

consumption rates. Table 11-38 presents the total fat 

content data for selected meat and dairy products 

taken from USDA (2007). 

11.7. REFERENCES FOR CHAPTER 11 

Cresanta, JL; Farris, RP; Croft, JB; Webber, LS; 

Frank, GC; Berenson, GS. (1988). Trends in 

fatty acid intakes of 10-year-old children, 

1973 to 1982. J Am Diet Assoc 88: 178-184. 

Devaney, B; Kalb, L; Briefel, R; Zavitsky-Novak, T; 

Clusen, N; Ziegler, P. (2004). Feeding 

infants and toddlers study: overview of the 

study design. J Am Diet Assoc 104: s8-13. 

http://dx.doi.org/10.1016/j.jada.2003.10.023. 

Fox, MK; Pac, S; Devaney, B; Jankowski, L. (2004). 

Feeding infants and toddlers study: What 

foods are infants and toddlers eating? J Am 

Diet Assoc 104: s22-s30. 

http://dx.doi.org/10.1016/j.jada.2003.10.026. 

Fox, MK; Reidy, K; Karwe, V; Ziegler, P. (2006). 

Average portions of foods commonly eaten 

by infants and toddlers in the United States. 

J Am Diet Assoc 106: S66-S76. 

http://dx.doi.org/10.1016/j.jada.2005.09.042. 

Frank, GC; Webber, LS; Farris, RP; Berenson, GS. 

(1986). Dietary databook: Quantifying 

dietary intakes of infants, children, and 

adolescents, the Bogalusa heart study, 

19731983. New Orleans, LA: National 

Research and Demonstration Center ­

Arteriosclerosis, Louisiana State University 

Medical Center. 

Mennella, JA; Ziegler, P; Briefel, R; Novak, T. 

(2006). Feeding Infants and Toddlers Study: 

the types of foods fed to Hispanic infants 

and toddlers. J Am Diet Assoc 106: S96­

106. 

http://dx.doi.org/10.1016/j.jada.2005.09.038. 

NCHS (National Center for Health Statistics). (1993). 

Joint policy on variance estimation and 

statistical reporting standards on NHANES 

III and CSFII reports: HNIS/NCHS Analytic 

Working Group recommendations.

Riverdale, MD: Human Nutrition

Information Service (HNIS)/Analytic 

Working Group. Agricultural Research 

Service, Survey Systems/Food Consumption 

Laboratory. 

Nicklas, TA. (1995). Dietary studies of children: the 

Bogalusa Heart Study experience. J Am Diet 

Assoc 95: 1127-1133. 

http://dx.doi.org/10.1016/S0002­

8223(95)00305-3. 

Nicklas, TA; Webber, LS; Srinivasan, SR; Berenson, 

GS. (1993). Secular trends in dietary intakes 

and cardiovascular risk factors of 10-y-old 

children: the Bogalusa Heart Study (1973­

1988). Am J Clin Nutr 57: 930-937. 

Ponza, M; Devaney, B; Ziegler, P; Reidy, K; 

Squatrito, C. (2004). Nutrient intakes and 

food choices of infants and toddlers 

participating in WIC. J Am Diet Assoc 104: 

s71-s79. 

http://dx.doi.org/10.1016/j.jada.2003.10.018. 

Smiciklas-Wright, H; Mitchell, DC; Mickle, SJ; 

Cook, AJ; Goldman, JD. (2002). Foods 

commonly eaten in the United States: 

Quantities consumed per eating occasion 

and in a day, 199496 [pre-publication 
Exposure Factors Handbook Page
 

September 2011 11-15
 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

version]. (NFS Report No. 96-5). Beltsville, 

MD: U.S. Department of Agriculture. 

http://www.ars.usda.gov/sp2userfiles/place/1 

2355000/pdf/portion.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000). Food commodity intake database 

[Database]. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2007). Analysis of fat intake based on the 

U.S. Department of Agriculture's 1994-96, 

1998 continuing survey of food intakes by 

individuals (CSFII) [EPA Report].

(EPA/600/R-05/021F). Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=116096. 

USDA (U.S. Department of Agriculture). (1980). 

Food and nutrient intakes of individuals in 1 

day in the United States, Spring 1977. 

Nationwide Food Consumption Survey 

197778: Preliminary report no. 2.

Washington, DC.

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/7778/nfcs7778_prelim_2.pdf 

. 

USDA (U.S. Department of Agriculture). (1993). 

Food and nutrient intakes by individuals in 

the United States, 1 day, 198788. 

Nationwide Food Consumption Survey 

1987-88. (Report no. 87-I-1). Washington, 

DC. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/8788/nfcs8788_rep_87-i1.pdf. 

USDA (U.S. Department of Agriculture). (1996a). 

Data tables: Results from USDA's 1994 

continuing survey of food intakes by 

individuals and 1994 diet and health 

knowledge survey. Riverdale, MD. 

USDA (U.S. Department of Agriculture). (1996b). 

Data tables: results from USDAs 1995 

Continuing survey of food intakes by 

individuals and 1995 diet and health 

knowledge survey. Riverdale, MD. 

USDA (U.S. Department of Agriculture). (1999a). 

Food and nutrient intakes by children 1994­

96, 1998: table set 17. Beltsville, MD. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/scs_all.pdf. 

USDA (U.S. Department of Agriculture). (1999b). 

USDA nutrient database for standard 

reference, release 13. Riverdale, MD. 

USDA (U.S. Department of Agriculture). (2000). 

1994-1996, 1998 continuing survey of food 

intakes by individuals (CSFII). Beltsville, 

MD: Agricultural Research Service, 

Beltsville Human Nutrition Research Center. 

USDA (U.S. Department of Agriculture). (2007). 

USDA nutrient database for standard 

reference, release 20. Riverdale, MD. 

http://www.ars.usda.gov/main/site_main.htm 

?modecode=12-35-45-00. 

Vitolins, MZ; Quandt, SA; Bell, RA; Arcury, TA; 

Case, LD. (2002). Quality of diets consumed 

by older rural adults. J Rural Health 18: 49­

56. 
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Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-3. Per Capita Intake of Total Meat and Total Dairy Products Based on 2003−2006 NHANES 

(g/kg-day, edible portion, uncooked weight) 

% 

Consuming 

Percentiles 

Population Group N Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Total Meat 

Whole Population 16,783 98 2.0 0.02 0.0 0.2 0.5 0.9 1.6 2.5 3.8 4.8 7.8 

Age Group 

Birth to 1 year 865 44 1.2 0.12 0.0* 0.0* 0.0 0.0 0.0 1.7 3.6 5.4* 9.3* 

1 to 2 years 1,052 98 4.0 0.12 0.0* 0.4* 0.8 2.0 3.4 5.5 8.0 10.0* 14.0* 

3 to 5 years 978 99 3.9 0.13 0.0* 0.7 1.4 2.1 3.3 5.0 7.6 8.5 12.4* 

6 o 12 years 2,256 99 2.8 0.06 0.1* 0.5 0.9 1.5 2.5 3.8 5.2 6.4 8.9* 

13 to 19 years 3,450 99 2.0 0.04 0.0 0.3 0.6 1.0 1.7 2.7 3.8 4.7 6.8 

20 to 49 years 4,289 99 1.8 0.03 0.0 0.3 0.5 1.0 1.6 2.4 3.4 4.1 5.7 

Females 13 to 49 years 4,103 99 1.6 0.04 0.0 0.2 0.4 0.8 1.3 2.1 3.0 3.6 5.1 

50 years and older 3,893 99 1.4 0.02 0.0 0.2 0.4 0.8 1.3 1.9 2.6 3.1 4.4 

Race 

Mexican American 4,450 98 2.2 0.05 0.0 0.2 0.5 1.0 1.8 3.0 4.2 5.4 8.3 

Non-Hispanic Black 4,265 99 2.2 0.05 0.0 0.3 0.6 1.0 1.7 2.9 4.5 5.8 9.0 

Non-Hispanic White 6,757 98 1.8 0.02 0.0 0.2 0.5 0.9 1.5 2.4 3.5 4.4 6.9 

Other Hispanic 562 97 2.2 0.08 0.0* 0.2 0.5 1.1 1.9 2.8 4.0 6.0 10.1* 

Other Race―Including Multiple 749 98 2.3 0.12 0.0* 0.1 0.5 1.0 1.9 2.9 4.5 6.4 9.6* 

23.4* 

18.7* 

23.4* 

19.5* 

13.6* 

13.5* 

12.0* 

12.2* 

8.6* 

18.9* 

23.4* 

18.7* 

19.5* 

15.1* 

Total Dairy Products 

Whole Population 16,783 99.7 6.6 0.16 0.0 0.2 0.5 1.3 3.2 7.1 15.4 25.0 56.8 

Age Group 

Birth to 1 year 865 86 10.1 0.76 0.0* 0.0* 0.0 1.2 6.4 11.5 19.6 43.2* 83.1* 

1 to 2 years 1,052 100 43.2 1.80 1.0* 5.7* 10.7 20.3 39.1 59.4 84.1 94.7* 141.22* 

3 to 5 years 978 100 24.0 0.76 0.9* 4.5 8.3 13.6 20.7 32.0 41.9 51.1 68.2* 

6 to 12 years 2,256 100 12.9 0.42 0.5* 1.5 2.6 5.6 10.8 17.8 26.0 31.8 42.9* 

13 to 19 years 3,450 100 5.5 0.25 0.1 0.4 0.6 1.6 4.0 7.6 12.3 16.4 24.9 

20 to 49 years 4,289 99.8 3.5 0.14 0.0 0.2 0.4 1.0 2.4 4.7 8.1 10.3 17.1 

Females 13 to 49 years 4,103 99.6 3.8 0.16 0.0 0.2 0.5 1.1 2.5 5.2 8.5 11.3 18.9 

50 years and older 3,893 100 3.3 0.09 0.0 0.2 0.4 1.0 2.3 4.5 7.3 9.6 15.2 

Race 

Mexican American 4,450 99.6 8.5 0.36 0.0 0.2 0.7 1.4 3.7 9.4 21.8 34.4 67.2 

Non-Hispanic Black 4,265 99.5 5.0 0.19 0.0 0.1 0.2 0.7 1.8 4.6 12.6 20.1 50.6 

Non-Hispanic White 6,757 99.8 6.6 0.19 0.1 0.3 0.6 1.4 3.3 7.1 14.8 24.5 54.1 

Other Hispanic 562 99 8.1 0.88 0.0* 0.1 0.4 1.2 3.1 7.0 20.5 39.2 69.2* 

Other Race―Including Multiple 749 99.6 6.7 0.50 0.0* 0.0 0.3 0.9 3.3 7.9 15.3 23.1 54.4* 

185.3* 

163.9* 

185.3* 

154.5* 

57.7* 

45.0* 

52.7* 

52.7* 

28.8* 

156.4* 

175.2* 

185.3* 

141.2* 

112.2* 

N = Sample size. 

SE = Standard error. 

Max = Maximum value. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on 

NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Source: U.S. EPA analysis of 2003−2006 NHANES data. 

Page Exposure Factors Handbook 11-16 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-4. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 2003−2006 NHANES 

(g/kg-day, edible portion, uncooked weight) 

Percentiles 

Population Group N Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Total Meat 

Whole Population 16,147 2.0 0.02 0.0 0.3 0.5 1.0 1.6 2.6 3.8 4.8 7.8 23.4* 

Age Group 

Birth to 1 year 385 2.7 0.20 0.0* 0.1* 0.2* 1.0 1.9 3.4 6.0* 8.1* 16.6* 18.7* 

1 to 2 years 1,030 4.1 0.10 0.1* 0.5* 1.0 2.2 3.5 5.6 8.0 10.1* 14.0* 23.4* 

3 to 5 years 968 3.9 0.13 0.0* 0.9 1.4 2.1 3.3 5.0 7.7 8.6 12.4* 19.5* 

6 to 12 years 2,250 2.8 0.06 0.1* 0.5 0.9 1.5 2.5 3.8 5.2 6.4 8.9* 13.6* 

13 to 19 years 3,422 2.0 0.04 0.0 0.4 0.6 1.1 1.7 2.7 3.8 4.7 6.9 13.5* 

20 to 49 years 4,248 1.8 0.03 0.0 0.3 0.5 1.0 1.6 2.4 3.4 4.1 5.8 12.0* 

Females 13 to 49 years 4,054 1.6 0.04 0.0 0.3 0.4 0.8 1.3 2.1 3.0 3.6 5.1 12.2* 

50 years and older 3,844 1.4 0.02 0.0 0.3 05 0.8 1.3 1.9 2.6 3.1 4.4 8.6* 

Race 

Mexican American 4,229 2.3 0.05 0.1 0.3 0.6 1.1 1.9 3.0 4.2 5.5 8.3 18.9* 

Non-Hispanic Black 4,154 2.2 0.05 0.1 0.4 0.6 1.1 1.7 2.9 4.5 5.8 9.0 23.4* 

Non-Hispanic White 6,520 1.9 0.02 0.0 0.3 0.5 0.9 1.6 2.4 3.5 4.5 7.0 18.7* 

Other Hispanic 535 2.3 0.08 0.1* 0.4 0.7 1.2 1.9 2.8 4.1 6.0 10.1* 19.5* 

Other Race―Including Multiple 709 2.3 0.12 0.0* 0.3 0.6 1.1 1.9 2.9 4.5 6.7 9.6* 15.1* 

Total Dairy Products 

Whole Population 16,657 6.6 0.16 0.0 0.3 0.5 1.3 3.2 7.1 15.5 25.0 56.8 185.3* 

Age Group 

Birth to 1 year 753 11.7 0.88 0.0* 0.1* 0.8* 3.1 7.8 12.3 22.1* 44.7* 86.4* 163.9* 

1 to 2 years 1,052 43.2 1.79 1.0* 5.7* 10.6 20.3 39.1 59.4 84.0 94.7* 141.2* 185.3* 

3 to 5 years 978 24.0 0.77 0.9* 4.7 8.3 13.7 20.7 32.0 41.9 51.1 68.2* 154.5* 

6 to 12 years 2,256 12.9 0.42 0.5* 1.6 2.6 5.6 10.8 17.8 26.0 31.8 42.9* 57.7* 

13 to 19 years 3,449 5.5 0.25 0.1 0.4 0.6 1.6 4.0 7.6 12.3 16.4 24.9 45.0* 

20 to 49 years 4,280 3.5 0.14 0.0 0.2 0.4 1.0 2.4 4.7 8.1 10.3 17.1 52.7* 

Females 13 to 49 years 4,095 3.8 0.16 0.0 0.2 0.5 1.1 2.5 5.3 8.5 11.3 18.9 52.7* 

50 years and older 3,889 3.3 0.09 0.0 0.2 0.4 1.0 2.3 4.5 7.3 9.6 15.2 28.8* 

Race 

Mexican American 4,406 8.6 0.36 0.0 0.3 0.5 1.4 3.8 9.5 21.8 34.4 67.1 156.4* 

Non-Hispanic Black 4,246 5.0 0.19 0.0 0.1 0.2 0.7 1.8 4.7 12.7 20.3 50.6 175.2* 

Non-Hispanic White 6,708 6.6 0.19 0.1 0.4 0.6 1.4 3.3 7.1 14.9 24.5 54.1 185.3* 

Other Hispanic 553 8.1 0.87 0.0* 0.2 0.5 1.2 3.2 7.1 20.6 40.1 72.7* 141.2* 

Other Race―Including Multiple 742 6.7 0.51 0.0* 0.0 0.3 0.9 3.3 7.9 15.3 23.1 54.4* 112.2* 

N = Sample size; 

SE = Standard error; 

Max = Maximum value. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on 

NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Source: U.S. EPA analysis of 2003−2006 NHANES data. 

Exposure Factors Handbook PageSeptember 2011 11-17
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Chapter 11 – Intake of Meats, Dairy Products and Fats

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-5. Per Capita Intake of Individual Meats and Dairy Products Based on 2003−2006 NHANES (g/kg-day, edible portion, uncooked weight) 

% 

Consuming 

% 

Consuming 

% 

Population Group N Mean SE Mean SE Consuming Mean SE 

Beef Pork Poultry 

Whole Population 16,783 

Age Group 

88 0.77 0.01 80 0.39 0.01 75 0.77 0.02 

Birth to 1 year 865 27 0.34 0.07 19 0.17 0.04 37 0.69 0.09 

1 to 2 years 1,052 84 1.38 0.08 73 0.75 0.06 81 1.87 0.07 

3 to 5 years 978 91 1.42 0.08 79 0.79 0.06 82 1.65 0.07 

6 to 12 years 2,256 92 1.11 0.04 84 0.52 0.02 77 1.18 0.06 

13 to 19 years 3,450 91 0.83 0.03 79 0.36 0.02 74 0.80 0.02 

20 to 49 years 4,289 88 0.73 0.02 81 0.36 0.02 77 0.71 0.02 

Females 13 to 49 years 4,103 86 0.60 0.02 79 0.28 0.01 77 0.66 0.02 

50 years and older 3,893 

Race 

87 0.58 0.01 82 0.33 0.01 71 0.50 0.02 

Mexican American 4,450 86 0.94 0.04 86 0.43 0.02 78 0.82 0.02 

Non-Hispanic Black 4,265 88 0.79 0.03 79 0.40 0.03 84 1.01 0.03 

Non-Hispanic White 6,757 88 0.74 0.01 81 0.38 0.01 72 0.70 0.02 

Other Hispanic 562 80 0.89 0.07 73 0.36 0.03 79 0.97 0.06 

Other Race―Including Multiple 749 84 0.84 0.06 78 0.41 0.03 80 1.00 0.10 

N = Sample size. 

SE = Standard error. 

Source: U.S. EPA analysis of 2003−2006 NHANES data. 

Page Exposure Factors Handbook 11-18 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-6. Consumer-Only Intake of Individual Meats and Dairy Products Based on 2003−2006 NHANES 

(g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE N Mean SE N Mean SE 

Beef Pork Poultry 

Whole Population 

Age Group 

14,328 0.88 0.01 13,180 0.49 0.01 12,660 1.03 0.02 

Birth to 1 year 233 1.28 0.20 172 0.93 0.17 315 1.89 0.16 

1 to 2 years 893 1.65 0.08 781 1.03 0.08 880 2.32 0.07 

3 to 5 years 879 1.56 0.08 784 1.00 0.07 800 2.02 0.08 

6 to 12 years 2,102 1.20 0.04 1,922 0.62 0.02 1,813 1.54 0.08 

13 to 19 years 3,140 0.91 0.03 2,770 0.46 0.02 2,652 1.07 0.03 

20 to 49 years 3,767 0.84 0.02 3,539 0.44 0.01 3,360 0.92 0.02 

Females 13 to 49 years old 3,585 0.70 0.02 3,283 0.36 0.01 3,224 0.86 0.03 

50 years and older 

Race 

3,314 0.66 0.01 3,212 0.40 0.01 2,840 0.70 0.02 

Mexican American 3,679 1.09 0.03 3,595 0.50 0.02 3,371 1.05 0.03 

Non-Hispanic Black 3,751 0.90 0.03 3,312 0.51 0.03 3,522 1.21 0.03 

Non-Hispanic White 5,843 0.84 0.02 5,304 0.48 0.01 4,769 0.97 0.02 

Other Hispanic 450 1.11 0.06 397 0.50 0.05 434 1.23 0.07 

Other Race―Including Multiple 605 1.00 0.06 572 0.53 0.04 564 1.26 0.10 

N = Sample size. 

SE = Standard error. 

Source: U.S. EPA analysis of 2003−2006 NHANES data. 

Exposure Factors Handbook PageSeptember 2011 11-19
Exposure Factors Handbook

Chapter 11 – Intake of Meats, Dairy Products and Fats

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-7. Mean Meat Intakes per Individual in a Day, by Sex and Age (g/day, as-consumed)a for 1977−1978 

Group Age (years) 

Total Meat, 

Poultry and 

Fish 

Beef Pork Lamb, Veal, 

Game 

Frankfurters, 

Sausages, 

Luncheon 

Meats, Spreads 

Total 

Poultry 

Chicken 

Only 

Meat 

Mixturesb 

Males and Females 

1 and Under 

1 to 2 

3 to 5 

6 to 8 

Males 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

75 and Over 

Females 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

75 and Over 

Males and Females 

All Ages 

72 

91 

121 

149 

188 

218 

272 

310 

285 

295 

274 

231 

196 

162 

176 

180 

184 

183 

187 

187 

159 

134 

207 

9 

18 

23 

33 

41 

53 

82 

90 

86 

75 

70 

54 

41 

38 

47 

46 

52 

48 

49 

52 

34 

31 

54 

4 

6 

8 

15 

22 

18 

24 

21 

27 

28 

32 

25 

39 

17 

19 

14 

19 

17 

19 

19 

21 

17 

20 

3 -

c 

-

c 

1 

3 -

c 

1 

2 

1 

1 

1 

2 

7 

1 

1 

2 

1 

1 

2 

2 

4 

2 

2 

2 

15 

15 

17 

19 

25 

25 

33 

30 

26 

29 

22 

19 

20 

18 

16 

18 

16 

14 

12 

12 

9 

20 

4 

16 

19 

20 

24 

27 

37 

45 

31 

31 

31 

29 

28 

27 

23 

28 

26 

24 

24 

26 

30 

19 

27 

1 

13 

19 

19 

21 

24 

32 

43 

29 

28 

29 

26 

25 

23 

22 

27 

24 

22 

21 

24 

25 

16 

24 

51 

32 

49 

55 

71 

87 

93 

112 

94 

113 

86 

72 

54 

55 

61 

61 

61 

66 

63 

60 

47 

49 

72 a Based on USDA Nationwide Food Consumption Survey 1977−1978 data for 1 day. b Includes mixtures containing meat, poultry, or fish as a main ingredient. c Less than 0.5 g/day, but more than 0. - Indicates data are not available. 

Source: USDA (1980). 

Page Exposure Factors Handbook 11-20 September 2011
 

 

 

 

 

 

 

 

 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-8. Mean Meat Intakes per Capita in a Day, by Sex and Age (g/day, as-consumed)a for 1987−1988 

Group Age (years) 

Total Meat, 

Poultry, and 

Fish 

Beef Pork Lamb, Veal, 

Game 

Frankfurters, 

Sausages, 

Luncheon 

Meats 

Total 

Poultry 

Chicken 

Only 

Meat 

Mixturesb 

Males and Females 

5 and Under 

Males 

6 to 11 

12 to 19 

20 and over 

Females 

6 to 11 

12 to 19 

20 and over 

All individuals 

92 

156 

252 

250 

151 

169 

170 

193 

10 

22 

38 

44 

26 

31 

29 

32 

9 

14 

17 

19 

9 

10 

12 

14 

<0.5 

<0.5 

1 

23 

1 

<0.5 

1 

1 

11 

13 

20 

2 

11 

18 

13 

17 

14 

27 

27 

31 

20 

17 

24 

26 

12 

24 

20 

25 

17 

13 

18 

20 

39 

74 

142 

108 

74 

80 

73 

86 a Based on USDA Nationwide Food Consumption Survey 1987−1988 data for 1 day. b Includes mixtures containing meat, poultry, or fish as a main ingredient. 

Source: USDA (1993). 

Exposure Factors Handbook PageSeptember 2011 11-21
Exposure Factors Handbook 

Chapter 11 – Intake of Meats, Dairy Products and Fats

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 11-22 September 2011

Table 11-9. Mean Meat Intakes per Capita in a Day, by Sex and Age (g/day, as-consumed)a for 1994 and 1995 

Group Age (years) 

Total Meat, 

Poultry, and 

Fish 

Beef Pork Lamb, Veal, 

Game 

Frankfurters, 

Sausages, 

Luncheon 

Meats 

Total 

Poultry Chicken Only Meat b Mixtures

1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 

Males and Females 

 5 and Under 

Males 

 6 to 11 

 12 to 19 

 20 and over 

Females 

 6 to 11 

 12 to 19 

 20 and over 

All individuals 

94 

131 

238 

266 

117 

164 

168 

195 

87 

161 

256 

283 

136 

158 

167 

202 

10 

19 

31 

35 

18 

23 

18 

24 

8 

18 

29 

41 

16 

22 

21 

27 

6 

9 

11 

17 

5 

5 

9 

11 

4 

7 

11 

14 

5 

7 

11 

10 

c 

-

0 

1 

2 

c 

-

c 

-

1 

1 

c 

-

c 

-

1 

1 

c 

-

0 

1 

1 

17 

22 

21 

29 

18 

16 

16 

21 

18 

27 

27 

27 

20 

10 

15 

21 

16 

19 

40 

39 

19 

20 

25 

29 

15 

25 

26 

31 

17 

19 

22 

24 

14 

16 

29 

30 

15 

15 

20 

23 

14 

22 

23 

27 

14 

18 

19 

21 

41 

51 

119 

124 

51 

94 

87 

98 

39 

68 

150 

149 

69 

82 

83 

104 a Based on USDA CSFII 1994 and 1995 data for 1 day. b Includes mixtures containing meat, poultry, or fish as a main ingredient. c Less than 0.5 grams/day, but more than 0. 

Source: USDA (1996a, b). 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-10. Mean Dairy Product Intakes per Capita in a Day, by Sex and Age 

(g/day, as-consumed)a for 1977−1978 

Group Age (years) Total Milk Fluid Milk Cheese Eggs 

Males and Females 

1 and Under 

1 to 2 

3 to 5 

6 to 8 

Males 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

75 and Over 

Females 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

75 and Over 

618 

404 

353 

433 

432 

504 

519 

388 

243 

203 

180 

217 

193 

402 

387 

316 

224 

182 

130 

139 

166 

214 

361 

397 

330 

401 

402 

461 

467 

353 

213 

192 

173 

204 

184 

371 

343 

279 

205 

158 

117 

128 

156 

205 

1 

8 

9 

10 

8 

9 

13 

15 

21 

18 

17 

14 

18 

7 

11 

11 

18 

19 

18 

19 

14 

20 

5 

20 

22 

18 

26 

28 

31 

32 

38 

41 

36 

36 

41 

14 

19 

21 

26 

26 

23 

24 

22 

19 a Based on USDA Nationwide Food Consumption Survey 1977−1978 data for 1 day. 

Source: USDA (1980). 

Exposure Factors Handbook Page
 

September 2011 11-23
 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-24 September 2011 

Table 11-11. Mean Dairy Product Intakes per Capita in a Day, by Sex and Age 

(g/day, as-consumed)a for 1987−1988 

Group Age (years) Total Fluid Milk Whole Milk Lowfat/Skim 

Milk Cheese Eggs 

Males and Females 

 5 and under 

Males 

 6 to 11 

 12 to 19 

 20 and over 

Females 

 6 to 11 

 12 to 19 

 20 and over 

All individuals 

347 

439 

392 

202 

310 

260 

148 

224 

177 

224 

183 

88 

135 

124 

55 

99 

129 

159 

168 

94 

135 

114 

81 

102 

7 

10 

12 

17 

9 

12 

15 

14 

11 

17 

17 

27 

14 

18 

17 

20 a 

Source: 

Based on USDA Nationwide Food Consumption Survey 1987−1988 data for 1 day. 

USDA (1993). 

 

 

 

 

 

 

 

 

Table 11-12. Mean Dairy Product Intakes per Capita in a Day, by Sex and Age 

(g/day, as-consumed)a for 1994 and 1995 

Group Age (years) Total Fluid Milk Whole Milk Lowfat Milk Cheese Eggs 

1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 

Males and Females 

5 and under 

Males 

6 to 11 

12 to 19 

20 and over 

Females 

6 to 11 

12 to 19 

20 and over 

All individuals 

424 

407 

346 

195 

340 

239 

157 

229 

441 

400 

396 

206 

330 

235 

158 

236 

169 

107 

105 

50 

101 

75 

37 

65 

165 

128 

105 

57 

93 

71 

32 

66 

130 

188 

160 

83 

136 

88 

56 

89 

129 

164 

176 

88 

146 

107 

57 

92 

12 

11 

19 

19 

17 

14 

16 

17 

9 

12 

20 

16 

13 

13 

15 

15 

11 

13 

18 

23 

12 

13 

15 

17 

13 

15 

24 

23 

15 

17 

16 

19 a Based on USDA CSFII 1994 and 1995 data for 1 day. 

Source: USDA (1996a, b). 
 

 

 

 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-13. Mean Quantities of Meat and Eggs Consumed Daily by Sex and Age, per Capita (g/day, as-consumed)a 

Age Group Sample 

Size Total Beef Pork 

Lamb, 

Veal, 

Game 

Organ 

Meats 

Frankfurters, 

Sausages, 

Luncheon Meats 

Poultry 

Eggs 

Mixtures, 

Mainly 

Meat/Poultry/ 

Fish 

Total Chicken 

Males and Females 

Under 1 

1 

2 

1 to 2 

3 

4 

5 

3 to 5 

5 and under 

1,126 

1,016 

1,102 

2,118 

1,831 

1,859 

884 

4,574 

7,818 

24 

80 

94 

87 

101 

115 

121 

112 

93 

1b 

5 

7 

6 

8 

10 

14 

11 

8 

-

b,c 

2 

6 

4 

6 

6 

6 

6 

5 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

c 

-

c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

2 

13 

18 

15 

19 

22 

22 

21 

17 

3 

12 

17 

15 

19 

20 

22 

21 

16 

2 

12 

16 

14 

18 

19 

19 

19 

15 

3 

13 

18 

16 

13 

13 

13 

13 

13 

16 

43 

41 

42 

43 

49 

51 

47 

42 

Males 

6 to 9 

6 to 11 

12 to 19 

787 

1,031 

737 

151 

154 

250 

18 

19 

30 

7 

7 

12 

-

b,c 

-

b,c 

1b 

-

b,c 

-

b,c 

0 

24 

24 

28 

23 

22 

31 

21 

20 

26 

11 

12 

22 

71 

72 

134 

Females 

6 to 9 

6 to 11 

12 to 19 

704 

969 

732 

121 

130 

158 

17 

18 

21 

4 

5 

5 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

-

b,c 

18 

19 

15 

19 

20 

21 

16 

17 

19 

10 

11 

13 

55 

60 

85 

Males and Females 

9 and under 

19 and under 

9,309 

11,287 

110 

152 

12 

18 

5 

7 

-

c 

-

b,c 

-

b,c 

-

b,c 

19 

20 

18 

22 

17 

19 

12 

14 

50 

76 a Based on data from 1994−1996, 1998 CSFII. b Estimate is not statistically reliable due to small sample size reporting intake. c Value less than 0.5, but greater than 0. 

Note: Consumption amounts shown are representative of the 1st day of each participant’s survey response. 

Source: USDA (1999a). 

Exposure Factors Handbook PageSeptember 2011 11-25
 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-14. Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%)a 

Age Group (years) Sample 

Size Total Beef Pork 

Lamb, 

Veal, 

Game 

Organ 

Meats 

Frankfurters, 

Sausages, 

Luncheon Meats 

Poultry 

Total Chicken Eggs 

Mixtures, 

Mainly 

Meat/Poultry/ 

Fish 

Males and Females 

Under 1 

1 

2 

1 to 2 

3 

4 

5 

3 to 5 

5 and under 

1,126 

1,016 

1,102 

2,118 

1,831 

1,859 

884 

4,574 

7,818 

26.0 

77.4 

85.2 

81.4 

86.2 

86.2 

87.1 

86.5 

77.5 

2.1 

11.9 

16.2 

14.1 

13.8 

16.1 

18.2 

16.0 

13.7 

1.1b 

7.3 

14.9 

11.2 

13.3 

13.8 

13.2 

13.4 

11.2 

0.2b 

0.8b 

0.8b 

0.8b 

0.5b 

0.5b 

0.6b 

0.5 

0.6 

0.2b 

0.2b 

0.2b 

0.2b 

-

b,c 

0.2b 

0.2b 

0.2b 

0.2b 

6.1 

26.3 

33.2 

29.9 

36.4 

37.0 

35.1 

36.1 

30.4 

6.3 

24.0 

27.6 

25.8 

28.3 

27.4 

27.7 

27.8 

24.5 

5.0 

23.1 

25.6 

24.4 

26.0 

25.1 

24.8 

25.3 

22.6 

6.7 

22.8 

27.3 

25.1 

19.8 

16.9 

16.4 

17.7 

18.9 

13.7 

32.2 

31.4 

31.8 

29.2 

30.5 

30.8 

30.2 

28.8 

Males 

6 to 9 

6 to 11 

12 to 19 

787 

1,031 

737 

87.4 

87.8 

86.8 

20.1 

22.0 

24.2 

11.9 

12.2 

15.8 

0.4b 

0.4b 

0.6b 

0.1b 

0.2b 

0.0 

37.4 

36.2 

31.8 

24.8 

22.9 

20.6 

22.3 

20.5 

17.6 

15.1 

15.6 

17.0 

36.2 

35.7 

38.3 

Females 

6 to 9 

6 to 11 

12 to 19 

704 

969 

732 

84.6 

86.5 

80.1 

19.4 

20.2 

22.0 

9.2 

10.0 

11.2 

0.4b 

0.4b 

0.1b 

0.2b 

0.1b 

0.1b 

33.5 

33.1 

24.6 

23.1 

22.9 

21.6 

20.2 

19.8 

18.9 

13.4 

13.3 

15.0 

32.4 

32.8 

34.0 

Males and Females 

9 and under 

19 and under 

9,309 

11,287 

80.9 

82.8 

16.1 

19.6 

10.9 

12.1 

0.5 

0.4 

0.2b 

0.1b 

24.3 

22.7 

24.3 

22.7 

22.0 

20.1 

17.1 

16.4 

31.0 

33.3 a Based on data from 1994−1996, 1998 CSFII. b Estimate is not statistically reliable due to small sample size reporting intake. c Value less than 0.5, but greater than 0. 

Note: Percentages shown are representative of the 1st day of each participant’s survey response. 

Source: USDA (1999a). 

Page Exposure Factors Handbook 11-26 September 2011 
 

 

 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-15. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, per Capita (g/day, as-consumed)a 

Age Group (year) Sample 

Size 

Total Milk 

and Milk 

Products 

Milk, Milk Drinks, Yogurt Milk 

Desserts Cheese Total Fluid Milk Yogurt Total Whole Lowfat Skim 

Males and Females 

Under 1 

1 

2 

1 to 2 

3 

4 

5 

3 to 5 

5 and under 

1,126 

1,016 

1,102 

2,118 

1,831 

1,859 

884 

4,574 

7,818 

762 

546 

405 

474 

419 

407 

417 

414 

477 

757 

526 

377 

450 

384 

369 

376 

376 

447 

61 

475 

344 

408 

347 

328 

330 

335 

327 

49 

347 

181 

262 

166 

147 

137 

150 

177 

11 

115 

141 

128 

150 

149 

159 

153 

127 

-

b,c 5b 

17 

11 

26 

27 

25 

26 

18 

4 

14 

10 

12 

10 

10 

9 

10 

10 

3 

11 

16 

14 

22 

23 

25 

23 

18 

1 

9 

11 

10 

12 

14 

14 

13 

11 

Males 

6 to 9 

6 to 11 

12 to 19 

787 

1,031 

737 

450 

450 

409 

405 

402 

358 

343 

335 

303 

127 

121 

99 

176 

172 

158 

29 

33 

40 

6 

6 3b 

31 

35 

29 

13 

12 

19 

Females 

6 to 9 

6 to 11 

12 to 19 

704 

969 

732 

380 

382 

269 

337 

336 

220 

288 

283 

190 

105 

108 

66 

146 

136 

92 

26 

29 

30 

4 

4 4b 

29 

30 

29 

13 

14 

14 

Males and Females 

9 and under 

19 and under 

9,309 

11,287 

453 

405 

417 

362 

323 

291 

153 

121 

141 

135 

22 

29 

8 

6 

23 

27 

12 

14 a Based on data from 1994−1996, 1998 CSFII. b Estimate is not statistically reliable due to small sample size reporting intake. c Value less than 0.5, but greater than 0. 

Note: Consumption amounts shown are representative of the 1st day of each participant’s survey response. 

Source: USDA (1999a). 

Exposure Factors Handbook PageSeptember 2011 11-27
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-16. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%)a 

Age Group (year) Sample 

Size 

Total Milk and 

Milk Products 

Milk, Milk Drinks, Yogurt 

Total 

Fluid Milk 

Yogurt Total Whole Lowfat Skim 

Milk 

Desserts Cheese 

Males and Females 

Under 1 

1 

2 

1 to 2 

3 

4 

5 

3 to 5 

5 and under 

1,126 

1,016 

1,102 

2,118 

1,831 

1,859 

884 

4,574 

7,818 

85.4 

95.3 

91.6 

93.4 

94.3 

93.2 

93.1 

93.5 

92.5 

84.6 

92.7 

87.3 

90.0 

88.3 

87.8 

86.4 

87.5 

88.0 

11.1 

87.7 

84.3 

86.0 

84.6 

85.0 

81.2 

83.6 

75.7 

8.3 

61.7 

44.8 

53.0 

42.5 

41.3 

38.1 

40.6 

41.0 

2.4 

26.5 

36.3 

31.5 

39.5 

40.4 

41.7 

40.6 

32.9 

0.2b 

1.5b 

5.2 

3.4 

6.8 

7.7 

6.5 

7.0 

4.9 

3.1 

10.0 

6.8 

8.4 

7.3 

5.8 

5.5 

6.2 

6.6 

4.5 

13.9 

17.5 

15.8 

21.4 

21.7 

21.4 

21.5 

17.5 

6.0 

29.7 

32.6 

31.2 

37.0 

36.9 

34.9 

36.3 

30.9 

Males 

6 to 9 

6 to 11 

12 to 19 

787 

1,031 

737 

93.2 

92.3 

81.3 

85.5 

84.6 

65.8 

80.7 

79.0 

59.6 

32.4 

30.8 

22.6 

44.3 

43.1 

30.7 

8.6 

9.5 

7.0 

3.8 

3.7 

1.7b 

24.0 

25.0 

13.6 

34.6 

32.3 

37.1 

Females 

6 to 9 

6 to 11 

12 to 19 

704 

969 

732 

90.2 

90.2 

75.4 

82.5 

81.5 

54.0 

77.5 

76.0 

49.7 

31.5 

33.2 

17.5 

40.8 

37.8 

23.9 

8.1 

8.4 

9.5 

2.9 

3.0 

2.2b 

24.1 

22.4 

17.1 

30.9 

31.9 

36.1 

Males and Females 

9 and under 

19 and under 

9,309 

11,287 

92.2 

86.7 

86.4 

75.6 

77.1 

68.1 

37.4 

30.1 

36.8 

33.1 

6.3 

7.5 

5.3 

3.8 

20.1 

18.6 

31.7 

33.5 a Based on data from 1994−1996, 1998 CSFII. b Estimate is not statistically reliable due to small sample size reporting intake. 

Note: Percentages shown are representative of the 1st day of each participant’s survey response. 

Source: USDA (1999a). 

Page Exposure Factors Handbook 11-28 September 2011 
Exposure Factors Handbook Page 

September 2011 11-29 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-17. Per Capita Intake of Total Meat and Total Dairy Products (g/kg-day, edible portion, uncooked weight) 

Population Group N Percent 

Consuming Mean SE Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 50+ years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 American Indian, Alaska Native 

 Asian, Pacific Islander 

 Black 

 Other 

 White 

Region 

 Midwest 

 Northeast 

 South 

 Midwest 

 West 

Urbanization 

 MSA, Central City 

 MSA, Outside Central City 

 Non-MSA 

20,607 

1,486 

2,096 

4,391 

2,089 

1,222 

4,677 

4,646 

4,687 

5,308 

5,890 

4,722 

177 

557 

2,740 

1,638 

15,495 

4,822 

3,692 

7,208 

4,822 

4,885 

6,164 

9,598 

4,845 

97.5 

40.0 

97.3 

98.8 

98.7 

98.8 

98.2 

98.2 

96.8 

97.6 

97.4 

98.0 

98.4 

96.8 

97.9 

96.5 

97.5 

97.9 

96.3 

97.7 

97.9 

97.6 

97.3 

97.3 

98.1 

2.1 

1.2 

4.1 

4.1 

2.9 

2.1 

1.9 

1.5 

2.1 

2.1 

2.1 

2.0 

2.4 

2.5 

2.6 

2.5 

1.9 

2.2 

2.1 

2.0 

2.2 

2.0 

2.1 

2.0 

2.1 

0.02 

0.1 

0.1 

0.05 

0.05 

0.05 

0.04 

0.02 

0.06 

0.04 

0.03 

0.04 

0.25 

0.17 

0.10 

0.08 

0.02 

0.04 

0.07 

0.03 

0.04 

0.06 

0.04 

0.04 

0.03 

Total Meat 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.2 

0.0 

0.2 

0.6 

0.4 

0.2 

0.2 

0.2 

0.1 

0.2 

0.1 

0.2 

0.3 

0.1 

0.3 

0.2 

0.2 

0.3 

0.0 

0.2 

0.3 

0.2 

0.1 

0.2 

0.3 

0.5 

0.0 

0.8 

1.2 

0.8 

0.5 

0.5 

0.4 

0.5 

0.5 

0.5 

0.5 

0.5 

0.3 

0.6 

0.5 

0.5 

0.6 

0.4 

0.5 

0.6 

0.4 

0.5 

0.5 

0.6 

1.0 

0.0 

1.9 

2.2 

1.5 

1.0 

1.0 

0.8 

1.0 

1.0 

0.9 

1.0 

1.0 

1.1 

1.2 

1.1 

0.9 

1.1 

0.9 

0.9 

1.1 

0.9 

0.9 

1.0 

1.0 

1.7 

0.0 

3.6 

3.6 

2.5 

1.9 

1.6 

1.3 

1.7 

1.7 

1.6 

1.6 

2.0 

2.1 

2.0 

2.0 

1.6 

1.8 

1.6 

1.7 

1.8 

1.6 

1.7 

1.6 

1.7 

2.7 

1.6 

5.7 

5.4 

3.8 

2.7 

2.5 

1.9 

2.8 

2.7 

2.7 

2.6 

3.3 

3.5 

3.3 

3.1 

2.5 

2.8 

2.7 

2.6 

2.8 

2.7 

2.7 

2.6 

2.7 

4.0 

4.2 

8.0 

7.7 

5.4 

3.8 

3.5 

2.7 

4.2 

4.0 

4.0 

3.8 

4.3 

4.5 

5.4 

4.9 

3.7 

4.1 

4.1 

3.9 

4.1 

4.0 

4.2 

3.9 

4.1 

5.3 

6.7 

9.8 

9.4 

6.5 

4.8 

4.2 

3.3 

5.4 

5.2 

5.4 

5.0 

6.3 

6.0 

7.1 

6.5 

4.8 

5.3 

5.4 

5.2 

5.3 

5.2 

5.6 

5.1 

5.1 

8.7 

10.7 

14.1 

12.7 

9.6 

7.1 

6.9 

4.8 

8.7 

8.7 

8.6 

7.9 

9.0 

9.6 

10.4 

10.8 

7.7 

9.1 

8.7 

8.3 

9.1 

8.1 

8.9 

8.0 

8.6 

30.3 

29.6 

20.6 

23.4 

18.0 

30.3 

13.4 

9.7 

21.2 

23.6 

30.3 

29.6 

12.4 

13.0 

23.6 

29.6 

30.3 

30.3 

20.5 

23.4 

30.3 

29.6 

23.6 

29.6 

30.3 
Page Exposure Factors Handbook 

11-30 September 2011 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-17. Per Capita Intake of Total Meat and Total Dairy Products Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Percent 

Consuming Mean SE Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Total Dairy Product 

Whole population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 50+ years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 American Indian, Alaska 

Native 

 Asian, Pacific Islander 

 Black 

 Other 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 MSA, Central City 

 MSA, Outside Central City 

 Non-MSA 

20,607 

1,486 

2,096 

4,391 

2,089 

1,222 

4,677 

4,646 

4,687 

5,308 

5,890 

4,722 

177 

557 

2,740 

1,638 

15,495 

4,822 

3,692 

7,208 

4,885 

6,164 

9,598 

4,845 

99.5 

79.5 

99.8 

100.0 

100.0 

99.8 

99.8 

99.8 

99.7 

99.5 

99.6 

99.4 

99.8 

97.0 

99.6 

99.1 

99.6 

99.7 

99.6 

99.6 

99.2 

99.6 

99.4 

99.7 

6.7 

12.6 

36.7 

23.3 

13.6 

5.6 

3.3 

3.2 

7.0 

6.6 

6.4 

6.7 

8.0 

6.4 

5.6 

9.5 

6.6 

7.0 

6.7 

6.0 

7.4 

6.5 

7.0 

6.3 

0.1 

0.9 

0.7 

0.3 

0.4 

0.2 

0.1 

0.1 

0.2 

0.2 

0.2 

0.1 

1.1 

0.4 

0.2 

0.6 

0.1 

0.3 

0.2 

0.1 

0.4 

0.2 

0.1 

0.3 

0.01 

0.0 

0.4 

1.1 

0.3 

0.01 

0.01 

0.02 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.2 

0.0 

3.9 

4.2 

1.8 

0.2 

0.2 

0.2 

0.2 

0.2 

0.2 

0.2 

0.0 

0.0 

0.1 

0.1 

0.3 

0.3 

0.3 

0.2 

0.2 

0.2 

0.2 

0.2 

0.4 

0.0 

7.7 

7.0 

3.5 

0.5 

0.3 

0.4 

0.4 

0.4 

0.4 

0.5 

0.1 

0.0 

0.2 

0.4 

0.5 

0.5 

0.6 

0.3 

0.4 

0.4 

0.5 

0.4 

1.2 

1.0 

17.4 

13.0 

6.7 

1.5 

0.9 

1.0 

1.3 

1.3 

1.2 

1.3 

0.8 

0.6 

0.6 

1.3 

1.4 

1.4 

1.5 

1.0 

1.4 

1.1 

1.4 

1.1 

3.2 

8.0 

31.3 

20.8 

11.7 

4.2 

2.2 

2.4 

3.4 

3.1 

3.1 

3.4 

3.1 

3.0 

2.1 

4.2 

3.4 

3.5 

3.4 

2.8 

3.7 

3.2 

3.4 

3.0 

7.3 

14.1 

49.8 

30.9 

18.5 

8.1 

4.6 

4.5 

8.0 

7.3 

6.8 

7.3 

11.0 

7.4 

6.5 

11.5 

7.2 

7.7 

7.3 

6.3 

8.5 

7.1 

7.7 

6.8 

16.1 

24.1 

72.1 

42.0 

26.0 

12.5 

7.6 

6.9 

16.9 

16.2 

15.2 

16.4 

21.2 

14.9 

14.7 

25.4 

15.6 

16.9 

15.9 

14.5 

17.5 

15.8 

16.9 

15.0 

25.4 

48.7 

88.3 

49.4 

31.5 

15.5 

9.9 

8.9 

26.9 

25.0 

24.7 

25.0 

30.2 

28.1 

23.3 

36.3 

24.7 

25.8 

25.7 

23.7 

27.6 

25.1 

26.3 

23.9 

52.1 

127 

126 

67.7 

42.7 

25.4 

14.9 

14.1 

55.3 

52.0 

52.8 

49.1 

68.9 

51.7 

45.4 

69.3 

51.2 

52.7 

54.2 

48.6 

54.5 

49.8 

54.3 

51.4 

223 

186 

223 

198 

80.6 

32.7 

36.4 

42.5 

156.8 

185.6 

164.8 

223.2 

146.2 

164.8 

185.6 

185.2 

223.2 

198.4 

185.6 

223.2 

185.2 

198.4 

223.2 

180.7 

N 

SE 

MSA 

Source: 

= Sample size. 

= Standard error. 

= Metropolitan statistical area. 

U.S. EPA analysis of 1994−1996, 1998 CSFII . 
Table 11-18. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Total Meat 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 50+ years 

 Whole population 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 American Indian, Alaska Native 

 Asian, Pacific Islander 

 Black 

 Other 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 MSA, Central City 

 MSA, Outside Central City 

 Non-MSA 

575 

2,044 

4,334 

2,065 

1,208 

4,593 

4,565 

19,384 

4,423 

4,995 

5,510 

4,456 

171 

503 

2,588 

1,508 

14,614 

4,573 

3,448 

6,798 

4,565 

5,783 

9,004 

4,597 

3.0 

4.2 

4.2 

2.9 

2.1 

1.9 

1.5 

2.1 

96.8 

97.6 

97.4 

98.0 

98.4 

96.8 

97.9 

96.5 

97.5 

97.9 

96.3 

97.7 

97.6 

97.3 

97.3 

98.1 

0.2 

0.1 

0.1 

0.1 

0.05 

0.04 

0.02 

0.02 

2.2 

2.1 

2.1 

2.0 

2.5 

2.6 

2.6 

2.6 

2.0 

2.2 

2.1 

2.1 

2.1 

2.2 

2.1 

2.2 

0.01 

0.04 

0.04 

0.1 

0.02 

0.04 

0.03 

0.04 

0.06 

0.04 

0.03 

0.04 

0.27 

0.18 

0.10 

0.09 

0.02 

0.04 

0.07 

0.03 

0.06 

0.04 

0.04 

0.02 

0.1 

0.6 

0.8 

0.5 

0.3 

0.4 

0.3 

0.4 

0.0 

0.0 

0.0 

0.0 

0.2 

0.0 

0.0 

0.1 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.3 

1.0 

1.2 

0.9 

0.6 

0.6 

0.5 

0.6 

0.4 

0.3 

0.3 

0.4 

0.4 

0.3 

0.5 

0.4 

0.3 

0.4 

0.4 

0.3 

0.3 

0.3 

0.3 

0.4 

1.0 

2.1 

2.2 

1.5 

1.1 

1.0 

0.8 

1.0 

0.6 

0.6 

0.5 

0.6 

0.5 

0.6 

0.7 

0.7 

0.5 

0.7 

0.5 

0.5 

0.5 

0.5 

0.6 

0.6 

2.2 

3.6 

3.6 

2.5 

1.9 

1.6 

1.3 

1.7 

1.0 

1.0 

1.0 

1.0 

1.1 

1.2 

1.2 

1.2 

1.0 

1.1 

1.0 

1.0 

1.0 

1.0 

1.0 

1.1 

4.2 

5.7 

5.5 

3.9 

2.8 

2.5 

2.0 

2.7 

1.7 

1.7 

1.7 

1.7 

2.1 

2.3 

2.0 

2.0 

1.6 

1.8 

1.7 

1.7 

1.6 

1.7 

1.7 

1.7 

7.4 

8.1 

7.7 

5.4 

3.8 

3.5 

2.7 

4.0 

2.8 

2.7 

2.7 

2.6 

3.3 

3.5 

3.3 

3.2 

2.5 

2.8 

2.7 

2.7 

2.7 

2.8 

2.6 

2.8 

9.2 

9.8 

9.4 

6.5 

4.8 

4.2 

3.3 

5.3 

4.2 

4.1 

4.0 

3.9 

4.3 

4.5 

5.4 

5.0 

3.7 

4.1 

4.2 

3.9 

4.0 

4.2 

3.9 

4.1 

12.9 

14.1 

12.7 

9.6 

7.1 

6.9 

4.8 

8.7 

5.5 

5.2 

5.5 

5.0 

6.3 

6.0 

7.2 

6.6 

4.8 

5.3 

5.5 

5.2 

5.2 

5.6 

5.2 

5.1 

29.6 

20.6 

23.4 

18.0 

30.3 

13.4 

9.7 

30.3 

8.7 

8.8 

8.7 

7.9 

9.0 

9.6 

10.5 

10.9 

7.7 

9.2 

8.7 

8.3 

8.1 

9.1 

8.0 

8.6 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Page 

September 2011 11-31 
Page Exposure Factors Handbook 

11-32 September 2011 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-18. Consumer-Only Intake of Total Meat and Total Dairy Products Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) (continued) 

Population Group N Mean SE Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Total Dairy Product 

Whole population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 50+ years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 American Indian, Alaskan Native 

 Asian, Pacific Islander 

 Black 

 Other 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 MSA, Central City 

 MSA, Outside Central City 

 Non-MSA 

20,287 

1,192 

2,093 

4,390 

2,089 

1,221 

4,666 

4,636 

4,630 

5,210 

5,801 

4,646 

176 

537 

2,708 

1,607 

15,259 

4,765 

3,638 

7,104 

4,780 

6,072 

9,440 

4,775 

6.7 

15.9 

36.8 

23.3 

13.6 

5.6 

3.3 

3.2 

99.7 

99.5 

99.6 

99.4 

99.8 

97.0 

99.6 

99.1 

99.6 

99.7 

99.6 

99.6 

99.2 

99.6 

99.4 

99.7 

0.1 

1.0 

0.7 

0.3 

0.4 

0.2 

0.1 

0.1 

7.1 

6.6 

6.4 

6.7 

8.0 

6.6 

5.7 

9.6 

6.7 

7.1 

6.8 

6.0 

7.4 

6.5 

7.0 

6.3 

0.02 

0.03 

0.4 

1.1 

0.3 

0.01 

0.01 

0.02 

0.2 

0.2 

0.2 

0.1 

1.1 

0.4 

0.2 

0.7 

0.1 

0.3 

0.2 

0.1 

0.4 

0.2 

0.1 

0.3 

0.2 

0.8 

4.2 

4.2 

1.8 

0.3 

0.2 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.4 

1.9 

7.8 

7.0 

3.5 

0.5 

0.3 

0.4 

0.2 

0.2 

0.2 

0.2 

0.0 

0.0 

0.1 

0.2 

0.3 

0.3 

0.3 

0.2 

0.2 

0.2 

0.3 

0.2 

1.3 

5.8 

17.4 

13.0 

6.7 

1.5 

0.9 

1.1 

0.5 

0.4 

0.4 

0.5 

0.1 

0.1 

0.2 

0.4 

0.6 

0.6 

0.6 

0.3 

0.5 

0.4 

0.5 

0.4 

3.3 

10.2 

31.3 

20.8 

11.7 

4.2 

2.3 

2.4 

1.3 

1.3 

1.2 

1.3 

0.8 

0.6 

0.6 

1.3 

1.4 

1.4 

1.5 

1.0 

1.5 

1.2 

1.4 

1.1 

7.4 

16.0 

49.8 

30.9 

18.5 

8.1 

4.6 

4.5 

3.4 

3.2 

3.1 

3.4 

3.1 

3.1 

2.1 

4.3 

3.4 

3.5 

3.4 

2.8 

3.8 

3.2 

3.5 

3.0 

16.2 

27.7 

72.1 

42.0 

26.0 

12.5 

7.6 

6.9 

8.0 

7.3 

6.8 

7.3 

11.1 

7.6 

6.6 

11.6 

7.2 

7.8 

7.3 

6.3 

8.5 

7.2 

7.8 

6.8 

25.5 

57.5 

88.3 

49.4 

31.5 

15.5 

9.9 

8.9 

16.9 

16.3 

15.2 

16.5 

21.2 

15.6 

14.8 

25.5 

15.7 

16.9 

16.0 

14.6 

17.8 

15.9 

17.0 

15.0 

52.2 

141.8 

126.2 

67.7 

42.7 

25.4 

14.9 

14.1 

26.9 

25.1 

24.7 

25.1 

30.2 

28.1 

23.4 

36.5 

24.7 

25.8 

25.8 

23.8 

27.7 

25.2 

26.4 

23.9 

223.2 

185.6 

223.2 

198.4 

80.6 

32.7 

36.4 

42.5 

55.4 

52.1 

53.0 

49.2 

68.9 

51.7 

45.4 

69.3 

51.3 

52.7 

54.3 

48.6 

54.6 

49.8 

54.3 

51.5 

N 

SE 

MSA 

Source: 

= Sample size. 

= Standard error. 

= Metropolitan statistical area. 

U.S. EPA analysis of 1994−1996, 1998 CSFII . 
Exposure Factors Handbook Page 

September 2011 11-33 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-19. Per Capita Intake of Individual Meats and Dairy Products Based on 1994−1996, 1998 CSFII (g/kg-day, edible portion, uncooked 

weight) 

Population Group N 

Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE 

Beef Pork Poultry Eggs 

Whole population 20,607 85.9 0.9 0.02 78.5 0.42 0.01 67.6 0.71 0.01 93.4 0.40 0.01 

Age Group 

 Birth to 1 year 1,486 25.3 0.4 0.04 17.7 0.15 0.02 30.1 0.66 0.05 27.9 0.30 0.04 

 1 to 2 years 2,096 85.5 1.7 0.06 69.7 0.72 0.03 73.7 1.7 0.05 92.3 1.3 0.04 

 3 to 5 years 4,391 90.8 1.8 0.04 79.8 0.84 0.02 73.0 1.5 0.03 95.1 0.91 0.03 

 6 to 12 years 2,089 92.7 1.3 0.04 82.4 0.59 0.03 67.1 0.93 0.03 95.8 0.51 0.02 

 13 to 19 years 1,222 91.1 1.0 0.05 81.5 0.40 0.03 65.5 0.68 0.03 95.4 0.33 0.02 

 20 to 49 years 4,677 86.1 0.8 0.03 78.9 0.37 0.01 69.0 0.64 0.02 94.1 0.31 0.01 

 50+ years 4,646 83.5 0.6 0.02 79.3 0.34 0.01 66.5 0.52 0.02 94.0 0.33 0.01 

Season 

 Fall 4,687 85.0 0.9 0.05 78.5 0.41 0.02 69.7 0.76 0.03 93.1 0.39 0.02 

 Spring 5,308 86.4 0.9 0.03 78.1 0.44 0.02 66.8 0.70 0.02 93.5 0.41 0.02 

 Summer 5,890 85.7 0.9 0.03 78.1 0.42 0.02 65.4 0.69 0.02 93.3 0.39 0.01 

 Winter 4,722 86.7 0.9 0.02 79.1 0.40 0.02 68.6 0.70 0.02 93.8 0.39 0.02 

Race 

 American Indian, Alaskan Native 177 87.9 1.3 0.21 85.2 0.49 0.06 78.1 0.62 0.07 94.5 0.49 0.06 

 Asian, Pacific Islander 557 78.6 0.9 0.08 71.5 0.63 0.11 78.1 0.90 0.09 84.7 0.46 0.05 

 Black 2,740 85.3 1.1 0.10 82.1 0.53 0.04 73.3 0.93 0.05 93.9 0.48 0.01 

 Other 1,638 85.0 1.1 0.05 79.4 0.48 0.03 68.7 0.83 0.06 89.9 0.62 0.05 

 White 15,495 86.4 0.9 0.02 78.0 0.39 0.01 66.1 0.66 0.01 93.9 0.36 0.01 

Region 

 Midwest 4,822 89.8 1.0 0.02 83.1 0.47 0.02 66.9 0.69 0.03 95.1 0.38 0.01 

 Northeast 3,692 82.0 0.8 0.08 72.1 0.41 0.02 68.3 0.78 0.04 91.2 0.36 0.02 

 South 7,208 86.1 0.9 0.02 79.8 0.42 0.02 67.2 0.70 0.02 94.2 0.39 0.01 

 West 4,885 85.1 0.9 0.04 77.0 0.36 0.03 68.4 0.70 0.03 92.5 0.44 0.02 

Urbanization 

 MSA, Central City 6,164 84.0 0.9 0.04 77.1 0.41 0.02 70.6 0.78 0.02 92.8 0.41 0.01 

 MSA, Outside Central City 9,598 85.9 0.9 0.02 77.2 0.39 0.01 68.5 0.72 0.02 93.4 0.39 0.01 

 Non-MSA 4,845 88.9 1.0 0.04 83.3 0.49 0.02 61.1 0.60 0.03 94.5 0.39 0.01 

N 

SE 

MSA 

Source: 

=Sample size. 

=Standard error. 

= Metropolitan statistical area. 

U.S. EPA analysis of 1994−1996, 1998 CSFII. 
Page Exposure Factors Handbook 

11-34 September 2011 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-20. Consumer-Only Intake of Individual Meats and Dairy Products Based on 1994−1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE N Mean SE N Mean SE N Mean SE 

Beef Pork Poultry Eggs 

Whole population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 50+ years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 American Indian, Alaskan Native 

 Asian, Pacific Islander 

 Black 

 Other 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 MSA, Central City 

 MSA, Outside Central City 

 Non-MSA 

17,116 

361 

1,795 

3,964 

1,932 

1,118 

4,058 

3,888 

3,894 

4,429 

4,855 

3,938 

157 

413 

2,280 

1,296 

12,970 

4,179 

2,936 

6,029 

3,972 

4,992 

7,937 

4,187 

1.1 

1.6 

2.0 

1.9 

1.4 

1.1 

1.0 

0.7 

1.1 

1.0 

1.1 

1.0 

1.5 

1.2 

1.3 

1.3 

1.0 

1.1 

1.0 

1.0 

1.1 

1.1 

1.0 

1.1 

0.02 

0.2 

0.06 

0.04 

0.04 

0.05 

0.04 

0.02 

0.06 

0.03 

0.03 

0.02 

0.15 

0.08 

0.11 

0.06 

0.02 

0.02 

0.08 

0.02 

0.04 

0.05 

0.02 

0.03 

15,431 

248 

1,488 

3,491 

1,731 

1,002 

3,732 

3,739 

3,547 

3,979 

4,354 

3,551 

144 

359 

2,122 

1,152 

11,654 

3,856 

2,502 

5,517 

3,556 

4,516 

7,028 

3,887 

0.53 

0.83 

1.0 

1.1 

0.72 

0.50 

0.47 

0.43 

0.5 

0.6 

0.5 

0.5 

0.6 

0.9 

0.6 

0.6 

0.5 

0.6 

0.6 

0.5 

0.5 

0.5 

0.5 

0.6 

0.01 

0.08 

0.04 

0.03 

0.03 

0.03 

0.01 

0.01 

0.02 

0.02 

0.02 

0.02 

0.05 

0.14 

0.04 

0.04 

0.01 

0.01 

0.02 

0.02 

0.03 

0.02 

0.02 

0.02 

13,702 

434 

1,552 

3,210 

1,421 

808 

3,221 

3,056 

3,217 

3,491 

3,810 

3,184 

116 

410 

2,025 

1,125 

10,026 

3,115 

2,522 

4,770 

3,295 

4,275 

6,461 

2,966 

1.1 

2.2 

2.2 

2.0 

1.4 

1.0 

0.9 

0.8 

1.1 

1.1 

1.1 

1.0 

0.8 

1.2 

1.3 

1.2 

1.0 

1.0 

1.1 

1.0 

1.0 

1.1 

1.0 

1.0 

0.01 

0.1 

0.06 

0.04 

0.04 

0.04 

0.02 

0.02 

0.03 

0.02 

0.03 

0.03 

0.08 

0.11 

0.05 

0.07 

0.02 

0.03 

0.03 

0.02 

0.03 

0.02 

0.02 

0.03 

18,450 

402 

1,936 

4,171 

2,001 

1,167 

4,399 

4,374 

4,211 

4,751 

5,245 

4,243 

159 

434 

2,462 

1,404 

13,991 

4,398 

3,236 

6,510 

4,306 

5,475 

8,565 

4,410 

0.42 

1.1 

1.4 

0.96 

0.53 

0.34 

0.33 

0.35 

0.4 

0.4 

0.4 

0.4 

0.5 

0.5 

0.5 

0.7 

0.4 

0.4 

0.4 

0.4 

0.5 

0.4 

0.4 

0.4 

0.01 

0.1 

0.04 

0.03 

0.02 

0.02 

0.01 

0.01 

0.02 

0.02 

0.01 

0.02 

0.07 

0.06 

0.02 

0.05 

0.01 

0.01 

0.02 

0.01 

0.02 

0.01 

0.01 

0.01 

N =Sample size. 

SE=Standard error. 

MSA = Metropolitan statistical area. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 
Exposure Factors Handbook Page 

September 2011 11-35 

Chapter 11—Intake of Meats, Dairy Products, and Fats Exposure Factors Handbook 

Table 11-21. Quantity (as-consumed) of Meat and Dairy Products Consumed per Eating Occasion and Percentage of Individuals Using These 

Foods in Two Days 

Quantity Consumed per Eating Occasion (g) 

Food category 

2 to 5 years old 6 to 11 years old 12 to 19 years old 

Males and Females 

(N = 2,109) 

Males and Females 

(N = 1,432) 

Males 

(N = 696) 

Females 

(N = 702) 

PC Mean SE PC Mean SE PC Mean SE PC Mean SE 

Meat 

Beef steaks 

Beef roasts 

Ground beef 

Ham 

Pork chops 

Bacon 

Pork breakfast sausage 

Frankfurters and luncheon meats 

Total chicken and turkey 

Chicken 

Turkey 

11.1 

5.2 

59.5 

6.9 

11.0 

10.4 

5.3 

51.7 

63.8 

44.6 

5.1 

58 

49 

31 

35 

48 

15 

33 

49 

46 

52 

63 

4 

5 

1 

4 

3 

1 

2 

1 

1 

1 

7 

11.3 

4.8 

63.7 

8.5 

10.1 

9.7 

6.0 

50.9 

53.8 

36.0 

5.7 

87 

67 

41 

40 

62 

19 

32 

57 

62 

70 

66 

9 

7 

1 

4 

4 

2 

3 

2 

2 

3 

5 

9.5 

5.1 

73.4 

11.6 

11.6 

14.9 

6.3 

46.7 

58.4 

34.3 

8.2 

168 

233a 

66 

68 

100 

25 

40a 

76 

100 

117 

117 

14 

149a 

3 

7 

8 

2 

4a 

3 

4 

5 

14 

9.4 

5.5 

61.5 

9.9 

8.5 

11.1 

3.3 

38.5 

54.1 

36.1 

5.8 

112 

97a 

52 

40 

72 

18 

40a 

57 

71 

80 

60a 

10 

16a 

3 

5 

7 

1 

5a 

3 

2 

3 

9a 

Dairy Product 

Fluid milk (all) 

Fluid milk consumed with cereal 

Whole milk 

Whole milk consumed with cereal 

Lowfat milk 

Lowfat milk consumed with cereal 

Skim milk 

Skim milk consumed with cereal 

Cheese, other than cream or cottage 

Ice cream and ice milk 

Boiled, poached, and baked eggs 

Fried eggs 

Scrambled eggs 

92.5 

68.1 

50.0 

33.8 

47.5 

31.5 

7.8 

4.9 

53.2 

18.4 

8.0 

17.3 

10.4 

196 

149 

202 

161 

189 

136 

171 

131 

24 

92 

36 

48 

59 

3 

4 

3 

5 

3 

4 

9 

11 

1 

3 

3 

1 

4 

89.2 

64.7 

39.5 

26.2 

52.8 

32.7 

11.1 

7.5 

50.4 

21.1 

8.2 

14.0 

7.1 

241 

202 

244 

212 

238 

198 

225 

188 

29 

135 

34 

58 

72 

4 

5 

7 

11 

4 

4 

9 

14 

1 

4 

3 

2 

5 

72.3 

44.4 

30.0 

14.8 

39.6 

24.3 

9.7 

6.5 

61.1 

14.2 

5.0 

14.9 

7.1 

337 

276 

333 

265 

326 

277 

375 

285a 

38 

221 

44a 

83 

72 

8 

10 

13 

18 

8 

12 

38 

23a 

2 

12 

9a 

5 

5 

64.4 

42.7 

22.4 

14.1 

32.4 

21.1 

13.5 

8.3 

53.9 

15.2 

7.7 

13.5 

8.9 

262 

222 

258 

235 

262 

227 

255 

181 

27 

187 

45 

59 

103 

8 

8 

7 

13 

13 

12 

14 

13 

1 

14 

7 

3 

9 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 11-36 September 2011 

Table 11-21. Quantity (as-consumed) of Meat and Dairy Products Consumed per Eating Occasion and Percentage of Individuals Using These Foods 

in Two Days (continued) 

Quantity Consumed per Eating Occasion (g) 

Food category PC 

20 to 39 years old 40 to 59 years old 60 years and older 

Males Females 

(N = 1,543) (N = 1,449) 

Males Females 

(N = 1,663) (N = 1,694 ) 

Males Females 

(N = 1,545) (N = 1,429) 

Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE 

Meat 

Beef steaks 

Beef roasts 

Ground beef 

Ham 

Pork chops 

Bacon 

Pork breakfast sausage 

Frankfurters and luncheon meats 

Total chicken and turkey 

Chicken 

Turkey 

17.1 

6.9 

65.3 

10.8 

12.8 

14.1 

6.6 

46.2 

57.3 

37.1 

6.8 

202 

132 

80 

78 

117 

26 

57 

88 

112 

122 

131 

20 

14 

4 

7 

8 

1 

4 

6 

4 

3 

21 

11.8 

5.8 

51.5 

9.7 

12.5 

12.4 

5.1 

35.6 

57.8 

35.5 

5.6 

121 

85 

52 

47 

71 

18 

37 

61 

78 

92 

76 

8 

8 

2 

4 

4 

1 

3 

2 

2 

3 

6 

18.3 

9.9 

50.0 

13.5 

14.3 

17.5 

6.6 

44.9 

56.8 

34.5 

8.5 

159 

119 

82 

68 

108 

22 

48 

79 

111 

124 

115 

7 

8 

3 

5 

6 

1 

4 

2 

4 

4 

12 

10.7 

9.6 

44.6 

12.2 

13.0 

14.8 

5.8 

34.3 

58.7 

36.0 

8.8 

117 

74 

57 

50 

67 

18 

38 

59 

80 

87 

81 

6 

5 

2 

4 

4 

1 

4 

2 

2 

2 

8 

13.4 

11.7 

40.7 

15.2 

16.4 

20.6 

10.7 

41.6 

53.8 

32.1 

7.7 

129 

102 

73 

56 

89 

19 

48 

62 

87 

99 

80 

7 

6 

3 

3 

3 

1 

4 

2 

3 

3 

7 

9.5 

8.8 

36.2 

14.4 

13.1 

17.4 

5.5 

33.9 

57.8 

34.0 

7.2 

95 

80 

62 

45 

62 

16 

34 

51 

71 

79 

77 

6 

4 

3 

3 

3 

1 

3 

2 

2 

2 

7 

Dairy Product 

Fluid milk (all) 

Fluid milk consumed with cereal 

Whole milk 

Whole milk consumed with cereal 

Lowfat milk 

Lowfat milk consumed with cereal 

Skim milk 

Skim milk consumed with cereal 

Cheese, other than cream or cottage 

Ice cream and ice milk 

Boiled, poached, and baked eggs 

Fried eggs 

Scrambled eggs 

58.0 

26.9 

22.9 

7.9 

29.4 

14.0 

9.3 

5.6 

63.8 

14.7 

9.4 

15.2 

10.7 

291 

275 

278 

272 

298 

284 

318 

260 

39 

200 

50 

86 

89 

9 

12 

11 

16 

15 

22 

13 

12 

2 

2 

4 

2 

4 

61.3 

32.4 

22.4 

8.7 

29.4 

15.2 

15.5 

9.3 

52.6 

13.6 

10.4 

14.6 

7.8 

209 

198 

202 

216 

198 

181 

235 

207 

30 

136 

39 

61 

74 

6 

5 

10 

14 

7 

5 

11 

10 

1 

6 

3 

3 

3 

60.5 

30.1 

20.3 

6.2 

31.2 

16.1 

15.1 

8.7 

48.3 

18.0 

12.0 

20.9 

11.1 

238 

211 

223 

216 

242 

212 

244 

197 

36 

173 

45 

83 

83 

6 

7 

15 

16 

7 

10 

12 

11 

1 

6 

3 

2 

3 

60.2 

30.2 

19.0 

6.1 

27.7 

13.1 

19.2 

11.8 

46.3 

14.2 

14.2 

17.5 

8.0 

169 

166 

142 

183 

159 

151 

193 

173 

29 

141 

38 

60 

66 

5 

5 

7 

10 

5 

7 

7 

7 

1 

8 

2 

2 

3 

73.9 

48.1 

22.3 

10.1 

40.2 

26.5 

17.7 

12.4 

40.9 

22.7 

15.7 

24.6 

12.0 

189 

170 

188 

177 

189 

165 

186 

174 

33 

138 

45 

70 

73 

5 

5 

9 

10 

5 

5 

9 

9 

2 

5 

3 

2 

4 

71.6 

46.6 

19.7 

9.9 

37.8 

24.4 

21.6 

14.2 

35.4 

18.9 

16.1 

18.3 

9.3 

154 

140 

137 

156 

161 

134 

154 

135 

26 

107 

39 

56 

64 

4 

6 

8 

13 

6 

5 

9 

9 

1 

4 

2 

2 

5 a 

N 

PC 

SE 

Source: 

Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation. 

= Sample size. 

= Percent consuming at least once in 2 days . 

= Standard error of the mean. 

Smiciklas-Wright et al. (2002), based on 1994−1996 CSFII data. 
 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-22. Consumption of Milk, Yogurt, and Cheese: Median Daily Servings (and 

ranges) by Demographic and Health Characteristics 

Subject Characteristic N Milk, Yogurt, and Cheese 

Sex 

Females 80 1.6 (0.2−5.6) 

Males 50 1.5 (0.3−7.4) 

Ethnicity 

African American 44 1.9 (0.2−4.5) 

European American 47 1.6 (0.2−5.6) 

Native American 39 1.3 (0.5−7.4) 

Age 

70 to 74 years 42 1.8 (0.3−7.4) 

75 to 79 years 36 1.6 (0.2−5.6) 

80 to 84 years 36 1.4 (0.2−4.5) 

85+ years 16 1.6 (0.2−3.8) 

Marital Status 

Married 49 1.5 (0.2−7.4) 

Not Married 81 1.7 (0.2−5.4) 

Education 

8th grade or less 37 1.8 (0.2−5.4) 

9th to 12th grades 47 1.6 (0.2−5.6) 

> High School 46 1.4 (0.3−7.4) 

Denture 

Yes 83 1.5 (0.2−7.4) 

No 47 1.6 (0.3−5.6) 

Chronic Disease 

0 7 2.0 (0.8−4.5) 

1 31 1.8 (0.3−5.6) 

2 56 1.6 (0.2−7.4) 

3 26 1.2 (0.2−4.8) 

4+ 10 1.5 (0.5−4.5) 

Weighta 

≤130 pounds 18 1.3 (0.3−5.4) 

131 to 150 pounds 32 1.6 (0.5−5.6) 

151 to 170 pounds 27 1.8 (0.2−4.5) 

171 to 190 pounds 22 1.6 (0.2−3.7) 

≥191 pounds 29 1.5 (0.2−7.4) a = Two missing values. 

N = Number of subjects. 

Source: Vitolins et al. (2002). 

Exposure Factors Handbook Page
 

September 2011 11-37
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-23. Characteristics of the Feeding Infants and Toddlers Study (FITS) Sample Population 

Sample Size Percentage of Sample 

Sex 

Males 

Females 

1,549 

1,473 

51.3 

48.7 

Age of Child 

4 to 6 months 

7 to 8 months 

9 to 11 months 

12 to 14 months 

15 to 18 months 

19 to 24 months 

862 

483 

679 

374 

308 

316 

28.5 

16.0 

22.5 

12.4 

10.2 

10.4 

Child’s Ethnicity 

Hispanic or Latino 

Non-Hispanic or Latino 

Missing 

367 

2,641 

14 

12.1 

87.4 

0.5 

Child’s Race 

White 

Black 

Other 

2,417 

225 

380 

80.0 

7.4 

12.6 

Urbanicity 

Urban 

Suburban 

Rural 

Missing 

1,389 

1,014 

577 

42 

46.0 

33.6 

19.1 

1.3 

Household Income 

Under $10,000 

$10,000 to $14,999 

$15,000 to $24,999 

$25,000 to $34,999 

$35,000 to $49,999 

$50,000 to $74,999 

$75,000 to $99,999 

$100,000 and Over 

Missing 

48 

48 

221 

359 

723 

588 

311 

272 

452 

1.6 

1.6 

7.3 

11.9 

23.9 

19.5 

10.3 

9.0 

14.9 

Receives WIC 

Yes 

No 

Missing 

821 

2,196 

5 

27.2 

72.6 

0.2 

Sample Size (Unweighted) 3,022 100.0 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Devaney et al. (2004). 

Page Exposure Factors Handbook 

11-38 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 11-24. Percentage of Infants and Toddlers Consuming Milk, Meat, or Other Protein Sources 

Percentage of Infants and Toddlers Consuming at Least Once in a 

Day Food Group/Food 4 to 6 7 to 8 9 to 11 12 to 14 15 to 18 19 to 24 

months months months months months months 

Cow’s Milk 0.8 2.9 20.3 84.8 88.3 87.7 

Whole 0.5 2.4 15.1 68.8 71.1 58.8 

Reduced-fat or Non-fat 0.3 0.5 5.3 17.7 20.7 38.1 

Unflavored 0.8 2.9 19.5 84.0 87.0 86.5 

Flavored 0.0 0.0 0.9 1.8 4.4 5.6 

Soy Milk	 0.0 0.5 1.7 1.5 3.9 3.8 

Any Meat or Protein Source 14.2 54.9 79.2 91.3 92.7 97.2 

Baby Food Meat 1.7 4.0 3.1 1.1 0.0 0.0 

Non-baby Food Meat 1.5 8.4 33.7 60.3 76.3 83.7 

Other Protein Sources 2.7 9.7 36.1 59.2 66.8 68.9 

Dried Beans and Peas, Vegetarian Meat Substitutes 0.6 1.3 3.3 7.0 6.6 9.9 

Eggs 0.7 2.9 7.3 17.0 25.0 25.2 

Peanut Butter, Nuts, and Seeds 0.0 0.5 1.9 8.8 11.6 10.4 

Cheese 0.4 2.1 18.5 34.0 39.1 41.1 

Yogurt 1.2 4.1 15.7 14.9 20.2 15.3 

Protein Sources in Mixed Dishes 11.0 43.3 46.2 30.1 25.5 20.5 

Baby Food Dinners 9.5 39.8 33.5 10.2 2.4 1.3 

Beans and Rice, Chili, Other Bean Mixtures 0.0 0.0 0.9 1.2 2.1 2.0 

Mixtures with Vegetables and/or Rice/Pasta 0.9 1.2 4.7 8.2 9.0 7.8 

Soupa	 0.9 3.4 10.1 12.5 13.8 11.5 

Types of Meatb 

Beef 0.9 2.6 7.7 16.1 16.3 19.3 

Chicken or Turkey 2.0 7.3 22.4 33.0 46.9 47.3 

Fish and Shellfish 0.0 0.5 1.9 5.5 8.7 7.1 

Hotdogs, Sausages, and Cold cuts 0.0 2.1 7.1 16.4 20.1 27.0 

Pork/Ham 0.3 1.7 4.0 9.7 11.2 13.9 

Other 0.3 0.6 2.5 2.8 2.1 3.9 a	 The amount of protein actually provided by soups varies. Soups could not be sorted reliably into different food 

groups because all soups were assigned the same 2-digit food code and many food descriptions lacked detail about 

major soup ingredients. b	 Includes baby food and non-baby food sources. 

Source:	 Fox et al. (2004). 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page
 

September 2011 11-39
 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-40 September 2011 

Table 11-25. Characteristics of WIC Participants and Non-Participantsa (percentages) 

Infants 4 to 6 months Infants 7 to 11 months Toddlers 12 to 24 months 

WIC NonParticipant Participant WIC NonParticipant Participant WIC NonParticipant Participant 

Sex 

 Males 

 Females 

Child’s Ethnicity 

 Hispanic or Latino 

 Non-Hispanic or Latino 

Child’s Race 

 White 

 Black 

 Other 

Child In Daycare 

 Yes 

 No 

Age of Mother 

 14 to 19 years 

 20 to 24 years 

 25 to 29 years 

 30 to 34 years 

 35 years or Older 

 Missing 

Mother’s Education 

 11th Grade or Less 

 Completed High School 

 Some Postsecondary 

 Completed College 

 Missing 

Parent’s Marital Status 

 Married 

 Not Married 

 Missing 

Mother or Female Guardian Work 

 Yes 

 No 

 Missing 

Urbanicity 

 Urban 

 Suburban 

 Rural 

 Missing 

 Sample Size (Unweighted) 

55 

45 

20 

80 

69 

15 

22 

39 

61 

18 

33 

29 

 9

 9

2 

23 

35 

33 

 7

2 

49 

50 

1 

46 

53 

1 

34 

36 

28 

 2

265 

54 

46 

b 

11 

89 

b 

84 

 4

11 

38 

62 

1 

13 

29 

33 

23 

2 

b 

2 

19 

26 

53 

1 

b 

93 

 7

1 

51 

48 

1 

b 

55 

 31

 13

 1 

597 

55 

45 

24 

76 

63 

17 

20 

34 

66 

13 

38 

23 

15 

11 

1 

15 

42 

32 

 9

2 

57 

42 

1 

45 

54 

1 

37 

 31

 30

 2 

351 

51 

49 

b 

8 

92 

b 

86 

 5

9 

b 

46 

54 

1 

11 

30 

36 

21 

1 

b 

2 

20 

27 

51 

0 

b 

93 

 7

0 

c 

60 

40 

0 

b 

50 

 34

 15

 1 

808 

57 

43 

22 

78 

67 

13 

20 

43 

57 

9 

33 

29 

18 

11 

0 

17 

42 

31 

 9

1 

58 

41 

1 

55 

45 

0 

35 

 35

 28

 2 

205 

52 

48 

b 

10 

89 

b 

84 

 5

11 

c 

53 

47 

1 

14 

26 

34 

26 

1 

b 

3 

19 

28 

48 

2 

b 

88 

11 

1 

c 

61 

38 

1 

b 

48 

 35

 16

 2 

791 a 

b 

c 

WIC 

Source: 

χ 2 test were conducted to test for statistical significance in the differences between WIC participants and non-participants within each 

age group for each variable. The results of χ2 test are listed next to the variable under the column labeled non-participants for each of 

the three age groups. 

= p>0.01; non-participants significantly different from WIC participants on the variable. 

= p<0.05; non-participants significantly different from WIC participants on the variable. 

= Special Supplemental Nutrition Program for Women, Infants, and Children. 

Ponza et al. (2004). 
 

 

Table 11-26. Food Choices for Infants and Toddlers by WIC Participation Status 

Infants 4 to 6 months Infants 7 to 11 months Toddlers 12 to 24 months 

WIC Non- WIC Non- WIC NonParticipant Participant Participant Participant Participant Participant
 

Cow’s Milk 1.0 0.6 11.4 13.2 92.3 85.8a 

Meat or Other Protein Source 

Baby Food Meat 

Non-baby Meat 

Eggs 

0.9 

3.7 

0.9 

2.0 

0.5b 

0.6 

3.3 

25.0 

8.5 

3.6 

22.0 

4.2b 

0.0 

77.7 

24.1 

0.3 

75.1 

23.0 

Peanut Butter, Nuts, Seeds 0.0 0.0 1.4 1.3 12.9 9.8 

Cheese 0.0 0.6 9.0 12.5 38.5 38.8 

Yogurt 0.8 1.4 5.5 13.3b 9.3 18.9b 

Sample Size (unweighted) 265 597 351 808 205 791
 a = p<0.05; non-participants significantly different from WIC participants.
 b = p<0.01; non-participants significantly different from WIC participants.
 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
 

Source:	 Ponza et al. (2004). 

 

 

 

 

 

 

 

 

 

 

c 

Table 11-27. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of
 

Milk, Meats, or Other Protein Sources on a Given Day
 Age 4 to 5 months Age 6 to 11 months Age 12 to 24 months 

Hispanic 

(N = 84) 

Non-Hispanic 

(N = 538) 

Hispanic 

(N = 163) 

Non-Hispanic 

(N = 1,228) 

Hispanic 

(N = 124) 

Non-Hispanic 

(N = 871) 

Milk 

Fed Any Cow’s or Goat Milk - - 7.5† 11.3 85.6 87.7 

Fed Cow’s Milk 

Whole - - 5.6† 8.3 61.7 66.3 

Reduced Fat or Non-fat - - 2.2† 3.0 29.0 27.0 

Meat or Other Protein Source 

Any Meat or Protein Sourcea 9.7† 5.3 71.6 62.0 90.3 94.7 

Non-baby Food Meat - - 22.5 19.2 72.3 76.0 

Other Protein Sources 1.4† - 26.5 21.2 70.1 65.3 

Beans and Peas 1.4† - 5.8† 1.8 19.1c 6.5 

Eggs - - 9.5 4.2 26.4 22.5 

Cheese - - 11.2 9.4 29.3 40.2 

Yogurt - - 7.7 9.8 15.7 17.0 

Protein Sources in Mixed Dishes 7.5† 4.4 44.8 41.6 33.3 22.7 

Baby Food dinners 

Soupb 

6.9† 

-

3.9 

-

24.7c 

16.3d 

35.3 

5.1 

3.5† 

23.4c 

3.9 

10.7 

Types of Meat

a 

Beef - - 5.0† 4.6 25.2 16.0 

Chicken and Turkey - - 11.2 11.9 46.5 43.6 

Hotdogs, Sausages, and Cold Cuts - - 7.2† 3.4 14.8 23.3 

Pork/Ham - - 3.8† 1.7 11.7 12.1 a	 Includes baby food and non-baby food sources. b	 The amount of protein actually provided by soups varies. Soups could not be sorted reliably into different food groups because many 

food descriptions lacked detail about major soup ingredients. 

= Significantly different from non-Hispanic at p <0.05. d = Significantly different from non-Hispanic at p >0.01. 

- = Less than 1% of the group consumed this food on a given day. 

† = Statistic is potentially unreliable because of a high coefficient of variation. 

N = Sample size. 

Source:	 Mennella et al. (2006). 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page
 

September 2011 11-41
 
 

 

 

 

 

 

 

 

 

 

 

 

 

Table 11-29. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly Consumed 

by Toddlers From the 2002 Feeding Infants and Toddlers Study 

Food Group Reference Unit 

12 to 14 months 

(N = 371) 

15 to 18 months 

(N = 312) 

19 to 24 months 

(N = 320) 

Mean ± SE 

Milk 

Milk fluid ounce 5.6± 0.14 5.9± 0.14 6.2± 0.17 

Milk, as a beverage 

Milk, on cereal 

fluid ounce 

fluid ounce 

5.7± 0.14 

3.4± 0.37 

6.1± 0.14 

2.7± 0.26 

6.4± 0.17 

3.6± 0.29 

Meats and other protein source 

All meats ounce 1.2± 0.06 1.3± 0.08 1.3± 0.07 

Beef ounce 0.8± 0.08 1.2± 0.15 1.2± 0.14 

Chicken or turkey, plain ounce 1.3± 0.10 1.3± 0.16 1.3± 0.10 

Hot dogs, luncheon meats, sausages 

Chicken, breadeda 

ounce 

ounce 

1.3± 0.13 

1.5 ± 0.14 

1.5± 0.13 

1.5± 0.13 

1.5± 0.12 

1.8± 0.12 

nugget 2.4 ± 0.22 2.4± 0.21 2.8± 0.19 

Scrambled eggs 

Peanut butter 

cup 

tablespoon 

0.2± 0.02 

0.7± 0.08 

0.3± 0.03 

0.7± 0.09 

0.3± 0.02 

0.9± 0.13 

Yogurt ounce 3.4± 0.19 3.8± 0.26 3.8± 0.28 

Cheese ounce 0.8± 0.05 0.8± 0.05 0.7± 0.04 a Not included in total for all meats because weight includes breading.
 

N = Number of respondents.
 

SE = Standard error of the mean. 

Source: Fox et al. (2006). 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-28. Average Portion Sizes per Eating Occasion of Meats and Dairy Products Commonly Consumed 

by Infants From the 2002 Feeding Infants and Toddlers Study 

4 to 5 months 6 to 8 months 9 to 11 months 

Food Group Reference Unit (N = 624) (N = 708) (N = 687) 

Mean ± SE 

Non-baby food meats ounce - 0.9 ± 0.16 0.8 ± 0.05 

Cheese ounce - - 0.7 ± 0.05 

Scrambled eggs cup - - 0.2 ± 0.02 

Yogurt ounce - - 3.1 ± 0.20 

Baby food dinners ounce 2.9 ± 0.24 3.3 ± 0.09 3.8 ± 0.11 

- = Cell size was too small to generate a reliable estimate. 

N = Number of respondents. 

SE = Standard error of the mean. 

Source: Fox et al. (2006). 

Page Exposure Factors Handbook 

11-42 September 2011 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page
 

September 2011 11-43
 

Table 11-30. Per Capita Total Fat Intake (g/day) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

Birth to <1 year 

All 

Females 

Males 

Birth to <1 month 

All 

Females 

Males 

1 to <3 months 

All 

Females 

Males 

3 to <6 months 

All 

Females 

Males 

6 to <12 months 

All 

Females 

Males 

1 to <2 years 

All 

Females 

Males 

2 to <3 years 

All 

Females 

Males 

3 to <6 years 

All 

Females 

Males 

6 to <11 years 

All 

Females 

Males 

11 to <16 years 

All 

Females 

Males 

1,422 

728 

694 

88 

50 

38 

245 

110 

135 

411 

223 

188 

678 

345 

333 

1,002 

499 

503 

994 

494 

500 

4,112 

2,018 

2,094 

1,553 

742 

811 

975 

493 

482 

29 

28 

30 

17 

19 

15 

22 

20 

23 

28 

27 

30 

33 

32 

34 

46 

45 

46 

51 

49 

52 

59 

56 

61 

68 

64 

72 

80 

69 

91 

18 

17 

18 

16 

15 

18 

18 

16 

19 

17 

17 

18 

17 

17 

16 

19 

18 

20 

21 

20 

21 

22 

21 

23 

24 

22 

25 

38 

29 

42 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.1 

0 

0.2 

8.5 

5.1 

11 

24 

25 

23 

27 

24 

29 

34 

33 

35 

41 

38 

43 

42 

37 

50 

19 

18 

20 

0 

0 

0 

0 

0 

0 

20 

16 

22 

25 

24 

25 

33 

33 

32 

37 

35 

39 

44 

43 

45 

50 

48 

55 

56 

49 

64 

31 

30 

32 

19 

18 

19 

27 

24 

28 

31 

29 

31 

34 

33 

34 

43 

43 

44 

48 

46 

50 

56 

54 

59 

66 

61 

70 

74 

65 

84 

40 

39 

40 

32 

29 

31 

34 

33 

34 

39 

38 

39 

43 

43 

44 

55 

54 

56 

60 

59 

61 

70 

68 

72 

81 

77 

86 

97 

82 

111 

59 

57 

61 

52 

39 

43 

47 

45 

55 

52 

51 

50 

62 

62 

62 

79 

77 

80 

87 

83 

89 

99 

96 

103 

111 

101 

115 

145 

123 

163 

107 

92 

107 

64 

52 

64 

75 

50 

75 

107 

74 

107 

100 

92 

100 

159 

116 

159 

197 

127 

197 

218 

194 

218 

179 

156 

179 

342 

259 

342 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-44 September 2011 

Table 11-30. Per Capita Total Fat Intake (g/day) (continued) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

16 to <21 years 

All 

Females 

Males 

21 to <31 years 

All 

Females 

Males 

31 to <41 years 

All 

Females 

Males 

41 to <51 years 

All 

Females 

Males 

51 to <61 years 

All 

Females 

Males 

61 to <71 years 

All 

Females 

Males 

71 to <81 years 

All 

Females 

Males 

81+ years 

All 

Females 

Males 

743 

372 

371 

1,412 

682 

730 

1,628 

781 

847 

1644 

816 

828 

1,578 

768 

810 

1,507 

719 

788 

888 

421 

467 

392 

190 

202 

85 

79 

92 

84 

65 

103 

83 

64 

101 

78 

63 

93 

73 

58 

88 

66 

53 

78 

60 

51 

68 

57 

49 

64 

47 

39 

53 

45 

31 

48 

43 

31 

45 

39 

29 

42 

37 

26 

40 

33 

24 

35 

27 

22 

29 

29 

23 

32 

37 

35 

41 

36 

30 

50 

36 

29 

49 

36 

31 

46 

31 

27 

39 

29 

26 

37 

28 

27 

34 

24 

22 

31 

54 

49 

57 

53 

43 

68 

52 

42 

69 

50 

43 

63 

46 

39 

57 

42 

36 

53 

41 

37 

48 

36 

32 

43 

76 

75 

77 

76 

59 

93 

74 

58 

96 

70 

59 

87 

66 

56 

82 

60 

49 

73 

55 

49 

67 

54 

48 

61 

108 

96 

114 

104 

81 

125 

106 

79 

127 

99 

78 

119 

90 

73 

110 

80 

68 

98 

72 

62 

86 

69 

64 

82 

168 

154 

186 

164 

126 

181 

162 

121 

190 

153 

114 

166 

137 

104 

156 

123 

96 

138 

104 

86 

114 

102 

84 

106 

463 

317 

463 

445 

201 

445 

376 

228 

376 

267 

208 

267 

306 

165 

306 

235 

184 

235 

201 

158 

201 

227 

132 

227 a 

N 

SE 

Source: 

Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants. 

= Sample size. 

= Standard error. 

U.S. EPA (2007). 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page
 

September 2011 11-45
 

Table 11-31. Per Capita Total Fat Intake (g/kg-day) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

Birth to <1 year 

All 

Females 

Males 

Birth to <1 month 

All 

Females 

Males 

1 to <3 months 

All 

Females 

Males 

3 to <6 months 

All 

Females 

Males 

6 to <12 months 

All 

Females 

Males 

1 to <2 years 

All 

Females 

Males 

2 to <3 years 

All 

Females 

Males 

3 to <6 years 

All 

Females 

Males 

6 to <11 years 

All 

Females 

Males 

11 to <16 years 

All 

Females 

Males 

1,422 

728 

694 

88 

50 

38 

245 

110 

135 

411 

223 

188 

678 

345 

333 

1,002 

499 

503 

994 

494 

500 

4,112 

2,018 

2,094 

1,553 

742 

811 

975 

493 

482 

4.0 

4.1 

4.0 

5.2 

5.9 

4.3 

4.5 

4.3 

4.7 

4.1 

4.2 

4.1 

3.7 

3.7 

3.6 

4.0 

4.1 

3.9 

3.6 

3.7 

3.6 

3.4 

3.4 

3.5 

2.6 

2.4 

2.7 

1.6 

1.4 

1.8 

2.8 

2.8 

2.8 

4.9 

4.6 

5.3 

3.8 

3.6 

3.9 

2.7 

2.8 

2.5 

1.8 

1.9 

1.7 

1.7 

1.6 

1.7 

1.5 

1.6 

1.5 

1.3 

1.3 

1.4 

1.1 

1.0 

1.1 

0.8 

0.7 

0.9 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1.0 

0.7 

1.3 

2.1 

2.2 

1.9 

1.9 

1.8 

2.0 

1.9 

1.8 

1.9 

1.3 

1.3 

1.4 

0.8 

0.7 

0.9 

2.3 

2.4 

2.3 

0 

0 

0 

0 

0 

0 

2.4 

2.3 

2.6 

2.7 

2.8 

2.6 

2.8 

3.0 

2.6 

2.6 

2.4 

2.6 

2.4 

2.4 

2.4 

1.7 

1.6 

1.8 

1.1 

0.9 

1.2 

4.1 

4.3 

4.0 

5.7 

6.2 

4.7 

4.9 

4.8 

4.9 

4.3 

4.5 

4.1 

3.8 

3.8 

3.7 

3.7 

3.7 

3.6 

3.4 

3.4 

3.4 

3.2 

3.1 

3.2 

2.3 

2.2 

2.4 

1.4 

1.3 

1.6 

5.6 

5.8 

5.5 

9.1 

8.4 

9.7 

6.8 

6.5 

7.0 

5.7 

6.0 

5.5 

4.8 

5.0 

4.6 

4.7 

5.0 

4.5 

4.4 

4.4 

4.3 

4.0 

4.0 

4.1 

3.0 

2.8 

3.1 

2.0 

1.7 

2.1 

8.9 

8.7 

9.2 

16 

13 

18 

12 

11 

10 

8.2 

8.2 

8.2 

7.0 

7.0 

6.8 

7.1 

6.9 

7.2 

6.4 

6.6 

6.1 

5.8 

5.8 

5.8 

4.2 

4.0 

4.4 

3.0 

2.6 

3.3 

20 

18 

20 

20 

16 

20 

18 

14 

18 

18 

18 

16 

11 

9.8 

11 

12 

9.7 

12 

12 

10 

12 

11 

11 

11 

9.9 

7.7 

9.9 

5.7 

5.0 

5.7 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-46 September 2011 

Table 11-31. Per Capita Total Fat Intake (g/kg-day) (continued) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

16 to <21 years 

All 

Females 

Males 

21 to <31 years 

All 

Females 

Males 

31 to <41 years 

All 

Females 

Males 

41 to <51 years 

All 

Females 

Males 

51 to <61 years 

All 

Females 

Males 

61 to <71 years 

All 

Females 

Males 

71 to <81 years 

All 

Females 

Males 

81+ years 

All 

Females 

Males 

743 

372 

371 

1,412 

682 

730 

1,628 

781 

847 

1,644 

816 

828 

1,578 

768 

810 

1,507 

719 

788 

888 

421 

467 

392 

190 

202 

1.3 

1.1 

1.4 

1.2 

1.0 

1.3 

1.1 

1.0 

1.2 

1.0 

0.9 

1.1 

0.9 

0.8 

1.0 

0.9 

0.8 

1.0 

0.8 

0.8 

0.9 

0.9 

0.8 

0.9 

0.66 

0.56 

0.73 

0.61 

0.52 

0.66 

0.55 

0.52 

0.54 

0.49 

0.43 

0.53 

0.46 

0.38 

0.50 

0.43 

0.39 

0.45 

0.37 

0.37 

0.37 

0.43 

0.39 

0.47 

0.54 

0.48 

0.63 

0.53 

0.44 

0.63 

0.49 

0.45 

0.59 

0.48 

0.43 

0.53 

0.42 

0.39 

0.47 

0.40 

0.36 

0.46 

0.40 

0.39 

0.42 

0.37 

0.35 

0.39 

0.81 

0.75 

0.85 

0.72 

0.65 

0.85 

0.69 

0.61 

0.85 

0.66 

0.61 

0.72 

0.61 

0.56 

0.65 

0.55 

0.50 

0.61 

0.56 

0.53 

0.61 

0.56 

0.54 

0.56 

1.2 

1.1 

1.2 

1.1 

0.9 

1.2 

1.0 

0.9 

1.2 

0.9 

0.9 

1.0 

0.86 

0.79 

0.95 

0.79 

0.74 

0.87 

0.78 

0.72 

0.82 

0.82 

0.82 

0.82 

1.6 

1.4 

1.7 

1.5 

1.3 

1.6 

1.4 

1.3 

1.5 

1.3 

1.2 

1.4 

1.2 

1.1 

1.3 

1.1 

1.0 

1.2 

1.0 

1.0 

1.1 

1.1 

1.1 

1.1 

2.7 

2.1 

2.9 

2.3 

2.0 

2.4 

2.1 

1.9 

2.3 

1.9 

1.7 

2.0 

1.7 

1.5 

1.9 

1.7 

1.5 

1.8 

1.5 

1.4 

1.5 

1.5 

1.5 

1.6 

6.0 

4.4 

6.0 

7.3 

3.7 

7.3 

4.7 

4.7 

4.3 

4.4 

2.9 

4.4 

3.8 

2.4 

3.8 

3.2 

3.2 

3.1 

3.2 

3.2 

2.6 

3.7 

2.1 

3.7 a 

N 

SE 

Source: 

Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitor ing and Assessing Childhood Exposures to 

Environmental Contaminants. 

= Sample size. 

= Standard error. 

U.S. EPA (2007). 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page 

September 2011 11-47 

 

 

Table 11-32. Consumer-Only Total Fat Intake (g/day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th Max 

Birth to <1 year 

All 1,301 31 16 7.0 24 32 41 61 107 

Females 664 30 16 5.1 24 32 40 58 92 

Males 637 32 16 9.0 25 33 41 62 107 

Birth to <1 month 

All 59 26 13 6.7 17 27 32 52 64 

Females 37 26 11 7.8 17 25 32 39 52 

Males 22 25 17 - - - - - 64 

1 to <3 months 

All 182 29 14 5.8 24 31 35 53 75 

Females 79 28 12 4.3 21 30 35 46 50 

Males 103 31 16 8.5 27 31 38 59 75 

3 to <6 months 

All 384 30 16 2.5 24 32 40 54 107 

Females 205 29 16 1.2 24 31 39 52 72 

Males 179 31 17 4.6 25 33 39 53 107 

6 to <12 months 

All 676 33 16 8.9 25 34 43 62 100 

Females 343 32 17 6.2 24 34 43 62 92 

Males 333 34 16 11 25 34 44 62 100 

1 to <2 year 

All 1,002 46 19 24 33 43 55 79 159 

Females 499 45 18 25 33 43 54 77 116 

Males 503 46 20 23 32 44 56 80 159 

2 to <3 years 

All 994 51 21 27 37 48 60 87 197 

Females 494 49 20 24 35 46 59 83 127 

Males 500 52 21 29 39 50 61 89 197 

3 to <6 years 

All 4,112 59 22 34 44 56 70 99 218 

Females 2,018 56 21 33 43 54 68 96 194 

Males 2,094 61 23 35 45 59 72 103 218 

6 to <11 years 

All 1,553 68 24 41 50 66 81 111 179 

Females 742 64 22 38 48 61 77 101 156 

Males 811 72 25 43 55 70 86 115 179 

11 to <16 years 

All 975 80 38 42 56 74 97 145 342 

Females 493 69 29 37 49 65 82 123 259 

Males 482 91 42 50 64 84 111 163 342 
 

Table 11-32. Consumer-Only Total Fat Intake (g/day) (continued) 

Percentiles Age Groupa N Mean SE 

10th 25th 50th 75th 95th Max 

16 to <21 years 

All 743 85 47 37 54 76 108 168 463 

Females 372 79 39 35 49 75 96 154 317 

Males 371 92 53 41 57 77 114 186 463 

21 to <31 years 

All 1,412 84 45 36 53 76 104 164 445 

Females 682 65 31 30 43 59 81 126 201 

Males 730 103 48 50 68 93 125 181 445 

31 to <41 years 

All 1,628 83 43 36 52 74 106 162 376 

Females 781 64 31 29 42 58 79 121 228 

Males 847 101 45 49 69 96 127 190 376 

41 to <51 years 

All 1,644 78 39 36 50 70 99 153 267 

Females 816 63 29 31 43 59 78 114 208 

Males 828 93 42 46 63 87 119 166 267 

51 to <61 years 

All 1,578 73 37 31 46 66 90 137 306 

Females 768 58 26 27 39 56 73 104 165 

Males 810 88 40 39 57 82 110 156 306 

61 to <71 years 

All 1,507 66 33 29 42 60 80 123 235 

Females 719 53 24 26 36 49 68 96 184 

Males 788 78 35 37 53 73 98 138 235 

71 to <81 years 

All 888 60 27 28 41 55 72 104 201 

Females 421 51 22 27 37 49 62 86 158 

Males 467 68 29 34 48 67 86 114 201 

81+ years 

All 392 57 29 24 36 54 69 102 227 

Females 190 49 23 22 32 48 64 84 132 

Males 202 64 32 31 43 61 82 106 227 

a Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring and Assessing Childhood Exposures 

to Environmental Contaminants. 

- = Percentiles were not calculated for sample sizes less than 30. 

N = Sample size. 

SE = Standard error. 

Source: U.S. EPA (2007). 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-48 September 2011 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page
 

September 2011 11-49
 

Table 11-33. Consumer-Only Total Fat Intake (g/kg-day) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

Birth to <1 year 

All 

Females 

Males 

Birth to <1 month 

All 

Females 

Males 

1 to <3 months 

All 

Females 

Males 

3 to <6 months 

All 

Females 

Males 

6 to <12 months 

All 

Females 

Males 

1 to <2 years 

All 

Females 

Males 

2 to <3 years 

All 

Females 

Males 

3 to <6 years 

All 

Females 

Males 

6 to <11 years 

All 

Females 

Males 

11 to <16 years 

All 

Females 

Males 

1,301 

664 

637 

59 

37 

22 

182 

79 

103 

384 

205 

179 

676 

343 

333 

1,002 

499 

503 

994 

494 

500 

4,112 

2,018 

2,094 

1,553 

742 

811 

975 

493 

482 

4.4 

4.5 

4.3 

7.8 

8.0 

7.4 

6.0 

5.9 

6.1 

4.4 

4.5 

4.3 

3.7 

3.7 

3.6 

4.0 

4.1 

3.9 

3.6 

3.7 

3.6 

3.4 

3.4 

3.5 

2.6 

2.4 

2.7 

1.6 

1.4 

1.8 

2.6 

2.6 

2.6 

4.1 

3.5 

4.9 

3.1 

2.9 

3.3 

2.5 

2.6 

2.4 

1.8 

1.9 

1.7 

1.7 

1.6 

1.7 

1.5 

1.6 

1.5 

1.3 

1.3 

1.4 

1.1 

1.0 

1.1 

0.80 

0.69 

0.86 

0.94 

0.67 

1.2 

1.4 

2.0 

-

1.0 

0.80 

1.8 

0.35 

0.14 

0.57 

1.0 

0.75 

1.3 

2.1 

2.2 

1.9 

1.9 

1.8 

2.0 

1.9 

1.8 

1.9 

1.3 

1.3 

1.4 

0.77 

0.67 

0.88 

2.9 

3.1 

2.8 

5.4 

5.3 

-

4.1 

4.3 

4.1 

3.1 

3.1 

3.1 

2.7 

2.8 

2.6 

2.8 

3.0 

2.6 

2.6 

2.4 

2.6 

2.4 

2.4 

2.4 

1.7 

1.6 

1.8 

1.1 

0.91 

1.2 

4.3 

4.5 

4.1 

8.0 

7.7 

-

6.0 

6.0 

6.0 

4.5 

4.7 

4.2 

3.8 

3.8 

3.7 

3.7 

3.7 

3.6 

3.4 

3.4 

3.4 

3.2 

3.1 

3.2 

2.3 

2.2 

2.4 

1.4 

1.3 

1.6 

5.8 

6.0 

5.6 

9.7 

9.1 

-

7.8 

7.7 

7.8 

5.8 

6.1 

5.6 

4.8 

5.0 

4.6 

4.7 

5.0 

4.5 

4.4 

4.4 

4.3 

4.0 

4.0 

4.1 

3.0 

2.8 

3.1 

2.0 

1.7 

2.1 

9.2 

8.9 

9.3 

16 

13 

-

12 

12 

12 

8.3 

8.2 

8.8 

7.0 

7.0 

6.8 

7.1 

6.9 

7.2 

6.4 

6.6 

6.1 

5.8 

5.8 

5.8 

4.2 

4.0 

4.4 

3.0 

2.6 

3.3 

20 

18 

20 

20 

16 

20 

18 

14 

18 

18 

18 

16 

11 

9.8 

11 

12 

9.7 

12 

12 

10 

12 

11 

11 

11 

9.9 

7.7 

9.9 

5.7 

5.0 

5.7 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-50 September 2011 

Table 11-33 Consumer-Only Total Fat Intake (g/kg-day) (continued) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

16 to <21 years 

All 

Females 

Males 

21 to <31 years 

All 

Females 

Males 

31 to <41 years 

All 

Females 

Males 

41 to <51 years 

All 

Females 

Males 

51 to <61 years 

All 

Females 

Males 

61 to <71 years 

All 

Females 

Males 

71 to <81 years 

All 

Females 

Males 

81+ years 

All 

Females 

Males 

743 

372 

371 

1,412 

682 

730 

1,628 

781 

847 

1,644 

816 

828 

1,578 

768 

810 

1,507 

719 

788 

888 

421 

467 

392 

190 

202 

1.3 

1.1 

1.4 

1.2 

1.0 

1.3 

1.1 

0.98 

1.2 

1.0 

0.92 

1.1 

0.94 

0.83 

1.0 

0.88 

0.79 

0.95 

0.82 

0.77 

0.87 

0.86 

0.83 

0.89 

0.66 

0.56 

0.73 

0.61 

0.52 

0.66 

0.55 

0.52 

0.54 

0.49 

0.43 

0.53 

0.46 

0.38 

0.50 

0.43 

0.39 

0.45 

0.37 

0.37 

0.37 

0.43 

0.39 

0.47 

0.54 

0.48 

0.63 

0.53 

0.44 

0.63 

0.49 

0.45 

0.59 

0.48 

0.43 

0.53 

0.42 

0.39 

0.47 

0.40 

0.36 

0.46 

0.40 

0.39 

0.42 

0.37 

0.35 

0.39 

0.81 

0.75 

0.85 

0.72 

0.65 

0.85 

0.69 

0.61 

0.85 

0.66 

0.61 

0.72 

0.61 

0.56 

0.65 

0.55 

0.50 

0.61 

0.56 

0.53 

0.61 

0.56 

0.54 

0.56 

1.2 

1.1 

1.2 

1.1 

0.93 

1.2 

1.0 

0.91 

1.2 

0.94 

0.86 

1.0 

0.86 

0.79 

0.95 

0.79 

0.74 

0.87 

0.78 

0.72 

0.82 

0.82 

0.82 

0.82 

1.6 

1.4 

1.7 

1.5 

1.3 

1.6 

1.4 

1.3 

1.5 

1.3 

1.2 

1.4 

1.2 

1.1 

1.3 

1.1 

0.99 

1.2 

1.0 

0.95 

1.1 

1.1 

1.1 

1.1 

2.7 

2.1 

2.9 

2.3 

2.0 

2.4 

2.1 

1.9 

2.3 

1.9 

1.7 

2.0 

1.7 

1.5 

1.9 

1.7 

1.5 

1.8 

1.5 

1.4 

1.5 

1.5 

1.5 

1.6 

6.0 

4.4 

6.0 

7.3 

3.7 

7.3 

4.7 

4.7 

4.3 

4.4 

2.9 

4.4 

3.8 

2.4 

3.8 

3.2 

3.2 

3.1 

3.2 

3.2 

2.6 

3.7 

2.1 

3.7 a 

-

N 

SE 

Source: 

Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants. 

= Percentiles were not calculated for sample sizes less than 30. 

= Sample size. 

= Standard error. 

U.S. EPA (2007). 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page
 

September 2011 11-51
 

Table 11-34. Consumer-Only Total Fat Intake―Top 10% of Animal Fat Consumers (g/day) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

Birth to <1 year 

All 

Females 

Males 

1 to <2 years 

All 

Females 

Males 

2 to <3 years 

All 

Females 

Males 

3 to <6 years 

All 

Females 

Males 

6 to <11 years 

All 

Females 

Males 

11 to <16 years 

All 

16 to <21 years 

All 

11 to <21 years 

All 

Females 

Males 

21 to <31 years 

All 

Females 

Males 

31 to <41 years 

All 

Females 

Males 

41 to <51 years 

All 

Females 

Males 

140 

70 

70 

109 

54 

55 

103 

58 

45 

461 

217 

244 

198 

71 

127 

96 

68 

165 

53 

112 

150 

44 

106 

148 

48 

100 

166 

49 

117 

45 

45 

45 

75 

68 

81 

79 

77 

81 

88 

84 

92 

94 

88 

97 

133 

167 

146 

117 

160 

151 

115 

166 

147 

120 

160 

137 

110 

148 

16 

15 

17 

20 

16 

22 

20 

16 

24 

25 

24 

25 

25 

21 

27 

53 

64 

60 

30 

65 

55 

31 

56 

51 

33 

53 

42 

30 

41 

28 

26 

28 

52 

52 

54 

55 

55 

52 

62 

59 

66 

66 

58 

69 

85 

98 

90 

81 

94 

97 

80 

107 

93 

79 

110 

88 

72 

106 

35 

35 

34 

61 

57 

67 

64 

65 

61 

72 

68 

76 

77 

70 

78 

95 

122 

105 

92 

117 

113 

97 

128 

110 

93 

125 

110 

86 

119 

45 

45 

44 

74 

70 

78 

74 

74 

73 

84 

80 

90 

88 

86 

91 

121 

154 

139 

111 

151 

139 

108 

161 

135 

106 

149 

136 

103 

142 

54 

54 

53 

85 

78 

90 

85 

79 

90 

102 

95 

103 

105 

100 

112 

154 

189 

168 

140 

191 

173 

131 

177 

172 

132 

201 

156 

130 

166 

77 

69 

79 

108 

89 

125 

116 

109 

121 

135 

130 

136 

140 

123 

168 

223 

278 

254 

162 

276 

236 

160 

254 

352 

160 

352 

208 

150 

218 

100 

92 

100 

159 

114 

159 

133 

116 

133 

218 

194 

218 

178 

156 

178 

342 

463 

463 

195 

463 

445 

201 

445 

376 

228 

376 

267 

208 

267 
Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-52 September 2011 

Table 11-34. Consumer-Only Total Fat Intake―Top 10% of Animal Fat Consumers (g/day) (continued) 

Age Groupa N Mean SE Percentiles 

10th 25th 50th 75th 95th Max 

51 to <61 years 

All 

Females 

Males 

61 to <71 years 

All 

Females 

Males 

71 to <81 years 

All 

81+ years 

All 

71+ years 

All 

Females 

Males 

183 

39 

144 

168 

47 

121 

104 

40 

144 

50 

94 

127 

96 

135 

114 

91 

123 

98 

97 

98 

83 

105 

41 

27 

41 

35 

24 

35 

28 

37 

30 

25 

30 

80 

63 

96 

74 

68 

87 

65 

60 

62 

54 

76 

98 

74 

112 

88 

74 

102 

76 

67 

72 

63 

88 

118 

86 

122 

108 

87 

117 

92 

86 

91 

72 

97 

144 

106 

151 

133 

103 

140 

109 

104 

107 

95 

115 

206 

126 

214 

183 

120 

197 

144 

137 

144 

123 

165 

306 

165 

306 

235 

184 

235 

201 

227 

227 

147 

227 a 

N 

SE 

Source: 

Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring and Assessin g Childhood Exposures 

to Environmental Contaminants. 

= Sample size. 

= Standard error. 

U.S. EPA (2007). 
Table 11-35. Consumer-Only Total Fat Intake―Top 10% of Animal Fat Consumers (g/kg-day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th Max 

Birth to <1 year 

All 

Females 

Males 

1 to <2 years 

All 

Females 

Males 

2 to <3 years 

All 

Females 

Males 

3 to <6 years 

All 

Females 

Males 

6 to <11 years 

All 

Females 

Males 

11 to <16 years 

All 

16 to <21 years 

All 

11 to <21 years 

All 

Females 

Males 

21 to <31 years 

All 

Females 

Males 

31 to <41 years 

All 

Females 

Males 

41 to <51 years 

All 

Females 

Males 

140 

70 

70 

109 

54 

55 

103 

58 

45 

461 

217 

244 

198 

71 

127 

96 

68 

165 

53 

112 

150 

44 

106 

148 

48 

100 

166 

49 

117 

4.7 

4.8 

4.6 

6.9 

6.6 

7.1 

6.1 

6.2 

6.1 

5.6 

5.5 

5.7 

4.2 

4.2 

4.2 

3.0 

2.5 

2.8 

2.6 

2.9 

2.2 

2.0 

2.2 

2.1 

2.1 

2.1 

1.8 

1.8 

1.9 

1.7 

1.6 

1.7 

1.5 

1.2 

1.6 

1.3 

1.2 

1.3 

1.3 

1.3 

1.3 

1.1 

1.1 

1.1 

0.85 

0.74 

0.84 

0.65 

0.90 

0.73 

0.54 

0.79 

0.59 

0.62 

0.58 

0.49 

0.45 

0.50 

2.8 

2.7 

2.8 

5.1 

5.1 

5.1 

4.6 

4.6 

4.5 

4.2 

4.2 

4.2 

3.0 

2.9 

3.0 

2.0 

1.7 

1.9 

1.7 

1.9 

1.5 

1.5 

1.6 

1.5 

1.5 

1.5 

1.3 

1.3 

1.4 

3.7 

3.7 

3.6 

5.7 

5.7 

5.8 

5.2 

5.2 

5.2 

4.7 

4.5 

4.8 

3.4 

3.3 

3.4 

2.4 

2.0 

2.1 

2.0 

2.3 

1.7 

1.8 

1.7 

1.7 

1.7 

1.6 

1.5 

1.4 

1.6 

4.6 

4.7 

4.4 

6.8 

6.7 

6.9 

5.8 

5.9 

5.6 

5.3 

5.3 

5.3 

3.8 

3.8 

3.8 

2.8 

2.4 

2.7 

2.3 

2.8 

2.1 

1.9 

2.1 

1.9 

1.9 

2.0 

1.8 

1.8 

1.8 

6.0 

6.0 

5.8 

7.7 

7.4 

8.0 

6.7 

6.8 

6.6 

6.2 

6.0 

6.2 

4.6 

4.8 

4.5 

3.3 

2.9 

3.1 

2.7 

3.1 

2.4 

2.3 

2.4 

2.4 

2.2 

2.6 

2.1 

2.1 

2.0 

7.7 

7.7 

7.5 

9.5 

9.3 

9.4 

8.3 

7.9 

8.4 

8.3 

7.8 

8.4 

6.0 

5.8 

6.3 

4.6 

3.7 

4.4 

3.4 

4.5 

3.2 

3.1 

3.2 

3.9 

2.8 

3.9 

2.8 

2.6 

2.8 

11 

9.5 

11 

12 

9.7 

12 

9.5 

9.5 

9.5 

11 

11 

11 

9.9 

7.7 

9.9 

5.7 

6.0 

6.0 

4.6 

6.0 

7.3 

3.7 

7.3 

4.7 

4.7 

4.3 

4.0 

2.9 

4.0 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Exposure Factors Handbook Page
 

September 2011 11-53
 
 

Table 11-35. Consumer-Only Total Fat Intake―Top 10% of Animal Fat Consumers (g/kg-day)(continued) 

Percentiles Age Groupa N Mean SE 

10th 25th 50th 75th 95th Max 

51 to <61 years 

All 183 1.7 0.46 1.2 1.3 1.6 1.9 2.5 3.8 

Females 39 1.5 0.34 1.1 1.3 1.4 1.7 2.0 2.4 

Males 144 1.7 0.48 1.2 1.4 1.6 1.9 2.6 3.8 

61 to <71 years 

All 168 1.6 0.42 1.2 1.3 1.5 1.8 2.5 3.2 

Females 47 1.6 0.42 1.1 1.3 1.5 1.7 2.3 3.2 

Males 121 1.6 0.43 1.2 1.3 1.5 1.8 2.5 3.1 

71 to <81 years 

All 104 1.4 0.37 1.0 1.1 1.3 1.5 2.0 3.2 

81+ years 

All 40 1.6 0.48 1.1 1.2 1.4 1.7 2.0 3.7 

71+ years 

All 144 1.4 0.41 1.0 1.1 1.3 1.6 2.0 3.7 

Females 50 1.4 0.41 0.96 1.1 1.4 1.6 1.8 3.2 

Males 94 1.5 0.41 1.1 1.2 1.3 1.5 2.1 3.7 

a Age groups are based on U.S. EPA (2005) Guidance on Selecting Age Groups for Monitoring and Assessing Childhood Exposures 

to Environmental Contaminants. 

N = Sample size 

SE = Standard error. 

Source: U.S. EPA (2007). 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Page Exposure Factors Handbook 

11-54 September 2011 
 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-36. Fat Intake Among Children Based on Data From the Bogalusa Heart Study, 1973−1982 (g/day) 

Age N Mean SD 

Percentiles Minimum Maximum 

10th 25th 50th 75th 90th 

Total Fat Intake 

6 months 125 37.1 17.5 18.7 25.6 33.9 46.3 60.8 3.4 107.6 

1 year 99 59.1 26.0 29.1 40.4 56.1 71.4 94.4 21.6 152.7 

2 years 135 86.7 41.3 39.9 55.5 79.2 110.5 141.1 26.5 236.4 

3 years 106 91.6 38.8 50.2 63.6 82.6 114.6 153.0 32.6 232.5 

4 years 219 98.6 56.1 46.0 66.8 87.0 114.6 163.3 29.3 584.6 

10 years 871 93.2 50.8 45.7 60.5 81.4 111.3 154.5 14.6 529.5 

13 years 148 107.0 53.9 53.0 69.8 90.8 130.7 184.1 9.8 282.2 

15 years 108 97.7 48.7 46.1 65.2 85.8 124.0 165.2 10.0 251.3 

17 years 159 107.8 64.3 41.4 59.7 97.3 140.2 195.1 8.5 327.4 

Total Animal Fat 

6 months 125 18.4 16.0 0.7 4.2 13.9 28.4 42.5 0.0 61.1 

1 year 99 36.5 20.0 15.2 23.1 33.0 45.9 65.3 0.0 127.1 

2 years 135 49.5 28.3 20.1 28.9 42.1 66.0 81.4 10.0 153.4 

3 years 106 50.1 29.4 21.3 29.1 42.9 64.4 88.9 14.1 182.6 

4 years 219 50.8 31.7 21.4 28.1 42.6 66.4 92.6 5.9 242.2 

10 years 871 54.1 39.6 20.3 30.6 45.0 64.6 97.5 0.0 412.3 

13 years 148 56.2 39.8 19.8 28.5 44.8 72.8 109.4 4.7 209.6 

15 years 108 53.8 35.1 15.9 28.3 44.7 67.9 105.8 0.6 182.1 

17 years 159 64.4 48.5 15.2 30.7 51.6 86.6 128.8 2.6 230.3 

Total Vegetable Fat Intake 

6 months 125 9.2 12.8 0.6 1.2 2.8 11.6 29.4 0.0 53.2 

1 year 99 15.4 14.3 3.7 6.1 11.3 18.1 38.0 0.2 70.2 

2 years 135 19.3 16.3 3.8 7.9 14.8 26.6 42.9 0.7 96.6 

3 years 106 21.1 15.5 3.9 8.6 18.7 26.6 45.2 1.0 70.4 

4 years 219 24.5 18.6 5.7 10.4 21.8 33.3 48.5 0.9 109.0 

10 years 871 23.7 21.6 4.3 9.5 18.3 30.6 49.0 0.6 203.7 

13 years 148 34.3 27.4 8.4 17.9 31.2 44.6 57.5 0.0 238.3 

15 years 108 27.3 22.8 5.1 11.9 22.6 38.1 54.4 0.7 132.2 

17 years 159 25.7 21.3 4.2 11.7 20.8 32.9 47.6 0.0 141.5 

Total Fish Fat Intake 

6 months 125 0.05 0.1 0.0 0.0 0.0 0.0 0.1 0.0 0.9 

1 year 99 0.05 0.2 0.0 0.0 0.0 0.0 0.0 0.0 1.9 

2 years 135 0.04 0.2 0.0 0.0 0.0 0.0 0.0 0.0 1.9 

3 years 106 0.1 0.6 0.0 0.0 0.0 0.0 0.0 0.0 4.5 

4 years 219 2.3 31.1 0.0 0.0 0.0 0.0 0.0 0.0 459.2 

10 years 871 0.3 1.5 0.0 0.0 0.0 0.0 0.0 0.0 19.2 

13 years 148 0.3 2.2 0.0 0.0 0.0 0.0 0.0 0.0 25.4 

15 years 108 0.4 1.5 0.0 0.0 0.0 0.0 1.5 0.0 9.5 

17 years 159 0.5 2.0 0.0 0.0 0.0 0.0 0.4 0.0 15.3 

N = Sample size. 

SD = Standard deviation. 

Source: Frank et al. (1986). 

Exposure Factors Handbook Page
 

September 2011 11-55
 
 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-37. Fat Intake Among Children Based on Data From the Bogalusa Heart Study, 1973−1982 

(g/kg-day) 

Age N Mean SD Percentiles Minimum Maximum 

10th 25th 50th 75th 90th 

Total Fat Intake 

6 months 125 4.9 2.3 2.4 3.3 4.7 6.2 8.0 0.4 13.2 

1 year 99 6.1 2.8 3.0 4.1 5.7 7.5 9.5 2.3 16.4 

2 years 132 7.0 3.3 3.4 4.5 6.2 8.6 11.9 2.1 18.7 

3 years 106 6.4 2.7 3.6 4.6 5.5 8.2 9.9 2.2 16.7 

4 years 218 6.1 3.7 2.9 4.0 5.2 7.0 10.0 2.0 38.2 

10 years 861 2.7 1.5 1.2 1.7 2.4 3.3 4.5 0.3 13.9 

13 years 147 2.3 1.3 1.0 1.5 2.0 2.8 3.8 0.2 10.2 

15 years 105 1.7 0.8 0.8 1.2 1.5 2.1 3.1 0.2 4.7 

17 years 149 1.8 1.0 0.7 0.9 1.6 2.2 3.1 0.2 6.2 

Total Animal Fat 

6 months 125 2.4 2.1 0.08 0.6 2.0 3.7 5.5 0.0 9.0 

1 year 99 3.8 2.1 1.7 2.4 3.4 4.9 6.5 0.0 13.6 

2 years 132 4.0 2.3 1.7 2.3 3.4 5.2 6.7 0.7 13.4 

3 years 106 3.5 2.0 1.6 2.1 3.1 4.2 6.1 0.9 13.1 

4 years 218 3.1 2.1 1.3 1.7 2.6 4.0 5.4 0.4 15.4 

10 years 861 16 1.2 0.6 0.8 1.3 1.9 2.8 0.00 10.8 

13 years 147 1.2 0.9 0.4 0.6 0.9 1.6 2.3 0.08 5.2 

15 years 105 1.0 0.6 0.3 0.5 0.8 1.3 1.9 0.01 3.1 

17 years 149 1.0 0.8 0.3 0.5 0.8 1.4 2.0 0.05 4.2 

Total Vegetable Fat Intake 

6 months 125 1.2 1.8 0.08 0.2 0.4 1.6 4.1 0.0 8.2 

1 year 99 1.6 1.6 0.4 0.6 1.2 1.9 3.8 0.02 7.6 

2 years 132 1.6 1.4 0.3 0.7 1.1 2.0 3.5 0.06 8.5 

3 years 106 1.5 1.1 0.3 0.6 1.4 2.0 3.0 0.08 5.1 

4 years 218 1.5 1.2 0.4 0.6 1.2 2.1 2.8 0.06 7.3 

10 years 861 0.7 0.6 0.1 0.3 0.5 0.9 1.4 0.02 4.2 

13 years 147 0.8 0.8 0.2 0.4 0.6 0.9 1.3 0.0 8.6 

15 years 105 0.5 0.4 0.09 0.2 0.4 0.7 0.9 0.01 2.2 

17 years 149 0.4 0.4 0.07 0.2 0.4 0.6 0.9 0.0 2.1 

Total Fish Fat Intake 

6 months 125 0.01 0.02 0.0 0.0 0.0 0.0 0.02 0.0 0.1 

1 year 99 0.01 0.03 0.0 0.0 0.0 0.0 0.0 0.0 0.2 

2 years 132 0.003 0.02 0.0 0.0 0.0 0.0 0.0 0.0 0.2 

3 years 106 0.01 0.04 0.0 0.0 0.0 0.0 0.0 0.0 0.3 

4 years 218 0.2 2.0 0.0 0.0 0.0 0.0 0.0 0.0 30.0 

10 years 861 0.01 0.05 0.0 0.0 0.0 0.0 0.0 0.0 0.6 

13 years 147 0.01 0.04 0.0 0.0 0.0 0.0 0.0 0.0 0.4 

15 years 105 0.01 0.03 0.0 0.0 0.0 0.0 0.04 0.0 0.2 

17 years 149 0.01 0.03 0.0 0.0 0.0 0.0 0.008 0.0 0.2 

N = Sample size. 

SD = Standard deviation. 

Source: Frank et al. (1986). 

Page Exposure Factors Handbook 

11-56 September 2011 
 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-38. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Productsa 

Product 

Moisture 

Content 

(%) 

Total Fat 

Content 

(%) 

Comment 

Meat 

Beef (composite of trimmed retail cuts; all grades) 70.62 

59.25 

60.44 

51.43 

6.16 

9.91 

19.24 

21.54 

Raw; lean only 

Cooked; lean only 

Raw; lean and fat, 1/4 in fat trim 

Cooked; lean and fat, 1/4 in fat trim 

Pork (composite of trimmed retail cuts) 

Cured ham 

Cured bacon 

72.34 

60.31 

65.11 

54.55 

63.46 

55.93 

40.20 

12.52 

12.32 

12.12 

16.49 

5.88 

9.66 

14.95 

17.18 

12.90 

8.32 

45.04 

43.27 

41.78 

40.30 

37.27 

Raw; lean only 

Cooked; lean only 

Raw; lean and fat 

Cooked; lean and fat 

Center slice, unheated; lean and fat 

Raw, center slice, country style; lean only 

Raw 

Cooked, baked 

Cooked, broiled 

Cooked, pan-fried 

Cooked, microwaved 

Lamb (composite of trimmed retail cuts) 73.42 

61.96 

60.70 

53.72 

5.25 

9.52 

21.59 

20.94 

Raw; lean only 

Cooked; lean only 

Raw; lean and fat, 1/4 in fat trim 

Cooked; lean and fat, 1/4 in fat trim 

Veal (composite of trimmed retail cuts) 75.91 

60.16 

72.84 

57.08 

2.87 

6.58 

6.77 

11.39 

Raw; lean only 

Cooked; lean only 

Raw; lean and fat, 1/4 in fat trim 

Cooked; lean and fat, 1/4 in fat trim 

Rabbit (domesticated) 72.82 

60.61 

58.82 

5.55 

8.05 

8.41 

Raw 

Cooked, roasted 

Cooked, stewed 

Chicken (broilers or fryers) 

Duck (domesticated) 

Turkey (all classes) 

75.46 

66.81 

63.79 

57.53 

65.99 

63.93 

59.45 

52.41 

73.77 

64.22 

48.50 

51.84 

74.16 

64.88 

70.40 

61.70 

71.97 

59.42 

3.08 

6.71 

7.41 

9.12 

15.06 

12.56 

13.60 

14.92 

5.95 

11.20 

39.34 

28.35 

2.86 

4.97 

8.02 

9.73 

8.26 

13.15 

Raw; meat only 

Cooked, stewed; meat only 

Cooked, roasted; meat only 

Cooked, fried; meat only 

Raw; meat and skin 

Cooked, stewed; meat and skin 

Cooked, roasted; meat and skin 

Cooked, fried, flour; meat and skin 

Raw; meat only 

Cooked, roasted; meat only 

Raw; meat and skin 

Cooked, roasted; meat and skin 

Raw; meat only 

Cooked, roasted; meat only 

Raw; meat and skin 

Cooked, roasted; meat and skin 

Raw; ground 

Cooked; ground 

Exposure Factors Handbook Page
 

September 2011 11-57
 
 

 

 

Exposure Factors Handbook 

Chapter 11—Intake of Meats, Dairy Products, and Fats 

Table 11-38. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Productsa (continued) 

Product 

Moisture 

Content 

(%) 

Total Fat 

Content 

(%) 

Comment 

Dairy 

Milk 

Whole 

Human 

Lowfat (1%) 

Reduced fat (2%) 

Skim or fat free 

Cream 

Half and half 

Light (coffee cream or table cream) 

Heavy-whipping 

Sour 

Sour, reduced fat 

Butter 

Cheese 

American 

Cheddar 

Swiss 

Cream 

Parmesan 

Cottage, lowfat 

Colby 

Blue 

Provolone 

Mozzarella 

Yogurt 

Egg 

88.32 

87.50 

89.81 

88.86 

90.38 

80.57 

73.75 

57.71 

70.95 

80.14 

15.87 

39.16 

36.75 

37.12 

53.75 

29.16; 20.84 

82.48; 79.31 

38.20 

42.41 

40.95 

50.01; 53.78 

85.07; 87.90 

75.84 

3.25 

4.38 

0.97 

1.92 

0.25 

11.50 

19.31 

37.00 

20.96 

12.00 

81.11 

31.25 

33.14 

27.80 

34.87 

25.83; 28.61 

1.02; 1.93 

32.11 

28.74 

26.62 

22.35; 15.92 

1.55; 3.25 

9.94 

3.25% milkfat 

Whole, mature, fluid 

Fluid, with added non-fat milk solids and vitamin A 

Fluid, with added non-fat milk solids and vitamin A 

Fluid, with added non-fat milk solids and vitamin A 

Fluid 

Fluid 

Fluid 

Cultured 

Cultured 

Salted 

Pasteurized 

Hard; grated 

1% fat; 2% fat 

Whole milk; Skim milk 

Plain, lowfat; Plain, with fat 

Chicken, whole raw, fresh a Based on the water and lipid content in 100 grams, edible portion. Total Fat Content = saturated, monosaturated, and 

polyunsaturated. For additional information, consult the USDA nutrient database. 

Source: USDA (2007). 

Page Exposure Factors Handbook 

11-58 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

12. INTAKE OF GRAIN PRODUCTS 

12.1. INTRODUCTION 

The American food supply is generally 

considered to be one of the safest in the world. 

Nevertheless, grain products may become 

contaminated with toxic chemicals by several 

different pathways. Ambient air pollutants may be 

deposited on or absorbed by the plants, or dissolved 

in rainfall or irrigation waters that contact the plants. 

Pollutants may also be absorbed through plant roots 

from contaminated soil and ground water. The 

addition of pesticides, soil additives, and fertilizers 

may also result in contamination of grain products. 

To assess exposure through this pathway, information 

on ingestion rates of grain products is needed. 

A variety of terms may be used to define intake of 

grain products (e.g., consumer-only intake, per capita 

intake, total grain intake, as-consumed intake, 

uncooked edible intake, dry-weight intake). As 

described in Chapter 9 (Intake of Fruits and 

Vegetables), consumer-only intake is defined as the 

quantity of grain products consumed by individuals 

during the survey period. These data are generated by 

averaging intake across only the individuals in the 

survey who consumed these food items. Per capita 

intake rates are generated by averaging 

consumer-only intakes over the entire population 

(including those that reported no intake). In general, 

per capita intake rates are appropriate for use in 

exposure assessments for which average dose 

estimates for individuals are of interest because they 

represent both individuals who ate the foods during 

the survey period and those who may eat the food 

items at some time but did not consume them during 

the survey period. Per capita intake, therefore, 

represents an average across the entire population of 

interest, but does so at the expense of 

underestimating consumption for the subset of the 

population that consumed the food in question. Total 

grain intake refers to the sum of all grain products 

consumed in a day. 

Intake rates may be expressed on the basis of the 

as-consumed weight (e.g., cooked or prepared) or on 

the uncooked or unprepared weight. As-consumed 

intake rates are based on the weight of the food in the 

form that it is consumed and should be used in 

assessments where the basis for the contaminant 

concentrations in foods is also indexed to the 

as-consumed weight. Some of the food ingestion 

values provided in this chapter are expressed as 

as-consumed intake rates because this is the fashion 

in which data were reported by survey respondents. 

Others are provided as uncooked weights based on 

analyses of survey data that account for weight 

changes that occur during cooking. This is of 

importance because concentration data to be used in 

the dose equation are often measured in uncooked 

food samples. It should be recognized that cooking 

can either increase or decrease food weight. 

Similarly, cooking can increase the mass of 

contaminant in food (due to formation reactions, or 

absorption from cooking oils or water) or decrease 

the mass of contaminant in food (due to vaporization, 

fat loss, or leaching). The combined effects of 

changes in weight and changes in contaminant mass 

can result in either an increase or decrease in 

contaminant concentration in cooked food. Therefore, 

if the as-consumed ingestion rate and the uncooked 

concentration are used in the dose equation, dose may 

be under-estimated or over-estimated. It is important 

for the assessor to be aware of these issues and 

choose intake rate data that best match the 

concentration data that are being used. For more 

information on cooking losses and conversions 

necessary to account for such losses, refer to 

Chapter 13 of this handbook. 

Sometimes contaminant concentrations in food 

are reported on a dry-weight basis. When these data 

are used in an exposure assessment, it is 

recommended that dry-weight intake rates also be 

used. Dry-weight food concentrations and intake 

rates are based on the weight of the food consumed 

after the moisture content has been removed. For 

information on converting the intake rates presented 

in this chapter to dry-weight intake rates, refer to 

Section 12.4. 

The purpose of this chapter is to provide intake 

data for grain products for the general population. 

The recommendations for ingestion rates of grain 

products are provided in the next section, along with 

a summary of the confidence ratings for these 

recommendations. The recommended values are 

based on the key study identified by 

U.S. Environmental Protection Agency (EPA) for this 

factor. Following the recommendations, the key study 

on ingestion of grain products is summarized. 

Relevant data on ingestion of grain products are also 

provided. These data are presented to provide the 

reader with added perspective on the current state-ofknowledge pertaining to ingestion of grain products 

among children. 

12.2. RECOMMENDATIONS 

Table 12-1 presents a summary of the 

recommended values for per capita and 

consumer-only intake of grain products. Table 12-2 

provides confidence ratings for the grain intake 

recommendations for the general population. 

Exposure Factors Handbook Page
 

September 2011 12-1 
 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

The U.S. EPA analysis of data from the 

2003−2006 National Health and Nutrition 

Examination Survey (NHANES) was used in 

selecting recommended intake rates. The U.S. EPA 

analysis was conducted using childhood age groups 

that differed slightly from U.S. EPA’s Guidance on 

Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005). However, for the 

purposes of the recommendations presented here, 

data were placed in the standardized age categories 

closest to those used in the analysis. 

The NHANES data on which the 

recommendations are based are short-term survey 

data and may not necessarily reflect the long-term 

distribution of average daily intake rates. However, 

because broad categories of food (i.e., total grains), 

are eaten on a daily basis throughout the year with 

minimal seasonality, the short-term distribution may 

be a reasonable approximation of the long-term 

distribution, although it will display somewhat 

increased variability. This implies that the upper 

percentiles shown here will tend to overestimate the 

corresponding percentiles of the true long-term 

distribution. In general, the recommended values 

based on U.S. EPA’s analysis of NHANES data 

represent the uncooked weight of the edible portion 

of grain products. 

Table 12-1. Recommended Values for Intake of Grains, Edible Portion, Uncookeda 

Age Group (years) 

Per Capita Consumers Only Multiple 

Percentiles Mean 95 Source th Percentile Mean 95th Percentile 

g/kg-day g/kg-day g/kg-day g/kg-day 

Total Grains 

Birth to 1 3.1 9.5b 4.1 10.3b 

See Table 12-3 

and Table 12-4 

U.S. EPA 

Analysis of 

NHANES 2003– 

2006 

1 to <2 6.4 12.4b 6.4 12.4b 

2 to <3 6.4 12.4b 6.4 12.4b 

3 to <6 6.2 11.1 6.2 11.1 

6 to <11 4.4 8.2 4.4 8.2 

11 to <16 2.4 5.0 2.4 5.0 

16 to <21 2.4 5.0 2.4 5.0 

20 to <50 2.2 4.6 2.2 4.6 

>50 1.7 3.5 1.7 3.5 

Individual Grain Products—See Table 12-5 and Table 12-6 a Analysis was conducted using slightly different childhood age groups than those recommended in Guidance on 

Selecting Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 

2005). Data were placed in the standardized age categories closest to those used in the analysis. b Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and 

Statistical Reporting Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group 

Recommendations (NCHS, 1993). 

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Chapter 12—Intake of Grain Products 

Table 12-2. Confidence in Recommendations for Intake of Grain Products 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The survey methodology and data analysis were adequate. 

The survey sampled more than 16,000 individuals. An 

analysis of primary data was conducted. 

No physical measurements were taken. The method relied 

on recent recall of grain products eaten. 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key study was directly relevant to grain intake. 

The data were demographically representative of the U.S. 

population (based on stratified random sample). 

Data were collected between 2003 and 2006. 

Data were collected for two non-consecutive days. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The NHANES data are publicly available. 

The methodology used was clearly described; enough 

information was included to reproduce the results. 

NHANES follows strict QA/QC procedures. The 

U.S. EPA analysis has only been reviewed internally, but 

the methodology has been used in an analysis of previous 

data. 

High 

Variability and Uncertainty 

Variability in Population 

Minimal Uncertainty 

Full distributions were provided for total grains. Means 

were provided for individual grain products. 

Data collection was based on recall for a two-day period; 

the accuracy of using these data to estimate long-term 

intake (especially at the upper percentiles) is uncertain. 

However, use of short-term data to estimate chronic 

ingestion can be assumed for broad categories of foods 

such as total grains. Uncertainty is greater for individual 

grain products. 

Medium to high for 

averages, low for long-term 

upper percentiles; low for 

individual foods 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The NCHS NHANES survey received a high level of peer 

review. The U.S. EPA analysis of these data has not been 

peer reviewed outside the Agency, but the methodology 

has been used in an analysis of previous data. 

There was one key study. 

Medium 

Overall Rating Medium to High 

confidence in the averages; 

Low confidence in the longterm upper percentiles 

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Chapter 12—Intake of Grain Products 

12.3. INTAKE STUDIES 

12.3.1. Key Grain Intake Study 

12.3.1.1.	 U.S. EPA Analysis of Consumption Data 

From 2003−2006 National Health and 

Nutrition Examination Survey 

(NHANES) 

The key source of recent information on 

consumption rates of grain products is the U.S. 

Centers for Disease Control and Prevention’s 

National Center for Health Statistics’ (NCHS) 

NHANES. Data from NHANES 2003−2006 have 

been used by the U.S. EPA, Office of Pesticide 

Programs (OPP) to generate per capita and 

consumer-only intake rates for both individual grain 

products and total grain products. 

NHANES is designed to assess the health and 

nutritional status of adults and children in the United 

States. In 1999, the survey became a continuous 

program that interviews a nationally representative 

sample of approximately 7,000 persons each year and 

examines a nationally representative sample of about 

5,000 persons each year, located in counties across 

the country, 15 of which are visited each year. Data 

are released on a 2-year basis; thus, for example, the 

2003 data are combined with the 2004 data to 

produce NHANES 2003−2004. 

The dietary interview component of NHANES is 

called What We Eat in America and is conducted by 

the U.S. Department of Agriculture (USDA) and the 

U.S. Department of Health and Human Services 

(DHHS). DHHS’ NCHS is responsible for the sample 

design and data collection, and USDA’s Food 

Surveys Research Group is responsible for the dietary 

data collection methodology, maintenance of the 

databases used to code and process the data, and data 

review and processing. Beginning in 2003, 

2 non-consecutive days of 24-hour intake data were 

collected. The first day was collected in-person, and 

the second day was collected by telephone, 3 to 

10 days later. These data were collected using 

USDA’s dietary data collection instrument, the 

Automated Multiple Pass Method. This method 

provides an efficient and accurate means of collecting 

intakes for large-scale national surveys. It is fully 

computerized and uses a five-step interview. Details 

can be found at USDA’s Agriculture Research 

Service (http://www.ars.usda.gov/ba/bhnrc/fsrg). 

For NHANES 2003−2004, there were 

12,761 persons selected; of these, 9,643 were 

considered respondents to the mobile examination 

center (MEC) examination and data collection. 

However, only 9,034 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,354 provided complete dietary intakes for Day 2. 

For NHANES 2005−2006, there were 12,862 persons 

selected; of these, 9,950 were considered respondents 

to the MEC examination and data collection. 

However, only 9,349 of the MEC respondents 

provided complete dietary intakes for Day 1. 

Furthermore, of those providing the Day 1 data, only 

8,429 provided complete dietary intakes for Day 2. 

The 2003−2006 NHANES surveys are stratified, 

multistage probability samples of the civilian 

non-institutionalized U.S. population. The sampling 

frame was organized using 2000 U.S. population 

census estimates. NHANES oversamples low income 

persons, adolescents 12 to 19 years, persons 60 years 

and older, African Americans, and Mexican 

Americans. Several sets of sampling weights are 

available for use with the intake data. By using 

appropriate weights, data for all 4 years of the 

surveys can be combined. Additional information on 

NHANES can be obtained at 

http://www.cdc.gov/nchs/nhanes.htm. 

In 2010, U.S. EPA, OPP used NHANES 

2003−2006 data to update the Food Commodity 

Intake Database (FCID) that was developed in earlier 

analyses of data from the USDA’s Continuing Survey 

of Food Intake by Individuals (CSFII) (U.S. EPA, 

2000; USDA, 2000) (see Section 12.3.2.4), NHANES 

data on the foods people reported eating were 

converted to the quantities of agricultural 

commodities eaten. "Agricultural commodity" is a 

term used by U.S. EPA to mean plant (or animal) 

parts consumed by humans as food; when such items 

are raw or unprocessed, they are referred to as "raw 

agricultural commodities." For example, an apple pie 

may contain the commodities apples, flour, fat, sugar, 

and spices. FCID contains approximately 558 unique 

commodity names and 8-digit codes. The FCID 

commodity names and codes were selected and 

defined by U.S. EPA and were based on the U.S. EPA 

Food Commodity Vocabulary 

(http://www.epa.gov/pesticides/foodfeed/). 

Intake rates were generated for a variety of food 

items/groups based on the agricultural commodities 

included in the FCID. These intake rates represent 

intake of all forms of the product (e.g., both home 

produced and commercially produced) for individuals 

who provided data for two days of the survey. Note 

that if the person reported consuming food for only 

one day, their two-day average would be half the 

amount reported for the one day of consumption. 

Individuals who did not provide information on body 

weight or for whom identifying information was 

unavailable were excluded from the analysis. 

Two-day average intake rates were calculated for all 

individuals in the database for each of the food 

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items/groups. These average daily intake rates were 

divided by each individual's reported body weight to 

generate intake rates in units of grams per kilogram 

of body weight per day (g/kg-day). The data were 

weighted according to the 4-year, 2-day sample 

weights provided in NHANES 2003−2006 to adjust 

the data for the sample population to reflect the 

national population. 

Summary statistics were generated on a 

consumer-only and on a per capita basis. Summary 

statistics, including number of observations, 

percentage of the population consuming the grains 

being analyzed, mean intake rate, and standard error 

of the mean intake rate were calculated for total 

grains and selected individual grains. Percentiles of 

the intake rate distribution (i.e., 1st, 5th, 10th, 25th, 50th, 

75th, 90th, 95th, 99th, and the maximum value) were 

also provided for total grains. Data were provided for 

the following age groups: birth to 1 year, 1 to 2 years, 

3 to 5 years, 6 to 12 years, 13 to 19 years, 20 to 

49 years, and ≥50 years. Data on females 13 to 49 

years were also provided. Because these data were 

developed for use in U.S. EPA’s pesticide registration 

program, the childhood age groups used are slightly 

different than those recommended in U.S. EPA’s 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

Table 12-3 presents per capita intake data for total 

grains in g/kg-day; Table 12-4 provides 

consumer-only intake data for total grains in 

g/kg-day. Table 12-5 provides per capita intake data 

for individual grains in g/kg-day, and Table 12-6 

provides consumer-only intake data for individual 

grains in g/kg-day. In general, these data represent 

intake of the edible portions of i.e., uncooked foods. 

The results are presented in units of g/kg-day. 

Thus, use of these data in calculating potential dose 

does not require the body-weight factor to be 

included in the denominator of the average daily dose 

(ADD) equation. It should be noted that converting 

these intake rates into units of g/day by multiplying 

by a single average body weight is inappropriate, 

because individual intake rates were indexed to the 

reported body weights of the survey respondents. 

Also, it should be noted that the distribution of 

average daily intake rates generated using short-term 

data (e.g., 2-day) does not necessarily reflect the 

long-term distribution of average daily intake rates. 

The distributions generated from short-term and 

long-term data will differ to the extent that each 

individual’s intake varies from day to day; the 

distributions will be similar to the extent that 

individuals’ intakes are constant from day to day. 

Day-to-day variation in intake among individuals will 

be high for grains that are not typically eaten every 

day. For these grains, the intake distribution 

generated from short-term data will not be a good 

reflection of the long-term distribution. On the other 

hand, for broad categories of foods (e.g., total grains) 

that are eaten on a daily basis throughout the year, the 

short-term distribution may be a reasonable 

approximation of the true long-term distribution, 

although it will show somewhat more variability. In 

this chapter, distributions are provided for broad 

categories of grains (e.g., total grains). Because of the 

increased variability of the short-term distribution, 

the short-term upper percentiles shown here may 

overestimate the corresponding percentiles of the 

long-term distribution. For individual foods, only the 

mean, standard error, and percent consuming are 

provided. An advantage of using the U.S. EPA’s 

analysis of NHANES data is that it provides 

distributions of intake rates for various age groups of 

children and adults, normalized by body weight. The 

data set was designed to be representative of the U.S. 

population and includes 4 years of intake data 

combined. Another advantage is the currency of the 

data; the NHANES data are from 2003−2006. 

However, short-term dietary data may not accurately 

reflect long-term eating patterns and may 

under-represent infrequent consumers of a given 

food. This is particularly true for the tails (extremes) 

of the distribution of food intake. Because these are 

2-day averages, consumption estimates at the upper 

end of the intake distribution may be underestimated 

if these consumption values are used to assess acute 

(i.e., short-term) exposures. Also, the analysis was 

conducted using slightly different childhood age 

groups than those recommended in U.S. EPA’s 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

However, given the similarities in the age groups 

used, the data should provide suitable intake 

estimates for the age groups of interest. 

12.3.2. Relevant Grain Intake Studies 

12.3.2.1.	 USDA (1996a, b, 1993, 1980)—Food and 

Nutrient Intakes of Individuals in 1 Day 

in the United States 

USDA calculated mean per capita intake rates for 

total and individual grain products using Nationwide 

Food Consumption Survey (NFCS) data from 

1977−1978 and 1987−1988 (USDA, 1993, 1980) and 

CSFII data from 1994 and 1995 (USDA, 1996a, b). 

The mean per capita intake rates for grain products 

are presented in Table 12-7 and Table 12-8 for the 

two NFCS survey years, respectively. Table 12-9 

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presents similar data from the 1994 and 1995 CSFII 

for grain products. 

The advantages of using these data are that they 

provide mean intake estimates for various grain 

products. The consumption estimates are based on 

short-term (i.e., 1-day) dietary data, which may not 

reflect long-term consumption. These data are based 

on older surveys and may not be entirely 

representative of current eating patterns. 

12.3.2.2.	 USDA (1999b)—Food Consumption, 

Prices, and Expenditures, 1970−1997

The USDA's Economic Research Service 

calculates the amount of food available for human 

consumption in the United States annually. Supply 

and utilization balance sheets are generated. These 

are based on the flow of food items from production 

to end uses. Total available supply is estimated as the 

sum of production (i.e., some products are measured 

at the farm level or during processing), starting 

inventories, and imports (USDA, 1999b). The 

availability of food for human use commonly termed 

as "food disappearance" is determined by subtracting 

exported foods, products used in industries, farm 

inputs (seed and feed), and end-of-the-year 

inventories from the total available supply (USDA, 

1999b). USDA (1999b) calculates the per capita food 

consumption by dividing the total food disappearance 

by the total U.S. population. 

USDA (1999b) estimated per capita consumption 

data for grain products from 1970−1997. In this 

section, the 1997 values, which are the most recent 

final data, are presented. Table 12-10 presents per 

capita consumption in 1997 for grains. 

An advantage of this study is that it provides per 

capita consumption rates for grains that are 

representative of long-term intake because 

disappearance data are generated annually. Daily per 

capita intake rates are generated by dividing annual 

consumption by 365 days/year. One of the limitations 

of this study is that disappearance data do not account 

for losses from the food supply from waste, spoilage, 

or foods fed to pets. Thus, intake rates based on these 

data may overestimate daily consumption because 

they are based on the total quantity of marketable 

commodity utilized. Therefore, these data may be 

useful for estimating bounding exposure estimates. It 

should also be noted that per capita estimates based 

on food disappearance are not a direct measure of 

actual consumption or quantity ingested, instead the 

data are used as indicators of changes in usage over 

time (USDA, 1999b). These data are based on older 

surveys and may not be entirely representative of 

current consumption patterns. 

12.3.2.3.	 USDA (1999a)—Food and Nutrient 

Intakes by Children 1994−1996, 1998, 

Table Set 17 

USDA (1999a) calculated national probability 

estimates of food and nutrient intake by children 

based on 4 years of the CSFII (1994−1996 and 1998) 

for children age 9 years and under, and on CSFII 

1994−1996 only for individuals age 10 years and 

over. The CSFII was a series of surveys designed to 

measure the kinds and amounts of foods eaten by 

Americans. Intake data, based on 24-hour dietary 

recall, were collected through in-person interviews on 

2 non-consecutive days. Section 12.3.2.4 provides 

additional information on these surveys. 

USDA used sample weights to adjust for 

non-response, to match the sample to the U.S. 

population in terms of demographic characteristics, 

and to equalize intakes over the four quarters of the 

year and the 7 days of the week. A total of 

503 breast-fed children were excluded from the 

estimates, but both consumers and non-consumers 

were included in the analysis. 

USDA (1999a) provided data on the mean per 

capita quantities (grams) of various food 

products/groups consumed per individual for 1 day, 

and the percent of individuals consuming those foods 

in 1 day of the survey. Table 12-11 and Table 12-12 

present data on the mean quantities (grams) of grain 

products consumed per individual for 1 day, and the 

percentage of survey individuals consuming grain 

products that survey day. Data on mean intakes or 

mean percentages are based on respondents’ Day-1 

intakes. 

The advantage of the USDA (1999a) study is that 

it uses the 1994−1996, 1998 CSFII data set, which 

includes 4 years of intake data, combined, and 

includes the supplemental data on children. These 

data are expected to be generally representative of the 

U.S. population, and they include data on a wide 

variety of grain products. The data set is one of a 

series of USDA data sets that are publicly available. 

One limitation of this data set is that it is based on 

1-day, and short-term dietary data may not accurately 

reflect long-term eating patterns. Other limitations of 

this study are that it only provides mean values of 

food intake rates, consumption is not normalized by 

body weight, and presentation of results is not 

consistent with U.S. EPA’s recommended age groups. 

These data are based on older surveys and may not be 

entirely representative of current eating patterns. 

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12.3.2.4.	 U.S. EPA Analysis of Continuing Survey 

of Food Intake by Individuals (CSFII) 

1994−1996, 1998 

U.S. EPA/OPP, in cooperation with USDA’s 

Agricultural Research Service, used data from the 

1994−1996, 1998 CSFII to develop the FCID (U.S. 

EPA, 2000; USDA, 2000), as described in 

Section 12.3.1.1. The CSFII 1994−1996 was 

conducted between January 1994 and January 1997 

with a target population of non-institutionalized 

individuals in all 50 states and Washington, DC. In 

each of the three survey years, data were collected for 

a nationally representative sample of individuals of 

all ages. The CSFII 1998 was conducted between 

December 1997 and December 1998 and surveyed 

children 9 years of age and younger. It used the same 

sample design as the CSFII 1994−1996 and was 

intended to be merged with CSFII 1994−1996 to 

increase the sample size for children. The merged 

surveys are designated as CSFII 1994−1996, 1998 

(USDA, 2000). Additional information on the CSFII 

can be obtained at http://www.ars.usda.gov/ 

Services/docs.htm?docid=14531. 

The CSFII 1994−1996, 1998 collected dietary 

intake data through in-person interviews on 

two non-consecutive days. The data were based on 

24-hour recall. A total of 21,662 individuals provided 

data for the first day; of those individuals, 20,607 

provided data for a second day. The 2-day response 

rate for the 1994−1996 CSFII was approximately 

76%. The 2-day response rate for CSFII 1998 was 

82%. The CSFII 1994−1996, 1998 surveys were 

based on a complex multistage area probability 

sample design. The sampling frame was organized 

using 1990 U.S. population census estimates, and the 

stratification plan took into account geographic 

location, degree of urbanization, and socioeconomic 

characteristics. Several sets of sampling weights are 

available for use with the intake data. By using 

appropriate weights, data for all 4 years of the 

surveys can be combined. USDA recommends that 

all four years be combined in order to provide an 

adequate sample size for children. 

The grain items/groups selected for the U.S. EPA 

analysis included total grains, and individual grain 

products such as cereal and rice. U.S. EPA (2003) 

presents the food codes and definitions used to 

determine the various grain products used in the 

analysis. CSFII data on the foods people reported 

eating were converted to the quantities of agricultural 

commodities eaten. Intake rates for these food 

items/groups and summary statistics were generated 

on both a per capita and a consumer-only basis using 

the same general methodology as in the U.S. EPA 

analysis of 2003−2006 NHANES data, as described 

in Section 12.3.1.1. Because these data were 

developed for use in U.S. EPA’s pesticide registration 

program, the childhood age groups used are slightly 

different than those recommended in U.S. EPA’s 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

Table 12-13 presents per capita intake data for 

total grains in g/kg-day; Table 12-14 provides 

consumer-only intake data for total grains in 

g/kg-day. Table 12-15 provides per capita intake data 

for individual grain products, and Table 12-16 

provides consumer-only intake data for individual 

grain products. In general, these data represent intake 

of the edible portions of unprepared (i.e., uncooked) 

foods. Table 12-17 through Table 12-24 present per 

capita intake data for individual grain products. The 

data come from CSFII 1994−1996 only. The results 

are presented in units of g/kg-day. These data 

represent as-consumed intake rates. 

The results are presented in units of g/kg-day. 

Thus, use of these data in calculating potential dose 

does not require the body-weight factor to be 

included in the denominator of the ADD equation. 

The cautions concerning converting these intake rates 

into units of g/day by multiplying by a single average 

body weight and the discussion of the use of short 

term data in the NHANES description in 

Section 12.3.1.1, apply to the CSFII estimates as 

well. 

A strength of U.S. EPA’s analysis is that it 

provides distributions of intake rates for various age 

groups of individuals, normalized by body weight. 

The analysis uses the 1994−1996, 1998 CSFII data 

set, which was designed to be representative of the 

U.S. population. Also, the data set includes 4 years of 

intake data combined and is based on a 2-day survey 

period. However, as discussed above, short-term 

dietary data may not accurately reflect long-term 

eating patterns and may under-represent infrequent 

consumers of a given food. This is particularly true 

for the tails (extremes) of the distribution of food 

intake. Also, the analysis was conducted using 

slightly different childhood age groups than those 

recommended in U.S. EPA’s Guidance on Selecting 

Age Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. 

EPA, 2005). However, given the similarities in the 

childhood age groups used, the data should provide 

suitable intake estimates for the age groups of 

interest. While the CSFII data are older than the 

NHANES data, they provide relevant information on 

consumption by season, region of the United States, 

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and urbanization, breakdowns that are not available 

in the publically released NHANES data. 

12.3.2.5.	 Smiciklas-Wright et al. (2002)—Foods 

Commonly Eaten in the United States: 

Quantities Consumed per Eating 

Occasion and in a Day, 1994−1996 

Using data gathered in the 1994−1996 USDA 

CSFII, Smiciklas-Wright et al. (2002) calculated 

distributions for the quantities of grain products 

consumed per eating occasion by members of the 

U.S. population (i.e., serving sizes). The estimates of 

serving size are based on data obtained from 

14,262 respondents, ages two and above, who 

provided two days of dietary intake information. 

Only dietary intake data from users of the specified 

food were used in the analysis (i.e., consumer-only 

data). Table 12-25 presents, as-consumed, the 

quantity of grain products consumed per eating 

occasion and the percentage of individuals using 

these foods in a 2-day period for a selected variety of 

grain products. Table 12-26 presents the same data by 

sex and age. 

These data are presented on an as-consumed basis 

(grams) and represent the quantity of grain products 

consumed per eating occasion. These estimates may 

be useful for assessing acute exposures to 

contaminants in specific foods, or other assessments 

where the amount consumed per eating occasion is 

necessary. Only the mean and standard deviation 

serving size data and percent of the population 

consuming the food during the 2-day survey period 

are presented in this handbook. Percentiles of serving 

sizes of the foods consumed by these age groups of 

the U.S. population can be found in Smiciklas-Wright 

et al. (2002). 

The advantages of using these data are that they 

were derived from the USDA CSFII and are 

representative of the U.S. population. The analysis 

conducted by Smiciklas-Wright et al. (2002) 

accounted for individual foods consumed as 

ingredients of mixed foods. Mixed foods were 

disaggregated via recipe files so that the individual 

ingredients could be grouped together with similar 

foods that were reported separately. Thus, weights of 

foods consumed as ingredients were combined with 

weights of foods reported separately to provide a 

more thorough representation of consumption. 

However, it should be noted that since the recipes for 

the mixed foods consumed were not provided by the 

respondents, standard recipes were used. As a result, 

the estimates of quantity consumed for some food 

types are based on assumptions about the types and 

quantities of ingredients consumed as part of mixed 

foods. This study used data from the 1994 to 1996 

CSFII; data from the 1998 children’s supplement 

were not included. 

12.3.2.6.	 Vitolins et al. (2002)—Quality of Diets 

Consumed by Older Rural Adults 

Vitolins et al. (2002) conducted a survey to 

evaluate the dietary intake, by food groups, of older 

(>70 years) rural adults. The sample consisted of 

130 community dwelling residents from two rural 

counties in North Carolina. Data on dietary intake 

over the preceding year were obtained in face-to-face 

interviews conducted in participants’ homes, or in a 

few cases, a senior center. The food frequency 

questionnaire used in the survey was a modified 

version of the National Cancer Institute Health Habits 

and History Questionnaire; this modified version 

included an expanded food list containing a greater 

number of ethnic foods than the original food 

frequency form. Demographic and personal data 

collected included sex, ethnicity, age, education, 

denture use, marital status, chronic disease, and 

weight. 

Food items reported in the survey were grouped 

into food groups similar to the USDA Food Guide 

Pyramid and the National Cancer Institute’s 5 A Day 

for Better Health program. These groups are 

(1) fruits, and vegetables; (2) bread, cereal, rice, and 

pasta; (3) milk, yogurt, and cheese; (4) meat, fish, 

poultry, beans, and eggs; and (5) fats, oils, sweets, 

and snacks. Medians, ranges, frequencies, and 

percentages were used to summarize intake of each 

food group, broken down by demographic and health 

characteristics. In addition, multiple regression 

models were used to determine which demographic 

and health factors were jointly predictive of intake of 

each of the five food groups. 

Thirty-four percent of the survey participants 

were African American, 36% were European 

American, and 30% were Native American. 

Sixty-two percent were female, 62% were not 

married at the time of the interview, and 65% had 

some high school education or were high school 

graduates. Almost all of the participants (95%) had 

one or more chronic diseases. Sixty percent of the 

respondents were between 70 and 79 years of age; the 

median age was 78 years old. Table 12-27 presents 

the median servings of bread, cereal, rice, and pasta 

broken down by demographic and health 

characteristic. Only sex was statistically predictive of 

bread, cereal, rice, and pasta intake (p < 0.01), with 

males consuming approximately an extra serving per 

day compared to women. Also, the multiple 

regression model indicated that sex was predictive of 

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breads, cereal, rice, and pasta intake after controlling 

for other demographic variables. 

One limitation of the study, as noted by the study 

authors, is that the study did not collect information 

on the length of time the participants had been 

practicing the dietary behaviors reported in the 

survey. The questionnaire asked participants to report 

the frequency of food consumption during the past 

year. The study authors noted that, currently, there are 

no dietary assessment tools that allow the collection 

of comprehensive dietary data over years of food 

consumption. Another limitation of the study is that 

the small sample size used makes associations by sex 

and ethnicity difficult. 

12.3.2.7.	 Fox et al. (2004)—Feeding Infants and 

Toddlers Study: What Foods Are Infants 

and Toddlers Eating 

Fox et al. (2004) used data from the Feeding 

Infants and Toddlers study (FITS) to assess food 

consumption patterns in infants and toddlers. The 

FITS was sponsored by Gerber Products Company 

and was conducted to obtain current information on 

food and nutrient intakes of children, ages 4 to 

24 months old, in the 50 states and the District of 

Columbia. The FITS is described in detail in 

Devaney et al. (2004). FITS was based on a random 

sample of 3,022 infants and toddlers for which 

dietary intake data were collected by telephone from 

their parents or caregivers between March and July 

2002. An initial recruitment and household interview 

was conducted, followed by an interview to obtain 

information on intake based on 24-hour recall. The 

interview also addressed growth, development, and 

feeding patterns. A second dietary recall interview 

was conducted for a subset of 703 randomly selected 

respondents. The study over-sampled children in the 

4 to 6 and 9 to 11 months age groups; sample weights 

were adjusted for non-response, over sampling, and 

under coverage of some subgroups. The response rate 

for the FITS was 73% for the recruitment interview. 

Of the recruited households, there was a response rate 

of 94% for the dietary recall interviews (Devaney et 

al., 2004). Table 12-28 shows the characteristics of 

the FITS population. 

Fox et al. (2004) analyzed the first set of 24-hour 

recall data collected from all study participants. For 

this analysis, children were grouped into six age 

categories: 4 to 6 months, 7 to 8 months, 9 to 

11 months, 12 to 14 months, 15 to 18 months, and 19 

to 24 months. Table 12-29 provides the percentage of 

infants and toddlers consuming different types of 

grains or grain products at least once a day. The 

percentages of children eating any type of grain or 

grain product ranged from 65.8% for 4 to 6 montholds to 99.2% for 19- to 24-month-olds. 

The advantages of this study is that it represents 

the U.S. population, and the sample size was large. 

One limitation of the analysis done by Fox et al. 

(2004) is that only frequency data were provided; no 

information on actual intake rates was included. In 

addition, Devaney et al. (2004) noted several 

limitations associated with the FITS data. For the 

FITS, a commercial list of infants and toddlers was 

used to obtain the sample used in the study. Since 

many of the households could not be located and did 

not have children in the target population, a lower 

response rate than would have occurred in a true 

national sample was obtained (Devaney et al., 2004). 

In addition, the sample was likely from a higher 

socioeconomic status when compared with all U.S. 

infants in this age group (4 to 24 months old), and the 

use of a telephone survey may have omitted 

lower-income households without telephones 

(Devaney et al., 2004). 

12.3.2.8.	 Ponza et al. (2004)—Nutrient Food 

Intakes and Food Choices of Infants and 

Toddlers Participating in WIC 

Ponza et al. (2004) conducted a study using 

selected data from the FITS to assess feeding 

patterns, food choices, and nutrient intake of infants 

and toddlers participating in the Special 

Supplemental Nutrition Program for Women, Infants, 

and Children (WIC). Ponza et al. (2004) evaluated 

FITS data for the following age groups: 4 to 

6 months (N = 862), 7 to 11 months (N = 1,159), and 

12 to 24 months (N = 996). Table 12-30 shows the 

total sample size described by WIC participants and 

non-participants. 

The foods consumed were analyzed by tabulating 

the percentage of infants who consumed specific 

foods/food groups per day (Ponza et al., 2004). 

Weighted data were used in all of the analyses used in 

the study (Ponza et al., 2004). Table 12-30 presents 

the demographic data for WIC participants and 

non-participants. Table 12-31 provides information 

on the food choices for the infants and toddlers 

studied. In general, there was little difference in grain 

product choices among WIC participants and 

non-participants, except for the 7 to 11 months age 

category (see Table 12-31). Non-participants, ages 7 

to 11 months, were more likely to eat non-infant 

cereals than WIC participants. 

An advantage of this study is that it had a 

relatively large sample size and was representative of 

the U.S. general population of infants and children. A 

limitation of the study is that intake values for foods 

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Chapter 12—Intake of Grain Products 

were not provided. Other limitations are those 

associated with the FITS data, as described 

previously in Section 12.3.2.7. 

12.3.2.9.	 Fox et al. (2006)—Average Portion of 

Foods Commonly Eaten by Infants and 

Toddlers in the United States 

Fox et al. (2006) estimated average portion sizes 

consumed per eating occasion by children 4 to 

24 months of age who participated in the FITS. The 

FITS is a cross-sectional study designed to collect 

and analyze data on feeding practices, food 

consumption, and usual nutrient intake of U.S. 

infants and toddlers and is described in 

Section 12.3.2.7 of this chapter. It included a 

stratified random sample of 3,022 children between 4 

and 24 months of age. 

Using the 24-hour recall data, Fox et al. (2006) 

derived average portion sizes for six major food 

groups, including breads and grains. Average portion 

sizes for select individual foods within these major 

groups were also estimated. For this analysis, 

children were grouped into six age categories: 4 to 

5 months, 6 to 8 months, 9 to 11 months, 12 to 

14 months, 15 to 18 months, and 19 to 24 months. 

Table 12-32 and Table 12-33 present the average 

portion sizes for grain products for infants and 

toddlers, respectively. 

12.3.2.10. Mennella et al. (2006)—Feeding Infants 

and Toddlers Study: The Types of Foods 

Fed to Hispanic Infants and Toddlers 

Mennella et al. (2006) investigated the types of 

food and beverages consumed by Hispanic infants 

and toddlers in comparison to the non-Hispanic 

infants and toddlers in the United States. The FITS 

2002 data for children between 4 and 24 months of 

age were used for the study. The data represent a 

random sample of 371 Hispanic and 

2,367 non-Hispanic infants and toddlers (Mennella et 

al., 2006). Mennella et al. (2006) grouped the infants 

as follows: 4 to 5 months (N = 84 Hispanic; 

538 non-Hispanic), 6 to 11 months 

(N = 163 Hispanic; 1,228 non-Hispanic), and 12 to 

24 months (N = 124 Hispanic; 871 non-Hispanic) of 

age. 

Table 12-34 provides the percentage of Hispanic 

and non-Hispanic infants and toddlers consuming 

grain products. In most instances, the percentages 

consuming the different types are similar. However, 6 

to 11 month old Hispanic children were more likely 

to eat rice and pasta than non-Hispanic children in 

this age groups. 

The advantage of the study is that it provides 

information on food preferences for Hispanic and 

non-Hispanic infants and toddlers. A limitation is that 

the study did not provide food intake data but 

provided frequency of use data instead. Other 

limitations are those noted previously in 

Section 12.3.2.7 for the FITS data. 

12.4.	 CONVERSION BETWEEN WET- AND 

DRY-WEIGHT INTAKE RATES 

The intake data presented in this chapter are 

reported in units of wet weight (i.e., as-consumed or 

uncooked weight of grain products consumed per day 

or per eating occasion). However, data on the 

concentration of contaminants in grain products may 

be reported in units of either wet or dry weight (e.g., 

mg contaminant per gram dry weight of grain 

products). It is essential that exposure assessors be 

aware of this difference, so that they may ensure 

consistency between the units used for intake rates 

and those used for concentration data (i.e., if the 

contaminant concentration is measured in dry weight 

of grain products, then the dry-weight units should be 

used for their intake values). 

If necessary, wet-weight (e.g., as-consumed) 

intake rates may be converted to dry-weight intake 

rates using the moisture content percentages 

presented in Table 12-35 and the following equation: 

IR = IR 100 −W  dw ww	 (Eqn. 12-1)    100 

where: 

IRdw = dry-weight intake rate, 

IRww = wet-weight intake rate, and 

W = percent water content. 

Alternatively, dry-weight residue levels in grain 

products may be converted to wet-weight residue 

levels for use with wet-weight (e.g., as-consumed) 

intake rates as follows: 

C = C 100 −W  ww dw (Eqn. 12-2)    100 

where: 

Cww = wet concentration rate,
 

Cdw = dry-weight concentration, and
 

W = percent water content.
 

Page Exposure Factors Handbook 

12-10 September 2011 
Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Exposure Factors Handbook Page
 

September 2011 12-11
 

The moisture data presented in Table 12-35 are 

for selected grain products taken from USDA (2007). 

12.5. REFERENCES FOR CHAPTER 12 

Devaney, B; Kalb, L; Briefel, R; Zavitsky-Novak, T; 

Clusen, N; Ziegler, P. (2004). Feeding 

infants and toddlers study: overview of the 

study design. J Am Diet Assoc 104: s8-13. 

http://dx.doi.org/10.1016/j.jada.2003.10.023. 

Fox, MK; Pac, S; Devaney, B; Jankowski, L. (2004). 

Feeding infants and toddlers study: What 

foods are infants and toddlers eating? J Am 

Diet Assoc 104: s22-s30. 

http://dx.doi.org/10.1016/j.jada.2003.10.026. 

Fox, MK; Reidy, K; Karwe, V; Ziegler, P. (2006). 

Average portions of foods commonly eaten 

by infants and toddlers in the United States. 

J Am Diet Assoc 106: S66-S76. 

http://dx.doi.org/10.1016/j.jada.2005.09.042. 

Mennella, JA; Ziegler, P; Briefel, R; Novak, T. 

(2006). Feeding Infants and Toddlers Study: 

the types of foods fed to Hispanic infants 

and toddlers. J Am Diet Assoc 106: S96­

106. 

http://dx.doi.org/10.1016/j.jada.2005.09.038. 

NCHS (National Center for Health Statistics). (1993). 

Joint policy on variance estimation and 

statistical reporting standards on NHANES 

III and CSFII reports: HNIS/NCHS Analytic 

Working Group recommendations. 

Riverdale, MD: Human Nutrition 

Information Service (HNIS)/Analytic 

Working Group. Agricultural Research 

Service, Survey Systems/Food Consumption 

Laboratory. 

Ponza, M; Devaney, B; Ziegler, P; Reidy, K; 

Squatrito, C. (2004). Nutrient intakes and 

food choices of infants and toddlers 

participating in WIC. J Am Diet Assoc 104: 

s71-s79. 

http://dx.doi.org/10.1016/j.jada.2003.10.018. 

Smiciklas-Wright, H; Mitchell, DC; Mickle, SJ; 

Cook, AJ; Goldman, JD. (2002). Foods 

commonly eaten in the United States: 

Quantities consumed per eating occasion 

and in a day, 1994−96 [pre-publication 

version]. (NFS Report No. 96-5). Beltsville, 

MD: U.S. Department of Agriculture. 

http://www.ars.usda.gov/sp2userfiles/place/1 

2355000/pdf/portion.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000). Food commodity intake database 

[Database]. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2003). CSFII analysis of food intake 

distributions. (EPA/600/R-03/029). 

Washington, DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=56610. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum. 

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

USDA (U.S. Department of Agriculture). (1980). 

Food and nutrient intakes of individuals in 1 

day in the United States, Spring 1977. 

Nationwide Food Consumption Survey 

1977–78: Preliminary report no. 2. 

Washington, DC. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/7778/nfcs7778_prelim_2.pdf 

. 

USDA (U.S. Department of Agriculture). (1993). 

Food and nutrient intakes by individuals in 

the United States, 1 day, 1987–88. 

Nationwide Food Consumption Survey 

1987-88: Report no. 87-I-1. (87-I-1). 

Washington, DC. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/8788/nfcs8788_rep_87-i1.pdf. 

USDA (U.S. Department of Agriculture). (1996a). 

Data tables: Results from USDA's 1994 

continuing survey of food intakes by 

individuals and 1994 diet and health 

knowledge survey. Riverdale, MD. 

USDA (U.S. Department of Agriculture). (1996b). 

Data tables: results from USDA’s 1995 

Continuing survey of food intakes by 

individuals and 1995 diet and health 

knowledge survey. Riverdale, MD. 

USDA (U.S. Department of Agriculture). (1999a). 

Food and nutrient intakes by children 1994­

96, 1998: table set 17. Beltsville, MD. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/scs_all.pdf. 

USDA (U.S. Department of Agriculture). (1999b). 

Food consumption prices and expenditures 

(1970−1997). Statistical Bulletin, No. 965. 

Washington, DC: Economic Research 

Service. 

USDA (U.S. Department of Agriculture). (2000). 

1994-1996, 1998 continuing survey of food 
 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

intakes by individuals (CSFII). Beltsville, 

MD: Agricultural Research Service, 

Beltsville Human Nutrition Research Center. 

USDA (U.S. Department of Agriculture). (2007). 

USDA nutrient database for standard 

reference, release 20. Riverdale, MD. 

http://www.ars.usda.gov/main/site_main.htm 

?modecode=12-35-45-00. 

Vitolins, MZ; Quandt, SA; Bell, RA; Arcury, TA; 

Case, LD. (2002). Quality of diets consumed 

by older rural adults. J Rural Health 18: 49­

56. 

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Exposure Factors Handbook Chapter 12—Intake of Grain Products 

Table 12-3. Per Capita Intake of Total Grains Based 2003–2006 NHANES (g/kg-day, edible portion, uncooked weight) 

Population Group 

% 

Consuming 

Percentiles 

N Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 16,783 100 2.6 0.04 0.2 0.6 0.8 1.3 2.0 3.2 5.1 6.7 9.9 34.8* 

Age Group 

Birth to 1 year 865 76 3.1 0.20 0.0* 0.0* 0.0 0.1 2.3 5.0 7.5 9.5* 12.5* 34.9* 

1 to 2 years 1,052 100 6.4 0.17 1.5* 2.3* 3.0 4.2 5.8 8.4 10.5 12.4* 15.9* 21.1* 

3 to 5 years 978 100 6.2 0.13 2.0* 2.4 3.3 4.4 5.9 7.6 9.6 11.1 13.2* 15.6* 

6 to 12 years 2,256 100 4.4 0.09 0.6* 1.4 1.8 2.8 4.1 5.5 7.4 8.2 11.1* 14.5* 

13 to 19 years 3,450 100 2.4 0.05 0.4 0.7 1.0 1.5 2.1 3.2 4.2 5.0 7.5 14.3* 

20 to 49 years 4,289 100 2.2 0.04 0.3 0.6 0.8 1.2 1.9 2.8 3.9 4.6 7.1 15.0* 

Females 13 to 49 years 4,103 100 1.9 0.04 0.2 0.5 0.8 1.1 1.7 2.5 3.4 3.9 5.5 9.8* 

50 years and older 3,893 100 1.7 0.03 0.3 0.5 0.7 1.0 1.5 2.1 2.9 3.5 5.2 9.4* 

Race 

Mexican American 4,450 99 3.0 0.05 0.1 0.8 1.0 1.6 2.4 3.9 5.8 7.2 10.6 17.8* 

Non-Hispanic Black 4,265 100 2.4 0.04 0.2 0.5 0.7 1.1 1.8 2.9 5.0 6.8 10.2 21.1* 

Non-Hispanic White 6,757 100 2.5 0.05 0.3 0.6 0.8 1.3 1.9 3.1 4.9 6.5 9.6 34.8* 

Other Hispanic 562 99 2.7 0.13 0.2* 0.7 1.0 1.5 2.1 3.3 5.3 7.0 9.8* 15.3* 

Other Race—Including Multiple Races 749 100 3.0 0.11 0.3* 0.6 0.9 1.5 2.5 3.9 6.0 7.5 11.1* 17.5* 

N = Sample size. 

SE = Standard error. 

Max = Maximum value. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting Standards on 

NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Source: Based on U.S. EPA analysis of 2003–2006 NHANES. 

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Chapter 12—Intake of Grain Products 

Table 12-4. Consumer-Only Intake of Total Grains Based 2003–2006 NHANES (g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE 

Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 16,556 2.6 0.04 0.3 0.6 0.8 1.3 2.0 3.2 5.1 6.7 9.9 

Age Group 

Birth to 1 year 644 4.1 0.18 0.1* 0.4* 0.8* 1.8 3.5 5.9 8.1* 10.3* 13.9* 

1 to 2 years 1,050 6.4 0.16 1.6* 2.4* 3.0 4.2 5.8 8.4 10.5 12.4* 15.9* 

3 to 5 years 977 6.2 0.13 2.0* 2.4 3.3 4.4 5.9 7.6 9.6 11.1 13.2* 

6 to 12 years 2,256 4.4 0.09 0.6* 1.4 1.8 2.8 4.1 5.5 7.4 8.2 11.1* 

13 to 19 years 3,450 2.4 0.05 0.4 0.7 1.0 1.5 2.1 3.2 4.2 5.0 7.5 

20 to 49 years 4,288 2.2 0.04 0.3 0.6 0.8 1.2 1.9 2.8 3.9 4.6 7.1 

Females 13 to 49 years 4,102 1.9 0.03 0.2 0.5 0.8 1.1 1.7 2.5 3.4 3.9 5.5 

50 years and older 3,891 1.7 0.03 0.3 0.5 0.7 1.0 1.5 2.1 2.9 3.5 5.2 

Race 

Mexican American 4,341 3.0 0.05 0.4 0.8 1.1 1.6 2.4 3.9 5.9 7.2 10.6 

Non-Hispanic Black 4,236 2.4 0.04 0.2 0.5 0.7 1.1 1.8 2.9 5.0 6.9 10.3 

Non-Hispanic White 6,694 2.5 0.05 0.3 0.6 0.8 1.3 2.0 3.1 4.9 6.5 9.6 

Other Hispanic 548 2.8 0.14 0.4* 0.7 1.0 1.5 2.1 3.4 5.4 7.1 9.8* 

Other Race—Including Multiple Races 737 3.1 0.11 0.3* 0.7 0.9 1.5 2.5 3.9 6.0 7.5 11.1* 

34.9* 

34.9* 

21.1* 

15.6* 

14.5* 

14.3* 

15.0* 

9.8* 

9.4* 

17.8* 

21.1* 

34.9* 

15.3* 

17.5* 

N = Sample size. 

SE = Standard error. 

Max = Maximum value. 

* Estimates are less statistically reliable based on guidance published in the Joint Policy on Variance Estimation and Statistical Reporting 

Standards on NHANES III and CSFII Reports: NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Source: Based on U.S. EPA analysis of 2003–2006 NHANES. 

Page Exposure Factors Handbook 12-14 September 2011
Table 12-5. Per Capita Intake of Individual Grain Products Based 2003–2006 NHANES 

(g/kg-day, edible portion, uncooked weight) 

Population Group N 

% 

Consuming Mean SE 

% 

Consuming Mean SE 

Cereal Rice 

Whole Population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 Females 13 to 49 years 

 50 years and older 

Race 

 Mexican American 

 Non-Hispanic Black 

 Non-Hispanic White 

 Other Hispanic 

Other Race—Including Multiple 

Races 

16,783 

865 

1,052 

978 

2,256 

3,450 

4,289 

4,103 

3,893 

4,450 

4,265 

6,757 

562 

749 

100 

81 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

99 

100 

3.7 

5.1 

8.7 

8.6 

6.3 

3.9 

3.2 

2.9 

2.2 

4.3 

3.6 

3.6 

3.9 

4.1 

0.04 

0.30 

0.18 

0.17 

0.10 

0.08 

0.04 

0.04 

0.04 

0.07 

0.06 

0.05 

0.20 

0.12 

88 

69 

87 

91 

89 

85 

89 

86 

89 

87 

86 

88 

92 

90 

0.2 

1.1 

0.6 

0.5 

0.3 

0.2 

0.3 

0.2 

0.1 

0.3 

0.3 

0.2 

0.6 

0.8 

0.01 

0.08 

0.06 

0.06 

0.03 

0.01 

0.01 

0.01 

0.01 

0.02 

0.02 

0.01 

0.05 

0.08 

N 

SE 

Source: 

= Sample size. 

= Standard error. 

Based on U.S. EPA analysis of 2003–2006 NHANES. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

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September 2011 12-15 
 

Table 12-6. Consumer-Only Intake of Individual Grain Products Based 2003–2006 NHANES 

(g/kg-day, edible portion, uncooked weight) 

Population Group 

N Mean SE N Mean SE 

Cereal Rice 

Whole Population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 Females 13 to 49 years 

 50 years and older 

Race 

 Mexican American 

 Non-Hispanic Black 

 Non-Hispanic White 

 Other Hispanic 

 Other Race—Including Multiple Races 

 16,613 

 696 

 1,051 

 978 

 2,256 

 3,450 

 4,289 

 4,103 

 3,893 

 4,372 

 4,244 

 6,707 

 550 

 740 

3.7 

6.3 

8.7 

8.6 

6.3 

3.9 

3.2 

2.9 

2.2 

4.3 

3.6 

3.6 

3.9 

4.1 

0.04 

0.31 

0.18 

0.17 

0.10 

0.08 

0.04 

0.04 

0.04 

0.07 

0.06 

0.05 

0.20 

0.13 

 14,447 

 552 

 928 

 875 

 2,000 

 2,898 

 3,812 

 3,511 

 3,382 

 3,757 

 3,645 

 5,887 

 491 

 667 

0.3 

1.5 

0.7 

0.5 

0.3 

0.2 

0.3 

0.2 

0.2 

0.3 

0.3 

0.2 

0.6 

0.8 

0.01 

0.10 

0.07 

0.06 

0.03 

0.02 

0.02 

0.02 

0.01 

0.02 

0.02 

0.01 

0.05 

0.08 

N 

SE 

Source: 

= Sample size. 

= Standard error. 

Based on U.S. EPA analysis of 2003–2006 NHANES. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 

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Chapter 12—Intake of Grain Products 

Table 12-7. Mean Grain Intake per Individual in a Day by Sex and Age (g/day as-consumed)a for 1977−1978 

Group Age (years) Total Grains Breads, Rolls, 

Biscuits 

Other Baked 

Goods Cereals, Pasta Mixtures, Mainly Grainb 

Males and Females 

<1 

1 to 2 

3 to 5 

6 to 8 

42 

158 

181 

206 

4 

27 

46 

53 

5 

24 

37 

56 

30 

44 

54 

60 

3 

63 

45 

38 

Males 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

≥75 

238 

288 

303 

253 

256 

234 

229 

235 

196 

67 

76 

91 

84 

82 

82 

78 

71 

70 

56 

80 

77 

53 

60 

58 

57 

60 

50 

51 

57 

53 

64 

40 

44 

48 

69 

58 

64 

74 

82 

52 

74 

50 

46 

35 

19 

Females 

9 to 11 

12 to 14 

15 to 18 

19 to 22 

23 to 34 

35 to 50 

51 to 64 

65 to 74 

≥75 

214 

235 

196 

161 

163 

161 

155 

175 

178 

58 

57 

57 

44 

49 

49 

52 

57 

54 

59 

61 

43 

36 

38 

37 

40 

42 

44 

44 

45 

41 

33 

32 

32 

36 

47 

58 

53 

72 

55 

48 

44 

43 

27 

29 

22 

Males and Females—All Ages 204 62 49 44 49 a Based on USDA Nationwide Food Consumption Survey 1977–1978 data for 1 day. b Includes mixtures containing grain as the main ingredient. 

Source: USDA (1980). 

Exposure Factors Handbook Page
 

September 2011 12-17 
Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 

12-18 September 2011 

Table 12-8. Mean Grain Intakes per Individual in a Day by Sex and Age (g/day as-consumed)a for 1987−1988 

Group 

Age (years) Total Grains Yeast Breads and 

Rolls 

Quick Breads, 

Pancakes, 

French Toast 

Cakes, 

Cookies, 

Pastries, 

Pies 

Crackers, 

Popcorn, 

Pretzels, 

Corn Chips 

Cereals and 

Pastas 

Mixtures, 

Mostly Grainb 

Males and 

Females ≤5 167 30 8 22 4 52 51 

Males 

6 to 11 268 51 16 37 8 74 83 

12 to 19 304 65 28 45 10 72 82 

≥20 272 65 20 37 8 58 83 

Females 

6 to 11 231 43 19 30 6 66 68 

12 to 19 239 45 13 29 7 52 91 

≥20 208 45 14 28 6 53 62 

All Individuals 237 52 16 32 7 57 72 a Based on USDA Nationwide Food Consumption Survey 1987–1988 data for 1 day. b Includes mixtures containing grain as the main ingredient. 

Source: USDA (1993). 

 

 

 

 

 

Table 12-9. Mean Grain Intakes per Individual in a Day by Sex and Age (g/day as-consumed)a for 1994−1995 

Group 

Age (years) 

Total Grains Yeast Breads 

and Rolls 

Quick Breads, 

Pancakes, 

French Toast 

Cakes, 

Cookies, 

Pastries, Pies 

Crackers, 

Popcorn, 

Pretzels, Corn 

Chips 

Cereals and 

Pastas 

Mixtures, 

Mostly Grainb 

1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 

Males and 

Females ≤5 213 210 26 28 11 11 22 23 8 7 58 57 89 84 

Males 

6 to 11 

12 to 19 

≥20 

285 

417 

357 

341 

364 

365 

51 

53 

64 

45 

54 

61 

15 

30 

22 

21 

21 

24 

42 

54 

43 

46 

43 

46 

12 

17 

13 

18 

22 

15 

66 

82 

86 

97 

84 

91 

101 

180 

128 

115 

138 

128 

Females 

6 to 11 

12 to 19 

≥20 

260 

317 

254 

286 

296 

257 

43 

40 

44 

46 

37 

45 

16 

16 

16 

21 

14 

15 

37 

39 

33 

51 

35 

34 

11 

17 

9 

14 

16 

10 

57 

63 

59 

54 

52 

69 

94 

142 

92 

100 

143 

83 

All Individuals 300 303 50 49 18 19 38 39 12 13 70 76 112 107 a Based on USDA CSFII 1994 and 1995 data for 1 day. b Includes mixtures containing grain as the main ingredient. 

Source: USDA (1996a, b). 
 

 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Table 12-10. Per Capita Consumption of Flour and Cereal Products in 1997 

Food Item 

Per Capita Consumption 

(g/day)

a 

Total Wheat Flourb 

Rye Flour 

Ricec 

Total Corn Productsd 

Oat Productse 

Barley Productsf 

Total Flour and Cereal Productsg 

186 

0.7 

24 

29 

8 

0.9 

249 a Original data were presented in lbs/year; data were converted to g/day by multiplying by a factor of 454 g/lb and 

dividing by 365 day/year. Consumption of most items at the processing level. Excludes quantities used in alcoholic 

beverages and fuel. b Includes white, whole wheat, and durum flour. c Milled basis. d Includes corn flour and meal, hominy and grits, and corn starch. e Includes rolled oats, ready-to-eat oat cereals, oat flour, and oat bran. f Includes barley flour, pearl barley, and malt and malt extract used in food processing. g Excludes wheat not ground into flour. 

Source: USDA (1999b). 

Exposure Factors Handbook Page
 

September 2011 12-19 
Table 12-11. Mean Quantities of Grain Products Consumed by Children Under 20 Years of Age, by Sex and Age, per Capita (g/day, as-consumed)a 

Yeast, Cereals and Pasta Cakes, Crackers, Quick Breads, Mixtures, Age Group Sample Breads, Cookies, Popcorn, Total

b Ready-to- Pancakes, Mainly (years) Size and Total Rice Pasta Pastries, Pretzels, Eat Cereals French Toast Grainc 

Rolls Pies Corn Chips 

Males and Females 

<1 1,126 56 2 29 1 2 1d 1 3 1 20 

1 1,016 192 16 57 11 9 9 9 16 7 87 

2 1,102 219 26 62 16 15 12 12 22 9 87 

1 to 2 2,118 206 21 59 13 12 11 11 19 8 87 

3 1,831 242 30 64 19 13 12 16 23 11 98 

4 1,859 264 36 67 22 15 11 17 30 13 102 

5 884 284 41 76 24 17 11 15 33 13 107 

3 to 5 4,574 264 36 69 22 15 11 16 29 12 102 

≤5 7,818 219 27 61 16 13 10 12 22 9 87 

Males 

6 to 9 787 310 45 77 28 18 15 23 39 16 109 

6 to 11 1,031 318 46 80 31 16 18 23 40 15 115 

12 to 19 737 406 54 82 29 27 17 26 49 19 175 

Females 

6 to 9 704 284 43 61 21 12 15 18 42 13 107 

6 to 11 969 280 43 62 20 14 15 19 42 14 101 

12 to 19 732 306 40 67 17 19 22 15 37 15 132 

Males and Females 

≤9 9,309 250 34 64 20 14 12 16 30 12 96 

≤19 11,287 298 40 69 22 17 15 18 36 14 120 a Based on data from 1994–1996, 1998 CSFII. b Includes yeast breads, rolls, cereals, pastas, quick breads, pancakes, French toast, cakes, cookies, pastries, pies, crackers, popcorn, pretzels, corn 

chips, and mixtures having a grain product as a main ingredient. Excludes grain products that were ingredients in food mixtures coded as a single 

item and tabulated under another food group; for example, noodles in tuna-noodle casserole are tabulated under Meat, Poultry, and Fish. c Includes mixtures having a grain product as a main ingredient, such as burritos, tacos, pizza, egg rolls, quiche, spaghetti with sauce, rice and pasta 

mixtures; frozen meals in which the main course is a grain mixture; noodle and rice soups; and baby-food macaroni and spaghetti mixtures. d Estimate is not statistically reliable due to small sample size reporting intake. 

Note: Consumption amounts shown are representative of the first day of each participant’s survey response. 

Source: USDA (1999a). 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 12-20 September 2011
 

 

 

Chapter 12—Intake of Grain Products Exposure Factors Handbook 

Table 12-12. Percentage of Individuals Under 20 Years of Age Consuming Grain Products, by Sex and Age (%)a 

Age Group (years) Sample 

Size Totalb 

Yeast, 

Breads 

and 

Rolls 

Cereals and Pasta Quick 

Breads, 

Pancakes, 

French Toast 

Cakes, 

Cookies, 

Pastries, 

Pies 

Crackers, 

Popcorn, 

Pretzels, 

Corn Chips 

Mixtures, 

Mainly 

Grain Total c

Ready-toEat 

Cereals 

Rice Pasta 

Males and Females 

<1 1,126 70.6 10.9 62.8 9.1 3.4 2.1 4.4 16.5 10.3 15.0 

1 1,016 98.2d 48.4 70.6 45.3 11.3 9.4 23.0 47.0 39.0 47.8 

2 1,102 99.0d 58.7 71.1 51.9 14.4 9.4 27.5 46.6 37.9 45.3 

1 to 2 2,118 98.7 53.7 70.9 48.7 12.9 9.4 25.3 46.8 38.4 46.5 

3 1,831 99.4d 64.1 69.7 53.3 11.1 8.6 28.8 46.1 38.5 49.0 

4 1,859 99.5d 67.0 69.1 54.8 11.4 7.1 28.6 52.3 39.4 46.2 

5 884 99.9d 69.2 70.4 54.9 11.4 6.8 25.2 52.4 32.1 47.4 

3 to 5 4,574 99.6d 66.8 69.7 54.3 11.3 7.5 27.5 50.3 36.7 47.5 

≤5 7,818 95.8 55.5 69.3 46.9 10.9 7.5 24.0 45.0 34.1 43.3 

Males 

6 to 9 787 98.9d 69.8 62.6 50.8 10.5 7.4 28.1 52.5 36.0 44.5 

6 to 11 1,031 99.0d 69.1 64.0 52.4 9.7 8.1 27.1 52.3 33.8 45.3 

12 to 19 737 98.2d 62.7 44.6 33.2 10.0 5.9 24.4 41.3 27.2 46.2 

Females 

6 to 9 704 99.7d 71.5 61.2 47.6 9.0 7.9 26.3 57.1 38.3 48.0 

6 to 11 969 99.3d 71.0 59.3 45.6 9.4 7.1 27.1 55.0 37.1 45.7 

12 to 19 732 97.6d 60.9 45.9 30.3 8.6 9.3 19.8 40.6 30.9 46.1 

Males and Females 

≤9 9,309 97.2 61.6 66.4 47.9 10.5 7.6 25.3 48.9 35.3 44.4 

≤19 11,287 97.6 62.4 57.6 41.7 9.9 7.6 24.2 46.1 32.5 45.1 a Based on data from 1994–1996, 1998 CSFII. b Includes yeast breads, rolls, cereals, pastas, quick breads, pancakes, French toast, cakes, cookies, pastries, pies, crackers, popcorn, 

pretzels, corn chips, and mixtures having a grain product as a main ingredient. Excludes grain products that were ingredients in food 

mixtures coded as a single item and tabulated under another food group; for example, noodles in tuna-noodle casserole are tabulated 

under Meat, Poultry, and Fish. c Includes mixtures having a grain product as a main ingredient, such as burritos, tacos, pizza, egg rolls, quiche, spaghetti with sauce, rice 

and pasta mixtures; frozen meals in which the main course is a grain mixture; noodle and rice soups; and baby-food macaroni and 

spaghetti mixtures. d Estimate is not statistically reliable due to small sample size reporting intake. 

Note: Percentages shown are representative of the first day of each participant’s survey response. 

Source: USDA (1999a). 

Exposure Factors Handbook PageSeptember 2011 12-21
Page Exposure Factors Handbook 

12-22 September 2011

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Table 12-13. Per Capita Intake of Total Grains Based on 1994–1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

Population Group N Percent 

Consuming Mean SE Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 ≥50 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian, Pacific Islander 

 Black 

 American Indian, Alaskan Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

20,607 

1,486 

2,096 

4,391 

2,089 

1,222 

4,677 

4,646 

4,687 

5,308 

5,890 

4,722 

557 

2,740 

177 

1,638 

15,495 

4,822 

3,692 

7,208 

4,885 

6,164 

9,598 

4,845 

99.5 

70.5 

99.8 

100.0 

100.0 

100.0 

99.9 

100.0 

99.5 

99.6 

99.5 

99.5 

98.5 

99.4 

99.7 

98.8 

99.6 

99.7 

99.6 

99.5 

99.4 

99.5 

99.5 

99.6 

2.7 

2.5 

6.4 

6.3 

4.3 

2.5 

2.2 

1.7 

2.6 

2.7 

2.6 

2.7 

3.6 

2.6 

2.9 

3.1 

2.6 

2.7 

2.8 

2.5 

2.8 

2.7 

2.7 

2.4 

0.0 

0.1 

0.1 

0.1 

0.1 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.2 

0.1 

0.2 

0.1 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.1 

0.2 

0.0 

1.1 

1.8 

0.9 

0.4 

0.3 

0.3 

0.2 

0.2 

0.3 

0.2 

0.0 

0.1 

0.3 

0.0 

0.3 

0.3 

0.3 

0.2 

0.2 

0.1 

0.3 

0.3 

0.6 

0.0 

2.1 

2.6 

1.7 

0.8 

0.6 

0.6 

0.6 

0.6 

0.7 

0.6 

1.1 

0.5 

0.5 

0.7 

0.7 

0.7 

0.7 

0.6 

0.7 

0.6 

0.7 

0.6 

0.9 

0.0 

2.8 

3.2 

2.0 

1.1 

0.8 

0.7 

0.9 

0.8 

0.9 

0.9 

1.5 

0.7 

0.8 

0.9 

0.9 

0.9 

1.0 

0.8 

0.9 

0.9 

0.9 

0.8 

1.3 

0.0 

4.2 

4.3 

2.8 

1.5 

1.3 

1.1 

1.3 

1.3 

1.3 

1.4 

2.3 

1.1 

1.3 

1.5 

1.3 

1.4 

1.4 

1.2 

1.4 

1.3 

1.4 

1.2 

2.1 

1.6 

5.9 

5.9 

4.0 

2.3 

1.9 

1.5 

2.1 

2.1 

2.1 

2.1 

3.2 

1.9 

2.2 

2.4 

2.0 

2.1 

2.2 

1.9 

2.2 

2.1 

2.1 

1.9 

3.3 

3.8 

7.9 

7.8 

5.4 

3.1 

2.8 

2.1 

3.3 

3.4 

3.3 

3.3 

4.7 

3.3 

4.2 

4.1 

3.2 

3.4 

3.5 

3.0 

3.5 

3.5 

3.4 

2.9 

5.2 

6.2 

10.4 

9.9 

7.0 

4.4 

3.9 

2.8 

5.0 

5.5 

5.1 

5.2 

6.2 

5.4 

6.3 

6.1 

5.0 

5.3 

5.3 

5.0 

5.4 

5.4 

5.3 

4.8 

6.8 

8.6 

12.1 

11.5 

8.2 

5.1 

4.7 

3.5 

6.6 

7.0 

6.8 

6.8 

7.3 

7.3 

7.5 

7.7 

6.6 

7.0 

6.8 

6.6 

7.0 

7.0 

6.9 

6.3 

10.3 

12.7 

16.8 

15.6 

11.1 

7.9 

7.1 

4.9 

10.0 

10.5 

10.5 

10.1 

11.2 

11.5 

12.0 

11.7 

9.8 

10.4 

11.0 

9.7 

10.3 

10.7 

10.0 

10.4 

31.6 

26.3 

31.6 

27.0 

17.2 

12.4 

16.1 

11.2 

26.3 

29.4 

28.2 

31.6 

24.6 

29.4 

16.8 

27.0 

31.6 

23.8 

31.6 

28.2 

20.8 

29.4 

31.6 

23.8 

N 

SE 

Source: 

= Sample size. 

= Standard error. 

U.S. EPA analysis of 1994–1996, 1998 CSFII. 
Exposure Factors Handbook Page 

September 2011 12-23 

Chapter 12—Intake of Grain Products Exposure Factors Handbook 

Table 12-14. Consumer-Only Intake of Total Grains Based on 1994–1996, 1998 CSFII (g/kg-day, edible portion, uncooked weight) 

Population Group N Mean SE Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 Birth to 1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 12 years 

 13 to 19 years 

 20 to 49 years 

 ≥50 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian, Pacific Islander 

 Black 

 American Indian, Alaskan Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

20,157 

1,048 

2,092 

4,389 

2,089 

1,222 

4,673 

4,644 

4,587 

5,190 

5,751 

4,629 

527 

2,675 

175 

1,570 

15,210 

4,743 

3,628 

7,053 

4,733 

6,023 

9,378 

4,756 

2.7 

3.6 

6.4 

6.3 

4.3 

2.5 

2.2 

1.7 

2.6 

2.7 

2.7 

2.7 

3.7 

2.6 

3.0 

3.2 

2.6 

2.7 

2.8 

2.5 

2.8 

2.8 

2.7 

2.4 

0.0 

0.1 

0.1 

0.1 

0.1 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.2 

0.1 

0.2 

0.1 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.1 

0.3 

0.1 

1.2 

1.8 

0.9 

0.4 

0.3 

0.3 

0.3 

0.3 

0.4 

0.3 

0.8 

0.2 

0.3 

0.5 

0.4 

0.4 

0.4 

0.3 

0.4 

0.3 

0.4 

0.3 

0.7 

0.3 

2.1 

2.6 

1.7 

0.8 

0.6 

0.6 

0.7 

0.7 

0.7 

0.7 

1.2 

0.5 

0.5 

0.7 

0.7 

0.7 

0.8 

0.6 

0.7 

0.7 

0.7 

0.6 

0.9 

0.6 

2.8 

3.2 

2.0 

1.1 

0.8 

0.7 

0.9 

0.9 

0.9 

0.9 

1.6 

0.7 

0.8 

1.0 

0.9 

0.9 

1.0 

0.8 

0.9 

0.9 

0.9 

0.8 

1.3 

1.4 

4.2 

4.3 

2.8 

1.5 

1.3 

1.1 

1.3 

1.3 

1.4 

1.4 

2.3 

1.1 

1.3 

1.5 

1.3 

1.4 

1.4 

1.2 

1.4 

1.3 

1.4 

1.2 

2.1 

2.8 

5.9 

5.9 

4.0 

2.3 

1.9 

1.5 

2.1 

2.1 

2.1 

2.1 

3.2 

1.9 

2.2 

2.4 

2.0 

2.1 

2.2 

1.9 

2.2 

2.1 

2.1 

1.9 

3.3 

4.8 

7.9 

7.8 

5.4 

3.1 

2.8 

2.1 

3.3 

3.4 

3.3 

3.3 

4.7 

3.3 

4.2 

4.1 

3.2 

3.4 

3.5 

3.0 

3.5 

3.5 

3.4 

2.9 

5.2 

7.4 

10.4 

9.9 

7.0 

4.4 

3.9 

2.8 

5.0 

5.5 

5.2 

5.2 

6.2 

5.4 

6.3 

6.2 

5.1 

5.3 

5.3 

5.0 

5.4 

5.4 

5.3 

4.8 

6.8 

9.2 

12.1 

11.5 

8.2 

5.1 

4.7 

3.5 

6.6 

7.0 

6.8 

6.8 

7.3 

7.3 

7.5 

7.7 

6.6 

7.0 

6.8 

6.6 

7.0 

7.0 

6.9 

6.4 

10.3 

13.4 

16.8 

15.6 

11.1 

7.9 

7.1 

4.9 

10.0 

10.6 

10.5 

10.1 

11.2 

11.5 

12.0 

11.7 

9.8 

10.4 

11.0 

9.8 

10.3 

10.7 

10.0 

10.4 

31.6 

26.3 

31.6 

27.0 

17.2 

12.4 

16.1 

11.2 

26.3 

29.4 

28.2 

31.6 

24.6 

29.4 

16.8 

27.0 

31.6 

23.8 

31.6 

28.2 

20.8 

29.4 

31.6 

23.8 

N 

SE 

Source: 

= Sample size. 

= Standard error. 

U.S. EPA analysis of 1994–1996, 1998 CSFII. 
 

Table 12-15. Per Capita Intake of Individual Grain Products Based on 1994–1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight) 

Cereal Rice 

Population Group 

 

 

 

 

 

N Percent 

Consuming Mean SE 

Percent 

Consuming Mean SE 

Whole Population 

Age Group 

Birth to 1 year 

1 to 2 years 

3 to 5 years 

6 to 12 years 

13 to 19 years 

 20 to 49 years 

 ≥50 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian, Pacific Islander 

 Black 

 American Indian, Alaskan Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

Non-metropolitan 

20,607 

1,486 

2,096 

4,391 

2,089 

1,222 

4,677 

4,646 

4,687 

5,308 

5,890 

4,722 

557 

2,740 

177 

1,638 

15,495 

4,822 

3,692 

7,208 

4,885 

6,164 

9,598 

4,845 

99.6 

74.6 

99.8 

100.0 

100.0 

100.0 

99.9 

100.0 

99.6 

99.6 

99.5 

99.6 

98.5 

99.5 

99.7 

98.9 

99.7 

99.7 

99.7 

99.6 

99.4 

99.6 

99.5 

99.7 

3.7 

4.0 

8.4 

8.7 

6.2 

4.1 

3.1 

2.2 

3.7 

3.8 

3.8 

3.7 

4.4 

3.8 

4.2 

4.3 

3.7 

3.9 

3.7 

3.6 

3.8 

3.8 

3.8 

3.5 

0.03 

0.14 

0.08 

0.07 

0.06 

0.06 

0.04 

0.02 

0.06 

0.07 

0.06 

0.05 

0.20 

0.12 

0.15 

0.12 

0.04 

0.09 

0.06 

0.04 

0.09 

0.06 

0.05 

0.06 

86.5 

60.2 

86.4 

87.9 

88.0 

85.8 

88.3 

84.5 

85.1 

87.1 

86.9 

87.1 

96.6 

86.3 

92.6 

85.9 

86.2 

88.2 

87.2 

85.0 

86.7 

87.2 

86.6 

85.6 

0.3 

0.7 

0.6 

0.5 

0.4 

0.3 

0.3 

0.2 

0.3 

0.3 

0.3 

0.3 

1.7 

0.3 

0.3 

0.6 

0.2 

0.2 

0.3 

0.2 

0.4 

0.4 

0.3 

0.2 

0.01 

0.04 

0.03 

0.03 

0.02 

0.02 

0.01 

0.01 

0.02 

0.02 

0.02 

0.02 

0.19 

0.02 

0.10 

0.08 

0.01 

0.02 

0.03 

0.01 

0.03 

0.02 

0.02 

 0.01 

N 

SE 

Source: 

= Sample size. 

= Standard error. 

U.S. EPA analysis of 1994–1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 

12-24 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Table 12-16. Consumer-Only Intake of Individual Grain Products Based on 1994–1996, 1998 CSFII 

(g/kg-day, edible portion, uncooked weight ) 

Population Group N 

Cereal 

Mean SE N 

Rice 

Mean SE 

Whole Population 20,227 3.8 0.03 17,481 0.3 0.01 

Age Group 

Birth to 1 year 1,116 5.4 0.16 900 1.2 0.07 

1 to 2 years 2,092 8.4 0.08 1,819 0.7 0.04 

3 to 5 years 4,389 8.7 0.07 3,869 0.6 0.03 

6 to 12 years 2,089 6.2 0.06 1,847 0.4 0.02 

13 to 19 years 1,222 4.1 0.06 1,038 0.3 0.03 

20 to 49 years 4,674 3.1 0.04 4,102 0.3 0.01 

≥50 years 4,645 2.2 0.02 3,906 0.2 0.01 

Season 

Fall 4,598 3.7 0.06 3,957 0.3 0.02 

Spring 5,213 3.8 0.07 4,530 0.3 0.02 

Summer 5,768 3.8 0.06 4,989 0.3 0.02 

Winter 4,648 3.7 0.06 4,005 0.3 0.02 

Race 

Asian, Pacific Islander 529 4.5 0.20 513 1.8 0.19 

Black 2,683 3.8 0.12 2,346 0.4 0.02 

American Indian, Alaskan Native 175 4.3 0.15 151 0.3 0.10 

Other/NA 1,579 4.4 0.13 1,375 0.7 0.08 

White 15,261 3.7 0.04 13,096 0.2 0.01 

Region 

Midwest 4,759 3.9 0.09 4,186 0.2 0.02 

Northeast 3,639 3.7 0.06 3,152 0.4 0.04 

South 7,081 3.6 0.04 6,029 0.3 0.01 

West 4,748 3.9 0.09 4,114 0.5 0.03 

Urbanization 

Central City 6,039 3.8 0.06 5,303 0.5 0.03 

Suburban 9,410 3.8 0.05 8,105 0.3 0.02 

Non-metropolitan 4,778 3.6 0.06 4,073 0.2 0.02 

N = Sample size. 

SE = Standard error. 

Source: U.S. EPA analysis of 1994–1996, 1998 CSFII. 

Exposure Factors Handbook Page
 

September 2011 12-25 
Table 12

-17. Per Capita Intake of Breadsa Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming Mean 

Percentile 

SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

87.2 

0.9 

30.2 

14.6 

77.2 

86.5 

87.1 

86.2 

88.1 

90.0 

91.6 

87.4 

87.1 

87.3 

86.9 

69.1 

83.1 

82.2 

80.4 

89.0 

89.1 

88.3 

87.5 

83.7 

85.6 

87.7 

88.5 

1.1 

0.0 

0.5 

0.3 

2.0 

2.3 

1.7 

1.1 

0.9 

0.9 

0.9 

1.1 

1.1 

1.1 

1.1 

0.8 

1.1 

1.4 

1.2 

1.1 

1.2 

1.1 

1.1 

1.1 

1.1 

1.1 

1.1 

0.01 

0.08 

0.16 

0.11 

0.06 

0.05 

0.04 

0.03 

0.02 

0.01 

0.02 

0.02 

0.02 

0.02 

0.02 

0.06 

0.03 

0.18 

0.04 

0.01 

0.02 

0.02 

0.02 

0.02 

0.02 

0.01 

0.02 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

0.0 

0.4 

0.9 

0.7 

0.4 

0.4 

0.4 

0.4 

0.4 

0.4 

0.4 

0.4 

0.0 

0.3 

0.3 

0.3 

0.4 

0.4 

0.4 

0.4 

0.3 

0.4 

0.4 

0.4 

0.9 

0.0 

0.0 

0.0 

1.4 

2.0 

1.4 

0.9 

0.8 

0.8 

0.8 

0.9 

0.9 

0.9 

0.8 

0.4 

0.7 

0.9 

0.9 

0.9 

0.9 

0.9 

0.9 

0.8 

0.8 

0.9 

0.9 

1.5 

0.0 

0.5 

0.0 

2.9 

3.3 

2.4 

1.5 

1.3 

1.3 

1.3 

1.5 

1.5 

1.5 

1.4 

1.2 

1.4 

1.7 

1.6 

1.5 

1.5 

1.5 

1.5 

1.4 

1.4 

1.5 

1.5 

2.3 

0.0 

1.8 

0.8 

4.4 

4.7 

3.5 

2.3 

2.0 

1.9 

1.9 

2.4 

2.3 

2.4 

2.3 

1.9 

2.3 

3.6 

2.7 

2.3 

2.5 

2.3 

2.3 

2.4 

2.3 

2.4 

2.3 

3.1 

0.0 

3.0 

1.7 

6.0 

5.8 

4.3 

2.8 

2.5 

2.3 

2.3 

3.1 

3.1 

3.1 

3.1 

2.9 

3.3 

4.1 

3.4 

3.0 

3.3 

2.9 

3.1 

3.2 

3.1 

3.1 

3.1 

5.1 

0.0 

4.8 

4.6 

8.5 

8.7 

6.7 

4.0 

3.9 

3.5 

2.9 

4.9 

5.1 

5.2 

5.1 

4.5 

6.3 

6.2 

5.6 

4.9 

5.7 

4.5 

4.9 

5.1 

5.1 

5.0 

5.0 

20.0 

1.8 

7.3 

7.3 

20.0 

13.2 

11.3 

7.5 

6.2 

8.4 

4.3 

14.6 

11.6 

17.1 

20.0 

14.6 

11.6 

20.0 

7.5 

17.1 

12.0 

9.8 

17.1 

20.0 

13.2 

14.6 

20.0 a 

SE 

Source: 

Includes breads, rolls, muffins, bagels, biscuits, cornbread, and tortillas.
 

= Standard error.
 

U.S. EPA analysis of the 1994–1996 CSFII.
 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 12-26 September 2011 
Table 12-18. Per Capita Intake of Sweetsa Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming 

Percentile 

Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

52.6 

2.5 

23.0 

12.1 

53.2 

62.1 

64.2 

54.3 

47.2 

52.9 

58.6 

53.7 

52.2 

50.0 

54.5 

40.2 

41.4 

35.3 

35.0 

56.3 

60.1 

55.4 

49.1 

47.7 

51.2 

54.6 

50.5 

0.6 

0.0 

0.3 

0.2 

1.2 

1.3 

1.2 

0.6 

0.4 

0.5 

0.5 

0.6 

0.6 

0.5 

0.6 

0.4 

0.5 

0.4 

0.4 

0.6 

0.7 

0.6 

0.6 

0.5 

0.6 

0.6 

0.6 

0.01 

0.04 

0.14 

0.10 

0.07 

0.06 

0.06 

0.03 

0.02 

0.02 

0.03 

0.03 

0.02 

0.02 

0.03 

0.08 

0.04 

0.11 

0.05 

0.01 

0.03 

0.03 

0.02 

0.02 

0.02 

0.02 

0.03 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.3 

0.8 

0.6 

0.2 

0.0 

0.1 

0.2 

0.2 

0.1 

0.0 

0.2 

0.0 

0.0 

0.0 

0.0 

0.2 

0.3 

0.2 

0.0 

0.0 

0.1 

0.2 

0.1 

0.8 

0.0 

0.0 

0.0 

1.7 

1.9 

1.7 

1.0 

0.6 

0.7 

0.8 

0.9 

0.8 

0.7 

0.9 

0.6 

0.6 

0.3 

0.5 

0.9 

1.0 

0.9 

0.8 

0.7 

0.8 

0.9 

0.8 

1.8 

0.0 

1.1 

0.4 

3.5 

3.6 

3.2 

1.8 

1.4 

1.3 

1.6 

1.8 

1.8 

1.6 

1.9 

1.4 

1.5 

1.7 

1.3 

1.8 

2.0 

1.7 

1.7 

1.6 

1.6 

1.8 

1.8 

2.5 

0.0 

2.0 

1.0 

4.8 

4.6 

3.9 

2.4 

1.9 

1.9 

2.1 

2.5 

2.6 

2.3 

2.6 

2.0 

2.3 

2.1 

1.9 

2.5 

2.9 

2.5 

2.3 

2.3 

2.3 

2.6 

2.5 

4.6 

0.4 

3.6 

3.6 

7.2 

8.8 

6.7 

3.7 

3.2 

3.2 

3.6 

4.7 

4.7 

4.1 

4.8 

3.1 

4.7 

2.8 

4.1 

4.7 

5.3 

4.8 

4.4 

3.8 

4.6 

4.5 

5.1 

22.0 

0.6 

6.4 

6.4 

19.3 

22.0 

20.9 

10.7 

11.1 

7.3 

5.7 

20.9 

22.0 

18.2 

12.3 

15.7 

19.3 

2.9 

7.0 

22.0 

22.0 

12.7 

20.9 

15.7 

20.9 

12.7 

22.0 a 

SE 

Source: 

Includes breakfast foods made with grains such as pancakes, waffles, and French toast.
 

= Standard error.
 

U.S. EPA analysis of the 1994–1996 CSFII. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products Exposure Factors Handbook 

Page 

September 2011 12-27 
Table 12-19. Per Capita Intake of Snacks Containing Grainsa Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming 

Percentile 

Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

43.1 

1.0 

29.0 

14.1 

58.1 

56.7 

51.3 

45.0 

41.1 

41.1 

37.7 

42.3 

43.6 

40.6 

45.8 

24.1 

29.5 

38.3 

28.4 

47.1 

49.2 

41.9 

41.1 

40.7 

40.1 

44.6 

44.1 

0.2 

0.0 

0.3 

0.1 

0.7 

0.7 

0.5 

0.3 

0.2 

0.1 

0.1 

0.2 

0.3 

0.2 

0.3 

0.1 

0.2 

0.2 

0.2 

0.3 

0.3 

0.2 

0.2 

0.2 

0.2 

0.3 

0.2 

0.01 

0.11 

0.08 

0.06 

0.04 

0.04 

0.03 

0.02 

0.01 

0.01 

0.01 

0.01 

0.01 

0.01 

0.02 

0.04 

0.02 

0.08 

0.03 

0.01 

0.01 

0.02 

0.01 

0.02 

0.01 

0.01 

0.01 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.4 

0.3 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.3 

0.0 

0.2 

0.0 

1.1 

0.9 

0.6 

0.4 

0.2 

0.2 

0.1 

0.3 

0.3 

0.2 

0.3 

0.0 

0.1 

0.2 

0.1 

0.3 

0.3 

0.2 

0.2 

0.2 

0.2 

0.3 

0.3 

0.7 

0.0 

0.9 

0.6 

2.0 

1.8 

1.3 

0.9 

0.6 

0.5 

0.3 

0.7 

0.8 

0.7 

0.8 

0.4 

0.5 

0.6 

0.5 

0.8 

0.8 

0.7 

0.7 

0.7 

0.7 

0.7 

0.7 

1.2 

0.0 

2.2 

0.9 

2.8 

3.2 

1.9 

1.4 

0.9 

0.7 

0.5 

1.0 

1.3 

1.0 

1.3 

1.0 

0.9 

1.1 

0.8 

1.2 

1.2 

1.2 

1.1 

1.2 

1.1 

1.2 

1.1 

2.6 

0.1 

2.5 

2.2 

5.0 

5.9 

4.6 

2.4 

1.8 

1.4 

0.8 

2.3 

2.9 

2.3 

2.9 

2.3 

2.1 

3.2 

2.4 

2.7 

2.7 

2.7 

2.4 

2.6 

2.6 

2.7 

2.3 

9.1 

3.7 

2.8 

3.7 

8.9 

9.1 

7.3 

5.1 

5.5 

5.6 

1.8 

8.0 

8.9 

7.1 

9.1 

4.4 

7.4 

4.9 

8.7 

9.1 

8.9 

9.1 

8.0 

8.7 

7.8 

9.1 

8.1 a 

SE 

Source: 

Includes grain snacks such as crackers, salty snacks, popcorn, and pretzels.
 

= Standard error.
 

U.S. EPA analysis of the 1994–1996 CSFII. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 12-28 September 2011 
Table 12-20. Per Capita Intake of Breakfast Foodsa Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming 

Percentile 

Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

11.8 

0.0 

4.2 

2.0 

20.4 

20.8 

23.7 

13.0 

8.9 

9.5 

10.4 

11.6 

11.6 

12.8 

11.3 

5.9 

12.7 

8.8 

10.2 

12.0 

12.1 

12.7 

10.7 

12.4 

12.0 

12.2 

10.7 

0.1 

0.0 

0.1 

0.1 

0.4 

0.4 

0.4 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.2 

0.1 

0.1 

0.1 

0.01 

0.00 

0.24 

0.16 

0.07 

0.06 

0.05 

0.03 

0.02 

0.01 

0.02 

0.02 

0.02 

0.02 

0.02 

0.07 

0.03 

0.08 

0.05 

0.01 

0.02 

0.03 

0.02 

0.02 

0.02 

0.02 

0.02 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

0.0 

1.9 

1.6 

1.5 

0.5 

0.0 

0.0 

0.1 

0.4 

0.4 

0.5 

0.3 

0.0 

0.4 

0.0 

0.0 

0.4 

0.4 

0.5 

0.2 

0.5 

0.4 

0.5 

0.3 

1.0 

0.0 

0.0 

0.0 

2.7 

2.5 

2.2 

0.9 

0.6 

0.6 

0.7 

1.0 

1.0 

1.0 

0.9 

0.6 

1.2 

0.3 

0.9 

1.0 

1.1 

1.2 

0.8 

1.0 

1.0 

1.0 

0.9 

2.4 

0.0 

4.1 

2.7 

4.8 

4.5 

3.4 

2.3 

1.5 

1.4 

1.2 

2.3 

2.3 

2.4 

2.6 

2.0 

2.1 

1.2 

2.6 

2.4 

2.6 

2.3 

2.2 

2.6 

2.5 

2.4 

2.2 

13.6 

0.0 

4.1 

4.1 

13.6 

8.0 

6.5 

3.9 

3.0 

3.8 

3.5 

13.6 

6.4 

6.0 

8.0 

2.8 

6.7 

1.2 

8.0 

13.6 

6.7 

8.0 

7.8 

13.6 

13.6 

7.8 

6.4 a 

SE 

Source: 

Includes breakfast food made with grains such as pancakes, waffles, and French toast.
 

= Standard error.
 

U.S. EPA analysis of the 1994–1996 CSFII.
 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products Exposure Factors Handbook 

Page 

September 2011 12-29 
Table 12

-21. Per Capita Intake of Pasta Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming 

Percentile
 

Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

13.0 

0.0 

7.5 

3.5 

16.0 

12.8 

13.4 

11.7 

13.9 

13.7 

9.0 

13.6 

13.2 

12.6 

12.6 

19.4 

7.0 

1.8 

9.6 

14.1 

12.1 

20.1 

9.5 

13.2 

13.4 

14.0 

10.3 

0.3 

0.0 

0.1 

0.1 

0.8 

0.6 

0.5 

0.3 

0.3 

0.2 

0.2 

0.3 

0.3 

0.3 

0.3 

0.5 

0.2 

0.1 

0.2 

0.3 

0.3 

0.5 

0.2 

0.3 

0.3 

0.3 

0.2 

0.02 

0.00 

0.22 

0.15 

0.15 

0.13 

0.12 

0.09 

0.04 

0.03 

0.06 

0.05 

0.05 

0.05 

0.06 

0.17 

0.10 

0.23 

0.09 

0.03 

0.05 

0.05 

0.05 

0.05 

0.05 

0.03 

0.05 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.0 

0.0 

0.0 

0.0 

3.4 

2.1 

2.0 

0.8 

1.1 

1.0 

0.0 

1.2 

1.1 

0.9 

0.8 

2.0 

0.0 

0.0 

0.0 

1.1 

0.8 

1.9 

0.0 

0.9 

1.2 

1.2 

0.1 

2.2 

0.0 

1.0 

0.0 

6.2 

4.4 

3.8 

2.1 

2.2 

1.9 

1.3 

2.4 

2.3 

2.1 

2.1 

3.3 

1.7 

0.0 

2.0 

2.3 

2.1 

2.8 

1.8 

2.2 

2.5 

2.2 

1.5 

5.1 

0.0 

3.3 

2.3 

10.6 

8.4 

7.5 

4.2 

4.1 

3.6 

2.9 

4.7 

5.8 

5.2 

5.1 

6.6 

3.6 

2.4 

3.5 

5.3 

5.2 

5.9 

4.4 

5.7 

5.3 

5.3 

4.2 

29.1 

0.0 

6.7 

6.7 

16.7 

14.3 

11.9 

29.1 

11.2 

11.8 

7.7 

16.7 

14.7 

15.4 

29.1 

11.2 

29.1 

3.6 

15.4 

16.7 

16.7 

15.4 

29.1 

14.1 

29.1 

16.7 

14.1 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994–1996 CSFII. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 12-30 September 2011 
Table 12-22. Per Capita Intake of Cooked Cereals Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming 

Percentile 

Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age Group 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

10.4 

0.9 

16.6 

8.3 

18.4 

16.0 

8.7 

5.6 

6.2 

11.6 

24.5 

12.0 

9.1 

9.3 

11.1 

4.4 

20.1 

7.6 

7.6 

9.3 

9.6 

9.0 

12.4 

9.4 

11.6 

9.9 

9.7 

0.4 

0.1 

1.9 

0.9 

1.6 

1.3 

0.5 

0.2 

0.1 

0.3 

0.6 

0.4 

0.3 

0.3 

0.4 

0.2 

0.7 

0.3 

0.4 

0.3 

0.3 

0.3 

0.4 

0.4 

0.4 

0.3 

0.3 

0.04 

0.54 

1.18 

0.82 

0.29 

0.28 

0.17 

0.09 

0.05 

0.03 

0.07 

0.08 

0.06 

0.08 

0.08 

0.20 

0.10 

0.32 

0.30 

0.04 

0.07 

0.10 

0.06 

0.09 

0.08 

0.05 

0.07 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.6 

0.0 

9.4 

0.0 

6.9 

5.3 

0.0 

0.0 

0.0 

0.9 

2.2 

1.1 

0.0 

0.0 

0.9 

0.0 

2.2 

0.0 

0.0 

0.0 

0.0 

0.0 

1.1 

0.0 

0.9 

0.0 

0.0 

2.3 

0.0 

16.1 

5.7 

10.7 

7.9 

4.0 

1.0 

1.1 

1.9 

3.4 

2.6 

2.0 

2.1 

2.5 

0.0 

4.4 

2.1 

2.0 

2.0 

2.1 

2.2 

2.6 

2.3 

2.6 

2.1 

2.3 

7.2 

0.0 

22.8 

22.8 

20.6 

16.1 

9.4 

4.3 

3.3 

4.4 

5.6 

8.1 

6.4 

6.9 

7.4 

5.3 

10.9 

5.8 

10.6 

6.1 

5.7 

5.9 

7.9 

8.0 

8.1 

6.9 

5.7 

72.5 

5.6 

22.8 

22.8 

33.9 

72.5 

24.1 

10.6 

9.2 

8.7 

10.6 

45.9 

20.9 

72.5 

44.5 

16.1 

33.9 

12.3 

72.5 

45.9 

45.9 

72.5 

31.7 

39.5 

72.5 

45.9 

26.9 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994–1996 CSFII. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products Exposure Factors Handbook 

Page 

September 2011 12-31 
Table 12

-23. Per Capita Intake of Ready-to-Eat Cerealsa Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming 

Percentile 

Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

39.7 

0.0 

19.9 

9.3 

64.9 

69.8 

64.0 

45.7 

30.5 

31.8 

47.9 

39.1 

40.1 

39.6 

39.9 

25.4 

34.0 

33.1 

33.3 

41.7 

42.2 

42.3 

37.4 

38.4 

40.0 

41.2 

35.8 

0.3 

0.0 

0.1 

0.1 

1.0 

1.1 

0.8 

0.4 

0.2 

0.2 

0.2 

0.3 

0.3 

0.3 

0.3 

0.2 

0.3 

0.3 

0.3 

0.3 

0.4 

0.4 

0.3 

0.3 

0.3 

0.4 

0.3 

0.01 

0.00 

0.07 

0.05 

0.04 

0.04 

0.03 

0.02 

0.01 

0.01 

0.01 

0.02 

0.02 

0.02 

0.02 

0.05 

0.02 

0.09 

0.04 

0.01 

0.02 

0.02 

0.01 

0.02 

0.01 

0.01 

0.01 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.7 

0.9 

0.6 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

0.0 

1.5 

1.7 

1.2 

0.6 

0.3 

0.2 

0.4 

0.4 

0.4 

0.4 

0.5 

0.1 

0.4 

0.4 

0.3 

0.5 

0.5 

0.5 

0.4 

0.4 

0.5 

0.5 

0.4 

1.0 

0.0 

0.3 

0.0 

2.5 

2.6 

2.0 

1.1 

0.7 

0.6 

0.7 

1.1 

1.0 

1.1 

1.0 

0.8 

1.0 

0.8 

1.1 

1.1 

1.1 

1.1 

1.0 

1.1 

1.1 

1.1 

0.8 

1.5 

0.0 

1.0 

0.3 

3.3 

3.3 

2.5 

1.5 

1.0 

0.9 

0.9 

1.6 

1.5 

1.6 

1.4 

1.2 

1.5 

1.4 

1.7 

1.5 

1.6 

1.6 

1.3 

1.6 

1.5 

1.6 

1.2 

2.9 

0.0 

1.8 

1.7 

4.9 

4.8 

4.0 

2.2 

1.7 

1.4 

1.5 

2.9 

2.9 

3.0 

2.7 

2.7 

3.2 

2.6 

3.0 

2.8 

2.9 

2.9 

2.8 

3.1 

2.8 

3.1 

2.6 

10.1 

0.0 

2.6 

2.6 

8.8 

10.1 

8.0 

6.4 

5.3 

5.2 

2.7 

8.8 

7.7 

7.8 

10.1 

4.9 

10.1 

4.4 

6.6 

8.8 

8.0 

8.0 

10.1 

8.8 

10.1 

8.0 

8.8 a 

SE 

Source: 

Includes dry ready-to-eat corn, rice, wheat, and bran cereals in the form of flakes, puffs, etc.
 

= Standard error.
 

U.S. EPA analysis of the 1994–1996 CSFII. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 12-32 September 2011 
Table 12-24. Per Capita Intake of Baby Cereals Based on 1994–1996, 1998 CSFII (g/kg-day, as-consumed) 

Population Group Percent 

Consuming 

Percentile 

Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th Max 

Whole Population 

Age 

 <5 months 

 6 to 12 months 

 <1 year 

 1 to 2 years 

 3 to 5 years 

 6 to 11 years 

 12 to 19 years 

 20 to 39 years 

 40 to 69 years 

 ≥70 years 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Race 

 Asian 

 Black 

 American Indian/Alaska Native 

 Other/NA 

 White 

Region 

 Midwest 

 Northeast 

 South 

 West 

Urbanization 

 Central City 

 Suburban 

 Non-metropolitan 

1.0 

40.8 

67.8 

53.4 

6.2 

0.3 

0.1 

0.0 

0.0 

0.1 

0.0 

0.9 

1.2 

0.8 

1.1 

0.7 

1.0 

0.6 

1.7 

1.0 

1.1 

1.2 

0.9 

0.9 

1.1 

1.1 

0.8 

0.0 

0.8 

2.5 

1.6 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.03 

0.24 

0.45 

0.27 

0.10 

0.06 

0.00 

0.00 

0.00 

0.00 

0.00 

0.07 

0.05 

0.06 

0.06 

0.04 

0.12 

0.04 

0.20 

0.03 

0.08 

0.04 

0.05 

0.06 

0.06 

0.04 

0.06 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.8 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.0 

2.8 

1.7 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

2.4 

6.9 

4.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

3.1 

11.3 

7.3 

0.8 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

8.8 

21.1 

19.7 

5.8 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.6 

0.0 

0.3 

0.0 

0.0 

0.0 

1.2 

0.0 

0.3 

0.5 

0.0 

0.0 

0.3 

0.1 

0.0 

37.6 

26.6 

37.6 

37.6 

12.5 

3.8 

0.1 

0.0 

0.0 

0.3 

0.0 

21.1 

26.6 

26.0 

37.6 

2.1 

37.6 

0.9 

26.6 

26.0 

21.1 

12.5 

37.6 

26.6 

37.6 

21.1 

26.0 

SE 

Source: 

= Standard error. 

U.S. EPA analysis of the 1994–1996 CSFII. 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products Exposure Factors Handbook 

Page 

September 2011 12-33 
Table 12-25. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and the Percentage of Individuals Using
 

These Foods in 2 Days
 

% Indiv. Using Quantity Consumed per Consumers Only 

Food at Least Eating Occasion Quantity Consumed per Eating Occasion at Specified Percentiles 

Food Category Once in 2 days (grams) (grams) 

Average SE 5th 10th 25th 50th 75th 90th 95th 

White bread 59.6 50 1 21 24 33 46 52 78 104 

Whole grain and wheat bread 28.1 50 1 24 25 37 50 56 72 92 

Rolls 48.0 58 1 27 33 43 48 70 89 110 

Biscuits 10.9 61 1 19 19 35 57 76 104 139 

Tortillas 15.5 60 1 14 21 32 48 79 107 135 

Quick breads and muffins 12.5 82 2 21 28 52 60 94 142 187 

Doughnuts and sweet rolls 12.4 77 1 26 36 47 65 93 133 164 

Crackers 17.4 26 1 6 9 12 18 30 47 62 

Cookies 30.7 40 1 9 12 20 31 50 75 96 

Cake 16.2 92 3 22 28 41 77 116 181 217 

Pie 8.5 150 3 52 72 102 143 168 246 300 

Pancakes and waffles 10.3 85 3 21 35 42 75 109 158 205 

Cooked cereal 10.3 248 6 81 117 157 233 291 455 484 

Oatmeal 6.1 264 6 116 117 176 232 333 454 473 

Ready-to-eat cereal 40.6 54 1 18 24 30 46 67 93 113 

Corn flakes 8.1 46 1 17 22 25 37 56 75 100 

Toasted oat rings 6.8 42 1 14 16 27 38 54 65 83 

Rice 28.0 150 3 27 40 76 131 192 312 334 

Pasta 36.0 162 3 26 43 73 133 210 318 420 

Macaroni and cheese 8.5 244 9 53 81 121 191 324 477 556 

Spaghetti with tomato sauce 8.0 436 15 122 124 246 371 494 740 983 

Pizza 19.9 169 5 36 52 78 140 214 338 422 

SE = Standard error. 

Source: Smiciklas-Wright et al. (2002) (based on 1994–1996 CSFII data). 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 12-34 September 2011 
Table 12-26. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and Percentage of Individuals Using These Foods 

in 2 Days, by Sex and Age 

Food Category 

Quantity Consumed per Eating Occasion (grams) 

2 to 5 years 6 to 11 years 12 to 19 years 

Males and Females 

(N = 2,109) 

Males and Females Males 

(N = 1,432) (N = 696) 

Females 

(N = 702) 

PC Mean SE PC Mean SE PC Mean SE PC Mean SE 

White bread 

Whole grain and wheat bread 

Rolls 

Biscuits 

Tortillas 

Quick breads and muffins 

Doughnuts and sweet rolls 

Crackers 

Cookies 

Cake 

Pie 

Pancakes and waffles 

Cooked cereal 

Oatmeal 

Ready-to-eat cereal 

Corn flakes 

Toasted oat rings 

Rice 

Pasta 

Macaroni and cheese 

Spaghetti with tomato sauce 

Pizza 

Corn chips 

Popcorn 

66.9 

24.3 

40.0 

8.3 

14.6 

9.6 

11.3 

25.4 

51.0 

14.6 

2.9 

19.1 

16.8 

10.4 

72.9 

11.2 

20.6 

29.6 

49.4 

17.8 

16.8 

23.7 

19.6 

11.6 

34 

37 

39 

38 

32 

55 

59 

17 

28 

70 

76 

49 

211 

221 

33 

33 

30 

84 

90 

159 

242 

86 

29 

20 

a 

1 

1 

2 

2 

4 

2 

1 

1 

3 

8 

1 

10 

9 

1 

2 

1 

3 

3 

8 

11 

3 

2 

1 

67.1 

20.5 

53.5 

9.7 

16.4 

9.6 

13.4 

17.2 

46.7 

19.7 

5.6 

21.5 

9.0 

5.7 

67.3 

13.1 

12.5 

24.6 

41.4 

13.2 

11.5 

32.8 

25.6 

12.7 

42 

44 

48 

48 

47 

67 

69 

26 

37 

79 

116 

77 

245 

256 

47 

42 

45 

124 

130 

217 

322 

108 

33 

31 

1 

1 

1 

3 

2 

5 

2 

2 

2 

4 

8 

3 

14 

19 

1 

2 

2 

6 

5 

13 

18 

6 

2 

2 

61.3 

14.5 

61.9 

12.2 

22.9 

11.0 

17.3 

10.6 

29.0 

15.1 

6.6 

13.5 

5.2 

2.4 

45.6 

10.4 

7.3 

24.2 

33.4 

7.5 

10.1 

39.6 

26.9 

7.8 

56 

60 

69 

72 

76 

125 

102 

39 

53 

99 

188 

96 

310b 

348b 

72 

62 

62 

203 

203 

408 

583 

205 

58 

54 

1 

2 

2 

4 

5 

12 

12 

5 

3 

9 

15 

6 

29b 

45b 

3 

4 

5 

10 

9 

46 

46 

13 

5 

5 

57.9 

17.6 

48.8 

10.3 

20.1 

11.0 

13.8 

14.2 

31.8 

15.5 

4.8 

8.2 

6.0 

2.3 

46.3 

8.7 

8.1 

28.8 

37.8 

10.7 

8.5 

30.5 

25.1 

10.5 

47 

53 

51 

55 

56 

79 

78 

26 

42 

85 

138b 

74 

256b 

321b 

52 

49 

42 

157 

155 

260 

479 

143 

44 

37 

1 

2 

1 

4 

3 

10 

5 

3 

2 

8 

12b 

5 

31b 

40b 

2 

4 

3 

10 

9 

30 

51 

8 

3 

4 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products Exposure Factors Handbook 

Page 

September 2011 12-35 
Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 12-36 September 2011 

Table 12-26. Quantity (as-consumed) of Grain Products Consumed per Eating Occasion and Percentage of Individuals Using These Foods 

in 2 Days, by Sex and Age (continued) 

Food Category 

Quantity Consumed per Eating Occasion (g) 

20 to <40 years 40 to <60 years >60 years 

Males Females 

(N = 1,543) (N = 1,449) 

Males Females 

(N = 1,663) (N = 1,694) 

Males Females 

(N = 1,545) (N = 1,429) 

PC Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE PC Mean SE 

White bread 

Whole grain and wheat bread 

Rolls 

Biscuits 

Tortillas 

Quick breads and muffins 

Doughnuts and sweet rolls 

Crackers 

Cookies 

Cake 

Pie 

Pancakes and waffles 

Cooked cereal 

Oatmeal 

Ready-to-eat cereal 

Corn flakes 

Toasted oat rings 

Rice 

Pasta 

Macaroni and cheese 

Spaghetti with tomato sauce 

Pizza 

Corn chips 

Popcorn 

63.0 

25.3 

62.0 

11.5 

20.6 

8.0 

13.3 

11.9 

20.8 

13.5 

5.8 

8.0 

5.2 

2.7 

26.9 

6.5 

4.2 

30.8 

37.1 

7.8 

8.6 

23.7 

16.2 

8.1 

63 

63 

73 

73 

79 

93 

94 

36 

56 

113 

161 

126 

313 

360a 

77 

73 

62 

199 

214 

301 

630 

253 

61 

63 

2 

1 

4 

3 

4 

7 

5 

3 

4 

6 

7 

15 

30 

42a 

3 

6 

4 

9 

8 

19 

48 

12 

5 

6 

54.9 

25.2 

46.4 

9.4 

20.1 

11.3 

11.2 

15.6 

26.5 

14.9 

7.2 

7.4 

7.3 

3.7 

34.7 

5.3 

5.4 

32.1 

37.1 

7.8 

7.8 

20.2 

17.9 

9.7 

47 

48 

53 

55 

53 

79 

68 

28 

39 

94 

150 

80 

219 

258 

55 

43 

42 

139 

155 

235 

385 

150 

35 

35 

1 

1 

1 

2 

2 

5 

2 

2 

2 

7 

9 

6 

11 

17 

1 

2 

2 

6 

6 

19 

22 

6 

2 

2 

59.7 

32.8 

47.9 

13.4 

13.4 

15.7 

13.4 

16.6 

27.6 

16.5 

11.8 

7.5 

9.7 

6.0 

29.8 

5.9 

4.8 

29.4 

34.3 

6.1 

5.5 

13.0 

12.8 

9.6 

59 

57 

65 

80 

67 

93 

88 

30 

47 

108 

162 

117 

300 

332 

68 

49 

46 

167 

208 

302 

543 

220 

47 

50 

2 

1 

1 

3 

3 

7 

4 

1 

2 

6 

6 

8 

16 

16 

2 

3 

2 

5 

7 

31 

59 

13 

4 

4 

55.3 

32.3 

43.4 

11.2 

12.7 

14.9 

11.0 

17.5 

29.0 

16.8 

9.9 

8.0 

10.3 

6.2 

29.7 

5.2 

4.1 

28.8 

34.7 

6.0 

5.4 

14.5 

12.0 

10.9 

46 

46 

52 

56 

52 

72 

72 

24 

36 

83 

151 

74 

243 

242 

51 

40 

35 

130 

140 

210 

386 

147 

33 

39 

1 

2 

1 

2 

2 

4 

4 

1 

1 

4 

8 

5 

11 

10 

1 

3 

2 

4 

5 

12 

18 

8 

2 

3 

59.3 

39.8 

37.8 

13.0 

4.2 

17.4 

11.4 

25.6 

29.7 

19.2 

16.4 

10.8 

20.9 

13.6 

44.6 

12.4 

4.3 

23.1 

27.9 

7.1 

5.0 

5.3 

4.8 

6.1 

51 

48 

54 

58 

47 

86 

65 

23 

40 

85 

154 

99 

255 

257 

53 

37 

36 

147 

167 

230 

450 

187 

30 

52 

1 

1 

1 

3 

4 

5 

2 

1 

2 

4 

7 

5 

8 

10 

1 

2 

3 

6 

7 

13 

22 

18 

3 

4 

54.8 

43.1 

30.6 

9.8 

5.4 

18.3 

10.4 

25.9 

32.2 

18.3 

13.3 

8.2 

20.2 

12.9 

44.0 

10.4 

4.9 

21.4 

27.9 

6.5 

4.5 

4.7 

5.3 

7.6 

41 

41 

43 

48 

41 

72 

56 

17 

30 

87 

137 

68 

216 

224 

41 

30 

27 

118 

132 

215 

379 

109 

21 

34 

1 

1 

1 

3 

2 

4 

2 

1 

1 

7 

5 

4 

8 

10 

1 

1 

2 

5 

5 

18 

33 

8 

2 

3 a Indicates a SE value that is greater than 0 but less than 0.5. b Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation. 

N = Sample size. 

PC = Percent consuming at least once in 2 days. 

SE = Standard error of the mean. 

Source: Smiciklas-Wright et al. (2002) (based on 1994–1996 CSFII data). 
 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Table 12-27. Consumption of Major Food Groups by Older Adults: Median Daily Servings (and ranges) by 

Demographic and Health Characteristics 

Subject Characteristic N Bread, Cereal, Rice and Pasta (servings/day) 

Sex a 

Females 80 2.7 (0.9–6.5) 

Males 50 3.6 (1.4–7.3) 

Ethnicity 

African American 44 3.3 (1.4–6.4) 

European American 47 3.2 (0.9–6.8) 

Native American 39 2.9 (1.1–7.3) 

Age 

70 to 74 years 42 3.3 (1.1–6.3) 

75 to 79 years 36 3.0 (0.9–6.8) 

80 to 84 years 36 3.2 (1.5–6.4) 

>85 years 16 3.6 (1.6–7.3) 

Marital Status 

Married 49 3.3 (1.1–5.8) 

Not Married 81 3.0 (0.9–7.3) 

Education 

8th grade or less 37 3.1 (1.1–7.3) 

9th to 12th grades 47 3.3 (1.1–6.8) 

>High School 46 3.2 (0.9–6.5) 

Dentures 

Yes 83 3.3 (1.1–6.4) 

No 47 3.1 (0.9–7.3) 

Chronic Diseases 

0 7 4.1 (2.2–6.4) 

1 31 3.3 (0.9–7.3) 

2 56 3.1 (1.1–5.8) 

3 26 3.7 (1.1–5.8) 

>4 10 2.9 (1.4–5.3) 

Weightb 

≤130 pounds 18 3.1 (1.1–5.4) 

131 to 150 pounds 32 3.3 (0.9–5.2) 

151 to 170 pounds 27 3.1 (1.4–7.3) 

171 to 190 pounds 22 3.6 (1.4–6.2) 

≥191 pounds 29 3.0 (1.1–6.8) a p < 0.05. b 2 missing values. 

N = Number of subjects. 

Source: Vitolins et al. (2002). 

Exposure Factors Handbook Page
 

September 2011 12-37 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Table 12-28. Characteristics of the Feeding Infant and Toddlers Study (FITS) Sample Population 

Sample Size Percentage of Sample 

Sex 

Males 

Females 

1,549 

1,473 

51.3 

48.7 

Age of Child 

4 to 6 months 

7 to 8 months 

9 to 11 months 

12 to 14 months 

15 to 18 months 

19 to 24 months 

862 

483 

679 

374 

308 

316 

28.5 

16.0 

22.5 

12.4 

10.2 

10.4 

Child’s Ethnicity 

Hispanic or Latino 

Non-Hispanic or Latino 

Missing 

367 

2,641 

14 

12.1 

87.4 

0.5 

Child’s Race 

White 

Black 

Other 

2,417 

225 

380 

80.0 

7.4 

12.6 

Urbanicity 

Urban 

Suburban 

Rural 

Missing 

1,389 

1,014 

577 

42 

46.0 

33.6 

19.1 

1.3 

Household Income 

Under $10,000 

$10,000 to $14,999 

$15,000 to $24,999 

$25,000 to $34,999 

$35,000 to $49,999 

$50,000 to $74,999 

$75,000 to $99,999 

$100,000 and Over 

Missing 

48 

48 

221 

359 

723 

588 

311 

272 

452 

1.6 

1.6 

7.3 

11.9 

23.9 

19.5 

10.3 

9.0 

14.9 

Receives WIC 

Yes 

No 

Missing 

821 

2,196 

5 

27.2 

72.6 

0.2 

Sample Size (Unweighted) 3,022 100.0 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Devaney et al. (2004). 

Page Exposure Factors Handbook 

12-38 September 2011 
 

 

Table 12-29. Percentage of Infants and Toddlers Consuming Different Types of Grain Products 

Percentage of Infants and Toddlers Consuming at Least Once in a Day 

Food Group/Food 4 to 6 7 to 8 9 to 11 12 to 14 15 to 18 19 to 24 

Months Months Months Months Months Months 

Any Grain or Grain Product 65.8 91.5 97.5 97.8 98.6 99.2 

Infant Cereals 64.8 81.2 63.8 23.9 9.2 3.1 

Non-infant Cerealsa 0.6 18.3 44.3 58.9 60.5 51.9 

Not Pre-sweetened 0.5 17.0 37.0 44.5 40.6 31.9 

Pre-sweetenedb 0.0 1.8 9.0 17.7 26.4 22.7 

Breads and Rollsc 0.6 9.9 24.5 47.3 52.7 53.1 

Crackers, Pretzels, Rice Cakes 3.0 16.2 33.4 45.2 46.4 44.7 

Cereal or Granola Bars 0.0 1.1 3.4 9.8 10.0 9.7 

Pancakes, Waffles, French Toast 0.1 0.8 7.5 15.1 16.1 15.4 

Rice and Pastad 2.3 4.5 18.2 26.2 39.0 35.9 

Other 0.2 0.1 2.7 2.8 2.5 4.5 

Grains in Mixed Dishes 0.4 5.3 24.1 48.3 52.0 55.1 

Sandwiches 0.0 1.1 8.6 21.5 25.8 25.8 

Burrito, Taco, Enchilada, Nachos 0.0 0.0 1.0 4.5 2.8 2.1 

Macaroni and Cheese 0.2 1.6 4.9 14.6 15.0 15.0 

Pizza 0.1 0.7 2.2 6.8 9.0 9.4 

Pot Pie/Hot Pocket 0.0 0.9 0.5 2.0 1.0 1.8 

Spaghetti, Ravioli, Lasagna 0.1 1.8 9.9 15.3 12.1 8.8 a Includes both ready-to-eat and cooked cereals. b Defined as cereals with more than 21.1 grams sugar per 100 grams. c Does not include bread in sandwiches. Sandwiches are included in mixed dishes. d Does not include rice or pasta in mixed dishes. 

Source: Fox et al. (2004). 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Exposure Factors Handbook Page
 

September 2011 12-39 
 

Table 12-30. a Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participants

(percentages) 

Infants 4 to 6 month Infants 7 to 11 month Toddlers 12 to 24 month 

WIC 

Participant Non-Participant 

WIC 

Participant Non-Participant 

WIC 

Participant Non-Participant 

Sex 

 Males 55 

 Females 45 

Child’s Ethnicity 

 Hispanic or Latino 20 

 Non-Hispanic or Latino 80 

Child’s Race 

 White 69 

 Black 15 

 Other 22 

Child in Daycare 

 Yes 39 

 No 61 

Age of Mother 

 14 to 19 years 18 

 20 to 24 years 33 

 25 to 29 years 29 

 30 to 34 years 9

 >35 years 9

 Missing 2 

Mother’s Education 

 11th Grade or Less 23 

 Completed High School 35 

 Some Postsecondary 33 

 Completed College 7

 Missing 2 

Parent’s Marital Status 

 Married 49 

 Not Married 50 

 Missing 1 

Mother or Female Guardian Works 

 Yes 46 

 No 53

 Missing 1

54 

46 

b 

11 

89 

b 

84 

 4

11 

38 

62 

b 

1 

13 

29 

33 

23 

2 

b 

2 

19 

26 

53 

1 

b 

93 

 7

1 

51 

48

1

55 

45 

24 

76 

63 

17 

20 

34 

66 

13 

38 

23 

15 

11 

1 

15 

42 

32 

 9

2 

57 

42 

1 

45 

54 

1 

51 

49 

b 

8 

92 

b 

86 

 5

9 

b 

46 

54 

b 

1 

11 

30 

36 

21 

1 

b 

2 

20 

27 

51 

0 

b 

93 

 7

0 

b 

60 

40

0

57 

43 

22 

78 

67 

13 

20 

43 

57 

9 

33 

29 

18 

11 

0 

17 

42 

31 

 9

1 

58 

41 

1 

55

45

0

52 

48 

b 

10 

89 

b 

84 

 5

11 

c 

53 

47 

b 

1 

14 

26 

34 

26 

1 

b 

3 

19 

28 

48 

2 

b 

88 

11 

1 

c 

61 

38 

1 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Page Exposure Factors Handbook 

12-40 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

c 

Table 12-30. Characteristics of Women, Infants, and Children (WIC) Participants and Non-Participantsa 

(percentages) (continued) 

Infants 4 to 6 months Infants 7 to 11 months Toddlers 12 to 24 months 

WIC WIC WIC 

Participant Non-Participant Participant Non-Participant Participant Non-Participant 

Urbanicity c c c 

Urban 34 55 37 50 35 48 

Suburban 36 31 31 34 35 35 

Rural 28 13 30 15 28 16 

Missing 2 1 2 1 2 2 

Sample Size (Unweighted) 265 597 351 808 205 791 a χ2 tests were conducted to test for statistical significance in the differences between WIC participants and nonparticipants within each age group for each variable. The results of χ2 tests are listed next to the variable under the 

column labeled non-participants for each of the three age groups. b = p < 0.05 non-participants significantly different from WIC participants on the variable. 

= p < 0.01 non-participants significantly different from WIC participants on the variable. 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Ponza et al. (2004). 

 

 

 

 

Table 12-31. Food Choices for Infants and Toddlers by Women, Infants, and Children (WIC) Participation 

Status 

Infants 4 to 6 months Infants 7 to 11 months Toddlers 12 to 24 months 

WIC Non- WIC Non- WIC NonParticipant Participant Participant Participant Participant Participant 

69.7 Infant Cereals 69.7 62.5 74.7 13.5 9.2 

Non-infant Cereals, Total 0.9 0.5 21.7 38.5a 58.1 56.0 

Not Pre-sweetened 0.5 0.5 18.7 32.9a 43.7 36.3 

Pre-sweetened 0.0 0.0 4.0 6.9 17.7 24.1 

Grains in Combination Foods 0.9 0.1 18.8 14.7 50.3 52.9
 

Sample Size (unweighted) 265 597 351 808 205 791
 a = p < 0.01 non-participants significantly different from WIC participants.
 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children.
 

Source: Ponza et al. (2004). 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Exposure Factors Handbook Page
 

September 2011 12-41 
 

Table 12-32. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by Infants 

From the 2002 Feeding Infants and Toddlers Study 

4 to 5 months 6 to 8 months 9 to 11 months Reference Food Group (N = 624) (N = 708) (N = 687) Unit Mean ± SE 

Infant cereal, dry tablespoon 3.1 ± 0.14 4.5 ± 0.14 5.2 ± 0.18 

Infant cereal, jarred tablespoon - 5.6 ± 0.26 7.4 ± 0.34 

Ready-to-eat cereal tablespoon - 2.3 ± 0.34 3.4 ± 0.21 

Crackers ounce - 0.2 ± 0.02 0.3 ± 0.01 

Crackers saltine - 2.2 ± 0.14 2.7 ± 0.12 

Bread slice - 0.5 ± 0.10 0.8 ± 0.06 

- = Cell size was too small to generate a reliable estimate. 

N = Number of respondents. 

SE = Standard error of the mean. 

Source: Fox et al. (2006). 

 

 

 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Table 12-33. Average Portion Sizes per Eating Occasion of Grain Products Commonly Consumed by
 

Toddlers From the 2002 Feeding Infants and Toddlers Study
 

Food Group Reference Unit 

12 to 14 months 

(N = 371) 

15 to 18 months 

(N = 312) 19 to 24 months (N = 320) 

Mean ± SE 

Bread slice 0.8 ± 0.04 0.9 ± 0.05 0.9 ± 0.05 

Rolls ounce 0.9 ± 0.11 1.0 ± 0.10 0.9 ± 0.15 

Ready-to-eat cereal cup 0.3 ± 0.02 0.5 ± 0.03 0.6 ± 0.04 

Hot cereal, prepared cup 0.6 ± 0.05 0.6 ± 0.05 0.7 ± 0.05 

Crackers ounce 0.3 ± 0.02 0.4 ± 0.02 0.4 ± 0.02 

Crackers saltine 3.3 ± 0.22 3.5 ± 0.22 3.7 ± 0.22 

Pasta cup 0.4 ± 0.04 0.4 ± 0.04 0.5 ± 0.05 

Rice cup 0.3 ± 0.04 0.4 ± 0.05 0.4 ± 0.05 

Pancakes and waffles 1 (4-inch diameter) 1.0 ± 0.08 1.4 ± 0.21 1.4 ± 0.17 

N = Number of respondents. 

SE = Standard error of the mean. 

Source: Fox et al. (2006). 

Page Exposure Factors Handbook 

12-42 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

c 

Table 12-34. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different Types of 

Grain Products on a Given Day 

Age 4 to 5 months Age 6 to 11 months Age 12 to 24 months 

Hispanic Non-Hispanic Hispanic Non-Hispanic Hispanic Non-Hispanic 

(N = 84) (N = 538) (N = 163) (N = 1,228) (N = 124) (N = 871) 

Any Grain or Grain Product 

Infant Cereal 

Non-infant Cereal 

Breadsb 

Tortillas 

Crackers, Pretzels, Rice Cakes 

Pancakes, Waffles, French Toast 

Rice and Pastad 

Rice 

Grains in Mixed Dishes 

Sandwiches 

Burrito, Taco, Enchilada, Nachos 

56.5 

55.2 

-

1.4c 

1.4c 

1.3c 

-

-

-

-

-

-

56.9 

56.5 

-

-

-

-

-

-

-

-

-

-

95.0 

74.1 

18.5a 

18.2 

4.0c 

27.8 

1.4c 

20.1a 

15.9e 

15.9 

4.0c 

1.3c 

93.5 

73.6 

29.2 

15.1 

-

22.5 

4.3 

10.3 

4.7 

13.0 

4.6 

-

97.1 

15.9 

45.3 

44.0 

6.7a, c 

35.6 

13.0 

44.3 

26.9a, c 

38.8a 

24.2 

2.1c 

98.9 

9.3 

57.8 

52.9 

0.6c 

46.9 

16.0 

32.9 

13.0 

54.4 

24.9 

3.0 

Macaroni and Cheese - - 3.0c 3.1 10.1 15.5 

Pizza - - - 1.4 1.0c, e 9.7 

Spaghetti, Ravioli, Lasagna - - 8.3c 4.6 9.3c 12.1 a	 = Significantly different from non-Hispanic at p < 0.05. b	 Does not include bread in sandwiches. Sandwiches are included in mixed dishes. Includes tortillas, also shown 

separately. 

= Statistic is potentially unreliable because of a high coefficient of variation. d	 Does not include rice or pasta in mixed dishes. Includes rice (e.g., white, brown, wild, and Spanish rice without meat) 

and pasta (e.g., spaghetti, macaroni, and egg noodles). Rice is also shown separately. e = Significantly different from non-Hispanic at p < 0.01. 

- = Less than 1% of the group consumed this food on a given day. 

N = Sample size. 

Source:	 Mennella et al. (2006). 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Exposure Factors Handbook Page
 

September 2011 12-43 
 

 

 

Exposure Factors Handbook 

Chapter 12—Intake of Grain Products 

Table 12-35. Mean Moisture Content of Selected Grain Products Expressed as Percentages of Edible 

Portions (grams per 100 grams of edible portion) 

Food Moisture Content Comments Raw Cooked 

Barley―pearled 10.09 68.80 

Corn―grain―endosperm 10.37 -

Corn―grain―bran 4.71 - crude 

Millet 8.67 71.41 

Oats 8.22 -

Rice―white―long-grained 11.62 68.44 

Rye 10.95 -

Rye―flour―medium 9.85 -

Sorghum 9.20 -

Wheat―hard white 9.57 -

Wheat―germ 11.12 - crude 

Wheat―bran 9.89 - crude 

Wheat―flour―whole grain 10.27 -

- Indicates that the grain product was not assessed for water content under these conditions. 

Source: USDA (2007). 

Page Exposure Factors Handbook 

12-44 September 2011 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

13.	 INTAKE OF HOME-PRODUCED 

FOODS 

13.1.	 INTRODUCTION 

Ingestion of home-produced foods can be a 

pathway for exposure to environmental contaminants. 

Home-produced foods can become contaminated in 

various ways. Ambient pollutants in the air may be 

deposited on plants, adsorbed onto or absorbed by the 

plants, or dissolved in rainfall or irrigation waters that 

contact the plants. Pollutants also may be adsorbed 

onto plant roots from contaminated soil and water. 

Finally, the addition of pesticides, soil additives, and 

fertilizers to crops or gardens may result in 

contamination of food products. Meat and dairy 

products can become contaminated if animals 

consume contaminated soil, water, or feed crops. 

Farmers, as well as rural and urban residents who 

consume home-produced foods, may be potentially 

exposed if these foods become contaminated. 

Exposure via the consumption of home-produced 

foods may be a significant route of exposure for these 

populations [U.S. Environmental Protection Agency 

(EPA) (1996, 1989)]. For example, consumption of 

home-produced fruits, vegetables, game, and fish has 

been shown to have an effect on blood lead levels in 

areas where soil lead contamination exists (U.S. EPA, 

1994). At Superfund sites where soil contamination is 

found, ingestion of home-produced foods has been 

considered a potential route of exposure (U.S. EPA, 

1993, 1991). Assessing exposures to individuals who 

consume home-produced foods requires knowledge 

of intake rates of such foods. 

Data from the 1987–1988 Nationwide Food 

Consumption Survey (NFCS) were used to generate 

intake rates for home-produced foods. The methods 

used to analyze the 1987–1988 NFCS data are 

presented in Section 13.3. 

13.2.	 RECOMMENDATIONS 

The data presented in this section may be used to 

assess exposure to contaminants in foods grown, 

raised, or caught at a specific site. Table 13-1 presents 

the recommended values for mean and upper 

percentile (i.e., 95th percentile) intake rates among 

consumers of the various home-produced food 

groups. The consumer-only data presented represent 

average daily intake rates of food items/groups over 

the 7-day survey period and do not account for 

variations in eating habits during the rest of the year. 

Thus, the recommended upper- percentile values, as 

well as the percentiles of the distributions presented 

in Section 13.3.1 may not necessarily reflect the 

long-term distribution of average daily intake of 

home-produced foods. Table 13-1 also provides 

mean and 95th percentile per capita intake rates for 

populations that garden, farm, or raise animals. Table 

13-2 presents the confidence ratings for homeproduced food intake. 

Because the consumer-only home-produced food 

intake rates presented in this chapter (See 

Section 13.3.1) are based on foods as brought into the 

household and not in the form in which they are 

consumed, preparation loss factors should be applied 

as appropriate. These factors are necessary to convert 

intake rates to those that are representative of foods 

“as consumed.” The per capita data presented in this 

chapter (See Section 13.3.2) account for preparation 

and post-cooking losses. Additional conversions may 

be necessary for both consumer-only and per capita 

data to ensure that the form of the food used to 

estimate intake (e.g., wet or dry weight) is consistent 

with the form used to measure contaminant 

concentration (see Section 13.3). 

The NFCS data used to generate intake rates of 

home-produced foods are more than 20 years old and 

may not be reflective of current eating patterns 

among consumers of home-produced foods. Although 

the U.S. Department of Agriculture (USDA) and 

others have conducted other food consumption 

studies since the release of the 1987–1988 NFCS, 

these studies do not include information on 

home-produced foods. 

Because the consumer-only analysis was 

conducted prior to the issuance of EPA’s Guidance on 

Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005), the age groups used 

are not entirely consistent with recent guidelines. 

Also, recommended home-produced food intake rates 

are not provided for children less than 1 year of age 

because the methodology used is based on the 

apportionment of home-produced foods used by a 

household among the members of that household 

who consume those foods. It was assumed that the 

diets of children under 1 year of age differ markedly 

from that of other household members; thus, they 

were not assumed to consume any portion of the 

home-produced food brought into the home. 

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Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-1. Summary of Recommended Values for Intake of Home-Produced Foods 

Age Groupa Mean 95th Percentile Multiple Percentiles Source g/kg-day 

Home-Produced Fruits 

Consumers Only, Unadjustedb 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

8.7 

4.1 

3.6 

1.9 

2.0 

2.7 

2.3 

60.6 

8.9 

15.8 

8.3 

6.8 

13.0 

8.7 

See Table 13-5 U.S. EPA Analysis of 

1987–1988 NFCS 

Per Capita for Populations That Garden or Farm, Adjustedc 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

50+ years 

1.0 (1.4) 

1.0 (1.4) 

0.78 (1.0) 

0.40 (0.52) 

0.13 (0.17) 

0.13 (0.17) 

0.15 (0.20) 

0.24 (0.31) 

4.8 (9.1) 

4.8 (9.1) 

3.6 (6.8) 

1.9 (3.5) 

0.62 (1.2) 

0.62 (1.2) 

0.70 (1.3) 

1.1 (2.1) 

NA Phillips and Moya 

(2012) 

Home-Produced Vegetables 

Consumers Only, Unadjustedb 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

5.2 

2.5 

2.0 

1.5 

1.5 

2.1 

2.5 

19.6 

7.7 

6.2 

6.0 

4.9 

6.9 

8.2 

See Table 13-10 U.S. EPA Analysis of 

1987–1988 NFCS 

Per Capita for Populations That Garden or Farm, Adjustedc 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

50+ years 

1.3 (2.7) 

1.3 (2.7) 

1.1 (2.3) 

0.80 (1.6) 

0.56 (1.1) 

0.56 (1.1) 

0.56 (1.1) 

0.60 (1.2) 

7.1 (14) 

7.1 (14) 

6.1 (12) 

4.2 (8.1) 

3.0 (5.7) 

3.0 (5.7) 

3.0 (5.7) 

3.2 (6.1) 

NA Phillips and Moya 

(2012) 

Page Exposure Factors Handbook 

13-2 September 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-1. Summary of Recommended Values for Intake of Home-Produced Foods (continued) 

Age Groupa Mean 95th Percentile Multiple 

Percentiles Source g/kg-day 

Home-Produced Meats 

Consumers Only, Unadjustedb 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

3.7 

3.6 

3.7 

1.7 

1.8 

1.7 

1.4 

10.0 

9.1 

14.0 

4.3 

6.2 

5.2 

3.5 

See Table 13-15 U.S. EPA Analysis of 

1987–1988 NFCS 

Per Capita for Populations That Farm or Raise Animals, Adjustedc 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

50+ years 

1.4 (1.4) 

1.4 (1.4) 

1.4 (1.4) 

1.0 (1.0) 

0.71 (0.73) 

0.71 (0.73) 

0.65 (0.66) 

0.51 (0.52) 

5.8 (6.0) 

5.8 (6.0) 

5.8 (6.0) 

4.1 (4.2) 

3.0 (3.1) 

3.0 (3.1) 

2.7 (2.8) 

2.1 (2.2) 

NA Phillips and Moya (2012) 

Home-Produced Dairy 

Per Capita for Populations That Farm or Raise Animals 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <50 years 

50+ years 

11 (13) 

11 (13) 

6.7 (8.3) 

3.9 (4.8) 

1.6 (2.0) 

1.6 (2.0) 

0.95 (1.2) 

0.92 (1.1) 

76 (92) 

76 (92) 

48 (58) 

28 (34) 

12 (14) 

12 (14) 

6.9 (8.3) 

6.7 (8.0) 

NA Phillips and Moya (2012) 

Home-Caught Fish 

Consumers Only, Unadjustedb 

1 to 2 years 

3 to 5 years 

6 to 11 years 

12 to 19 years 

20 to 39 years 

40 to 69 years 

≥70 years 

-

d 

-

2.8 

1.5 

1.9 

1.8 

1.2 

-

-

7.1 

4.7 

4.5 

4.4 

3.7 

See Table 13-20 U.S. EPA Analysis of 

1987–1988 NFCS 

a Analysis was conducted prior to Agency’s issuance of Guidance on Selecting Age Groups for Monitoring and 

Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005). b Not adjusted to account for preparation or post-cooking losses. c Adjusted for preparation and post-cooking losses. d Data not presented for age groups/food groups where less than 20 observations were available. 

NA = Not available. 

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September 2011 13-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-2. Confidence in Recommendations for Intake of Home-Produced Foods 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The NFCS survey methodology and the approach to 

data analysis were adequate, but individual intakes 

were inferred from household consumption data. The 

sample size was large (approximately 10,000 

individuals). 

Non-response bias cannot be ruled out due to low 

response rate. Also, some biases may have occurred 

from using household data to estimate individual 

intake. 

Medium (Means) 

Low (Distributions) 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The U.S. EPA analysis of the NFCS data specifically 

addressed home-produced intake. 

Data from a nationwide survey, representative of the 

general U.S. population was used. 

The data were collected in 1987–1988. 

Household data were collected over 1 week. 

Low (Means and short-term 

distributions) 

Low (Long-term distributions) 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The methods used to analyze the data are described 

in detail in this handbook; the primary data are 

accessible through USDA. 

Sufficient details on the methods used to analyze the 

data are presented to allow the results to be 

reproduced. 

Quality assurance of NFCS data was good; quality 

control of the secondary data was sufficient. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions of home-produced intake rates were 

provided in the NFCS analysis. Phillips and Moya 

(2012) presented mean and 95th percentile values. 

Sources of uncertainty include: individuals’ estimates 

of food weights, allocation of household food to 

family members, and potential changes in eating 

patterns since these data were collected. 

Low to Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The study was reviewed by USDA and EPA. 

There was one key study that described the primary 

analysis of NFCS data and 1 key study that described 

a secondary analysis of the NFCS home-produced 

data. 

Medium 

Overall Rating Low to Medium (Means and shortterm distributions) 

Low (Long-term distributions) 

Page Exposure Factors Handbook 

13-4 September 2011 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

13.3.	 KEY STUDY FOR INTAKE OF HOMEPRODUCED FOODS 

13.3.1.	 U.S. EPA Analysis of NFCS 1987–1988; 

Moya and Phillips (2001) Analysis of 

Consumption of Home-Produced Foods 

U.S. EPA’s National Center for Environmental 

Assessment (NCEA) analyzed USDA's 1987–1988 

NFCS data to generate intake rates for 

home-produced foods. In addition, Moya and Phillips 

(2001) present a summary of these analyses. For the 

purposes of this study, home-produced foods were 

defined as home-produced fruits and vegetables, meat 

and dairy products derived from consumer-raised 

livestock or game meat, and home-caught fish. 

Until 1988, USDA conducted the NFCS every 

10 years to analyze the food consumption behavior 

and dietary status of Americans (USDA, 1992). 

While more recent food consumption surveys have 

been conducted to estimate food intake among the 

general population (e.g., USDA’s Continuing Survey 

of Food Intake by Individuals [CSFII] and the 

National Health and Nutrition Examination Survey 

[NHANES]), these surveys have not collected data 

that can be used to estimate consumption of 

home-produced foods. Thus, the 1987–1988 NFCS 

data set is currently the best available source of 

information for this factor. 

The 1987–1988 NFCS was conducted between 

April 1987 and August 1988. The survey used a 

statistical sampling technique designed to ensure that 

all seasons, geographic regions of the 

48 conterminous states in the United States, and 

socioeconomic and demographic groups were 

represented (USDA, 1994). There were two 

components of the NFCS. The household component 

collected information over a 7-day period on the 

socioeconomic and demographic characteristics of 

households, as well as the types, amount, value, and 

sources of foods consumed by the household (USDA, 

1994). Meanwhile, the individual intake component 

collected information on food intakes of individuals 

within each household over a 3-day period (USDA, 

1993). The sample size for the 1987–1988 survey 

was approximately 4,300 households (more 

than 10,000 individuals; approximately 

3,000 children). This was a decrease from the 

previous survey conducted in 1977–1978, which 

sampled approximately 15,000 households (more 

than 36,000 individuals) (USDA, 1994). The sample 

size was lower in the 1987–1988 survey as a result of 

budgetary constraints and low response rate [38% for 

the household survey and 31% for the individual 

survey; USDA (1993)]. 

The USDA data were adjusted by applying 

sample weights calculated by USDA to the data set 

prior to analysis. The USDA sample weights were 

designed to “adjust for survey non-response and other 

vagaries of the sample selection process” (USDA, 

1988). Also, the USDA weights are calculated “so 

that the weighted sample total equals the known 

population total, in thousands, for several 

characteristics thought to be correlated with eating 

behavior” (USDA, 1988). 

The food groups selected for analysis of 

home-produced food intake included major food 

groups (i.e., total fruits, total vegetables, total meats, 

total dairy, total fish and shellfish) and individual 

food items for which greater than 30 households 

reported eating the home-produced form of the item; 

fruits and vegetables categorized as exposed, 

protected, and roots; and various USDA fruit and 

vegetable subcategories (e.g., dark green vegetables, 

citrus fruits). These food groups were identified in 

the NFCS data base according to NFCS-defined food 

codes. Appendix 13A presents the codes and 

definitions used to determine the major food groups. 

Foods with these codes, for which the source was 

identified as home-produced, were included in the 

analysis. The codes and definitions for individual 

items in these food groups, as well as other 

subcategories (e.g., exposed, protected, dark green, 

citrus) considered to be home-produced are in 

Appendix 13B. 

Although the individual intake component of the 

NFCS gives the best measure of the amount of each 

food group eaten by each individual in the household, 

it could not be used directly to measure consumption 

of home-produced food because the individual 

component does not identify the source of the food 

item (i.e., as home-produced or not). Therefore, an 

analytical method that incorporated data from both 

the household and individual survey components was 

developed to estimate individual home-produced 

food intake. 

The household data were used to determine 

(1) the amount of each home-produced food items 

used during a week by household members, and 

(2) the number of meals eaten in the household by 

each household member during a week. Note that the 

household survey reports the total amount of each 

food item used in the household (whether by guests 

or household members); the amount used by 

household members was derived by multiplying the 

total amount used in the household by the proportion 

of all meals served in the household (during the 

survey week) that were consumed by household 

members. The individual survey data were used to 

generate average sex- and age-specific serving sizes 

for each food item. The age categories used in the 

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September 2011 13-5 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Page 	 Exposure Factors Handbook 

13-6 September 2011 

analysis were as follows: 1 to 2 years, 3 to 5 years, 

6 to 11 years, 12 to 19 years, 20 to 39 years, 40 to 

69 years, and 70 years and older (intake rates were 

not calculated for children under 1 year of age; the 

rationale for this is discussed after equation 13-1). 

The serving sizes were used during subsequent 

analyses to generate home-produced food intake rates 

for individual household members. Assuming that the 

proportion of the household quantity of each 

home-produced food item/group was a function of 

the number of meals and the mean sex- and agespecific serving size for each family member, 

individual intakes of home-produced food were 

calculated for all members of the survey population 

using the following general equation: 


    m  iq

w = w i  i f (Eqn. 13-1) 

∑

n 

mi qi   i =l 

where: 

wi =	 Home-produced amount of food 

item/group attributed to member 

i during the week (g/week), 

wf =	 Total quantity of home-produced 

food item/group used by the family 

members (g/week), 

mi =	 Number of meals of household 

food consumed by member i during 

the week (meals/week), and 

qi =	 Serving size for an individual 

within the age and sex category of 

the member (g/meal). 

Daily intake of a home-produced food group was 

determined by dividing the weekly value (wi) by 7. 

Intake rates were indexed to the self-reported body 

weight of the survey respondent and reported in units 

of g/kg-day. Intake rates were not calculated for 

children less than 1 year of age because their diet 

differs markedly from that of other household 

members, and, thus, the assumption that all members 

share all foods would be invalid for this age group. 

For the major food groups (i.e., fruits, vegetables, 

meats, dairy, and fish) and individual foods 

consumed by at least 30 households, distributions of 

home-produced intake among consumers were 

generated for the entire data set and for the following 

subcategories: age groups, urbanization categories, 

seasons, racial classifications, regions, and responses 

to a questionnaire. 

Consumers were defined as members of survey 

households who reported consumption of the food 

item/group of interest during the 1-week survey 

period. 

In addition, for the major food groups, 

distributions were generated for each region by 

season, urbanization, and responses to the 

questionnaire. Table 13-3 presents the codes, 

definitions, and a description of the data included in 

each of the subcategories. Intake rates were not 

calculated for food items/groups for which less than 

30 households reported home-produced usage 

because the number of observations may be 

inadequate for generating distributions that would be 

representative of that segment of consumers. Fruits 

and vegetables were also classified as exposed, 

protected, or roots, as shown in Appendix 13B. 

Exposed foods are those that are grown above ground 

and are likely to be contaminated by pollutants 

deposited on surfaces of the foods that are eaten. 

Protected products are those that have outer 

protective coatings that are typically removed before 

consumption. 

Distributions of intake were tabulated for these 

food classes for the same subcategories listed 

previously. Distributions were also tabulated for the 

following USDA food classifications: dark green 

vegetables, deep yellow vegetables, other vegetables, 

citrus fruits, and other fruits. Finally, the percentages 

of total intake of the food items/groups consumed 

within survey households that can be attributed to 

home production were tabulated. The percentage of 

intake that was home-produced was calculated as the 

ratio of total intake of the home-produced food 

item/group by the survey population to the total 

intake of all forms of the food by the survey 

population. 

Percentiles of average daily intake derived from 

short-time intervals (e.g., 7 days) will not, in general, 

be reflective of long-term patterns. This is especially 

true in regards to consumption of many 

home-produced products (e.g., fruits, vegetables), 

where a strong seasonal component often is 

associated with their use. For the major food 

categories, to try to derive the long-term distribution 

of average daily intake rates from the short-term data 

available here, an approach was developed that 

attempted to account for seasonal variability in 

consumption. This approach used regional 

“seasonally adjusted distributions” to approximate 

regional long-term distributions and then combined 

these regional adjusted distributions (in proportion to 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Exposure Factors Handbook Page
 

September 2011 13-7 

the weights for each region) to obtain a U.S. adjusted 

distribution that approximated the U.S. long-term 

distribution. See Moya and Phillips (2001) for details. 

The percentiles of the seasonally adjusted 

distribution for a given region were generated by 

averaging the corresponding percentiles of each of 

the four seasonal distributions of the region. More 

formally, the seasonally adjusted distribution for each 

region is such that its inverse cumulative distribution 

function is the average of the inverse cumulative 

distribution functions of each of the seasonal 

distributions of that region. The use of regional 

seasonally adjusted distributions to approximate 

regional long-term distributions is based on the 

assumption that each individual consumes the same 

regional percentile levels for each season and 

consumes at a constant weekly rate throughout a 

given season. For instance, if the 60th percentile 

weekly intake level in the South is 14.0 grams in the 

summer and 7.0 grams in each of the three other 

seasons, then the individual in the South with an 

average weekly intake of 14.0 grams during the 

summer is assumed to have an intake of 14.0 grams 

for each week of the summer and an intake of 

7.0 grams for each week of the other seasons. 

Note that the seasonally adjusted distributions 

were generated using the overall distributions (i.e., 

both consumers and non-consumers). However, 

because all the other distributions presented in this 

section are based on consumers only, the percentiles 

for the adjusted distributions have been revised to 

reflect the percentiles among consumers only. Given 

the assumption about how each individual consumes, 

the percentage consuming for the seasonally adjusted 

distributions gives an estimate of the percentage of 

the population consuming the specified food category 

at any time during the year. 

The intake data presented in this chapter for 

consumers of home-produced foods and the total 

number of individuals surveyed may be used to 

calculate the mean and the percentiles of the 

distribution of home-produced food consumption in 

the overall population (consumers and

non-consumers) as follows: 

Assuming that IRp is the home-produced intake 

rate of the food group at the pth percentile and Nc is 

the weighted number of individuals consuming the 

home-produced food item, and NT is the weighted 

total number of individuals surveyed, then NT - Nc is 

the weighted number of individuals who reported 

zero consumption of the food item. In addition, there 

are (p / 100 × Nc) individuals below the pth percentile. 

Therefore, the percentile that corresponds to a 

particular intake rate (IRp) for the overall distribution 

of home-produced food consumption (including 

consumers and non-consumers) can be obtained by: 

 p	  ×Nc (NT − Nc )

 + 

p th	 100  = 100×	 (Eqn. 13-2) overall NT 

For example, the percentile of the overall 

population that is equivalent to the 50th percentile 

consumer-only intake rate for home-produced fruits 

would be calculated as follows: 

From Table 13-5, the 50th percentile 

home-produced fruit intake rate (IR50) is 

1.07 g/kg-day. The weighted number of 

individuals consuming fruits (Nc) is 14,744,000. 

From Table 13-4, the weighted total number of 

individuals surveyed (NT) is 188,019,000. The 

number of individuals consuming fruits below the 

50th percentile is 

p / 100 × Nc	 

 = (0.5) × (14,744,000)
 

= 7,372,000
 

The number of individuals that did not consume 

fruit during the survey period is 

NT - Nc	 

 = 188,019,000 – 14,744,000
 

= 173,275,000 

The total number of individuals with 

home-produced intake rates at or below 

1.07 g/kg-day is 

(p / 100 × Nc) + (NT - Nc) = 7,372,000 

+ 173,275,000 

= 180,647,000 

The percentile of the overall population that is 

represented by this intake rate is 

pth overall 100 × (180,647,000 / 188,019,000)
 

 96th percentile
 

Therefore, an intake rate of 1.07 g/kg-day of 

home-produced fruit corresponds to the 96th 

percentile of the overall population. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Following this same procedure, 5.97 g/kg-day, 

which is the 90th percentile of the consumers-only 

population, corresponds to the 99th percentile of the 

overall population. Likewise, 0.063 g/kg-day, which 

is the 1st percentile of the consumers-only population, 

corresponds to the 92nd percentile of the overall 

population. Note that the consumers-only distribution 

corresponds to the tail of the distribution for the 

overall population. Consumption rates below the 92nd 

percentile are very close to zero. The mean intake 

rate for the overall population can be calculated by 

multiplying the mean intake rate among consumers 

by the proportion of individuals consuming the 

home-produced food item Nc / NT. 

Table 13-4 displays the weighted numbers NT and 

the unweighted total survey sample sizes for each 

subcategory and overall. Note that the total 

unweighted number of observations in Table 13-4 

(9,852) is somewhat lower than the number of 

observations reported by USDA; this study only used 

observations for family members for which age and 

body weight were specified. 

The intake rate distributions (among consumers) 

for total home-produced fruits, vegetables, meats, 

fish, and dairy products are shown, respectively, in 

Table 13-5 through Table 13-29. These tables also 

show the proportion of respondents consuming the 

item during the (1-week) survey period. Homeproduced vegetables were the most commonly 

consumed of the major food groups (18.3%), 

followed by fruit (7.8%), meat (4.9%), fish (2.1%), 

and dairy products (0.7%). The intake rates for the 

major food groups varied according to region, age, 

urbanization code, race, and responses to survey 

questions. In general, intake rates of home-produced 

foods were higher among populations in 

non-metropolitan and suburban areas and lowest in 

central city areas. Results of the regional analyses 

indicate that intake of home-produced fruits, 

vegetables, meat, and dairy products was generally 

highest for individuals in the Midwest and South 

regions and lowest for those in the Northeast region. 

Intake rates of home-caught fish were generally 

highest among consumers in the South. Homeproduced intake was generally higher among 

individuals who indicated that they operate a farm, 

grow their own vegetables, raise animals, and catch 

their own fish. The results of the seasonal analyses 

for all regions combined indicate that, in general, 

home-produced fruits and vegetables were eaten at a 

higher rate in summer and home-caught fish was 

consumed at a higher rate in spring; however, 

seasonal intake varied based on individual regions. 

Table 13-30 presents seasonally adjusted intake rate 

distributions for the major food groups. 

Table 13-31 through Table 13-57 show 

distributions of intake for individual home-produced 

food items for households that reported consuming 

the home-produced form of the food during the 

survey period. Intake rate distributions among 

consumers for home-produced foods categorized as 

exposed fruits and vegetables, protected fruits and 

vegetables, and root vegetables are presented in Table 

13-58 through Table 13-62; the intake distributions 

for various USDA classifications (e.g., dark green 

vegetables) are presented in Table 13-63 through 

Table 13-67. The results are presented in units of 

g/kg-day. Table 13-68 presents the fraction of 

household intake attributed to home-produced forms 

of the food items/groups evaluated. Thus, use of these 

data in calculating potential dose does not require the 

body-weight factor to be included in the denominator 

of the average daily dose in equation 1-2 in Chapter 

1. Note that converting these intake rates into units of 

g/day by multiplying by a single average body weight 

is inappropriate, because individual intake rates were 

indexed to the reported body weights of the survey 

respondents. 

As mentioned previously, the intake rates derived 

in this section are based on the amount of household 

food consumption. As measured by the NFCS, the 

amount of food consumed by the household is a 

measure of consumption in an economic sense (i.e., a 

measure of the weight of food brought into the 

household that has been consumed [used up] in some 

manner). In addition to food being consumed by 

persons, food may be used up by spoiling, by being 

discarded (e.g., inedible parts), through cooking 

processes, and other methods. 

USDA estimated preparation losses for various 

foods (USDA, 1975). For meats, a net cooking loss, 

which includes dripping and volatile losses, and a net 

post-cooking loss, which involves losses from 

cutting, bones, excess fat, scraps and juices, were 

derived for a variety of cuts and cooking methods. 

For each meat type, U.S. EPA has averaged these 

losses across all cuts and cooking methods to obtain a 

mean net cooking loss and a mean net post-cooking 

loss. Table 13-69 provides mean percentage values 

for all meats and fish. For individual fruits and 

vegetables, USDA (1975) also gave cooking and 

post-cooking losses. These data, averaged across all 

types of fruits and vegetables to give mean net 

cooking and post-cooking losses, also are provided in 

Table 13-69. 

The formula presented in equation 13-3 can be 

used to convert the home-produced intake rates 

tabulated here to rates reflecting actual consumption: 

Page Exposure Factors Handbook 

13-8 September 2011 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Exposure Factors Handbook Page
 

September 2011 13-9 

I A = I × (1 − L 1 ) × (1 − L 2 ) (Eqn. 13-3) 

where: 

IA = the adjusted intake rate,
 

I = the tabulated intake rate,
 

L1 = the cooking or preparation loss, and
 

L2 = the post-cooking loss.
 

Corrections based on post-cooking losses only apply 

to fruits that are eaten in cooked forms. For raw 

forms of the fruits, paring or preparation loss data 

should be used to correct for losses from the removal 

of skin, peel, core, caps, pits, stems, and defects, or 

from the draining of liquids from canned or frozen 

forms. To obtain preparation losses for food 

categories, the preparation losses of the individual 

foods making up the category can be averaged. 

In calculating ingestion exposure, assessors 

should use consistent forms (e.g., as consumed or dry 

weight) in combining intake rates with contaminant 

concentrations (see Chapter 9). 

The USDA NFCS data set is the largest publicly 

available source of information on home-produced 

food consumption habits in the United States. The 

advantages of using this data set are that it is 

expected to be representative of the U.S. population 

and that it provides information on a wide variety of 

food groups. However, the data collected by the 

USDA NFCS are based on short-term dietary recall, 

and the intake distributions generated from this data 

set may not accurately reflect long-term intake 

patterns, particularly with the tails (extremes) of the 

distributions. Also, the two survey components (i.e., 

household and individual) do not define food 

items/groups in a consistent manner; as a result, some 

errors may be introduced into these analyses because 

the two survey components are linked. The results 

presented in this chapter also may be biased by 

assumptions that are inherent in the analytical method 

utilized. The analytical method may not capture all 

high-end consumers within households because 

average serving sizes are used in calculating the 

proportion of home-produced food consumed by each 

household member. Thus, for instance, in a 

two-person household in which one member had high 

intake and another had low intake, the method used 

would assume that both members had an equal and 

moderate level of intake. In addition, the analyses 

assume that all family members consume a portion of 

the home-produced food used within the household. 

However, not all family members may consume each 

home-produced food item, and serving sizes allocated 

in this instance may not be entirely representative of 

the portion of household foods consumed by each 

family member. As was mentioned earlier, no 

analyses were performed for children under 1 year of 

age. 

The preparation loss factors discussed previously 

are intended to convert intake rates based on 

“household consumption” to rates reflective of what 

individuals actually consume. However, these factors 

do not include losses to spoilage, feeding to pets, 

food thrown away, and other methods. It also should 

be noted that because this analysis is based on the 

1987–1988 NFCS, it may not reflect recent changes 

in food consumption patterns. The low response rate 

associated with the 1987–1988 NFCS also 

contributes to the uncertainty of the home-produced 

intake rates generated using these data. 

13.3.2.	 Phillips and Moya (2012)―Estimation of 

Age-Specific Per Capita Home-Produced 

Food Intake Among Populations That 

Garden, Farm, or Raise Animals 

Phillips and Moya (2012) used the consumer 

intake data for home-produced fruits, vegetables, 

meats, and dairy products from the analysis described 

in Section 13.3.1 to estimate per capita intake rates 

for the populations that garden, farm, or raise 

animals. The consumer-only intake values in 

Section 13.3.1 are based on short-term dietary survey 

data and may be appropriate for estimating short-term 

intake, but may over-estimate exposure over longer 

time periods. Also, the intake rates in Section 13.3.1 

represent intake of foods brought into the household 

and have not been adjusted to account for preparation 

losses and post-cooking losses. Phillips and Moya 

(2012) converted the distribution of consumer-only 

intake rates for populations that garden, farm, and 

raise animals to the distribution of per capita rates 

using equation 13-2 and adjusted these data to 

account for preparation losses and post-cooking 

losses using equation 13-3. Data for households that 

garden, farm, or raise animals were used because 

they were assumed to represent both households who 

ate home-produced foods during the survey period as 

well as those who did not eat home-produced foods 

during the survey period, but may eat these foods at 

some other time during the year. Also, the data in 

Section 13.3.1 for the populations that garden, farm, 

or raise animals are not provided by age group, but 

represent data for all ages of the survey population 

combined. Phillips and Moya (2012) calculated agespecific intake rates using ratios of age-specific 

dietary intake to total population intake rates, based 

on survey data for intake of total fruits, vegetables, 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Page Exposure Factors Handbook 

13-10 September 2011 

meats, and dairy from all sources (i.e., both homeproduced and commercial sources) from the 1994­

1996, 1998 CSFII, as described in Chapters 9 and 11. 

The age groups used are those recommended in U.S. 

EPA (2005). Age-specific intake mean and 95th 

percentile intake rates were estimated as: agespecific ratio × mean (or 95th percentile) per capita 

intake for the total population, where the age-specific 

ratio = age-specific mean per capita total intake 

(g/kg-day)/ total population mean per capita total 

intake (g/kg-day). Table 13-70 provides the both the 

adjusted and unadjusted estimated mean and 95th percapita intake rates for the total populations that 

garden, farm, and raise animals. Table 13-70 also 

provides age-specific per capita intake rates based on 

data that have been adjusted to account for 

preparation and post-cooking losses. 

The advantages of this analysis are that it 

provides data for populations that may be of 

particular interest because they may represent the 

high-end of the per capita home-produced food intake 

distribution (Phillips and Moya, 2012), and that agespecific intake rates are provided for the age groups 

recommended by U.S. EPA (2005). However, it 

should be noted that these estimates are based on data 

that are more than 20 years old and may not reflect 

recent changes in consumption patterns. Also, the 

data for children less than 1 year of age are 

considered to be less certain than for other age groups 

because the diets of children in this age range would 

be expected to be highly variable (Phillips and Moya, 

2012). Other limitations associated with this analysis 

are the same as those described in Section 13.3.1 for 

the analysis of the NFCS data. 

13.4.	 RELEVANT STUDY FOR INTAKE OF 

HOME-PRODUCED FOODS 

13.4.1.	 National Gardening Association (2009) 

According to a survey by the National Gardening 

Association (2009), an estimated 36 million (or 31%) 

of U.S. households participated in food gardening in 

2008. Food gardening includes growing vegetables, 

berries, fruit, and herbs. Of the estimated 36 million 

food-gardening households, 23% participated in 

vegetable gardening, 12% participated in herb 

gardening, 10% participated in growing fruit trees, 

and 6% grew berries. Table 13-71 contains 

demographic data on food gardening in 2008 by sex, 

age, education, household income, and household 

size. Table 13-72 contains information on the types of 

vegetables grown by home gardeners in 2008. 

Tomatoes, cucumbers, peppers, beans, carrots, 

summer squash, onions, lettuce, peas, and corn are 

among the vegetables grown by the largest 

percentage of gardeners. 

13.5. REFERENCES FOR CHAPTER 13 

Moya, J; Phillips, L. (2001). Analysis of consumption 

of home-produced foods. J Expo Anal 

Environ Epidemiol 11: 398-406. 

http://dx.doi.org/10.1038/sj.jea.7500181. 

NGA (National Gardening Association). (2009). The 

impact of home and community gardening 

in America. South Burlington, VT. 

Phillips, L; Moya, J. (2012). Estimation of agespecific per capita home-produced food 

intake among populations that garden, farm, 

or raise animals. J Expo Sci Environ 

Epidemiol 22: 101-108. 

http://dx.doi.org/10.1038/jes.2011.17. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1989). Risk assessment guidance for 

superfund: Volume 1: Human health 

evaluation manual (part A): Interim final 

[EPA Report]. (EPA/540/1-89/002). 

Washington, DC: U.S. Environmental 

Protection Agency, Office of Emergency and 

Remedial Response. 

http://www.epa.gov/oswer/riskassessment/ra 

gsa/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1991). Superfund record of decision: Union 

Pacific Railroad Yard, ID. (EPA/ROD/R10­

91/029). 

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=91000XC0.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1993). Superfund Record of Decision (EPA 

Region 4): USDOE Oak Ridge Reservation, 

Operable Unit 16, Oak Ridge, TN., 

September 1993. (EPARODR0493166). 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB94964021. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1994). Validation strategy for the integrated 

exposure uptake biokinetic model for lead in 

children. (EPA/540/R-94/039). Washington, 

DC: U.S. Environmental Protection Agency, 

Office of Solid Waste and Emergency 

Response. 

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=20012SIX.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1996). Soil screening fact sheet guidance. 

(EPA/540/F-95/041). Washington, DC. 

http://www.epa.gov/superfund/health/conme 

dia/soil/index.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

 

 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum. 

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

USDA (U.S. Department of Agriculture). (1975). 

Food yields summarized by different stages 

of preparation: Agricultural Handbook No. 

102. Washington, DC. 

USDA (U.S. Department of Agriculture). (1988). 

Dataset: Nationwide food consumption 

survey 1987/88 household food use. 

Washington, DC. 

USDA (U.S. Department of Agriculture). (1992). 

Changes in food consumption and 

expenditures in American households during 

the 1980s. (Statistical Bulletin No. 849). 

Washington, DC. 

USDA (U.S. Department of Agriculture). (1993). 

Food and nutrient intakes by individuals in 

the United States, 1 day, 198788. 

Nationwide Food Consumption Survey 

1987-88. (Report no. 87-I-1). Washington, 

DC. 

http://www.ars.usda.gov/SP2UserFiles/Place 

/12355000/pdf/8788/nfcs8788_rep_87-i1.pdf. 

USDA (U.S. Department of Agriculture). (1994). 

Food consumption and dietary levels of 

households in the United States, 19871988. 

Washington, DC. 

Exposure Factors Handbook Page
 

September 2011 13-11
 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-3. Subcategory Codes, Definitions, and Descriptions 

Code Definition Description 

Regiona 

1 Northeast Includes Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, 

and Vermont. 

2 Midwest Includes Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South 

Dakota, and Wisconsin. 

3 South Includes Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, 

Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia. 

4 West Includes Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and 

Wyoming. 

Urbanization 

1 Central City Cities with populations of 50,000 or more that is the main city within the metropolitan statistical area (MSA). 

2 Suburban An area that is generally within the boundaries of an MSA but is not within the legal limit of the central city. 

3 Non-metropolitan An area that is not within an MSA. 

Race 

1 -­ White (Caucasian) 

2 -­ Black 

3 -­ Asian and Pacific Islander 

4 -­ Native American, Aleuts, and Eskimos 

5, 8, 9 Other/NA Don't know, no answer, some other race 

Responses to Survey Questions 

Grow Question 75 Did anyone in the household grow any vegetables or fruit for use in the household? 

Raise Animals Question 76 Did anyone in the household produce any animal products such as milk, eggs, meat, or poultry for home use in your 

household? 

Fish/Hunt Question 77 Did anyone in the household catch any fish or shoot game for home use? 

Farm Question 79 Did anyone in the household operate a farm or ranch? 

Season 

Spring - April, May, June 

Summer - July, August, September 

Fall - October, November, December 

Winter - January, February, March 

a Alaska and Hawaii were not included. 

Source: USDA (1988). 

Page Exposure Factors Handbook 13-12 September 2011 
Chapter 13—

Exposure Factors Handbook 

Intake of Home-Produced Foods 

Exposure Factors Handbook Page September 2011 13-13 

Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in Analysis of Food Intake 

All Regions Northeast Midwest South West 

wgtd unwgtd wgtd unwgtd wgtd unwgtd wgtd unwgtd wgtd unwgtd 

Total 

Age (years) 

 < 1 

 1 to 2 

 3 to 5 

 6 to 11 

 12 to 19 

 20 to 39 

 40 to 69 

 ≥ 70 

Season 

 Fall 

 Spring 

 Summer 

 Winter 

Urbanization 

 Central City 

 Non-metropolitan 

 Suburban 

Race 

 Asian 

 Black 

 Native American 

 Other/NA 

 White 

Response to Questionnaire 

 Do you garden? 

 Do you raise animals? 

 Do you hunt? 

 Do you fish? 

 Do you farm? 

188,019,000 

2,814,000 

5,699,000 

8,103,000 

16,711,000 

20,488,000 

61,606,000 

56,718,000 

15,880,000 

47,667,000 

46,155,000 

45,485,000 

48,712,000 

56,352,000 

45,023,000 

86,584,000 

2,413,000 

21,746,000 

1,482,000 

4,787,000 

157,531,000 

6,8152,000 

10,097,000 

20,216,000 

39,733,000 

7,329,000 

9,852 

156 

321 

461 

937 

1,084 

3,058 

3,039 

796 

1,577 

3,954 

1,423 

2,898 

2,217 

3,001 

4,632 

114 

1,116 

91 

235 

8,294 

3,744 

631 

1,148 

2,194 

435 

41,167,000 

545,000 

1,070,000 

1,490,000 

3,589,000 

4,445,000 

12,699,000 

13,500,000 

3,829,000 

9,386,000 

10,538,000 

9,460,000 

11,783,000 

9,668,000 

5,521,000 

25,978,000 

333,000 

3,542,000 

38,000 

1,084,000 

36,170,000 

12,501,000 

1,178,000 

3,418,000 

5,950,000 

830,000 

2,018 

29 

56 

92 

185 

210 

600 

670 

176 

277 

803 

275 

663 

332 

369 

1,317 

13 

132 

4 

51 

1,818 

667 

70 

194 

321 

42 

46,395,000 

812,000 

1,757,000 

2,251,000 

4,263,000 

5,490,000 

15,627,000 

13,006,000 

3,189,000 

14,399,000 

10,657,000 

10,227,000 

11,112,000 

17,397,000 

14,296,000 

14,702,000 

849,000 

2,794,000 

116,000 

966,000 

41,670,000 

22,348,000 

3,742,000 

6,948,000 

12,621,000 

2,681,000 

2,592 

44 

101 

133 

263 

310 

823 

740 

178 

496 

1,026 

338 

732 

681 

1,053 

858 

37 

126 

6 

37 

2,386 

1,272 

247 

411 

725 

173 

64,331,000 

889,000 

1,792,000 

2,543,000 

5,217,000 

6,720,000 

21,786,000 

19,635,000 

5,749,000 

13,186,000 

16,802,000 

17,752,000 

16,591,000 

17,245,000 

19,100,000 

27,986,000 

654,000 

13,701,000 

162,000 

1,545,000 

48,269,000 

20,518,000 

2,603,000 

6,610,000 

13,595,000 

2,232,000 

3,399 

51 

105 

140 

284 

369 

1,070 

1,080 

300 

439 

1,437 

562 

961 

715 

1,197 

1,487 

32 

772 

8 

86 

2,501 

1,136 

162 

366 

756 

130 

36,066,000 

568,000 

1,080,000 

1,789,000 

3,612,000 

3,833,000 

11,494,000 

10,577,000 

3,113,000 

10,696,000 

8,158,000 

7,986,000 

9,226,000 

12,042,000 

6,106,000 

17,918,000 

577,000 

1,709,000 

1,166,000 

1,192,000 

31,422,000 

12,725,000 

2,574,000 

3,240,000 

7,567,000 

1,586,000 

1,841 

32 

59 

95 

204 

195 

565 

549 

142 

365 

688 

246 

542 

489 

382 

970 

32 

86 

73 

61 

1,589 

667 

152 

177 

392 

90 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-5. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—All Regions Combined 

Population Nc Nc % 

Group wgtd Unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 14,744,000 817 7.84 2.68 0.19 0.06 0.17 0.28 0.50 1.07 2.37 5.97 

Age (years) 

1 to 2 360,000 23 6.32 8.74 3.10 0.96 1.09 1.30 1.64 3.48 7.98 19.30 

3 to 5 550,000 34 6.79 4.07 1.48 0.01 0.01 0.36 0.98 1.92 2.73 6.02 

6 to 11 1,044,000 75 6.25 3.59 0.68 0.01 0.19 0.40 0.70 1.31 3.08 11.80 

12 to 19 1,189,000 67 5.80 1.94 0.37 0.09 0.13 0.27 0.44 0.66 2.35 6.76 

20 to 39 3,163,000 164 5.13 1.95 0.33 0.08 0.13 0.20 0.37 0.70 1.77 4.17 

40 to 69 5,633,000 309 9.93 2.66 0.30 0.06 0.19 0.29 0.47 1.03 2.33 5.81 

≥ 70 2,620,000 134 16.50 2.25 0.23 0.04 0.22 0.38 0.61 1.18 2.35 5.21 

Season 

Fall 3,137,000 108 6.58 1.57 0.16 0.26 0.30 0.39 0.57 1.04 1.92 3.48 

Spring 2,963,000 301 6.42 1.58 0.14 0.09 0.20 0.25 0.42 0.86 1.70 4.07 

Summer 4,356,000 145 9.58 3.86 0.64 0.01 0.09 0.16 0.45 1.26 3.31 10.90 

Winter 4,288,000 263 8.80 3.08 0.34 0.04 0.17 0.27 0.56 1.15 2.61 8.04 

Urbanization 

Central City 3,668,000 143 6.51 2.31 0.26 0.04 0.18 0.33 0.57 1.08 2.46 5.34 

Non-metropolitan 4,118,000 278 9.15 2.41 0.31 0.06 0.13 0.23 0.45 1.15 2.42 4.46 

Suburban 6,898,000 394 7.97 3.07 0.32 0.13 0.23 0.30 0.49 0.99 2.33 7.26 

Race 

Black 450,000 20 2.07 1.87 0.85 0.13 0.28 0.46 0.61 1.13 1.53 2.29 

White 14,185,000 793 9.00 2.73 0.19 0.07 0.18 0.28 0.51 1.07 2.46 6.10 

Response to Questionnaire 

Households who garden 12,742,000 709 18.70 2.79 0.21 0.06 0.18 0.29 0.53 1.12 2.50 6.10 

Households who farm 1,917,000 112 26.16 2.58 0.26 0.07 0.28 0.41 0.75 1.61 3.62 5.97 

11.10 

60.60 

8.91 

15.80 

8.34 

6.84 

13.00 

8.69 

4.97 

5.10 

14.60 

15.30 

10.50 

8.34 

15.20 

2.29 

11.70 

11.80 

7.82 

24.00 

60.60 

48.30 

32.20 

18.50 

16.10 

23.80 

11.70 

10.60 

8.12 

53.30 

24.90 

14.30 

24.00 

37.00 

19.30 

24.00 

24.90 

15.80 

60.60 

60.60 

48.30 

32.20 

18.50 

37.00 

53.30 

15.30 

10.60 

31.70 

60.60 

48.30 

19.30 

53.30 

60.60 

19.30 

60.60 

60.60 

15.80 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Moya and Phillips (2001). (Based on EPA's analyses of the 1987–1988 NFCS.) 

Page Exposure Factors Handbook 13-14 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-6. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,279,000 72 3.11 0.93 0.22 0.08 0.08 0.16 0.31 0.49 0.78 1.29 

Season 

Fall 260,000 8 2.77 * * * * * * * * * 

Spring 352,000 31 3.34 0.88 0.23 0.09 0.16 0.17 0.29 0.49 0.88 1.83 

Summer 271,000 9 2.86 * * * * * * * * * 

Winter 396,000 24 3.36 0.71 0.11 0.18 0.21 0.23 0.29 0.54 0.88 1.38 

Urbanization 

Central City 50,000 3 0.52 * * * * * * * * * 

Non-metropolitan 176,000 10 3.19 * * * * * * * * * 

Suburban 1,053,000 59 4.05 1.05 0.26 0.18 0.23 0.29 0.44 0.54 0.81 1.29 

Response to Questionnaire 

Households who garden 983,000 59 7.86 1.04 0.26 0.09 0.18 0.21 0.38 0.54 0.88 1.38 

Households who farm 132,000 4 15.90 * * * * * * * * * 

2.16 

* 

2.16 

* 

1.79 

* 

* 

2.75 

2.75 

* 

11.70 

* 

7.13 

* 

2.75 

* 

* 

11.70 

11.70 

* 

11.70 

* 

7.13 

* 

2.75 

* 

* 

11.70 

11.70 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-15
 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-7. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 4,683,000 302 10.09 3.01 0.41 0.04 0.13 0.24 0.47 1.03 2.31 

Season 

Fall 1,138,000 43 7.90 1.54 0.19 0.26 0.30 0.47 0.61 1.07 1.92 

Spring 1,154,000 133 10.83 1.69 0.28 0.09 0.21 0.26 0.42 0.92 1.72 

Summer 1,299,000 44 12.70 7.03 1.85 0.06 0.09 0.13 0.43 1.55 8.34 

Winter 1,092,000 82 9.83 1.18 0.18 0.03 0.06 0.15 0.36 0.61 1.42 

Urbanization 

Central City 1,058,000 42 6.08 1.84 0.39 0.04 0.10 0.26 0.52 1.07 1.90 

Non-metropolitan 1,920,000 147 13.43 2.52 0.54 0.06 0.11 0.15 0.40 1.03 2.07 

Suburban 1,705,000 113 11.60 4.29 0.87 0.09 0.20 0.31 0.48 0.76 3.01 

Response to Questionnaire 

Households who garden 4,060,000 267 18.17 3.27 0.47 0.04 0.10 0.20 0.45 1.07 2.37 

Households who farm 694,000 57 25.89 2.59 0.30 0.06 0.19 0.41 1.26 1.63 3.89 

6.76 

3.48 

2.89 

16.10 

2.61 

2.82 

4.43 

13.90 

7.15 

6.76 

13.90 

4.34 

4.47 

37.00 

3.73 

9.74 

6.84 

18.00 

14.60 

8.34 

53.30 

5.33 

16.00 

60.60 

10.90 

10.90 

53.30 

60.60 

53.30 

11.10 

60.60 

5.33 

31.70 

60.60 

10.90 

10.90 

53.30 

60.60 

60.60 

11.10 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-16 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-8. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 4,148,000 208 6.45 2.97 0.30 0.11 0.24 0.36 0.60 1.35 3.01 

Season 

Fall 896,000 29 6.80 1.99 0.44 0.39 0.43 0.45 0.65 1.13 1.96 

Spring 620,000 59 3.69 2.05 0.26 0.16 0.28 0.31 0.45 1.06 4.09 

Summer 1,328,000 46 7.48 2.84 0.65 0.08 0.16 0.27 0.44 1.31 2.83 

Winter 1,304,000 74 7.86 4.21 0.65 0.11 0.24 0.38 0.89 1.88 3.71 

Urbanization 

Central City 1,066,000 39 6.18 3.33 0.54 0.24 0.39 0.46 0.83 2.55 4.77 

Non-metropolitan 1,548,000 89 8.10 2.56 0.39 0.08 0.27 0.34 0.61 1.40 2.83 

Suburban 1,534,000 80 5.48 3.14 0.60 0.11 0.16 0.28 0.51 1.10 2.29 

Response to Questionnaire 

Households who garden 3,469,000 174 16.91 2.82 0.29 0.16 0.28 0.38 0.65 1.39 2.94 

Households who farm 296,000 16 13.26 * * * * * * * * 

8.18 

4.97 

5.01 

6.10 

14.10 

8.18 

5.97 

11.80 

6.10 

* 

14.10 

8.18 

6.58 

14.30 

19.70 

10.60 

10.40 

15.50 

14.10 

* 

23.80 

10.60 

7.05 

24.00 

23.80 

14.30 

24.00 

23.80 

21.10 

* 

24.00 

10.60 

7.05 

24.00 

23.80 

14.30 

24.00 

23.80 

24.00 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-17
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-9. Consumer-Only Intake of Home-Produced Fruits (g/kg-day)—West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE 

p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 4,574,000 233 12.68 2.62 0.31 0.15 0.28 0.33 0.62 1.20 2.42 

Season 

Fall 843,000 28 7.88 1.47 0.25 0.29 0.29 0.30 0.48 1.04 2.15 

Spring 837,000 78 10.26 1.37 0.16 0.17 0.20 0.25 0.51 0.98 1.61 

Summer 1,398,000 44 17.51 2.47 0.47 0.19 0.28 0.40 0.62 1.28 3.14 

Winter 1,496,000 83 16.22 4.10 0.79 0.07 0.30 0.33 0.77 1.51 3.74 

Urbanization 

Central City 1,494,000 59 12.41 1.99 0.42 0.07 0.24 0.34 0.53 0.86 2.04 

Non-metropolitan 474,000 32 7.76 2.24 0.53 0.18 0.28 0.42 0.63 0.77 2.64 

Suburban 2,606,000 142 14.54 3.04 0.46 0.18 0.28 0.31 0.71 1.39 3.14 

Response to Questionnaire 

Households who garden 4,170,000 207 32.77 2.76 0.34 0.10 0.28 0.31 0.63 1.20 2.54 

Households who farm 795,000 35 50.13 1.85 0.26 0.28 0.28 0.60 0.71 1.26 2.50 

5.39 

2.99 

2.95 

7.26 

11.10 

4.63 

4.25 

5.81 

5.81 

4.63 

10.90 

4.65 

5.29 

10.90 

18.50 

9.52 

10.90 

10.30 

10.90 

5.00 

24.90 

5.39 

6.68 

13.00 

48.30 

19.30 

10.90 

32.20 

24.90 

6.81 

48.30 

5.39 

7.02 

13.00 

48.30 

19.30 

10.90 

48.30 

48.30 

6.81 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-18 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-10. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—All Regions Combined 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 34,392,000 1,855 18.29 2.08 0.07 0.00 0.11 0.18 0.45 1.11 2.47 5.20 7.54 

Age 

1 to 2 951,000 53 16.69 5.20 0.85 0.02 0.25 0.38 1.23 3.27 5.83 13.10 19.60 

3 to 5 1,235,000 76 15.24 2.46 0.28 0.00 0.05 0.39 0.71 1.25 3.91 6.35 7.74 

6 to 11 3,024,000 171 18.10 2.02 0.25 0.01 0.10 0.16 0.40 0.89 2.21 4.64 6.16 

12 to 19 3,293,000 183 16.07 1.48 0.14 0.00 0.06 0.15 0.32 0.81 1.83 3.71 6.03 

20 to 39 8,593,000 437 13.95 1.47 0.10 0.02 0.08 0.16 0.27 0.76 1.91 3.44 4.92 

40 to 69 12,828,000 700 22.62 2.07 0.10 0.01 0.12 0.21 0.53 1.18 2.47 5.12 6.94 

≥ 70 4,002,000 211 25.20 2.51 0.19 0.01 0.15 0.24 0.58 1.37 3.69 6.35 8.20 

Season 

Fall 11,026,000 394 23.13 1.88 0.13 0.05 0.11 0.18 0.41 0.98 2.11 4.88 6.94 

Spring 6,540,000 661 14.17 1.36 0.07 0.00 0.04 0.14 0.32 0.70 1.63 3.37 5.21 

Summer 11,081,000 375 24.36 2.86 0.19 0.07 0.16 0.22 0.71 1.62 3.44 6.99 9.75 

Winter 5,745,000 425 11.79 1.79 0.11 0.00 0.04 0.16 0.47 1.05 2.27 3.85 6.01 

Urbanization 

Central City 6,183,000 228 10.97 1.40 0.12 0.01 0.07 0.15 0.30 0.75 1.67 3.83 4.67 

Non-metropolitan 13,808,000 878 30.67 2.68 0.12 0.02 0.16 0.26 0.60 1.45 3.27 6.35 9.33 

Suburban 14,341,000 747 16.56 1.82 0.09 0.00 0.11 0.16 0.39 0.96 2.18 4.32 6.78 

Race 

Black 1,872,000 111 8.61 1.78 0.23 0.00 0.08 0.14 0.44 0.93 2.06 4.68 5.70 

White 31,917,000 1,714 20.26 2.10 0.07 0.01 0.11 0.18 0.45 1.12 2.48 5.18 7.68 

Response to Questionnaire 

Households who garden 30,217,000 1,643 44.34 2.17 0.07 0.01 0.11 0.19 0.48 1.18 2.68 5.35 7.72 

Households who farm 4,319,000 262 58.93 3.29 0.25 0.00 0.16 0.29 0.85 1.67 3.61 8.88 11.80 

15.50 

27.00 

10.60 

17.60 

7.71 

10.50 

14.90 

12.50 

12.50 

8.35 

18.70 

10.60 

9.96 

17.50 

12.50 

8.20 

15.50 

15.50 

17.60 

27.00 

27.00 

12.80 

23.60 

9.04 

20.60 

22.90 

15.50 

18.90 

23.60 

27.00 

20.60 

16.60 

27.00 

20.60 

18.90 

27.00 

23.60 

23.60 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Moya and Phillips (2001). (Based on EPA's analyses of the 1987–1988 NCFS.) 

Exposure Factors Handbook PageSeptember 2011 13-19
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-11. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 4,883,000 236 11.86 1.78 0.17 0.00 0.08 0.14 0.28 0.75 1.89 6.03 

Season 

Fall 1,396,000 41 14.87 1.49 0.41 0.08 0.13 0.17 0.27 0.58 1.17 6.64 

Spring 1,204,000 102 11.43 0.82 0.11 0.00 0.00 0.04 0.17 0.46 0.95 2.26 

Summer 1,544,000 48 16.32 2.83 0.47 0.11 0.15 0.16 0.74 1.29 3.63 7.82 

Winter 739,000 45 6.27 1.67 0.27 0.00 0.00 0.09 0.26 1.25 2.77 3.63 

Urbanization 

Central City 380,000 14 3.93 * * * * * * * * * 

Non-metropolitan 787,000 48 14.25 3.05 0.54 0.00 0.05 0.11 0.20 2.18 4.61 9.04 

Suburban 3,716,000 174 14.30 1.59 0.17 0.00 0.08 0.14 0.28 0.72 1.64 4.82 

Response to Questionnaire 

Households who garden 4,381,000 211 35.05 1.92 0.18 0.00 0.08 0.14 0.31 0.88 2.18 6.16 

Households who farm 352,000 19 42.41 * * * * * * * * * 

7.82 

9.97 

3.11 

9.75 

6.10 

* 

12.70 

6.80 

7.82 

* 

12.70 

10.20 

6.52 

14.90 

8.44 

* 

14.90 

10.20 

12.70 

* 

14.90 

10.20 

6.78 

14.90 

8.44 

* 

14.90 

10.20 

14.90 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-20 September 2011
 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-12. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 12,160,000 699 26.21 2.26 0.12 0.02 0.08 0.18 0.49 1.15 2.58 5.64 

Season 

Fall 4,914,000 180 34.13 1.84 0.18 0.01 0.07 0.16 0.42 1.03 2.10 5.27 

Spring 2,048,000 246 19.22 1.65 0.15 0.06 0.15 0.22 0.46 0.91 1.72 4.49 

Summer 3,319,000 115 32.45 3.38 0.39 0.11 0.16 0.30 0.85 2.07 3.94 7.72 

Winter 1,879,000 158 16.91 2.05 0.26 0.00 0.02 0.07 0.36 0.88 2.13 5.32 

Urbanization 

Central City 3,177,000 113 18.26 1.36 0.19 0.00 0.06 0.11 0.25 0.71 1.67 3.94 

Non-metropolitan 5,344,000 379 37.38 2.73 0.19 0.02 0.11 0.26 0.60 1.31 3.15 7.19 

Suburban 3,639,000 207 24.75 2.35 0.22 0.03 0.15 0.22 0.64 1.39 2.75 4.87 

Response to Questionnaire 

Households who garden 10,927,000 632 48.89 2.33 0.13 0.02 0.10 0.18 0.50 1.18 2.74 5.81 

Households who farm 1,401,000 104 52.26 3.97 0.43 0.14 0.34 0.55 0.87 2.18 5.24 10.60 

7.74 

6.88 

5.83 

14.00 

7.83 

5.50 

10.60 

7.18 

7.75 

14.40 

17.50 

13.10 

12.80 

19.60 

16.70 

9.96 

17.50 

19.60 

16.70 

17.50 

23.60 

13.10 

23.60 

22.90 

20.60 

16.60 

23.60 

20.60 

23.60 

23.60 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-21
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-13. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 11,254,000 618 17.49 2.19 0.12 0.03 0.16 0.24 0.56 1.24 2.69 4.92 

Season 

Fall 2,875,000 101 21.80 2.07 0.28 0.10 0.11 0.19 0.52 1.14 2.69 4.48 

Spring 2,096,000 214 12.47 1.55 0.11 0.01 0.09 0.26 0.53 0.94 2.07 3.58 

Summer 4,273,000 151 24.07 2.73 0.32 0.11 0.17 0.25 0.62 1.54 3.15 5.99 

Winter 2,010,000 152 12.12 1.88 0.14 0.00 0.16 0.35 0.64 1.37 2.69 3.79 

Urbanization 

Central City 1,144,000 45 6.63 1.10 0.16 0.01 0.10 0.15 0.26 0.62 1.37 2.79 

Non-metropolitan 6,565,000 386 34.37 2.78 0.18 0.05 0.22 0.35 0.71 1.66 3.31 5.99 

Suburban 3,545,000 187 12.67 1.44 0.11 0.00 0.11 0.20 0.40 0.93 1.72 3.61 

Response to Questionnaire 

Households who garden 9,447,000 522 46.04 2.27 0.12 0.03 0.16 0.26 0.61 1.37 3.02 5.18 

Households who farm 1,609,000 91 72.09 3.34 0.46 0.00 0.13 0.23 1.03 1.72 3.15 9.56 

7.43 

6.02 

4.81 

9.70 

5.35 

3.70 

9.56 

5.26 

7.43 

11.80 

17.00 

15.50 

8.35 

23.60 

7.47 

4.21 

18.90 

8.20 

15.50 

23.60 

27.00 

18.90 

10.30 

27.00 

8.36 

4.58 

27.00 

8.20 

23.60 

23.60 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-22 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-14. Consumer-Only Intake of Home-Produced Vegetables (g/kg-day)—West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 6,035,000 300 16.73 1.81 0.14 0.01 0.10 0.17 0.38 0.90 2.21 4.64 

Season 

Fall 1,841,000 72 17.21 2.01 0.29 0.10 0.15 0.20 0.48 1.21 2.21 4.85 

Spring 1,192,000 99 14.61 1.06 0.17 0.00 0.01 0.05 0.20 0.36 0.91 3.37 

Summer 1,885,000 59 23.6 2.39 0.37 0.07 0.10 0.25 0.55 1.37 3.23 4.67 

Winter 1,117,000 70 12.11 1.28 0.17 0.01 0.15 0.20 0.48 0.77 1.43 2.81 

Urbanization 

Central City 1,482,000 56 12.31 1.80 0.28 0.03 0.07 0.16 0.48 1.10 2.95 4.64 

Non-metropolitan 1,112,000 65 18.21 1.52 0.22 0.00 0.01 0.20 0.27 0.68 2.13 4.13 

Suburban 3,441,000 179 19.20 1.90 0.20 0.01 0.10 0.15 0.39 0.93 2.20 4.63 

Response to Questionnaire 

Households who garden 5,402,000 276 42.45 1.91 0.00 0.01 0.10 0.17 0.43 1.07 2.37 4.67 

Households who farm 957,000 48 60.34 2.73 0.00 0.12 0.41 0.47 0.77 1.42 3.27 6.94 

6.21 

7.72 

5.54 

8.36 

5.12 

4.85 

5.12 

7.98 

6.21 

10.90 

11.40 

12.50 

8.60 

15.50 

7.57 

11.40 

8.16 

12.50 

12.50 

15.50 

15.50 

12.50 

8.60 

15.50 

7.98 

11.40 

8.16 

15.50 

15.50 

15.50 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-23
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-15. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—All Regions Combined 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 9,257,000 569 4.92 2.21 0.11 0.12 0.24 0.37 0.66 1.39 2.89 4.89 

Age 

1 to 2 276,000 22 4.84 3.65 0.61 0.39 0.95 0.95 1.19 2.66 4.72 8.68 

3 to 5 396,000 26 4.89 3.61 0.51 0.80 0.80 1.51 2.17 2.82 3.72 7.84 

6 to 11 1,064,000 65 6.37 3.65 0.45 0.37 0.65 0.72 1.28 2.09 4.71 8.00 

12 to 19 1,272,000 78 6.21 1.70 0.17 0.19 0.32 0.47 0.62 1.23 2.35 3.66 

20 to 39 2,732,000 158 4.43 1.82 0.15 0.12 0.19 0.30 0.53 1.11 2.65 4.52 

40 to 69 2,872,000 179 5.06 1.72 0.11 0.02 0.21 0.34 0.58 1.17 2.38 3.67 

≥ 70 441,000 28 2.78 1.39 0.23 0.09 0.09 0.13 0.55 1.01 1.81 2.82 

Season 

Fall 2,852,000 107 5.98 1.57 0.14 0.12 0.21 0.35 0.52 1.11 2.27 3.19 

Spring 1,726,000 197 3.74 2.37 0.15 0.24 0.32 0.45 0.78 1.69 3.48 5.00 

Summer 2,368,000 89 5.21 3.10 0.38 0.02 0.19 0.41 0.85 1.77 4.34 7.01 

Winter 2,311,000 176 4.74 1.98 0.17 0.14 0.24 0.37 0.65 1.33 2.43 3.96 

Urbanization 

Central City 736,000 28 1.31 1.15 0.18 0.18 0.19 0.21 0.44 0.72 1.58 2.69 

Non-metropolitan 4,932,000 315 10.95 2.70 0.18 0.12 0.26 0.41 0.75 1.63 3.41 6.06 

Suburban 3,589,000 226 4.15 1.77 0.10 0.03 0.29 0.37 0.68 1.33 2.49 3.66 

Race 

Black 128,000 6 0.59 * * * * * * * * 

White 8,995,000 556 5.71 2.26 0.11 0.09 0.26 0.39 0.68 1.41 2.91 5.00 

Response to Questionnaire 

Households who raise animals 5,256,000 343 52.06 2.80 0.15 0.21 0.39 0.62 1.03 1.94 3.49 5.90 

6.78 

10.00 

9.13 

14.00 

4.34 

6.23 

5.16 

3.48 

4.41 

6.67 

10.50 

6.40 

3.40 

8.47 

4.71 

* 

7.01 

7.84 

14.00 

11.50 

13.00 

15.30 

6.78 

9.17 

5.90 

7.41 

6.78 

10.10 

22.30 

10.90 

3.64 

15.30 

7.20 

* 

14.00 

14.00 

23.20 

11.50 

13.00 

15.30 

7.51 

10.90 

7.46 

7.41 

7.84 

13.00 

22.30 

23.20 

3.64 

23.20 

10.10 

* 

23.20 

23.20 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Moya and Phillips (2001). (Based on EPA's analyses of the 1987–1988 NFCS.) 

Page Exposure Factors Handbook 13-24 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-16. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,113,000 52 2.70 1.46 0.21 0.29 0.34 0.35 0.64 0.89 1.87 2.68 

Season 

Fall 569,000 18 6.06 * * * * * * * * * 

Spring 66,000 8 0.63 * * * * * * * * * 

Summer 176,000 6 1.86 * * * * * * * * * 

Winter 302,000 20 2.56 2.02 0.56 0.29 0.31 0.43 0.62 1.11 2.38 2.93 

Urbanization 

Central City 0 0 0.00 - - - - - - - - -

Non-metropolitan 391,000 17 7.08 * * * * * * * * * 

Suburban 722,000 35 2.78 1.49 0.15 0.29 0.35 0.43 0.68 1.39 2.34 2.68 

Response to Questionnaire 

Households who raise animals 509,000 25 43.21 2.03 0.39 0.62 0.65 0.65 0.88 1.62 2.38 2.93 

Households who farm 373,000 15 44.94 * * * * * * * * * 

2.89 

* 

* 

* 

7.46 

-

* 

2.89 

7.46 

* 

10.90 

* 

* 

* 

10.90 

-

* 

3.61 

10.90 

* 

10.90 

* 

* 

* 

10.90 

-

* 

3.61 

10.90 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

- Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-25
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-17. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 3,974,000 266 8.57 2.55 0.18 0.13 0.26 0.39 0.66 1.40 3.39 

Season 

Fall 1,261,000 49 8.76 1.76 0.23 0.21 0.26 0.37 0.50 1.19 2.66 

Spring 940,000 116 8.82 2.58 0.22 0.24 0.31 0.41 0.73 1.98 3.67 

Summer 930,000 38 9.09 4.10 0.75 0.09 0.13 0.58 0.89 2.87 5.42 

Winter 843,000 63 7.59 2.00 0.24 0.12 0.24 0.33 0.65 1.36 2.69 

Urbanization 

Central City 460,000 18 2.64 * * * * * * * * 

Non-metropolitan 2,477,000 175 17.33 3.15 0.26 0.09 0.30 0.43 0.82 2.38 4.34 

Suburban 1,037,000 73 7.05 1.75 0.20 0.29 0.37 0.41 0.66 1.11 2.03 

Response to Questionnaire 

Households who raise animals 2,165,000 165 57.86 3.20 0.22 0.26 0.39 0.58 1.07 2.56 4.42 

Households who farm 1,483,000 108 55.32 3.32 0.29 0.37 0.54 0.59 1.07 2.75 4.71 

5.75 

3.49 

5.14 

8.93 

4.11 

* 

6.15 

4.16 

6.06 

6.78 

7.20 

6.06 

7.79 

15.30 

5.30 

* 

9.17 

5.39 

9.13 

9.17 

15.30 

6.78 

11.50 

22.30 

8.10 

* 

15.30 

7.20 

15.30 

15.30 

22.30 

6.78 

13.00 

22.30 

12.20 

* 

22.30 

10.10 

15.30 

15.30 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-26 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-18. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,355,000 146 3.66 2.24 0.19 0.02 0.16 0.30 0.72 1.53 3.07 5.07 

Season 

Fall 758,000 28 5.75 1.81 0.29 0.12 0.16 0.19 0.82 1.53 2.38 3.19 

Spring 511,000 53 3.04 2.33 0.27 0.19 0.30 0.50 0.75 1.80 2.82 5.16 

Summer 522,000 18 2.94 * * * * * * * * * 

Winter 564,000 47 3.40 1.80 0.25 0.04 0.20 0.25 0.72 1.40 2.17 3.55 

Urbanization 

Central City 40,000 1 0.23 * * * * * * * * * 

Non-metropolitan 1,687,000 97 8.83 2.45 0.26 0.12 0.19 0.40 0.78 1.61 3.19 6.09 

Suburban 628,000 48 2.24 1.79 0.23 0.02 0.03 0.04 0.63 1.40 2.31 4.56 

Response to Questionnaire 

Households who raise animals 1,222,000 74 46.95 3.16 0.32 0.26 0.67 0.84 1.34 2.11 3.79 6.67 

Households who farm 1,228,000 72 55.02 2.85 0.32 0.20 0.50 0.60 1.01 1.93 3.48 6.23 

6.71 

4.41 

6.71 

* 

4.58 

* 

7.84 

4.61 

8.47 

8.47 

14.00 

7.84 

7.51 

* 

8.47 

* 

14.00 

6.40 

14.00 

14.00 

14.00 

7.84 

7.51 

* 

8.47 

* 

14.00 

6.40 

14.00 

14.00 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-27
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-19. Consumer-Only Intake of Home-Produced Meats (g/kg-day)—West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,815,000 105 5.03 1.89 0.21 0.15 0.23 0.39 0.66 1.42 2.49 3.66 

Season 

Fall 264,000 12 2.47 * * * * * * * * * 

Spring 209,000 20 2.56 1.86 0.23 0.30 0.43 0.87 1.22 1.56 2.43 3.48 

Summer 740,000 27 9.27 2.20 0.32 0.19 0.41 0.54 1.07 1.69 3.27 4.44 

Winter 602,000 46 6.53 2.11 0.46 0.14 0.36 0.43 0.67 1.19 2.35 3.64 

Urbanization 

Central City 236,000 9 1.96 * * * * * * * * * 

Non-metropolitan 377,000 26 6.17 2.10 0.70 0.33 0.33 0.41 0.67 1.19 1.77 3.72 

Suburban 1,202,000 70 6.71 1.95 0.20 0.15 0.23 0.37 0.78 1.52 2.71 4.20 

Response to Questionnaire 

Households who raise animals 1,360,000 79 52.84 2.12 0.27 0.15 0.23 0.39 0.82 1.56 2.71 4.20 

Households who farm 758,000 48 47.79 2.41 0.43 0.14 0.33 0.47 0.79 1.55 2.91 4.71 

4.71 

* 

4.20 

4.71 

7.02 

* 

4.97 

4.71 

4.97 

7.02 

8.00 

* 

4.20 

8.00 

23.20 

* 

23.20 

8.00 

8.00 

23.20 

23.20 

* 

4.20 

8.00 

23.20 

* 

23.20 

8.00 

23.20 

23.20 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-28 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-20. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—All Regions Combined 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 3,914,000 239 2.08 2.07 0.24 0.08 0.09 0.20 0.23 0.43 1.00 2.17 4.68 

Age 

1 to 2 82,000 6 1.44 * * * * * * * * * * 

3 to 5 142,000 11 1.75 * * * * * * * * * * 

6 to 11 382,000 29 2.29 2.78 0.84 0.16 0.16 0.18 0.23 0.55 1.03 3.67 7.05 

12 to 19 346,000 21 1.69 1.52 0.41 0.20 0.20 0.20 0.20 0.31 0.98 1.79 4.68 

20 to 39 962,000 59 1.56 1.91 0.33 0.08 0.08 0.09 0.12 0.44 1.06 2.18 4.46 

40 to 69 1,524,000 86 2.69 1.79 0.26 0.09 0.09 0.21 0.28 0.35 0.99 1.99 4.43 

≥ 70 450,000 24 2.83 1.22 0.23 0.10 0.10 0.23 0.23 0.57 0.76 1.56 3.73 

Season 

Fall 1,220,000 45 2.56 1.31 0.22 0.18 0.18 0.20 0.21 0.32 0.92 1.79 2.64 

Spring 1,112,000 114 2.41 3.08 0.56 0.10 0.12 0.31 0.34 0.56 1.27 2.64 6.68 

Summer 911,000 29 2.00 1.88 0.42 0.08 0.08 0.09 0.20 0.30 0.76 3.19 4.43 

Winter 671,000 51 1.38 2.05 0.37 0.09 0.09 0.11 0.16 0.51 1.06 2.09 5.89 

Urbanization 

Central City 999,000 46 1.77 1.79 0.34 0.09 0.09 0.16 0.28 0.61 1.07 1.85 3.73 

Non-metropolitan 1,174,000 94 2.61 3.15 0.57 0.10 0.12 0.31 0.36 0.57 1.88 3.86 6.52 

Suburban 1,741,000 99 2.01 1.50 0.23 0.08 0.08 0.18 0.20 0.29 0.59 1.38 4.37 

Race 

Black 593,000 41 2.73 1.81 0.37 0.18 0.18 0.20 0.29 0.32 0.98 2.17 4.68 

White 3,228,000 188 2.05 2.07 0.28 0.08 0.08 0.16 0.23 0.39 1.00 2.16 4.99 

Response to Questionnaire 

Households who fish 3,553,000 220 8.94 2.22 0.26 0.08 0.08 0.18 0.23 0.47 1.09 2.23 5.61 

7.83 

* 

* 

7.85 

6.67 

9.57 

6.56 

3.73 

3.73 

10.80 

5.65 

7.85 

9.57 

7.83 

7.05 

9.57 

6.68 

7.85 

15.50 

* 

* 

25.30 

8.44 

13.00 

10.80 

5.12 

6.56 

37.30 

9.57 

13.10 

9.57 

37.30 

10.80 

9.57 

16.10 

16.10 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Moya and Phillips (2001). (Based on EPA's analyses of the 1987–1988 NFCS.) 

Exposure Factors Handbook PageSeptember 2011 13-29
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-21. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 334,000 12 0.81 * * * * * * * * 

Season 

Fall 135,000 4 1.44 * * * * * * * * 

Spring 14,000 2 0.13 * * * * * * * * 

Summer 132,000 3 1.40 * * * * * * * * 

Winter 53,000 3 0.45 * * * * * * * * 

Urbanization 

Central City 0 0.00 - - - - - - - -

Non-metropolitan 42,000 4 0.76 * * * * * * * * 

Suburban 292,000 8 1.12 * * * * * * * * 

Response to Questionnaire 

Households who fish 334,000 12 5.61 * * * * * * * * 

* 

* 

* 

* 

* 

-

* 

* 

* 

* 

* 

* 

* 

* 

-

* 

* 

* 

* 

* 

* 

* 

* 

-

* 

* 

* 

* 

* 

* 

* 

* 

-

* 

* 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

- Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-30 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-22. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,113,000 71 2.40 2.13 0.42 0.08 0.08 0.20 0.23 0.47 1.03 

Season 

Fall 362,000 13 2.51 * * * * * * * * 

Spring 224,000 27 2.10 3.45 1.22 0.12 0.12 0.12 0.31 0.49 0.82 

Summer 264,000 8 2.58 * * * * * * * * 

Winter 263,000 23 2.37 2.38 0.53 0.51 0.51 0.51 0.55 1.03 1.56 

Urbanization 

Central City 190,000 9 1.09 * * * * * * * 

Non-metropolitan 501,000 40 3.50 3.42 0.72 0.12 0.12 0.33 0.47 0.53 1.88 

Suburban 422,000 22 2.87 0.91 0.18 0.08 0.08 0.08 0.20 0.30 0.55 

Response to Questionnaire 

Households who fish 956,000 60 7.57 2.35 0.49 0.08 0.08 0.12 0.23 0.47 1.12 

1.95 

* 

1.67 

* 

2.13 

* 

5.65 

1.28 

2.16 

6.10 

* 

15.50 

* 

5.89 

* 

6.56 

2.09 

6.52 

6.56 

* 

16.10 

* 

6.10 

* 

13.10 

2.78 

6.56 

16.10 

* 

25.30 

* 

13.10 

* 

25.30 

3.73 

25.30 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-31
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-23. Consumer-Only Intake of Home-Caught Fish (g/kg-day)—South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,440,000 101 2.24 2.74 0.48 0.09 0.09 0.20 0.29 0.51 1.48 

Season 

Fall 274,000 11 2.08 * * * * * * * * 

Spring 538,000 58 3.20 4.00 0.94 0.31 0.31 0.39 0.45 0.87 1.94 

Summer 376,000 14 2.12 * * * * * * * * 

Winter 252,000 18 1.52 * * * * * * * * 

Urbanization 

Central City 281,000 16 1.63 * * * * * * * * 

Non-metropolitan 550,000 41 2.88 3.33 1.06 0.29 0.29 0.34 0.51 1.12 1.94 

Suburban 609,000 44 2.18 2.73 0.50 0.20 0.20 0.28 0.29 0.43 1.08 

Response to Questionnaire 

Households who fish 1,280,000 95 9.42 3.00 0.51 0.09 0.09 0.20 0.28 0.71 1.93 

3.37 

* 

3.71 

* 

* 

* 

3.19 

4.37 

3.67 

5.61 

* 

8.33 

* 

* 

* 

4.43 

8.33 

6.68 

8.44 

* 

13.00 

* 

* 

* 

6.67 

10.40 

8.44 

37.30 

* 

45.20 

* 

* 

* 

45.20 

13.00 

37.30 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-32 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-24. Consumer-Only Intake of Home-Caught Fish (g/kg-day)―West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,027,000 55 2.85 1.57 0.27 0.10 0.16 0.20 0.24 0.44 0.84 1.79 

Season 

Fall 449,000 17 4.20 * * * * * * * * * 

Spring 336,000 27 4.12 1.35 0.29 0.10 0.10 0.24 0.33 0.44 0.61 1.68 

Summer 139,000 4 1.74 * * * * * * * * * 

Winter 103,000 7 1.12 * * * * * * * * * 

Urbanization 

Central City 528,000 21 4.38 2.03 0.53 0.33 0.33 0.43 0.53 0.71 1.45 1.85 

Non-metropolitan 81,000 9 1.33 * * * * * * * * * 

Suburban 418,000 25 2.33 1.09 0.25 0.18 0.18 0.20 0.21 0.31 0.59 1.21 

Response to Questionnaire 

Households who fish 983,000 53 12.99 1.63 0.28 0.10 0.16 0.20 0.22 0.55 0.96 1.79 

3.73 

* 

4.68 

* 

* 

3.73 

* 

2.90 

3.73 

5.67 

* 

5.61 

* 

* 

9.57 

* 

4.68 

* 

5.67 

9.57 

* 

5.67 

* 

* 

9.57 

* 

5.61 

9.57 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-33
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-25. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—All Regions 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,409,000 89 0.75 14.00 1.62 0.18 0.45 0.51 3.18 10.20 19.50 34.20 

Age 

1 to 2 79,000 6 1.39 * * * * * * * * * 

3 to 5 57,000 5 0.70 * * * * * * * * * 

6 to 11 264,000 16 1.58 * * * * * * * * * 

12 to 19 84,000 5 0.41 * * * * * * * * * 

20 to 39 612,000 36 0.99 7.41 1.02 0.21 0.40 0.45 1.89 6.46 12.10 15.40 

40 to 69 216,000 16 0.38 * * * * * * * * * 

≥ 70 77,000 3 0.48 * * * * * * * * * 

Season 

Fall 211,000 7 0.44 * * * * * * * * * 

Spring 253,000 27 0.55 17.80 4.27 0.63 0.65 0.67 5.06 12.20 19.50 50.90 

Summer 549,000 22 1.21 15.30 2.73 0.45 0.45 0.51 5.36 10.60 25.10 34.90 

Winter 396,000 33 0.81 8.08 1.99 0.18 0.21 0.28 0.74 5.47 11.50 19.80 

Urbanization 

Central City 115,000 7 0.20 * * * * * * * * * 

Non-metropolitan 988,000 59 2.19 16.80 2.10 0.48 0.96 1.89 6.74 10.80 20.40 34.90 

Suburban 306,000 23 0.35 9.86 2.38 0.40 0.40 0.45 0.57 5.36 13.10 28.10 

Race 

Black 0 0 0.00 - - - - - - - - -

White 1,382,000 86 0.88 14.30 1.65 0.18 0.45 0.51 3.82 10.30 19.50 34.20 

Response to Questionnaire 

Households who raise animals 1,228,000 80 12.16 15.90 1.73 0.18 0.40 1.89 6.13 10.80 19.60 34.90 

Households who farm 1,020,000 63 13.92 17.10 1.99 0.40 0.74 3.18 9.06 12.10 20.40 34.90 

44.00 

* 

* 

* 

* 

19.50 

* 

* 

* 

80.10 

36.70 

20.40 

* 

44.00 

28.90 

-

44.00 

44.00 

44.00 

72.60 

* 

* 

* 

* 

23.00 

* 

* 

* 

111.00 

46.80 

72.60 

* 

80.10 

50.90 

-

80.10 

80.10 

80.10 

111.00 

* 

* 

* 

* 

23.00 

* 

* 

* 

111.00 

46.80 

72.60 

* 

111.00 

50.90 

-

111.00 

111.00 

111.00 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

- Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Moya and Phillips (2001). (Based on EPA's analyses of the 1987–1988 NFCS.) 

Page Exposure Factors Handbook 13-34 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-26. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 312,000 16 0.76 * * * * * * * * * 

Season 

Fall 48,000 2 0.51 * * * * * * * * * 

Spring 36,000 4 0.34 * * * * * * * * * 

Summer 116,000 4 1.23 * * * * * * * * * 

Winter 112,000 6 0.95 * * * * * * * * * 

Urbanization 

Central City 0 0 0.00 - - - - - - - - -

Non-metropolitan 240,000 10 4.35 * * * * * * * * * 

Suburban 72,000 6 0.28 * * * * * * * * * 

Response to Questionnaire 

Households who raise animals 312,000 16 26.49 * * * * * * * * * 

Households who farm 312,000 16 37.59 * * * * * * * * * 

* 

* 

* 

* 

* 

-

* 

* 

* 

* 

* 

* 

* 

* 

* 

-

* 

* 

* 

* 

* 

* 

* 

* 

* 

-

* 

* 

* 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

- Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-35
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-27. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 594,000 36 1.28 18.60 3.15 0.45 0.45 1.97 8.27 12.40 23.00 44.00 

Season 

Fall 163,000 5 1.13 * * * * * * * * * 

Spring 94,000 12 0.88 * * * * * * * * * 

Summer 252,000 11 2.46 * * * * * * * * * 

Winter 85,000 8 0.76 * * * * * * * * * 

Urbanization 

Central City 43,000 1 0.25 * * * * * * * * * 

Non-metropolitan 463,000 31 3.24 23.30 3.40 4.25 8.27 9.06 12.10 16.00 31.40 44.00 

Suburban 88,000 4 0.60 * * * * * * * * * 

Response to Questionnaire 

Households who raise animals 490,000 32 13.09 22.30 3.33 4.25 5.36 8.27 10.80 15.40 31.40 44.00 

Households who farm 490,000 32 18.28 22.30 3.33 4.25 5.36 8.27 10.80 15.40 31.40 44.00 

46.80 

* 

* 

* 

* 

* 

46.80 

* 

46.80 

46.80 

111.00 

* 

* 

* 

* 

* 

111.00 * 

111.00 

111.00 

111.00 

* 

* 

* 

* 

* 

111.00 * 

111.00 

111.00 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-36 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-28. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 242,000 17 0.38 * * * * * * * * * 

Season 

Fall 0 0 0.00 - - - - - - - - -

Spring 27,000 3 0.16 * * * * * * * * * 

Summer 131,000 5 0.74 * * * * * * * * * 

Winter 84,000 9 0.51 * * * * * * * * * 

Urbanization 

Central City 27,000 3 0.16 * * * * * * * * * 

Non-metropolitan 215,000 14 1.13 * * * * * * * * * 

Suburban 0 0 0.00 - - - - - - - - -

Response to Questionnaire 

Households who raise animals 215,000 14 8.26 * * * * * * * * * 

Households who farm 148,000 8 6.63 * * * * * * * * * 

* 

-

* 

* 

* 

* 

* 

-

* 

* 

* 

-

* 

* 

* 

* 

* 

-

* 

* 

* 

-

* 

* 

* 

* 

* 

-

* 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

- Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-37
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-29. Consumer-Only Intake of Home-Produced Dairy (g/kg-day)—West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 261,000 20 0.72 10.00 2.75 0.18 0.18 0.21 0.51 6.10 13.30 

Season 

Fall 0 0 0.00 

--------

Spring 96,000 8 1.18 * * * * * * * * 

Summer 50,000 2 0.63 * * * * * * * * 

Winter 115,000 10 1.25 * * * * * * * * 

Urbanization 

Central City 45,000 3 0.37 * * * * * * * * 

Non-metropolitan 70,000 4 1.15 * * * * * * * * 

Suburban 146,000 13 0.81 * * * * * * * * 

Response to Questionnaire 

Households who raise animals 211,000 18 8.20 * * * * * * * * 

Households who farm 70,000 7 4.41 * * * * * * * * 

28.10 -

* 

* 

* 

* 

* 

* 

* 

* 

28.90 -

* 

* 

* 

* 

* 

* 

* 

* 

50.90 -

* 

* 

* 

* 

* 

* 

* 

* 

50.90 -

* 

* 

* 

* 

* 

* 

* 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-38 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-30. Seasonally Adjusted Consumer-Only Home-Produced Intake (g/kg-day) 

Population Group 

Percent 

Consuming p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total Vegetable 

Northeast 16.50 0.00 0.02 0.04 0.20 0.46 1.37 3.32 5.70 

Midwest 33.25 0.00 0.04 0.08 0.29 0.81 1.96 4.40 7.41 

South 24.00 0.00 0.03 0.06 0.21 0.61 1.86 3.95 5.63 

West 23.75 0.00 0.02 0.04 0.11 0.49 1.46 2.99 5.04 

All Regions 24.60 0.01 0.03 0.06 0.22 0.64 1.80 4.00 6.08 

Total Fruit 

Northeast 3.50 0.00 0.02 0.05 0.17 0.36 0.66 1.48 3.00 

Midwest 12.75 0.00 0.01 0.01 0.14 0.79 2.98 5.79 9.52 

South 8.00 0.01 0.03 0.11 0.38 0.95 2.10 6.70 10.20 

West 17.75 0.00 0.06 0.09 0.29 0.69 1.81 4.75 8.54 

All Regions 10.10 0.00 0.02 0.06 0.25 0.75 2.35 5.61 9.12 

Total Meat 

Northeast 6.25 0.00 0.03 0.08 0.13 0.21 0.70 1.56 1.91 

Midwest 9.25 0.00 0.04 0.22 0.05 1.61 3.41 5.25 7.45 

South 5.75 0.01 0.03 0.05 0.19 0.53 1.84 3.78 4.95 

West 9.50 0.00 0.03 0.10 0.24 0.56 1.30 2.29 3.38 

All Regions 7.40 0.00 0.04 0.09 0.22 0.66 1.96 4.05 5.17 

8.78 

1.31 

12.00 

8.91 

11.70 

5.10 

22.20 

14.90 

14.50 

17.60 

4.09 

11.90 

8.45 

7.20 

9.40 

10.10 

20.10 

16.20 

11.20 

20.10 

5.63 

27.10 

16.40 

18.40 

27.10 

4.80 

13.60 

9.45 

9.10 

13.60 

Source: Moya and Phillips (2001). (Based on U.S. EPA's analyses of the 1987–1988 NFCS.) 

Exposure Factors Handbook PageSeptember 2011 13-39
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-31. Consumer-Only Intake of Home-Produced Apples (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 5,306,000 272 2.82 1.19 0.08 0.08 0.23 0.28 0.45 0.82 1.47 

Age 

1 to 2 199,000 12 3.49 * * * * * * * * 

3 to 5 291,000 16 3.59 * * * * * * * * 

6 to 11 402,000 25 2.41 1.28 0.19 0.47 0.47 0.56 0.74 0.96 1.29 

12 to 19 296,000 12 1.44 * * * * * * * * 

20 to 39 1,268,000 61 2.06 0.80 0.11 0.19 0.23 0.26 0.30 0.60 0.92 

40 to 69 1,719,000 90 3.03 0.96 0.14 0.06 0.09 0.26 0.40 0.65 1.08 

≥ 70 1,061,000 52 6.68 1.45 0.14 0.20 0.26 0.45 0.63 1.18 1.82 

Season 

Fall 1,707,000 60 3.58 1.28 0.12 0.26 0.30 0.32 0.58 1.03 1.66 

Spring 639,000 74 1.38 0.95 0.11 0.19 0.24 0.28 0.38 0.57 1.10 

Summer 1,935,000 68 4.25 1.12 0.17 0.06 0.09 0.19 0.40 0.69 1.41 

Winter 1,025,000 70 2.10 1.30 0.18 0.19 0.23 0.32 0.57 0.88 1.59 

Urbanization 

Central City 912,000 30 1.62 1.24 0.26 0.23 0.26 0.39 0.51 0.92 1.59 

Non-metropolitan 2,118,000 122 4.70 1.27 0.13 0.06 0.12 0.25 0.41 0.90 1.55 

Suburban 2,276,000 120 2.63 1.09 0.09 0.19 0.24 0.29 0.44 0.77 1.29 

Race 

Black 84,000 4 0.39 * * * * * * * * 

White 5,222,000 268 3.31 1.18 0.08 0.08 0.23 0.28 0.45 0.80 1.41 

Region 

Midwest 2,044,000 123 4.41 1.38 0.15 0.22 0.29 0.30 0.52 0.92 1.61 

Northeast 442,000 18 1.07 * * * * * * * * 

South 1,310,000 65 2.04 1.10 0.11 0.20 0.24 0.30 0.44 0.92 1.38 

West 1,510,000 66 4.19 1.20 0.13 0.06 0.19 0.26 0.47 0.79 1.82 

Response to Questionnaire 

Households who garden 4,707,000 246 6.91 1.21 0.08 0.13 0.25 0.30 0.47 0.82 1.47 

Households who farm 1,299,000 68 17.72 1.39 0.13 0.06 0.36 0.54 0.70 0.96 1.58 

2.38 

* 

* 

2.98 

* 

1.55 

1.59 

3.40 

2.69 

2.00 

2.29 

2.75 

2.19 

2.92 

2.29 

* 

2.38 

2.69 

* 

1.90 

2.75 

2.38 

2.99 

3.40 

* 

* 

4.00 

* 

1.97 

2.38 

3.62 

3.40 

2.78 

2.98 

3.40 

2.26 

3.48 

3.40 

* 

3.40 

3.40 

* 

2.98 

3.62 

3.40 

4.00 

5.42 

* 

* 

4.00 

* 

5.42 

9.83 

4.20 

4.25 

5.87 

9.83 

10.10 

10.10 

9.83 

5.42 

* 

5.42 

9.83 

* 

4.00 

4.25 

5.87 

4.91 

10.10 

* 

* 

4.00 

* 

5.42 

9.83 

4.20 

4.25 

5.87 

9.83 

10.10 

10.10 

9.83 

5.42 

* 

10.10 

10.10 * 

4.91 

4.25 

10.10 

5.87 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-40 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-32. Consumer-Only Intake of Home-Produced Asparagus (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 763,000 66 0.41 0.56 0.05 0.10 0.14 0.19 0.28 0.40 0.71 1.12 

Age 

1 to 2 8,000 1 0.14 * * * * * * * * * 

3 to 5 25,000 3 0.31 * * * * * * * * * 

6 to 11 31,000 3 0.19 * * * * * * * * * 

12 to 19 70,000 5 0.34 * * * * * * * * * 

20 to 39 144,000 11 0.23 * * * * * * * * * 

40 to 69 430,000 38 0.76 0.47 0.05 0.11 0.11 0.18 0.23 0.40 0.60 0.88 

≥ 70 55,000 5 0.35 * * * * * * * * * 

Season 

Fall 62,000 2 0.13 * * * * * * * * * 

Spring 608,000 59 1.32 0.61 0.06 0.10 0.16 0.19 0.30 0.45 0.88 1.18 

Summer 0 0 0.00 

---------

Winter 93,000 5 0.19 * * * * * * * * * 

Urbanization 

Central City 190,000 9 0.34 * * * * * * * * * 

Non-metropolitan 215,000 27 0.48 0.76 0.12 0.10 0.11 0.14 0.23 0.54 1.24 1.75 

Suburban 358,000 30 0.41 0.43 0.04 0.11 0.17 0.18 0.28 0.37 0.58 0.70 

Race 

Black 0 0 0.00 

---------

White 763,000 66 0.48 0.56 0.05 0.10 0.14 0.19 0.28 0.40 0.71 1.12 

Region 

Midwest 368,000 33 0.79 0.48 0.06 0.10 0.11 0.14 0.23 0.40 0.61 0.93 

Northeast 270,000 20 0.66 0.72 0.10 0.18 0.23 0.23 0.37 0.60 0.93 1.24 

South 95,000 9 0.15 * * * * * * * * * 

West 30,000 4 0.08 * * * * * * * * * 

Response to Questionnaire 

Households who garden 669,000 59 0.98 0.53 0.06 0.10 0.14 0.18 0.28 0.40 0.70 1.12 

Households who farm 157,000 16 2.14 * * * * * * * * * 

1.63 

* 

* 

* 

* 

* 

1.24 * 

* 

1.63 -

* 

* 

1.92 

0.93 -

1.63 

1.12 

1.63 * 

* 

1.63 * 

1.97 

* 

* 

* 

* 

* 

1.75 * 

* 

1.97 -

* 

* 

1.97 

1.12 -

1.97 

1.97 

1.92 * 

* 

1.97 

* 

1.97 

* 

* 

* 

* 

* 

1.75 * 

* 

1.97 -

* 

* 

1.97 

1.12 -

1.97 

1.97 

1.92 * 

* 

1.97 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-41
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-33. Consumer-Only Intake of Home-Produced Beef (g/kg-day) 

Population Nc Nc % 

Group wgtd Unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 4,958,000 304 2.64 2.45 0.15 0.18 0.37 0.47 0.88 1.61 3.07 

Age 

1 to 2 110,000 8 1.93 * * * * * * * * 

3 to 5 234,000 13 2.89 * * * * * * * * 

6 to 11 695,000 38 4.16 3.77 0.59 0.35 0.66 0.75 1.32 2.11 4.43 

12 to 19 656,000 41 3.20 1.72 0.16 0.38 0.48 0.51 0.90 1.51 2.44 

20 to 39 1,495,000 83 2.43 2.06 0.20 0.27 0.35 0.39 0.68 1.59 2.73 

40 to 69 1,490,000 105 2.63 1.84 0.14 0.18 0.36 0.46 0.83 1.52 2.38 

≥ 70 188,000 11 1.18 * * * * * * * * 

Season 

Fall 1,404,000 55 2.95 1.55 0.17 0.18 0.35 0.36 0.52 1.33 2.01 

Spring 911,000 108 1.97 2.32 0.16 0.27 0.39 0.51 1.04 1.96 3.29 

Summer 1,755,000 69 3.86 3.48 0.41 0.10 0.61 0.75 1.02 2.44 4.43 

Winter 888,000 72 1.82 1.95 0.28 0.04 0.38 0.39 0.67 1.33 2.14 

Urbanization 

Central City 100,000 5 0.18 * * * * * * * * 

Non-metropolitan 3,070,000 194 6.82 2.80 0.22 0.18 0.38 0.50 0.86 1.81 3.57 

Suburban 1,788,000 105 2.07 1.93 0.15 0.27 0.38 0.42 0.91 1.52 2.44 

Race 

Black 0 0 0.00 

--------

White 4,950,000 303 3.14 2.45 0.15 0.18 0.37 0.47 0.88 1.61 3.07 

Region 

Midwest 2,261,000 161 4.87 2.83 0.23 0.18 0.35 0.42 0.85 2.01 3.66 

Northeast 586,000 25 1.42 1.44 0.21 0.35 0.35 0.47 0.74 1.06 1.68 

South 1,042,000 61 1.62 2.45 0.35 0.10 0.39 0.58 0.82 1.59 2.41 

West 1,069,000 57 2.96 2.20 0.28 0.31 0.38 0.56 1.04 1.60 2.86 

Response to Questionnaire 

Households who raise animals 3,699,000 239 36.63 2.66 0.16 0.18 0.39 0.66 1.04 1.83 3.48 

Households who farm 2,850,000 182 38.89 2.63 0.20 0.27 0.39 0.59 0.90 1.64 3.25 

5.29 

* 

* 

11.40 

3.53 

4.88 

4.10 

* 

2.86 

4.22 

7.51 

4.23 

* 

6.03 

4.06 -

5.29 

5.90 

2.62 

6.36 

4.06 

5.39 

5.39 

7.24 

* 

* 

12.50 

3.57 

6.50 

5.39 

* 

3.90 

5.23 

11.40 

5.39 

* 

8.44 

5.10 -

7.24 

8.39 

2.62 

7.24 

4.42 

7.51 

7.51 

13.30 

* 

* 

13.30 

4.28 

8.26 

5.90 

* 

7.24 

8.62 

18.70 

19.40 

* 

18.70 

7.51 -

13.30 

18.70 

6.03 

13.30 

7.51 

12.50 

11.30 

19.40 

* 

* 

13.30 

4.28 

8.26 

5.90 

* 

7.24 

9.28 

18.70 

19.40 

* 

19.40 

9.28 -

19.40 

18.70 

6.03 

13.30 

19.40 

19.40 

19.40 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-42 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-34. Consumer-Only Intake of Home-Produced Beets (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,214,000 125 1.18 0.51 0.05 0.03 0.07 0.11 0.19 0.40 0.59 

Age 

1 to 2 27,000 2 0.47 * * * * * * * * 

3 to 5 51,000 4 0.63 * * * * * * * * 

6 to 11 167,000 10 1.00 * * * * * * * * 

12 to 19 227,000 13 1.11 * * * * * * * * 

20 to 39 383,000 22 0.62 0.38 0.06 0.08 0.08 0.12 0.14 0.29 0.56 

40 to 69 951,000 51 1.68 0.43 0.04 0.05 0.07 0.07 0.21 0.40 0.55 

≥ 70 408,000 23 2.57 0.58 0.09 0.03 0.03 0.05 0.27 0.45 0.91 

Season 

Fall 562,000 21 1.18 0.55 0.09 0.03 0.05 0.05 0.26 0.36 0.95 

Spring 558,000 55 1.21 0.47 0.09 0.07 0.08 0.11 0.14 0.27 0.45 

Summer 676,000 22 1.49 0.39 0.05 0.08 0.12 0.12 0.18 0.40 0.55 

Winter 418,000 27 0.86 0.73 0.15 0.07 0.07 0.07 0.28 0.52 0.83 

Urbanization 

Central City 651,000 27 1.16 0.52 0.12 0.11 0.14 0.18 0.26 0.40 0.55 

Non-metropolitan 758,000 51 1.68 0.58 0.09 0.05 0.07 0.07 0.18 0.39 0.66 

Suburban 805,000 47 0.93 0.45 0.06 0.03 0.05 0.08 0.14 0.40 0.56 

Race 

Black 0 0 0.00 --------

White 2,186,000 124 1.39 0.52 0.05 0.03 0.07 0.11 0.21 0.40 0.59 

Region 

Midwest 885,000 53 1.91 0.63 0.08 0.05 0.11 0.18 0.32 0.45 0.91 

Northeast 230,000 13 0.56 * * * * * * * * 

South 545,000 31 0.85 0.45 0.12 0.07 0.08 0.08 0.18 0.26 0.48 

West 554,000 28 1.54 0.40 0.08 0.03 0.05 0.07 0.12 0.29 0.55 

Response to Questionnaire 

Households who garden 2,107,000 120 3.09 0.53 0.05 0.03 0.07 0.10 0.21 0.40 0.61 

Households who farm 229,000 11 3.12 * * * * * * * * 

1.03 

* 

* 

* 

* 

1.00 

0.93 

1.36 

1.36 

0.87 

0.62 

1.13 

0.91 

1.36 

0.93 -

1.03 

1.15 

* 

0.66 

0.62 

1.03 

* 

1.36 

* 

* 

* 

* 

1.00 

1.15 

1.36 

1.36 

1.59 

0.91 

2.32 

1.12 

1.40 

1.00 -

1.36 

1.36 

* 

0.94 

0.70 

1.36 

* 

3.69 

* 

* 

* 

* 

1.12 

1.40 

1.59 

1.40 

4.08 

0.91 

3.69 

3.69 

4.08 

2.32 -

3.69 

3.69 

* 

4.08 

2.32 

3.69 

* 

4.08 

* 

* 

* 

* 

1.12 

1.40 

1.59 

1.40 

4.08 

0.91 

3.69 

3.69 

4.08 

2.32 -

4.08 

3.69 

* 

4.08 

2.32 

4.08 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-43
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-35. Consumer-Only Intake of Home-Produced Broccoli (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,745,000 80 0.93 0.42 0.05 0.08 0.08 0.16 0.20 0.29 0.46 0.82 

Age 

1 to 2 0 0 0.00 ---------

3 to 5 13,000 1 0.16 * * * * * * * * * 

6 to 11 187,000 9 1.12 * * * * * * * * * 

12 to 19 102,000 4 0.50 * * * * * * * * * 

20 to 39 486,000 19 0.79 * * * * * * * * * 

40 to 69 761,000 37 1.34 0.41 0.07 0.08 0.11 0.16 0.22 0.35 0.46 0.61 

≥ 70 196,000 10 1.23 * * * * * * * * * 

Season 

Fall 624,000 20 1.31 0.29 0.04 0.08 0.08 0.08 0.18 0.23 0.38 0.45 

Spring 258,000 27 0.56 0.54 0.12 0.05 0.15 0.17 0.27 0.33 0.59 1.25 

Summer 682,000 22 1.50 0.51 0.11 0.08 0.13 0.18 0.22 0.40 0.66 0.89 

Winter 181,000 11 0.37 * * * * * * * * * 

Urbanization 

Central City 165,000 5 0.29 * * * * * * * * * 

Non-metropolitan 647,000 34 1.44 0.42 0.04 0.05 0.13 0.17 0.22 0.37 0.59 0.75 

Suburban 933,000 41 1.08 0.43 0.08 0.08 0.08 0.14 0.21 0.24 0.44 0.68 

Race 

Black 0 0 0.00 ---------

White 1,719,000 79 1.09 0.42 0.05 0.08 0.08 0.16 0.20 0.29 0.46 0.82 

Region 

Midwest 792,000 38 1.71 0.26 0.06 0.08 0.08 0.08 0.18 0.21 0.28 0.34 

Northeast 427,000 19 1.04 * * * * * * * * * 

South 373,000 16 0.58 * * * * * * * * * 

West 153,000 7 0.42 * * * * * * * * * 

Response to Questionnaire 

Households who garden 1,729,000 78 2.54 0.42 0.05 0.08 0.08 0.16 0.20 0.29 0.46 0.82 

Households who farm 599,000 29 8.17 0.47 0.08 0.05 0.08 0.15 0.20 0.31 0.66 0.89 

0.97 -

* 

* 

* 

* 

0.82 

* 

0.53 

2.37 

0.97 

* 

* 

0.89 

2.37 -

0.97 

0.40 

* 

* 

* 

0.97 

0.97 

2.48 -

* 

* 

* 

* 

3.02 

* 

0.82 

3.02 

2.48 

* 

* 

0.97 

2.48 -

2.48 

3.02 

* 

* 

* 

2.48 

3.02 

3.02 -

* 

* 

* 

* 

3.02 

* 

0.82 

3.02 

2.48 

* 

* 

0.97 

3.02 -

3.02 

3.02 

* 

* 

* 

3.02 

3.02 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-44 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-36. Consumer-Only Intake of Home-Produced Cabbage (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,019,000 89 1.07 1.03 0.10 0.11 0.20 0.32 0.42 0.78 1.33 

Age 

1 to 2 14,000 2 0.25 * * * * * * * * 

3 to 5 29,000 1 0.36 * * * * * * * * 

6 to 11 61,000 3 0.37 * * * * * * * * 

12 to 19 203,000 9 0.99 * * * * * * * * 

20 to 39 391,000 16 0.63 * * * * * * * * 

40 to 69 966,000 44 1.70 1.14 0.18 0.22 0.22 0.33 0.41 0.71 1.41 

≥ 70 326,000 13 2.05 * * * * * * * * 

Season 

Fall 570,000 21 1.20 1.28 0.32 0.19 0.19 0.20 0.39 0.54 1.49 

Spring 126,000 15 0.27 * * * * * * * * 

Summer 1,142,000 39 2.51 0.97 0.09 0.20 0.22 0.33 0.56 0.83 1.24 

Winter 181,000 14 0.37 * * * * * * * * 

Urbanization 

Central City 157,000 5 0.28 * * * * * * * * 

Non-metropolitan 1,079,000 48 2.40 0.94 0.09 0.20 0.32 0.34 0.45 0.71 1.33 

Suburban 783,000 36 0.90 1.26 0.21 0.03 0.22 0.33 0.45 1.05 1.37 

Race 

Black 7,000 1 0.03 * * * * * * * * 

White 1,867,000 83 1.19 1.05 0.11 0.11 0.20 0.25 0.41 0.79 1.37 

Region 

Midwest 884,000 37 1.91 0.74 0.07 0.11 0.19 0.22 0.36 0.60 1.10 

Northeast 277,000 11 0.67 * * * * * * * * 

South 616,000 32 0.96 1.11 0.13 0.03 0.20 0.22 0.45 0.85 1.79 

West 242,000 9 0.67 * * * * * * * * 

Response to Questionnaire 

Households who garden 1,921,000 86 2.82 1.07 0.10 0.11 0.20 0.32 0.45 0.79 1.37 

Households who farm 546,000 26 7.45 1.00 0.12 0.20 0.21 0.35 0.59 0.83 1.37 

1.97 

* 

* 

* 

* 

* 

1.82 

* 

5.29 

* 

1.79 

* 

* 

1.79 

2.17 

* 

1.97 

1.29 

* 

2.17 

* 

1.97 

1.79 

2.35 

* 

* 

* 

* 

* 

5.29 

* 

5.43 

* 

2.35 

* 

* 

2.35 

5.29 

* 

2.35 

1.49 

* 

2.35 

* 

2.35 

2.35 

5.43 

* 

* 

* 

* 

* 

5.43 

* 

5.43 

* 

2.77 

* 

* 

2.77 

5.43 

* 

5.43 

1.82 

* 

2.77 

* 

5.43 

2.35 

5.43 

* 

* 

* 

* 

* 

5.43 

* 

5.43 

* 

2.77 

* 

* 

2.77 

5.43 

* 

5.43 

1.98 

* 

2.77 

* 

5.43 

2.35 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-45
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-37. Consumer-Only Intake of Home-Produced Carrots (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 4,322,000 193 2.30 0.44 0.04 0.04 0.06 0.09 0.18 0.33 0.53 

Age 

1 to 2 51,000 4 0.89 * * * * * * * * 

3 to 5 53,000 3 0.65 * * * * * * * * 

6 to 11 299,000 14 1.79 * * * * * * * * 

12 to 19 389,000 17 1.90 * * * * * * * * 

20 to 39 1,043,000 46 1.69 0.28 0.03 0.04 0.05 0.08 0.12 0.20 0.41 

40 to 69 1,848,000 82 3.26 0.43 0.03 0.04 0.07 0.12 0.22 0.37 0.55 

≥ 70 574,000 24 3.61 0.44 0.06 0.07 0.18 0.20 0.26 0.37 0.54 

Season 

Fall 1,810,000 66 3.80 0.46 0.10 0.09 0.11 0.12 0.20 0.31 0.51 

Spring 267,000 28 0.58 0.56 0.10 0.14 0.15 0.20 0.22 0.39 0.61 

Summer 1,544,000 49 3.39 0.39 0.04 0.04 0.05 0.07 0.16 0.38 0.51 

Winter 701,000 50 1.44 0.44 0.07 0.04 0.04 0.06 0.16 0.23 0.64 

Urbanization 

Central City 963,000 29 1.71 0.28 0.04 0.04 0.06 0.08 0.16 0.21 0.39 

Non-metropolitan 1,675,000 94 3.72 0.52 0.09 0.04 0.05 0.07 0.20 0.33 0.51 

Suburban 1,684,000 70 1.94 0.45 0.04 0.07 0.09 0.12 0.20 0.38 0.64 

Race 

Black 107,000 7 0.49 * * * * * * * * 

White 3,970,000 178 2.52 0.41 0.03 0.04 0.08 0.11 0.19 0.33 0.53 

Region 

Midwest 2,001,000 97 4.31 0.46 0.04 0.04 0.08 0.14 0.20 0.37 0.54 

Northeast 735,000 29 1.79 0.41 0.09 0.04 0.05 0.06 0.09 0.15 0.64 

South 378,000 20 0.59 0.63 0.36 0.04 0.04 0.05 0.15 0.27 0.41 

West 1,208,000 47 3.35 0.37 0.03 0.07 0.09 0.14 0.19 0.33 0.46 

Response to Questionnaire 

Households who garden 4,054,000 182 5.95 0.40 0.03 0.04 0.07 0.09 0.18 0.33 0.51 

Households who farm 833,000 40 11.37 0.36 0.06 0.09 0.09 0.11 0.18 0.23 0.46 

0.80 

* 

* 

* 

* 

0.56 

0.78 

0.96 

0.78 

0.99 

0.84 

1.05 

0.53 

0.96 

0.80 

* 

0.78 

0.96 

1.09 

0.50 

0.76 

0.76 

0.62 

1.08 

* 

* 

* 

* 

0.76 

1.01 

1.08 

1.08 

2.11 

0.96 

1.53 

0.59 

1.19 

1.09 

* 

1.01 

1.10 

1.71 

0.99 

0.84 

1.08 

1.19 

2.21 

* 

* 

* 

* 

1.19 

1.53 

1.08 

1.71 

2.94 

1.19 

3.06 

0.96 

7.79 

1.71 

* 

1.59 

2.11 

2.21 

7.79 

0.96 

1.71 

2.11 

7.79 

* 

* 

* 

* 

1.19 

2.21 

1.08 

7.79 

2.94 

1.19 

3.06 

0.96 

7.79 

1.71 

* 

3.06 

3.06 

2.21 

7.79 

0.96 

3.06 

2.94 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-46 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-38. Consumer-Only Intake of Home-Produced Corn (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 6,891,000 421 3.67 0.89 0.06 0.05 0.12 0.17 0.24 0.48 0.91 

Age 

1 to 2 205,000 13 3.60 * * * * * * * * 

3 to 5 313,000 24 3.86 1.25 0.26 0.33 0.33 0.40 0.60 1.00 1.21 

6 to 11 689,000 43 4.12 0.93 0.17 0.11 0.12 0.19 0.25 0.51 1.08 

12 to 19 530,000 32 2.59 0.59 0.10 0.10 0.11 0.14 0.21 0.34 0.71 

20 to 39 1,913,000 108 3.11 0.60 0.06 0.07 0.14 0.15 0.21 0.37 0.71 

40 to 69 2,265,000 142 3.99 0.86 0.11 0.11 0.15 0.17 0.26 0.52 0.88 

≥ 70 871,000 53 5.48 0.94 0.26 0.04 0.05 0.11 0.19 0.36 0.76 

Season 

Fall 2,458,000 89 5.16 0.54 0.08 0.04 0.11 0.14 0.19 0.32 0.55 

Spring 1,380,000 160 2.99 0.64 0.06 0.14 0.17 0.19 0.26 0.45 0.77 

Summer 1,777,000 62 3.91 1.82 0.26 0.07 0.18 0.34 0.64 0.94 2.13 

Winter 1,276,000 110 2.62 0.55 0.05 0.11 0.12 0.15 0.22 0.41 0.61 

Urbanization 

Central City 748,000 27 1.33 0.74 0.14 0.04 0.04 0.05 0.18 0.55 0.93 

Non-metropolitan 4,122,000 268 9.16 0.96 0.08 0.07 0.12 0.17 0.25 0.53 1.00 

Suburban 2,021,000 126 2.33 0.80 0.13 0.11 0.15 0.17 0.24 0.40 0.65 

Race 

Black 188,000 9 0.86 * * * * * * * * 

White 6,703,000 412 4.26 0.89 0.07 0.05 0.12 0.16 0.24 0.48 0.88 

Region 

Midwest 2,557,000 188 5.51 0.93 0.10 0.04 0.12 0.17 0.25 0.46 0.93 

Northeast 586,000 33 1.42 0.61 0.08 0.10 0.17 0.19 0.24 0.38 0.88 

South 2,745,000 153 4.27 0.87 0.10 0.07 0.12 0.17 0.28 0.56 0.94 

West 1,003,000 47 2.78 1.00 0.28 0.11 0.15 0.15 0.18 0.40 0.75 

Response to Questionnaire 

Households who garden 6233000 387 9.15 0.88 0.06 0.05 0.14 0.17 0.24 0.50 0.91 

Households who farm 1739000 114 23.73 1.20 0.18 0.04 0.11 0.17 0.23 0.38 0.97 

1.88 

* 

1.67 

3.13 

1.55 

1.53 

1.42 

1.34 

1.27 

1.21 

4.52 

1.16 

2.04 

2.13 

1.34 

* 

1.88 

2.28 

1.34 

1.55 

2.23 

1.82 

3.37 

3.37 

* 

5.35 

3.37 

1.88 

2.04 

3.22 

6.49 

1.42 

1.57 

6.84 

1.47 

2.23 

3.38 

1.71 

* 

3.22 

3.22 

1.71 

3.37 

6.49 

3.13 

6.49 

7.44 

* 

5.35 

4.52 

1.88 

3.70 

7.44 

9.23 

5.35 

5.15 

9.23 

2.04 

3.04 

7.44 

9.23 

* 

7.44 

6.84 

1.71 

5.69 

9.23 

6.84 

9.23 

9.23 

* 

5.35 

4.52 

1.88 

3.70 

7.44 

9.23 

5.69 

6.68 

9.23 

3.94 

3.04 

8.97 

9.23 

* 

9.23 

7.44 

1.71 

8.97 

9.23 

9.23 

9.23 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-47
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-39. Consumer-Only Intake of Home-Produced Cucumbers (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 3,994,000 141 2.12 1.02 0.16 0.03 0.07 0.11 0.24 0.54 1.13 

Age 

1 to 2 132,000 5 2.32 * * * * * * * * 

3 to 5 107,000 4 1.32 * * * * * * * * 

6 to 11 356,000 12 2.13 * * * * * * * * 

12 to 19 254,000 10 1.24 * * * * * * * * 

20 to 39 864,000 29 1.40 0.50 0.09 0.03 0.05 0.06 0.18 0.31 0.62 

40 to 69 1,882,000 68 3.32 1.33 0.30 0.04 0.07 0.18 0.39 0.68 1.29 

≥ 70 399,000 13 2.51 * * * * * * * * 

Season 

Fall 370,000 12 0.78 * * * * * * * * 

Spring 197,000 15 0.43 * * * * * * * * 

Summer 3,427,000 114 7.53 1.06 0.18 0.00 0.07 0.11 0.24 0.52 1.13 

Winter 0 0 0.00 --------

Urbanization 

Central City 640,000 18 1.14 * * * * * * * * 

Non-metropolitan 1,530,000 64 3.40 1.74 0.34 0.10 0.12 0.19 0.39 1.06 1.67 

Suburban 1,824,000 59 2.11 0.67 0.08 0.00 0.07 0.16 0.28 0.50 0.83 

Race 

Black 86,000 2 0.40 * * * * * * * * 

White 3,724,000 132 2.36 0.94 0.16 0.03 0.06 0.10 0.22 0.50 1.03 

Region 

Midwest 969,000 31 2.09 1.00 0.39 0.03 0.04 0.05 0.14 0.45 1.03 

Northeast 689,000 22 1.67 1.92 0.68 0.23 0.28 0.28 0.48 0.68 1.53 

South 1,317,000 54 2.05 0.89 0.11 0.00 0.12 0.18 0.29 0.75 1.28 

West 1,019,000 34 2.83 0.60 0.11 0.07 0.07 0.10 0.21 0.43 0.70 

Response to Questionnaire 

Households who garden 3,465,000 123 5.08 1.05 0.18 0.03 0.07 0.10 0.28 0.52 1.13 

Households who farm 710,000 29 9.69 0.70 0.11 0.00 0.00 0.14 0.19 0.39 1.27 

2.11 

* 

* 

* 

* 

1.35 

2.11 

* 

* 

* 

2.12 -

* 

3.09 

1.34 

* 

1.49 

2.35 

4.18 

1.73 

1.29 

2.11 

1.49 

2.79 

* 

* 

* 

* 

1.49 

3.27 

* 

* 

* 

2.79 -

* 

4.50 

1.73 

* 

2.40 

2.45 

11.70 

2.13 

2.11 

2.79 

1.71 

13.40 

* 

* 

* 

* 

2.12 

13.70 

* 

* 

* 

13.40 -

* 

13.70 

3.27 

* 

13.40 

13.40 

13.70 

4.50 

3.27 

13.40 

2.09 

13.70 

* 

* 

* 

* 

2.12 

13.70 

* 

* 

* 

13.70 -

* 

13.70 

3.27 

* 

13.70 

13.40 

13.70 

4.50 

3.27 

13.70 

2.09 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-48 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-40. Consumer-Only Intake of Home-Produced Eggs (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,075,000 124 1.10 0.73 0.10 0.07 0.15 0.18 0.27 0.47 0.90 

Age 

1 to 2 21,000 3 0.37 * * * * * * * * 

3 to 5 20,000 2 0.25 * * * * * * * * 

6 to 11 170,000 12 1.02 * * * * * * * * 

12 to 19 163,000 14 0.80 * * * * * * * * 

20 to 39 474,000 30 0.77 0.63 0.09 0.07 0.07 0.22 0.30 0.42 0.81 

40 to 69 718,000 43 1.27 0.59 0.06 0.14 0.14 0.15 0.32 0.51 0.84 

≥ 70 489,000 18 3.08 * * * * * * * * 

Season 

Fall 542,000 18 1.14 * * * * * * * * 

Spring 460,000 54 1.00 1.31 0.29 0.16 0.33 0.39 0.50 0.67 1.31 

Summer 723,000 26 1.59 0.50 0.08 0.07 0.14 0.14 0.26 0.33 0.54 

Winter 350,000 26 0.72 0.86 0.10 0.17 0.18 0.22 0.40 0.75 1.17 

Urbanization 

Central City 251,000 9 0.45 * * * * * * * * 

Non-metropolitan 1,076,000 65 2.39 0.73 0.12 0.07 0.14 0.17 0.26 0.47 0.92 

Suburban 748,000 50 0.86 0.85 0.20 0.14 0.15 0.21 0.38 0.59 1.17 

Race 

Black 63,000 9 0.29 * * * * * * * * 

White 2,012,000 115 1.28 0.74 0.11 0.07 0.15 0.18 0.27 0.48 0.90 

Region 

Midwest 665,000 37 1.43 0.79 0.20 0.07 0.14 0.14 0.22 0.34 1.08 

Northeast 87,000 7 0.21 * * * * * * * * 

South 823,000 44 1.28 0.54 0.06 0.15 0.18 0.20 0.26 0.36 0.60 

West 500,000 36 1.39 0.92 0.28 0.17 0.21 0.21 0.46 0.67 1.05 

Response to Questionnaire 

Households who raise animals 1,824,000 113 18.06 0.75 0.11 0.07 0.15 0.17 0.26 0.48 0.90 

Households who farm 741,000 44 10.11 0.90 0.17 0.15 0.17 0.18 0.27 0.67 1.19 

1.36 

* 

* 

* 

* 

1.32 

1.30 

* 

* 

2.10 

1.36 

1.62 

* 

1.34 

1.36 

* 

1.36 

1.51 

* 

1.18 

1.36 

1.36 

1.65 

1.69 

* 

* 

* 

* 

1.93 

1.36 

* 

* 

3.26 

1.51 

1.93 

* 

1.65 

1.85 

* 

1.69 

2.10 

* 

1.62 

1.36 

1.85 

1.85 

6.58 

* 

* 

* 

* 

2.50 

1.38 

* 

* 

13.50 

1.65 

1.93 

* 

6.58 

13.50 

* 

6.58 

9.16 

* 

1.93 

13.50 

6.58 

6.58 

13.50 

* 

* 

* 

* 

2.50 

1.38 

* 

* 

13.50 

1.65 

1.93 

* 

9.16 

13.50 

* 

13.50 

9.16 

* 

1.93 

13.50 

13.50 

9.16 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-49
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-41. Consumer-Only Intake of Home-Produced Game (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,707,000 185 1.44 0.97 0.06 0.00 0.12 0.21 0.40 0.71 1.22 

Age 

1 to 2 89,000 8 1.56 * * * * * * * * 

3 to 5 94,000 8 1.16 * * * * * * * * 

6 to 11 362,000 28 2.17 1.09 0.14 0.12 0.23 0.43 0.63 0.76 1.48 

12 to 19 462,000 27 2.25 1.04 0.14 0.21 0.21 0.29 0.63 0.85 1.22 

20 to 39 844,000 59 1.37 0.82 0.11 0.10 0.12 0.19 0.30 0.63 1.09 

40 to 69 694,000 41 1.22 0.96 0.14 0.12 0.17 0.29 0.34 0.51 1.41 

≥ 70 74,000 7 0.47 * * * * * * * * 

Season 

Fall 876,000 31 1.84 1.00 0.16 0.12 0.15 0.22 0.43 0.63 1.19 

Spring 554,000 68 1.20 0.91 0.09 0.00 0.10 0.17 0.44 0.75 1.22 

Summer 273,000 9 0.60 * * * * * * * * 

Winter 1,004,000 77 2.06 1.07 0.11 0.00 0.00 0.17 0.39 0.82 1.52 

Urbanization 

Central City 506,000 20 0.90 0.69 0.13 0.00 0.00 0.19 0.28 0.63 0.77 

Non-metropolitan 1,259,000 101 2.80 0.95 0.09 0.00 0.12 0.17 0.32 0.66 1.19 

Suburban 942,000 64 1.09 1.15 0.10 0.00 0.26 0.40 0.52 0.82 1.52 

Race 

Black 0 0 0.00 --------

White 2,605,000 182 1.65 0.98 0.06 0.00 0.12 0.20 0.38 0.73 1.38 

Region 

Midwest 1,321,000 97 2.85 0.88 0.08 0.00 0.08 0.22 0.34 0.61 1.10 

Northeast 394,000 20 0.96 1.13 0.22 0.29 0.29 0.32 0.43 0.77 1.41 

South 609,000 47 0.95 1.26 0.13 0.00 0.12 0.15 0.63 1.09 1.93 

West 383,000 21 1.06 0.63 0.07 0.12 0.15 0.19 0.40 0.63 0.77 

Response to Questionnaire 

Households who hunt 2,357,000 158 11.66 1.04 0.07 0.00 0.14 0.28 0.44 0.75 1.44 

2.27 

* 

* 

2.67 

1.99 

1.57 

2.51 

* 

2.50 

1.75 

* 

2.20 

1.48 

2.27 

2.51 -

2.34 

1.99 

3.13 

2.38 

1.12 

2.38 

2.67 

* 

* 

2.85 

3.13 

2.50 

3.19 

* 

3.13 

2.52 

* 

2.67 

1.99 

3.05 

2.85 -

2.85 

2.51 

3.13 

3.19 

1.22 

2.90 

3.61 

* 

* 

2.90 

3.13 

4.59 

3.61 

* 

3.19 

3.61 

* 

4.59 

2.34 

4.59 

3.13 -

3.61 

4.59 

3.61 

3.19 

1.52 

3.61 

4.59 

* 

* 

2.90 

3.13 

4.59 

3.61 

* 

3.19 

3.61 

* 

4.59 

2.34 

4.59 

3.61 -

4.59 

4.59 

3.61 

3.19 

1.52 

4.59 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-50 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-42. Consumer-Only Intake of Home-Produced Lettuce (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,520,000 80 0.81 0.39 0.03 0.00 0.04 0.09 0.17 0.28 

Age 

1 to 2 54,000 4 0.95 * * * * * * * 

3 to 5 25,000 2 0.31 * * * * * * * 

6 to 11 173,000 7 1.04 * * * * * * * 

12 to 19 71,000 3 0.35 * * * * * * * 

20 to 39 379,000 17 0.62 * * * * * * * 

40 to 69 485,000 26 0.86 0.48 0.06 0.12 0.12 0.12 0.22 0.49 

≥ 70 317,000 20 2.00 0.45 0.07 0.05 0.07 0.11 0.22 0.29 

Season 

Fall 214,000 8 0.45 * * * * * * * 

Spring 352,000 35 0.76 0.45 0.05 0.05 0.07 0.12 0.20 0.45 

Summer 856,000 30 1.88 0.30 0.04 0.02 0.03 0.05 0.14 0.23 

Winter 98,000 7 0.20 * * * * * * * 

Urbanization 

Central City 268,000 8 0.48 * * * * * * * 

Non-metropolitan 566,000 36 1.26 0.37 0.05 0.02 0.03 0.04 0.12 0.29 

Suburban 686,000 36 0.79 0.35 0.04 0.00 0.09 0.10 0.15 0.23 

Race 

Black 51,000 3 0.23 * * * * * * * 

White 1,434,000 75 0.91 0.38 0.03 0.00 0.04 0.09 0.16 0.28 

Region 

Midwest 630,000 33 1.36 0.38 0.06 0.02 0.03 0.04 0.16 0.23 

Northeast 336,000 16 0.82 * * * * * * * 

South 305,000 20 0.47 0.35 0.06 0.00 0.00 0.13 0.16 0.28 

West 249,000 11 0.69 * * * * * * * 

Response to Questionnaire 

Households who garden 1,506,000 78 2.21 0.39 0.03 0.00 0.04 0.09 0.17 0.28 

Households who farm 304,000 18 4.15 * * * * * * * 

0.55 

* 

* 

* 

* 

* 

0.68 

0.57 

* 

0.58 

0.42 

* 

* 

0.55 

0.49 

* 

0.55 

0.57 

* 

0.48 

* 

0.55 

* 

0.84 

* 

* 

* 

* 

* 

0.89 

1.03 

* 

0.80 

0.60 

* 

* 

0.81 

0.77 

* 

0.89 

0.94 

* 

0.58 

* 

0.84 

* 

1.03 

* 

* 

* 

* 

* 

1.05 

1.03 

* 

0.99 

0.81 

* 

* 

0.89 

0.99 

* 

1.03 

1.03 

* 

1.04 

* 

1.03 

* 

1.05 

* 

* 

* 

* 

* 

1.28 

1.03 

* 

1.28 

0.89 

* 

* 

1.28 

1.05 

* 

1.05 

1.03 

* 

1.28 

* 

1.05 

* 

1.28 

* 

* 

* 

* 

* 

1.28 

1.03 

* 

1.28 

0.89 

* 

* 

1.28 

1.05 

* 

1.28 

1.03 

* 

1.28 

* 

1.28 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-51
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-43. Consumer-Only Intake of Home-Produced Lima Beans (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,917,000 109 1.02 0.45 0.04 0.00 0.09 0.12 0.19 0.29 0.55 

Age 

1 to 2 62,000 3 1.09 * * * * * * * * 

3 to 5 35,000 2 0.43 * * * * * * * * 

6 to 11 95,000 7 0.57 * * * * * * * * 

12 to 19 108,000 6 0.53 * * * * * * * * 

20 to 39 464,000 20 0.75 0.38 0.07 0.03 0.11 0.13 0.18 0.23 0.49 

40 to 69 757,000 44 1.33 0.45 0.06 0.09 0.11 0.12 0.20 0.29 0.56 

≥ 70 361,000 25 2.27 0.52 0.11 0.08 0.19 0.19 0.23 0.29 0.64 

Season 

Fall 375,000 14 0.79 * * * * * * * * 

Spring 316,000 39 0.68 0.42 0.06 0.08 0.09 0.13 0.23 0.31 0.55 

Summer 883,000 29 1.94 0.50 0.10 0.00 0.09 0.12 0.17 0.29 0.49 

Winter 343,000 27 0.70 0.53 0.06 0.00 0.03 0.11 0.31 0.54 0.76 

Urbanization 

Central City 204,000 8 0.36 * * * * * * * * 

Non-metropolitan 1,075,000 69 2.39 0.30 0.03 0.03 0.09 0.12 0.17 0.21 0.32 

Suburban 638,000 32 0.74 0.75 0.10 0.00 0.08 0.09 0.32 0.68 0.99 

Race 

Black 213,000 9 0.98 * * * * * * * * 

White 1,704,000 100 1.08 0.38 0.03 0.00 0.09 0.11 0.18 0.25 0.49 

Region 

Midwest 588,000 36 1.27 0.43 0.06 0.00 0.00 0.11 0.25 0.31 0.42 

Northeast 68,000 6 0.17 * * * * * * * * 

South 1,261,000 67 1.96 0.47 0.06 0.03 0.10 0.13 0.18 0.25 0.63 

West 0 0 0.00 --------

Response to Questionnaire 

Households who garden 1,610,000 97 2.36 0.45 0.04 0.03 0.09 0.12 0.18 0.29 0.53 

Households who farm 62,000 6 0.85 * * * * * * * * 

0.99 

* 

* 

* 

* 

0.94 

0.87 

1.86 

* 

0.75 

1.53 

0.86 

* 

0.49 

1.71 

* 

0.86 

0.99 

* 

1.10 -

0.94 

* 

1.69 

* 

* 

* 

* 

1.10 

1.71 

1.86 

* 

1.31 

1.71 

0.87 

* 

0.77 

1.86 

* 

0.99 

1.53 

* 

1.71 -

1.71 

* 

1.86 

* 

* 

* 

* 

1.10 

1.91 

1.86 

* 

1.91 

1.86 

1.69 

* 

1.69 

1.86 

* 

1.53 

1.69 

* 

1.86 -

1.86 

* 

1.91 

* 

* 

* 

* 

1.10 

1.91 

1.86 

* 

1.91 

1.86 

1.69 

* 

1.91 

1.86 

* 

1.91 

1.69 

* 

1.91 -

1.91 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-52 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-44. Consumer-Only Intake of Home-Produced Okra (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,696,000 82 0.90 0.39 0.04 0.00 0.05 0.10 0.15 0.30 0.46 

Age 

1 to 2 53,000 2 0.93 * * * * * * * * 

3 to 5 68,000 3 0.84 * * * * * * * * 

6 to 11 218,000 11 1.30 * * * * * * * * 

12 to 19 194,000 9 0.95 * * * * * * * * 

20 to 39 417,000 18 0.68 * * * * * * * * 

40 to 69 587,000 32 1.03 0.40 0.05 0.07 0.11 0.14 0.25 0.31 0.46 

≥ 70 130,000 6 0.82 * * * * * * * * 

Season 

Fall 228,000 9 0.48 * * * * * * * * 

Spring 236,000 24 0.51 0.39 0.06 0.03 0.05 0.07 0.11 0.41 0.60 

Summer 1,144,000 41 2.52 0.39 0.06 0.00 0.05 0.10 0.14 0.30 0.44 

Winter 88,000 8 0.18 * * * * * * * * 

Urbanization 

Central City 204,000 6 0.36 * * * * * * * * 

Non-metropolitan 1,043,000 55 2.32 0.37 0.05 0.00 0.03 0.08 0.15 0.26 0.44 

Suburban 449,000 21 0.52 0.51 0.07 0.07 0.10 0.11 0.31 0.46 0.60 

Race 

Black 236,000 13 1.09 * * * * * * * * 

White 1,419,000 68 0.90 0.43 0.04 0.00 0.07 0.10 0.18 0.33 0.52 

Region 

Midwest 113,000 7 0.24 * * * * * * * * 

Northeast 

South 1,443,000 70 2.24 0.37 0.04 0.00 0.05 0.08 0.14 0.26 0.44 

West 140,000 5 0.39 * * * * * * * * 

Response to Questionnaire 

Households who garden 1,564,000 77 2.29 0.38 0.04 0.00 0.05 0.10 0.15 0.30 0.45 

Households who farm 233,000 14 3.18 * * * * * * * * 

0.78 

* 

* 

* 

* 

* 

0.78 

* 

* 

0.78 

1.15 

* 

* 

0.78 

1.14 

* 

1.14 

* 

0.75 

* 

1.07 

* 

1.21 

* 

* 

* 

* 

* 

1.14 

* 

* 

1.00 

1.53 

* 

* 

1.53 

1.15 

* 

1.21 

* 

1.21 

* 

1.21 

* 

1.53 

* 

* 

* 

* 

* 

1.14 

* 

* 

1.07 

1.53 

* 

* 

1.53 

1.15 

* 

1.53 

* 

1.53 

* 

1.53 

* 

1.53 

* 

* 

* 

* 

* 

1.14 

* 

* 

1.07 

1.53 

* 

* 

1.53 

1.15 

* 

1.53 

* 

1.53 

* 

1.53 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-53
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-45. Consumer-Only Intake of Home-Produced Onions (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 6,718,000 370 3.57 0.30 0.02 0.00 0.01 0.03 0.09 0.21 0.38 

Age 

1 to 2 291,000 17 5.11 * * * * * * * * 

3 to 5 178,000 9 2.20 * * * * * * * * 

6 to 11 530,000 31 3.17 0.30 0.06 0.01 0.01 0.03 0.11 0.23 0.38 

12 to 19 652,000 37 3.18 0.21 0.04 0.01 0.01 0.01 0.06 0.14 0.26 

20 to 39 1,566,000 78 2.54 0.29 0.03 0.01 0.04 0.06 0.09 0.19 0.30 

40 to 69 2,402,000 143 4.23 0.25 0.02 0.00 0.00 0.01 0.08 0.17 0.36 

≥ 70 1,038,000 52 6.54 0.43 0.09 0.00 0.01 0.03 0.14 0.29 0.46 

Season 

Fall 1,557,000 59 3.27 0.38 0.07 0.00 0.03 0.06 0.12 0.26 0.44 

Spring 1,434,000 147 3.11 0.20 0.02 0.00 0.01 0.03 0.06 0.11 0.26 

Summer 2,891,000 101 6.36 0.31 0.03 0.01 0.02 0.04 0.11 0.23 0.38 

Winter 836,000 63 1.72 0.29 0.04 0.00 0.00 0.01 0.03 0.20 0.46 

Urbanization 

Central City 890,000 37 1.58 0.22 0.03 0.00 0.01 0.03 0.07 0.19 0.30 

Non-metropolitan 2,944,000 177 6.54 0.32 0.02 0.01 0.03 0.07 0.14 0.26 0.43 

Suburban 2,884,000 156 3.33 0.29 0.04 0.00 0.01 0.01 0.06 0.13 0.36 

Race 

Black 253,000 16 1.16 * * * * * * * * 

White 6,266,000 345 3.98 0.31 0.02 0.00 0.01 0.03 0.09 0.22 0.39 

Region 

Midwest 2,487,000 143 5.36 0.27 0.02 0.00 0.04 0.06 0.10 0.22 0.34 

Northeast 876,000 52 2.13 0.23 0.04 0.00 0.00 0.01 0.01 0.11 0.35 

South 1,919,000 107 2.98 0.33 0.03 0.00 0.03 0.04 0.15 0.25 0.39 

West 1,436,000 68 3.98 0.33 0.07 0.00 0.01 0.02 0.06 0.15 0.39 

Response to Questionnaire 

Households who garden 6,441,000 356 9.45 0.30 0.02 0.00 0.01 0.03 0.09 0.21 0.38 

Households who farm 1,390,000 81 18.97 0.38 0.04 0.03 0.04 0.05 0.11 0.28 0.52 

0.61 

* 

* 

0.61 

0.57 

0.64 

0.55 

0.56 

0.60 

0.43 

0.69 

0.64 

0.52 

0.63 

0.64 

* 

0.62 

0.56 

0.64 

0.69 

0.55 

0.61 

0.94 

0.91 

* 

* 

1.36 

0.76 

0.94 

0.69 

2.68 

0.78 

0.52 

0.97 

0.92 

0.56 

0.91 

0.97 

* 

0.94 

0.72 

1.05 

1.08 

0.97 

0.92 

1.11 

1.49 

* 

* 

1.36 

0.91 

1.49 

1.11 

3.11 

3.11 

1.41 

1.49 

1.36 

0.56 

1.49 

3.11 

* 

1.77 

1.34 

1.36 

1.49 

3.11 

1.77 

1.49 

3.11 

* 

* 

1.36 

0.91 

1.49 

1.41 

3.11 

3.11 

1.77 

1.49 

1.36 

0.56 

1.77 

3.11 

* 

3.11 

1.34 

1.41 

1.77 

3.11 

3.11 

1.49 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-54 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-46. Consumer-Only Intake of Home-Produced Other Berries (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,626,000 99 0.86 0.48 0.04 0.00 0.05 0.09 0.23 0.38 0.59 

Age 

1 to 2 41,000 2 0.72 * * * * * * * * 

3 to 5 53,000 3 0.65 * * * * * * * * 

6 to 11 106,000 10 0.63 * * * * * * * * 

12 to 19 79,000 5 0.39 * * * * * * * * 

20 to 39 309,000 20 0.50 0.39 0.06 0.08 0.09 0.09 0.13 0.33 0.55 

40 to 69 871,000 51 1.54 0.49 0.06 0.08 0.10 0.13 0.25 0.39 0.61 

≥ 70 159,000 7 1.00 * * * * * * * * 

Season 

Fall 379,000 13 0.80 * * * * * * * * 

Spring 287,000 29 0.62 0.31 0.04 0.05 0.05 0.08 0.18 0.25 0.41 

Summer 502,000 18 1.10 * * * * * * * * 

Winter 458,000 39 0.94 0.54 0.07 0.00 0.10 0.16 0.23 0.39 0.62 

Urbanization 

Central City 378,000 15 0.67 * * * * * * * * 

Non-metropolitan 466,000 37 1.04 0.64 0.09 0.00 0.09 0.10 0.25 0.44 1.02 

Suburban 722,000 45 0.83 0.45 0.05 0.09 0.13 0.16 0.26 0.38 0.54 

Race 

Black 76,000 4 0.35 * * * * * * * * 

White 1,490,000 93 0.95 0.50 0.04 0.05 0.09 0.10 0.25 0.40 0.60 

Region 

Midwest 736,000 56 1.59 0.46 0.06 0.00 0.08 0.09 0.13 0.30 0.59 

Northeast 211,000 11 0.51 * * * * * * * * 

South 204,000 12 0.32 * * * * * * * * 

West 415,000 18 1.15 * * * * * * * * 

Response to Questionnaire 

Households who garden 1,333,000 84 1.96 0.47 0.05 0.01 0.00 0.09 0.20 0.35 0.55 

Households who farm 219,000 16 2.99 * * * * * * * * 

1.07 

* 

* 

* 

* 

0.79 

0.77 

* 

* 

0.54 

* 

1.07 

* 

1.31 

0.59 

* 

1.07 

1.12 

* 

* 

* 

1.07 

* 

1.28 

* 

* 

* 

* 

1.07 

1.28 

* 

* 

0.72 

* 

1.95 

* 

2.21 

0.90 

* 

1.31 

1.28 

* 

* 

* 

1.28 

* 

2.21 

* 

* 

* 

* 

1.07 

2.21 

* 

* 

1.07 

* 

2.08 

* 

2.21 

2.08 

* 

2.21 

2.21 

* 

* 

* 

2.21 

* 

2.21 

* 

* 

* 

* 

1.07 

2.21 

* 

* 

1.07 

* 

2.08 

* 

2.21 

2.08 

* 

2.21 

2.21 

* 

* 

* 

2.21 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-55
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-47. Consumer-Only Intake of Home-Produced Peaches (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,941,000 193 1.56 1.67 0.17 0.05 0.17 0.23 0.47 0.90 1.88 

Age 

1 to 2 103,000 8 1.81 * * * * * * * * 

3 to 5 65,000 6 0.80 * * * * * * * * 

6 to 11 329,000 26 1.97 3.11 0.63 0.10 0.10 0.14 0.63 1.13 6.36 

12 to 19 177,000 13 0.86 * * * * * * * * 

20 to 39 573,000 35 0.93 1.17 0.17 0.05 0.06 0.23 0.47 0.81 1.30 

40 to 69 1,076,000 70 1.90 1.53 0.28 0.06 0.19 0.24 0.56 0.89 1.61 

≥ 70 598,000 33 3.77 1.01 0.20 0.09 0.14 0.18 0.28 0.82 1.19 

Season 

Fall 485,000 19 1.02 * * * * * * * * 

Spring 756,000 91 1.64 1.67 0.30 0.05 0.06 0.10 0.28 0.77 1.45 

Summer 1,081,000 35 2.38 2.26 0.48 0.17 0.23 0.36 0.57 1.12 2.99 

Winter 619,000 48 1.27 1.25 0.10 0.04 0.24 0.56 0.78 1.04 1.71 

Urbanization 

Central City 429,000 12 0.76 * * * * * * * * 

Non-metropolitan 1,110,000 99 2.47 1.87 0.26 0.06 0.26 0.39 0.65 1.02 2.18 

Suburban 1,402,000 82 1.62 1.47 0.18 0.05 0.14 0.20 0.46 0.92 1.87 

Race 

Black 39,000 1 0.18 * * * * * * * * 

White 2,861,000 191 1.82 1.70 0.17 0.05 0.17 0.23 0.50 0.90 1.96 

Region 

Midwest 824,000 75 1.78 1.39 0.29 0.18 0.22 0.26 0.46 0.74 1.19 

Northeast 75,000 5 0.18 * * * * * * * * 

South 852,000 51 1.32 1.67 0.26 0.04 0.14 0.18 0.64 1.02 1.96 

West 1,190,000 62 3.30 1.80 0.33 0.05 0.14 0.23 0.47 0.86 1.94 

Response to Questionnaire 

Households who garden 2,660,000 174 3.90 1.75 0.19 0.05 0.17 0.26 0.53 0.93 1.96 

Households who farm 769,000 54 10.49 1.56 0.25 0.07 0.18 0.23 0.46 0.90 2.02 

3.79 

* 

* 

8.53 

* 

2.92 

2.63 

1.60 

* 

4.44 

6.36 

2.35 

* 

3.86 

3.79 

* 

3.79 

3.06 

* 

3.83 

4.43 

3.79 

2.99 

6.36 

* 

* 

8.53 

* 

2.99 

4.43 

3.79 

* 

6.77 

8.53 

2.60 

* 

6.36 

4.43 

* 

6.36 

3.56 

* 

6.36 

7.37 

6.36 

6.36 

12.30 

* 

* 

11.50 

* 

5.27 

12.30 

7.13 

* 

22.30 

12.30 

3.56 

* 

11.50 

7.37 

* 

12.30 

11.50 

* 

8.53 

12.30 

12.30 

8.53 

22.30 

* 

* 

11.50 

* 

5.27 

12.30 

7.13 

* 

22.30 

12.30 

3.56 

* 

22.30 

7.37 

* 

22.30 

22.30 

* 

8.53 

12.30 

22.30 

8.53 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-56 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-48. Consumer-Only Intake of Home-Produced Pears (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,513,000 94 0.80 0.94 0.10 0.10 0.18 0.24 0.43 0.68 1.09 

Age 

1 to 2 24,000 3 0.42 * * * * * * * * 

3 to 5 45,000 3 0.56 * * * * * * * * 

6 to 11 145,000 10 0.87 * * * * * * * * 

12 to 19 121,000 7 0.59 * * * * * * * * 

20 to 39 365,000 23 0.59 0.62 0.06 0.11 0.32 0.38 0.43 0.50 0.68 

40 to 69 557,000 33 0.98 0.66 0.06 0.10 0.11 0.33 0.42 0.65 0.92 

≥ 70 256,000 15 1.61 * * * * * * * * 

Season 

Fall 308,000 11 0.65 * * * * * * * * 

Spring 355,000 39 0.77 0.69 0.08 0.10 0.11 0.18 0.34 0.60 0.87 

Summer 474,000 16 1.04 * * * * * * * * 

Winter 376,000 28 0.77 1.48 0.28 0.11 0.11 0.38 0.65 0.95 1.38 

Urbanization 

Central City 222,000 11 0.39 * * * * * * * * 

Non-metropolitan 634,000 44 1.41 0.78 0.09 0.33 0.35 0.42 0.44 0.57 0.81 

Suburban 657,000 39 0.76 0.85 0.12 0.10 0.11 0.18 0.39 0.73 1.10 

Race 

Black 51,000 3 0.23 * * * * * * * * 

White 1,462,000 91 0.93 0.97 0.10 0.11 0.24 0.35 0.44 0.70 1.09 

Region 

Midwest 688,000 57 1.48 0.87 0.09 0.22 0.34 0.38 0.44 0.65 1.04 

Northeast 18,000 2 0.04 * * * * * * * * 

South 377,000 13 0.59 * * * * * * * * 

West 430,000 22 1.19 1.14 0.29 0.10 0.11 0.11 0.36 0.75 1.13 

Response to Questionnaire 

Households who garden 1,312,000 85 1.93 0.95 0.10 0.10 0.18 0.35 0.43 0.68 1.09 

Households who farm 528,000 35 7.20 1.09 0.21 0.11 0.22 0.38 0.43 0.61 1.09 

1.60 

* 

* 

* 

* 

1.22 

1.10 

* 

* 

1.15 

* 

4.82 

* 

1.56 

1.50 

* 

1.60 

1.60 

* 

* 

2.76 

1.56 

2.76 

2.76 

* 

* 

* 

* 

1.24 

1.13 

* 

* 

1.83 

* 

5.16 

* 

1.86 

2.57 

* 

2.88 

2.57 

* 

* 

4.82 

2.88 

4.82 

5.16 

* 

* 

* 

* 

1.24 

1.51 

* 

* 

2.54 

* 

5.16 

* 

2.88 

4.79 

* 

5.16 

4.79 

* 

* 

5.16 

5.16 

5.16 

5.16 

* 

* 

* 

* 

1.24 

1.51 

* 

* 

2.54 

* 

5.16 

* 

2.88 

4.79 

* 

5.16 

4.79 

* 

* 

5.16 

5.16 

5.16 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-57
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-49. Consumer-Only Intake of Home-Produced Peas (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 4,252,000 226 2.26 0.51 0.03 0.05 0.10 0.14 0.23 0.32 0.62 

Age 

1 to 2 163,000 9 2.86 * * * * * * * * 

3 to 5 140,000 7 1.73 * * * * * * * * 

6 to 11 515,000 26 3.08 0.61 0.09 0.15 0.15 0.22 0.30 0.39 0.90 

12 to 19 377,000 22 1.84 0.41 0.04 0.06 0.13 0.16 0.24 0.36 0.50 

20 to 39 1,121,000 52 1.82 0.41 0.06 0.10 0.12 0.14 0.18 0.25 0.41 

40 to 69 1,366,000 80 2.41 0.46 0.05 0.07 0.10 0.12 0.23 0.30 0.61 

≥ 70 458,000 26 2.88 0.33 0.06 0.03 0.03 0.05 0.18 0.27 0.37 

Season 

Fall 1,239,000 41 2.60 0.30 0.03 0.03 0.05 0.12 0.21 0.26 0.35 

Spring 765,000 78 1.66 0.44 0.04 0.06 0.11 0.12 0.19 0.33 0.52 

Summer 1,516,000 51 3.33 0.59 0.07 0.07 0.13 0.17 0.22 0.39 0.82 

Winter 732,000 56 1.50 0.75 0.09 0.12 0.18 0.21 0.27 0.54 0.95 

Urbanization 

Central City 558,000 19 0.99 * * * * * * * * 

Non-metropolitan 2,028,000 126 4.50 0.48 0.04 0.08 0.14 0.17 0.25 0.35 0.58 

Suburban 1,666,000 81 1.92 0.51 0.05 0.07 0.12 0.13 0.23 0.39 0.68 

Race 

Black 355,000 19 1.63 * * * * * * * * 

White 3,784,000 203 2.40 0.50 0.03 0.03 0.10 0.13 0.22 0.33 0.60 

Region 

Midwest 1,004,000 55 2.16 0.40 0.07 0.03 0.05 0.10 0.14 0.25 0.35 

Northeast 241,000 14 0.59 * * * * * * * * 

South 2,449,000 132 3.81 0.57 0.04 0.13 0.17 0.20 0.26 0.37 0.68 

West 558,000 25 1.55 0.38 0.06 0.07 0.07 0.10 0.22 0.27 0.48 

Response to Questionnaire 

Households who garden 3,980,000 214 5.84 0.51 0.03 0.03 0.10 0.14 0.23 0.32 0.63 

Households who farm 884,000 55 12.06 0.46 0.06 0.03 0.05 0.09 0.21 0.35 0.52 

1.04 

* 

* 

1.35 

0.71 

0.85 

1.00 

1.00 

0.60 

0.92 

1.35 

1.54 

* 

1.04 

1.00 

* 

1.00 

0.88 

* 

1.24 

0.90 

1.04 

0.90 

1.46 

* 

* 

1.40 

0.82 

1.36 

1.30 

1.00 

0.71 

1.40 

1.60 

2.36 

* 

1.36 

1.30 

* 

1.40 

1.54 

* 

1.60 

0.94 

1.54 

1.40 

2.66 

* 

* 

2.06 

0.82 

2.71 

2.36 

1.46 

1.00 

2.06 

2.66 

2.89 

* 

1.89 

2.28 

* 

2.66 

2.71 

* 

2.66 

1.40 

2.66 

1.60 

2.89 

* 

* 

2.06 

0.82 

2.71 

2.36 

1.46 

1.00 

2.06 

2.66 

2.89 

* 

2.89 

2.36 

* 

2.89 

2.89 

* 

2.66 

1.40 

2.89 

2.89 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-58 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-50. Consumer-Only Intake of Home-Produced Peppers (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 5,153,000 208 2.74 

Age 

1 to 2 163,000 6 2.86 * * * * * * * * 

3 to 5 108,000 5 1.33 * * * * * * * * 

6 to 11 578,000 26 3.46 0.23 0.04 0.00 0.00 0.03 0.09 0.16 0.30 

12 to 19 342,000 16 1.67 * * * * * * * * 

20 to 39 1,048,000 40 1.70 0.22 0.06 0.02 0.03 0.06 0.09 0.12 0.22 

40 to 69 2,221,000 88 3.92 0.25 0.03 0.01 0.03 0.05 0.08 0.17 0.32 

≥ 70 646,000 25 4.07 0.26 0.06 0.02 0.02 0.02 0.07 0.14 0.24 

Season 

Fall 1,726,000 53 3.62 0.20 0.03 0.00 0.03 0.04 0.09 0.17 0.24 

Spring 255,000 28 0.55 0.30 0.07 0.00 0.02 0.04 0.07 0.15 0.32 

Summer 2,672,000 94 5.87 

Winter 500,000 33 1.03 

Urbanization 

Central City 865,000 30 1.53 0.25 0.04 0.04 0.06 0.07 0.11 0.18 0.27 

Non-metropolitan 1,982,000 89 4.40 0.24 0.04 0.01 0.02 0.03 0.07 0.12 0.27 

Suburban 2,246,000 87 2.59 0.25 0.03 0.00 0.03 0.04 0.09 0.16 0.29 

Race 

Black 127,000 6 0.58 * * * * * * * * 

White 4,892,000 198 3.11 0.25 0.02 0.02 0.03 0.04 0.09 0.15 0.29 

Region 

Midwest 1,790,000 74 3.86 0.23 0.04 0.01 0.02 0.03 0.06 0.15 0.26 

Northeast 786,000 31 1.91 

South 1,739,000 72 2.70 0.23 0.03 0.03 0.07 0.08 0.11 0.17 0.27 

West 778,000 29 2.16 0.21 0.05 0.02 0.02 0.03 0.04 0.09 0.25 

Response to Questionnaire 

Households who garden 4,898,000 199 7.19 0.24 0.02 0.00 0.02 0.03 0.08 0.15 0.29 

Households who farm 867,000 35 11.83 0.30 0.08 0.00 0.03 0.03 0.07 0.17 0.36 

* 

* 

0.43 

* 

0.40 

0.48 

0.92 

0.35 

1.09 

0.36 

0.54 

0.49 

* 

0.49 

0.39 

0.43 

0.54 

0.48 

0.60 

* 

* 

0.77 

* 

0.62 

0.74 

0.94 

0.40 

1.20 

0.94 

0.77 

0.97 

* 

0.92 

0.85 

0.53 

0.92 

0.85 

0.85 

* 

* 

0.85 

* 

2.48 

1.50 

1.07 

1.07 

1.53 

1.10 

2.48 

1.50 

* 

1.81 

2.48 

1.81 

1.07 

1.50 

2.48 

* 

* 

0.85 

* 

2.48 

1.50 

1.07 

1.07 

1.53 

1.10 

2.48 

1.53 

* 

2.48 

2.48 

1.81 

1.07 

2.48 

2.48 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-59
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-51. Consumer-Only Intake of Home-Produced Pork (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,732,000 121 0.92 1.23 0.10 0.09 0.14 0.31 0.54 0.90 1.71 

Age 

1 to 2 38,000 5 0.67 * * * * * * * * 

3 to 5 26,000 3 0.32 * * * * * * * * 

6 to 11 129,000 11 0.77 * * * * * * * * 

12 to 19 291,000 20 1.42 1.28 0.24 0.31 0.32 0.34 0.52 0.89 1.75 

20 to 39 511,000 32 0.83 1.21 0.18 0.11 0.28 0.41 0.55 0.79 1.43 

40 to 69 557,000 38 0.98 1.02 0.12 0.12 0.18 0.22 0.41 0.81 1.71 

≥ 70 180,000 12 1.13 * * * * * * * * 

Season 

Fall 362,000 13 0.76 * * * * * * * * 

Spring 547,000 59 1.19 1.13 0.13 0.11 0.14 0.22 0.35 0.90 1.50 

Summer 379,000 15 0.83 * * * * * * * * 

Winter 444,000 34 0.91 1.40 0.24 0.13 0.26 0.38 0.50 0.88 2.21 

Urbanization 

Central City 90,000 2 0.16 * * * * * * * * 

Non-metropolitan 1,178,000 77 2.62 1.39 0.13 0.09 0.22 0.41 0.62 0.97 1.75 

Suburban 464,000 42 0.54 0.88 0.12 0.11 0.12 0.18 0.33 0.59 1.10 

Race 

Black 0 0 0.00 --------

White 1,732,000 121 1.10 1.23 0.10 0.09 0.14 0.31 0.54 0.90 1.71 

Region 

Midwest 844,000 64 1.82 1.06 0.12 0.09 0.12 0.21 0.50 0.67 1.20 

Northeast 97,000 5 0.24 * * * * * * * * 

South 554,000 32 0.86 1.35 0.15 0.18 0.26 0.34 0.81 1.26 1.75 

West 237,000 20 0.66 1.15 0.31 0.13 0.32 0.38 0.44 0.73 1.10 

Response to Questionnaire 

Households who raise animals 1,428,000 100 14.14 1.34 0.10 0.14 0.32 0.41 0.59 0.97 1.75 

Households who farm 1,218,000 82 16.62 1.30 0.11 0.22 0.34 0.41 0.59 0.92 1.71 

2.73 

* 

* 

* 

3.69 

2.90 

1.78 

* 

* 

2.68 

* 

3.08 

* 

3.16 

2.28 -

2.73 

2.68 

* 

2.44 

1.75 

2.90 

3.08 

3.37 

* 

* 

* 

3.69 

3.08 

2.28 

* 

* 

3.68 

* 

4.93 

* 

3.69 

2.73 -

3.37 

3.37 

* 

3.08 

2.73 

3.37 

3.69 

4.93 

* 

* 

* 

4.29 

4.93 

3.16 

* 

* 

4.29 

* 

7.41 

* 

4.93 

2.90 -

4.93 

3.69 

* 

4.29 

7.41 

4.29 

4.93 

7.41 

* 

* 

* 

4.29 

4.93 

3.16 

* 

* 

4.29 

* 

7.41 

* 

7.41 

2.90 -

7.41 

3.73 

* 

4.29 

7.41 

4.93 

4.93 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-60 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-52. Consumer-Only Intake of Home-Produced Poultry (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 1,816,000 105 0.97 1.57 0.12 0.20 0.30 0.42 0.64 1.23 2.19 

Age 

1 to 2 91,000 8 1.60 * * * * * * * * 

3 to 5 70,000 5 0.86 * * * * * * * * 

6 to 11 205,000 12 1.23 * * * * * * * * 

12 to 19 194,000 12 0.95 * * * * * * * * 

20 to 39 574,000 33 0.93 1.17 0.15 0.17 0.40 0.40 0.56 1.15 1.37 

40 to 69 568,000 30 1.00 1.51 0.24 0.20 0.20 0.30 0.49 0.77 2.69 

≥ 70 80,000 3 0.50 * * * * * * * * 

Season 

Fall 562,000 23 1.18 1.52 0.18 0.41 0.42 0.46 0.81 1.39 2.23 

Spring 374,000 34 0.81 1.87 0.28 0.17 0.23 0.30 0.52 1.38 3.29 

Summer 312,000 11 0.69 * * * * * * * * 

Winter 568,000 37 1.17 1.55 0.20 0.20 0.20 0.43 0.60 1.23 2.18 

Urbanization 

Central City 230,000 8 0.41 * * * * * * * * 

Non-metropolitan 997,000 56 2.21 1.48 0.13 0.20 0.28 0.41 0.67 1.19 2.10 

Suburban 589,000 41 0.68 1.94 0.23 0.23 0.27 0.43 0.62 1.59 2.69 

Race 

Black 44,000 2 0.20 * * * * * * * * 

White 1,772,000 103 1.12 1.57 0.12 0.20 0.30 0.42 0.62 1.23 2.19 

Region 

Midwest 765,000 41 1.65 1.60 0.14 0.41 0.42 0.56 0.98 1.39 2.19 

Northeast 64,000 4 0.16 * * * * * * * * 

South 654,000 38 1.02 1.67 0.25 0.17 0.20 0.30 0.46 0.91 2.11 

West 333,000 22 0.92 1.24 0.18 0.27 0.27 0.43 0.56 1.02 1.89 

Response to Questionnaire 

Households who raise animals 1,333,000 81 13.20 1.58 0.12 0.23 0.41 0.47 0.71 1.37 2.19 

Households who farm 917,000 59 12.51 1.54 0.18 0.20 0.23 0.30 0.60 1.06 2.18 

3.17 

* 

* 

* 

* 

1.80 

3.29 

* 

2.69 

4.60 

* 

2.95 

* 

3.17 

4.59 

* 

3.17 

2.70 

* 

4.59 

2.45 

2.93 

3.47 

3.83 

* 

* 

* 

* 

2.93 

4.60 

* 

3.17 

5.15 

* 

3.47 

* 

3.29 

4.83 

* 

3.86 

3.17 

* 

4.83 

2.93 

3.29 

4.83 

5.33 

* 

* 

* 

* 

4.59 

5.15 

* 

3.17 

5.33 

* 

6.17 

* 

3.86 

6.17 

* 

5.33 

3.86 

* 

6.17 

2.93 

5.33 

6.17 

6.17 

* 

* 

* 

* 

4.59 

5.15 

* 

3.17 

5.33 

* 

6.17 

* 

5.33 

6.17 

* 

6.17 

5.33 

* 

6.17 

2.93 

6.17 

6.17 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-61
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-53. Consumer-Only Intake of Home-Produced Pumpkins (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,041,000 87 1.09 0.78 0.07 0.13 0.18 0.24 0.32 0.56 1.07 

Age 

1 to 2 73,000 4 1.28 * * * * * * * * 

3 to 5 18,000 2 0.22 * * * * * * * * 

6 to 11 229,000 9 1.37 * * * * * * * * 

12 to 19 244,000 10 1.19 * * * * * * * * 

20 to 39 657,000 26 1.07 0.80 0.13 0.18 0.18 0.30 0.38 0.48 1.03 

40 to 69 415,000 20 0.73 0.82 0.16 0.29 0.29 0.32 0.37 0.52 0.96 

≥ 70 373,000 15 2.35 * * * * * * * * 

Season 

Fall 1,345,000 49 2.82 0.82 0.09 0.13 0.18 0.28 0.37 0.61 1.17 

Spring 48,000 6 0.10 * * * * * * * * 

Summer 405,000 13 0.89 * * * * * * * * 

Winter 243,000 19 0.50 * * * * * * * * 

Urbanization 

Central City 565,000 20 1.00 0.63 0.11 0.18 0.18 0.24 0.28 0.38 0.94 

Non-metropolitan 863,000 44 1.92 0.64 0.10 0.13 0.17 0.19 0.31 0.51 0.67 

Suburban 613,000 23 0.71 1.10 0.13 0.29 0.29 0.30 0.47 1.04 1.47 

Race 

Black 22,000 1 0.10 * * * * * * * * 

White 2,019,000 86 1.28 0.78 0.07 0.13 0.18 0.24 0.32 0.56 1.10 

Region 

Midwest 1,370,000 54 2.95 0.82 0.10 0.13 0.23 0.24 0.32 0.57 1.04 

Northeast 15,000 1 0.04 * * * * * * * * 

South 179,000 10 0.28 * * * * * * * * 

West 477,000 22 1.32 0.79 0.10 0.18 0.19 0.31 0.37 0.74 1.17 

Response to Questionnaire 

Households who garden 1,987,000 85 2.92 0.77 0.07 0.13 0.18 0.24 0.32 0.56 1.04 

Households who farm 449,000 18 6.13 * * * * * * * * 

1.47 

* 

* 

* 

* 

1.73 

1.47 

* 

1.73 

* 

* 

* 

1.24 

1.22 

1.79 

* 

1.47 

1.73 

* 

* 

1.47 

1.46 

* 

1.79 

* 

* 

* 

* 

2.67 

3.02 

* 

1.79 

* 

* 

* 

1.33 

1.45 

2.67 

* 

1.79 

2.67 

* 

* 

1.51 

1.79 

* 

3.02 

* 

* 

* 

* 

2.67 

3.02 

* 

3.02 

* 

* 

* 

2.24 

4.48 

2.67 

* 

3.02 

3.02 

* 

* 

1.51 

3.02 

* 

4.48 

* 

* 

* 

* 

2.67 

3.02 

* 

3.02 

* 

* 

* 

2.24 

4.48 

2.67 

* 

4.48 

4.48 

* 

* 

1.51 

4.48 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-62 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-54. Consumer-Only Intake of Home-Produced Snap Beans (g/kg-day) 

Population Nc Nc % 

Group wgtd Unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 12,308,000 739 6.55 0.80 0.03 0.06 0.15 0.19 0.34 0.57 1.04 

Age 

1 to 2 246,000 17 4.32 * * * * * * * * 

3 to 5 455,000 32 5.62 1.49 0.24 0.00 0.00 0.35 0.90 1.16 1.66 

6 to 11 862,000 62 5.16 0.90 0.12 0.00 0.20 0.22 0.32 0.64 1.21 

12 to 19 1,151,000 69 5.62 0.64 0.06 0.00 0.16 0.22 0.32 0.50 0.81 

20 to 39 2,677,000 160 4.35 0.61 0.04 0.07 0.13 0.16 0.26 0.50 0.79 

40 to 69 4,987,000 292 8.79 0.72 0.03 0.10 0.16 0.23 0.36 0.56 0.86 

≥ 70 1,801,000 100 11.34 0.92 0.12 0.06 0.07 0.15 0.37 0.64 1.22 

Season 

Fall 3,813,000 137 8.00 0.81 0.08 0.06 0.15 0.18 0.27 0.54 1.18 

Spring 2,706,000 288 5.86 0.90 0.05 0.03 0.15 0.22 0.37 0.59 1.11 

Summer 2,946,000 98 6.48 0.63 0.05 0.00 0.12 0.16 0.33 0.50 0.85 

Winter 2,843,000 216 5.84 0.86 0.05 0.11 0.18 0.24 0.42 0.62 1.12 

Urbanization 

Central City 2,205,000 78 3.91 0.60 0.06 0.06 0.07 0.16 0.26 0.51 0.71 

Non-metropolitan 5,696,000 404 12.65 0.96 0.05 0.09 0.18 0.23 0.37 0.68 1.19 

Suburban 4,347,000 255 5.02 0.70 0.04 0.10 0.14 0.19 0.34 0.52 0.93 

Race 

Black 634,000 36 2.92 0.76 0.14 0.25 0.25 0.28 0.30 0.48 1.04 

White 11,519,000 694 7.31 0.81 0.03 0.07 0.15 0.19 0.35 0.57 1.06 

Region 

Midwest 4,651,000 307 10.02 0.86 0.06 0.07 0.15 0.19 0.34 0.55 0.99 

Northeast 990,000 52 2.40 0.57 0.07 0.00 0.10 0.11 0.18 0.49 0.82 

South 4,755,000 286 7.39 0.88 0.04 0.13 0.21 0.25 0.40 0.68 1.22 

West 1,852,000 92 5.14 0.59 0.04 0.07 0.14 0.18 0.27 0.51 0.74 

Response to Questionnaire 

Households who garden 11,843,000 700 17.38 0.79 0.03 0.06 0.15 0.19 0.33 0.56 1.02 

Households who farm 2,591,000 157 35.35 0.80 0.05 0.06 0.13 0.19 0.41 0.66 1.12 

1.58 

* 

3.20 

1.79 

1.34 

1.24 

1.45 

1.70 

1.52 

1.72 

1.30 

1.72 

1.23 

1.89 

1.36 

1.30 

1.63 

1.70 

1.28 

1.72 

1.20 

1.60 

1.54 

2.01 

* 

4.88 

2.75 

1.79 

1.64 

1.77 

2.01 

2.01 

2.85 

1.70 

2.02 

1.54 

2.70 

1.77 

1.34 

2.01 

2.47 

1.36 

2.01 

1.52 

2.01 

1.98 

3.90 

* 

6.90 

4.81 

2.72 

2.05 

2.70 

9.96 

4.82 

5.66 

2.05 

3.85 

1.93 

4.88 

2.98 

5.98 

3.90 

4.88 

1.97 

3.23 

2.19 

3.85 

2.96 

9.96 

* 

6.90 

5.66 

2.72 

4.26 

4.23 

9.96 

9.96 

6.90 

2.63 

7.88 

3.35 

9.96 

6.08 

5.98 

9.96 

9.96 

3.09 

5.98 

2.19 

9.96 

4.23 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-63
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-55. Consumer-Only Intake of Home-Produced Strawberries (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,057,000 139 1.09 0.65 0.05 0.04 0.08 0.12 0.26 0.47 0.82 1.47 

Age 

1 to 2 30,000 2 0.53 * * * * * * * * * 

3 to 5 66,000 6 0.81 * * * * * * * * * 

6 to 11 153,000 15 0.92 * * * * * * * * * 

12 to 19 201,000 11 0.98 * * * * * * * * * 

20 to 39 316,000 22 0.51 0.32 0.06 0.08 0.08 0.11 0.12 0.21 0.46 0.82 

40 to 69 833,000 55 1.47 0.64 0.06 0.02 0.07 0.18 0.36 0.58 0.94 1.42 

≥ 70 449,000 27 2.83 0.64 0.11 0.04 0.04 0.09 0.26 0.47 0.70 1.66 

Season 

Fall 250,000 8 0.52 * * * * * * * * * 

Spring 598,000 66 1.30 0.83 0.10 0.08 0.09 0.18 0.28 0.47 0.97 1.93 

Summer 388,000 11 0.85 * * * * * * * * * 

Winter 821,000 54 1.69 0.51 0.06 0.02 0.04 0.11 0.21 0.39 0.60 1.27 

Urbanization 

Central City 505,000 23 0.90 0.75 0.12 0.04 0.04 0.09 0.38 0.49 1.33 1.47 

Non-metropolitan 664,000 52 1.47 0.62 0.11 0.02 0.07 0.08 0.13 0.39 0.81 1.66 

Suburban 888,000 64 1.03 0.62 0.06 0.08 0.18 0.22 0.35 0.53 0.70 1.27 

Race 

Black 0 0 0.00 ---------

White 2,057,000 139 1.31 0.65 0.05 0.04 0.08 0.12 0.26 0.47 0.82 1.47 

Region 

Midwest 1,123,000 76 2.42 0.69 0.08 0.02 0.07 0.08 0.18 0.42 1.00 1.66 

Northeast 382,000 25 0.93 0.64 0.10 0.09 0.16 0.18 0.26 0.47 0.87 1.46 

South 333,000 23 0.52 0.67 0.08 0.13 0.21 0.38 0.52 0.62 0.70 1.00 

West 219,000 15 0.61 * * * * * * * * * 

Response to Questionnaire 

Households who garden 1,843,000 123 2.70 0.64 0.05 0.04 0.08 0.12 0.23 0.45 0.82 1.46 

Households who farm 87,000 9 1.19 * * * * * * * * * 

1.77 

* 

* 

* 

* 

0.97 

1.47 

1.89 

* 

2.54 

* 

1.46 

1.69 

2.16 

1.56 -

1.77 

1.93 

1.83 

1.00 

* 

1.77 

* 

2.72 

* 

* 

* 

* 

1.56 

2.37 

2.72 

* 

4.83 

* 

2.37 

2.37 

4.83 

2.97 -

2.72 

2.97 

2.16 

2.72 

* 

2.54 

* 

4.83 

* 

* 

* 

* 

1.56 

2.37 

2.72 

* 

4.83 

* 

2.37 

2.37 

4.83 

2.97 -

4.83 

4.83 

2.16 

2.72 

* 

4.83 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. - Indicates data are not available. 

SE = Sandard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-64 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-56. Consumer-Only Intake of Home-Produced Tomatoes (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 16,737,000 743 8.90 1.18 0.05 0.08 0.15 0.23 0.39 0.74 1.46 

Age 

1 to 2 572,000 26 10.04 3.14 0.53 0.73 0.86 0.93 1.23 1.66 4.00 

3 to 5 516,000 26 6.37 1.61 0.27 0.50 0.51 0.51 0.75 1.25 1.65 

6 to 11 1,093,000 51 6.54 1.63 0.27 0.22 0.31 0.39 0.53 0.76 1.66 

12 to 19 1,411,000 61 6.89 0.72 0.09 0.00 0.00 0.18 0.27 0.52 0.85 

20 to 39 4,169,000 175 6.77 0.85 0.10 0.07 0.13 0.15 0.25 0.52 1.00 

40 to 69 6,758,000 305 11.92 1.05 0.05 0.11 0.17 0.28 0.40 0.75 1.41 

≥ 70 1,989,000 89 12.53 1.26 0.09 0.11 0.24 0.30 0.48 1.14 1.77 

Season 

Fall 5,516,000 201 11.57 1.02 0.09 0.07 0.14 0.22 0.34 0.60 1.34 

Spring 1,264,000 127 2.74 0.84 0.06 0.14 0.19 0.24 0.37 0.63 1.11 

Summer 8,122,000 279 17.86 1.30 0.09 0.11 0.17 0.24 0.41 0.80 1.55 

Winter 1,835,000 136 3.77 1.37 0.18 0.09 0.21 0.29 0.50 0.83 1.49 

Urbanization 

Central City 2,680,000 90 4.76 1.10 0.13 0.00 0.15 0.23 0.35 0.75 1.51 

Non-metropolitan 7,389,000 378 16.41 1.26 0.07 0.11 0.22 0.26 0.42 0.76 1.47 

Suburban 6,668,000 275 7.70 1.13 0.09 0.08 0.14 0.18 0.37 0.67 1.38 

Race 

Black 743,000 28 3.42 0.61 0.09 0.00 0.00 0.07 0.24 0.51 0.90 

White 15,658,000 703 9.94 1.22 0.06 0.11 0.17 0.24 0.41 0.76 1.49 

Region 

Midwest 6,747,000 322 14.54 1.18 0.09 0.06 0.15 0.21 0.36 0.68 1.41 

Northeast 2,480,000 87 6.02 1.17 0.16 0.08 0.14 0.15 0.35 0.75 1.38 

South 4,358,000 202 6.77 1.15 0.09 0.00 0.21 0.25 0.42 0.75 1.43 

West 3,152,000 132 8.74 1.23 0.10 0.18 0.24 0.28 0.41 0.77 1.84 

Response to Questionnaire 

Households who garden 14,791,000 661 21.70 1.21 0.06 0.08 0.15 0.23 0.41 0.76 1.50 

Households who farm 2,269,000 112 30.96 1.42 0.16 0.00 0.18 0.23 0.42 0.77 1.86 

2.50 

7.26 

3.00 

5.20 

1.67 

1.83 

2.40 

2.51 

2.24 

1.75 

3.05 

2.48 

2.16 

2.77 

2.35 

1.18 

2.55 

2.51 

2.44 

2.32 

2.78 

2.51 

3.55 

3.54 

10.70 

6.25 

5.70 

1.94 

2.10 

3.05 

2.99 

2.87 

2.00 

4.05 

3.38 

2.95 

3.85 

3.32 

1.55 

3.59 

3.69 

3.52 

3.67 

3.08 

3.52 

5.20 

7.26 

10.70 

6.25 

9.14 

3.39 

5.52 

4.50 

3.67 

6.25 

3.79 

7.26 

8.29 

7.26 

6.87 

5.52 

1.66 

7.26 

6.87 

10.90 

6.82 

7.26 

7.26 

9.14 

19.30 

10.70 

6.25 

9.14 

3.39 

19.30 

5.00 

3.67 

10.70 

5.28 

10.90 

19.30 

8.29 

10.70 

19.30 

1.66 

19.30 

19.30 

10.90 

9.14 

7.26 

19.30 

9.14 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-65
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-57. Consumer-Only Intake of Home-Produced White Potatoes (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 5,895,000 281 3.14 1.66 0.11 0.00 0.19 0.31 0.55 1.27 2.07 

Age 

1 to 2 147,000 10 2.58 * * * * * * * * 

3 to 5 119,000 6 1.47 * * * * * * * * 

6 to 11 431,000 24 2.58 2.19 0.39 0.00 0.00 0.41 0.72 1.76 3.10 

12 to 19 751,000 31 3.67 1.26 0.19 0.07 0.19 0.26 0.38 1.22 1.80 

20 to 39 1,501,000 66 2.44 1.24 0.12 0.16 0.16 0.20 0.48 1.00 1.62 

40 to 69 1,855,000 95 3.27 1.86 0.23 0.13 0.26 0.35 0.70 1.31 2.04 

≥ 70 1,021,000 45 6.43 1.27 0.12 0.21 0.22 0.36 0.55 1.21 1.69 

Season 

Fall 2,267,000 86 4.76 1.63 0.22 0.16 0.22 0.27 0.46 1.13 1.79 

Spring 527,000 58 1.14 1.23 0.13 0.07 0.11 0.20 0.41 0.86 1.91 

Summer 2,403,000 81 5.28 1.63 0.18 0.00 0.19 0.32 0.62 1.32 2.09 

Winter 698,000 56 1.43 2.17 0.20 0.14 0.40 0.50 0.86 2.02 2.95 

Urbanization 

Central City 679,000 25 1.20 0.96 0.15 0.16 0.16 0.18 0.38 0.56 1.52 

Non-metropolitan 3,046,000 159 6.77 1.96 0.16 0.18 0.27 0.37 0.77 1.50 2.38 

Suburban 2,110,000 95 2.44 1.49 0.17 0.11 0.19 0.32 0.54 0.93 1.68 

Race 

Black 140,000 5 0.64 * * * * * * * * 

White 5,550,000 269 3.52 1.67 0.11 0.14 0.21 0.31 0.55 1.28 2.09 

Region 

Midwest 2,587,000 133 5.58 1.77 0.15 0.18 0.24 0.34 0.64 1.35 2.15 

Northeast 656,000 31 1.59 1.28 0.20 0.07 0.13 0.17 0.35 0.86 1.97 

South 1,796,000 84 2.79 2.08 0.24 0.16 0.35 0.46 0.92 1.56 2.40 

West 796,000 31 2.21 0.76 0.11 0.16 0.22 0.26 0.41 0.54 0.96 

Response to Questionnaire 

Households who garden 5,291,000 250 7.76 1.65 0.11 0.00 0.21 0.31 0.56 1.28 2.09 

Households who farm 1,082,000 62 14.76 1.83 0.18 0.07 0.21 0.58 0.92 1.46 2.31 

3.11 

* 

* 

5.94 

2.95 

2.54 

3.43 

2.35 

3.43 

2.86 

3.08 

4.26 

2.07 

3.55 

3.11 

* 

3.11 

3.77 

2.95 

3.44 

1.40 

3.10 

3.80 

4.76 

* 

* 

6.52 

3.11 

3.08 

5.29 

2.88 

4.14 

3.08 

5.29 

5.40 

2.25 

5.64 

4.76 

* 

4.76 

5.29 

3.80 

5.64 

1.95 

4.28 

5.09 

9.52 

* 

* 

6.52 

4.14 

4.29 

12.80 

3.92 

12.80 

4.28 

9.43 

6.00 

2.54 

12.80 

9.43 

* 

9.52 

9.43 

5.09 

12.80 

3.11 

9.52 

6.52 

12.80 

* 

* 

6.52 

4.14 

5.09 

12.80 

3.92 

12.80 

4.28 

9.43 

6.00 

2.54 

12.80 

9.43 

* 

12.80 

9.43 

5.09 

12.80 

3.11 

12.80 

6.52 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-66 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-58. Consumer-Only Intake of Home-Produced Exposed Fruit (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 11,770,000 679 6.26 1.49 0.08 0.04 0.14 0.26 0.45 0.83 1.70 

Age 

1 to 2 306,000 19 5.37 * * * * * * * * 

3 to 5 470,000 30 5.80 2.60 0.78 0.00 0.00 0.37 1.00 1.82 2.64 

6 to 11 915,000 68 5.48 2.52 0.42 0.00 0.17 0.37 0.62 1.11 2.91 

12 to 19 896,000 50 4.37 1.33 0.21 0.08 0.12 0.26 0.40 0.61 2.27 

20 to 39 2,521,000 139 4.09 1.09 0.14 0.08 0.13 0.17 0.30 0.62 1.07 

40 to 69 4,272,000 247 7.53 1.25 0.11 0.06 0.16 0.25 0.44 0.72 1.40 

≥ 70 2,285,000 118 14.39 1.39 0.12 0.04 0.21 0.28 0.57 0.96 1.66 

Season 

Fall 2,877,000 100 6.04 1.37 0.12 0.26 0.29 0.34 0.54 1.03 1.88 

Spring 2,466,000 265 5.34 1.49 0.15 0.09 0.20 0.25 0.43 0.86 1.65 

Summer 3,588,000 122 7.89 1.75 0.25 0.00 0.09 0.13 0.39 0.64 1.76 

Winter 2,839,000 192 5.83 1.27 0.11 0.04 0.10 0.23 0.46 0.83 1.55 

Urbanization 

Central City 2,552,000 99 4.53 1.34 0.20 0.04 0.10 0.26 0.45 0.86 1.60 

Non-metropolitan 3,891,000 269 8.64 1.78 0.17 0.06 0.10 0.17 0.42 0.94 1.94 

Suburban 5,267,000 309 6.08 1.36 0.09 0.09 0.21 0.29 0.47 0.77 1.65 

Race 

Black 250,000 12 1.15 * * * * * * * * 

White 11,411,000 663 7.24 1.51 0.08 0.06 0.16 0.26 0.45 0.86 1.72 

Region 

Midwest 4,429,000 293 9.55 1.60 0.14 0.04 0.13 0.22 0.42 0.88 1.88 

Northeast 1,219,000 69 2.96 0.76 0.12 0.08 0.09 0.17 0.30 0.47 0.78 

South 2,532,000 141 3.94 1.51 0.18 0.08 0.23 0.30 0.51 0.92 1.63 

West 3,530,000 174 9.79 1.60 0.14 0.10 0.24 0.32 0.57 0.96 1.97 

Response to Questionnaire 

Households who garden 10,197,000 596 14.96 1.55 0.09 0.04 0.16 0.26 0.45 0.88 1.73 

Households who farm 1,917,000 112 26.16 2.32 0.25 0.07 0.28 0.37 0.68 1.30 3.14 

3.16 

* 

5.41 

6.98 

3.41 

2.00 

2.61 

3.73 

2.88 

2.91 

4.29 

2.61 

2.37 

4.07 

3.16 

* 

3.31 

3.58 

1.39 

2.63 

3.72 

3.41 

5.00 

4.78 

* 

6.07 

11.70 

4.78 

3.58 

3.25 

4.42 

4.25 

4.67 

6.12 

4.66 

2.88 

5.98 

4.67 

* 

4.78 

4.78 

2.86 

5.98 

5.00 

5.00 

6.12 

12.00 

* 

32.50 

15.70 

5.90 

12.90 

13.00 

5.39 

5.41 

8.27 

13.00 

8.16 

13.00 

15.70 

7.29 

* 

12.00 

12.00 

5.21 

15.70 

13.00 

12.90 

15.70 

32.50 

* 

32.50 

15.90 

5.90 

12.90 

13.00 

7.13 

5.41 

32.50 

15.70 

11.30 

13.00 

32.50 

12.90 

* 

32.50 

32.50 

7.13 

15.70 

13.00 

32.50 

15.70 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-67
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-59. Consumer-Only Intake of Home-Produced Protected Fruits (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 3,855,000 173 2.05 5.74 0.63 0.15 0.27 0.34 0.93 2.34 7.45 16.00 

Age 

1 to 2 79,000 5 1.39 * * * * * * * * * 

3 to 5 80,000 4 0.99 * * * * * * * * * 

6 to 11 181,000 9 1.08 * * * * * * * * * 

12 to 19 377,000 20 1.84 2.96 0.99 0.12 0.16 0.28 0.39 1.23 2.84 7.44 

20 to 39 755,000 29 1.23 4.51 1.08 0.18 0.36 0.49 1.22 1.88 4.47 14.60 

40 to 69 1,702,000 77 3.00 5.65 0.87 0.11 0.24 0.29 0.67 2.22 9.36 15.50 

≥ 70 601,000 26 3.78 4.44 0.69 0.26 0.26 0.29 1.95 3.29 7.06 8.97 

Season 

Fall 394,000 12 0.83 * * * * * * * * * 

Spring 497,000 36 1.08 2.08 0.35 0.16 0.18 0.26 0.38 1.22 4.08 5.10 

Summer 1,425,000 47 3.13 7.39 1.45 0.11 0.27 0.39 1.25 3.06 10.30 16.60 

Winter 1,539,000 78 3.16 6.24 0.91 0.15 0.30 0.38 1.39 2.65 8.23 17.80 

Urbanization 

Central City 1,312,000 50 2.33 3.94 0.58 0.15 0.26 0.33 0.83 3.01 5.01 9.23 

Non-metropolitan 506,000 19 1.12 * * * * * * * * * 

Suburban 2,037,000 104 2.35 6.83 0.94 0.11 0.25 0.29 0.59 2.01 10.30 17.90 

Race 

Black 200,000 8 0.92 * * * * * * * * * 

White 3,655,000 165 2.32 5.91 0.65 0.12 0.26 0.33 1.06 2.44 7.46 16.00 

Region 

Midwest 657,000 24 1.42 10.70 2.60 0.25 0.26 0.29 1.18 7.44 14.60 24.10 

Northeast 105,000 5 0.26 * * * * * * * * * 

South 1,805,000 74 2.81 4.77 0.65 0.16 0.36 0.45 1.23 2.54 5.10 15.20 

West 1,288,000 70 3.57 4.85 0.93 0.11 0.18 0.27 0.49 1.84 5.34 12.30 

Response to Questionnaire 

Households who garden 3,360,000 146 4.93 5.90 0.70 0.12 0.27 0.34 1.16 2.42 7.46 16.00 

Households who farm 357,000 14 4.87 * * * * * * * * * 

19.70 

* 

* 

* 

11.40 

16.10 

21.20 

9.97 

* 

6.57 

24.10 

21.20 

9.97 

* 

23.80 

* 

21.20 

41.30 

* 

16.60 

18.80 

19.10 

* 

47.30 

* 

* 

* 

19.10 

24.10 

41.30 

15.20 

* 

6.79 

53.60 

47.30 

18.80 

* 

53.60 

* 

47.30 

53.60 

* 

23.80 

47.30 

47.30 

* 

53.60 

* 

* 

* 

19.10 

24.10 

41.30 

15.20 

* 

6.79 

53.60 

47.30 

18.80 

* 

53.60 

* 

53.60 

53.60 

* 

24.00 

47.30 

53.60 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-68 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-60. Consumer-Only Intake of Home-Produced Exposed Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 28,762,000 1,511 15.30 1.52 0.05 0.00 0.09 0.17 0.40 0.86 1.83 3.55 

Age 

1 to 2 815,000 43 14.30 3.48 0.51 0.02 0.24 0.83 1.20 1.89 4.23 10.70 

3 to 5 1,069,000 62 13.19 1.74 0.22 0.00 0.01 0.05 0.58 1.16 2.53 3.47 

6 to 11 2,454,000 134 14.68 1.39 0.18 0.00 0.04 0.09 0.31 0.64 1.60 3.22 

12 to 19 2,611,000 143 12.74 1.07 0.09 0.00 0.03 0.14 0.30 0.66 1.46 2.35 

20 to 39 6,969,000 348 11.31 1.05 0.08 0.01 0.07 0.12 0.26 0.56 1.26 2.33 

40 to 69 10,993,000 579 19.38 1.60 0.08 0.00 0.14 0.24 0.48 0.98 1.92 3.59 

≥ 70 3,517,000 185 22.15 1.68 0.12 0.01 0.15 0.24 0.52 1.13 2.38 4.08 

Season 

Fall 8,865,000 314 18.60 1.31 0.10 0.05 0.11 0.18 0.33 0.65 1.56 3.13 

Spring 4,863,000 487 10.54 1.14 0.06 0.00 0.05 0.15 0.34 0.66 1.39 2.76 

Summer 10,151,000 348 22.32 2.03 0.13 0.00 0.11 0.20 0.61 1.30 2.52 4.32 

Winter 4,883,000 362 10.02 1.21 0.10 0.00 0.02 0.14 0.37 0.67 1.42 2.76 

Urbanization 

Central City 4,859,000 173 8.62 1.11 0.10 0.01 0.06 0.08 0.28 0.70 1.43 2.49 

Non-metropolitan 11,577,000 711 25.71 1.87 0.09 0.02 0.17 0.25 0.50 1.16 2.20 4.12 

Suburban 12,266,000 625 14.17 1.35 0.07 0.00 0.10 0.16 0.36 0.74 1.58 3.22 

Race 

Black 1,713,000 100 7.88 1.23 0.13 0.00 0.08 0.14 0.35 0.89 1.51 3.32 

White 26,551,000 1,386 16.85 1.53 0.05 0.00 0.10 0.18 0.40 0.86 1.82 3.48 

Region 

Midwest 10,402,000 570 22.42 1.48 0.09 0.01 0.07 0.16 0.39 0.81 1.69 3.55 

Northeast 4,050,000 191 9.84 1.65 0.18 0.00 0.08 0.14 0.26 0.67 1.75 5.58 

South 9,238,000 503 14.36 1.55 0.08 0.05 0.16 0.26 0.52 1.00 1.92 3.19 

West 5,012,000 245 13.90 1.43 0.10 0.00 0.03 0.15 0.39 0.76 2.13 3.45 

Response to Questionnaire 

Households who garden 25,737,000 1,361 37.76 1.57 0.06 0.00 0.09 0.17 0.41 0.89 1.97 3.63 

Households who farm 3,596,000 207 49.07 2.17 0.16 0.00 0.18 0.37 0.65 1.38 2.81 6.01 

5.12 

11.90 

6.29 

5.47 

3.78 

3.32 

5.22 

4.96 

4.45 

4.02 

6.35 

3.69 

3.29 

6.10 

5.22 

3.92 

5.12 

4.67 

6.80 

4.52 

4.84 

5.45 

6.83 

10.30 

12.10 

7.36 

13.30 

5.67 

7.57 

8.99 

6.96 

8.92 

7.51 

12.70 

8.86 

8.34 

12.20 

8.61 

5.55 

10.30 

11.90 

12.70 

9.92 

7.51 

10.30 

10.30 

20.60 

12.10 

8.86 

13.30 

5.67 

20.60 

19.00 

10.20 

12.20 

10.70 

19.00 

20.60 

12.10 

19.00 

20.60 

7.19 

20.60 

20.60 

14.90 

13.30 

8.34 

20.60 

13.30 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-69
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-61. Consumer-Only Intake of Home-Produced Protected Vegetables (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 11,428,000 656 6.08 1.01 0.05 0.10 0.15 0.19 0.32 0.63 1.20 2.24 

Age 

1 to 2 348,000 21 6.11 2.46 0.49 0.32 0.32 0.54 1.36 1.94 2.96 3.88 

3 to 5 440,000 32 5.43 1.30 0.21 0.23 0.23 0.32 0.48 1.04 1.48 2.51 

6 to 11 1,052,000 63 6.30 1.10 0.13 0.19 0.21 0.32 0.39 0.79 1.31 2.14 

12 to 19 910,000 51 4.44 0.78 0.09 0.06 0.16 0.24 0.35 0.58 0.82 1.85 

20 to 39 3,227,000 164 5.24 0.76 0.06 0.11 0.15 0.17 0.24 0.51 0.97 1.73 

40 to 69 3,818,000 226 6.73 0.93 0.07 0.07 0.14 0.17 0.32 0.60 1.11 1.87 

≥ 70 1,442,000 89 9.08 1.05 0.16 0.12 0.21 0.24 0.36 0.57 1.21 1.86 

Season 

Fall 3,907,000 143 8.20 0.85 0.07 0.12 0.16 0.20 0.32 0.57 1.10 1.73 

Spring 2,086,000 236 4.52 0.70 0.04 0.06 0.14 0.17 0.27 0.49 0.91 1.44 

Summer 3,559,000 118 7.82 1.40 0.16 0.10 0.18 0.23 0.38 0.78 1.69 3.05 

Winter 1,876,000 159 3.85 0.93 0.08 0.12 0.14 0.18 0.31 0.60 1.20 2.32 

Urbanization 

Central City 1,342,000 49 2.38 1.00 0.15 0.12 0.15 0.17 0.32 0.72 1.18 2.36 

Non-metropolitan 5,934,000 391 13.18 1.07 0.06 0.11 0.17 0.21 0.35 0.65 1.30 2.51 

Suburban 4,152,000 216 4.80 0.93 0.08 0.07 0.15 0.19 0.29 0.56 1.15 1.85 

Race 

Black 479,000 27 2.20 1.50 0.23 0.16 0.26 0.33 0.87 0.94 2.20 3.05 

White 10,836,000 625 6.88 0.99 0.05 0.10 0.15 0.19 0.32 0.61 1.20 2.17 

Region 

Midwest 4,359,000 273 9.40 1.01 0.07 0.11 0.17 0.23 0.33 0.57 1.08 2.45 

Northeast 807,000 48 1.96 0.70 0.09 0.06 0.15 0.17 0.27 0.51 0.99 1.71 

South 4,449,000 253 6.92 1.08 0.07 0.13 0.17 0.21 0.38 0.71 1.38 2.32 

West 1,813,000 82 5.03 0.96 0.16 0.07 0.12 0.15 0.21 0.48 1.01 1.86 

Response to Questionnaire 

Households who garden 10,286,000 602 15.09 1.01 0.05 0.10 0.15 0.19 0.34 0.64 1.21 2.32 

Households who farm 2,325,000 142 31.72 1.30 0.15 0.09 0.17 0.21 0.34 0.60 1.40 3.55 

3.05 

9.42 

5.10 

3.12 

2.20 

2.51 

3.04 

3.05 

2.51 

1.86 

5.40 

3.06 

2.83 

3.55 

2.67 

3.23 

3.04 

3.68 

2.33 

3.05 

3.12 

3.05 

5.40 

6.49 

9.42 

5.31 

5.40 

2.69 

3.63 

6.84 

9.23 

4.78 

3.74 

9.23 

4.76 

4.78 

6.84 

6.49 

4.95 

6.49 

6.84 

2.77 

5.40 

9.23 

6.49 

9.23 

9.42 

9.42 

5.31 

5.40 

2.69 

4.76 

7.44 

9.23 

5.31 

5.73 

9.42 

6.39 

4.78 

9.42 

9.23 

4.95 

9.42 

7.44 

2.77 

9.42 

9.23 

9.23 

9.23 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-70 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-62. Consumer-Only Intake of Home-Produced Root Vegetables (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 13,750,000 743 7.31 1.16 0.06 0.00 0.04 0.11 0.25 0.67 1.47 

Age 

1 to 2 371,000 22 6.51 2.52 0.61 0.17 0.17 0.22 0.36 0.92 3.67 

3 to 5 390,000 23 4.81 1.28 0.32 0.00 0.00 0.12 0.23 0.46 1.68 

6 to 11 1,106,000 67 6.62 1.32 0.21 0.00 0.01 0.04 0.23 0.52 1.63 

12 to 19 1,465,000 76 7.15 0.94 0.12 0.01 0.01 0.07 0.27 0.57 1.37 

20 to 39 3,252,000 164 5.28 0.87 0.07 0.01 0.05 0.10 0.20 0.56 1.24 

40 to 69 4,903,000 276 8.64 1.13 0.10 0.00 0.03 0.12 0.25 0.68 1.27 

≥ 70 2,096,000 107 13.20 1.22 0.10 0.02 0.03 0.17 0.38 0.85 1.71 

Season 

Fall 4,026,000 153 8.45 1.42 0.15 0.05 0.14 0.17 0.31 0.92 1.67 

Spring 2,552,000 260 5.53 0.69 0.06 0.00 0.02 0.03 0.14 0.37 0.77 

Summer 5,011,000 169 11.02 1.19 0.12 0.00 0.05 0.13 0.28 0.73 1.51 

Winter 2,161,000 161 4.44 1.17 0.12 0.00 0.01 0.04 0.24 0.56 1.56 

Urbanization 

Central City 2,385,000 96 4.23 0.75 0.08 0.03 0.04 0.14 0.22 0.43 0.92 

Non-metropolitan 6,094,000 366 13.54 1.43 0.10 0.01 0.07 0.13 0.28 0.76 1.85 

Suburban 5,211,000 279 6.02 1.06 0.09 0.00 0.01 0.07 0.23 0.73 1.19 

Race 

Black 521,000 31 2.40 0.88 0.39 0.00 0.01 0.04 0.09 0.54 0.77 

White 12,861,000 697 8.16 1.18 0.06 0.01 0.05 0.13 0.26 0.68 1.50 

Region 

Midwest 5,572,000 314 12.01 1.31 0.10 0.03 0.07 0.17 0.27 0.74 1.67 

Northeast 1,721,000 92 4.18 0.84 0.10 0.00 0.01 0.01 0.14 0.48 1.18 

South 3,842,000 205 5.97 1.38 0.14 0.01 0.05 0.13 0.28 0.69 1.70 

West 2,555,000 130 7.08 0.77 0.06 0.00 0.02 0.11 0.24 0.57 0.98 

Response to Questionnaire 

Households who garden 12,578,000 682 18.46 1.15 0.06 0.00 0.04 0.12 0.26 0.67 1.50 

Households who farm 2,367,000 136 32.30 1.39 0.13 0.11 0.16 0.18 0.37 0.88 1.85 

2.81 

7.25 

4.26 

3.83 

2.26 

2.11 

2.74 

2.86 

3.26 

1.69 

2.74 

3.08 

1.91 

3.32 

2.34 

1.06 

2.82 

3.23 

2.05 

3.32 

1.69 

2.81 

3.11 

3.71 

10.40 

4.73 

5.59 

3.32 

3.08 

3.56 

3.21 

3.85 

2.80 

3.64 

4.14 

2.70 

4.24 

3.26 

1.25 

3.72 

4.26 

2.77 

3.83 

2.45 

3.64 

4.58 

9.52 

10.40 

4.73 

7.47 

5.13 

4.64 

9.52 

4.01 

12.30 

4.24 

10.40 

6.21 

3.56 

11.30 

6.29 

12.30 

9.52 

10.40 

4.78 

12.30 

3.72 

7.47 

7.47 

12.80 

10.40 

4.73 

7.47 

5.13 

6.03 

12.80 

4.77 

12.80 

7.69 

11.90 

11.30 

3.93 

12.80 

11.90 

12.30 

12.80 

11.90 

6.03 

12.80 

3.72 

12.80 

7.69 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-71
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-63. Consumer-Only Intake of Home-Produced Dark Green Vegetables (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 8,855,000 428 4.71 0.39 0.03 0.00 0.00 0.01 0.09 0.21 0.44 0.92 1.25 

Age 

1 to 2 180,000 8 3.16 * * * * * * * * * * 

3 to 5 226,000 12 2.79 * * * * * * * * * * 

6 to 11 826,000 39 4.94 0.31 0.05 0.00 0.01 0.02 0.09 0.18 0.39 0.95 1.04 

12 to 19 628,000 32 3.07 0.42 0.15 0.00 0.01 0.01 0.06 0.20 0.37 0.92 1.64 

20 to 39 1,976,000 87 3.21 0.34 0.06 0.00 0.00 0.01 0.09 0.18 0.38 0.67 0.92 

40 to 69 3,710,000 184 6.54 0.40 0.04 0.00 0.00 0.03 0.08 0.23 0.48 0.98 1.25 

≥ 70 1,253,000 63 7.89 0.41 0.07 0.00 0.00 0.01 0.11 0.23 0.47 0.93 1.08 

Season 

Fall 2,683,000 88 5.63 0.44 0.07 0.01 0.04 0.09 0.15 0.24 0.46 0.79 1.08 

Spring 1,251,000 127 2.71 0.56 0.08 0.00 0.00 0.01 0.10 0.31 0.54 1.28 2.81 

Summer 3,580,000 124 7.87 0.34 0.04 0.00 0.00 0.01 0.06 0.15 0.41 0.98 1.15 

Winter 1,341,000 89 2.75 0.27 0.04 0.00 0.00 0.01 0.02 0.15 0.37 0.66 1.17 

Urbanization 

Central City 1,298,000 48 2.30 0.27 0.04 0.00 0.00 0.01 0.11 0.21 0.32 0.63 0.92 

Non-metropolitan 3,218,000 167 7.15 0.33 0.04 0.00 0.00 0.02 0.07 0.17 0.45 0.75 1.00 

Suburban 4,279,000 211 4.94 0.48 0.05 0.00 0.01 0.02 0.09 0.23 0.46 1.15 2.18 

Race 

Black 724,000 49 3.33 1.04 0.18 0.00 0.10 0.11 0.22 0.55 1.17 3.29 3.86 

White 7,963,000 373 5.05 0.32 0.02 0.00 0.00 0.01 0.08 0.20 0.38 0.78 1.07 

Region 

Midwest 2,668,000 121 5.75 0.28 0.04 0.00 0.00 0.01 0.06 0.21 0.36 0.50 0.98 

Northeast 1,554,000 76 3.77 0.51 0.09 0.00 0.00 0.00 0.06 0.20 0.49 1.25 1.93 

South 2,945,000 148 4.58 0.48 0.05 0.04 0.07 0.09 0.15 0.29 0.64 0.92 1.28 

West 1,628,000 81 4.51 0.32 0.07 0.00 0.00 0.01 0.04 0.11 0.31 0.66 0.93 

Response to Questionnaire 

Households who garden 8,521,000 412 12.50 0.40 0.03 0.00 0.00 0.01 0.09 0.21 0.45 0.92 1.25 

Households who farm 1,450,000 66 19.78 0.38 0.06 0.00 0.00 0.01 0.07 0.23 0.48 0.95 1.25 

3.53 

* 

* 

1.28 

4.86 

2.94 

3.29 

3.45 

3.86 

4.86 

2.48 

2.04 

1.07 

2.48 

3.86 

4.86 

2.37 

2.48 

3.53 

3.86 

4.86 

3.53 

2.48 

5.82 

* 

* 

1.28 

4.86 

4.29 

5.82 

3.45 

4.29 

5.82 

2.48 

2.18 

1.07 

5.82 

4.86 

4.86 

5.82 

3.02 

5.82 

4.29 

4.86 

5.82 

3.02 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-72 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-64. Consumer-Only Intake of Home-Produced Deep Yellow Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 5,467,000 245 2.91 0.64 0.04 0.04 0.07 0.13 0.22 0.42 0.77 1.44 

Age 

1 to 2 124,000 8 2.18 * * * * * * * * * 

3 to 5 61,000 4 0.75 * * * * * * * * * 

6 to 11 382,000 17 2.29 * * * * * * * * * 

12 to 19 493,000 21 2.41 0.47 0.09 0.06 0.06 0.06 0.09 0.36 0.78 1.13 

20 to 39 1,475,000 63 2.39 0.53 0.08 0.05 0.06 0.12 0.17 0.31 0.51 1.22 

40 to 69 2,074,000 96 3.66 0.54 0.05 0.04 0.09 0.14 0.22 0.40 0.65 1.09 

≥ 70 761,000 32 4.79 0.78 0.09 0.08 0.20 0.28 0.37 0.57 1.24 1.61 

Season 

Fall 2,664,000 97 5.59 0.74 0.08 0.09 0.12 0.14 0.26 0.45 0.97 1.73 

Spring 315,000 34 0.68 0.56 0.08 0.14 0.15 0.20 0.25 0.45 0.64 1.01 

Summer 1,619,000 52 3.56 0.51 0.06 0.04 0.05 0.06 0.23 0.41 0.64 0.96 

Winter 869,000 62 1.78 0.63 0.09 0.04 0.04 0.06 0.17 0.35 0.80 1.54 

Urbanization 

Central City 1,308,000 43 2.32 0.51 0.07 0.04 0.06 0.14 0.21 0.39 0.59 0.96 

Non-metropolitan 2,100,000 118 4.66 0.67 0.08 0.04 0.06 0.09 0.22 0.37 0.87 1.39 

Suburban 2,059,000 84 2.38 0.71 0.07 0.06 0.09 0.13 0.26 0.43 0.97 1.67 

Race 

Black 129,000 8 0.59 * * * * * * * * * 

White 5,093,000 229 3.23 0.65 0.04 0.05 0.09 0.14 0.24 0.43 0.80 1.50 

Region 

Midwest 2,792,000 128 6.02 0.75 0.06 0.04 0.13 0.19 0.28 0.51 0.96 1.73 

Northeast 735,000 29 1.79 0.40 0.08 0.04 0.06 0.06 0.09 0.15 0.64 1.09 

South 557,000 30 0.87 0.54 0.21 0.05 0.05 0.08 0.22 0.31 0.44 0.77 

West 1,383,000 58 3.83 0.60 0.07 0.06 0.13 0.14 0.22 0.41 0.64 1.44 

Response to Questionnaire 

Households who garden 5,177,000 233 7.60 0.62 0.04 0.04 0.09 0.13 0.23 0.42 0.75 1.42 

Households who farm 1,088,000 51 14.85 0.61 0.09 0.09 0.09 0.12 0.19 0.34 0.94 1.28 

2.03 

* 

* 

* 

1.44 

2.03 

1.33 

1.99 

2.23 

1.42 

1.67 

2.23 

1.41 

2.12 

2.03 

* 

2.03 

2.23 

1.37 

1.22 

1.89 

1.99 

1.73 

2.67 

* 

* 

* 

1.58 

2.67 

3.02 

1.99 

3.02 

2.41 

2.31 

4.37 

2.24 

4.37 

2.67 

* 

2.67 

3.02 

2.21 

6.63 

2.31 

2.67 

3.02 

6.63 

* 

* 

* 

1.58 

2.67 

3.02 

1.99 

6.63 

2.41 

2.31 

4.37 

2.24 

6.63 

2.67 

* 

4.37 

4.37 

2.21 

6.63 

2.31 

4.37 

3.02 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-73
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-65. Consumer-Only Intake of Home-Produced Other Vegetables (g/kg-day) 

Population Nc Nc % 

Group Wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 25,221,000 1,437 13.41 1.38 0.05 0.01 0.11 0.18 0.36 0.78 1.65 3.09 

Age 

1 to 2 613,000 38 10.76 3.80 0.63 0.19 0.27 0.40 1.04 2.61 4.55 7.74 

3 to 5 887,000 59 10.95 2.15 0.27 0.00 0.23 0.37 0.72 1.37 3.16 4.47 

6 to 11 2,149,000 134 12.86 1.30 0.14 0.00 0.12 0.19 0.35 0.80 1.61 3.04 

12 to 19 2,379,000 141 11.61 0.98 0.09 0.00 0.06 0.12 0.32 0.64 1.33 2.05 

20 to 39 6,020,000 328 9.77 0.93 0.06 0.03 0.09 0.15 0.24 0.56 1.12 2.19 

40 to 69 9,649,000 547 17.01 1.40 0.09 0.01 0.11 0.19 0.40 0.84 1.58 2.92 

≥ 70 3,226,000 174 20.31 1.58 0.14 0.02 0.15 0.24 0.46 0.95 1.91 3.46 

Season 

Fall 6,934,000 253 14.55 1.19 0.09 0.05 0.15 0.19 0.33 0.72 1.44 2.74 

Spring 5,407,000 567 11.71 1.16 0.06 0.00 0.04 0.10 0.31 0.71 1.39 2.67 

Summer 8,454,000 283 18.59 1.79 0.15 0.00 0.12 0.18 0.39 0.97 1.97 4.13 

Winter 4,426,000 334 9.09 1.19 0.07 0.00 0.14 0.23 0.41 0.73 1.49 2.41 

Urbanization 

Central City 4,148,000 161 7.36 0.97 0.09 0.04 0.09 0.16 0.32 0.61 1.23 1.97 

Non-metropolitan 10,721,000 710 23.81 1.78 0.09 0.03 0.16 0.23 0.47 1.01 2.01 4.05 

Suburban 10,292,000 564 11.89 1.14 0.06 0.00 0.09 0.15 0.31 0.65 1.44 2.69 

Race 

Black 1,347,000 84 6.19 1.30 0.17 0.04 0.17 0.21 0.35 0.71 1.49 3.88 

White 23,367,000 1,327 14.83 1.39 0.05 0.01 0.11 0.18 0.38 0.79 1.65 3.04 

Region 

Midwest 8,296,000 522 17.88 1.43 0.09 0.03 0.12 0.19 0.37 0.73 1.65 3.05 

Northeast 2,914,000 162 7.08 1.33 0.17 0.00 0.06 0.11 0.24 0.60 1.64 3.07 

South 9,218,000 518 14.33 1.53 0.08 0.01 0.17 0.25 0.49 1.03 1.76 3.37 

West 4,733,000 233 13.12 1.08 0.10 0.01 0.07 0.12 0.26 0.57 1.21 2.41 

Response to Questionnaire 

Households who garden 22,417,000 1,291 32.89 1.44 0.05 0.01 0.11 0.18 0.38 0.82 1.70 3.22 

Households who farm 3,965,000 239 54.10 1.95 0.16 0.01 0.14 0.23 0.52 1.21 2.04 5.32 

4.52 

11.20 

5.96 

4.57 

3.17 

3.04 

4.65 

5.79 

4.00 

4.21 

6.14 

3.37 

3.22 

5.74 

3.77 

5.47 

4.49 

4.65 

5.41 

4.70 

3.73 

4.65 

7.02 

9.95 

18.00 

8.41 

9.95 

5.41 

5.10 

14.10 

9.96 

6.74 

7.35 

14.60 

7.00 

7.00 

14.10 

6.81 

6.21 

9.96 

11.20 

12.00 

8.33 

8.02 

9.95 

14.60 

18.40 

18.00 

14.00 

9.95 

5.41 

7.00 

18.40 

11.40 

9.96 

14.00 

18.40 

11.00 

8.85 

18.40 

11.40 

7.72 

18.40 

18.40 

14.10 

18.00 

11.40 

18.40 

15.90 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-74 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-66. Consumer-Only Intake of Home-Produced Citrus (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 2,530,000 125 1.35 4.76 0.61 0.08 0.16 0.29 0.76 1.99 5.10 

Age 

1 to 2 54,000 4 0.95 * * * * * * * * 

3 to 5 51,000 3 0.63 * * * * * * * * 

6 to 11 181,000 9 1.08 * * * * * * * * 

12 to 19 194,000 14 0.95 * * * * * * * * 

20 to 39 402,000 18 0.65 * * * * * * * * 

40 to 69 1,183,000 55 2.09 4.54 0.81 0.08 0.15 0.25 0.52 1.74 5.24 

≥ 70 457,000 21 2.88 4.43 0.76 0.08 0.08 0.49 1.95 3.53 6.94 

Season 

Fall 280,000 8 0.59 * * * * * * * * 

Spring 437,000 33 0.95 2.31 0.38 0.16 0.18 0.24 0.37 1.36 4.15 

Summer 334,000 11 0.73 * * * * * * * * 

Winter 1,479,000 73 3.04 6.47 0.95 0.15 0.33 0.49 1.64 2.93 8.59 

Urbanization 

Central City 1,053,000 43 1.87 3.57 0.52 0.15 0.33 0.45 1.13 3.01 4.97 

Non-metropolitan 0 0 0.00 - - - - - - - -

Suburban 1,477,000 82 1.71 5.61 0.91 0.08 0.11 0.25 0.52 1.81 8.12 

Race 

Black 200,000 8 0.92 * * * * * * * * 

White 2,330,000 117 1.48 4.93 0.63 0.08 0.15 0.28 0.78 2.34 5.34 

Region 

Midwest 64,000 4 0.14 * * * * * * * * 

Northeast 0 0 0.00 - - - - - - - -

South 1,240,000 55 1.93 5.18 0.74 0.16 0.38 0.64 1.60 3.42 6.50 

West 1,226,000 66 3.40 4.56 0.98 0.08 0.11 0.24 0.37 1.42 4.53 

Response to Questionnaire 

Households who garden 2,151,000 102 3.16 4.55 0.66 0.08 0.15 0.28 0.76 1.99 4.99 

Households who farm 130,000 5 1.77 * * * * * * * * 

14.10 

* 

* 

* 

* 

* 

15.20 

8.97 

* 

5.10 

* 

19.10 

7.46 

-

17.90 

* 

14.10 

* 

-

14.10 

12.40 

12.40 

* 

19.70 

* 

* 

* 

* 

* 

19.70 

8.97 

* 

6.50 

* 

23.80 

8.97 

-

23.80 

* 

19.70 

* 

-

19.70 

20.00 

17.90 

* 

32.20 

* 

* 

* 

* 

* 

23.80 

15.70 

* 

7.52 

* 

47.90 

20.00 

-

47.90 

* 

32.20 

* 

-

23.80 

47.90 

32.20 

* 

47.90 

* 

* 

* 

* 

* 

23.80 

15.70 

* 

7.52 

* 

47.90 

20.00 

-

47.90 

* 

47.90 

* 

-

23.80 

47.90 

47.90 

* 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

- Indicates data are not available. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Exposure Factors Handbook PageSeptember 2011 13-75
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-67. Consumer-Only Intake of Home-Produced Other Fruit (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE p1 p5 p10 p25 p50 p75 p90 p95 p99 MAX 

Total 12,615,000 706 6.71 2.20 0.19 0.05 0.15 0.26 0.46 0.91 1.91 

Age 

1 to 2 306,000 19 5.37 * * * * * * * * 

3 to 5 499,000 31 6.16 2.66 0.76 0.00 0.00 0.38 1.02 1.87 2.71 

6 to 11 915,000 68 5.48 2.60 0.44 0.00 0.18 0.39 0.64 1.14 2.99 

12 to 19 1,021,000 54 4.98 1.62 0.28 0.08 0.12 0.26 0.39 0.61 2.36 

20 to 39 2,761,000 146 4.48 1.85 0.37 0.08 0.13 0.18 0.31 0.62 1.39 

40 to 69 4,610,000 259 8.13 2.09 0.31 0.07 0.15 0.25 0.44 0.77 1.77 

≥ 70 2,326,000 119 14.65 1.66 0.18 0.04 0.21 0.36 0.57 1.07 1.65 

Season 

Fall 2,923,000 102 6.13 1.39 0.11 0.26 0.30 0.38 0.57 1.07 1.88 

Spring 2,526,000 268 5.47 1.47 0.15 0.09 0.20 0.25 0.43 0.83 1.65 

Summer 4,327,000 144 9.51 

Winter 2,839,000 192 5.83 1.29 0.11 0.04 0.10 0.23 0.45 0.83 1.55 

Urbanization 

Central City 2,681,000 102 4.76 1.79 0.29 0.04 0.17 0.29 0.52 0.89 1.60 

Non-metropolitan 4,118,000 278 9.15 2.43 0.31 0.07 0.12 0.24 0.45 1.13 2.43 

Suburban 5,756,000 324 6.65 2.25 0.31 0.13 0.20 0.28 0.45 0.76 1.81 

Race 

Black 250,000 12 1.15 * * * * * * * * 

White 12,256,000 690 7.78 2.24 0.19 0.07 0.15 0.26 0.47 0.92 1.94 

Region 

Midwest 4,619,000 298 9.96 3.07 0.43 0.04 0.13 0.24 0.45 1.04 2.35 

Northeast 1,279,000 72 3.11 0.93 0.22 0.08 0.09 0.16 0.31 0.48 0.81 

South 3,004,000 157 4.67 1.99 0.26 0.08 0.24 0.30 0.55 1.10 1.82 

West 3,653,000 177 10.13 1.76 0.16 0.10 0.22 0.29 0.54 0.97 2.04 

Response to Questionnaire 

Households who garden 10,926,000 619 16.03 2.38 0.21 0.04 0.16 0.26 0.47 0.99 1.96 

Households who farm 1,917,000 112 26.16 2.57 0.27 0.07 0.28 0.36 0.73 1.55 3.62 

4.59 

* 

5.54 

7.13 

3.92 

3.70 

3.17 

4.06 

2.89 

2.89 

2.70 

2.61 

4.60 

4.72 

* 

4.65 

6.73 

1.29 

4.06 

4.35 

4.94 

5.80 

8.12 

* 

6.30 

12.10 

6.81 

6.64 

9.77 

5.21 

4.06 

4.59 

4.79 

10.40 

8.12 

7.61 

* 

8.26 

14.20 

2.16 

6.30 

5.75 

10.40 

8.06 

18.40 

* 

33.20 

16.20 

8.12 

37.00 

18.40 

11.70 

5.39 

8.26 

8.06 

15.40 

24.00 

18.40 

* 

18.40 

53.30 

11.70 

16.20 

13.00 

18.40 

16.20 

62.60 

* 

33.20 

16.50 

8.12 

37.00 

53.30 

11.70 

5.54 

33.20 

11.30 

15.40 

53.30 

62.60 

* 

62.60 

62.60 

11.70 

24.00 

13.00 

62.60 

16.20 

* Intake data not provided for subpopulations for which there were less than 20 observations. 

SE = Standard error. 

p = Percentile of the distribution. 

Nc wgtd = Weighted number of consumers. 

Nc unwgtd = Unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-76 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-68. Fraction of Food Intake That Is Home-Produced 

Total Total Total Total Total Exposed Protected 

Fruits Vegetables Meats Dairy Fish Vegetables Vegetables 

Root 

Vegetables 

Exposed 

Fruits 

Protected 

Fruits 

Total 

Season 

Fall 

Spring 

Summer 

Winter 

Urbanization 

Central City 

Non-metropolitan 

Suburban 

Race 

Black 

White 

Region 

Northeast 

Midwest 

South 

West 

Response to Questionnaire 

Households who garden 

Households who raise animals 

Households who farm 

Households who fish 

0.040 0.068 0.024 0.012 0.094 0.095 0.069 

0.021 

0.021 

0.058 

0.059 

0.081 

0.037 

0.116 

0.041 

0.020 

0.020 

0.034 

0.022 

0.008 

0.011 

0.022 

0.008 

0.076 

0.160 

0.079 

0.063 

0.106 

0.050 

0.164 

0.052 

0.073 

0.039 

0.101 

0.048 

0.027 

0.052 

0.047 

0.027 

0.144 

0.058 

0.003 

0.064 

0.018 

0.000 

0.043 

0.004 

0.053 

0.219 

0.075 

0.037 

0.207 

0.079 

0.027 

0.134 

0.054 

0.007 

0.049 

0.027 

0.081 

0.001 

0.031 

0.000 

0.014 

0.063 

0.110 

0.037 

0.109 

0.029 

0.081 

0.005 

0.059 

0.042 

0.062 

0.038 

0.112 

0.069 

0.057 

0.009 

0.046 

0.017 

0.023 

0.010 

0.024 

0.006 

0.007 

0.008 

0.133 

0.126 

0.108 

0.062 

0.148 

0.091 

0.079 

0.016 

0.109 

0.077 

0.060 

0.101 

-

0.161 

-

0.173 

-

0.308 

-

-

0.306 

0.319 

-

-

0.207 

0.254 

-

-

-

-

0.325 

0.233 

-

0.420 

-

0.178 

-

0.394 

-

0.043 

0.060 

0.020 

0.066 

0.026 

0.016 

0.088 

0.035 

0.012 

0.050 

0.018 

0.077 

0.042 

0.029 

0.106 

-

0.173 

-

0.050 

0.039 

0.047 

0.068 

0.044 

0.030 

0.100 

0.043 

0.008 

0.059 

0.010 

0.078 

0.040 

0.075 

0.116 

-

0.328 

-

0.037 

0.008 

0.008 

0.054 

0.068 

0.026 

0.025 

0.050 

0.007 

0.045 

0.002 

0.048 

0.044 

0.054 

0.094 

-

0.030 

-

Exposure Factors Handbook PageSeptember 2011 13-77
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-68. Fraction of Food Intake That Is Home-Produced (continued) 

Dark Green Deep Yellow Other Citrus Other 

Vegetables Vegetables Vegetables Fruits Fruits Apples Peaches Pears Strawberries Other Berries 

Total 

Season 

Fall 

Spring 

Summer 

Winter 

Urbanization 

Central City 

Non-metropolitan 

Suburban 

Race 

Black 

White 

Region 

Northeast 

Midwest 

South 

West 

Response to Questionnaire 

Households who garden 

Households who farm 

0.044 0.065 0.069 0.038 0.042 0.030 0.147 

0.059 

0.037 

0.063 

0.018 

0.099 

0.017 

0.080 

0.041 

0.069 

0.051 

0.114 

0.044 

0.114 

0.014 

0.010 

0.091 

0.027 

0.025 

0.070 

0.030 

0.032 

0.013 

0.053 

0.024 

0.090 

0.206 

0.133 

0.183 

0.012 

0.090 

0.054 

0.038 

0.122 

0.058 

0.026 

0.154 

0.053 

0.035 

0.000 

0.056 

0.022 

0.077 

0.042 

0.017 

0.066 

0.024 

0.087 

0.272 

0.121 

0.053 

0.043 

0.056 

0.071 

0.026 

0.082 

0.012 

0.045 

0.004 

0.051 

0.007 

0.035 

0.018 

0.164 

0.039 

0.054 

0.049 

0.034 

0.019 

0.174 

0.022 

0.063 

0.034 

0.102 

0.077 

0.055 

0.000 

0.001 

0.060 

0.103 

0.008 

0.083 

0.031 

0.046 

0.004 

0.052 

0.024 

0.043 

0.027 

0.164 

0.143 

0.238 

0.120 

0.220 

0.140 

0.328 

0.180 

0.368 

0.087 

0.005 

0.107 

0.227 

0.070 

0.292 

0.316 

0.461 

0.067 

0.038 

0.075 

0.066 

0.111 

0.038 

0.155 

0.068 

0.004 

0.089 

0.002 

0.112 

0.080 

0.093 

0.169 

0.606 

0.111 

0.408 

0.064 

0.088 

0.217 

0.107 

0.133 

0.101 

0.000 

0.125 

0.085 

0.209 

0.072 

0.044 

0.232 

0.057 

0.217 

0.163 

0.155 

0.232 

0.308 

0.228 

0.282 

0.175 

0.470 

0.214 

0.205 

0.231 

0.177 

0.233 

0.306 

0.548 

Page Exposure Factors Handbook 13-78 September 2011
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 13—Exposure Factors Handbook 

Intake of Home-Produced Foods 

Table 13-68. Fraction of Food Intake That Is Home-Produced (continued) 

Asparagus Beets Broccoli Cabbage Carrots Corn Cucumbers Lettuce Lima Beans Okra Onions 

Total 

Season 

Fall 

Spring 

Summer 

Winter 

Urbanization 

Central City 

Non-metropolitan 

Suburban 

Race 

Black 

White 

Region 

Northeast 

Midwest 

South 

West 

Response to Questionnaire 

Households who garden 

Households who farm 

0.063 0.203 0.015 0.038 0.043 0.078 0.148 0.010 0.121 

0.024 

0.103 

0 

0.019 

0.199 

0.191 

0.209 

0.215 

0.013 

0.011 

0.034 

0.006 

0.054 

0.011 

0.080 

0.008 

0.066 

0.015 

0.063 

0.025 

0.076 

0.048 

0.118 

0.043 

0.055 

0.040 

0.320 

0 

0.013 

0.010 

0.017 

0.002 

0.070 

0.082 

0.176 

0.129 

0.058 

0.145 

0.040 

0.212 

0.377 

0.127 

0.004 

0.040 

0.016 

0.004 

0.082 

0.045 

0.018 

0.091 

0.039 

0.025 

0.173 

0.047 

0.029 

0.377 

0.088 

0.009 

0.017 

0.009 

0.037 

0.132 

0.165 

0.000 

0.071 

0.000 

0.224 

0.000 

0.018 

0.001 

0.056 

0.068 

0.042 

0.019 

0.093 

0.060 

0.155 

0.007 

0.011 

0.103 

0.135 

0.091 

0.194 

0.015 

0.015 

0.074 

0.432 

0.145 

0.202 

0.020 

0.025 

0.013 

0.006 

0.047 

0.053 

0.029 

0.029 

0.025 

0.101 

0.020 

0.039 

0.020 

0.124 

0.088 

0.069 

0.147 

0.193 

0.140 

0.119 

0.009 

0.020 

0.006 

0.009 

0.026 

0.149 

0.140 

0.000 

0.125 

0.432 

0.420 

0.316 

0.043 

0.159 

0.099 

0.219 

0.103 

0.185 

0.220 

0.524 

0.349 

0.524 

0.031 

0.063 

0.258 

0.103 

0.270 

0.299 

0.211 

0.304 

0.123 

0.068 

0.411 

0.299 

0.069 

0.373 

0.000 

0.224 

0.291 

0.333 

0.618 

0.821 

0.056 

0.066 

0.033 

0.091 

0.029 

0.017 

0.127 

0.050 

0.009 

0.068 

0.022 

0.098 

0.047 

0.083 

0.148 

0.361 

Exposure Factors Handbook PageSeptember 2011 13-79
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-68. Fraction of Food Intake That Is Home-Produced (continued) 

Peas Peppers Pumpkin Snap 

Beans Tomatoes White Potatoes Beef Game Pork Poultry Eggs 

Total 0.069 0.107 0.155 0.155 0.184 0.038 0.038 0.276 

Season 

Fall 

Spring 

Summer 

Winter 

0.046 

0.048 

0.126 

0.065 

0.138 

0.031 

0.194 

0.03 

0.161 

0.046 

0.19 

0.154 

0.199 

0.152 

0.123 

0.147 

0.215 

0.045 

0.318 

0.103 

0.058 

0.010 

0.060 

0.022 

0.028 

0.027 

0.072 

0.022 

0.336 

0.265 

0.100 

0.330 

Urbanization 

Central City 

Non-metropolitan 

Suburban 

0.033 

0.123 

0.064 

0.067 

0.228 

0.086 

0.130 

0.250 

0.127 

0.066 

0.307 

0.118 

0.100 

0.313 

0.156 

0.009 

0.080 

0.029 

0.001 

0.107 

0.026 

0.146 

0.323 

0.316 

Race 

Black 

White 

0.047 

0.076 

0.039 

0.121 

0.022 

0.187 

0.046 

0.186 

0.060 

0.202 

0.007 

0.044 

0.000 

0.048 

0.000 

0.359 

Region 

Northeast 

Midwest 

South 

West 

0.021 

0.058 

0.106 

0.051 

0.067 

0.188 

0.113 

0.082 

0.002 

0.357 

0.044 

0.181 

0.052 

0.243 

0.161 

0.108 

0.117 

0.291 

0.149 

0.182 

0.016 

0.065 

0.042 

0.013 

0.014 

0.076 

0.022 

0.041 

0.202 

0.513 

0.199 

0.207 

Response to Questionnaire 

Households who garden 

Households who farm 

Households who raise animals 

Households who hunt 

0.193 

0.308 --

0.246 

0.564 --

0.230 

0.824 --

0.384 

0.623 --

0.398 

0.616 --

0.090 

0.134 --

-

0.485 

0.478 -

---

0.729 

0.013 

0.012 

0.015 

0.010 

0.014 

0.001 

0.040 

0.006 

0.000 

0.017 

0.006 

0.021 

0.012 

0.011 -

0.242 

0.239 -

0.011 

0.011 

0.012 

0.007 

0.014 

0.002 

0.026 

0.011 

0.001 

0.014 

0.002 

0.021 

0.012 

0.008 -

0.156 

0.151 -

0.014 

0.009 

0.022 

0.013 

0.011 

0.002 

0.029 

0.014 

0.002 

0.017 

0.004 

0.019 

0.012 

0.021 -

0.146 

0.214 -

- Indicates data are not available. 

Source: Based on EPA's analyses of the 1987–1988 NFCS. 

Page Exposure Factors Handbook 13-80 September 2011
 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-69. Percent Weight Losses From Food Preparation 

Food Group Mean Net Preparation/Cooking Loss (%) Mean Net Post Cooking (%) 

Meatsa 29.7b 29.7c 

Fish and shellfishd 31.5b 10.5c 

Fruits 25.4e 30.5f 

Vegetablesg 12.4h 22i 

a Averaged over various cuts and preparation methods for various meats including beef, pork, 

chicken, turkey, lamb, and veal. b Includes dripping and volatile losses during cooking. c Includes losses from cutting, shrinkage, excess fat, bones, scraps, and juices. d Averaged over a variety of fish and shellfish to include bass, bluefish, butterfish, cod, flounder, 

haddock, halibut, lake trout, mackerel, perch, porgy, red snapper, rockfish, salmon, sea trout, shad, 

smelt, sole, spot, squid, swordfish steak, trout, whitefish, clams, crab, crayfish, lobster, oysters, and 

shrimp and shrimp dishes. e Based on preparation losses. Averaged over apples, pears, peaches, strawberries, and oranges. 

Includes losses from removal of skin or peel, core or pit, stems or caps, seeds, and defects. Also 

includes losses from removal of drained liquids from canned or frozen forms. f Averaged over apples and peaches. Include losses from draining cooked forms. g Averaged over various vegetables to include asparagus, beets, broccoli, cabbage, carrots, corn, 

cucumbers, lettuce, lima beans, okra, onions, green peas, peppers, pumpkins, snap beans, tomatoes, 

and potatoes. h Includes losses due to paring, trimming, flowering the stalk, thawing, draining, scraping, shelling, 

slicing, husking, chopping, and dicing and gains from the addition of water, fat, or other ingredients. 

Averaged over various preparation methods. i Includes losses from draining or removal of skin. Based on potatoes only. 

Source: Derived from USDA (1975) 

Exposure Factors Handbook Page
 

September 2010 13-81 
 

 

Table 13-70. Estimated Age-Specific Per Capita Home-Produced Intake (adjusted; g/kg-day)a 

Home-Produced Home-Produced Home-Produced Home-Produced 

Fruits Vegetables Meats Dairy 

Gardening Farming Gardening Farming Population that Farming Population that Farming
 

Population Population Population Population Raises Animals Population Raises Animals Population
 

Mean 95th Mean 95th Mean 95th Mean 95th Mean 95th Mean 95th Mean 95th Mean 95th
 

Unadjusted (g/kg-day)b 

Total 

population 0.52 2.4 0.67 4.5 0.96 5.1 1.9 9.8 1.5 6.1 1.5 6.3 1.9 14 2.4 17 

Adjusted (g/kg-day)c 

Total 

population 0.27 1.2 0.35 2.4 0.66 3.5 1.3 6.7 0.71 3.0 0.73 3.1 1.9 14 2.4 17 

Birth to 1 yeard 1.0 4.4 1.2 8.4 0.87 4.7 1.8 8.9 0.41 1.7 0.42 1.8 3.6 26 4.5 32 

1 to <2 years 1.0 4.8 1.4 9.1 1.3 7.1 2.7 14 1.4 5.8 1.4 6.0 11 76 13 92 

2 to <3 years 1.0 4.8 1.4 9.1 1.3 7.1 2.7 14 1.4 5.8 1.4 6.0 11 76 13 92 

3 to <6 years 0.78 3.6 1.0 6.8 1.1 6.1 2.3 12 1.4 5.8 1.4 6.0 6.7 48 8.3 58 

6 to <11 years 0.40 1.9 0.52 3.5 0.80 4.2 1.6 8.1 1.0 4.1 1.0 4.2 3.9 28 4.8 34 

11 to <16 years 0.13 0.62 0.17 1.2 0.56 3.0 1.1 5.7 0.71 3.0 0.73 3.1 1.6 12 2.0 14 

16 to <21 years 0.13 0.62 0.17 1.2 0.56 3.0 1.1 5.7 0.71 3.0 0.73 3.1 1.6 12 2.0 14 

21 to <50 years 0.15 0.70 0.20 1.3 0.56 3.0 1.1 5.7 0.65 2.7 0.66 2.8 0.95 6.9 1.2 8.3 

50+ years 0.24 1.1 0.31 2.1 0.60 3.2 1.2 6.1 0.51 2.1 0.52 2.2 0.92 6.7 1.1 8.0 a	 Calculated as: per capita home-produced intake for total population of households that garden, farm, or raise animals (See Section 13.3.1), times age-specific 

ratio of mean per capita total intake to mean per capita total intake for total population, based on analysis of 1994–96 and 1998 CSFII data (See Chapters 9 and 

11). b Not adjusted for food preparation or post-cooking losses.
 c Adjusted to account for food preparation and post-cooking losses; no adjustments made to dairy.
 d Estimates are uncertain for this age group because of the wide range of intake patterns for children under 1 year of age.
 

Source:	 Phillips and Moya (2012). 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Page Exposure Factors Handbook 13-82 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-71. 2008 Food Gardening by Demographic Factors 

Demographic 

Factor 

Percentage of Total Households 

That Have Gardens (%) 

Total 

(~36 million) 

31 

Sex 

Female 

Male 

54 

46 

Age 

18–34 

35–44 

45–54 

55 and over 

21 

11 

24 

44 

Education 

College graduate 

Some college 

High school 

43 

36 

21 

Household income 

$75,000 and over 

$50–$74,999 

$35–$49,999 

Under $35,000 

Undesignated 

22 

16 

24 

21 

17 

Household size 

One person 

Two person 

Three to four person 

Five or more persons 

20 

40 

32 

9 

Source: National Gardening Association (2009). 

Exposure Factors Handbook Page
 

September 2011 13-83 
 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13-72. Percentage of Gardening Households Growing 

Different Vegetables in 2008 

Vegetable Percent (%) 

Tomatoes 

Cucumbers 

Sweet peppers 

Beans 

Carrots 

Summer squash 

Onions 

Hot peppers 

Lettuce 

Peas 

Sweet Corn 

Radish 

Potatoes 

Salad greens 

Pumpkins 

Watermelon 

Spinach 

Broccoli 

Melon 

Cabbage 

Beets 

Winter squash 

Asparagus 

Collards 

Cauliflower 

Celery 

Brussels sprouts 

Leeks 

Kale 

Parsnips 

Chinese cabbage 

Rutabaga 

86 

47 

46 

39 

34 

32 

32 

31 

28 

24 

23 

20 

18 

17 

17 

16 

15 

15 

15 

14 

11 

10 

9 

9 

7 

5 

5 

3 

3 

2 

2 

1 

Source: National Gardening Association (2009). 

Page Exposure Factors Handbook 

13-84 September 2011 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

APPENDIX 13A
 

FOOD CODES AND DEFINITIONS OF MAJOR FOOD GROUPS USED IN THE ANALYSIS
 

OF THE 1987–1988 USDA NFCS DATA TO ESTIMATE HOME-PRODUCED INTAKE RATES
 

Exposure Factors Handbook Page
 

September 2011 13A-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13A-1. Food Codes and Definitions of Major Food Groups Used in Analysis of the 1987–1988 

USDA NFCS Data to Estimate Intake of Home-Produced Foods 

Food Product Household Code/Definitiona Individual Code 

MAJOR FOOD GROUPS 

Total Fruits 50­ Fresh Fruits 

citrus 

other vitamin-C rich 

other fruits 

512­ Commercially Canned Fruits 

522­ Commercially Frozen Fruits 

533­ Canned Fruit Juice 

534­ Frozen Fruit Juice 

535­ Aseptically Packed Fruit Juice 

536­ Fresh Fruit Juice 

542­ Dried Fruits 

(includes baby foods) 

6­ Fruits 

citrus fruits and juices 

dried fruits 

other fruits 

fruits/juices & nectar 

fruit/juices baby food 

(includes baby foods) 

Total Vegetables 48­ Potatoes, Sweet Potatoes 

49­ Fresh Vegetables 

dark green 

deep yellow 

tomatoes 

light green 

other 

511­ Commercially Canned Vegetables 

521­ Commercially Frozen Vegetables 

531­ Canned Vegetable Juice 

532­ Frozen Vegetable Juice 

537­ Fresh Vegetable Juice 

538­ Aseptically Packed Vegetable Juice 

541­ Dried Vegetables 

(does not include soups, sauces, gravies, mixtures, and ready-toeat dinners; includes baby foods except mixtures/dinners) 

7­ Vegetables (all forms) 

white potatoes & Puerto Rican starchy 

dark green vegetables 

deep yellow vegetables 

tomatoes and tom. mixtures 

other vegetables 

veg. and mixtures/baby food 

veg. with meat mixtures 

(includes baby foods; mixtures, mostly vegetables) 

Total Meats 44­ Meat 

beef 

pork 

veal 

lamb 

mutton 

goat 

game 

lunch meat 

mixtures 

451­ Poultry 

(does not include soups, sauces, gravies, mixtures, and ready-toeat dinners; includes baby foods except mixtures) 

20­ Meat, type not specified 

21­ Beef 

22­ Pork 

23­ Lamb, veal, game, carcass meat 

24­ Poultry 

25­ Organ meats, sausages, lunchmeats, meat 

spreads 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, 

poultry and fish base; and gelatin-based drinks; 

includes baby foods) 

Total Dairy 40­ Milk Equivalent 

fresh fluid milk 

processed milk 

cream and cream substitutes 

frozen desserts with milk 

cheese 

dairy-based dips 

(does not include soups, sauces, gravies, mixtures, and ready-toeat dinners) 

1­ Milk and Milk Products 

milk and milk drinks 

cream and cream substitutes 

milk desserts, sauces, and gravies 

cheeses 

(includes regular fluid milk, human milk, imitation milk 

products, yogurt, milk-based meal replacements, and 

infant formulas) 

Total Fish 452­ Fish, Shellfish 

various species 

fresh, frozen, commercial, dried 

(does not include soups, sauces, gravies, mixtures, and ready-toeat dinners) 

26­ Fish, Shellfish 

various species and forms 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, 

poultry and fish base; and gelatin-based drinks) a Food items within these categories that were identified by the household as being home-produced or home-caught (i.e., source 

code pertaining to home-produced foods) were included in the analysis. 

Page Exposure Factors Handbook 

13A-2 September 2011 
Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

APPENDIX 13B 

1987−1988 NFCS FOOD CODES AND DEFINITIONS OF INDIVIDUAL FOOD ITEMS USED IN 

ESTIMATING THE FRACTION OF HOUSEHOLD FOOD INTAKE THAT IS HOME-PRODUCED 

Exposure Factors Handbook Page
 

September 2011 13B-1 
 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced 

Food Product Household Code/Definition Individual Code 

INDIVIDUAL FOODS 

White Potatoes 4811­ White Potatoes, fresh 

4821­ White Potatoes, commercially canned 

4831­ White Potatoes, commercially frozen 

4841­ White Potatoes, dehydrated 

4851­ White Potatoes, chips, sticks, salad 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

71­ White Potatoes and Puerto Rican Starchy Veg. 

baked, boiled, chips, sticks, creamed, scalloped, 

au gratin, fried, mashed, stuffed, puffs, salad, 

recipes, soups, Puerto Rican starchy vegetables 

(does not include vegetables soups; vegetable 

mixtures; or vegetable with meat mixtures) 

Peppers 4913­ Green/Red Peppers, fresh 

5111201 Sweet Green Peppers, commercially canned 

5111202 Hot Chili Peppers, commercially canned 

5211301 Sweet Green Peppers, commercially frozen 

5211302 Green Chili Peppers, commercially frozen 

5211303 Red Chili Peppers, commercially frozen 

5413112 Sweet Green Peppers, dry 

5413113 Red Chili Peppers, dry 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

7512100 Pepper, hot chili, raw 

7512200 Pepper, raw 

7512210 Pepper, sweet green, raw 

7512220 Pepper, sweet red, raw 

7522600 Pepper, green, cooked, NS as to fat added 

7522601 Pepper, green, cooked, fat not added 

7522602 Pepper, green, cooked, fat added 

7522604 Pepper, red, cooked, NS as to fat added 

7522605 Pepper, red, cooked, fat not added 

7522606 Pepper, red, cooked, fat added 

7522609 Pepper, hot, cooked, NS as to fat added 

7522610 Pepper, hot, cooked, fat not added 

7522611 Pepper, hot, cooked, fat added 

7551101 Peppers, hot, sauce 

7551102 Peppers, pickled 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Onions 4953­ Onions, Garlic, fresh 

onions 

chives 

garlic 

leeks 

5114908 Garlic Pulp, raw 

5114915 Onions, commercially canned 

5213722 Onions, commercially frozen 

5213723 Onions with Sauce, commercially frozen 

5413103 Chives, dried 

5413105 Garlic Flakes, dried 

5413110 Onion Flakes, dried 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

7510950 Chives, raw 

7511150 Garlic, raw 

7511250 Leek, raw 

7511701 Onions, young green, raw 

7511702 Onions, mature 

7521550 Chives, dried 

7521740 Garlic, cooked 

7522100 Onions, mature cooked, NS as to fat added 

7522101 Onions, mature cooked, fat not added 

7522102 Onions, mature cooked, fat added 

7522103 Onions, pearl cooked 

7522104 Onions, young green cooked, NS as to fat 

7522105 Onions, young green cooked, fat not added 

7522106 Onions, young green cooked, fat added 

7522110 Onion, dehydrated 

7541501 Onions, creamed 

7541502 Onion rings 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Page Exposure Factors Handbook 

13B-2 September 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Corn 4956­ Corn, fresh 

5114601 Yellow Corn, commercially canned 

5114602 White Corn, commercially canned 

5114603 Yellow Creamed Corn, commercially canned 

5114604 White Creamed Corn, commercially canned 

5114605 Corn on Cob, commercially canned 

5114607 Hominy, canned 

5115306 Low Sodium Corn, commercially canned 

5115307 Low Sodium Cr. Corn, commercially canned 

5213501 Yellow Corn on Cob, commercially frozen 

5213502 Yellow Corn off Cob, commercially frozen 

5213503 Yell. Corn with Sauce, commercially frozen 

5213504 Corn with other Veg., commercially frozen 

5213505 White Corn on Cob, commercially frozen 

5213506 White Corn off Cob, commercially frozen 

5213507 Wh. Corn with Sauce, commercially frozen 

5413104 Corn, dried 

5413106 Hominy, dry 

5413603 Corn, instant baby food 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby food) 

7510960 Corn, raw 

7521600 Corn, cooked, NS as to color/fat added 

7521601 Corn, cooked, NS as to color/fat not added 

7521602 Corn, cooked, NS as to color/fat added 

7521605 Corn, cooked, NS as to color/cream style 

7521607 Corn, cooked, dried 

7521610 Corn, cooked, yellow/NS as to fat added 

7521611 Corn, cooked, yellow/fat not added 

7521612 Corn, cooked, yellow/fat added 

7521615 Corn, yellow, cream style 

7521616 Corn, cooked, yell. & wh./NS as to fat 

7521617 Corn, cooked, yell. & wh./fat not added 

7521618 Corn, cooked, yell. & wh./fat added 

7521619 Corn, yellow, cream style, fat added 

7521620 Corn, cooked, white/NS as to fat added 

7521621 Corn, cooked, white/fat not added 

7521622 Corn, cooked, white/fat added 

7521625 Corn, white, cream style 

7521630 Corn, yellow, canned, low sodium, NS fat 

7521631 Corn, yell., canned, low sod., fat not add 

7521632 Corn, yell., canned, low sod., fat added 

7521749 Hominy, cooked 

752175­ Hominy, cooked 

7541101 Corn scalloped or pudding 

7541102 Corn fritter 

7541103 Corn with cream sauce 

7550101 Corn relish 

76405­ Corn, baby 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; includes baby food) 

Apples 5031­ Apples, fresh 

5122101 Applesauce with sugar, commercially canned 

5122102 Applesauce without sugar, comm. canned 

5122103 Apple Pie Filling, commercially canned 

5122104 Apples, Applesauce, baby/jr., comm. canned 

5122106 Apple Pie Filling, Low Cal., comm. canned 

5223101 Apple Slices, commercially frozen 

5332101 Apple Juice, canned 

5332102 Apple Juice, baby, Comm. canned 

5342201 Apple Juice, comm. frozen 

5342202 Apple Juice, home frozen 

5352101 Apple Juice, aseptically packed 

5362101 Apple Juice, fresh 

5423101 Apples, dried 

(includes baby food; except mixtures) 

6210110 Apples, dried, uncooked 

6210115 Apples, dried, uncooked, low sodium 

6210120 Apples, dried, cooked, NS as to sweetener 

6210122 Apples, dried, cooked, unsweetened 

6210123 Apples, dried, cooked, with sugar 

6310100 Apples, raw 

6310111 Applesauce, NS as to sweetener 

6310112 Applesauce, unsweetened 

6310113 Applesauce with sugar 

6310114 Applesauce with low calorie sweetener 

6310121 Apples, cooked or canned with syrup 

6310131 Apple, baked NS as to sweetener 

6310132 Apple, baked, unsweetened 

6310133 Apple, baked with sugar 

6310141 Apple rings, fried 

6310142 Apple, pickled 

6310150 Apple, fried 

6340101 Apple, salad 

6340106 Apple, candied 

6410101 Apple cider 

6410401 Apple juice 

6410405 Apple juice with vitamin C 

6710200 Applesauce baby fd., NS as to str. or jr. 

6710201 Applesauce baby food, strained 

6710202 Applesauce baby food, junior 

6720200 Apple juice, baby food 

(includes baby food; except mixtures) 

Exposure Factors Handbook Page
 

September 2011 13B-3 
 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Tomatoes 4931­ Tomatoes, fresh 

5113­ Tomatoes, commercially canned 

5115201 Tomatoes, low sodium, commercially canned 

5115202 Tomato Sauce, low sodium, comm. canned 

5115203 Tomato Paste, low sodium, comm. canned 

5115204 Tomato Puree, low sodium, comm. canned 

5311­ Canned Tomato Juice and Tomato Mixtures 

5321­ Frozen Tomato Juice 

5371­ Fresh Tomato Juice 

5381102 Tomato Juice, aseptically packed 

5413115 Tomatoes, dry 

5614­ Tomato Soup 

5624­ Condensed Tomato Soup 

5654­ Dry Tomato Soup 

(does not include mixtures, and ready-to-eat dinners) 

74­ Tomatoes and Tomato Mixtures 

raw, cooked, juices, sauces, mixtures, soups, 

sandwiches 

Snap Beans 4943­ Snap or Wax Beans, fresh 

5114401 Green or Snap Beans, commercially canned 

5114402 Wax or Yellow Beans, commercially canned 

5114403 Beans, baby/jr., commercially canned 

5115302 Green Beans, low sodium, comm. canned 

5115303 Yell. or Wax Beans, low sod., comm. canned 

5213301 Snap or Green Beans, comm. frozen 

5213302 Snap or Green w/sauce, comm. frozen 

5213303 Snap or Green Beans w/other veg., comm. fr. 

5213304 Sp. or Gr. Beans w/other veg./sc., comm. fr. 

5213305 Wax or Yell. Beans, comm. frozen 

(does not include soups, mixtures, and ready-to-eat 

dinners; includes baby foods) 

7510180 Beans, string, green, raw 

7520498 Beans, string, cooked, NS color/fat added 

7520499 Beans, string, cooked, NS color/no fat 

7520500 Beans, string, cooked, NS color & fat 

7520501 Beans, string, cooked, green/NS fat 

7520502 Beans, string, cooked, green/no fat 

7520503 Beans, string, cooked, green/fat 

7520511 Beans, str., canned, low sod., green/NS fat 

7520512 Beans, str., canned, low sod., green/no fat 

7520513 Beans, str., canned, low sod., green/fat 

7520600 Beans, string, cooked, yellow/NS fat 

7520601 Beans, string, cooked, yellow/no fat 

7520602 Beans, string, cooked, yellow/fat 

7540301 Beans, string, green, creamed 

7540302 Beans, string, green, w/mushroom sauce 

7540401 Beans, string, yellow, creamed 

7550011 Beans, string, green, pickled 

7640100 Beans, green, string, baby 

7640101 Beans, green, string, baby, str. 

7640102 Beans, green, string, baby, junior 

7640103 Beans, green, string, baby, creamed 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; includes baby foods) 

Beef 441­ Beef 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

21­ Beef 

beef, nfs 

beef steak 

beef oxtails, neck bones, ribs 

roasts, stew meat, corned, brisket, sandwich 

steaks 

ground beef, patties, meatballs 

other beef items 

beef baby food 

(excludes meat, poultry, and fish with non-meat items; frozen 

plate meals; soups and gravies with meat, poultry, and fish 

base; and gelatin-based drinks; includes baby food) 

Page Exposure Factors Handbook 

13B-4 September 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Pork 442­ Pork 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

22­ Pork 

pork, nfs; ground dehydrated 

chops 

steaks, cutlets 

ham 

roasts 

Canadian bacon 

bacon, salt pork 

other pork items 

pork baby food 

(excludes meat, poultry, and fish with non-meat items; frozen 

plate meals; soups and gravies with meat, poultry and fish 

base; and gelatin-based drinks; includes baby food) 

Game 445­ Variety Meat, Game 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

233­ Game 

(excludes meat, poultry, and fish with non-meat items; frozen 

plate meals; soups and gravies with meat, poultry, and fish 

base; and gelatin-based drinks) 

Poultry 451­ Poultry 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

24­ Poultry 

chicken 

turkey 

duck 

other poultry 

poultry baby food 

(excludes meat, poultry, and fish with non-meat items; frozen 

plate meals; soups and gravies with meat, poultry, and fish 

base; and gelatin-based drinks; includes baby food) 

Eggs 46­ Eggs (fresh equivalent) 

fresh 

processed eggs, substitutes 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

3­ Eggs 

eggs 

egg mixtures 

egg substitutes 

eggs baby food 

froz. meals with egg as main ingred. 

(includes baby foods) 

Broccoli 4912­ Fresh Broccoli (and home canned/froz.) 

5111203 Broccoli, comm. canned 

52112­ Comm. Frozen Broccoli 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

722­ Broccoli (all forms) 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Carrots 4921­ Fresh Carrots (and home canned/froz.) 

51121­ Comm. Canned Carrots 

5115101 Carrots, Low Sodium, Comm. Canned 

52121­ Comm. Frozen Carrots 

5312103 Comm. Canned Carrot Juice 

5372102 Carrot Juice Fresh 

5413502 Carrots, Dried Baby Food 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7310­ Carrots (all forms) 

7311140 Carrots in Sauce 

7311200 Carrot Chips 

76201­ Carrots, baby 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; includes baby foods except 

mixtures) 

Pumpkin 4922­ Fresh Pumpkin, Winter Squash (and home 

canned/froz.) 

51122­ Pumpkin/Squash, Baby or Junior, Comm. 

Canned 

52122­ Winter Squash, Comm. Frozen 

5413504 Squash, Dried Baby Food 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

732­ Pumpkin (all forms) 

733­ Winter squash (all forms) 

76205­ Squash, baby 

(does not include vegetable soups; vegetables mixtures; or 

vegetable with meat mixtures; includes baby foods) 

Exposure Factors Handbook Page
 

September 2011 13B-5 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Asparagus 4941­ Fresh Asparagus (and home canned/froz.) 

5114101 Comm. Canned Asparagus 

5115301 Asparagus, Low Sodium, Comm. Canned 

52131­ Comm. Frozen Asparagus 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7510080 Asparagus, raw 

75202­ Asparagus, cooked 

7540101 Asparagus, creamed or with cheese 

(does not include vegetable soups; vegetables mixtures, or 

vegetable with meat mixtures) 

Lima Beans 4942­ Fresh Lima and Fava Beans (and home 

canned/froz.) 

5114204 Comm. Canned Mature Lima Beans 

5114301 Comm. Canned Green Lima Beans 

5115304 Comm. Canned Low Sodium Lima Beans 

52132­ Comm. Frozen Lima Beans 

54111­ Dried Lima Beans 

5411306 Dried Fava Beans 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures; does not include succotash) 

7510200 Lima Beans, raw 

752040­ Lima Beans, cooked 

752041­ Lima Beans, canned 

75402­ Lima Beans with sauce 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; does not include succotash) 

Cabbage 4944­ Fresh Cabbage (and home canned/froz.) 

4958601 Sauerkraut, home canned or pkgd 

5114801 Sauerkraut, comm. canned 

5114904 Comm. Canned Cabbage 

5114905 Comm. Canned Cabbage (no sauce; incl. 

baby) 

5115501 Sauerkraut, low sodium., comm. canned 

5312102 Sauerkraut Juice, comm. canned 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7510300 Cabbage, raw 

7510400 Cabbage, Chinese, raw 

7510500 Cabbage, red, raw 

7514100 Cabbage salad or coleslaw 

7514130 Cabbage, Chinese, salad 

75210­ Chinese Cabbage, cooked 

75211­ Green Cabbage, cooked 

75212­ Red Cabbage, cooked 

752130­ Savoy Cabbage, cooked 

75230­ Sauerkraut, cooked 

7540701 Cabbage, creamed 

755025­ Cabbage, pickled or in relish 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Lettuce 4945­ Fresh Lettuce, French Endive (and home 

canned/froz.) 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

75113­ Lettuce, raw 

75143­ Lettuce salad with other veg. 

7514410 Lettuce, wilted, with bacon dressing 

7522005 Lettuce, cooked 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Okra 4946­ Fresh Okra (and home canned/froz.) 

5114914 Comm. Canned Okra 

5213720 Comm. Frozen Okra 

5213721 Comm. Frozen Okra with Oth. Veg. & Sauce 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7522000 Okra, cooked, NS as to fat 

7522001 Okra, cooked, fat not added 

7522002 Okra, cooked, fat added 

7522010 Lufta, cooked (Chinese Okra) 

7541450 Okra, fried 

7550700 Okra, pickled 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Page Exposure Factors Handbook 

13B-6 September 2011 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Peas 4947­ Fresh Peas (and home canned/froz.) 

51147­ Comm Canned Peas (incl. baby) 

5115310 Low Sodium Green or English Peas (canned) 

5115314 Low Sod. Blackeyed, Gr. or Imm. Peas 

(canned) 

5114205 Blackeyed Peas, comm. canned 

52134­ Comm. Frozen Peas 

5412­ Dried Peas and Lentils 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7512000 Peas, green, raw 

7512775 Snowpeas, raw 

75223­ Peas, cowpeas, field or blackeyed, cooked 

75224­ Peas, green, cooked 

75225­ Peas, pigeon, cooked 

75231­ Snowpeas, cooked 

7541650 Pea salad 

7541660 Pea salad with cheese 

75417­ Peas, with sauce or creamed 

76409­ Peas, baby 

76411­ Peas, creamed, baby 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; includes baby foods except 

mixtures) 

Cucumbers 4952­ Fresh Cucumbers (and home canned/froz.) 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7511100 Cucumbers, raw 

75142­ Cucumber salads 

752167­ Cucumbers, cooked 

7550301 Cucumber pickles, dill 

7550302 Cucumber pickles, relish 

7550303 Cucumber pickles, sour 

7550304 Cucumber pickles, sweet 

7550305 Cucumber pickles, fresh 

7550307 Cucumber, Kim Chee 

7550311 Cucumber pickles, dill, reduced salt 

7550314 Cucumber pickles, sweet, reduced salt 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Beets 4954­ Fresh Beets (and home canned/froz.) 

51145­ Comm. Canned Beets (incl. baby) 

5115305 Low Sodium Beets (canned) 

5213714 Comm. Frozen Beets 

5312104 Beet Juice 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7510250 Beets, raw 

752080­ Beets, cooked 

752081­ Beets, canned 

7540501 Beets, harvard 

7550021 Beets, pickled 

76403­ Beets, baby 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; includes baby foods except 

mixtures) 

Strawberries 5022­ Fresh Strawberries 

5122801 Comm. Canned Strawberries with sugar 

5122802 Comm. Canned Strawberries without sugar 

5122803 Canned Strawberry Pie Filling 

5222­ Comm. Frozen Strawberries 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

6322­ Strawberries 

6413250 Strawberry Juice 

(includes baby food; except mixtures) 

Exposure Factors Handbook Page
 

September 2011 13B-7 
 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Other Berries 5033­ Fresh Berries Other than Strawberries 

5122804 Comm. Canned Blackberries with sugar 

5122805 Comm. Canned Blackberries without sugar 

5122806 Comm. Canned Blueberries with sugar 

5122807 Comm. Canned Blueberries without sugar 

5122808 Canned Blueberry Pie Filling 

5122809 Comm. Canned Gooseberries with sugar 

5122810 Comm. Canned Gooseberries without sugar 

5122811 Comm. Canned Raspberries with sugar 

5122812 Comm. Canned Raspberries without sugar 

5122813 Comm. Canned Cranberry Sauce 

5122815 Comm. Canned Cranberry-Orange Relish 

52233­ Comm. Frozen Berries (not strawberries) 

5332404 Blackberry Juice (home and comm. canned) 

5423114 Dried Berries (not strawberries) 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

6320­ Other Berries 

6321­ Other Berries 

6341101 Cranberry salad 

6410460 Blackberry Juice 

64105­ Cranberry Juice 

(includes baby food; except mixtures) 

Peaches 5036­ Fresh Peaches 

51224­ Comm. Canned Peaches (incl. baby) 

5223601 Comm. Frozen Peaches 

5332405 Home Canned Peach Juice 

5423105 Dried Peaches (baby) 

5423106 Dried Peaches 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

62116­ Dried Peaches 

63135­ Peaches 

6412203 Peach Juice 

6420501 Peach Nectar 

67108­ Peaches, baby 

6711450 Peaches, dry, baby 

(includes baby food; except mixtures) 

Pears 5037­ Fresh Pears 

51225­ Comm. Canned Pears (incl. baby) 

5332403 Comm. Canned Pear Juice, baby 

5362204 Fresh Pear Juice 

5423107 Dried Pears 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

62119­ Dried Pears 

63137­ Pears 

6341201 Pear salad 

6421501 Pear Nectar 

67109­ Pears, baby 

6711455 Pears, dry, baby 

(includes baby food; except mixtures) 

Page Exposure Factors Handbook 

13B-8 September 2011 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

EXPOSED/PROTECTED FRUITS/VEGETABLES, ROOT VEGETABLES 

Exposed Fruits 5022­ Strawberries, fresh 

5023101 Acerola, fresh 

5023401 Currants, fresh 

5031­ Apples/Applesauce, fresh 

5033­ Berries other than Strawberries, fresh 

5034­ Cherries, fresh 

5036­ Peaches, fresh 

5037­ Pears, fresh 

50381­ Apricots, Nectarines, Loquats, fresh 

5038305 Dates, fresh 

50384­ Grapes, fresh 

50386­ Plums, fresh 

50387­ Rhubarb, fresh 

5038805 Persimmons, fresh 

5038901 Sapote, fresh 

51221­ Apples/Applesauce, canned 

51222­ Apricots, canned 

51223­ Cherries, canned 

51224­ Peaches, canned 

51225­ Pears, canned 

51228­ Berries, canned 

5122903 Grapes with sugar, canned 

5122904 Grapes without sugar, canned 

5122905 Plums with sugar, canned 

5122906 Plums without sugar, canned 

5122907 Plums, canned, baby 

5122911 Prunes, canned, baby 

5122912 Prunes, with sugar, canned 

5122913 Prunes, without sugar, canned 

5122914 Raisin Pie Filling 

5222­ Frozen Strawberries 

52231­ Apples Slices, frozen 

52233­ Berries, frozen 

52234­ Cherries, frozen 

52236­ Peaches, frozen 

52239­ Rhubarb, frozen 

53321­ Canned Apple Juice 

53322­ Canned Grape Juice 

62101­ Apple, dried 

62104­ Apricot, dried 

62108­ Currants, dried 

62110­ Date, dried 

62116­ Peaches, dried 

62119­ Pears, dried 

62121­ Plum, dried 

62122­ Prune, dried 

62125­ Raisins 

63101­ Apples/applesauce 

63102­ Wi-apple 

63103­ Apricots 

63111­ Cherries, maraschino 

63112­ Acerola 

63113­ Cherries, sour 

63115­ Cherries, sweet 

63117­ Currants, raw 

63123­ Grapes 

6312601 Juneberry 

63131­ Nectarine 

63135­ Peach 

63137­ Pear 

63139­ Persimmons 

63143­ Plum 

63146­ Quince 

63147­ Rhubarb/Sapodillo 

632­ Berries 

64101­ Apple Cider 

64104­ Apple Juice 

64105­ Cranberry Juice 

64116­ Grape Juice 

64122­ Peach Juice 

64132­ Prune/Strawberry Juice 

6420101 Apricot Nectar 

64205­ Peach Nectar 

64215­ Pear Nectar 

67102­ Applesauce, baby 

67108­ Peaches, baby 

Exposure Factors Handbook Page
 

September 2011 13B-9 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Exposed Fruits 

(continued) 

5332402 Canned Prune Juice 

5332403 Canned Pear Juice 

5332404 Canned Blackberry Juice 

5332405 Canned Peach Juice 

53421­ Frozen Grape Juice 

5342201 Frozen Apple Juice, comm. fr. 

5342202 Frozen Apple Juice, home fr. 

5352101 Apple Juice, asep. packed 

5352201 Grape Juice, asep. packed 

5362101 Apple Juice, fresh 

5362202 Apricot Juice, fresh 

5362203 Grape Juice, fresh 

5362204 Pear Juice, fresh 

5362205 Prune Juice, fresh 

5421­ Dried Prunes 

5422­ Raisins, Currants, dried 

5423101 Dry Apples 

5423102 Dry Apricots 

5423103 Dates without pits 

5423104 Dates with pits 

5423105 Peaches, dry, baby 

5423106 Peaches, dry 

5423107 Pears, dry 

5423114 Berries, dry 

5423115 Cherries, dry 

(includes baby foods) 

67109­ Pears, baby 

6711450 Peaches, baby, dry 

6711455 Pears, baby, dry 

67202­ Apple Juice, baby 

6720380 White Grape Juice, baby 

67212­ Pear Juice, baby 

(includes baby foods/juices except mixtures; excludes 

fruit mixtures) 

Protected Fruits 501­ Citrus Fruits, fresh 

5021­ Cantaloupe, fresh 

5023201 Mangoes, fresh 

5023301 Guava, fresh 

5023601 Kiwi, fresh 

5023701 Papayas, fresh 

5023801 Passion Fruit, fresh 

5032­ Bananas, Plantains, fresh 

5035­ Melons other than Cantaloupe, fresh 

50382­ Avocados, fresh 

5038301 Figs, fresh 

5038302 Figs, cooked 

5038303 Figs, home canned 

5038304 Figs, home frozen 

50385­ Pineapple, fresh 

5038801 Pomegranates, fresh 

5038902 Cherimoya, fresh 

5038903 Jackfruit, fresh 

5038904 Breadfruit, fresh 

5038905 Tamarind, fresh 

5038906 Carambola, fresh 

5038907 Longan, fresh 

5121­ Citrus, canned 

51226­ Pineapple, canned 

5122901 Figs with sugar, canned 

5122902 Figs without sugar, canned 

5122909 Bananas, canned, baby 

5122910 Bananas and Pineapple, canned, baby 

5122915 Litchis, canned 

61­ Citrus Fr., Juices (incl. cit. juice mixtures) 

62107­ Bananas, dried 

62113­ Figs, dried 

62114­ Lychees/Papayas, dried 

62120­ Pineapple, dried 

62126­ Tamarind, dried 

63105­ Avocado, raw 

63107­ Bananas 

63109­ Cantaloupe, Carambola 

63110­ Cassaba Melon 

63119­ Figs 

63121­ Genip 

63125­ Guava/Jackfruit, raw 

6312650 Kiwi 

6312651 Lychee, raw 

6312660 Lychee, cooked 

63127­ Honeydew 

63129­ Mango 

63133­ Papaya 

63134­ Passion Fruit 

63141­ Pineapple 

63145­ Pomegranate 

63148­ Sweetsop, Soursop, Tamarind 

63149­ Watermelon 

64120­ Papaya Juice 

64121­ Passion Fruit Juice 

64124­ Pineapple Juice 

64133­ Watermelon Juice 

6420150 Banana Nectar 

Page Exposure Factors Handbook 

13B-10 September 2011 
 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Protected Fruits 5122916 Mangos with sugar, canned 64202­ Cantaloupe Nectar 

(continued) 5122917 Mangos without sugar, canned 

5122918 Mangos, canned, baby 

5122920 Guava with sugar, canned 

5122921 Guava without sugar, canned 

5122923 Papaya with sugar, canned 

5122924 Papaya without sugar, canned 

52232­ Bananas, frozen 

52235­ Melon, frozen 

52237­ Pineapple, frozen 

5331­ Canned Citrus Juices 

53323­ Canned Pineapple Juice 

5332408 Canned Papaya Juice 

5332410 Canned Mango Juice 

5332501 Canned Papaya Concentrate 

5341­ Frozen Citrus Juice 

5342203 Frozen Pineapple Juice 

5351­ Citrus and Citrus Blend Juices, asep. packed 

5352302 Pineapple Juice, asep. packed 

5361­ Fresh Citrus and Citrus Blend Juices 

5362206 Papaya Juice, fresh 

5362207 Pineapple-Coconut Juice, fresh 

5362208 Mango Juice, fresh 

5362209 Pineapple Juice, fresh 

5423108 Pineapple, dry 

5423109 Papaya, dry 

5423110 Bananas, dry 

5423111 Mangos, dry 

5423117 Litchis, dry 

5423118 Tamarind, dry 

5423119 Plantain, dry 

(includes baby foods) 

64203­ Guava Nectar 

64204­ Mango Nectar 

64210­ Papaya Nectar 

64213­ Passion Fruit Nectar 

64221­ Soursop Nectar 

6710503 Bananas, baby 

6711500 Bananas, baby, dry 

6720500 Orange Juice, baby 

6721300 Pineapple Juice, baby 

(includes baby foods/juices except mixtures; excludes fruit 

mixtures) 

Exposure Factors Handbook Page
 

September 2011 13B-11
 
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Exposed Veg. 491­ Fresh Dark Green Vegetables 

493­ Fresh Tomatoes 

4941­ Fresh Asparagus 

4943­ Fresh Beans, Snap or Wax 

4944­ Fresh Cabbage 

4945­ Fresh Lettuce 

4946­ Fresh Okra 

49481­ Fresh Artichokes 

49483­ Fresh Brussel Sprouts 

4951­ Fresh Celery 

4952­ Fresh Cucumbers 

4955­ Fresh Cauliflower 

4958103 Fresh Kohlrabi 

4958111 Fresh Jerusalem Artichokes 

4958112 Fresh Mushrooms 

4958113 Mushrooms, home canned 

4958114 Mushrooms, home frozen 

4958118 Fresh Eggplant 

4958119 Eggplant, cooked 

4958120 Eggplant, home frozen 

4958200 Fresh Summer Squash 

4958201 Summer Squash, cooked 

4958202 Summer Squash, home canned 

4958203 Summer Squash, home frozen 

4958402 Fresh Bean Sprouts 

4958403 Fresh Alfalfa Sprouts 

4958504 Bamboo Shoots 

4958506 Seaweed 

4958508 Tree Fern, fresh 

4958601 Sauerkraut 

5111­ Dark Green Vegetables (all are exposed) 

5113­ Tomatoes 

5114101 Asparagus, comm. canned 

51144­ Beans, green, snap, yellow, comm. canned 

5114704 Snow Peas, comm. canned 

5114801 Sauerkraut, comm. canned 

5114901 Artichokes, comm. canned 

5114902 Bamboo Shoots, comm. canned 

5114903 Bean Sprouts, comm. canned 

5114904 Cabbage, comm. canned 

5114905 Cabbage, comm. canned, no sauce 

5114906 Cauliflower, comm. canned, no sauce 

5114907 Eggplant, comm. canned, no sauce 

5114913 Mushrooms, comm. canned 

5114914 Okra, comm. canned 

5114918 Seaweeds, comm. canned 

5114920 Summer Squash, comm. canned 

721­ Dark Green Leafy Veg. 

722­ Dark Green Non-Leafy Veg. 

74­ Tomatoes and Tomato Mixtures 

7510050 Alfalfa Sprouts 

7510075 Artichoke, Jerusalem, raw 

7510080 Asparagus, raw 

75101­ Beans, sprouts and green, raw 

7510275 Brussel Sprouts, raw 

7510280 Buckwheat Sprouts, raw 

7510300 Cabbage, raw 

7510400 Cabbage, Chinese, raw 

7510500 Cabbage, Red, raw 

7510700 Cauliflower, raw 

7510900 Celery, raw 

7510950 Chives, raw 

7511100 Cucumber, raw 

7511120 Eggplant, raw 

7511200 Kohlrabi, raw 

75113­ Lettuce, raw 

7511500 Mushrooms, raw 

7511900 Parsley 

7512100 Pepper, hot chili 

75122­ Peppers, raw 

7512750 Seaweed, raw 

7512775 Snowpeas, raw 

75128­ Summer Squash, raw 

7513210 Celery Juice 

7514100 Cabbage or Cole Slaw 

7514130 Chinese Cabbage Salad 

7514150 Celery with cheese 

75142­ Cucumber salads 

75143­ Lettuce salads 

7514410 Lettuce, wilted with bacon dressing 

7514600 Greek salad 

7514700 Spinach salad 

7520600 Algae, dried 

75201­ Artichoke, cooked 

75202­ Asparagus, cooked 

75203­ Bamboo Shoots, cooked 

752049­ Beans, string, cooked 

75205­ Beans, green, cooked/canned 

75206­ Beans, yellow, cooked/canned 

75207­ Bean Sprouts, cooked 

752085­ Breadfruit 

752090­ Brussel Sprouts, cooked 

75210­ Cabbage, Chinese, cooked 

75211­ Cabbage, green, cooked 

Page Exposure Factors Handbook 

13B-12 September 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Exposed Veg. 5114923 Chinese or Celery Cabbage, comm. canned 75212­ Cabbage, red, cooked 

(cont.) 51152­ Tomatoes, canned, low sod. 

5115301 Asparagus, canned, low sod. 

5115302 Beans, Green, canned, low sod. 

5115303 Beans, Yellow, canned, low sod. 

5115309 Mushrooms, canned, low sod. 

51154­ Greens, canned, low sod. 

5115501 Sauerkraut, low sodium 

5211­ Dark Gr. Veg., comm. frozen (all exp.) 

52131­ Asparagus, comm. froz. 

52133­ Beans, snap, green, yellow, comm. froz. 

5213407 Peapods, comm. froz. 

5213408 Peapods, with sauce, comm. froz. 

5213409 Peapods, with other veg., comm. froz. 

5213701 Brussel Sprouts, comm. froz. 

5213702 Brussel Sprouts, comm. froz. with cheese 

5213703 Brussel Sprouts, comm. froz. with other veg. 

5213705 Cauliflower, comm. froz. 

5213706 Cauliflower, comm. froz. with sauce 

5213707 Cauliflower, comm. froz. with other veg. 

5213708 Caul., comm. froz. with other veg. & sauce 

5213709 Summer Squash, comm. froz. 

5213710 Summer Squash, comm. froz. with other veg. 

5213716 Eggplant, comm. froz. 

5213718 Mushrooms with sauce, comm. froz. 

5213719 Mushrooms, comm. froz. 

5213720 Okra, comm. froz. 

5213721 Okra, comm. froz., with sauce 

5311­ Canned Tomato Juice and Tomato Mixtures 

5312102 Canned Sauerkraut Juice 

5321­ Frozen Tomato Juice 

5371­ Fresh Tomato Juice 

5381102 Aseptically Packed Tomato Juice 

5413101 Dry Algae 

5413102 Dry Celery 

5413103 Dry Chives 

5413109 Dry Mushrooms 

5413111 Dry Parsley 

5413112 Dry Green Peppers 

5413113 Dry Red Peppers 

5413114 Dry Seaweed 

5413115 Dry Tomatoes 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

752130­ Cabbage, savoy, cooked 

75214­ Cauliflower 

75215­ Celery, Chives, Christophine (chayote) 

752167­ Cucumber, cooked 

752170­ Eggplant, cooked 

752171­ Fern shoots 

752172­ Fern shoots 

752173­ Flowers of sesbania, squash or lily 

7521801 Kohlrabi, cooked 

75219­ Mushrooms, cooked 

75220­ Okra/lettuce, cooked 

7522116 Palm Hearts, cooked 

7522121 Parsley, cooked 

75226­ Peppers, pimento, cooked 

75230­ Sauerkraut, cooked/canned 

75231­ Snowpeas, cooked 

75232­ Seaweed 

75233­ Summer Squash 

7540050 Artichokes, stuffed 

7540101 Asparagus, creamed or with cheese 

75403­ Beans, green with sauce 

75404­ Beans, yellow with sauce 

7540601 Brussel Sprouts, creamed 

7540701 Cabbage, creamed 

75409­ Cauliflower, creamed 

75410­ Celery/Chiles, creamed 

75412­ Eggplant, fried, with sauce, etc. 

75413­ Kohlrabi, creamed 

75414­ Mushrooms, Okra, fried, stuffed, creamed 

754180­ Squash, baked, fried, creamed, etc. 

7541822 Christophine, creamed 

7550011 Beans, pickled 

7550051 Celery, pickled 

7550201 Cauliflower, pickled 

755025­ Cabbage, pickled 

7550301 Cucumber pickles, dill 

7550302 Cucumber pickles, relish 

7550303 Cucumber pickles, sour 

7550304 Cucumber pickles, sweet 

7550305 Cucumber pickles, fresh 

7550307 Cucumber, Kim Chee 

7550308 Eggplant, pickled 

7550311 Cucumber pickles, dill, reduced salt 

7550314 Cucumber pickles, sweet, reduced salt 

7550500 Mushrooms, pickled 

7550700 Okra, pickled 

75510­ Olives 

7551101 Peppers, hot 

7551102 Peppers, pickled 

7551301 Seaweed, pickled 

7553500 Zucchini, pickled 

76102­ Dark Green Veg., baby 

76401­ Beans, baby (excl. most soups & mixtures) 

Exposure Factors Handbook Page
 

September 2011 13B-13 
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Protected Veg. 4922­ Fresh Pumpkin, Winter Squash 

4942­ Fresh Lima Beans 

4947­ Fresh Peas 

49482­ Fresh Soy Beans 

4956­ Fresh Corn 

4958303 Succotash, home canned 

4958304 Succotash, home frozen 

4958401 Fresh Cactus (prickly pear) 

4958503 Burdock 

4958505 Bitter Melon 

4958507 Horseradish Tree Pods 

51122­ Comm. Canned Pumpkin and Squash (baby) 

51142­ Beans, comm. canned 

51143­ Beans, lima and soy, comm. canned 

51146­ Corn, comm. canned 

5114701 Peas, green, comm. canned 

5114702 Peas, baby, comm. canned 

5114703 Peas, blackeyed, comm. canned 

5114705 Pigeon Peas, comm. canned 

5114919 Succotash, comm. canned 

5115304 Lima Beans, canned, low sod. 

5115306 Corn, canned, low sod. 

5115307 Creamed Corn, canned, low sod. 

511531­ Peas and Beans, canned, low sod. 

52122­ Winter Squash, comm. froz. 

52132­ Lima Beans, comm. froz. 

5213401 Peas, gr., comm. froz. 

5213402 Peas, gr., with sauce, comm. froz. 

5213403 Peas, gr., with other veg., comm. froz. 

5213404 Peas, gr., with other veg., comm. froz. 

5213405 Peas, blackeyed, comm. froz. 

5213406 Peas, blackeyed, with sauce, comm. froz. 

52135­ Corn, comm. froz. 

5213712 Artichoke Hearts, comm. froz. 

5213713 Baked Beans, comm. froz. 

5213717 Kidney Beans, comm. froz. 

5213724 Succotash, comm. froz. 

5411­ Dried Beans 

5412­ Dried Peas and Lentils 

5413104 Dry Corn 

5413106 Dry Hominy 

5413504 Dry Squash, baby 

5413603 Dry Creamed Corn, baby 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

732­ Pumpkin 

733­ Winter Squash 

7510200 Lima Beans, raw 

7510550 Cactus, raw 

7510960 Corn, raw 

7512000 Peas, raw 

7520070 Aloe vera juice 

752040­ Lima Beans, cooked 

752041­ Lima Beans, canned 

7520829 Bitter Melon 

752083­ Bitter Melon, cooked 

7520950 Burdock 

752131­ Cactus 

752160­ Corn, cooked 

752161­ Corn, yellow, cooked 

752162­ Corn, white, cooked 

752163­ Corn, canned 

7521749 Hominy 

752175­ Hominy 

75223­ Peas, cowpeas, field or blackeyed, cooked 

75224­ Peas, green, cooked 

75225­ Peas, pigeon, cooked 

75301­ Succotash 

75402­ Lima Beans with sauce 

75411­ Corn, scalloped, fritter, with cream 

7541650 Pea salad 

7541660 Pea salad with cheese 

75417­ Peas, with sauce or creamed 

7550101 Corn relish 

76205­ Squash, yellow, baby 

76405­ Corn, baby 

76409­ Peas, baby 

76411­ Peas, creamed, baby 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Page Exposure Factors Handbook 

13B-14 September 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Root Vegetables 48­ Potatoes, Sweetpotatoes 

4921­ Fresh Carrots 

4953­ Fresh Onions, Garlic 

4954­ Fresh Beets 

4957­ Fresh Turnips 

4958101 Fresh Celeriac 

4958102 Fresh Horseradish 

4958104 Fresh Radishes, no greens 

4958105 Radishes, home canned 

4958106 Radishes, home frozen 

4958107 Fresh Radishes, with greens 

4958108 Fresh Salsify 

4958109 Fresh Rutabagas 

4958110 Rutabagas, home frozen 

4958115 Fresh Parsnips 

4958116 Parsnips, home canned 

4958117 Parsnips, home frozen 

4958502 Fresh Lotus Root 

4958509 Ginger Root 

4958510 Jicama, including yambean 

51121­ Carrots, comm. canned 

51145­ Beets, comm. canned 

5114908 Garlic Pulp, comm. canned 

5114910 Horseradish, comm. prep. 

5114915 Onions, comm. canned 

5114916 Rutabagas, comm. canned 

5114917 Salsify, comm. canned 

5114921 Turnips, comm. canned 

5114922 Water Chestnuts, comm. canned 

51151­ Carrots, canned, low sod. 

5115305 Beets, canned, low sod. 

5115502 Turnips, low sod. 

52121­ Carrots, comm. froz. 

5213714 Beets, comm. froz. 

5213722 Onions, comm. froz. 

5213723 Onions, comm. froz., with sauce 

5213725 Turnips, comm. froz. 

5312103 Canned Carrot Juice 

5312104 Canned Beet Juice 

5372102 Fresh Carrot Juice 

5413105 Dry Garlic 

5413110 Dry Onion 

5413502 Dry Carrots, baby 

5413503 Dry Sweet Potatoes, baby 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

71­ White Potatoes and Puerto Rican St. Veg. 

7310­ Carrots 

7311140 Carrots in sauce 

7311200 Carrot chips 

734­ Sweetpotatoes 

7510250 Beets, raw 

7511150 Garlic, raw 

7511180 Jicama (yambean), raw 

7511250 Leeks, raw 

75117­ Onions, raw 

7512500 Radish, raw 

7512700 Rutabaga, raw 

7512900 Turnip, raw 

752080­ Beets, cooked 

752081­ Beets, canned 

7521362 Cassava 

7521740 Garlic, cooked 

7521771 Horseradish 

7521850 Lotus root 

752210­ Onions, cooked 

7522110 Onions, dehydrated 

752220­ Parsnips, cooked 

75227­ Radishes, cooked 

75228­ Rutabaga, cooked 

75229­ Salsify, cooked 

75234­ Turnip, cooked 

75235­ Water Chestnut 

7540501 Beets, harvard 

75415­ Onions, creamed, fried 

7541601 Parsnips, creamed 

7541810 Turnips, creamed 

7550021 Beets, pickled 

7550309 Horseradish 

7551201 Radishes, pickled 

7553403 Turnip, pickled 

76201­ Carrots, baby 

76209­ Sweetpotatoes, baby 

76403­ Beets, baby 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

USDA SUBCATEGORIES 

Dark Green 491­ Fresh Dark Green Vegetables 72­ Dark Green Vegetables 

Vegetables 5111­ Comm. Canned Dark Green Veg. 

51154­ Low Sodium Dark Green Veg. 

5211­ Comm. Frozen Dark Green Veg. 

5413111 Dry Parsley 

5413112 Dry Green Peppers 

5413113 Dry Red Peppers 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures/dinners; excludes vegetable juices and dried 

vegetables) 

all forms 

leafy, nonleafy, dk. gr. veg. soups 

Exposure Factors Handbook Page
 

September 2011 13B-15 
 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 13—Intake of Home-Produced Foods 

Table 13B-1. Food Codes and Definitions for Individual Food Items Used in Analysis of the 1987–1988 

USDA NFCS Household Data to Estimate Fraction of Food Intake That Is Home-Produced (continued) 

Food Product Household Code/Definition Individual Code 

Deep Yellow 492­ Fresh Deep Yellow Vegetables 73­ Deep Yellow Vegetables 

Vegetables 5112­ Comm. Canned Deep Yellow Veg. 

51151­ Low Sodium Carrots 

5212­ Comm. Frozen Deep Yellow Veg. 

5312103 Carrot Juice 

54135­ Dry Carrots, Squash, Sw. Potatoes 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures/dinners; excludes vegetable juices and dried 

vegetables) 

all forms 

carrots, pumpkin, squash, sweet potatoes, dp. yell. veg. 

soups 

Other 494­ Fresh Light Green Vegetables 75­ Other Vegetables 

Vegetables 495­ Fresh Other Vegetables 

5114­ Comm. Canned Other Veg. 

51153­ Low Sodium Other Veg. 

51155­ Low Sodium Other Veg. 

5213­ Comm. Frozen Other Veg. 

5312102 Sauerkraut Juice 

5312104 Beet Juice 

5411­ Dried Beans 

5412­ Dried Peas, Lentils 

541310­ Dried Other Veg. 

5413114 Dry Seaweed 

5413603 Dry Cr. Corn, baby 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures/dinners; excludes vegetable juices and dried 

vegetables) 

all forms 

Citrus Fruits 501­ Fresh Citrus Fruits 

5121­ Comm. Canned Citrus Fruits 

5331­ Canned Citrus and Citrus Blend Juice 

5341­ Frozen Citrus and Citrus Blend Juice 

5351­ Aseptically Packed Citrus and Citr. Blend 

Juice 

5361­ Fresh Citrus and Citrus Blend Juice 

(includes baby foods; excludes dried fruits) 

61­ Citrus Fruits and Juices 

6720500 Orange Juice, baby food 

6720600 Orange-Apricot Juice, baby food 

6720700 Orange-Pineapple Juice, baby food 

6721100 Orange-Apple-Banana Juice, baby food 

(excludes dried fruits) 

Other Fruits 502­ Fresh Other Vitamin C-Rich Fruits 

503­ Fresh Other Fruits 

5122­ Comm. Canned Fruits Other than Citrus 

5222­ Frozen Strawberries 

5223­ Frozen Other than Citr. or Vitamin C-Rich Fr. 

5332­ Canned Fruit Juice Other than Citrus 

5342­ Frozen Juices Other than Citrus 

5352­ Aseptically Packed Fruit Juice Other than 

Citr. 

5362­ Fresh Fruit Juice Other than Citrus 

542­ Dry Fruits 

(includes baby foods; excludes dried fruits) 

62­ Dried Fruits 

63­ Other Fruits 

64­ Fruit Juices and Nectars Excluding Citrus 

671­ Fruits, baby 

67202­ Apple Juice, baby 

67203­ Baby Juices 

67204­ Baby Juices 

67212­ Baby Juices 

67213­ Baby Juices 

673­ Baby Fruits 

674­ Baby Fruits 

Page Exposure Factors Handbook 

13B-16 September 2011 
Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Exposure Factors Handbook Page
 

September 2011 14-1 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

14. TOTAL FOOD INTAKE 

14.1. INTRODUCTION 

The U.S. food supply is generally considered to 

be one of the safest in the world. Nevertheless, 

contamination of foods may occur as a result of 

environmental pollution of the air, water, or soil, or 

the intentional use of chemicals such as pesticides or 

other agrochemicals. Ingestion of contaminated foods 

is a potential pathway of exposure to such 

contaminants. To assess chemical exposure through 

this pathway, information on food ingestion rates is 

needed. Chapters 9 through 13 of this handbook 

report per capita and consumer-only data on food 

consumption rates for various food items and food 

categories. These intake rates were estimated by the 

U.S. Environmental Protection Agency (EPA) using 

databases developed by the U.S. Department of 

Agriculture (USDA). U.S. EPA (2007) expanded the 

analysis of food intake in order to examine 

individuals’ food consumption habits in greater 

detail. Using data from the USDA’s Continuing 

Survey of Food Intake by Individuals (CSFII) 

conducted in 1994−1996 and 1998, U.S. EPA (2007) 

derived distributions to characterize (1) the total food 

intake among various groups in the U.S. population, 

subdivided by age, race, geographic region, and 

urbanization; (2) the contribution of various food 

categories (e.g., meats, grains, vegetables, etc.) to 

total food intake among these populations; and 

(3) the contribution of various food categories to total 

food intake among individuals exhibiting low- or 

high-end consumption patterns of a specific food 

category (e.g., individuals below the 10th percentile 

or above the 90th percentile for fish consumption). 

These data may be useful for assessing exposure 

among populations exhibiting lower or higher than 

usual intake of certain types of foods (e.g., people 

who eat little or no meat, or people who eat large 

quantities of fish). Recently, U.S. EPA’s Office of 

Pesticide Programs (OPP) used data from the 2003 to 

2006 National Health and Nutrition Examination 

Survey (NHANES) to estimate intake of various 

foods, including total foods. 

The recommendations for total food intake rates 

are provided in the next section, along with a 

summary of the confidence ratings for these 

recommendations. Following the recommendations, 

the studies on total food intake are summarized. 

14.2. RECOMMENDATIONS 

Table 14-1 presents a summary of recommended 

values for total food intake. Table 14-2 presents the 

confidence ratings for these recommendations. The 

recommended total food intake rates are based on 

data from the U.S. EPA/OPP’s recent analysis of 

NHANES data from 2003 to 2006. For information 

about the proportion of total intake represented by the 

major food groups, it is recommended that the data 

based on a re-analysis of the data from U.S. EPA 

(2007) be used. Section 14.4 describes this reanalysis, and Table 14-3 through Table 14-11 provide 

the data. However, it should be noted that, because 

the U.S. EPA (2007) data are based on 1994−1996 

and 1998 CSFII data, they may not reflect recent 

changes that may have occurred in consumption 

patterns. 

Both of the studies of total dietary intake 

presented in this chapter are based on data collected 

over a 2-day period and may not necessarily reflect 

the long-term distribution of average daily intake 

rates. However, because the broad categories of foods 

used in this analysis (e.g., total foods, total fruits, 

total vegetables, etc.) are typically eaten on a daily 

basis throughout the year with minimal seasonality, 

the short-term distribution may be a reasonable 

approximation of the long-term distribution, although 

it will display somewhat increased variability. This 

implies that the upper percentiles shown here will 

tend to overestimate the corresponding percentiles of 

the true long-term distribution. 
 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 

14-2 September 2011 

Table 14-1. Recommended Values for Per Capita Total Food Intake, Edible Portion, Uncooked Weight 

Age Group (years) Mean 95th Percentile Multiple 

Percentiles Source g/kg-day 

Children 

Birth to <1 91 208c 

See Table 14-12 U.S. EPA/OPP analysis 

of NHANES 2003−2006 

1 to <3 113 185c 

3 to <6 79 137 

6 to <11a 47 92 

11 to <16b 28 56 

16 to <21b 28 56 

Adults 

21 to <50 29 63 

≥50 29 59 a Based on data for ages 6 to <13 years. b Based on data for ages 13 to <20 years. 

14.2.1. * c Estimates are less statistically reliable based on guidance published in the Joint Policy 

on Variance Estimation and Statistical Reporting Standards on NHANES III and CSFII Reports: 

NHIS/NCHS Analytical Working Group Recommendations (NCHS, 1993). 

Note: Total food intake was defined as intake of the sum of all foods, beverages, and water ingested. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Exposure Factors Handbook Page
 

September 2011 14-3 

Table 14-2. Confidence in Recommendations for Total Food Intake 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodologies were adequate and the analytical approaches 

were competently executed. The study sizes were very large; sample 

sizes varied with age. The response rates were good. The studies 

analyzed primary data on recall of ingestion. 

No direct measurements were taken. The studies relied on survey data. 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The analyses were specifically designed to address food intake. 

The populations studied were representative of the U.S. population. 

The data used were the most current data publicly available at the time the 

analysis was conducted for the handbook. However, the data used in the 

re-analysis of the U.S. EPA study are now 11−15 years old. The national 

trends in bodyweight,(increasing obesity prevalence) may in part be due 

to changes in food intake patterns. 

Ingestion rates were estimated based on short-term data collected in the 

CSFII 1994−1996, 1998 and NHANES 2003−2006. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The NHANES and CSFII data are publicly available. The U.S. EPA 

(2007) report is available online. 

The methodology was clearly presented; enough information was 

included to reproduce results. 

NHANES and CSFII follow strict QA/QC procedures. U.S. EPA’s 

analysis of NHANES data has only been reviewed internally, but the 

methodology has been used in an analysis of previous data. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Short term distributions of total intake were provided. The survey was 

not designed to capture long-term day-to-day variability. 

The survey data were based on recall over a 2-day period. The 

U.S. EPA/OPP analysis of NHANES data included all foods, beverages, 

and water ingested. Beverages, sugar, candy, and sweets, and nuts and nut 

products were not included in the re-analysis of the U.S. EPA (2007) data. 

There is also some uncertainty associated with the translation of mixed 

foods (i.e., recipes) to food commodity ingredients in both studies. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The USDA CSFII survey received a high level of peer review. The 

U.S. EPA (2007) analysis was also peer reviewed; however, the 

re-analysis of these data using the new age categories for children was not 

peer reviewed outside the Agency. The methodology used in the 

NHANES 2003−2006 analysis is the same as used in previous peerreviewed analysis conducted by U.S. EPA/OPP. 

Two studies were available for this factor. 

Medium 

Overall Rating Medium 
 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

14.3.	 STUDIES OF TOTAL FOOD INTAKE 

14.4.	 U.S. EPA Re−Analysis of 1994−1996, 

1998 Continuing Survey of Food Intake 

by Individuals (CSFII), Based on 

U.S. EPA (2007)―Analysis of Total Food 

Intake and Composition of Individual’s 

Diet Based on U.S. Department of 

Agriculture’s (USDA’s) 1994−1996, 1998 

CSFII 

U.S. EPA’s National Center for Environmental 

Assessment (NCEA) conducted an analysis to 

evaluate the total food intake of individuals in the 

United States using data from the USDA’s 

1994−1996, 1998 CSFII (USDA, 2000) and 

U.S. EPA’s Food Commodity Intake Database 

(FCID) (U.S. EPA, 2000). The 1994−1996 CSFII and 

its 1998 Supplemental Children’s Survey were 

designed to obtain data from a statistically 

representative sample of non-institutionalized 

persons living in the United States. Survey 

participants were selected using a multistage process. 

The respondents were interviewed twice to collect 

information on food consumption during

2 non-consecutive days. For both survey days, data 

were collected by an in-home interviewer. The Day 2 

interview was conducted 3 to10 days later and on a 

different day of the week. Of the more than 

20,000 individuals surveyed, approximately 10,000 

were under 21 years of age, and approximately 9,000 

were under the age of 11. The 1994−1996 survey and 

1998 supplement are referred to collectively as CSFII 

1994−1996, 1998. Each individual in the survey was 

assigned a sample weight based on his or her 

demographic data; these weights were taken into 

account when calculating mean and percentile values 

of food consumption for the various demographic 

categories that were analyzed in the study. The 

sample weighting process used in the CSFII 

1994−1996, 1998 is discussed in detail in USDA 

(2000). 

For the analysis of total food intake, food 

commodity codes provided in U.S. EPA’s FCID 

(U.S. EPA, 2000) were used to translate as-eaten 

foods (e.g., beef stew) identified by USDA food 

codes in the CSFII data set into food commodities 

(e.g., beef, potatoes, carrots, etc.). The method used 

to translate USDA food codes into U.S. EPA 

commodity codes is discussed in detail in USDA 

(2000). The U.S. EPA commodity codes were 

assigned to broad food categories (e.g., total meats, 

total vegetables, etc.) for use in the analysis. Total 

food intake was defined as intake of the sum of all 

foods in the following major food categories: dairy, 

meats, fish, eggs, grains, vegetables, fruits, and fats. 

Beverages, sugar, candy, and sweets, and nuts (and 

nut products) were not included because they could 

not be categorized into the major food groups. Also, 

human milk intake was not included. Percent 

consuming, mean, standard error, and a range of 

percentile values were calculated on the basis of 

grams of food per kilogram of body weight per day 

(g/kg-day) and on the basis of grams per day (g/day). 

In addition to total food intake, intake of the various 

major food groups for the various age groups in units 

of g/day and g/kg-day were also estimated for 

comparison to total intake. 

To evaluate variability in the contributions of the 

major food groups to total food intake, individuals 

were ranked from lowest to highest, based on total 

food intake. Three subsets of individuals were 

defined, as follows: a group at the low end of the 

distribution of total intake (below the 10th percentile 

of total intake), a mid-range or central group (the 45th 

to 55th percentile of total intake), and a group at the 

high end of the distribution of total intake (above the 

90th percentile of total intake). Mean total food intake 

(in g/day and g/kg-day), mean intake of each of the 

major food groups (in g/day and g/kg-day), and the 

percent of total food intake that each of these food 

groups represents were calculated for each of the 

three populations (i.e., individuals with low-end, 

central, and high-end total food intake). A similar 

analysis was conducted to estimate the contribution 

of the major food groups to total food intake for 

individuals at the low-end, central, and high-end of 

the distribution of total meat intake, total dairy 

intake, total meat and dairy intake, total fish intake, 

and total fruit and vegetable intake. For example, to 

evaluate the variability in the diets of individuals at 

the low-end, mid-range, and high-end of the 

distribution of total meat intake, survey individuals 

were ranked according to their reported total meat 

intake. Three subsets of individuals were formed as 

described above. Mean total food intake, intake of the 

major food groups, and the percent of total food 

intake represented by each of the major food groups 

were tabulated. U.S. EPA (2007) presented the 

results of the analysis for the following age groups: 

<1 year, 1 to 2 years, 3 to 5 years, 6 to 11 years, 12 to 

19 years, 20 to 39 years, 40 to 69 years, and 70 years 

and older. The data were tabulated in units of 

g/kg-day and g/day. 

The analysis presented in U.S. EPA (2007) was 

conducted before U.S. EPA published the guidance 

entitled Selecting Age Groups for Monitoring and 

Assessing Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005). As a result, the age 

groups used for children in U.S. EPA (2007) were not 

Page Exposure Factors Handbook 

14-4 September 2011 
Exposure Factors Handbook 

Chapter 14—Total Food Intake 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

entirely consistent with the age groups recommended 

in the 2005 guidance. In order to conform to the 

standard age categories for children recommended in 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005), each 

of the tables from U.S. EPA (2007) was modified by 

re-analyzing the source data and applying the new 

childhood age categories (i.e., <1 month, 1 to 

<3 months, 3 to <6 months, 6 to <12 months, 1 to 

<2 years, 2 to <3 years, 3 to <6 years, 6 to <11 years, 

11 to <16 years, and 16 to <21 years). Table 14-3 

presents distributions of total food intake in units of 

g/day and g/kg-day. Table 14-4 and Table 14-5 

compare total food intake to intake of the various 

major food groups for the various age groups in units 

of g/day and g/kg-day, respectively. It should be 

noted that some U.S. EPA commodity codes are 

listed under more than one food category. For this 

reason, in the tables, the intake rates for the 

individual food categories do not necessarily add up 

to the figure given for total food intake (U.S. EPA, 

2007). Also, data are not reported for food groups for 

which there were less than 20 consumers in a 

particular age group. Table 14-6 through Table 14-11 

present the contributions of the major food groups to 

total food intake for individuals (in the various age 

groups) at the low-end, central, and high-end of the 

distribution of total food intake (see Table 14-6), total 

meat intake (see Table 14-7), total meat and dairy 

intake (see Table 14-8), total fish intake (see Table 

14-9), total fruit and vegetable intake (see Table 

14-10), and total dairy intake (see Table 14-11) in 

units of g/day and g/kg-day. For each of the 

three classes of consumers, consumption of 

nine different food categories is presented (i.e., total 

foods, dairy, meats, fish, eggs, grains, vegetables, 

fruits, and fats). For example, in Table 14-9 one will 

find the mean consumption of meats, eggs, 

vegetables, etc. for individuals with an unusually 

high (or low or average) consumption of fish. 

As discussed in previous chapters, the 

1994−1996, 1998 CSFII data have both advantages 

and limitations with regard to estimating food intake 

rates. The large sample size (more than 

20,000 persons) is sufficient to allow categorization 

within narrowly defined age categories. In addition, 

the survey was designed to obtain a statistically valid 

sample of the entire U.S. population that included 

children and low income groups. However, the 

survey design is of limited utility for assessing small 

and potentially at-risk populations based on ethnicity, 

medical status, geography, or other factors (such as 

activity level). Another limitation is that data are 

based on a 2-day survey period and, as such, may not 

accurately reflect long-term eating patterns. This is 

particularly true for the extremes of the distribution 

of food intake. 

14.4.1.	 U.S. EPA Analysis of National Health and 

Nutrition Examination Survey 

(NHANES) 2003−2006 Data 

U.S. EPA/OPP used data from the 2003 to 2006 

NHANES to estimate intake of various individual 

foods, major food groups, and total foods. This 

chapter presents the data for total foods (Chapter 9 

provides data on the intake of fruits and vegetables; 

Chapter 11 provides data on intake of meat, dairy 

products, and fats, and Chapter 12 provides data on 

intake of grain and grain products). The total intake 

rates presented here represent intake of all forms of 

foods eaten (e.g., both home produced and 

commercially produced). Individuals who provided 

data for 2 days of the survey were included in the 

intake estimates. Individuals who did not provide 

information on body weight or for whom identifying 

information was unavailable were excluded from the 

analysis. The U.S. EPA/OPP analysis of 2003−2006 

NHANES data included all foods, beverages, and 

water ingested. Two-day average intake rates were 

calculated for all individuals in the database for each 

of the food items/groups. These average daily intake 

rates were divided by each individual's reported body 

weight to generate intake rates in units of grams per 

kilogram of body weight per day (g/kg-day). The data 

were weighted according to the 4-year, 2-day sample 

weights provided in the 2003−2006 NHANES to 

adjust the data for the sample population to reflect the 

national population. 

Intake data from the NHANES were based on 

uncooked forms of the edible portion of the food 

items/groups. Summary statistics, including: number 

of individuals represented in the estimates, mean 

intake rate, and standard error of the mean intake rate 

were calculated for total foods. Percentiles of the 

intake rate distribution (i.e., 1st, 5th, 10th, 25th, 50th, 

75th, 90th, 95th, 99th, and the maximum value) were 

also provided. The data represent per capita data. 

However, the intake rates are the same as those for 

consumers only because all survey respondents ate 

some type of food during the survey period. Data 

were provided for the following age groups: <1 year, 

1 to <3 years, 3 to <6 years, 6 to <13 years, 13 to 

<20 years, 20 to <50 years, ≥50 years, females 

only―13 to 49 years, and all ages combined. Data 

were also generated for various racial/ethnic groups 

(i.e., Mexican American, non-Hispanic Black, 

non-Hispanic White, other Hispanic, and other race). 

Table 14-12 presents intake data for total foods in 

Exposure Factors Handbook Page
 

September 2011 14-5 
 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

g/kg-day from the 2003−2006 NHANES analysis for 

these age groups and racial/ethnic groups. 

The strength of U.S. EPA’s analysis is that it 

provides distributions of total food intake for various 

age groups of children and adults, normalized by 

body weight. The analysis uses the 2003−2006 

NHANES data set, which was designed to be 

representative of the U.S. population. The data set 

includes 4 years of intake data combined, and is 

based on a 2-day survey period. Because these data 

were developed for use in U.S. EPA’s pesticide 

registration program, the childhood age groups used 

are slightly different than those recommended in 

U.S. EPA’s Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). 

However, given the similarities in the age groups 

used, the data should provide suitable intake 

estimates for the age groups of interest. The data for 

infants <12 months could not be separated out into 

the recommended age groups due to sample size 

limitations. This analysis generated data for total 

foods only. Analyses to estimate the proportion of 

total food intake represented by the various food 

groups were not conducted for this data set. 

14.5. REFERENCES FOR CHAPTER 14 

NCHS (National Center for Health Statistics). (1993). 

Joint policy on variance estimation and 

statistical reporting standards on NHANES 

III and CSFII reports: HNIS/NCHS Analytic 

Working Group recommendations. 

Riverdale, MD: Human Nutrition 

Information Service (HNIS)/Analytic 

Working Group. Agricultural Research 

Service, Survey Systems/Food Consumption 

Laboratory. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000). Food commodity intake database 

[Database]. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2007). Analysis of total food intake and 

composition of individual's diet based on the 

USDA's 1994-1996, 1998 continuing survey 

of food intakes by individuals (CSFII) [EPA 

Report]. (EPA/600/R-05/062F). Washington, 

DC. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=132173. 

USDA (U.S. Department of Agriculture). (2000). 

1994-1996, 1998 continuing survey of food 

intakes by individuals (CSFII). Beltsville, 

MD: Agricultural Research Service, 

Beltsville Human Nutrition Research Center. 

Page Exposure Factors Handbook 

14-6 September 2011 
Table 14-3. Per Capita Total Food Intake, Edible Portion, Uncookeda 

Age Group N b cons.

N 

Totalc 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Total Food Intake (g/day) 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

21 to <40 years 

40 to <70 years 

70 years and older 

59 

183 

385 

676 

1,002 

994 

4,112 

1,553 

975 

743 

2,950 

4,818 

1,393 

88 

245 

411 

678 

1,002 

994 

4,112 

1,553 

975 

743 

2,950 

4,818 

1,393 

67.0 

74.7 

93.7 

99.7 

100 

100 

100 

100 

100 

100 

100 

100 

100 

67 

80 

197 

507 

1,039 

1,024 

1,066 

1,118 

1,209 

1,184 

1,100 

1,100 

1,000 

59 

70 

150 

344 

407 

377 

380 

372 

499 

634 

518 

468 

430 

0 

0 

0 

34 

216 

312 

416 

438 

343 

308 

-

-

-

0 

0 

0 

141 

414 

491 

548 

586 

536 

467 

493 

472 

449 

0 

0 

12 

191 

570 

575 

629 

680 

657 

556 

579 

567 

549 

0 

0 

100 

283 

770 

752 

805 

846 

851 

750 

778 

766 

741 

67 

94 

167 

413 

998 

994 

1,020 

1,052 

1,124 

1,061 

1,040 

1,030 

982 

108 

120 

286 

600 

1,244 

1,257 

1,276 

1,344 

1,491 

1,447 

1,390 

1,350 

1,280 

142 

168 

385 

925 

1,556 

1,517 

1,548 

1,642 

1,860 

1,883 

1,780 

1,710 

1,560 

221 

188 

476 

1,220 

1,756 

1,649 

1,746 

1,825 

2,179 

2,283 

2,110 

1,930 

1,820 

222 

273 

705 

1,823 

2,215 

2,071 

2,168 

2,218 

2,668 

3,281 

3,120 

2,480 

2,260 

222 

404 

1,151 

2,465 

3,605 

2,737 

4,886 

3,602 

4,548 

8,840 

5,640 

4,320 

3,090 

Total Food Intake (g/kg-day) 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

20 to <40 years 

40 to <70 years 

70 years and older 

59 

183 

385 

676 

1,002 

994 

4,112 

1,553 

975 

743 

2,950 

4,818 

1,393 

88 

245 

411 

678 

1,002 

994 

4,112 

1,553 

975 

743 

2,950 

4,818 

1,393 

67.0 

74.7 

93.7 

99.7 

100 

100 

100 

100 

100 

100 

100 

100 

100 

20 

16 

28 

56 

90 

74 

61 

40 

24 

18 

16 

14 

15 

18 

14 

21 

36 

37 

29 

24 

17 

11 

9 

7 

6 

6 

0 

0 

0 

3 

17 

23 

21 

10 

5 

5 

-

-

-

0 

0 

0 

17 

38 

34 

30 

17 

9 

6 

6 

6 

6 

0 

0 

2 

22 

48 

39 

34 

21 

11 

8 

8 

7 

8 

0 

0 

15 

33 

65 

52 

44 

28 

16 

12 

11 

10 

10 

19 

18 

24 

47 

85 

72 

57 

38 

22 

16 

15 

14 

14 

33 

25 

38 

66 

109 

92 

73 

49 

30 

22 

20 

18 

19 

43 

36 

53 

99 

137 

113 

91 

61 

38 

30 

25 

23 

24 

61 

40 

65 

134 

161 

126 

102 

70 

45 

35 

30 

26 

27 

69 

55 

107 

211 

207 

146 

132 

88 

55 

47 

38 

34 

35 

69 

76 

169 

233 

265 

194 

239 

122 

82 

115 

70 

75 

47 

a 

b 

c 

PC 

SE 

-

Source: 

Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and fats. Beverages, sugar, candy, 

and sweets, and nuts (and nut products) were not included because they could not be categorized into the major food groups. 

Number of consumers. Thenumber of consumers of total food may be less than the number of individuals in the study sample for the youngest age groups because human milk was not 

included in the total food intake estimates presented here. 

Sample size. 

= Percent consuming. 

= Standard error. 

= Value not available. 

U.S. EPA analysis of 1994–1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-7 
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion, uncooked) 

Food Group N 

consa 

N 

totalb 

PC 

(%) Mean SE 

Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group: Birth to <1 month 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

59 

51 

0 

0 

0 

5 

27 

2 

58 

88 

88 

88 

88 

88 

88 

88 

88 

88 

67.0 

58.0 

0.0 

0.0 

0.0 

5.7 

30.7 

2.3 

65.9 

67 

41 

-

-

-

-

5 

-

19 

59 

38 

-

-

-

-

23 

-

16 

0 

0 

-

-

-

-

0 

-

0 

0 

0 

-

-

-

-

0 

-

0 

0 

0 

-

-

-

-

0 

-

0 

0 

0 

-

-

-

-

0 

-

0 

67 

40 

-

-

-

-

0 

-

20 

108 

72 

-

-

-

-

0.29 

-

32 

142 

81 

-

-

-

-

16 

-

38 

221 

156 

-

-

-

-

32 

-

64 

222 

156 

-

-

-

-

108 

-

64 

222 

156 

-

-

-

-

125 

-

64 

Age Group: 1 to <3 months 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

183 

147 

1 

0 

0 

44 

88 

23 

176 

245 

245 

245 

245 

245 

245 

245 

245 

245 

74.7 

60.0 

0.4 

0.0 

0.0 

18.0 

35.9 

9.4 

71.8 

80 

37 

-

-

-

1 

15 

4 

21 

70 

40 

-

-

-

5 

33 

21 

17 

0 

0 

-

-

-

0 

0 

0 

0 

0 

0 

-

-

-

0 

0 

0 

0 

0 

0 

-

-

-

0 

0 

0 

0 

0 

0 

-

-

-

0 

0 

0 

0 

94 

19 

-

-

-

0 

0 

0 

27 

120 

72 

-

-

-

0 

0.92 

0 

34 

168 

89 

-

-

-

3 

74 

0 

42 

188 

103 

-

-

-

9 

94 

31 

49 

273 

129 

-

-

-

20 

119 

114 

65 

404 

155 

-

-

-

45 

211 

171 

72 

Age Group: 3 to <6 months 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

385 

308 

44 

28 

1 

284 

263 

218 

357 

411 

411 

411 

411 

411 

411 

411 

411 

411 

93.7 

74.9 

10.7 

6.8 

0.2 

69.1 

64.0 

53.0 

86.9 

197 

56 

2 

0.23 

-

8 

34 

68 

28 

150 

56 

7 

3 

-

11 

46 

102 

17 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

12 

0 

0 

0 

-

0 

0 

0 

0 

100 

0 

0 

0 

-

0 

0 

0 

20 

167 

60 

0 

0 

-

4 

13 

15 

30 

286 

85 

0 

0 

-

11 

58 

99 

38 

385 

109 

1 

0 

-

21 

102 

196 

45 

476 

124 

13 

0.49 

-

27 

120 

282 

53 

705 

260 

29 

4 

-

44 

184 

522 

81 

1,151 

496 

92 

50 

-

68 

226 

750 

106 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-8 September 2011 
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion, uncooked) (continued) 

Food Group N a cons.

N 

totalb 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group: 6 to <12 months 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

676 

628 

500 

352 

34 

653 

662 

639 

661 

678 

678 

678 

678 

678 

678 

678 

678 

678 

99.7 

92.6 

73.7 

51.9 

5.0 

96.3 

97.6 

94.2 

97.5 

507 

151 

22 

6 

0.62 

33 

91 

169 

31 

344 

246 

27 

13 

3 

28 

67 

142 

16 

34 

0 

0 

0 

0 

0 

0 

0 

0 

141 

0 

0 

0 

0 

0.83 

2 

0 

2 

191 

1.0 

0 

0 

0 

6 

14 

17 

7 

283 

26 

0 

0 

0 

14 

41 

70 

23 

413 

71 

14 

0 

0 

28 

81 

147 

31 

600 

124 

32 

2 

0 

45 

127 

232 

40 

925 

401 

59 

22 

0 

66 

180 

335 

51 

1,220 

722 

78 

42 

0 

84 

231 

425 

58 

1,823 

1,297 

117 

73 

21 

125 

285 

670 

81 

2,465 

1,873 

269 

103 

42 

260 

452 

1,254 

90 

Age Group: 1 to <2 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

1,002 

999 

965 

906 

188 

997 

1,000 

986 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

100 

99.7 

96.3 

90.4 

18.8 

99.5 

99.8 

98.4 

100 

1,039 

489 

47 

14 

3 

66 

120 

254 

39 

407 

332 

37 

21 

10 

34 

75 

204 

17 

216 

1 

0 

0 

0 

8 

9 

0 

8 

414 

38 

0 

0 

0 

19 

25 

4 

15 

570 

94 

6 

0 

0 

27 

37 

30 

20 

770 

241 

20 

1 

0 

42 

68 

99 

28 

998 

451 

39 

4 

0 

60 

107 

209 

37 

1,244 

681 

66 

23 

0 

83 

155 

349 

48 

1,556 

917 

100 

45 

11 

111 

220 

532 

62 

1,756 

1,090 

120 

57 

21 

126 

255 

664 

69 

2,215 

1,474 

181 

86 

45 

172 

402 

828 

87 

3,605 

2,935 

221 

212 

135 

209 

739 

1,762 

146 

Age Group:2 to <3 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

994 

994 

981 

943 

190 

993 

994 

970 

994 

994 

994 

994 

994 

994 

994 

994 

994 

994 

100 

100 

98.7 

94.9 

19.1 

99.9 

100 

97.6 

100 

1,024 

383 

60 

18 

4 

81 

145 

279 

42 

377 

243 

41 

24 

12 

35 

89 

230 

18 

312 

6 

0 

0 

0 

16 

18 

0 

11 

491 

54 

8 

0 

0 

32 

45 

2 

17 

575 

104 

14 

0 

0 

41 

57 

25 

22 

752 

201 

31 

1 

0 

58 

86 

117 

30 

994 

346 

51 

7 

0 

78 

128 

231 

40 

1,257 

510 

80 

27 

0 

99 

178 

382 

51 

1,517 

709 

115 

50 

13 

126 

249 

594 

65 

1,649 

838 

139 

60 

26 

147 

302 

750 

73 

2,071 

1,079 

199 

93 

53 

195 

431 

992 

101 

2,737 

1,378 

280 

169 

127 

263 

846 

2,042 

129 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-9 
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion, uncooked) (continued) 

Food Group N a cons.

N 

totalb 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group:3 to <6 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

4,112 

4,112 

4,062 

3,910 

801 

4,111 

4,111 

4,021 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

100 

100 

98.8 

95.1 

19.5 

100 

100 

97.8 

100 

1,066 

392 

73 

16 

5 

101 

170 

243 

50 

380 

249 

49 

23 

16 

41 

89 

220 

19 

416 

14 

0 

0 

0 

29 

30 

0 

14 

548 

68 

11 

0 

0 

44 

56 

2 

23 

629 

121 

20 

0 

0 

54 

75 

16 

27 

805 

224 

38 

1 

0 

72 

109 

85 

36 

1,020 

356 

65 

6 

0 

95 

156 

196 

47 

1,276 

522 

97 

24 

0 

122 

213 

344 

60 

1,548 

706 

133 

47 

19 

155 

280 

516 

74 

1,746 

805 

163 

59 

36 

175 

329 

642 

85 

2,168 

1,151 

230 

99 

71 

230 

454 

1,000 

113 

4,886 

3,978 

433 

290 

192 

410 

915 

2,252 

167 

Age Group: 6 to <11 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

1,553 

1,553 

1,533 

1,490 

258 

1,553 

1,553 

1,515 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

100 

100 

98.7 

95.9 

16.6 

100 

100 

97.6 

100 

1,118 

408 

87 

16 

6 

119 

210 

193 

58 

372 

243 

56 

22 

17 

48 

103 

184 

22 

438 

10 

0 

0 

0 

31 

42 

0 

16 

586 

63 

12 

0 

0 

54 

76 

1 

27 

680 

126 

24 

0 

0 

67 

96 

8 

33 

846 

229 

48 

2 

0 

87 

136 

60 

42 

1,052 

371 

79 

6 

0 

114 

193 

141 

56 

1,344 

557 

116 

22 

0 

143 

264 

280 

70 

1,642 

741 

156 

46 

23 

179 

342 

440 

86 

1,825 

837 

195 

58 

38 

201 

410 

545 

95 

2,218 

1,130 

268 

107 

102 

262 

560 

880 

121 

3,602 

2,680 

435 

163 

169 

513 

896 

1,406 

168 

Age Group: 11 to <16 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

975 

975 

970 

930 

167 

975 

975 

923 

975 

975 

975 

975 

975 

975 

975 

975 

975 

975 

100 

100 

99.5 

95.4 

17.1 

100 

100 

94.7 

100 

1,209 

368 

114 

19 

9 

136 

280 

195 

69 

499 

291 

75 

27 

24 

63 

146 

202 

33 

343 

1 

1 

0 

0 

33 

65 

0 

18 

536 

25 

18 

0 

0 

56 

105 

0 

28 

657 

43 

32 

0 

0 

70 

124 

0.68 

34 

851 

152 

63 

2 

0 

93 

176 

31 

47 

1,124 

307 

101 

7 

0 

127 

246 

135 

64 

1,491 

507 

154 

25 

0 

168 

352 

273 

83 

1,860 

740 

208 

53 

30 

212 

472 

483 

110 

2,179 

948 

244 

72 

62 

249 

552 

635 

131 

2,668 

1,401 

355 

123 

125 

333 

713 

930 

176 

4,548 

1,972 

578 

244 

227 

645 

1,333 

1,535 

321 

Age Group: 16 to <21 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

743 

742 

730 

703 

143 

743 

743 

671 

743 

743 

743 

743 

743 

743 

743 

743 

743 

743 

100 

99.9 

98.3 

94.6 

19.2 

100 

100 

90.3 

100 

1,184 

283 

139 

21 

10 

150 

325 

168 

74 

634 

279 

127 

30 

33 

93 

204 

237 

42 

308 

0 

0 

0 

0 

13 

43 

0 

13 

467 

8 

12 

0 

0 

48 

86 

0 

22 

556 

19 

28 

0 

58 

128 

0 

30 

750 

63 

64 

1 

0 

88 

194 

3 

46 

1,061 

196 

116 

7 

0 

132 

280 

74 

67 

1,447 

410 

185 

29 

0 

190 

400 

242 

94 

1,883 

649 

266 

59 

34 

256 

562 

432 

129 

2,283 

934 

310 

89 

76 

307 

683 

665 

148 

3,281 

1,235 

458 

126 

146 

543 

1,160 

1,023 

213 

8,840 

1,866 

2,343 

223 

399 

730 

2,495 

2,270 

391 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-10 September 2011 
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, edible portion, uncooked) (continued) 

Food Group N a cons.

N 

totalb 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group: 20 years and older 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

9,161 

9,161 

9,161 

9,161 

9,161 

9,161 

9,161 

9,161 

9,161 

9,161 

9,143 

9,005 

8,621 

2,648 

9,152 

9,161 

8,566 

9,161 

100 

99.8 

98.3 

94.1 

28.9 

99.9 

100 

93.5 

100 

1,110 

221 

130 

24 

15 

136 

309 

191 

64 

481 -

228 -

90 -

32 -

36 -

84 -

171 -

224 -

34 -

 477

9 

 15

0 

0 

 42

 91

0 

 20

570 

20 

35 

0.13 

0 

53 

124 

0 

26 

769 

60 

65 

2 

0 

79 

191 

18 

39 

1,030 

153 

111 

10 

0 

116 

281 

125 

57 

1,360 

312 

171 

36 

12 

167 

394 

280 

81 

1,730 

509 

246 

63 

56 

238 

525 

473 

109 

2,010 

643 

299 

87 

86 

297 

626 

625 

127 

2,650 

1,020 

457 

129 

162 

462 

850 

996 

178 

5,640 

3,720 

1,010 

445 

434 

1,110 

1,810 

2,690 

359 a 

b 

c 

PC 

SE 

-

Source: 

Number of consumers. The number of consumers of total food may be less than the number of individuals in the study sample for the youngest age groups because human milk 

was not included in the total food intake estimates presented here. 

Sample size. 

Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and fats. Beverages, 

sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major fo od groups. 

= Percent consuming. 

= Standard error. 

= Value not available or data not reported where the number of consumers was less than 20. 

U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page

September 2011 14-11
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Gr oups (g/kg-day, edible portion, uncooked) 

Food Group N 

consa 

N 

totalb 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group: Birth to <1 month 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

59 

51 

0 

0 

0 

5 

27 

2 

58 

88 

88 

88 

88 

88 

88 

88 

88 

88 

67.0 

58.0 

0.0 

0.0 

0.0 

5.7 

30.7 

2.3 

65.9 

20 

12 

-

-

-

-

2 

-

6 

18 

12 

-

-

-

-

6 

-

5 

0 

0 

-

-

-

-

0 

-

0 

0 

0 

-

-

-

-

0 

-

0 

0 

0 

-

-

-

-

0 

-

0 

0 

0 

-

-

-

-

0 

-

0 

19 

13 

-

-

-

-

0 

-

6 

33 

21 

-

-

-

-

0 

-

9 

43 

25 

-

-

-

-

4 

-

11 

61 

43 

-

-

-

-

12 

-

18 

69 

49 

-

-

-

-

30 

-

20 

69 

49 

-

-

-

-

35 

-

20 

Age Group: 1 to <3 months 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

183 

147 

1 

0 

0 

44 

88 

23 

176 

245 

245 

245 

245 

245 

245 

245 

245 

245 

74.7 

60.0 

0.4 

0.0 

0.0 

18.0 

35.9 

9.4 

71.8 

16 

8 

-

-

-

0 

3 

1 

4 

14 

9 

-

-

-

1 

6 

5 

4 

0 

0 

-

-

-

0 

0 

0 

0 

0 

0 

-

-

-

0 

0 

0 

0 

0 

0 

-

-

-

0 

0 

0 

0 

0 

0 

-

-

-

0 

0 

0 

0 

18 

4 

-

-

-

0 

0 

0 

5 

25 

15 

-

-

-

0 

0 

0 

7 

36 

20 

-

-

-

1 

13 

0 

9 

40 

26 

-

-

-

2 

17 

7 

11 

55 

34 

-

-

-

3 

26 

19 

14 

76 

43 

-

-

-

9 

34 

43 

18 

Age Group: 3 to <6 months 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

385 

308 

44 

28 

1 

284 

263 

218 

357 

411 

411 

411 

411 

411 

411 

411 

411 

411 

93.7 

74.9 

10.7 

6.8 

0.2 

69.1 

64.0 

53.0 

86.9 

28 

8 

0 

0 

-

1 

5 

9 

4 

21 

8 

1 

0 

-

2 

7 

15 

3 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

2 

0 

0 

0 

-

0 

0 

0 

0 

15 

0 

0 

0 

-

0 

0 

0 

2 

24 

8 

0 

0 

-

1 

2 

2 

4 

38 

12 

0 

0 

-

1 

8 

13 

6 

53 

16 

0 

0 

-

3 

14 

29 

7 

65 

20 

1 

0 

-

4 

18 

37 

8 

107 

38 

4 

1 

-

6 

25 

72 

12 

169 

73 

13 

4 

-

10 

52 

110 

17 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-12 September 2011 
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups ( g/kg-day, edible portion, uncooked) (continued) 

Food Group N 

consa 

N 

totalb 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group: 6 to <12 months 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

676 

628 

500 

352 

34 

653 

662 

639 

661 

678 

678 

678 

678 

678 

678 

678 

678 

678 

99.7 

92.6 

73.7 

51.9 

5.0 

96.3 

97.6 

94.2 

97.5 

56 

16 

2 

1 

0 

4 

10 

19 

3 

36 

26 

3 

1 

0 

3 

8 

16 

2 

3 

0 

0 

0 

0 

0 

0 

0 

0 

17 

0 

0 

0 

0 

0 

0 

0 

0 

22 

0 

0 

0 

0 

1 

2 

2 

1 

33 

3 

0 

0 

0 

2 

5 

8 

2 

47 

8 

1 

0 

0 

3 

9 

16 

3 

66 

14 

4 

0 

0 

5 

14 

26 

4 

99 

38 

6 

2 

0 

7 

20 

36 

6 

134 

72 

8 

4 

0 

9 

25 

46 

7 

211 

165 

12 

7 

2 

14 

34 

84 

8 

233 

180 

30 

11 

4 

26 

67 

138 

10 

Age Group: 1 to <2 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

1,002 

999 

965 

906 

188 

997 

1,000 

986 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

1,002 

100 

99.7 

96.3 

90.4 

18.8 

99.5 

99.8 

98.4 

100 

90 

43 

4 

1 

0 

6 

10 

22 

3 

37 

30 

3 

2 

1 

3 

7 

18 

2 

17 

0 

0 

0 

0 

1 

1 

0 

0.73 

38 

3 

0 

0 

0 

2 

2 

0 

1 

48 

8 

1 

0 

0 

2 

3 

3 

2 

65 

20 

2 

0 

0 

4 

6 

9 

2 

85 

38 

3 

0 

0 

5 

9 

18 

3 

109 

59 

6 

2 

0 

7 

14 

31 

4 

137 

83 

8 

4 

1 

9 

19 

44 

5 

161 

100 

10 

5 

2 

11 

22 

58 

6 

207 

137 

14 

7 

3 

15 

33 

81 

8 

265 

216 

21 

15 

12 

19 

61 

144 

11 

Age Group: 2 to <3 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

994 

994 

981 

943 

190 

993 

994 

970 

994 

994 

994 

994 

994 

994 

994 

994 

994 

994 

100 

100 

98.7 

94.9 

19.1 

99.9 

100 

97.6 

100 

74 

28 

4 

1 

0 

6 

10 

20 

3 

29 

18 

3 

2 

1 

3 

6 

17 

1 

23 

0 

0 

0 

0 

1 

1 

0 

1 

34 

4 

1 

0 

0 

2 

3 

0 

1 

39 

7 

1 

0 

0 

3 

4 

2 

1 

52 

14 

2 

0 

0 

4 

6 

8 

2 

72 

24 

4 

0 

0 

5 

9 

16 

3 

92 

37 

6 

2 

0 

7 

13 

27 

4 

113 

52 

8 

4 

1 

9 

18 

44 

5 

126 

63 

9 

4 

2 

10 

22 

56 

5 

146 

84 

14 

6 

4 

14 

34 

71 

7 

194 

108 

20 

13 

11 

28 

64 

114 

9 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-13 
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups ( g/kg-day, edible portion, uncooked) (continued) 

Food Group N 

consa 

N 

totalb 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group:3 to <6 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

4,112 

4,112 

4,062 

3,910 

801 

4,111 

4,111 

4,021 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

4,112 

100 

100 

98.8 

95.1 

19.5 

100 

100 

97.8 

100 

61 

22 

4 

1 

0 

6 

10 

14 

3 

24 

15 

3 

1 

1 

3 

5 

13 

1 

21 

1 

0 

0 

0 

2 

2 

0 

1 

30 

4 

1 

0 

0 

2 

3 

0 

1 

34 

7 

1 

0 

0 

3 

4 

1 

2 

44 

12 

2 

0 

0 

4 

6 

5 

2 

57 

20 

4 

0 

0 

5 

9 

11 

3 

73 

30 

5 

1 

0 

7 

12 

20 

3 

91 

41 

8 

3 

1 

9 

16 

30 

4 

102 

48 

9 

3 

2 

10 

19 

39 

5 

132 

66 

13 

5 

4 

14 

26 

57 

6 

239 

195 

23 

13 

12 

27 

60 

124 

10 

Age Group: 6 to <11 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

1,553 

1,553 

1,533 

1,490 

258 

1,553 

1,553 

1,515 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

1,553 

100 

100 

98.7 

95.9 

16.6 

100 

100 

97.6 

100 

40 

15 

3 

1 

0 

4 

7 

7 

2 

17 

10 

2 

1 

1 

2 

4 

7 

1 

10 

0 

0 

0 

0 

1 

1 

0 

1 

17 

2 

0 

0 

0 

2 

2 

0 

1 

21 

4 

1 

0 

0 

2 

3 

0 

1 

28 

7 

2 

0 

0 

3 

5 

2 

1 

38 

13 

3 

0 

0 

4 

7 

5 

2 

49 

20 

4 

1 

0 

5 

9 

10 

3 

61 

27 

6 

2 

1 

7 

12 

16 

3 

70 

33 

7 

2 

1 

8 

15 

21 

4 

88 

42 

10 

4 

3 

11 

20 

32 

5 

122 

79 

18 

8 

7 

16 

50 

55 

9 

Age Group: 11 to <16 years 

Total Food Intakec 

Total Dairy Intake 

Total Meat Intake 

Total Egg Intake 

Total Fish Intake 

Total Grain Intake 

Total Vegetable Intake 

Total Fruit Intake 

Total Fat Intake 

975 

975 

970 

930 

167 

975 

975 

923 

975 

975 

975 

975 

975 

975 

975 

975 

975 

975 

100 

100 

99.5 

95.4 

17.1 

100 

100 

94.7 

100 

24 

7 

2 

0 

0 

3 

5 

4 

1 

11 

6 

1 

1 

0 

1 

3 

4 

1 

5 

0 

0 

0 

0 

1 

1 

0 

0 

9 

0 

0 

0 

0 

1 

2 

0 

0 

11 

1 

1 

0 

0 

1 

2 

0 

1 

16 

3 

1 

0 

0 

2 

3 

1 

1 

22 

6 

2 

0 

0 

2 

5 

3 

1 

30 

10 

3 

0 

0 

3 

7 

6 

2 

38 

15 

4 

1 

1 

5 

9 

10 

2 

45 

20 

5 

1 

1 

5 

11 

14 

3 

55 

29 

7 

3 

2 

7 

14 

18 

4 

82 

38 

10 

7 

7 

9 

31 

32 

5 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-14 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, edible portion, uncooked) (continued) 

Food Group N 

consa 

N 

totalb 

PC 

(%) Mean SE Percentiles 

1 5 10 25 50 75 90 95 99 Max 

Age Group: 16 to <21 years 

Total Food Intakec 743 743 100 18 9 5 6 8 12 16 22 30 35 47 115 

Total Dairy Intake 742 743 99.9 4 4 0 0 0 1 3 6 10 12 19 25 

Total Meat Intake 730 743 98.3 2 2 0 0 0 1 2 3 4 5 7 30 

Total Egg Intake 703 743 94.6 0 0 0 0 0 0 0 0 1 1 2 3 

Total Fish Intake 143 743 19.2 0 1 0 0 0 0 0 0 1 1 2 7 

Total Grain Intake 743 743 100 2 1 0 1 1 1 2 3 4 5 7 12 

Total Vegetable Intake 743 743 100 5 3 1 1 2 3 4 6 8 10 15 32 

Total Fruit Intake 671 743 90.3 3 4 0 0 0 0 1 4 7 10 16 29 

Total Fat Intake 743 743 100 1 1 0 0 0 1 1 1 2 2 3 5 

Age Group: 20 years and older 

Total Food Intakec 9,161 9,161 100 15 7 - 6 8 10 14 19 24 28 37 75 

Total Dairy Intake 9,161 9,143 99.8 3 3 - 0 0 1 2 4 7 9 14 41 

Total Meat Intake 9,161 9,005 98.3 2 1 - 0 0 1 2 2 3 4 6 13 

Total Egg Intake 9,161 8,621 94.1 0 0 - 0 0 0 0 0 1 1 2 8 

Total Fish Intake 9,161 2,648 28.9 0 0 - 0 0 0 0 0 1 1 2 8 

Total Grain Intake 9,161 9,152 100 2 1 - 1 1 1 2 2 3 4 6 16 

Total Vegetable Intake 9,161 9,161 100 4 2 - 1 2 3 4 5 7 9 12 28 

Total Fruit Intake 9,161 8,566 93.5 3 3 - 0 0 0 2 4 7 9 15 52 

Total Fat Intake 9,161 9,161 100 1 0 - 0 0 1 1 1 1 2 2 4 a Number of consumers. The number of consumers of total food may be less than the number of individuals in the study sample for the youngest age groups because human 

milk was not included in the total food intake estimates presented here. b Sample size. c Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and fats. Beverages, 

sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups. 

PC = Percent consuming. 

SE = Standard error. 

- = Data not reported where the number of consumers was less than 20. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-15 
Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Food Intake 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: Birth to <1 month (g/day) Age Group: Birth to <1 month (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

0 0.0 64 100.0 196 100.0 

0 0.0 39 61.2 109 55.4 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 4 2.1 

0 0.0 5 7.4 24 12.1 

0 0.0 0 0.0 8 4.1 

0 0.0 19 29.4 52 26.2 

Total Foodsa 0 0.0 20 100.0 58 100.0 

Total Dairy 0 0.0 14 70.5 35 60.1 

Total Meats 0 0.0 0 0.0 0 0.0 

Total Fish 0 0.0 0 0.0 0 0.0 

Total Eggs 0 0.0 0 0.0 0 0.0 

Total Grains 0 0.0 0 0.0 1 2.1 

Total Vegetables 0 0.0 0 0.1 6 10.0 

Total Fruits 0 0.0 0 0.0 0 0.0 

Total Fatsb 0 0.0 6 29.4 16 27.8 

Age Group: 1 to <3 months (g/day) Age Group: 1 to <3 months (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

0 0.0 94 100.0 206 100.0 

0 0.0 53 56.9 63 30.8 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 1 1.1 3 1.3 

0 0.0 11 12.0 58 28.4 

0 0.0 0 0.0 27 13.0 

0 0.0 27 28.4 49 23.6 

Total Foodsa 0 0.0 18 100.0 44 100.0 

Total Dairy 0 0.0 9 51.9 20 45.4 

Total Meats 0 0.0 0 0.0 0 0.0 

Total Fish 0 0.0 0 0.0 0 0.0 

Total Eggs 0 0.0 0 0.0 0 0.0 

Total Grains 0 0.0 0 1.1 0 0.5 

Total Vegetables 0 0.0 3 18.9 7 16.4 

Total Fruits 0 0.0 0 0.0 5 12.3 

Total Fatsb 0 0.0 5 27.7 11 24.4 

Age Group: 3 to <6 months (g/day) Age Group: 3 to <6 months (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

1 100.0 166 100.0 507 100.0 

0 3.0 69 41.9 90 17.8 

0 0.0 0 0.2 4 0.8 

0 0.0 0 0.0 0 0.1 

0 0.0 1 0.3 1 0.1 

1 74.5 8 4.9 14 2.8 

0 10.9 27 16.3 73 14.4 

0 9.9 24 14.6 284 56.0 

0 1.3 34 20.4 36 7.2 

Total Foodsa 0 100.0 24 100.0 73 100.0 

Total Dairy 0 0.5 9 37.3 13 17.9 

Total Meats 0 0.0 0 0.5 1 0.8 

Total Fish 0 0.0 0 0.0 0 0.1 

Total Eggs 0 0.0 0 0.0 0 0.0 

Total Grains 0 85.0 1 4.0 2 3.4 

Total Vegetables 0 7.4 5 20.8 11 14.5 

Total Fruits 0 6.7 4 15.0 40 55.0 

Total Fatsb 0 0.2 5 21.3 5 7.5 

Page Exposure Factors Handbook 14-16 September 2011 
Chapter 14—Total Food Intake 

Exposure Factors Handbook 

Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Food Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 6 to <12 months (g/day) Age Group: 6 to <12 months (g/kg-day) 

Total Foodsa 124 100.0 414 100.0 1,358 100.0 

Total Dairy 33 26.4 72 17.5 770 56.7 

Total Meats 3 2.4 19 4.6 47 3.5 

Total Fish 0 0.2 1 0.3 0 0.0 

Total Eggs 1 0.5 7 1.6 8 0.6 

Total Grains 11 9.1 37 8.9 50 3.7 

Total Vegetables 30 24.2 90 21.9 121 8.9 

Total Fruits 30 24.4 151 36.5 314 23.1 

Total Fatsb 14 11.6 35 8.4 44 3.2 

Total Foodsa 15 100.0 47 100.0 144 100.0 

Total Dairy 4 25.4 6 13.8 77 53.1 

Total Meats 0 2.3 2 4.9 5 3.4 

Total Fish 0 0.2 0 0.2 0 0.0 

Total Eggs 0 0.9 1 1.5 1 0.8 

Total Grains 2 10.7 4 9.1 5 3.6 

Total Vegetables 3 21.9 10 22.4 14 9.8 

Total Fruits 4 25.9 19 40.0 37 25.8 

Total Fatsb 2 11.4 4 7.5 5 3.2 

Age Group: 1 to <2 years (g/day) Age Group: 1 to <2 years (g/kg-day) 

Total Foodsa 407 100.0 998 100.0 1,859 100.0 

Total Dairy 113 27.8 487 48.8 1,008 54.2 

Total Meats 28 6.9 46 4.6 66 3.5 

Total Fish 1 0.3 3 0.3 4 0.2 

Total Eggs 9 2.2 16 1.6 22 1.2 

Total Grains 44 10.8 63 6.3 81 4.3 

Total Vegetables 82 20.1 101 10.2 165 8.9 

Total Fruits 100 24.6 238 23.8 446 24.0 

Total Fatsb 24 5.8 38 3.8 61 3.3 

Total Foodsa 35 100.0 85 100.0 167 100.0 

Total Dairy 10 29.5 41 48.1 94 56.1 

Total Meats 3 7.5 4 4.7 5 3.2 

Total Fish 0 0.4 1 0.5 0 0.2 

Total Eggs 1 2.1 1 1.4 2 0.9 

Total Grains 4 10.9 5 6.0 7 4.3 

Total Vegetables 7 18.6 10 11.9 13 7.8 

Total Fruits 8 23.0 19 22.8 40 24.0 

Total Fatsb 2 6.4 3 3.8 5 3.2 

Age Group: 2 to <3 years (g/day) Age Group: 2 to <3 years (g/kg-day) 

Total Foodsa 448 100.0 989 100.0 1,760 100.0 

Total Dairy 118 26.3 370 37.4 698 39.7 

Total Meats 50 11.1 60 6.1 72 4.1 

Total Fish 1 0.3 4 0.4 7 0.4 

Total Eggs 12 2.7 14 1.4 24 1.4 

Total Grains 62 13.7 86 8.7 98 5.6 

Total Vegetables 98 21.9 145 14.6 185 10.5 

Total Fruits 70 15.6 255 25.8 609 34.6 

Total Fatsb 31 6.8 44 4.4 56 3.2 

Total Foodsa 32 100.0 72 100.0 129 100.0 

Total Dairy 8 24.8 26 36.3 54 42.2 

Total Meats 4 11.2 4 5.3 5 3.8 

Total Fish 0 0.4 0 0.2 0 0.3 

Total Eggs 1 3.6 1 1.7 2 1.3 

Total Grains 4 13.8 6 8.0 7 5.6 

Total Vegetables 7 22.0 10 13.3 13 10.0 

Total Fruits 5 16.2 21 29.8 42 32.9 

Total Fatsb 2 7.1 3 3.9 4 3.2 

Exposure Factors Handbook PageSeptember 2011 14-17 
Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Food Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 3 to <6 years (g/day) Age Group: 3 to <6 years (g/kg-day) 

Total Foodsa 527 100.0 1,020 100.0 1,817 100.0 

Total Dairy 144 27.3 378 37.0 728 40.1 

Total Meats 53 10.0 72 7.0 94 5.2 

Total Fish 3 0.6 5 0.5 9 0.5 

Total Eggs 11 2.0 15 1.5 24 1.3 

Total Grains 76 14.4 103 10.1 132 7.3 

Total Vegetables 117 22.3 163 16.0 233 12.8 

Total Fruits 76 14.4 216 21.2 509 28.0 

Total Fatsb 34 6.5 50 4.9 68 3.7 

Total Foodsa 28 100.0 57 100.0 108 100.0 

Total Dairy 8 27.3 21 36.3 43 40.3 

Total Meats 3 10.4 4 7.1 5 4.8 

Total Fish 0 0.5 0 0.5 0 0.4 

Total Eggs 1 2.1 1 1.6 1 1.1 

Total Grains 4 14.0 6 9.9 8 7.1 

Total Vegetables 6 22.0 9 16.0 14 12.5 

Total Fruits 4 15.2 13 22.1 31 29.0 

Total Fatsb 2 6.4 3 4.8 4 3.7 

Age Group: 6 to <11 years (g/day) Age Group: 6 to <11 years (g/kg-day) 

Total Foodsa 565 100.0 1,060 100.0 1,886 100.0 

Total Dairy 147 26.1 370 34.9 766 40.6 

Total Meats 65 11.4 95 9.0 104 5.5 

Total Fish 2 0.3 6 0.6 10 0.5 

Total Eggs 10 1.7 16 1.5 22 1.2 

Total Grains 89 15.8 116 10.9 157 8.3 

Total Vegetables 136 24.1 203 19.2 294 15.6 

Total Fruits 66 11.6 178 16.8 426 22.6 

Total Fatsb 39 6.8 58 5.5 76 4.0 

Total Foodsa 16 100.0 38 100.0 73 100.0 

Total Dairy 4 26.2 15 38.6 30 40.8 

Total Meats 2 11.9 3 8.1 4 5.9 

Total Fish 0 0.5 0 0.5 0 0.4 

Total Eggs 0 1.8 1 1.6 1 1.3 

Total Grains 2 14.7 4 10.8 7 9.0 

Total Vegetables 4 24.7 7 18.0 11 15.5 

Total Fruits 2 11.2 6 14.9 15 21.2 

Total Fatsb 1 7.3 2 5.3 3 4.3 

Age Group: 11 to <16 years (g/day) Age Group: 11 to <16 years (g/kg-day) 

Total Foodsa 513 100.0 1,127 100.0 2,256 100.0 

Total Dairy 92 17.9 308 27.3 808 35.8 

Total Meats 71 13.9 116 10.3 172 7.6 

Total Fish 4 0.8 7 0.6 16 0.7 

Total Eggs 10 1.9 20 1.8 28 1.2 

Total Grains 84 16.3 133 11.8 207 9.2 

Total Vegetables 162 31.6 258 22.9 459 20.3 

Total Fruits 42 8.2 203 18.0 420 18.6 

Total Fatsb 40 7.8 64 5.7 114 5.0 

Total Foodsa 8 100.0 22 100.0 46 100.0 

Total Dairy 1 17.3 6 26.9 18 38.4 

Total Meats 1 14.7 2 10.3 3 7.0 

Total Fish 0 0.9 0 0.8 0 0.8 

Total Eggs 0 1.8 0 2.2 1 1.3 

Total Grains 1 16.6 3 11.7 4 9.3 

Total Vegetables 3 31.7 5 23.4 9 18.4 

Total Fruits 1 7.2 4 17.4 8 18.2 

Total Fatsb 1 8.3 1 5.9 2 4.8 

Page Exposure Factors Handbook 14-18 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 14-6. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Food Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 16 to <21 years (g/day) Age Group: 16 to <21 years (g/kg-day) 

Total Foodsa 438 100.0 1,060 100.0 2,590 100.0 Total Foodsa 6 100.0 16 100.0 38 100.0 

Total Dairy 56 12.8 219 20.7 759 29.3 Total Dairy 1 12.2 4 23.8 10 27.4 

Total Meats 61 14.0 141 13.3 272 10.5 Total Meats 1 15.6 2 11.5 4 10.0 

Total Fish 7 1.5 11 1.1 14 0.5 Total Fish 0 1.7 0 1.0 0 0.5 

Total Eggs 8 1.9 17 1.6 29 1.1 Total Eggs 0 1.8 0 1.6 0 1.1 

Total Grains 67 15.2 138 13.0 241 9.3 Total Grains 1 14.8 2 13.1 4 9.9 

Total Vegetables 148 33.8 312 29.4 620 23.9 Total Vegetables 2 34.0 5 30.0 10 25.3 

Total Fruits 48 11.0 138 13.1 487 18.8 Total Fruits 1 10.2 2 10.9 8 19.7 

Total Fatsb 33 7.6 72 6.8 136 5.3 Total Fatsb 1 8.1 1 7.1 2 5.0 

Age Group: 20 years and older (g/day) Age Group: 20 years and older (g/kg-day) 

Total Foodsa 451 100.0 1,030 100.0 2,140 100.0 Total Foodsa 6 100.0 14 100.0 30 100.0 

Total Dairy 55 12.1 188 18.3 520 24.3 Total Dairy 1 12.5 3 19.4 7 24.9 

Total Meats 74 16.5 128 12.5 210 9.8 Total Meats 1 17.3 2 12.2 2 8.2 

Total Fish 7 1.6 13 1.2 25 1.2 Total Fish 0 1.6 0 1.4 0 0.9 

Total Eggs 15 3.2 23 2.3 34 1.6 Total Eggs 0 3.5 0 2.3 0 1.5 

Total Grains 69 15.3 130 12.7 230 10.8 Total Grains 1 15.6 2 13.1 3 10.1 

Total Vegetables 147 32.6 291 28.4 516 24.2 Total Vegetables 2 32.1 4 28.9 7 23.5 

Total Fruits 40 8.9 174 17.0 466 21.8 Total Fruits 0 7.9 2 14.9 7 23.6 

Total Fatsb 34 7.6 60 5.9 105 4.9 Total Fatsb 0 7.7 1 6.1 1 4.6 a Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and 

fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups. b Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-19 
 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-7. Per Capita Intake of Total Foodsa and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat Intake 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: Birth to <1 month (g/day)c Age Group: Birth to <1 month (g/kg-day)c 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

67 100.0 - - - -

41 61.5 - - - -

0 0.0 - - - -

0 0.0 - - - -

0 0.0 - - - -

0 0.7 - - - -

5 7.7 - - - -

1 1.3 - - - -

19 28.3 - - - -

Total Foodsa 20 100.0 - - - -

Total Dairy 12 61.6 - - - -

Total Meats 0 0.0 - - - -

Total Fish 0 0.0 - - - -

Total Eggs 0 0.0 - - - -

Total Grains 0 0.7 - - - -

Total Vegetables 2 7.7 - - - -

Total Fruits 0 1.1 - - - -

Total Fatsb 6 28.4 - - - -

Age Group: 1 to <3 months (g/day)d Age Group: 1 to <3 months (g/kg-day)d 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

79 100.0 - - 149 100.0 

37 46.4 - - 103 68.9 

0 0.0 - - 1 0.7 

0 0.0 - - 0 0.0 

0 0.0 - - 0 0.0 

1 1.5 - - 0 0.1 

15 18.6 - - 3 2.1 

4 5.2 - - 0 0.0 

21 26.4 - - 42 28.2 

Total Foodsa 16 100.0 - - 47 100.0 

Total Dairy 8 47.9 - - 32 68.9 

Total Meats 0 0.0 - - 0 0.7 

Total Fish 0 0.0 - - 0 0.0 

Total Eggs 0 0.0 - - 0 0.0 

Total Grains 0 1.4 - - 0 0.1 

Total Vegetables 3 16.8 - - 1 2.1 

Total Fruits 1 5.6 - - 0 0.0 

Total Fatsb 4 26.5 - - 13 28.2 

Age Group: 3 to <6 months (g/day)e Age Group: 3 to <6 months (g/kg-day)e 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

181 100.0 - - 316 100.0 

55 30.1 - - 62 19.7 

0 0.0 - - 16 4.9 

0 0.0 - - 0 0.1 

0 0.1 - - 1 0.5 

7 3.7 - - 16 5.0 

31 17.0 - - 56 17.9 

59 32.9 - - 133 42.3 

28 15.3 - - 28 8.9 

Total Foodsa 26 100.0 - - 41 100.0 

Total Dairy 8 30.6 - - 8 20.5 

Total Meats 0 0.0 - - 2 4.9 

Total Fish 0 0.0 - - 0 0.1 

Total Eggs 0 0.0 - - 0 0.3 

Total Grains 1 3.7 - - 2 4.8 

Total Vegetables 4 16.9 - - 7 17.6 

Total Fruits 8 32.2 - - 17 41.7 

Total Fatsb 4 15.6 - - 4 9.2 

Page Exposure Factors Handbook 14-20 September 2011 
Chapter 14—Total Food Intake 

Exposure Factors Handbook 

Table 14-7. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 6 to <12 months (g/day) Age Group: 6 to <12 months (g/kg-day) 

Total Foodsa 347 100.0 466 100.0 922 100.0 

Total Dairy 80 23.0 108 23.2 384 41.6 

Total Meats 0 0.0 14 2.9 85 9.3 

Total Fish 0 0.0 0 0.1 0 0.0 

Total Eggs 2 0.5 3 0.6 11 1.2 

Total Grains 24 6.8 29 6.2 51 5.6 

Total Vegetables 69 19.8 116 24.8 135 14.7 

Total Fruits 143 41.3 162 34.8 216 23.4 

Total Fatsb 27 7.7 31 6.7 43 4.6 

Total Foodsa 40 100.0 48 100.0 99 100.0 

Total Dairy 9 22.6 11 23.9 41 41.1 

Total Meats 0 0.0 1 3.0 9 9.3 

Total Fish 0 0.0 0 0.1 0 0.0 

Total Eggs 0 0.5 0 1.0 1 0.9 

Total Grains 3 6.6 3 6.0 6 5.8 

Total Vegetables 8 19.7 10 21.9 15 15.4 

Total Fruits 17 41.9 17 36.5 23 23.1 

Total Fatsb 2 7.8 3 7.1 5 4.6 

Age Group: 1 to <2 years (g/day) Age Group: 1 to <2 years (g/kg-day) 

Total Foodsa 921 100.0 992 100.0 1,229 100.0 

Total Dairy 464 50.4 483 48.7 460 37.4 

Total Meats 2 0.2 39 4.0 128 10.4 

Total Fish 3 0.3 2 0.2 6 0.5 

Total Eggs 8 0.9 14 1.5 24 1.9 

Total Grains 56 6.1 64 6.5 78 6.4 

Total Vegetables 97 10.5 113 11.3 189 15.4 

Total Fruits 250 27.2 228 23.0 290 23.6 

Total Fatsb 30 3.3 38 3.8 57 4.6 

Total Foodsa 82 100.0 90 100.0 108 100.0 

Total Dairy 41 49.9 46 50.5 43 40.1 

Total Meats 0 0.2 3 3.8 11 10.0 

Total Fish 0 0.3 0 0.3 0 0.5 

Total Eggs 1 0.8 1 1.4 2 1.9 

Total Grains 5 6.1 6 6.1 7 6.9 

Total Vegetables 9 11.1 10 10.8 16 15.1 

Total Fruits 22 27.3 21 22.7 22 20.8 

Total Fatsb 3 3.3 3 3.8 5 4.7 

Age Group: 2 to <3 years (g/day) Age Group: 2 to <3 years (g/kg-day) 

Total Foodsa 950 100.0 947 100.0 1,131 100.0 

Total Dairy 426 44.9 373 39.3 374 33.0 

Total Meats 7 0.7 52 5.4 148 13.1 

Total Fish 4 0.5 4 0.5 2 0.2 

Total Eggs 12 1.3 18 1.9 21 1.9 

Total Grains 73 7.7 76 8.1 90 8.0 

Total Vegetables 104 10.9 146 15.4 202 17.9 

Total Fruits 279 29.4 226 23.8 232 20.5 

Total Fatsb 29 3.0 40 4.2 62 5.5 

Total Foodsa 71 100.0 68 100.0 83 100.0 

Total Dairy 31 44.2 26 37.7 27 32.3 

Total Meats 1 0.7 4 5.5 10 12.4 

Total Fish 0 0.5 0 0.3 0 0.2 

Total Eggs 1 1.3 1 1.3 2 1.8 

Total Grains 6 7.8 6 8.3 7 8.1 

Total Vegetables 8 11.1 10 15.1 14 16.8 

Total Fruits 21 29.6 18 26.7 19 23.1 

Total Fatsb 2 3.1 3 4.0 4 5.2 

Exposure Factors Handbook PageSeptember 2011 14-21 
Table 14-7. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 3 to <6 years (g/day) Age Group: 3 to <6 years (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

991 

419 

10 

7 

10 

98 

128 

257 

35 

100.0 

42.3 

1.0 

0.7 

1.0 

9.9 

13.0 

25.9 

3.6 

1,037 

376 

65 

6 

16 

101 

170 

238 

48 

100.0 

36.3 

6.3 

0.5 

1.5 

9.8 

16.4 

22.9 

4.7 

1,246 

389 

176 

4 

24 

117 

217 

243 

73 

100.0 

31.2 

14.1 

0.3 

1.9 

9.4 

17.4 

19.5 

5.9 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

57 

24 

1 

0 

1 

6 

7 

15 

2 

100.0 

42.1 

1.0 

0.6 

1.0 

9.9 

13.0 

26.1 

3.6 

59 

23 

4 

0 

1 

6 

9 

13 

3 

100.0 

38.2 

6.0 

0.5 

1.4 

9.5 

15.8 

22.0 

4.8 

74 

23 

10 

0 

1 

7 

13 

15 

4 

100.0 

31.3 

13.4 

0.3 

2.0 

9.4 

17.5 

20.1 

5.7 

Age Group: 6 to <11 years (g/day) Age Group: 6 to <11 years (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

1,028 

424 

11 

6 

13 

121 

164 

214 

40 

100.0 

41.3 

1.1 

0.6 

1.3 

11.8 

16.0 

20.8 

3.9 

1,087 

386 

79 

5 

15 

117 

212 

191 

59 

100.0 

35.5 

7.3 

0.5 

1.4 

10.7 

19.5 

17.6 

5.4 

1,300 

382 

206 

4 

17 

136 

270 

198 

81 

100.0 

29.4 

15.8 

0.3 

1.3 

10.4 

20.7 

15.2 

6.2 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

36 

15 

0 

0 

0 

4 

5 

8 

1 

100.0 

41.5 

1.0 

0.9 

1.2 

11.5 

15.1 

21.7 

3.8 

39 

15 

3 

0.32 

0.42 

4 

7 

6 

2 

100.0 

38.7 

7.0 

0.8 

1.1 

10.7 

19.1 

15.6 

5.1 

51 

15 

8 

0 

1 

5 

10 

8 

3 

100.0 

29.7 

14.8 

0.3 

1.5 

10.4 

20.2 

16.5 

6.0 

Age Group: 11 to <16 years (g/day) Age Group: 11 to <16 years (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

1,043 

342 

17 

13 

17 

116 

227 

238 

44 

100.0 

32.8 

1.6 

1.3 

1.6 

11.1 

21.7 

22.8 

4.2 

1,194 

377 

101 

7 

13 

144 

260 

202 

67 

100.0 

31.6 

8.5 

0.6 

1.1 

12.1 

21.8 

16.9 

5.6 

1,606 

435 

268 

7 

21 

159 

404 

204 

106 

100.0 

27.1 

16.7 

0.4 

1.3 

9.9 

25.2 

12.7 

6.6 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

19 

6 

0 

0 

0 

2 

4 

4 

1 

100.0 

31.5 

1.6 

1.5 

1.5 

11.6 

22.2 

23.1 

4.4 

22 

6 

2 

0 

0 

3 

5 

4 

1 

100.0 

27.0 

8.8 

0.5 

1.3 

11.7 

24.1 

18.9 

5.7 

33 

10 

5 

0 

0 

3 

8 

4 

2 

100.0 

29.7 

16.3 

0.5 

1.4 

10.0 

23.3 

11.7 

6.7 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-22 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 14-7. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 16 to <21 years (g/day) Age Group: 16 to <21 years (g/kg-day) 

Total Foodsa 922 100.0 1,084 100.0 1,957 100.0 Total Foodsa 15 100.0 18 100.0 28 100.0 

Total Dairy 307 33.3 280 25.8 403 20.6 Total Dairy 4 30.3 4 24.0 5 18.1 

Total Meats 12 1.3 115 10.6 385 19.7 Total Meats 0 1.3 2 9.6 5 19.8 

Total Fish 20 2.1 9 0.9 12 0.6 Total Fish 0 2.2 0 1.0 0 0.4 

Total Eggs 14 1.5 15 1.4 31 1.6 Total Eggs 0 1.4 0 1.9 0 1.6 

Total Grains 131 14.2 147 13.6 231 11.8 Total Grains 2 14.5 2 12.8 3 12.3 

Total Vegetables 215 23.3 287 26.5 532 27.2 Total Vegetables 4 24.6 5 27.5 8 28.9 

Total Fruits 151 16.4 147 13.5 226 11.6 Total Fruits 3 17.8 3 15.7 3 12.4 

Total Fatsb 42 4.5 73 6.7 139 7.1 Total Fatsb 1 4.6 1 6.2 2 6.5 

Age Group: 20 years and older (g/day) Age Group: 20 years and older (g/kg-day) 

Total Foodsa 943 100.0 1,030 100.0 1,560 100.0 Total Foodsa 14 100.0 15 100.0 21 100.0 

Total Dairy 213 22.6 211 20.4 254 16.3 Total Dairy 3 22.6 3 20.7 3 15.9 

Total Meats 15 1.6 111 10.8 338 21.7 Total Meats 0 1.6 2 10.3 4 21.3 

Total Fish 25 2.6 12 1.2 13 0.8 Total Fish 0 2.6 0 1.3 0 0.9 

Total Eggs 17 1.8 21 2.0 33 2.1 Total Eggs 0 1.8 0 2.1 0 2.0 

Total Grains 113 12.0 124 12.0 196 12.5 Total Grains 2 11.9 2 12.2 3 12.2 

Total Vegetables 259 27.4 282 27.2 446 28.5 Total Vegetables 4 27.3 4 27.6 6 28.2 

Total Fruits 234 24.9 192 18.6 165 10.5 Total Fruits 3 25.3 3 18.2 3 12.3 

Total Fatsb 38 4.1 59 5.7 115 7.4 Total Fatsb 1 4.0 1 5.5 1 7.0 a Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and 

fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups. b Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats. c All individuals in this sample group consumed 0 g/day of meat. Therefore, results are reported in the low-end decile. d Only one individual in this sample group consumed more than 0 g/day of meat. This result is reported in the high-end decile. All other samples are reported in 

the low-end decile. e All individuals in this sample group below the 89th percentile consumed 0 g/day of meat. Therefore, only high-end and low-end consumer groups are reported. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-23 
Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat and Dairy Intake 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: Birth to <1 month (g/day) Age Group: Birth to <1 month (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

12 100.0 60 100.0 185 100.0 

0 0.0 40 67.3 127 69.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.3 0 0.0 4 2.2 

8 66.1 2 3.4 1 0.4 

0 0.0 0 0.0 0 0.0 

3 27.1 18 29.2 52 28.4 

Total Foodsa 4 100.0 18 100.0 56 100.0 

Total Dairy 0 0.0 12 67.1 39 69.0 

Total Meats 0 0.0 0 0.0 0 0.0 

Total Fish 0 0.0 0 0.0 0 0.0 

Total Eggs 0 0.0 0 0.0 0 0.0 

Total Grains 0 0.2 0 0.0 1 2.1 

Total Vegetables 2 64.4 1 3.7 0 0.5 

Total Fruits 0 0.0 0 0.0 0 0.0 

Total Fatsb 1 27.5 5 29.2 16 28.4 

Age Group: 1 to <3 months (g/day) Age Group: 1 to <3 months (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

36 100.0 84 100.0 166 100.0 

0 0.0 19 22.4 109 65.6 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.9 1 1.2 1 0.8 

21 58.8 42 50.7 4 2.7 

2 4.3 0 0.0 6 3.7 

10 26.7 21 25.4 45 27.2 

Total Foodsa 7 100.0 14 100.0 41 100.0 

Total Dairy 0 0.0 3 24.0 26 64.1 

Total Meats 0 0.0 0 0.0 0 0.0 

Total Fish 0 0.0 0 0.0 0 0.0 

Total Eggs 0 0.0 0 0.0 0 0.0 

Total Grains 0 0.8 0 2.0 0 0.6 

Total Vegetables 4 57.8 7 48.7 0 1.1 

Total Fruits 0 5.4 0 0.0 3 7.7 

Total Fatsb 2 26.4 4 25.0 11 26.5 

Age Group: 3 to <6 months (g/day) Age Group: 3 to <6 months (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

121 100.0 204 100.0 334 100.0 

0 0.0 60 29.7 159 47.7 

0 0.0 0 0.3 5 1.4 

0 0.0 0 0.0 0 0.1 

0 0.0 0 0.1 1 0.2 

5 4.5 7 3.2 12 3.7 

44 36.4 29 14.5 27 8.0 

52 42.9 80 39.0 74 22.3 

15 12.3 27 13.2 54 16.3 

Total Foodsa 17 100.0 30 100.0 45 100.0 

Total Dairy 0 0.0 8 26.5 24 53.4 

Total Meats 0 0.0 0 0.6 1 1.3 

Total Fish 0 0.0 0 0.0 0 0.1 

Total Eggs 0 0.0 0 0.3 0 0.1 

Total Grains 1 4.5 1 3.7 2 3.6 

Total Vegetables 6 37.1 3 11.2 2 5.3 

Total Fruits 7 41.7 14 46.0 8 17.3 

Total Fatsb 2 12.6 3 11.4 8 18.7 

Page Exposure Factors Handbook 14-24 September 2011 
 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat and Dairy Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 6 to <12 months (g/day) Age Group: 6 to <12 months (g/kg-day) 

Total Foodsa 253 100.0 403 100.0 1,284 100.0 

Total Dairy 1 0.5 71 17.6 827 64.5 

Total Meats 1 0.3 17 4.1 45 3.5 

Total Fish 0 0.0 1 0.4 0 0.0 

Total Eggs 3 1.0 3 0.7 7 0.5 

Total Grains 22 8.5 32 8.0 45 3.5 

Total Vegetables 95 37.7 82 20.3 108 8.4 

Total Fruits 110 43.4 166 41.1 209 16.3 

Total Fatsb 17 6.7 32 8.0 41 3.2 

Total Foodsa 29 100.0 43 100.0 135 100.0 

Total Dairy 0 0.4 8 18.0 87 64.2 

Total Meats 0 0.3 2 4.7 5 3.3 

Total Fish 0 0.0 0 0.3 0 0.0 

Total Eggs 0 1.1 0 0.9 1 0.5 

Total Grains 2 8.0 3 7.1 5 3.5 

Total Vegetables 11 38.2 9 20.0 12 8.6 

Total Fruits 13 43.4 17 40.4 22 16.6 

Total Fatsb 2 6.7 4 8.3 4 3.2 

Age Group: 1 to <2 years (g/day) Age Group: 1 to <2 years (g/kg-day) 

Total Foodsa 569 100.0 1,014 100.0 1,687 100.0 

Total Dairy 46 8.0 456 45.0 1,165 69.0 

Total Meats 30 5.2 43 4.2 52 3.1 

Total Fish 2 0.4 2 0.2 3 0.2 

Total Eggs 12 2.0 13 1.3 19 1.1 

Total Grains 54 9.5 64 6.3 65 3.8 

Total Vegetables 128 22.5 114 11.3 111 6.6 

Total Fruits 264 46.4 278 27.4 209 12.4 

Total Fatsb 25 4.5 36 3.6 59 3.5 

Total Foodsa 51 100.0 82 100.0 155 100.0 

Total Dairy 4 7.7 38 45.6 106 68.2 

Total Meats 3 5.5 4 5.3 4 2.8 

Total Fish 0 0.2 0 0.3 0 0.1 

Total Eggs 1 2.1 1 1.6 1 0.9 

Total Grains 5 9.5 6 7.2 6 3.7 

Total Vegetables 11 22.2 11 13.0 11 6.9 

Total Fruits 24 46.6 19 22.7 21 13.7 

Total Fatsb 2 4.5 3 3.8 5 3.4 

Age Group: 2 to <3 years (g/day) Age Group: 2 to <3 years (g/kg-day) 

Total Foodsa 641 100.0 981 100.0 1,546 100.0 

Total Dairy 57 9.0 348 35.5 883 57.1 

Total Meats 45 6.9 59 6.0 60 3.9 

Total Fish 4 0.6 3 0.3 4 0.3 

Total Eggs 21 3.2 18 1.9 20 1.3 

Total Grains 75 11.8 86 8.7 86 5.6 

Total Vegetables 155 24.1 148 15.1 143 9.2 

Total Fruits 240 37.5 264 26.9 286 18.5 

Total Fatsb 32 5.0 42 4.3 55 3.6 

Total Foodsa 46 100.0 73 100.0 114 100.0 

Total Dairy 4 8.2 24 32.6 67 58.3 

Total Meats 3 7.4 5 6.5 4 3.8 

Total Fish 0 0.4 0 0.3 0 0.2 

Total Eggs 1 3.2 1 1.6 2 1.3 

Total Grains 5 11.6 6 8.7 7 5.7 

Total Vegetables 11 23.6 11 14.9 11 9.5 

Total Fruits 18 38.7 22 29.9 19 16.6 

Total Fatsb 2 5.2 3 4.3 4 3.7 

Exposure Factors Handbook PageSeptember 2011 14-25 
Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat and Dairy Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 3 to <6 years (g/day) Age Group: 3 to <6 years (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

702 

75 

52 

5 

15 

85 

159 

258 

35 

100.0 

10.7 

7.5 

0.7 

2.2 

12.0 

22.6 

36.7 

5.0 

1,043 

352 

79 

5 

16 

107 

167 

251 

51 

100.0 

33.8 

7.6 

0.5 

1.5 

10.2 

16.0 

24.1 

4.9 

1,646 

878 

88 

5 

19 

121 

191 

259 

67 

100.0 

53.3 

5.4 

0.3 

1.2 

7.3 

11.6 

15.8 

4.1 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

39 

4 

3 

0 

1 

5 

9 

14 

2 

100.0 

10.8 

7.6 

0.8 

2.2 

12.0 

22.7 

36.1 

5.1 

59 

20 

4 

0 

1 

6 

10 

15 

3 

100.0 

33.6 

7.1 

0.4 

1.6 

10.0 

16.1 

25.0 

4.7 

97 

52 

5 

0 

1 

7 

11 

16 

4 

100.0 

53.1 

5.2 

0.3 

1.0 

7.2 

11.7 

16.2 

4.1 

Age Group: 6 to <11 years (g/day) Age Group: 6 to <11 years (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

725 

76 

66 

6 

16 

101 

202 

198 

43 

100.0 

10.5 

9.2 

0.8 

2.3 

13.9 

27.9 

27.3 

6.0 

1,061 

366 

91 

7 

17 

116 

205 

178 

56 

100.0 

34.5 

8.6 

0.7 

1.6 

10.9 

19.4 

16.7 

5.3 

1,727 

883 

105 

6 

18 

151 

245 

221 

73 

100.0 

51.1 

6.1 

0.3 

1.1 

8.7 

14.2 

12.8 

4.2 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

21 

2 

2 

0 

1 

3 

6 

6 

1 

100.0 

11.6 

9.9 

0.8 

2.4 

14.1 

27.0 

25.9 

6.2 

38 

13 

3 

0 

1 

4 

7 

7 

2 

100.0 

34.8 

8.2 

0.6 

1.4 

10.9 

18.7 

17.8 

5.4 

68 

35 

4 

0 

1 

6 

10 

8 

3 

100.0 

51.0 

5.9 

0.4 

1.0 

9.2 

14.1 

12.4 

4.4 

Age Group: 11 to <16 years (g/day) Age Group: 11 to <16 years (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

727 

38 

58 

10 

16 

103 

234 

213 

42 

100.0 

5.2 

8.0 

1.4 

2.2 

14.2 

32.2 

29.3 

5.8 

1,111 

299 

118 

11 

22 

137 

265 

176 

66 

100.0 

26.9 

10.6 

1.0 

2.0 

12.4 

23.9 

15.8 

6.0 

2,045 

1,004 

161 

12 

26 

181 

332 

204 

104 

100.0 

49.1 

7.9 

0.6 

1.3 

8.9 

16.2 

10.0 

5.1 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

12 

1 

1 

0 

0 

2 

4 

3 

1 

100.0 

4.9 

9.3 

1.3 

2.5 

14.2 

32.4 

27.0 

6.3 

23 

6 

2 

0 

0 

3 

6 

4 

1 

100.0 

26.0 

10.9 

0.6 

1.5 

11.5 

24.5 

17.1 

6.1 

43 

21 

3 

0 

1 

4 

7 

5 

2 

100.0 

47.9 

7.5 

0.8 

1.2 

9.1 

15.5 

11.8 

4.9 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-26 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 14-8. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Meat and Dairy Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 16 to <21 years (g/day) Age Group: 16 to <21 years (g/kg-day) 

Total Foodsa 610 100.0 1,017 100.0 2,379 100.0 Total Foodsa 9 100.0 15 100.0 34 100.0 

Total Dairy 22 3.5 204 20.1 923 38.8 Total Dairy 0 3.8 3 19.1 13 39.1 

Total Meats 42 6.8 128 12.6 256 10.8 Total Meats 1 6.8 2 13.4 4 10.8 

Total Fish 12 1.9 12 1.2 8 0.3 Total Fish 0 1.8 0 0.9 0 0.3 

Total Eggs 13 2.2 19 1.8 28 1.2 Total Eggs 0 2.0 0 1.8 0 1.1 

Total Grains 87 14.3 140 13.8 233 9.8 Total Grains 1 14.6 2 14.3 3 10.1 

Total Vegetables 202 33.1 305 29.9 492 20.7 Total Vegetables 3 34.0 5 30.4 7 20.8 

Total Fruits 177 29.1 133 13.1 282 11.9 Total Fruits 3 28.1 2 12.2 4 11.2 

Total Fatsb 34 5.6 68 6.6 127 5.3 Total Fatsb 1 5.5 1 6.8 2 5.4 

Age Group: 20 years and older (g/day) Age Group: 20 years and older (g/kg-day) 

Total Foodsa 679 100.0 1,050 100.0 1,860 100.0 Total Foodsa 9 100.0 14 100.0 26 100.0 

Total Dairy 28 4.1 157 14.9 696 37.5 Total Dairy 0 3.9 2 15.2 10 37.6 

Total Meats 45 6.6 136 12.9 208 11.2 Total Meats 1 6.8 2 12.7 3 10.4 

Total Fish 21 3.1 14 1.3 17 0.9 Total Fish 0 3.1 0 1.4 0 1.0 

Total Eggs 19 2.8 22 2.1 29 1.5 Total Eggs 0 2.8 0 2.1 0 1.5 

Total Grains 99 14.6 131 12.5 185 10.0 Total Grains 1 14.5 2 12.9 3 9.8 

Total Vegetables 236 34.7 319 30.3 385 20.7 Total Vegetables 3 35.0 4 29.9 5 20.3 

Total Fruits 179 26.3 190 18.1 215 11.6 Total Fruits 2 26.1 3 18.1 3 13.1 

Total Fatsb 34 5.0 65 6.1 100 5.4 Total Fatsb 0 5.1 1 6.0 1 5.1 a Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and 

fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups. b Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-27 
 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fish Intake 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: Birth to <1 month (g/day)a Age Group: Birth to <1 month (g/kg-day)a 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

67 100.0 - - - -

41 61.5 - - - -

0 0.0 - - - -

0 0.0 - - - -

0 0.0 - - - -

0 0.7 - - - -

5 7.7 - - - -

1 1.3 - - - -

19 28.3 - - - -

Total Foodsb 20 100.0 - - - -

Total Dairy 12 61.6 - - - -

Total Meats 0 0.0 - - - -

Total Fish 0 0.0 - - - -

Total Eggs 0 0.0 - - - -

Total Grains 0 0.7 - - - -

Total Vegetables 2 7.7 - - - -

Total Fruits 0 1.1 - - - -

Total Fatsc 6 28.4 - - - -

Age Group: 1 to <3 months (g/day)a Age Group: 1 to <3 months (g/kg-day)a 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

80 100.0 - - - -

37 46.5 - - - -

0 0.0 - - - -

0 0.0 - - - -

0 0.0 - - - -

1 1.5 - - - -

15 18.5 - - - -

4 5.2 - - - -

21 26.4 - - - -

Total Foodsb 16 100.0 - - - -

Total Dairy 8 48.2 - - - -

Total Meats 0 0.0 - - - -

Total Fish 0 0.0 - - - -

Total Eggs 0 0.0 - - - -

Total Grains 0 1.4 - - - -

Total Vegetables 3 16.6 - - - -

Total Fruits 1 5.5 - - - -

Total Fatsc 4 26.5 - - - -

Age Group: 3 to <6 months (g/day)d Age Group: 3 to <6 months (g/kg-day)d 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

196 100.0 - - 410 100.0 

55 28.3 - - 159 38.8 

2 0.8 - - 28 6.8 

0 0.0 - - 17 4.1 

0 0.1 - - 4 1.0 

8 3.9 - - 47 11.5 

34 17.2 - - 34 8.3 

68 34.7 - - 30 7.2 

28 14.1 - - 81 19.8 

Total Foodsb 28 100.0 - - 53 100.0 

Total Dairy 8 28.9 - - 21 38.8 

Total Meats 0 0.7 - - 4 6.8 

Total Fish 0 0.0 - - 2 4.1 

Total Eggs 0 0.1 - - 1 1.0 

Total Grains 1 3.8 - - 6 11.5 

Total Vegetables 5 17.1 - - 4 8.3 

Total Fruits 9 33.9 - - 4 7.2 

Total Fatsc 4 14.5 - - 11 19.8 

Page Exposure Factors Handbook 14-28 September 2011 
Chapter 14—Total Food Intake 

Exposure Factors Handbook 

Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fish Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 6 to <12 months (g/day)e Age Group: 6 to <12 months (g/kg-day)e 

Total Foodsb 799 100.0 - - 770 100.0 

Total Dairy 334 41.8 - - 287 37.3 

Total Meats 38 4.7 - - 46 6.0 

Total Fish 0 0.0 - - 7 0.9 

Total Eggs 11 1.4 - - 14 1.9 

Total Grains 47 5.9 - - 66 8.6 

Total Vegetables 101 12.6 - - 117 15.3 

Total Fruits 227 28.4 - - 194 25.2 

Total Fatsc 37 4.7 - - 36 4.7 

Total Foodsb 81 100.0 - - 74 100.0 

Total Dairy 34 41.8 - - 27 37.1 

Total Meats 4 4.7 - - 4 6.0 

Total Fish 0 0.0 - - 1 0.9 

Total Eggs 1 1.4 - - 1 2.0 

Total Grains 5 5.9 - - 6 8.4 

Total Vegetables 10 12.6 - - 12 15.6 

Total Fruits 23 28.4 - - 19 25.2 

Total Fatsc 4 4.7 - - 3 4.7 

Age Group: 1 to <2 years (g/day)e Age Group: 1 to <2 years (g/kg-day)e 

Total Foodsb 1,032 100.0 - - 1,139 100.0 

Total Dairy 496 48.1 - - 461 40.5 

Total Meats 46 4.5 - - 56 4.9 

Total Fish 0 0.0 - - 26 2.3 

Total Eggs 14 1.4 - - 19 1.7 

Total Grains 65 6.3 - - 76 6.7 

Total Vegetables 118 11.4 - - 151 13.2 

Total Fruits 247 24.0 - - 300 26.3 

Total Fatsc 39 3.8 - - 43 3.8 

Total Foodsb 90 100.0 - - 98 100.0 

Total Dairy 43 48.2 - - 41 42.4 

Total Meats 4 4.4 - - 5 4.8 

Total Fish 0 0.0 - - 2 2.2 

Total Eggs 1 1.3 - - 2 1.6 

Total Grains 6 6.2 - - 7 6.7 

Total Vegetables 10 11.4 - - 12 12.3 

Total Fruits 22 24.0 - - 25 25.5 

Total Fatsc 3 3.8 - - 4 3.8 

Age Group: 2 to <3 years (g/day)e Age Group: 2 to <3 years (g/kg-day)e 

Total Foodsb 1,015 100.0 - - 1,107 100.0 

Total Dairy 381 37.6 - - 424 38.3 

Total Meats 62 6.1 - - 53 4.8 

Total Fish 0 0.0 - - 31 2.8 

Total Eggs 18 1.8 - - 17 1.6 

Total Grains 81 7.9 - - 84 7.6 

Total Vegetables 144 14.2 - - 142 12.8 

Total Fruits 276 27.2 - - 304 27.4 

Total Fatsc 42 4.2 - - 43 3.9 

Total Foodsb 73 100.0 - - 82 100.0 

Total Dairy 28 37.9 - - 31 37.6 

Total Meats 4 6.0 - - 4 4.6 

Total Fish 0 0.0 - - 2 2.9 

Total Eggs 1 1.7 - - 1 1.5 

Total Grains 6 7.9 - - 6 7.5 

Total Vegetables 10 14.1 - - 10 12.7 

Total Fruits 20 27.0 - - 23 28.5 

Total Fatsc 3 4.2 - - 3 3.9 

Exposure Factors Handbook PageSeptember 2011 14-29 
Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fish Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 3 to <6 years (g/day)e Age Group: 3 to <6 years (g/kg-day)e 

Total Foodsb 1,053 100.0 - - 1,156 100.0 

Total Dairy 390 37.1 - - 399 34.5 

Total Meats 76 7.2 - - 62 5.3 

Total Fish 0 0.0 - - 43 3.7 

Total Eggs 16 1.5 - - 17 1.4 

Total Grains 101 9.6 - - 103 8.9 

Total Vegetables 168 15.9 - - 193 16.7 

Total Fruits 237 22.5 - - 273 23.6 

Total Fatsc 50 4.8 - - 50 4.3 

Total Foodsb 60 100.0 - - 66 100.0 

Total Dairy 22 37.1 - - 22 33.9 

Total Meats 4 7.1 - - 3 5.3 

Total Fish 0 0.0 - - 2 3.7 

Total Eggs 1 1.5 - - 1 1.6 

Total Grains 6 9.5 - - 6 9.0 

Total Vegetables 9 15.8 - - 11 16.9 

Total Fruits 14 22.7 - - 16 23.8 

Total Fatsc 3 4.7 - - 3 4.3 

Age Group: 6 to <11 years (g/day)e Age Group: 6 to <11 years (g/kg-day)e 

Total Foodsb 1,109 100.0 - - 1,23 

4 

100.0 

Total Dairy 408 36.8 - - 430 34.8 

Total Meats 89 8.0 - - 76 6.2 

Total Fish 0 0.0 - - 51 4.1 

Total Eggs 15 1.3 - - 22 1.8 

Total Grains 119 10.7 - - 126 10.2 

Total Vegetables 208 18.8 - - 233 18.9 

Total Fruits 190 17.1 - - 218 17.7 

Total Fatsc 58 5.2 - - 61 4.9 

Total Foodsb 40 100.0 - - 44 100.0 

Total Dairy 15 37.0 - - 16 35.6 

Total Meats 3 7.9 - - 3 6.1 

Total Fish 0 0.0 - - 2 4.1 

Total Eggs 1 1.3 - - 1 1.6 

Total Grains 4 10.7 - - 4 10.1 

Total Vegetables 7 18.5 - - 8 18.4 

Total Fruits 7 17.3 - - 8 17.5 

Total Fatsc 2 5.2 - - 2 4.9 

Page Exposure Factors Handbook 14-30 September 2011 
Chapter 14—Total Food Intake 

Exposure Factors Handbook 

Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fish Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 11 to <16 years (g/day)e Age Group: 11 to <16 years (g/kg-day)e 

Total Foodsb 1,197 100.0 - - 1,378 100.0 

Total Dairy 372 31.1 - - 397 28.8 

Total Meats 117 9.8 - - 104 7.5 

Total Fish 0 0.0 - - 72 5.2 

Total Eggs 17 1.4 - - 28 2.0 

Total Grains 135 11.3 - - 146 10.6 

Total Vegetables 277 23.1 - - 310 22.5 

Total Fruits 190 15.8 - - 226 16.4 

Total Fatsc 69 5.8 - - 76 5.5 

Total Foodsb 24 100.0 - - 28 100.0 

Total Dairy 7 31.1 - - 9 30.9 

Total Meats 2 9.7 - - 2 6.9 

Total Fish 0 0.0 - - 1 4.9 

Total Eggs 0 1.4 - - 1 1.9 

Total Grains 3 11.3 - - 3 10.5 

Total Vegetables 5 22.9 - - 6 21.1 

Total Fruits 4 16.2 - - 5 17.1 

Total Fatsc 1 5.7 - - 1 5.2 

Age Group: 16 to <21 years (g/day)e Age Group: 16 to <21 years (g/kg-day)e 

Total Foodsb 1,171 100.0 - - 1,339 100.0 

Total Dairy 288 24.6 - - 261 19.5 

Total Meats 143 12.2 - - 139 10.4 

Total Fish 0 0.0 - - 86 6.5 

Total Eggs 20 1.7 - - 21 1.6 

Total Grains 146 12.5 - - 162 12.1 

Total Vegetables 325 27.8 - - 357 26.6 

Total Fruits 160 13.7 - - 219 16.3 

Total Fatsc 75 6.4 - - 80 6.0 

Total Foodsb 18 100.0 - - 19 100.0 

Total Dairy 4 24.5 - - 4 20.3 

Total Meats 2 11.9 - - 2 9.4 

Total Fish 0 0.0 - - 1 6.7 

Total Eggs 0 1.7 - - 0 1.6 

Total Grains 2 12.5 - - 2 12.0 

Total Vegetables 5 27.9 - - 5 26.0 

Total Fruits 2 13.9 - - 3 16.9 

Total Fatsc 1 6.4 - - 1 5.9 

Exposure Factors Handbook PageSeptember 2011 14-31 
 

 

 

 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-9. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fish Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 20 years and older (g/day) Age Group: 20 years and older (g/kg-day) 

Total Foodsb 1,040 100.0 1,060 100.0 1,340 100.0 

Total Dairy 207 20.0 205 19.3 250 18.7 

Total Meats 126 12.1 143 13.4 121 9.1 

Total Fish 0 0.0 0 0.0 102 7.7 

Total Eggs 22 2.1 24 2.2 27 2.0 

Total Grains 134 12.9 133 12.5 152 11.4 

Total Vegetables 303 29.2 300 28.3 348 26.0 

Total Fruits 165 15.9 180 16.9 238 17.8 

Total Fatsc 62 6.0 64 6.0 74 5.5 

Total Foodsb 14 100.0 15 100.0 19 100.0 

Total Dairy 3 20.2 3 19.1 4 19.0 

Total Meats 2 11.9 2 12.7 2 8.5 

Total Fish 0 0.0 0 0.0 1 7.6 

Total Eggs 0 2.0 0 2.0 0 1.9 

Total Grains 2 13.0 2 12.3 2 11.2 

Total Vegetables 4 29.1 4 28.3 5 26.0 

Total Fruits 2 16.1 3 18.2 4 18.7 

Total Fatsc 1 5.9 1 5.8 1 5.2 

a All individuals in this sample group consumed 0 g/day of fish. Therefore, only low-end consumers are reported. b Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and 

fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups. c Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats. d Only one individual in this sample group consumed more than 0 g/day of fish. Therefore, this sample is reported in the high-end consumer group and all other 

samples are placed in the low-end consumer group. e All individuals in this sample group below the 80th percentile consumed 0 g/day of fish. Therefore, only high-end and low-end consumer groups are reported. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Page Exposure Factors Handbook 14-32 September 2011 
 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fruit and Vegetable Intake 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: Birth to <1 month (g/day)a Age Group: Birth to <1 month (g/kg-day)a 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

49 100.0 - - 101 100.0 

34 69.7 - - 21 21.1 

0 0.0 - - 0 0.0 

0 0.0 - - 0 0.0 

0 0.0 - - 0 0.0 

1 1.2 - - 0.21 0.2 

0 0.0 - - 44 43.3 

0 0.0 - - 8 7.6 

14 29.1 - - 25 24.8 

Total Foodsb 14 100.0 - - 29 100.0 

Total Dairy 10 69.6 - - 6 19.4 

Total Meats 0 0.0 - - 0 0.0 

Total Fish 0 0.0 - - 0 0.0 

Total Eggs 0 0.0 - - 0 0.0 

Total Grains 0 1.3 - - 0 0.2 

Total Vegetables 0 0.0 - - 13 44.8 

Total Fruits 0 0.0 - - 2 6.4 

Total Fatsc 4 29.1 - - 7 25.4 

Age Group: 1 to <3 months (g/day)a Age Group: 1 to <3 months (g/kg-day)a 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

49 100.0 - - 171 100.0 

34 69.2 - - 16 9.5 

0 0.0 - - 0 0.0 

0 0.0 - - 0 0.0 

0 0.0 - - 0 0.0 

1 1.9 - - 2 1.0 

0 0.0 - - 89 52.0 

0 0.0 - - 18 10.2 

14 28.9 - - 40 23.4 

Total Foodsb 11 100.0 - - 35 100.0 

Total Dairy 7 69.4 - - 4 11.5 

Total Meats 0 0.0 - - 0 0.0 

Total Fish 0 0.0 - - 0 0.0 

Total Eggs 0 0.0 - - 0 0.0 

Total Grains 0 1.7 - - 0 1.1 

Total Vegetables 0 0.0 - - 16 46.8 

Total Fruits 0 0.0 - - 5 13.9 

Total Fatsc 3 29.0 - - 8 22.7 

Age Group: 3 to <6 months (g/day) Age Group: 3 to <6 months (g/kg-day) 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

69 100.0 144 100.0 495 100.0 

47 68.0 51 35.6 49 9.9 

0 0.0 2 1.3 4 0.8 

0 0.0 0 0.3 0 0.0 

0 0.0 1 0.4 0 0.0 

2 3.3 10 6.7 12 2.4 

0 0.0 24 16.6 88 17.7 

0 0.0 29 19.9 311 62.8 

20 28.4 25 17.7 27 5.4 

Total Foodsb 11 100.0 21 100.0 70 100.0 

Total Dairy 7 68.1 8 37.2 7 10.1 

Total Meats 0 0.0 0 1.5 1 0.7 

Total Fish 0 0.0 0 0.3 0 0.0 

Total Eggs 0 0.0 0 0.5 0 0.0 

Total Grains 0 3.2 1 6.6 2 2.6 

Total Vegetables 0 0.0 3 15.1 12 17.7 

Total Fruits 0 0.0 4 20.8 44 62.4 

Total Fatsc 3 28.5 4 16.9 4 5.5 

Exposure Factors Handbook PageSeptember 2011 14-33 
 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fruit and Vegetable Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 6 to <12 months (g/day) Age Group: 6 to <12 months (g/kg-day) 

Total Foodsb 189 100.0 461 100.0 951 100.0 

Total Dairy 91 48.3 129 28.0 207 21.8 

Total Meats 8 4.0 17 3.6 37 3.9 

Total Fish 1 0.4 1 0.2 0 0.0 

Total Eggs 4 1.9 9 1.9 8 0.8 

Total Grains 23 12.1 31 6.8 41 4.3 

Total Vegetables 18 9.4 83 18.1 160 16.8 

Total Fruits 15 7.7 158 34.3 459 48.2 

Total Fatsc 31 16.3 31 6.8 35 3.6 

Total Foodsb 21 100.0 57 100.0 100 100.0 

Total Dairy 10 48.1 19 33.2 18 17.9 

Total Meats 1 3.6 2 4.3 4 3.8 

Total Fish 0 0.4 0 0.1 0 0.0 

Total Eggs 0 1.7 1 1.0 1 0.7 

Total Grains 2 11.4 4 6.5 5 4.6 

Total Vegetables 2 9.3 10 16.9 19 19.0 

Total Fruits 2 8.4 18 30.8 50 49.5 

Total Fatsc 3 16.8 4 6.6 4 3.9 

Age Group: 1 to <2 years (g/day) Age Group: 1 to <2 years (g/kg-day) 

Total Foodsb 796 100.0 1,048 100.0 1,499 100.0 

Total Dairy 578 72.7 535 51.0 425 28.4 

Total Meats 35 4.5 46 4.4 62 4.2 

Total Fish 1 0.1 3 0.3 5 0.4 

Total Eggs 8 1.0 16 1.5 17 1.1 

Total Grains 49 6.2 65 6.2 77 5.1 

Total Vegetables 56 7.1 123 11.7 179 11.9 

Total Fruits 26 3.2 210 20.1 687 45.8 

Total Fatsc 36 4.6 41 3.9 39 2.6 

Total Foodsb 68 100.0 88 100.0 133 100.0 

Total Dairy 49 71.8 44 49.6 39 29.5 

Total Meats 3 4.7 4 4.5 5 3.6 

Total Fish 0 0.2 0 0.3 0 0.2 

Total Eggs 1 1.1 1 1.2 2 1.2 

Total Grains 4 6.2 6 6.9 7 5.2 

Total Vegetables 5 7.1 11 12.6 15 11.6 

Total Fruits 2 3.4 18 20.5 60 45.4 

Total Fatsc 3 4.7 3 3.7 4 2.7 

Age Group: 2 to <3 years (g/day) Age Group: 2 to <3 years (g/kg-day) 

Total Foodsb 601 100.0 942 100.0 1,589 100.0 

Total Dairy 308 51.2 352 37.4 384 24.1 

Total Meats 53 8.8 59 6.3 64 4.0 

Total Fish 2 0.3 4 0.5 5 0.3 

Total Eggs 14 2.3 18 2.0 20 1.3 

Total Grains 72 12.0 80 8.5 91 5.7 

Total Vegetables 81 13.4 141 15.0 202 12.7 

Total Fruits 24 4.0 237 25.1 765 48.1 

Total Fatsc 38 6.3 40 4.2 46 2.9 

Total Foodsb 43 100.0 69 100.0 114 100.0 

Total Dairy 22 51.3 27 39.3 27 23.6 

Total Meats 4 8.8 4 6.0 4 3.8 

Total Fish 0 0.3 0 0.4 0 0.4 

Total Eggs 1 2.3 1 1.9 2 1.4 

Total Grains 5 12.0 6 8.6 7 5.7 

Total Vegetables 6 13.8 10 14.0 14 12.4 

Total Fruits 2 3.7 17 24.6 56 49.1 

Total Fatsc 3 6.3 3 4.1 3 2.9 

Page Exposure Factors Handbook 14-34 September 2011 
Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fruit and Vegetable Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 3 to <6 years (g/day) Age Group: 3 to <6 years (g/kg-day) 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

731 

388 

60 

4 

13 

92 

92 

27 

45 

100.0 

53.1 

8.2 

0.5 

1.7 

12.5 

12.5 

3.6 

6.1 

1,014 

385 

74 

7 

14 

96 

174 

199 

49 

100.0 

38.0 

7.3 

0.7 

1.4 

9.4 

17.1 

19.6 

4.9 

1,594 

401 

81 

9 

21 

113 

231 

668 

53 

100.0 

25.1 

5.1 

0.6 

1.3 

7.1 

14.5 

41.9 

3.3 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

40 

21 

3 

0 

1 

5 

5 

1 

2 

100.0 

52.7 

8.6 

0.4 

1.6 

12.4 

13.0 

3.4 

6.1 

58 

22 

4 

0 

1 

6 

10 

11 

3 

100.0 

38.2 

7.0 

0.6 

1.4 

10.3 

16.5 

19.5 

4.9 

95 

25 

5 

0 

1 

7 

13 

41 

3 

100.0 

25.8 

4.8 

0.5 

1.1 

6.8 

13.9 

42.5 

3.3 

Age Group: 6 to <11 years (g/day) Age Group: 6 to <11 years (g/kg-day) 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

784 

385 

76 

5 

16 

105 

103 

26 

48 

100.0 

49.2 

9.7 

0.6 

2.1 

13.3 

13.2 

3.4 

6.2 

1,068 

406 

88 

6 

16 

117 

213 

144 

59 

100.0 

38.0 

8.3 

0.6 

1.5 

11.0 

19.9 

13.5 

5.5 

1,664 

448 

98 

8 

17 

127 

313 

559 

64 

100.0 

26.9 

5.9 

0.5 

10. 

7.6 

18.8 

33.6 

3.9 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

23 

11 

2 

0 

1 

3 

3 

1 

1 

100.0 

47.0 

10.1 

0.8 

2.3 

13.8 

13.8 

3.6 

6.4 

38 

14 

3 

0 

1 

5 

7 

5 

2 

100.0 

37.6 

8.9 

0.4 

1.5 

11.8 

19.1 

13.3 

5.4 

64 

18 

4 

0 

1 

5 

11 

22 

3 

100.0 

27.5 

5.7 

0.5 

1.2 

8.1 

17.7 

33.6 

3.9 

Age Group: 11 to <16 years (g/day) Age Group: 11 to <16 years (g/kg-day) 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

709 

301 

91 

3 

13 

106 

125 

13 

49 

100.0 

42.4 

12.8 

0.4 

1.8 

15.0 

17.7 

1.9 

6.9 

1,149 

362 

112 

10 

20 

136 

286 

136 

66 

100.0 

31.5 

9.7 

0.8 

1.7 

11.8 

24.9 

11.8 

5.8 

1,911 

395 

146 

14 

24 

165 

458 

597 

87 

100.0 

20.7 

7.7 

0.7 

1.3 

8.6 

24.0 

31.2 

4.5 

Total Foodsb 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsc 

12 

5 

1 

0 

0 

2 

2 

0 

1 

100.0 

42.0 

12.4 

0.5 

1.9 

14.8 

18.2 

2.2 

7.0 

23 

8 

2 

0 

0 

3 

5 

3 

1 

100.0 

33.1 

9.8 

0.5 

1.7 

12.1 

23.0 

12.3 

5.9 

39 

9 

3 

0 

1 

3 

9 

13 

2 

100.0 

22.3 

6.4 

0.5 

1.5 

8.8 

22.4 

32.3 

4.2 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-35 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 14-10. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Fruit and Vegetable Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 16 to <21 years (g/day) Age Group: 16 to <21 years (g/kg-day) 

Total Foodsb 624 100.0 970 100.0 2,353 100.0 Total Foodsb 9 100.0 16 100.0 34 100.0 

Total Dairy 238 38.1 203 21.0 449 19.1 Total Dairy 4 39.0 3 21.0 6 17.8 

Total Meats 76 12.2 112 11.5 245 10.4 Total Meats 1 11.7 2 12.7 3 9.6 

Total Fish 8 1.2 15 1.6 17 0.7 Total Fish 0 1.4 0 0.8 0 0.6 

Total Eggs 21 3.3 16 1.6 30 1.3 Total Eggs 0 3.4 0 2.5 0 1.0 

Total Grains 100 16.1 138 14.2 211 9.0 Total Grains 1 16.2 2 14.6 3 10.0 

Total Vegetables 109 17.5 283 29.2 615 26.1 Total Vegetables 2 17.9 5 30.7 9 25.8 

Total Fruits 18 2.9 121 12.5 644 27.4 Total Fruits 0 1.8 1 9.1 10 30.0 

Total Fatsc 46 7.3 66 6.8 116 4.9 Total Fatsc 1 7.2 1 7.5 2 4.4 

Age Group: 20 years and older (g/day) Age Group: 20 years and older (g/kg-day) 

Total Foodsb 602 100.0 1,040 100.0 1,920 100.0 Total Foodsb 8 100.0 14 100.0 27 100.0 

Total Dairy 178 29.6 215 20.6 282 14.7 Total Dairy 2 28.6 3 20.3 4 14.7 

Total Meats 99 16.4 129 12.4 168 8.7 Total Meats 1 16.9 2 13.0 2 7.5 

Total Fish 11 1.8 15 1.4 23 1.2 Total Fish 0 1.8 0 1.2 0 1.3 

Total Eggs 21 3.5 23 2.2 28 1.5 Total Eggs 0 3.4 0 2.1 0 1.3 

Total Grains 105 17.5 131 12.6 177 9.2 Total Grains 1 17.8 2 13.2 2 9.0 

Total Vegetables 115 19.1 306 29.4 527 27.4 Total Vegetables 2 19.6 4 29.7 7 27.2 

Total Fruits 16 2.6 138 13.3 610 31.7 Total Fruits 0 2.5 2 12.5 9 33.9 

Total Fatsc 45 7.5 64 6.2 83 4.3 Total Fatsc 1 7.7 1 6.3 1 3.8 a All individuals in this sample group below the 75th percentile consumed 0 g/day of fruits and vegetables. Therefore, only high-end and low-end consumer 

groups are reported. b Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, grains, vegetables, fruits, and 

fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups. c Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats. 

Source: U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-36 September 2011 
Chapter 14—Total Food Intake 

Exposure Factors Handbook 

Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Dairy Intake 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: Birth to <1 month (g/day) Age Group: Birth to <1 month (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

12 100.0 60 100.0 185 100.0 

0 0.0 40 67.3 127 69.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.3 0 0.0 4 2.2 

8 66.1 2 3.4 1 0.4 

0 0.0 0 0.0 0 0.0 

3 27.1 18 29.2 52 28.4 

Total Foodsa 4 100.0 18 100.0 56 100.0 

Total Dairy 0 0.0 12 67.1 39 69.0 

Total Meats 0 0.0 0 0.0 0 0.0 

Total Fish 0 0.0 0 0.0 0 0.0 

Total Eggs 0 0.0 0 0.0 0 0.0 

Total Grains 0 0.2 0 0.0 1 2.1 

Total Vegetables 2 64.4 1 3.7 0 0.5 

Total Fruits 0 0.0 0 0.0 0 0.0 

Total Fatsb 1 27.5 5 29.2 16 28.4 

Age Group: 1 to <3 months (g/day) Age Group: 1 to <3 months (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

36 100.0 84 100.0 166 100.0 

0 0.0 19 22.4 109 65.6 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.0 0 0.0 0 0.0 

0 0.9 1 1.2 0 0.8 

21 58.8 42 50.7 4 2.7 

2 4.3 0 0.0 6 3.7 

10 26.7 21 25.4 45 27.2 

Total Foodsa 7 100.0 14 100.0 41 100.0 

Total Dairy 0 0.0 3 24.0 26 64.1 

Total Meats 0 0.0 0 0.0 0 0.0 

Total Fish 0 0.0 0 0.0 0 0.0 

Total Eggs 0 0.0 0 0.0 0 0.0 

Total Grains 0 0.8 0 2.0 0 0.6 

Total Vegetables 4 57.8 7 48.7 0 1.1 

Total Fruits 0 5.4 0 0.0 3 7.7 

Total Fatsb 2 26.4 4 25.0 11 26.5 

Age Group: 3 to <6 months (g/day) Age Group: 3 to <6 months (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

132 100.0 217 100.0 346 100.0 

0 0.0 59 27.0 160 46.3 

1 0.4 2 1.0 4 1.1 

0 0.0 0 0.0 0 0.1 

0 0.0 0 0.2 1 0.2 

6 4.5 8 3.8 12 3.4 

46 34.9 37 17.0 26 7.6 

58 44.1 84 38.8 87 25.1 

16 11.9 26 12.1 55 15.8 

Total Foodsa 19 100.0 32 100.0 44 100.0 

Total Dairy 0 0.0 8 24.8 24 54.9 

Total Meats 0 0.5 0 0.7 0 1.0 

Total Fish 0 0.0 0 0.0 0 0.1 

Total Eggs 0 0.0 0 0.3 0 0.1 

Total Grains 1 4.5 1 3.8 2 3.4 

Total Vegetables 7 35.6 4 13.7 2 5.0 

Total Fruits 8 43.0 14 45.8 7 15.9 

Total Fatsb 2 12.2 3 10.7 8 19.2 

Exposure Factors Handbook PageSeptember 2011 14-37 
 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Dairy Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 6 to <12 months (g/day) Age Group: 6 to <12 months (g/kg-day) 

Total Foodsa 317 100.0 368 100.0 1,285 100.0 

Total Dairy 0 0.0 71 19.2 833 64.8 

Total Meats 11 3.4 16 4.4 41 3.2 

Total Fish 0 0.0 1 0.3 0 0.0 

Total Eggs 3 0.9 5 1.4 6 0.5 

Total Grains 27 8.6 23 6.3 46 3.6 

Total Vegetables 114 35.9 75 20.4 106 8.2 

Total Fruits 137 43.3 147 39.9 211 16.4 

Total Fatsb 20 6.4 30 8.2 40 3.1 

Total Foodsa 36 100.0 43 100.0 135 100.0 

Total Dairy 0 0.0 8 18.2 87 64.8 

Total Meats 1 3.5 2 4.8 4 3.0 

Total Fish 0 0.0 0 0.3 0 0.0 

Total Eggs 0 1.0 1 2.1 1 0.5 

Total Grains 3 7.9 3 7.7 5 3.5 

Total Vegetables 13 35.3 8 17.9 11 8.2 

Total Fruits 16 44.6 18 40.7 22 16.6 

Total Fatsb 2 6.3 4 8.1 4 3.1 

Age Group: 1 to <2 years (g/day) Age Group: 1 to <2 years (g/kg-day) 

Total Foodsa 601 100.0 989 100.0 1,700 100.0 

Total Dairy 40 6.7 451 45.6 1,170 68.8 

Total Meats 43 7.1 51 5.2 45 2.6 

Total Fish 3 0.5 4 0.4 3 0.2 

Total Eggs 14 2.3 15 1.5 18 1.1 

Total Grains 57 9.5 65 6.5 63 3.7 

Total Vegetables 139 23.1 120 12.1 112 6.6 

Total Fruits 268 44.7 240 24.3 226 13.3 

Total Fatsb 29 4.8 38 3.8 58 3.4 

Total Foodsa 55 100.0 86 100.0 154 100.0 

Total Foodsa 3 6.1 38 44.0 106 68.5 

Total Dairy 4 7.2 4 4.8 4 2.6 

Total Meats 0 0.5 1 0.6 0 0.1 

Total Fish 1 2.3 2 1.8 1 0.8 

Total Eggs 5 9.5 6 6.9 6 3.7 

Total Grains 12 21.8 11 13.0 10 6.7 

Total Vegetables 25 46.3 21 24.5 21 13.8 

Total Fruits 3 4.7 3 3.7 5 3.4 

Age Group: 2 to <3 years (g/day) Age Group: 2 to <3 years (g/kg-day) 

Total Foodsa 661 100.0 996 100.0 1,528 100.0 

Total Dairy 48 7.3 348 34.9 885 57.9 

Total Meats 61 9.3 63 6.3 55 3.6 

Total Fish 2 0.3 6 0.6 5 0.3 

Total Eggs 25 3.8 20 2.1 19 1.3 

Total Grains 78 11.9 82 8.2 86 5.6 

Total Vegetables 163 24.7 144 14.5 137 9.0 

Total Fruits 237 35.8 279 28.0 277 18.1 

Total Fatsb 37 5.5 41 4.1 55 3.6 

Total Foodsa 47 100.0 72 100.0 114 100.0 

Total Dairy 3 7.2 24 33.7 67 58.4 

Total Meats 4 9.4 4 6.2 4 3.6 

Total Fish 0 0.3 0 0.4 0 0.2 

Total Eggs 2 3.7 1 1.5 1 1.3 

Total Grains 5 11.6 6 8.5 6 5.7 

Total Vegetables 12 24.6 10 14.0 11 9.3 

Total Fruits 17 36.4 22 30.2 20 17.3 

Total Fatsb 3 5.5 3 4.2 4 3.6 

Page Exposure Factors Handbook 14-38 September 2011 
 

 

 

 

 

 

 

 

 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Dairy Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % 

Age Group: 3 to <6 years (g/day) Age Group: 3 to <6 years (g/kg-day) 

Total Foodsa 725 100.0 1,047 100.0 1,612 100.0 

Total Dairy 64 8.9 355 33.9 886 55.0 

Total Meats 75 10.4 72 6.9 70 4.3 

Total Fish 4 0.6 6 0.5 6 0.4 

Total Eggs 19 2.6 15 1.4 18 1.1 

Total Grains 87 12.1 104 9.9 116 7.2 

Total Vegetables 168 23.2 173 16. 183 11.3 

Total Fruits 253 34.9 257 24.5 251 15.6 

Total Fatsb 40 5.6 49 4.7 63 3.9 

Total Foodsa 41 100.0 58 100.0 97 100.0 

Total Dairy 4 8.8 20 34.2 52 54.0 

Total Meats 4 10.6 4 6.6 4 4.4 

Total Fish 0 0.5 0 0.5 0 0.3 

Total Eggs 1 2.6 1 1.5 1 1.0 

Total Grains 5 12.1 6 9.9 7 7.2 

Total Vegetables 10 23.8 9 16.3 11 11.6 

Total Fruits 14 34.0 14 24.7 16 16.5 

Total Fatsb 2 5.7 3 4.7 4 4.0 

Age Group: 6 to <11 years (g/day) Age Group: 6 to <11 years (g/kg-day) 

Total Foodsa 766 100.0 1,053 100.0 1,722 100.0 

Total Dairy 63 8.2 372 35.4 892 51.8 

Total Meats 99 12.9 80 7.6 87 5.1 

Total Fish 6 0.8 5 0.5 6 0.4 

Total Eggs 17 2.2 14 1.3 17 1.0 

Total Grains 105 13.7 113 10.7 152 8.8 

Total Vegetables 221 28.9 214 20.3 242 14.0 

Total Fruits 194 25.3 175 16.6 227 13.2 

Total Fatsb 49 6.4 56 5.3 70 4.1 

Total Foodsa 25 100.0 38 100.0 67 100.0 

Total Dairy 2 8.1 13 34.2 35 51.9 

Total Meats 3 13.2 2 8.0 3 4.9 

Total Fish 0 0.8 0 0.5 0 0.4 

Total Eggs 1 2.3 1 1.8 1 0.9 

Total Grains 3 13.6 4 10.7 6 9.0 

Total Vegetables 7 29.5 8 19.7 9 13.7 

Total Fruits 6 24.4 7 17.8 9 13.5 

Total Fatsb 2 6.6 2 5.2 3 4.2 

Age Group: 11 to <16 years (g/day) Age Group: 11 to <16 years (g/kg-day) 

Total Foodsa 747 100.0 1,094 100.0 2,020 100.0 

Total Dairy 22 3.0 307 28.0 1,017 50.3 

Total Meats 102 13.6 101 9.2 134 6.7 

Total Fish 8 1.1 9 0.8 12 0.6 

Total Eggs 20 2.7 18 1.6 25 1.2 

Total Grains 104 13.9 133 12.2 181 9.0 

Total Vegetables 239 32.0 265 24.2 322 16.0 

Total Fruits 197 26.4 180 16.4 204 10.1 

Total Fatsb 47 6.2 62 5.6 100 5.0 

Total Foodsa 13 100.0 22 100.0 42 100.0 

Total Dairy 0 2.9 6 27.3 21 49.4 

Total Meats 2 13.8 2 9.6 3 6.4 

Total Fish 0 1.0 0 0.6 0 0.8 

Total Eggs 0 2.6 0 1.7 1 1.2 

Total Grains 2 13.7 3 12.2 4 9.1 

Total Vegetables 4 33.0 5 23.3 6 15.1 

Total Fruits 3 25.7 4 17.8 5 11.9 

Total Fatsb 1 6.2 1 5.9 2 4.8 

Exposure Factors Handbook PageSeptember 2011 14-39 
Table 14-11. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for Individuals With Low-End, 

Mid-Range, and High-End Total Dairy Intake (continued) 

Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer Food 

Group 

Low-End 

Consumer 

Mid-Range 

Consumer 

High-End 

Consumer 

Intake % Intake % Intake % Intake % Intake % Intake % 

Age Group: 16 to <21 years (g/day) Age Group: 16 to <21 years (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

647 

8 

101 

8 

12 

90 

228 

152 

37 

100.0 

1.2 

15.7 

1.2 

1.8 

13.9 

35.2 

23.5 

5.8 

1,095 

197 

125 

16 

28 

162 

324 

154 

73 

100.0 

18.0 

11.4 

1.5 

2.5 

14.8 

29.6 

14.1 

6.7 

2,233 

950 

197 

8 

27 

217 

438 

249 

114 

100.0 

42.5 

8.8 

0.4 

1.2 

9.7 

19.6 

11.2 

5.1 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

10 

0 

2 

0 

0 

1 

4 

2 

1 

100.0 

1.2 

15.1 

1.1 

1.7 

14.1 

35.8 

23.9 

5.6 

17 

3 

2 

0 

0 

2 

5 

3 

1 

100.0 

16.6 

13.6 

0.9 

2.2 

14.0 

28.6 

16.1 

6.5 

33 

14 

3 

0 

0 

3 

7 

3 

2 

100.0 

42.8 

8.9 

0.3 

1.2 

9.6 

20.0 

10.6 

5.1 

Age Group: 20 years and older (g/day) Age Group: 20 years and older (g/kg-day) 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

741 

9 

117 

16 

20 

113 

258 

159 

42 

100.0 

1.2 

15.8 

2.2 

2.7 

15.2 

34.8 

21.4 

5.6 

1,030 

155 

129 

16 

23 

130 

304 

189 

62 

100.0 

15.1 

12.6 

1.6 

2.3 

12.6 

29.6 

18.4 

6.0 

1,810 

725 

156 

19 

26 

176 

361 

226 

89 

100.0 

40.1 

8.6 

1.1 

1.4 

9.7 

20.0 

12.5 

4.9 

Total Foodsa 

Total Dairy 

Total Meats 

Total Fish 

Total Eggs 

Total Grains 

Total Vegetables 

Total Fruits 

Total Fatsb 

10 

0 

2 

0 

0 

2 

4 

2 

1 

100.0 

1.2 

15.8 

2.1 

2.7 

15.0 

34.5 

21.9 

5.5 

14 

2 

2 

0 

0 

2 

4 

3 

1 

100.0 

14.8 

12.3 

1.6 

2.3 

12.5 

29.5 

19.4 

5.9 

25 

10 

2 

0 

0 

2 

5 

3 

1 

100.0 

41.0 

7.3 

1.0 

1.4 

9.5 

19.4 

14.2 

4.5 a 

b 

Source: 

Total food intake was defined as intake of the sum of all foods in the following major food categories: dairy, meats, fish, eggs, g rains, vegetables, fruits, and 

fats. Beverages, sugar, candy, and sweets, and nuts and nut products were not included because they could not be categorized into the major food groups. 

Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats. 

U.S. EPA analysis of 1994−1996, 1998 CSFII. 

Exposure Factors Handbook 

Chapter 14—Total Food Intake 

Page Exposure Factors Handbook 14-40 September 2011 
Table 14-12. Intake of Total Fooda (g/kg-day), Edible Portion, Uncooked Weight 

Age or Race/Ethnic Group N Mean SEb LCLc UCLd Percentiles 

Mine 1st 5th 10th 25th 50th 75th 90th 95th 99th Maxf 

<1 year 

1 to <3 years 

3 to <6 years 

6 to <13 years 

13 to <20 years 

20 to <50 years 

>50 years 

All Ages 

Female 13 to 49 years 

Mexican American 

Non−Hispanic Black 

Non−Hispanic White 

Other Hispanic 

Other 

865 

1,052 

978 

2,256 

3,450 

4,289 

3,893 

16,783 

4,103 

4,450 

4,265 

6,757 

562 

749 

90.9 

113.1 

78.6 

47.1 

27.5 

29.4 

29.1 

36.1 

28.8 

40.2 

30.7 

36.0 

39.5 

40.3 

3.50 

2.46 

1.27 

1.15 

0.69 

0.74 

0.55 

0.56 

0.85 

0.86 

0.85 

0.72 

2.01 

1.94 

Age 

108.0 

76.0 

44.7 

26.0 

27.9 

28.0 

35.0 

27.1 

38.4 

29.0 

34.6 

35.4 

36.3 

98.1 

118.1 

81.2 

49.4 

28.9 

30.9 

30.3 

37.2 

30.5 

42.0 

32.4 

37.5 

43.7 

44.3 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

0* 

38.3* 

28.3* 

7.1* 

5.0 

4.1 

0 

3.4 

3.1 

4.8 

0 

5.4 

0* 

0* 

0* 

54.0* 

41.3 

16.1 

9.4 

9.4 

10.0 

10.0 

9.0 

11.1 

7.1 

10.5 

12.1 

11.2 

3.8 

65.2 

45.9 

21.3 

11.7 

12.1 

13.0 

13.0 

11.5 

14.0 

9.6 

13.5 

14.1 

14.1 

32.0 

84.5 

55.5 

30.1 

17.1 

17.8 

18.6 

19.4 

17.1 

19.7 

14.6 

20.2 

20.8 

21.9 

90.0 

106.6 

73.0 

42.2 

24.5 

25.9 

26.2 

28.8 

24.9 

29.5 

22.3 

29.5 

27.9 

31.9 

134.2 

137.8 

96.5 

59.3 

34.8 

37.6 

36.3 

43.1 

36.7 

48.7 

36.8 

43.1 

42.9 

50.1 

179.9 

164.3 

119.0 

76.8 

46.6 

52.3 

49.5 

66.7 

52.7 

82.6 

60.8 

64.9 

83.1 

76.6 

207.7* 

184.9* 

136.5 

92.3 

56.3 

62.8 

58.5 

89.4 

62.9 

108.4 

83.4 

84.1 

115.2 

99.0 

277.8* 

244.2* 

167.4* 

128.1* 

75.2 

82.1 

80.8 

148.0 

84.1 

163.5 

147.4 

141.9 

170.7* 

157.1* 

355.2* 

346.0* 

254.0* 

167.3* 

122.0* 

211.2* 

119.6* 

355.2* 

211.2* 

278.1* 

304.1* 

355.2* 

346.0* 

315.6* a Total food includes all foods, beverages, and water ingested. b SE = Standard error of the mean. c LCL = Lower confidence limit of the mean. d UCL = Upper confidence limit of the mean. e Min = Minimum value. f Max = Maximum value. 

* Estimates are less statistically reliable based on guidance published in

and CSFII Reports: NHIS/NCHS Analytical Working Group Recomm

Source: U.S. EPA analysis of NHANES 2003−2006 data. 

 the Joi

endatio

nt Policy

ns (NCH

 on Variance Est

S, 1993). 

imation and Statistical Reporting Standards on NHANES III 

Exposure Factors Handbook 

Chapter 14—Total Food Intake Exposure Factors Handbook 

Page 

September 2011 14-41 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

15. HUMAN MILK INTAKE 

15.1. INTRODUCTION 

Human lactation is known to impart a wide range 

of benefits to nursing infants, including protection 

against infection, increases in cognitive development, 

and avoidance of allergies due to intolerance to cow’s 

milk (Gartner et al., 2005). Ingestion of human milk 

also has been associated with a reduction in risk of 

post-neonatal death in the United States. (Chen and 

Rogan, 2004). The American Academy of Pediatrics 

(AAP) recommends exclusive breast-feeding for 

approximately the first 6 months and supports the 

continuation of breast-feeding for the first year and 

beyond if desired by the mother and child (Gartner et 

al., 2005). However, contaminants may find their way 

into human milk of lactating mothers because 

mothers are themselves exposed, thus making human 

milk a potential source of exposure to toxic 

substances for nursing infants. Lipid-soluble 

chemical compounds accumulate in body fat and may 

be transferred to breast-fed infants in the lipid portion 

of human milk. Water soluble chemicals also may 

partition into the aqueous phase and be excreted via 

human milk. Because nursing infants obtain most—if 

not all—of their dietary intake from human milk, 

they are especially vulnerable to exposures to these 

compounds. Estimating the magnitude of the 

potential dose to infants from human milk requires 

information on the milk intake rate (quantity of 

human milk consumed per day) and the duration 

(months) over which breast-feeding occurs. 

Information on the fat content of human milk also is 

needed for estimating dose from human milk residue 

concentrations that have been indexed to lipid 

content. 

Several studies have generated data on human 

milk intake. Typically, human milk intake has been 

measured over a 24-hour period by weighing the 

infant before and after each feeding without changing 

its clothing (test weighing). The sum of the difference 

between the measured weights over the 24-hour 

period is assumed to be equivalent to the amount of 

human milk consumed daily. Intakes measured using 

this procedure are often corrected for evaporative 

water losses (insensible water losses) between infant 

weighings (NAS, 1991). Neville et al. (1988) 

evaluated the validity of the test weight approach 

among bottle-fed infants by comparing the weights of 

milk taken from bottles with the differences between 

the infants' weights before and after feeding. When 

test weight data were corrected for insensible weight 

loss, they were not significantly different from bottle 

weights. Conversions between weight and volume of 

human milk consumed are made using the density of 

human milk (approximately 1.03 g/mL) (NAS, 1991). 

Techniques for measuring human milk intake using 

stable isotopes such as deuterium have been 

developed. The advantages of these techniques over 

test weighing procedures are that they are less 

burdensome for the mother and do not interfere with 

normal behavior (Albernaz et al., 2003). However, 

few data based on this technique were found in the 

literature. 

Among infants born in 2004, 73.8% were breastfed postpartum, 41.5% at 6 months, and 20.9% at 12 

months. Studies of nursing mothers in industrialized 

countries have shown that average intakes among 

infants ranged from approximately 500 to 800 

mL/day, with the highest intake reported for infants 3 

to <6 months old (see Table 15-1). 

The recommendations for human milk intake 

rates and lipid intake rates are provided in the next 

section along with a summary of the confidence 

ratings for these recommendations. The 

recommended values are based on key studies 

identified by U.S. Environmental Protection Agency 

(EPA) for this factor. Following the 

recommendations, key studies on human milk intake 

are summarized. Relevant data on lipid content and 

fat intake, breast-feeding duration, and the estimated 

percentage of the U.S. population that breast-feeds 

also are presented. 

A number of other studies exist in the literature, 

but they focus on other aspects of lactation such as 

growth patterns of nursing infants, supplementary 

food and energy intake, and nutrition of lactating 

mothers (González-Cossío et al., 1998; Drewett et al., 

1993; Dewey et al., 1992). These studies are not 

included in this chapter because they do not focus on 

the exposure factor of interest. Other studies in the 

literature focus on formula intake. Because some 

baby formula is prepared by adding water, these data 

are presented in Chapter 3-Ingestion of Water and 

Other Select Liquids. 

15.2. RECOMMENDATIONS 

The studies described in Section 15.3 were used 

in selecting recommended values for human milk 

intake and lipid intake. Although different survey 

designs, testing periods, and populations were used 

by the studies to estimate intake, the mean and 

standard deviation estimates reported in these studies 

are relatively consistent. There are, however, 

limitations with the data. With the exception of Butte 

et al. (1984) and Arcus-Arth et al. (2005), data were 

not presented on a body weight basis. This is 

particularly important because intake rates may be 

higher on a body weight basis for younger infants 

Exposure Factors Handbook Page
 

September 2011 15-1
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

than older infants. Also, the data used to derive the 

recommendations are more than 15 years old and the 

sample size of the studies was small. Other 

populations of concern—such as mothers highly 

committed to breast-feeding, sometimes for periods 

longer than 1 year—may not be captured by the 

studies presented in this chapter. Note that data for 

infants 12 months old are not included in the 

recommendation table because the U.S. EPA’s 

standard age group for children, as described in 

Chapter 1 of this handbook, is 6 to <12 months and it 

may not be appropriate to use this value to represent 

the next age group of 1 to <2 years old. 

15.2.1. Human Milk Intake 

Table 15-1 presents a summary of recommended 

values for human milk and lipid intake rates, and 

Table 15-2 presents the confidence ratings for these 

recommendations. The human milk intake rates for 

nursing infants that have been reported in the studies 

described in this section are summarized in 

Table 15-3 in units of mL/day and in Table 15-4 in 

units of mL/kg-day (i.e., indexed to body weight). It 

should be noted that the decrease in human milk with 

age is likely a result of complementary foods being 

introduced as the child grows and not necessarily a 

decrease in total energy intake. To conform to the 

new standardized age groupings used in this 

handbook (see Chapter 1), data from Pao et al. 

(1980), Dewey and Lönnerdal (1983), Butte et al. 

(1984), Neville et al. (1988), Dewey et al. (1991a), 

Dewey et al. (1991b), Butte et al. (2000), and 

Arcus-Arth et al. (2005) were compiled for each 

month of the first year of life. Recommendations 

were converted to mL/day by using a density of 

human milk of 1.03 g/mL, and rounded to two 

significant figures. Only two studies [i.e., Butte et al. 

(1984), and Arcus-Arth et al. (2005)] provided data 

on a body weight basis. For some months, multiple 

studies were available; for others only one study was 

available. Weighted means were calculated for each 

age in months. When upper percentiles were not 

available from a study, they were estimated by adding 

two standard deviations to the mean value. When 

multiple studies were available, recommendations for 

upper percentiles were calculated as the midpoint of 

the range of upper percentile values of the studies 

available for each age in months. These 

month-by-month intakes were composited to yield 

intake rates for the standardized age groups by 

calculating a weighted average. Recommendations 

are provided for the population of exclusively breastfed infants because this population may have higher 

exposures than partially breast-fed infants. 

Exclusively breast-fed in this chapter refers to infants 

whose sole source of milk comes from human milk, 

with no other milk substitutes. Partially breast-fed 

refers to infants whose source of milk comes from 

both human milk and other milk substitutes (i.e., 

formula). Note that some studies define partially 

breast-fed as infants whose dietary intake comes from 

not only human milk and formula, but also from 

other solid foods (e.g., strained fruits, vegetables, 

meats). 

15.2.2. Lipid Content and Lipid Intake 

Table 15-5 presents recommended lipid intake 

rates in units of mL/day. The table parallels the 

human milk intake tables (see Table 15-3). With the 

exception of the data from Butte et al. (1984), the 

rates were calculated assuming a lipid content of 4% 

(Kent et al., 2006; Arcus-Arth et al., 2005; Mitoulas 

et al., 2003; Mitoulas et al., 2002; NAS, 1991; Butte 

et al., 1984). In the case of the Butte et al. (1984) 

study, lipid intake rates were provided and were used 

in place of the estimated lipid intakes. Table 15-6 

presents lipid intake rates on a body weight basis 

(mL/kg-day). These were calculated from the values 

presented in Table 15-4 multiplied by 4% lipid 

content. 

Page Exposure Factors Handbook 

15-2 September 2011 
Exposure Factors Handbook Page
 

September 2011 15-3
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-1. Recommended Values for Human Milk and Lipid Intake Rates for Exclusively BreastFed Infants 

Age Group 

Mean a Upper Percentile

mL/day mL/kg-day mL/day mL/kg-day Source 

Human Milk Intake 

Birth to <1 month 510 150 950 220 b, c 

1 to <3 months 690 140 980 190 b, c, d, e, f 

3 to <6 months 770 110 1,000 150 b, c, d, e, f, g, h 

6 to <12 months 620 83 1,000 130 b, c, d, f, g, h 

i Lipid Intake

Birth to <1 month 20 6.0 38 8.7 b, c 

1 to <3 months 27 5.5 40 8.0 b, c, d, e, f 

3 to <6 months 30 4.2 42 6.1 b, c, d, e, f, g, h 

6 to <12 months 25 3.3 42 5.2 b, c, d, f, g, h 

a 

b 

c 

d 

e 

f 

g 

h 

i 

Upper percentile is reported as mean plus 2 standard deviations. 

Neville et al. (1988). 

Arcus-Arth et al. (2005). 

Pao et al. (1980). 

Butte et al. (1984). 

Dewey and Lönnerdal (1983). 

Butte et al. (2000). 

Dewey et al. (1991b). 

The recommended value for the lipid content of human milk is 4.0%. See Section 15.4 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-2. Confidence in Recommendations for Human Milk Intake 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

Methodology uses changes in body weight as a surrogate for total 

ingestion. More sophisticated techniques measuring stable isotopes 

have been developed, but data with this technique were not 

available. Sample sizes from individual studies were relatively 

small (7–108). Mothers selected for the studies were volunteers. 

The studies analyzed primary data. 

Mothers were instructed in the use of infant scales to minimize 

measurement errors. Three out of the eight studies indicated 

correcting data for insensible water loss. Some biases may be 

introduced by including partially breast-fed infants. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The studies focused on estimating human milk intake. 

Most studies focused on the U.S. population, but were not national 

samples. Populations studied were mainly from high socioeconomic 

status. One study included populations from Sweden and Finland. 

However, this may not affect the amount of intake, but, rather, the 

prevalence and initiation of lactation. 

Studies were conducted between 1980 and 2000. However, this may 

not affect the amount of intake but rather the prevalence and 

initiation of lactation. 

Infants were not studied long enough to fully characterize day-today variability. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

All key studies are available from the peer-reviewed literature. 

The methodology was clearly presented, but some studies did not 

discuss adjustments due to insensible weight loss. 

Some steps were taken to ensure data quality. For example, mothers 

were trained to use the scales. However, this element could not be 

fully evaluated from the information presented in the published 

studies. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Variability was not very well-characterized. Mothers committed to 

breast-feeding more than 1 year were not captured. 

Not correcting for insensible water loss may underestimate intake. 

Low 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The studies appeared in peer-reviewed journals. 

There are eight key studies. The results of studies from different 

researchers are in agreement. 

High 

Overall Rating Medium 

Page Exposure Factors Handbook 

15-4 September 2011 
 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-3. Human Milk Intake Rates Derived From Key Studies for Exclusively Breast-Fed Infants 

(mL/day) 

Age 

(months) 

Number of 

Children 

Mean 

Intake 

(mL/day) 

Upper 

Percentile 

Consumption 

(mL/day)a 

Source 

Weighted Mean Intake and Upper Percentile 

Consumption (across all key studies) 

(mL/day) 

Individual Age Composite Age Groups 

Meanb Upperc Meanb Upperc 

0 <1 6 to 13 511 951 Neville et al. (1988) 511 951 511 951 

1 

11 

37 

10 to 12 

16 

600 

729 

679d 

673 

918 

981 

889 

1,057 

Pao et al. (1980) 

Butte et al. (1984) 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

670 973 

692 983 

2 

10 to 12 

19 

40 

679d 

756 

704 

889 

1,096 

958 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Butte et al. (1984) 

713 992 

3 

2 

37 

10 

16 

73 

40 

833 

702 

713 

782 

788 

728 

–e 

924 

935 

1,126 

1,047 

988 

Pao et al. (1980) 

Butte et al. (1984) 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Dewey et al. (1991b) 

Butte et al. (2000) 

758 1,025 

769 1,024 

4 

12 

13 

41 

690 

810 

718 

888 

1,094 

996 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Butte et al. (1984) 

739 991 

5 12 

11 

814 

805 

1,074 

1,039 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 810 1,057 

6 

1 

13 

11 

60 

30 

682 

744 

896 

747 

637 

– e 

978 

1,140 

1,079 

1,050 

Pao et al. (1980) 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Dewey et al. (1991b) 

Butte et al. (2000) 

741 1,059 

622 1,024 

7 12 700 1,000 Neville et al. (1988) 700 1,000 

8 9 604 1,012 Neville et al. (1988) 604 1,012 

9 12 

50 

600 

627 

1,028 

1,049 

Neville et al. (1988) 

Dewey et al. (1991b) 614 1,039 

10 11 535 989 Neville et al. (1988) 535 989 

11 8 538 1,004 Neville et al. (1988) 538 1,004 

12 

8 

42 

13 

391 

435 

403 

877 

922 

931 

Neville et al. (1988) 

Dewey et al. (1991b; 1991a) 

Butte et al. (2000) 

410 904 410 904 

a 

b 

c 

d 

e 

Upper percentile is reported as mean plus 2 standard deviations. 

Calculated as the mean of the means. 

Middle of the range of upper percentiles. 

Calculated for infants 1 to <2 months old. 

Standard deviations and upper percentiles not calculated for small sample sizes. 

Exposure Factors Handbook Page
 

September 2011 15-5
 
 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-4. Human Milk Intake Rates Derived From Key Studies for Exclusively Breast-Fed Infants 

(mL/kg-day) 

Age 

(months) 

Number 

of 

Children 

Mean 

Intake 

(mL/kg 

-day) 

Upper 

Percentile 

Consumption 

(mL/kg-day)a 

Source 

Weighted Mean Intake and Upper Percentile 

Consumption (cross all key studies) 

(mL/kg-day) 

Individual Age Composite Age 

Groups 

Meanb Upperc Mean Upperc 

0 <1 9 to 25 150 217 Arcus-Arth et al. (2005) 150 217 150 217 

1 37 

25 

154 

150 

200 

198 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 

152 199 

144 187 2 40 

25 

125 

144 

161 

188 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 

135 175 

3 37 

108 

114 

127 

152 

163 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 

121 158 

4 41 110 149

57 

108 

112 

142 

148 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 

110 145 

5 26 100 140 Arcus-Arth et al. (2005) 100 140 

6 39 101 141 Arcus-Arth et al. (2005) 101 141 

7 8 75 125 Arcus-Arth et al. (2005) 75 125 83 130

9 57 72 118 Arcus-Arth et al. (2005) 72 118 

12 42 47 101 Arcus-Arth et al. (2005) 47 101 47 101 a Upper percentile is reported as mean plus two standard deviations. b Calculated as the mean of the means. c Middle of the range of upper percentiles. 

Page Exposure Factors Handbook 

15-6 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-5. Lipid Intake Rates Derived From Key Studies for Exclusively Breast-Fed Infants (mL/day)a 

Age 

(months) 

Number of 

Children 

Mean 

Intake 

(mL/day) 

Upper Percentile 

Consumption 

(mL/day)b 

Source 

Weighted Mean Intake and Upper Percentile 

Consumption (across all key studies) 

(mL/day) 

Individual Age Composite Age Groups 

Meanc Upperd Meanc Upperd 

0 <1 6 to 13 20 38 Neville et al. (1988) 20 38 20 38 

1 

11 

37 

10 to 12 

16 

24 

27 

27 

27 

37 

43 

36 

42 

Pao et al. (1980) 

Butte et al. (1984) 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

26 39 

27 40 

2 

10 to 12 

19 

40 

27 

30 

24 

36 

44 

38 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Butte et al. (1984) 

27 40 

3 

2 

37 

10 

16 

73 

40 

33 

23 

29 

31 

32 

29 

–e 

37 

37 

45 

42 

40 

Pao et al. (1980) 

Butte et al. (1984) 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Dewey et al. (1991b) 

Butte et al. (2000) 

30 41 

30 42 

4 

12 

13 

41 

28 

32 

25 

36 

44 

41 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Butte et al. (1984) 

28 40 

5 12 

11 

33 

32 

43 

42 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 33 43 

6 

1 

13 

11 

60 

30 

27 

30 

36 

30 

25 

–e 

39 

46 

43 

42 

Pao et al. (1980) 

Neville et al. (1988) 

Dewey and Lönnerdal (1983) 

Dewey et al. (1991b) 

Butte et al. (2000) 

30 40 

25 42 

7 12 28 40 Neville et al. (1988) 28 40 

8 9 24 40 Neville et al. (1988) 24 40 

9 12 

50 

24 

25 

41 

42 

Neville et al. (1988) 

Dewey et al. (1991b) 24 41 

10 11 21 40 Neville et al. (1988) 21 40 

11 9 22 40 Neville et al. (1988) 22 40 

12 

9 

42 

13 

16 

17 

16 

35 

37 

37 

Neville et al. (1988) 

Dewey et al. (1991b; 1991a) 

Butte et al. (2000) 

16 36 16 36 

a 

b 

c 

d 

e 

Except for Butte et al. (1984), values were calculated from Table 15-3 using 4% lipid content. 

Upper percentile is reported as mean plus 2 standard deviations. 

Calculated as the mean of the means. 

Middle of the range of upper percentiles. 

Standard deviations and upper percentiles not calculated for small sample sizes. 

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Chapter 15—Human Milk Intake 

Table 15-6. Lipid Intake Rates Derived From Key Studies for Exclusively Breast-Fed Infants (mL/kg-day)a 

Age 

(months) 

Number 

of 

Children 

Mean 

Intake 

(mL/kgday) 

Upper 

Percentile 

Consumption 

(mL/kg-day)b 

Source 

Weighted Mean Intake and Upper 

Percentile Consumptionb (across all 

key studies) 

(mL/kg-day) 

Individual Age Composite Age 

Groups 

Meanc Upperd Meane Upperd 

0 <1 9 to 25 6.0 8.7 Arcus-Arth et al. (2005) 6.0 8.7 6.0 8.7 

1 37 

25 

5.7 

6.0 

9.1 

8.7 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 5.9 8.9 

5.5 8.0 

2 40 

25 

4.3 

5.8 

6.7 

7.5 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 5.1 7.1 

3 37 

108 

3.7 

5.1 

6.1 

6.5 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 4.4 6.3 

4.2 6.1 4 41 

57 

3.7 

4.5 

6.3 

5.9 

Butte et al. (1984) 

Arcus-Arth et al. (2005) 4.1 6.1 

5 26 4.0 5.6 Arcus-Arth et al. (2005) 4.0 5.8 

6 39 4.0 5.6 Arcus-Arth et al. (2005) 4.0 5.6 

7 8 3.0 5.0 Arcus-Arth et al. (2005) 3.0 5.0 3.3 5.2 

9 57 2.9 4.7 Arcus-Arth et al. (2005) 2.9 4.7 

12 42 1.9 4.0 Arcus-Arth et al. (2005) 1.9 4.0 1.9 4.0 

a Except for Butte et al. (1984), values were calculated from Table 15-4 using 4% lipid content. b Upper percentile is reported as mean plus two standard deviations. c Calculated as the mean of the means. d Middle of the range of upper percentiles. 

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Chapter 15—Human Milk Intake 

15.3.	 KEY STUDIES ON HUMAN MILK 

INTAKE 

15.3.1.	 Pao et al. (1980)—Milk Intakes and 

Feeding Patterns of Breast-Fed Infants 

Pao et al. (1980) conducted a study of 22 healthy 

nursing infants to estimate human milk intake rates. 

Infants were categorized as completely breast-fed or 

partially breast-fed. Breast-feeding mothers were 

recruited through La Leche League groups. Except 

for one Black infant, all other infants were from 

White middle-class families in southwestern Ohio. 

The goal of the study was to enroll infants as close to 

1 month of age as possible and to obtain records near 

1, 3, 6, and 9 months of age (Pao et al., 1980). 

However, not all mother-infant pairs participated at 

each time interval. Data were collected for these 22 

infants using the test weighing method. Records were 

collected for three consecutive 24-hour periods at 

each test interval. The weight of human milk was 

converted to volume by assuming a density of 

1.03 g/mL. Daily intake rates were calculated for 

each infant based on the mean of the three 24-hour 

periods. Table 15-7 presents mean daily human milk 

intake rates for the infants surveyed at each time 

interval. These data are presented as they are reported 

in Pao et al. (1980). For completely breast-fed 

infants, the mean intake rates were 600 mL/day at 1 

month of age, 833 mL/day at 3 months of age, and 

682 mL/day at 6 months of age. Partially breast-fed 

infants had mean intake rates of 485 mL/day, 467 

mL/day, 395 mL/day, and <554 mL/day at 1, 3, 6, 

and 9 months of age, respectively. Pao et al. (1980) 

also noted that intake rates for boys in both groups 

were slightly higher than for girls. 

The advantage of this study is that data for both 

exclusively and partially breast-fed infants were 

collected for multiple time periods. Also, data for 

individual infants were collected over 3 consecutive 

days, which would account for some individual 

variability. However, the number of infants in the 

study was relatively small. In addition, this study did 

not account for insensible weight loss, which may 

underestimate the amount of human milk ingested. 

15.3.2.	 Dewey and Lönnerdal (1983)—Milk and 

Nutrient Intake of Breast-Fed Infants 

From 1 to 6 Months: Relation to Growth 

and Fatness 

Dewey and Lönnerdal (1983) monitored the 

dietary intake of 20 nursing infants between age 

1 and 6 months. The number of study participants 

dropped to 13 by the end of the 6th month. Most of 

the infants in the study were exclusively breast-fed. 

One infant’s intake was supplemented by formula 

during the first and second month of life. During the 

3rd, 4th, and 5th months, three, four, and five infants, 

respectively, were given some formula to supplement 

their intake. Two infants were given only formula (no 

human milk) during the 6th month. According to 

Dewey and Lönnerdal (1983), the mothers were all 

well-educated and recruited through Lamaze 

childbirth classes in the Davis area of California. 

Human milk intake volume was estimated based on 

two 24-hour test weighings per month. Table 15-8 

presents human milk intake rates for the various age 

groups. Human milk intake averaged 673, 782, and 

896 mL/day at 1, 3, and 6 months of age, 

respectively. 

The advantage of this study is that it evaluated 

nursing infants for a period of 6 months based on two 

24-hour observations per infant per month. However, 

corrections for insensible weight loss apparently were 

not made. Also, the number of infants in the study 

was relatively small, and the study participants were 

not representative of the general population. During 

the study period, some infants were given some 

formula (i.e., up to five infants during the 5th month). 

Without the raw data, these subjects could not be 

excluded from the study results. Thus, these subjects 

may affect the results when deriving 

recommendations for exclusively breast-fed infants. 

15.3.3.	 Butte et al. (1984)—Human Milk Intake 

and Growth in Exclusively Breast-Fed 

Infants 

Human milk intake was studied in exclusively 

breast-fed infants during the first 4 months of life 

(Butte et al., 1984). Nursing mothers were recruited 

through the Baylor Milk Bank Program in Texas. 

Forty-five mother-infant pairs participated in the 

study. However, data for some time periods (i.e., 1, 2, 

3, or 4 months) were missing for some mothers as a 

result of illness or other factors. The mothers were 

from the middle-to-upper socioeconomic stratum and 

had a mean age of 28.0 ± 3.1 years. A total of 41 

mothers were White, 2 were Hispanic, 1 was Asian, 

and 1 was West Indian. Infant growth progressed 

satisfactorily during the course of the study. 

The amount of milk ingested over a 24-hour 

period was determined by weighing the infant before 

and after feeding. The study did not indicate whether 

the data were corrected for insensible water or weight 

loss. The study evaluated the accuracy of the test 

weighing procedure using a bottle-fed infant. Test 

weighing occurred over a 24-hour period for most 

study participants, but intake among several infants 

was studied over longer periods (48 to 96 hours) to 

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Chapter 15—Human Milk Intake 

assess individual variation in intake. Eight of the 

infants received some food supplementation during 

the study period. Six of them received less than 60 

kcal/day of formula, oatmeal, glucose water, or rice 

water for 1 or 2 days. One infant received an 

additional 90 kcal/day of infant formula and rice 

water for 6 days during the 4th month because of 

inadequate milk production. When converting values 

reported as g/day to mL/day, using a conversion 

factor of 1.03 g/mL, mean human milk intake ranged 

from 702 mL/day at 3 months to 729 mL/day at 1 

month, with an overall mean of 712 mL/day for the 

entire study period (see Table 15-9). Intakes also 

were calculated on the basis of body weight (see 

Table 15-9). 

The advantage of this study is that data for a 

larger number of exclusively breast-fed infants were 

collected than in previous studies. However, data 

were collected for infants up to 4 months and 

day-to-day variability was not characterized for all 

infants. Eighteen percent (i.e., 8 out of 45) of the 

infants received some formula supplementation 

during the study period. Without the raw data, these 

subjects could not be excluded from the study results. 

Therefore, values derived from this study for 

exclusively breast-fed infants may be somewhat 

underestimated. 

15.3.4.	 Neville et al. (1988)—Studies in Human 

Lactation: Milk Volumes in Lactating 

Women During the Onset of Lactation 

and Full Lactation 

Neville et al. (1988) studied human milk intake 

among 13 infants during the 1st year of life. The 

mothers were all multiparous, non-smoking, White 

women of middle- to upper-socioeconomic status 

living in Denver, CO. All women in the study 

practiced exclusive breast-feeding for at least 

5 months. Solid foods were introduced at mean age 

of 7 months. Daily milk intake was estimated by the 

test weighing method with corrections for insensible 

weight loss. Data were collected daily from birth to 

14 days, weekly from weeks 3 through 8, and 

monthly until the study period ended at 1 year after 

inception. One infant was weaned at 8 months, while 

all others were weaned on or after the 12 months. 

Formula was used occasionally (≤ 240 mL/week) 

after 4 months in three infants. Table 15-10 lists the 

estimated human milk intakes for this study. 

Converting values reported as g/day to mL/day, using 

a conversion factor of 1.03 g/mL, mean human milk 

intakes were 748 mL/day, 713 mL/day, 744 mL/day, 

and 391 mL/day at 1, 3, 6, and 12 months of age, 

respectively. 

In comparison to the previously described studies, 

Neville et al. (1988) collected data on numerous days 

over a relatively long time period (12 months) and 

they were corrected for insensible weight loss. 

However, the intake rates presented in Table 15-10 

are estimated based on intake only during a 24-hour 

period. Consequently, these intake rates are based on 

short-term data that do not account for day-to-day 

variability among individual infants. Also, a smaller 

number of subjects was included than in the previous 

studies. Three infants were given some formula after 

4 months. Without the raw data, these subjects could 

not be excluded from the study results. Thus, data 

presented for infants between 5 and 12 months may 

underestimate the intake of exclusively breast-fed 

infants. 

15.3.5. Dewey et al. (1991b; 1991a)—(a) 

Maternal Versus Infant Factors Related 

to Human Milk Intake and Residual 

Volume: The DARLING Study; (b) 

Adequacy of Energy Intake Among 

Breast-Fed Infants in the DARLING 

Study: Relationships to Growth, Velocity, 

Morbidity, and Activity Levels 

The Davis Area Research on Lactation, Infant 

Nutrition and Growth (DARLING) study was 

conducted in 1986 to evaluate growth patterns, 

nutrient intake, morbidity, and activity levels in 

infants who were breast-fed for at least their first 

12 months of life (Dewey et al., 1991b; Dewey et al., 

1991a). Subjects were non-randomly selected 

through letters to new parents using birth listings. 

One of the criteria used for selection was that 

mothers did not plan to feed their infants more than 

120 mL/day of other milk or formula for the first 12 

months of life. Seventy-three infants aged 3 months 

were included in the study. At subsequent time 

intervals, the number of infants included in the study 

was somewhat lower as a result of attrition. All 

infants in the study were healthy and of normal 

gestational age and weight at birth, and they did not 

consume solid foods until after they were 4 months 

old. The mothers were highly educated and of 

“relatively high socioeconomic status.” 

Human milk intake was estimated by weighing 

the infants before and after each feeding and 

correcting for insensible water loss. Test weighings 

were conducted over a 4-day period every 3 months. 

The results of the study indicate that human milk 

intake declines over the first 12 months of life. This 

decline is associated with the intake of solid food. 

When converting values reported as g/day to mL/day, 

using a conversion factor of 1.03 g/mL, mean human 

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Chapter 15—Human Milk Intake 

milk intake was estimated to be 788 mL/day, 747 

mL/day, 627 mL/day, and 435 mL/day at 3, 6, 9, and 

12 months, respectively (see Table 15-11). Based on 

the estimated intakes at 3 months of age, variability 

between individuals (coefficient of variation [CV] = 

16.3%) was higher than the average day-to-day 

variability (CV = 8.9 ± 5.4%) for the infants in the 

study (Dewey et al., 1991a). 

The advantages of this study are that data were 

collected over a relatively long-time (4 days) period 

at each test interval, which would account for some 

day-to-day infant variability, and corrections for 

insensible water loss were made. Data from this study 

are assumed to represent exclusively breast-fed 

infants because mothers were specifically recruited 

for that purpose. It is, however, unclear from the 

Dewey et al. (1991a) study if this criterion was met 

throughout the length of the study period. 

15.3.6.	 Butte et al. (2000)—Infant Feeding Mode 

Affects Early Growth and Body 

Composition 

Butte et al. (2000) conducted a study to assess the 

effect of infant feeding mode on growth and body 

composition during the first 2 years of life. The study 

was conducted in the Houston, TX, area, recruited 

through the Children’s Nutrition Research Center 

(CNRC) referral system. The study was approved by 

the Baylor Affiliates Review Boards for Human 

Subject Research. The overall sample was 76 healthy 

term infants at 0.5, 3, 6, 9, 12, 18, and 24 months of 

age. The sample size varied between 71 to 76 infants 

for each age group. Repeated measurements for body 

composition and anthropometric were performed. 

The mothers agreed to either exclusively breast-feed 

or formula feed the infants for the first 4 months of 

life. 

At 3-month or 6-month study intervals, the 

feeding history was taken. The mothers or caretakers 

were questioned about breast-feeding frequency, and 

the use of formula, milk, juice, solids, water, and 

vitamin or mineral supplements. Also, infant food 

intake was quantified at 3, 6, 12, and 24 months with 

a 3-day weighted intake record completed by the 

mother or caretaker (Butte et al., 2000). The intake of 

human milk was assessed by test weighing; the infant 

weights were calculated before and after each 

feeding. Using a pre-weighing and post-weighing 

method, the intake of formula and other foods and 

beverages was measured for 3 days by the mothers 

using a digital scale and recorded on predetermined 

forms. 

The average duration of breast-feeding was 

11.4 months (standard deviation [SD] = 5.8). Butte et 

al. (2000) reported that infants were exclusively 

breast-fed for at least the first 4 months—except for 

one who was weaned at 109 days, another who 

received formula at 102 days, and another who was 

given cereal at 106 days. Table 15-12 shows the 

infant feeding characteristics. Table 15-13 shows the 

intakes of human milk for the infants. When 

converting values reported as g/day to mL/day, using 

a conversion factor of 1.03 g/mL, mean human milk 

intake was estimated to be 728 mL/day at 3 months 

(weighted average of boys and girls), 637 mL/day at 

6 months (weighted average of boys and girls), and 

403 mL/day at 12 months (weighted average of boys 

and girls) (see Table 15-13). Table 15-14 shows 

feeding practices by percentage for infants. Table 

15-15 provides the mean body weights of breast-fed 

infants. 

Advantages of this study are that it provides 

intake data for breast-fed infants for their first 

4 months. The study also provides the mean weights 

for the infants by feeding type and by sex. The 

limitations of the study are that the sample size is 

small and limited to one geographical location. The 

authors did not indicate if results were corrected for 

insensible weight loss. Because mothers could 

introduce formula after 4 months, only the data for 

the 3-month old infants can be considered exclusively 

breast-fed. 

15.3.7.	 Arcus-Arth et al. (2005)—Breast Milk 

and Lipid Intake Distributions for 

Assessing Cumulative Exposure and Risk 

Arcus-Arth et al. (2005) derived population 

distributions for average daily milk and lipid intakes 

in g/kg-day for infants age 0–6 months and 0– 

12 months for infants fed according to the AAP 

recommendations. The AAP recommends exclusively 

breast-feeding for the first 6 months of life, with 

human milk as the only source of milk until age 

1 year and the introduction of solid foods after 

6 months. The distributions were derived based on 

data in the peer-reviewed literature and data sets 

supplied by the publication authors for infants 7 days 

and older (Arcus-Arth et al., 2005). As cited in 

Arcus-Arth et al. (2005), data sources included 

Dewey et al. (1991b; 1991a), Hofvander et al. (1982), 

Neubauer et al. (1993), Ferris et al. (1993), 

Salmenpera et al. (1985), and Stuff and Nichols 

(1989). The authors also evaluated intake rates for 

infants breast-fed exclusively over the 1st year and 

provided a regression line of intake versus age for 

estimating short-term exposures. Arcus-Arth et al. 

(2005) derived human milk intake rates for the entire 

infant population (nursing and non-nursing) from 

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Chapter 15—Human Milk Intake 

U.S. data on consumption, prevalence and duration. 

Arcus-Arth et al. (2005) defined exclusive breastfeeding (EBF) as “breast milk is the sole source of 

calories, with no or insignificant calories from other 

liquid or solid food sources,” and predominant 

breast-feeding as “breast milk is the sole milk source 

with significant calories from other foods.” The data 

that were consistent with AAP advice were used to 

construct the AAP data set (Arcus-Arth et al., 2005). 

The 0–12 months EBF data set was created using 0– 

6 month AAP data and data from the EBF infants 

older than 6 months of age. Because there are no data 

in the AAP data set for any individual infant followed 

at regular, frequent intervals during the 12-month 

period, population distributions were derived with 

assumptions regarding individual intake variability 

over time (Arcus-Arth et al., 2005). Two methods 

were used. In Method 1, the average population daily 

intake at each age was described by a regression line, 

assuming normality. Arcus-Arth et al. (2005) noted 

that age specific intake data were consistent with the 

assumption of normality. In Method 2, intake over 

time was simulated for 2,500 hypothetical infants and 

the distribution intakes derived from 2,500 individual 

intakes (Arcus-Arth et al., 2005). The population 

intake distribution was derived following Method 1. 

Table 15-16 presents the means and standard 

deviations for intake data at different ages; the 

variability was greatest for the two youngest and 

three oldest age groups. The values in Table 15-16 

using Method 1 were used to derive the 

recommendations presented in Table 15-1 because it 

provides data for the fine age categories. When 

converting values reported as g/day to mL/day, using 

a conversion factor of 1.03 g/mL, mean human milk 

intake was estimated to be 150 mL/kg-day at 

1 month, 127 mL/kg-day at 3 months, 

101 mL/kg-day at 6 months, and 47 mL/kg-day at 

12 months (see Table 15-16). Time weighted average 

intakes for larger age groups (i.e., 0–6 months, 0– 

12 months) are presented in Table 15-17. 

An advantage of this study is that it was designed 

to represent the infant population whose mothers 

follow the AAP recommendations. Intake was 

calculated on a body weight basis. In addition, the 

data used to derive the distributions were from peerreviewed literature and data sets supplied by the 

publication authors. The distributions were derived 

from data for infants fed in accordance to AAP 

recommendations, and they most likely represent 

daily average milk intake for a significant portion of 

breast-fed infants today (Arcus-Arth et al., 2005). 

The limitations of the study are that the data used 

were from mothers who were predominantly White, 

well-nourished, and from middle or high 

socioeconomic status. Arcus-Arth et al. (2005) also 

included data from Sweden and Finland. However, 

human milk volume in mL/day is similar among all 

women except for severely malnourished women 

(Arcus-Arth et al., 2005). According to Arcus-Arth et 

al. (2005): “Although few infants are exclusively 

breast-fed for 12 months, the EBF distributions may 

represent a more highly exposed subpopulation of 

infants exclusively breast-fed in excess of 6 months.” 

15.4.	 KEY STUDIES ON LIPID CONTENT 

AND LIPID INTAKE FROM HUMAN 

MILK 

Human milk contains more than 200 constituents, 

including lipids, various proteins, carbohydrates, 

vitamins, minerals, and trace elements as well as 

enzymes and hormones. The lipid content of human 

milk varies according to the length of time that an 

infant nurses, and it increases from the beginning to 

the end of a single nursing session (NAS, 1991). The 

lipid portion accounts for approximately 4% of 

human milk (3.9% ± 0.4%) (NAS, 1991). This value 

is supported by various studies that evaluated lipid 

content from human milk (Kent et al., 2006; ArcusArth et al., 2005; Mitoulas et al., 2003; Mitoulas et 

al., 2002; Butte et al., 1984). Several studies also 

estimated the quantity of lipid consumed by breastfeeding infants. These values are appropriate for 

performing exposure assessments for nursing infants 

when the contaminant(s) have residue concentrations 

that are indexed to the fat portion of human milk. 

15.4.1.	 Butte et al. (1984)—Human Milk Intake 

and Growth in Exclusively Breast-Fed 

Infants 

Butte et al. (1984) analyzed the lipid content of 

human milk samples taken from women who 

participated in a study of human milk intake among 

exclusively breast-fed infants. The study was 

conducted with more than 40 women during a 

4-month period. Table 15-18 presents the mean lipid 

content of human milk at various infants’ ages. The 

overall lipid content for the 4-month study period 

was 3.43 ± 0.69% (3.4%). Butte et al. (1984) also 

calculated lipid intakes from 24-hour human milk 

intakes and the lipid content of the human milk 

samples. Lipid intake was estimated to range from 

22.9 mL/day (3.7 mL/kg-day) to 27.2 mL/day 

(5.7 mL/kg-day). 

The number of women included in this study was 

small, and these women were selected primarily from 

middle to high socioeconomic classes. Thus, data on 

human milk lipid content from this study may not be 

entirely representative of human milk lipid content 

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Chapter 15—Human Milk Intake 

among the U.S. population. Also, these estimates are 

based on short-term data, and day-to-day variability 

was not characterized. 

15.4.2.	 Mitoulas et al. (2002)—Variation in Fat, 

Lactose, and Protein in Human Milk 

Over 24 h and Throughout the First Year 

of Lactation 

Mitoulas et al. (2002) conducted a study of 

healthy nursing women to determine the volume and 

composition of human milk during the 1st year of 

lactation. Nursing mothers were recruited through the 

Nursing Mothers’ Association of Australia. All 

infants were completely breast-fed on demand for at 

least 4 months. Complementary solid food was 

introduced between 4 and 6 months of age. Mothers 

consumed their own ad libitum diets throughout the 

study. Seventeen mothers initially provided data for 

milk production and fat content, whereas lactose, 

protein, and energy were initially obtained from nine 

mothers. The number of mothers participating in the 

study decreased at 6 months because of the cessation 

of sample collection from 11 mothers, the maximum 

period of exclusive breast-feeding. 

Milk samples were collected before and after each 

feed from each breast over a 24–28 hour period. Milk 

yield was determined by weighing the mother before 

and after each feed from each breast. Insensible water 

loss was accounted for by weighing the mother 

20 minutes after the end of each feeding. The rate of 

water loss during this 20-minute period was used to 

calculate insensible water loss during the feeding. 

Samples of milk produced at the beginning of the 

feeding (foremilk) and at the end of the feeding 

(hindmilk) were averaged to provide the fat, protein, 

lactose, and energy content for each feed. In all cases 

the left and right breasts were treated separately; 

therefore, N represents the number of individual 

breasts sampled. 

Table 15-19 presents mean human milk 

production and composition at each age interval. The 

mean fat, lactose, and protein contents (g/L) were 

37.4 (standard error [SE] = 0.6), 61.4 (SE = 0.6), and 

9.2 (SE = 0.2), respectively. Composition did not 

vary between left and right breasts or preferred and 

non-preferred breasts. Milk production was constant 

for the first 6 months and thereafter steadily declined. 

Mitoulas et al. (2002) reported a mean 24-hour milk 

production from both breasts was 798 (SD = 232) 

mL. The fat content of milk decreased between 1 and 

4 months before increasing to 12 months of lactation. 

The concentration of protein decreased to 6 months 

and then remained steady. Lactose remained constant 

throughout the 12 months of lactation. The decrease 

of energy at 2 months and subsequent increase by 

9 months can be attributed to changes in fat content. 

Assuming a density of human milk of 1.03 g/mL, the 

overall fat content in human milk was 3.6%. Milk 

production, as well as concentrations of fat, lactose, 

protein, and energy, differed significantly between 

women. 

The focus of this study was on human milk 

composition and production, not on infant’s human 

milk intake. The advantage of this study is that it 

evaluated nursing mothers for a period of 12 months. 

However, the number of mother-infant pairs in the 

study was small (17 mothers with infants) and may 

not be entirely representative of the U.S. population. 

This study accounted for insensible water loss, which 

increases the accuracy of the amount of human milk 

produced. 

15.4.3.	 Mitoulas et al. (2003)—Infant Intake of 

Fatty Acids From Human Milk Over the 

First Year of Lactation 

Mitoulas et al. (2003) conducted a study of five 

healthy nursing women to determine the content of 

fat in human milk and fat intake by infants during the 

1st year of lactation. Thirty nursing mothers were 

recruited through the Australian Breast-feeding 

Association or from private healthcare facilities. All 

infants were completely breast-fed on demand for at 

least 4 months. Complementary solid food was 

introduced between 4 and 6 months of age. Mothers 

consumed their own ad libitum diets throughout the 

study. 

Milk samples were collected before and after each 

feed from each breast over a 24–28 hour period. 

Fore- and hind-milk samples were averaged to 

provide the fat content for each feed. Milk yield was 

determined by weighing the mother before and after 

each feed from each breast. Insensible water loss was 

accounted for by weighing the mother 20 minutes 

after the end of each feeding. The rate of water loss 

during those 20 minutes was used to calculate 

insensible water loss during the feeding. 

Table 15-20 presents changes in volume of human 

milk produced and milk fat content over the 1st year 

of lactation. The mean volumes of milk produced for 

both breasts combined were 813, 791, 912, 810, 677, 

and 505 mL/day at 1, 2, 4, 6, 9, and 12 months, 

respectively. The average daily production over the 

12 months was 751 mL/day with a mean fat content 

of 35.5 g/L. Assuming a density of human milk of 

1.03 g/mL, the fat content in human milk was 3.4% 

over the 12 month period. There was a significant 

difference in the proportional composition of fatty 

acids during the course of lactation. Table 15-21 

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Chapter 15—Human Milk Intake 

provides average fatty acid composition during the 

first 12 months of lactation. Additionally, fatty acid 

composition varied during the course of the day. 

The focus of this study was on human milk 

composition and production—not on infant’s human 

milk intake. The advantage of this study is that it 

evaluated the human milk composition for a period of 

12 months. However, the number of mother-infant 

pairs in the study was small (five mothers with 

infants) and may not be entirely representative of the 

entire U.S. population. This study accounted for 

insensible water loss, which increases the accuracy of 

the amount of human milk produced. 

15.4.4.	 Arcus-Arth et al. (2005)—Breast Milk 

and Lipid Intake Distributions for 

Assessing Cumulative Exposure and Risk 

Arcus-Arth et al. (2005) derived population 

distributions for average daily milk and lipid intakes 

in g/kg a day for infants 0–6 months and 0– 

12 months of age for infants fed according to the 

AAP recommendations. Lipid intakes were calculated 

from lipid content and milk intakes measured on the 

same infant (Arcus-Arth et al., 2005). Table 15-22 

provides lipid intakes based on data from Dewey et 

al. (1991a) and Table 15-23 provides lipid intakes 

calculated assuming 4% lipid content and milk intake 

in the AAP data set. The mean measured lipid content 

ranged from 3.67%–4.16%, with a mean of 3.9% 

over the 12 month period. Arcus-Arth et al. (2005) 

noted that the distributions presented are intended to 

represent the U.S. infant population. 

An advantage of this study is that it was designed 

to represent the population of infants who are breastfed according to the AAP recommendations. In 

addition, the data used to derive the distributions 

were from peer-review literature and data sets 

supplied by the publication authors. The limitation of 

the study are that the data used were from mothers 

that were predominantly white, well-nourished, and 

from mid- or upper-socioeconomic status; however, 

human milk volume in mL/day is similar among all 

women except for severely malnourished women 

(Arcus-Arth et al., 2005). The authors noted that 

“although few infants are exclusively breast-fed for 

12 months, the exclusively breast-fed distributions 

may represent a more highly exposed subpopulation 

of infants exclusively breast-fed in excess of 

6 months.” The distributions were derived from data 

for infants fed in accordance to AAP 

recommendations, and they most likely represent 

daily average milk intake for a significant portion of 

breast-fed infants today (Arcus-Arth et al., 2005). 

15.4.5.	 Kent et al. (2006)—Volume and 

Frequency of Breast-Feeding and Fat 

Content of Breast Milk Throughout the 

Day 

Kent et al. (2006) collected data from 

71 Australian mothers who were exclusively nursing 

their 1–6 month-old infants. The study focused on 

examining the variation of milk consumed from each 

breast, the degree of fullness of each breast before 

and after feeding, and the fat content of milk 

consumed from each breast during daytime and 

nighttime feedings. The volume of milk was 

measured using test-weighing procedures with no 

correction for infant insensible water loss. On 

average, infants had 11 ± 3 breast-feedings per day 

(range = 6–18). The interval between feedings was 

2 hours and 18 minutes ± 43 minutes (range = 

4 minutes to 10 hours, 58 minutes). The 24-hour 

average human milk intake was 765 ± 164 mL/day 

(range = 464–1,317 mL/day). The fat content of milk 

ranged from 22.3 g/L to 61.6 g/L (2.2%–6.0%) with 

an average of 41.1 g/L (4.0%). 

This study examined breast-feeding practices of 

volunteer mothers in Australia. Although amounts of 

milk consumed by Australian infants may be similar 

to infants in the U.S. population, results could not be 

broken out by smaller age groups to examine 

variability with age. The study provides estimates of 

fat content from a large number of samples. 

15.5.	 RELEVANT STUDY ON LIPID INTAKE 

FROM HUMAN MILK 

15.5.1.	 Maxwell and Burmaster (1993)—A 

Simulation Model to Estimate a 

Distribution of Lipid Intake From 

Human Milk During the First Year of 

Life 

Maxwell and Burmaster (1993) used a 

hypothetical population of 5,000 infants between 

birth and 1 year of age to simulate a distribution of 

daily lipid intake from human milk. The hypothetical 

population represented both bottle-fed and breast-fed 

infants aged 1–365 days. A distribution of daily lipid 

intake was developed based on data in Dewey et al. 

(1991b) on human milk intake for infants at 3, 6, 9, 

and 12 months and human milk lipid content, and 

survey data in Ryan et al. (1991) on the percentage of 

breast-fed infants under 12 months (i.e., 

approximately 22%). A model was used to simulate 

intake among 1,113 of the 5,000 infants expected to 

be breast-fed. The results indicated that lipid intake 

among nursing infants under 12 months can be 

characterized by a normal distribution with a mean of 

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26.0 mL/day and a standard deviation of 7.2 mL/day 

(see Table 15-24). The model assumes that nursing 

infants are completely breast-fed and does not 

account for infants who are breast-fed longer than 1 

year. Based on data collected by Dewey et al. 

(1991b), Maxwell and Burmaster (1993) estimated 

the lipid content of human milk to be 36.7 g/L at 3 

months (35.6 mg/g or 3.6%), 39.2 g/L at 6 months 

(38.1 mg/g or 3.8%), 41.6 g/L at 9 months (40.4 mg/g 

or 4.0%), and 40.2 g/L at 12 months (39.0 mg/g or 

3.9%). 

The limitation of this study is that it provides a 

snapshot of daily lipid intake from human milk for 

breast-fed infants. These results also are based on a 

simulation model and there are uncertainties 

associated with the assumptions made. Another 

limitation is that lipid intake was not derived for the 

U.S. EPA recommended age categories. The 

estimated mean lipid intake rate represents the 

average daily intake for nursing infants under 

12 months. The study also did not generate new data. 

A reanalysis of previously reported data on human 

milk intake and human milk lipid intake were 

provided. 

15.6. OTHER FACTORS 

Many factors influence the initiation, 

continuation, and amount of human milk intake. 

These factors are complex and may include 

considerations such as maternal nutritional status, 

parity, parental involvement, support from lactation 

consultants, mother’s working status, infant’s age, 

weight, sex, food supplementation, the frequency of 

breast-feeding sessions each day, the duration of 

breast-feeding for each event, the duration of breastfeeding during childhood, ethnicity, geographic area, 

and other socioeconomic factors. For example, a 

study conducted in the United Kingdom found that 

social and educational factors most influenced the 

initiation and continuation of lactation (Wright et al., 

2006). Prenatal and postnatal lactation consultant 

intervention was found to be effective in increasing 

lactation duration and intensity (Bonuck et al., 2005). 

15.6.1. Population of Nursing Infants 

Breast-feeding rates in the United States have 

consistently increased since 1993. McDowell et al. 

(2008) reported that the percentage of infants who 

were ever breast-fed increased from 60% in 1993– 

1994 to 77% among infants born in 2005–2006 

according to the data from the National Health and 

Nutrition Examination Surveys (NHANES). This 

exceeded the goal of 75% set in the Healthy People 

2010 McDowell et al. (2008). Rates among nonHispanic black women increased significantly from 

36% in 1993–1994 to 65% in 2005–2006. Income 

and age had a significant impact on breast-feeding 

rates. Breast-feeding rates among higher income 

women were 74% compared to 57% among lower 

income women (McDowell et al., 2008). 

In another study to monitor progress toward 

achieving the Centers for Disease Control and 

Prevention (CDC) Healthy People 2010 breastfeeding objectives (initiation and duration), Scanlon 

et al. (2007) analyzed data from the National 

Immunization Survey (NIS). NIS uses random-digit 

dialing to survey households to survey age-eligible 

children, followed by a mail survey to eligible 

children’s vaccination providers to validate the 

vaccination information. NIS is conducted annually 

by the CDC to obtain national, state, and selected 

urban area estimation on vaccinations rates among 

U.S. children ages 19–35 months. The interview 

response rate for years 2001–2006 ranged between 

64.5% and 76.1%. Questions regarding breastfeeding were added to the NIS survey in 2001. The 

sample population was infants born during 2000– 

2004. Scanlon et al. (2007) noted that because data in 

their analysis are for children ages 19–35 months at 

the time of the NIS interview, each cross-sectional 

survey includes children from birth cohorts that span 

3 calendar years; the breast-feeding data were 

analyzed by year-of-birth during 2000–2004 (birth 

year cohort instead if survey year). 

Among infants born in 2000, breast-feeding rates 

were 70.9% (CI = 69.0–72.8) for the postpartum 

period (in hospital before discharge), 34.2% 

(CI = 32.2–36.2) at 6 months, and 15.7 (CI = 14.2– 

17.2) at 12 months. For infants born in 2004, these 

rates had increased to 73.8% (CI = 72.8–74.8) for the 

postpartum period, 41.5% (CI = 40.4–42.6) at 6 

months, and 20.9 (CI = 20.0–21.8) at 12 months. 

Rates of breast-feeding through 3 months were 

lowest among black infants (19.8%), infants whose 

mothers were <20 years of age (16.8%), those whose 

mothers had a high school education or less (22.9% 

and 23.9%), those whose mothers were unmarried 

(18.8%), those who resided in rural areas (23.9%), 

and those whose families had an income-to-poverty 

ratio of <100% (23.9%). Table 15-25 shows data for 

exclusive breast-feeding through 3 and 6 months by 

socioeconomic characteristics for infants born in 

2004. 

Scanlon et al. (2007) noted the following 

limitations could affect the utility of these data: 

(1) breast-feeding behavior was based on 

retrospective self-report by mothers or other 

caregivers, whose responses might be subject to 

recall bias; (2) the NIS question defining early 

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postpartum breast-feeding or initiation—"Was 

[child's name] ever breast-fed or fed breast milk?"— 

collects information that might differ from the 

HP2010 objective for initiation; and (3) although 

survey data were weighted to make them 

representative of all U.S. children ages 19– 

35 months, some bias might remain. The advantage 

of the study is that is representative of the U.S. infant 

population. 

In 2007, CDC released the CDC Breast-feeding 

Report Card, which has been updated every year 

since. The CDC National Immunization Program in 

partnership with the CDC National Center for Health 

Statistics conducts the NIS within all 50 states, the 

District of Columbia, and selected geographic areas 

within the states. Five breast-feeding goals are in the 

Healthy People 2010 report. The Breast-feeding 

Report Card presents data for each state for the 

following categories of infants: ever breast-fed, 

breast-fed at 6 months, breast-fed at 12 months, 

exclusive breast-feeding through 3 months, and 

exclusive breast-feeding through 6 months (CDC, 

2009). These indicators are used to measure a state’s 

ability to promote, protect, and support breastfeeding. Table 15-26 presents these data for the 

estimated percentage of infants born in 2006. The 

advantage of this report is that it provides data for 

each state and is representative of the U.S. infant 

population. 

Analysis of breast-feeding practices in other 

developing countries also was found in the literature. 

Marriott et al. (2007) researched feeding practices in 

developing countries in the first year of life, based on 

24-hour recall data. Marriott et al. (2007) used 

secondary data from the Demographic and Health 

Surveys (DHS) for more than 35,000 infants in 

20 countries. This survey has been conducted since 

1986 and was expanded to provide a standardized 

survey instrument that can be used by developing 

countries to collect data on maternal-infant health and 

intake and household variables, as well as to build 

national health statistics (Marriott et al., 2007). The 

analysis was based on the responses of the survey 

mothers for questions on whether they were currently 

breast-feeding and had fed other liquids and solid 

foods to their infants in the previous 24 hours. The 

data incorporated were from between 1999 and 2003. 

Marriott et al. (2007) selected the youngest infant 

(i.e., less than 1 year old) in each of the families; 

multiples were included such as twins or triplets. 

Separate analyses were conducted for infants less 

than 6 months old and infants 6 months and older, but 

less than 12 months old. Food and liquid variables 

other than water and infant formulas were collapsed 

into broader food categories for cross-country 

comparisons (Marriott et al., 2007). Tinned, 

powdered, and any other specified animal milks were 

collapsed. In addition, all other liquids such as herbal 

teas, fruit juices, and sugar water (excluding unique 

country-specific liquids) were collapsed into other 

liquids and the 10 types of solid food groups into an 

any-solid-foods category (Marriott et al., 2007). Data 

were pooled from the 20 countries to provide a large 

sample size and increase statistical power. 

Table 15-27 and Table 15-28 present the percentage 

of mothers who were currently breast-feeding and 

separately had fed their infants other liquids or solid 

food by age groups. Table 15-29 presents the pooled 

data summary for the study period. The current 

breast-feeding was consistent across countries for 

both age groups; the countries that reported the 

highest percentages of current breast-feeding for the 

0- to 6-month-old infants also reported the highest 

percentages in the 6- to 12-month-old infants. Pooled 

data show that 96.6% of the 0- to 6-month-old infants 

and 87.9% of the 6- to 12-month-old infants were 

breast-feeding. Feeding of other fluids was lowest in 

the 0- to 6-month-old infants, with the percentage 

feeding water the highest of this category. The 

percentage of mothers feeding commercial infant 

formulas was the lowest in most countries. 

There are other older studies that analyze ethnic 

and racial differences in breast-feeding practices. Li 

and Grummer-Strawn (2002) investigated ethnic and 

racial disparities in lactation in the United States 

using data from the NHANES III that was conducted 

between 1988 and 1994. NHANES II participants 

were ages 2 months and older. The data were 

collected during a home interview from a parent or a 

proxy respondent for the child (Li and GrummerStrawn, 2002). The sample population consisted of 

children 12–71 months of age at time of interview. 

The NHANES III response rate for children 

participating was approximately 94% (Li and 

Grummer-Strawn, 2002). Data for a total of 2,863 

exclusively breast-fed, 6,140 ever breast-fed, and 

6,123 continued breast-fed children were included in 

the analysis (Li and Grummer-Strawn, 2002). The 

percentage of children ever breast-fed was 60% 

among non-Hispanic Whites, 26% among 

non-Hispanic Blacks, and 54% among Mexican 

Americans. This percentage decreased to 27%, 9%, 

and 23% respectively by 6 months. The percentage of 

children fed exclusively human milk at 4 months also 

was significantly lower for Blacks at 8.5%, compared 

to 22.6% for Whites and 14.1% for Mexican 

Americans. The racial and ethnic differences in 

proportion of children ever breast-fed is presented in 

Table 15-30, the proportion of children who received 

any breast milk at 6 months are presented in 

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Chapter 15—Human Milk Intake 

Table 15-31, and the proportion of children 

exclusively breast-fed at 4 months is presented in 

Table 15-32. 

Li and Grummer-Strawn (2002) noted that there 

may have been some lag time between birth and the 

time of the interview. This may have caused 

misclassification if the predicator variables changed 

considerably between birth and the time of interview. 

Also, NHANES III did not collect information on 

maternal education. Instead, the educational level of 

the household head was used as a proxy. The 

advantage of this study is that it is representative of 

the U.S. children’s population. 

Data from some older studies provide historical 

information on breast-feeding practices in the United 

States. These data are provided in this chapter to 

show trends in the U.S. population. In 1991, the 

National Academy of Sciences (NAS) reported that 

the percentage of breast-feeding women has changed 

dramatically over the years (NAS, 1991). The Ross 

Products Division of Abbott Laboratories conducted 

a large national mail survey in 1995 to determine 

patterns of breast-feeding during the first 6 months of 

life. The Ross Laboratory Mothers’ Survey was first 

developed in 1955 and has been expanded to include 

many more infants. Before 1991, the survey was 

conducted on a quarterly basis, and approximately 

40,000 to 50,000 questionnaires were mailed each 

quarter (Ryan, 1997). Beginning in 1991, the survey 

was conducted monthly; 35,000 questionnaires were 

mailed each month. Over time, the response rate has 

been consistently in the range of 50 ± 5%. In 1989 

and 1995, 196,000 and 720,000 questionnaires were 

mailed, respectively. Ryan (1997) reported rates of 

breast-feeding through 1995 and compared them with 

those in 1989. 

The survey demonstrates increases in both the 

initiation of breast-feeding and continued breastfeeding at 6 months of age between 1989 and 1991. 

Table 15-33 presents the percentage of breast-feeding 

in hospitals and at 6 months of age by selected 

demographic characteristics. In 1995, the incidence 

of breast-feeding at birth and at 6 months for all 

infants was approximately 59.7% and 21.6%, 

respectively. The largest increases in the initiation of 

breast-feeding between 1989 and 1995 occurred 

among women who were black, were less than 

20 years of age, earned less than $10,000 per year, 

had no more than a grade school education, were 

living in the South Atlantic region of the United 

States, had infants of low birth weight, were 

employed full time outside the home at the time they 

received the survey, and participated in the Women, 

Infants, and Children program (WIC). In 1995, as in 

1989, the initiation of breast-feeding was highest 

among women who were more than 35 years of age, 

earned more than $25,000 per year, were 

college-educated, did not participate in the WIC 

program, and were living in the Mountain and Pacific 

regions of the United States. 

Data on the actual length of time that infants 

continue to breast-feed beyond 5 or 6 months were 

limited (NAS, 1991). However, Maxwell and 

Burmaster (1993) estimated that approximately 22% 

of infants under 1 year are breast-fed. This estimate 

was based on a reanalysis by Ryan et al. (1991) of 

survey data collected by Ross Laboratories (Maxwell 

and Burmaster, 1993). Studies also have indicated 

that breast-feeding practices may differ among ethnic 

and socioeconomic groups and among regions of the 

United States. More recently, the Ross Products 

Division of Abbott Laboratories reported the results 

of their ongoing Ross Mothers Survey in 2003 

(Abbott Labs, 2003). Table 15-34 presents the 

percentages of mothers who breast-feed, based on 

ethnic background and demographic variables. These 

data update the values presented in the NAS (1991) 

report. 

15.6.2. Intake Rates Based on Nutritional Status 

Information on differences in the quality and 

quantity of human milk on the basis of ethnic or 

socioeconomic characteristics of the population is 

limited. Lönnerdal et al. (1976) studied human milk 

volume and composition (nitrogen, lactose, proteins) 

among underprivileged and privileged Ethiopian 

mothers. No significant differences were observed 

between the data for these two groups. Similar data 

were observed for well-nourished Swedish mothers. 

Lönnerdal et al. (1976) stated that these results 

indicate that human milk quality and quantity are not 

affected by maternal malnutrition. However, Brown 

et al. (1986b; 1986a) noted that the lactational 

capacity and energy concentration of marginally 

nourished women in Bangladesh were “modestly less 

than in better nourished mothers.” Human milk 

intake rates for infants of marginally nourished 

women in this study were 690 ± 122 g/day at 3 

months, 722 ± 105 g/day at 6 months, and 

719 ± 119 g/day at 9 months (Brown et al., 1986a). 

Brown et al. (1986a) observed that human milk from 

women with larger measurements of arm 

circumference and triceps skinfold thickness had 

higher concentrations of fat and energy than mothers 

with less body fat. Positive correlations between 

maternal weight and milk fat concentrations also 

were observed. These results suggest that milk 

composition may be affected by maternal nutritional 

status. 

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Chapter 15—Human Milk Intake 

15.6.3.	 Frequency and Duration of Feeding 

Hofvander et al. (1982) reported on the frequency 

of feeding among 25 bottle-fed and 25 breast-fed 

infants at ages 1, 2, and 3 months. The mean number 

of meals for these age groups was approximately five 

meals a day (see Table 15-35). Neville et al. (1988) 

reported slightly higher mean feeding frequencies. 

The mean number of meals per day for exclusively 

breast-fed infants was 7.3 at ages 2–5 months and 

8.2 at ages 2 weeks to 1 month. Neville et al. (1988) 

reported that, for infants between the ages of 1 week 

and 5 months, the average duration of a breastfeeding session is 16–18 minutes. 

Buckley (2001) studied the breast-feeding 

patterns, dietary intake, and growth measurement of 

children who continued to breast-feed beyond 1 year 

of age. The sample was 38 mother-child pairs living 

in the Washington, DC, area. The criteria for 

inclusion in the study were that infants or their 

mothers had no hospitalization of either subject 

3 months prior to the study and that the mother was 

currently breast-feeding a 1-year-old or older child 

(Buckley, 2001). The participants were recruited 

through local medical consultants and the La Leche 

League members. The children selected as the final 

study subjects consisted of 22 boys and 16 girls with 

ages ranging from 12 to 43 months old. The data 

were collected using a 7-day breast-feeding diary. 

The frequency and length of breast-feeding varied 

with the age of the child (Buckley, 2001). The author 

noted a statistically significant difference in the mean 

number of breast-feeding episodes each day and the 

average total minutes of breast-feeding between the 

1-, 2-, and 3-year-old groups. Table 15-36 provides 

the comparison of breast-feeding patterns between 

age groups. An advantage of this study is that the 

frequency and duration data are based primarily on a 

7-day diary and some dietary recall. Limitations of 

the study are the small sample size and that it is 

limited to one geographical area. 

15.7. REFERENCES FOR CHAPTER 15 

Abbott Labs (Abbott Laboratories). (2003). 

Breastfeeding trends - 2003. In Ross 

mothers survey. Columbus, OH: Ross 

Products Division of Abbott Laboratories. 

http://abbottnutrition.com/Downloads/News 

AndMedia/MediaCenter/BF_Trends_2003.p 

df. 

Albernaz, E; Victora, CG; Haisma, H; Wright, A; 

Coward, WA. (2003). Lactation counseling 

increases breast-feeding duration but not 

breast milk intake as measured by isotopic 

methods. J Nutr 133: 205-210. 

Arcus-Arth, A; Krowech, G; Zeise, L. (2005). Breast 

milk and lipid intake distributions for 

assessing cumulative exposure and risk. J 

Expo Anal Environ Epidemiol 15: 357-365. 

http://dx.doi.org/10.1038/sj.jea.7500412. 

Bonuck, KA; Trombley, M; Freeman, K; Mckee, D. 

(2005). Randomized, controlled trial of a 

prenatal and postnatal lactation consultant 

intervention on duration and intensity of 

breastfeeding up to 12 months. Pediatrics 

116: 1413-1426. 

http://dx.doi.org/10.1542/peds.2005-0435. 

Brown, KH; Akhtar, NA; Robertson, AD; Ahmed, 

MG. (1986a). Lactational capacity of 

marginally nourished mothers: Relationships 

between maternal nutritional status and 

quantity and proximate composition of milk. 

Pediatrics 78: 909-919. 

Brown, KH; Robertson, AD; Akhtar, NA.	 (1986b). 

Lactational capacity of marginally nourished 

mothers: Infants' milk nutrient consumption 

and patterns of growth. Pediatrics 78: 920­

927. 

Buckley, KM. (2001). Long-term breastfeeding: 

Nourishment or nurturance? J Hum Lact 17: 

304-312. 

Butte, NF; Garza, C; Smith, EO; Nichols, BL. 

(1984). Human milk intake and growth in 

exclusively breast-fed infants. J Pediatr 104: 

187-195. 

Butte, NF; Wong, WW; Hopkinson, JM; Smith, EO; 

Ellis, KJ. (2000). Infant feeding mode 

affects early growth and body composition. 

Pediatrics 106: 1355-1366. 

CDC (Centers for Disease Control and Prevention). 

(2009). Breastfeeding report card 2009: 

Breastfeeding practices – results from the 

National Immunization Survey. Atlanta, GA. 

http://www.cdc.gov/breastfeeding/pdf/2009 

BreastfeedingReportCard.pdf. 

Chen, A; Rogan, WJ. (2004). Breastfeeding and the 

risk of postneonatal death in the United 

States. Pediatrics 113: e435-e439. 

Dewey, KG; Heinig, MJ; Nommsen, LA; Lonnerdal, 

B. (1991a). Maternal versus infant factors 

related to breast milk intake and residual 

milk volume: the DARLING study. 

Pediatrics 87: 829-837. 

Dewey, KG; Heinig, MJ; Nommsen, LA; Lönnerdal, 

B. (1991b). Adequacy of energy intake 

among breast-fed infants in the DARLING 

study: relationships to growth velocity, 

morbidity, and activity levels. Davis Area 

Research on Lactation, Infant Nutrition and 

Page Exposure Factors Handbook 

15-18 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Chapter 15—Human Milk Intake 

Growth. J Pediatr 119: 538-547. 

Dewey, KG; Lönnerdal, B. (1983). Milk and nutrient 

intake of breast-fed infants from 1 to 6 

months: relation to growth and fatness. J 

Pediatr Gastroenterol Nutr 2: 497-506. 

Dewey, KG; Peerson, JM; Heinig, MJ; Nommsen, 

LA; Lönnerdal, B; Lopez de Romaña, G; de 

Kanashiro, HC; Black, RE; Brown, KH. 

(1992). Growth patterns of breast-fed infants 

in affluent (United States) and poor (Peru) 

communities: implications for timing of 

complementary feeding. Am J Clin Nutr 56: 

1012-1018. 

Drewett, R; Amatayakul, K; Wongsawasdii, L; 

Mangklabruks, A; Ruckpaopunt, S; 

Ruangyuttikarn, C; Baum, D; Imong, S; 

Jackson, D; Woolridge, M. (1993). Nursing 

frequency and the energy intake from breast 

milk and supplementary food in a rural Thai 

population: a longitudinal study. Eur J Clin 

Nutr 47: 880-891. 

Ferris, AM; Neubauer, SH; Bendel, RB; Green, KW; 

Ingardia, CJ; Reece, EA. (1993). Perinatal 

lactation protocol and outcome in mothers 

with and without insulin-dependent diabetes 

mellitus. Am J Clin Nutr 58: 43-48. 

Gartner, LM; Morton, J; Lawrence, RA; Naylor, AJ; 

O'Hare, D; Schanler, RJ; Eidelman, AI; 

Breastfeeding, AAO, PSO. (2005). 

Breastfeeding and the use of the human 

milk. Pediatrics 115: 496-506. 

http://dx.doi.org/10.1542/peds.2004-2491. 

González-Cossío, T; Habicht, JP; Rasmussen, KM; 

Delgado, HL. (1998). Impact of food 

supplementation during lactation on infant 

breast-milk intake and on the proportion of 

infants exclusively breast-fed. J Nutr 128: 

1692-1702. 

Hofvander, Y; Hagman, U; Hillervik, C; Sjölin, S. 

(1982). The amount of milk consumed by 1­

3 months old breast- or bottle-fed infants. 

Acta Paediatr Scand 71: 953-958. 

Kent, JC; Mitoulas, LR; Cregan, MD; Ramsay, DT; 

Doherty, DA; Hartmann, PE. (2006). 

Volume and frequency of breastfeedings and 

fat content of breast milk throughout the 

day. Pediatrics 117: e387-e395. 

http://dx.doi.org/10.1542/peds.2005-1417. 

Li, R; Grummer-Strawn, L. (2002). Racial and ethnic 

disparities in breastfeeding among United 

States infants: Third National Health and 

Nutrition Examination Survey, 1988-1994. 

Birth 29: 251-257. 

Lönnerdal, B; Forsum, E; Gebre-Medhin, M; 

Hambraeus, L. (1976). Breast milk 

composition in Ethiopian and Swedish 

mothers. II. Lactose, nitrogen, and protein 

contents. Am J Clin Nutr 29: 1134-1141. 

Marriott, BM; Campbell, L; Hirsch, E; Wilson, D. 

(2007). Preliminary data from demographic 

and health surveys on infant feeding in 20 

developing countries. J Nutr 137: 518S523S. 

Maxwell, NI; Burmaster, DE. (1993). A simulation 

model to estimate a distribution of lipid 

intake from breast milk during the first year 

of life. J Expo Anal Environ Epidemiol 3: 

383-406. 

McDowell, MM; Wang, CY; Kennedy-Stephenson, J. 

(2008). Breastfeeding in the United States: 

Findings from the National Health and 

Nutrition Examination Surveys, 1999-2006. 

NCHS1-8. 

Mitoulas, LR; Gurrin, LC; Doherty, DA; Sherriff, JL; 

Hartmann, PE. (2003). Infant intake of fatty 

acids from human milk over the first year of 

lactation. Br J Nutr 90: 979-986. 

http://dx.doi.org/10.1079/BJN2003979. 

Mitoulas, LR; Kent, JC; Cox, DB; Owens, RA; 

Sherriff, JL; Hartmann, PE. (2002). 

Variation in fat, lactose and protein in 

human milk over 24 h and throughout the 

first year of lactation. Br J Nutr 88: 29-37. 

http://dx.doi.org/10.1079/BJNBJN2002579. 

NAS (National Academy of Sciences). (1991). 

Nutrition during lactation. Washington, DC: 

The National Academies Press. 

http://www.nap.edu/catalog.php?record_id= 

1577. 

Neubauer, SH; Ferris, AM; Chase, CG; Fanelli, J; 

Thompson, CA; Lammi-Keefe, CJ; Clark, 

RM; Jensen, RG; Bendel, RB; Green, KW. 

(1993). Delayed lactogenesis in women with 

insulin-dependent diabetes mellitus. Am J 

Clin Nutr 58: 54-60. 

Neville, MC; Keller, R; Seacat, J; Lutes, V; Neifert, 

M; Casey, C; Allen, J; Archer, P. (1988). 

Studies in human lactation: milk volumes in 

lactating women during the onset of 

lactation and full lactation. Am J Clin Nutr 

48: 1375-1386. 

Pao, EM; Himes, JM; Roche, AF. (1980). Milk 

intakes and feeding patterns of breast-fed 

infants. J Am Diet Assoc 77: 540-545. 

Ryan, AS. (1997). The resurgence of breastfeeding in 

the United States. Pediatrics 99: E12. 

Ryan, AS; Rush, D; Krieger, FW; Lewandowski, GE. 

(1991). Recent declines in breast-feeding in 

the United States, 1984 through 1989. 

Pediatrics 88: 719-727. 

Exposure Factors Handbook Page
 

September 2011 15-19 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Salmenperä, L; Perheentupa, J; Siimes, MA. (1985). 

Exclusively breast-fed healthy infants grow 

slower than reference infants. Pediatr Res 

19: 307-312. 

Scanlon, K; Grummer-Strawn, L; Shealy, K; Jefferds, 

M; Chen, J; Singleton, J; Philip, C. (2007). 

Breastfeeding trends and updated national 

health objectives for exclusive 

breastfeeding—United States, birth years 

2000-2004. 56: 760-763. 

Stuff, JE; Nichols, BL. (1989). Nutrient intake and 

growth performance of older infants fed 

human milk. J Pediatr 115: 959-968. 

Wright, CM; Parkinson, K; Scott, J. (2006). Breastfeeding in a UK urban context: who breastfeeds, for how long and does it matter? 

Public Health Nutr 9: 686-691. 

Page Exposure Factors Handbook 

15-20 September 2011 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Exposure Factors Handbook Page
 

September 2011 15-21 

Table 15-7. Daily Intakes of Human Milk 

Intake 

Age Number of Infants 

Mean ± SD (mL/day) a Intake Range (mL/day) 

Completely Breast-fed 

 1 month 11 600 ± 159 426–989 

 3 months 2 833 645–1,000 

 6 months 1 682 616–786 

Partially Breast-fed 

 1 month 4 485 ± 79 398–655 

 3 months 11 467 ± 100 242–698 

 6 months 6 395 ± 175 147–684 

 9 months 3 <554 451–732 

a Data expressed as mean ± standard deviation. 

Source: Pao et al. (1980). 

Table 15-8. Human Milk Intakes for Infants Aged 1–6 Months 

Intake 

Age Number of Infants 

Mean ± SD (mL/day) Intake Range (mL/day) 

1 month 

2 months 

3 months 

4 months 

5 months 

6 months 

16 

19 

16 

13 

11 

11 

673 ± 192 

756 ± 170 

782 ± 172 

810 ± 142 

805 ± 117 

896 ± 122 

341–1,003 

449–1,055 

492–1,053 

593–1,045 

554–1,045 

675–1,096 

Source: Dewey and Lönnerdal (1983). 

Table 15-9. Human Milk Intake Among Exclusively Breast-Fed Infants During the First 4 Months of Life 

Age Number of Infants Intake (mL/day)a 

Mean ± SD 

Intake (mL/kg-day)a 

Mean ± SD Feedings/Day Body Weightb (kg) 

1 month 37 729 ± 126 154 ± 23 8.3 ± 1.9 4.7 

2 months 40 704 ± 127 125 ± 18 7.2 ±1.9 5.6 

3 months 37 702 ± 111 114 ± 19 6.8 ± 1.9 6.2 

4 months 41 718 ± 124 108 ± 17 6.7 ± 1.8 6.7 

a Values reported by the author in units of g/day and g/kg-day were converted to units of mL/day and mL/kg-day by 

dividing by 1.03 g/mL (density of human milk). b Calculated by dividing human milk intake (g/day) by human milk intake (g/kg-day). 

SD = Standard deviation. 

Source: Butte et al. (1984). 
 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-10. Human Milk Intake During a 24-Hour Period 

Age 

(days) Number of Infants 

Intake (mL/day)a Intake by Age 

Category 

(mL/day) Mean ± SD Range a, b 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

14 

21 

28 

6 

9 

10 

10 

11 

9 

7 

8 

9 

9 

8 

9 

10 

13 

43 ± 68 

177 ± 83 

360 ± 149 

438 ± 171 

483 ± 125 

493 ± 162 

556 ± 162 

564 ± 154 

563 ± 74 

569 ± 128 

597 ± 163 

634 ± 150 

632 ± 82 

748 ± 174 

–30–145c 

43–345 

203–668 

159–674 

314–715 

306–836 

394–817 

398–896 

456–699 

355–841 

386–907 

404–895 

538–763 

481–1,111 

511 ± 220 

35 

42 

49 

56 

12 

12 

10 

12 

649 ± 114 

690 ± 108 

688 ± 112 

674 ± 95 

451–903 

538–870 

543–895 

540–834 

679 ± 105 

90 10 713 ± 111 595–915 713 ± 111 

120 12 690 ± 97 553–822 690 ± 97 

150 12 814 ± 130 668–1,139 814 ± 130 

180 13 744 ± 117 493–909 744 ± 117 

210 12 700 ± 150 472–935 700 ± 150 

240 9 604 ± 204 280–973 604 ± 204 

270 12 600 ± 214 217–846 600 ± 214 

300 11 535 ± 227 125–868 535 ± 227 

330 8 538 ± 233 117–835 538 ± 233 

360 8 391 ± 243 63–748 391 ± 243 

a Values reported by the author in units of g/day were converted to units of mL/day by dividing by 

1.03 g/mL (density of human milk). b Multiple data sets were combined by producing simulated data sets fitting the known mean and SD for 

each age, compositing the data sets to correspond to age groups of 0 to <1 month and 1 to <2 months, and 

calculating new means and SD’s on the composited data. c Negative value due to insensible weight loss correction. 

SD = Standard deviation. 

Source: Neville et al. (1988). 

Page Exposure Factors Handbook 

15-22 September 2011 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-11. Human Milk Intake Estimated by the Darling Study 

Age Number of Infants Intake (mL/day)a 

Mean ± SD 

3 months 

6 months 

9 months 

12 months 

73 

60 

50 

42 

788 ± 129 

747 ± 166 

627 ± 211 

435 ± 244 

a Values reported by the author in units of g/day were converted to units of mL/day by 

dividing by 1.03 g/mL (density of human milk). 

SD = Standard deviation. 

Source: Dewey et al. (1991b). 

Table 15-12. Mean Breast-Fed Infants Characteristicsa 

Boys (N = 14) Girls (N = 26) 

Ethnicity (White, Black, Hispanic, Asian) (N) 10/1/2/1 

Duration of Breast-Feeding (days) 315 ± 152 

Duration of Formula Feeding (days) 184 ± 153 

Age at Introduction of Formula (months) 6.2 ± 2.9 

Age at Introduction of Solids (months) 5.0 ± 1.5 

Age at Introduction of Cow’s Milk (months) 13.1 ± 3.1 

21/1/3/1 

362 ± 190 

105 ± 121 

5.2 ± 2.3 

5.0 ± 0.09 

12.5 ± 3.8 

a Mean ± standard deviation. 

N = Number of infants. 

Source: Butte et al. (2000). 

Table 15-13. Mean Human Milk Intake of Breast-Fed Infants (mL/day)a 

Age Group Boys Girls 

3 months 790 ± 172 (N = 14) 694 ± 108 (N = 26) 

6 months 576 ± 266 (N = 12) 678 ± 250 (N = 18) 

12 months 586 ± 286 (N = 2) 370 ± 260 (N = 11) 

24 months – – 

a 3-day average; values reported by the author in units of g/day were converted to units of mL/day by 

dividing by 1.03 g/mL (density of human milk); mean ± standard deviation. 

N = Number of infants. 

– = Not quantitated. 

Source: Butte et al. (2000). 

Exposure Factors Handbook Page
 

September 2011 15-23 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Page Exposure Factors Handbook 

15-24 September 2011 

Table 15-14. Feeding Practices by Percent of Infants 

Infants 

Age 

3 

months 

6 

months 

9 

months 

12 

months 

18 

months 

24 

months 

Percentage 

Infants Still Breast-Fed 100 80 58 38 25 5 

Breast-Fed Infants Given Formula 0 40 48 30 10 2 

Formula-Fed Infants Given Breast Milk 100 100 94 47 6 0 

Use of Cow’s Milk for Breast-Fed Infants – – 8 65 82 88 

Use of Cow’s Milk for Formula-Fed Infants – – 28 67 89 92 

Source: Butte et al. (2000). 

 

 

Table 15-15. Body Weight of Breast-Fed Infantsa 

Weight (kg) 

Age Boys Girls 

0.5 months 3.9 ± 0.4 (n = 14) 3.7 ± 0.5 (n = 19) 

3 months 6.4 ± 0.6 (n = 14) 6.0 ± 0.6 (n = 19) 

6 months 8.1 ± 0.8 (n = 14) 7.5 ± 0.6 (n = 18) 

9 months 9.3 ± 1.0 (n = 14) 8.4 ± 0.6 (n = 19) 

12 months 10.1 ± 1.1 (n = 14) 9.2 ± 0.7 (n = 19) 

18 months 11.6 ± 1.2 (n = 14) 10.7 ± 1.0 (n = 19) 

24 months 12.7 ± 1.3 (n = 12) 11.8 ± 1.1 (n = 19) 

a Mean ± standard deviation. 

n = Number of infants. 

Source: Butte et al. (2000). 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Exposure Factors Handbook Page
 

September 2011 15-25 

Table 15-16. AAP Data Set Milk Intake Rates at Different Ages 

Age Mean 

(mL/kg-day)a 

SD 

(mL/kg-day)a CV Skewness Statisticb N 

7 days 

14 days 

30 days 

60 days 

90 days 

120 days 

150 days 

180 days 

210 days 

270 days 

360 days 

143 

156 

150 

144 

127 

112 

100 

101 

75 

72 

47 

37 

40 

24 

22 

18 

18 

21 

20 

25 

23 

27 

0.26 

0.26 

0.16 

0.15 

0.14 

0.16 

0.21 

0.20 

0.33 

0.32 

0.57 

0.598 

–1.39 

0.905 

0.433 

–0.168 

0.696 

–1.077 

–1.860 

–0.844 

–0.184 

0.874 

10 

9 

25 

25 

108 

57 

26 

39 

8 

57 

42 

a Values reported by the author in units of g/kg-day were converted to units of mL/kg-day by 

dividing by 1.03 g/mL (density of human milk). b 

 Statistic/SE: -2 < Statistic/SE < +2 suggests a normal distribution. 

SD = Standard deviation. 

CV = Coefficient of variation. 

N = Number of infants. 

Source: Arcus-Arth et al. (2005). 

 

 

 

 

 

 

 

 

Table 15-17. Average Daily Human Milk Intake (mL/kg-day)a 

Averaging Period Mean (SD) 

Population Percentile 

5 10 25 50 75 90 95 99 

AAP 0 to 6 months 

Method 1 126 (21) 92 99 112 126 140 152 160 174 

Method 2 123 (7) 112 114 118 123 127 131 133 138 

AAP 0 to 12 months 

Method 1 98 (22) 61 69 83 98 113 127 135 150 

Method 2 99 (5) 90 92 95 99 102 105 107 110 

EBF 0 to 12 months 110 (21) 75 83 95 110 124 137 144 159 

General Pop. 

0 to 6 months 79 0 0 24 92 123 141 152 170 

0 to 12 months 51 0 0 12 49 85 108 119 138 

a Values reported by the author in units of g/kg-day were converted to units of mL/kg-day by dividing by 

1.03 g/mL (density of human milk). 

AAP = American Academy of Pediatrics. 

EBF = Exclusively breast-fed. 

Source: Arcus-Arth et al. (2005). 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Page Exposure Factors Handbook 

15-26 September 2011 

Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively 

Breast-Fed Infants 

Age 

(months) 

Number 

of 

Observations 

Lipid Content 

(mg/g) 

Mean ± SD 

Lipid 

Content %a 

Lipid 

Intake 

(mL/day)b 

Mean ± SD 

Lipid 

Intake 

(mL/kg-day)b 

Mean ± SD 

1 37 36.2 ± 7.5 3.6 27 ± 8 5.7 ± 1.7 

2 40 34.4 ± 6.8 3.4 24 ± 7 4.3 ± 1.2 

3 37 32.2 ± 7.8 3.2 23 ± 7 3.7 ± 1.2 

4 41 34.8 ± 10.8 3.5 25 ± 8 3.7 ± 1.3 

a Percents calculated from lipid content reported in mg/g. b Values reported by the author in units of g/day and g/kg-day were converted to units of mL/day and mL/kgday by dividing by 1.03 g/mL (density of human milk). 

Source: Butte et al. (1984). 

 

Table 15-19. Human Milk Production and Composition During the First 12 Months of Lactationa 

Age Group 

(months) 

Volume, per 

Breast (mL/24 

hours) 

Fat 

(g/L) 

Lactose 

(g/L) 

Protein 

(g/L) 

Energy 

(kJ/mL) 

Mean SE N Mean SE N Mean SE N Mean SE N Mean SE N 

1 416 24 34 39.9 1.4 34 59.7 0.8 18 10.5 0.4 18 2.7 0.06 18 

2 408 23 34 35.2 1.4 34 60.4 1.1 18 9.6 0.4 18 2.5 0.06 18 

4 421 20 34 35.4 1.4 32 62.6 1.3 16 9.3 0.4 18 2.6 0.09 16 

6 413 25 30 37.3 1.4 28 62.5 1.7 16 8.0 0.4 16 2.6 0.09 16 

9 354 47 12 40.7 1.7 12 62.8 1.5 12 8.3 0.5 12 2.8 0.09 12 

12 252 51 10 40.9 3.3 10 61.4 2.9 10 8.3 0.6 10 2.8 0.14 10 

1 to 12 399 11 154 37.4 0.6 150 61.4 0.6 90 9.2 0.2 92 2.7 0.04 90 

a Infants were completely breast-fed to 4 months and complementary solid food was introduced between 4 

and 6 months. 

SE = Standard error. 

N = Number of individual breasts. 

Source: Mitoulas et al. (2002). 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Exposure Factors Handbook Page
 

September 2011 15-27 

Table 15-20. Changes in Volume of Human Milk Produced and Milk Fat Content During the First Year a of Lactation

Age Group 

(months) 

Volume, Left 

Breast (mL/day) 

Volume, Right Breast 

(mL/day) 

Fat, Left Breast 

(g/L) 

Fat, Right Breast 

(g/L) 

N Mean SE Mean SE Mean SE Mean SE 

1 5 338 52 475 69 38 1.5 38 2.6 

2 5 364 52 427 42 31 2.2 30 2.9 

4 5 430 51 482 58 32 3.3 29 2.6 

6 5 373 75 437 56 33 2.5 33 2.5 

9 5 312 65 365 94 43 2.2 38 3.3 

12 5 203 69 302 85 40 4.8 42 5.0 

1 to 12 30 337 26 414 28 36 1.4 35 1.5 

Statistical 

significance: P 

NS NS 0.004 0.008 

a Infants were completely breast-fed to 4 months, and complementary solid food 

between 4 and 6 months. 

N = Number of mothers. 

SE = Standard error. 

NS = No statistical difference. 

P = Probability. 

Source: Mitoulas et al. (2003). 

was introduced 

Table 15-21. Changes in Fatty Acid Composition of Human Milk During the First Year of Lactation 

(g/100 g total fatty acids) 

Fatty Acid 

1 month 2 months 4 months 6 months 9 months 12 months 

Mean SE Mean SE Mean SE Mean SE Mean SE Mean SE 

Medium-Chain 

Saturated 

14.2 0.4 13.9 0.6 12.0 0.5 11.5 0.2 14.1 0.3 17.0 0.4 

Odd-Chain 

Saturated 

0.9 0.01 0.9 0.02 0.8 0.02 0.8 0.03 0.8 0.02 0.8 0.02 

Long-Chain 

Saturated 

34.1 0.3 33.7 0.3 32.8 0.3 31.8 0.6 31.4 0.6 33.9 0.6 

MonoUnsaturated 37.5 0.2 33.7 0.4 38.6 0.5 37.5 0.5 37.3 0.5 33.0 0.5 

Trans 2.0 0.08 2.2 0.1 2.2 0.09 4.6 0.02 1.7 0.2 1.8 0.09 

PolyUnsaturated 12.7 0.2 9.5 0.2 11.8 0.4 13.4 0.6 8.0 0.1 6.7 0.03 

SE = Standard error. 

Source: Mitoulas et al. (2003). 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Page Exposure Factors Handbook 

15-28 September 2011 

Table 15-22. Comparison Daily Lipid Intake Based on Lipid Content Assumptions (mL/kg-day)a, b 

Lipid Content Used in 

Calculation Mean Population Percentile 

5 10 25 50 75 90 95 99 

Measured Lipid Contentc 3.6 2.0 2.3 2.9 3.6 4.3 4.9 5.2 5.9 

4% Lipid Contentd 3.9 2.5 2.8 3.3 3.8 4.4 4.9 5.2 5.8 

a Values reported by the author in units of g/kg-day were converted to units of mL/kg-day by dividing 

by 1.03 g/mL (density of human milk). b 

 Estimates based on data from Dewey et al. (1991a). c 

 Lipid intake derived from lipid content and milk intake measurements. d 

 Lipid intake derived using 4% lipid content value and milk intake. 

Source: Arcus-Arth et al. (2005). 

 

Table 15-23. Distribution of Average Daily Lipid Intake (mL/kg-day) Assuming 4% Milk Lipid Contenta 

Mean Population Percentile 

5 10 25 50 75 90 95 99 

AAP Infants 0–12 months 3.9 2.4 2.8 3.3 3.9 4.5 5.1 5.4 6.0 

a Values reported by the author in units of g/kg-day were converted to units of mL/kg-day by dividing by 

1.03 g/mL (density of human milk). 

AAP = American Academy of Pediatrics. 

Source: Arcus-Arth et al. (2005). 

 

Table 15-24. Predicted Lipid Intakes for Breast-Fed Infants Under 12 Months of Age 

Statistic Value 

Number of Observations in Simulation 

Minimum Lipid Intake 

Maximum Lipid Intake 

Arithmetic Mean Lipid Intake 

Standard Deviation Lipid Intake 

1,113 

1.0 mL/daya 

51.0 mL/daya 

26.0 mL/daya 

7.2 mL/daya 

a Values reported by the author in units of g/day were converted to units of mL/day by dividing by 1.03 g/mL 

(density of human milk). 

Source: Maxwell and Burmaster (1993). 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Exposure Factors Handbook Page
 

September 2011 15-29 

Table 15-25. Socioeconomic Characteristics of Exclusively Breast-Fed Infants 

Born in 2004 

Percent of Exclusive Breast-Feeding Infants through 3 and 6 Months 

3 months 6 months 

Characteristic % 95% CI % 95% CI 

U.S. Overall (N = 17,654) 30.5 29.4–31.6 11.3 10.5–12.1 

Infant Sex 

Male 30.7 29.1–32.3 10.8 9.8–11.8 

Femalea 30.3 28.7–31.9 11.7 10.5–12.9 

Race/Ethnicity (child) 

Hispanic 30.8 28.3–33.3 11.5 9.7–13.3 

White, non-Hispanica 

Black, non-Hispanic 

33.0 

19.8b 

31.6–34.4 

17.0–22.6 

11.8 

7.3b 

10.9–12.7 

5.5–9.1 

Asian, non-Hispanic 30.6 25.0–36.2 14.5 10.0–19.0 

Other 29.3 24.9–33.7 12.2 9.2–15.2 

Maternal Age (years) 

<20 16.8b 10.3–23.3 6.1b 1.5–10.7 

20 to 29 26.2b 24.4–28.0 8.4b 7.3–9.5 

≥30a 34.6 33.2–36.0 13.8 12.7–14.9 

Household Head Education 

<High school 

High school 

Some college 

23.9b 

22.9b 

32.8b 

21.0–26.8 

20.9–24.9 

30.3–35.3 

9.1b 

8.2b 

12.3b 

7.1–11.1 

7.0–9.4 

10.2–14.4 

College graduatea 41.5 39.7–43.3 15.4 14.1–16.7 

Marital Status 

Marrieda 35.4 34.0–36.8 13.4 12.4–14.4 

Unmarried 18.8b 16.9–20.7 6.1b 5.0–7.2 

Residence 

MSA, center citya 30.7 29.0–32.4 11.7 10.5–12.9 

MSA, non-center city 

Non-MSA 

32.8 

23.9b 

30.9–34.7 

21.8–26.0 

12.1 

8.2b 

10.8–13.4 

6.9–9.5 

Poverty income ratio (%) 

<100 23.9b 21.6–26.2 8.3b 6.9–9.7 

100 to <184 26.6b 23.8–29.4 8.9b 7.2–10.6 

185 to <349 33.2b 30.9–35.5 11.8b 10.3–13.3 

≥350a 37.7 35.7–39.7 14.0 12.6–15.4 

a Referent group. b 

 p <0.05 by chi-square test, compared with referent group. 

N = Number of infants. 

MSA = Metropolitan statistical area. 

Source: Scanlon et al. (2007). 
 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-26. Geographic-Specific Breast-Feeding Percent Rates Among Children 

Born in 2006a 

State 

Ever 

Breast-Fed 

Breast-Fed 

at 6 Months 

Breast-Fed 

at 12 

Months 

Exclusive BreastFeeding through 

3 Months 

Exclusive BreastFeeding through 

6 Months 

U.S. National 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

Dist of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

73.9 43.4 22.7 33.1 13.6 

58.8 26.6 11.4 24.2 6.3 

88.5 48.9 26.2 45.5 16.9 

76.5 45.3 22.3 29.7 11.9 

61.5 26.9 10.6 23.6 6.3 

84.7 53.0 31.1 42.4 18.6 

82.5 59.5 30.5 49.2 22.6 

74.9 41.9 23.3 35.1 14.4 

66.7 32.8 15.4 28.1 7.5 

69.6 45.6 20.2 31.3 13.3 

75.7 37.2 18.2 30.7 11.9 

62.5 36.4 18.1 28.0 14.8 

88.2 56.3 35.0 44.9 22.4 

79.8 55.1 25.3 46.7 17.7 

69.5 38.7 15.9 28.5 11.9 

71.1 37.2 18.9 28.9 10.6 

68.1 33.2 15.8 32.3 10.6 

78.1 43.8 23.6 36.0 16.8 

53.6 28.9 15.8 27.2 9.4 

49.1 20.7 9.9 17.8 5.0 

75.0 45.7 26.0 38.7 18.1 

76.4 43.3 25.4 28.5 10.1 

78.2 44.7 24.5 39.0 13.5 

64.8 31.2 14.4 23.5 10.7 

79.9 51.6 24.7 39.8 15.0 

48.3 20.1 8.7 16.8 4.6 

65.3 33.1 14.9 24.8 8.5 

82.7 56.8 30.6 40.8 20.5 

Page Exposure Factors Handbook 

15-30 September 2011 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-26. Geographic-Specific Breast-Feeding Percent Rates Among Children 

Born in 2006a (continued) 

State 

Ever 

Breast-Fed 

Breast-Fed 

at 6 Months 

Breast-Fed 

at 12 

Months 

Exclusive BreastFeeding through 

3 Months 

Exclusive BreastFeeding through 

6 Months 

Nebraska 76.8 46.2 22.6 31.7 11.9 

Nevada 79.3 45.3 22.5 31.8 9.7 

New Hampshire 78.4 55.1 30.5 42.6 20.6 

New Jersey 81.4 53.0 27.4 29.7 13.2 

New Mexico 72.6 42.2 25.7 33.2 14.0 

New York 76.4 49.4 28.9 24.9 9.6 

North Carolina 66.9 36.7 18.9 30.2 13.1 

North Dakota 71.1 37.6 20.6 33.7 11.1 

Ohio 58.5 29.7 12.0 22.4 9.1 

Oklahoma 65.6 27.4 12.4 30.6 8.4 

Oregon 91.4 63.0 37.0 56.6 20.8 

Pennsylvania 67.6 35.8 19.4 29.3 10.1 

Rhode Island 75.4 40.4 19.8 31.8 8.7 

South Carolina 61.3 30.4 13.9 25.5 9.6 

South Dakota 76.8 47.5 22.1 36.5 17.6 

Tennessee 58.8 37.9 14.8 28.2 12.8 

Texas 78.2 48.7 25.3 34.2 14.2 

Utah 92.8 69.5 33.9 50.8 24.0 

Vermont 80.1 59.5 38.4 49.2 23.5 

Virginia 79.7 48.3 25.8 38.7 18.8 

Washington 86.4 58.0 35.0 48.8 25.3 

West Virginia 58.8 27.2 12.6 21.3 8.4 

Wisconsin 75.3 48.6 25.9 45.2 16.8 

Wyoming 84.2 50.8 26.7 46.2 16.8 

a Exclusive breast-feeding information is from the 2006 NIS survey data only and is defined 

as ONLY breast milk: no solids, no water, no other liquids. 

Source: CDC (2009). 

Exposure Factors Handbook Page
 

September 2011 15-31 
 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 

0–6 Months Olda 

Country Breast-Feeding Water Milk Formula Other Liquids Solid Foods 

Armenia 86.1 62.7 22.9 13.1 48.1 23.9 

Bangladesh 99.6 30.2 13.6 5.3 19.7 20.3 

Cambodia 98.9 87.9 2.1 3.3 6.7 16.6 

Egypt 95.5 22.9 11.1 4.3 27.6 13.2 

Ethiopia 98.8 26.3 19 0 10.8 5.3 

Ghana 99.6 41.9 6.7 3.5 4.3 15.6 

India 98.1 40.2 21.2 0 7.1 6.5 

Indonesia 92.8 37 0.7 24.2 8.7 43 

Jordan 92.4 58.5 3 25.1 13.8 20.2 

Kazakhstan 94.4 53.7 21.4 8.2 37.4 15.4 

Kenya 99.7 60 35.1 4.8 35.9 46.3 

Malarwi 100 46 1.4 1.7 5.2 42.3 

Nambia 95.3 65.4 0 0 17.9 33.4 

Nepal 100 23.3 12.3 0 2.8 9.3 

Nigeria 99.1 78.2 9.2 12.7 17.9 18.5 

Philippines 80.5 53.4 4.4 30 12.4 16.8 

Uganda 98.7 15.1 20.3 1.5 10.3 11.4 

Vietnam 98.7 45.9 16.9 0.8 8.9 18.7 

Zamibia 99.6 52.6 2.1 2.7 6.7 31.2 

Zimbabwe 100 63.9 1.6 3.2 9 43.7 

Pooled 96.6 45.9 11.9 9 15.1 21.9 

a Percentage of mothers who stated that they currently breast-feed and separately had fed their infants four 

categories of liquid or solid food in the past 24 hours by country for infants age 0 to 6 months old. 

Source: Marriott et al. (2007). 

Page Exposure Factors Handbook 

15-32 September 2011 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 

6–12 Months Olda 

Country Breast-Feeding Water Milk Formula Other Liquids Solid Foods 

Armenia 53.4 91.1 56.9 11.6 85.3 88.1 

Bangladesh 96.2 87.7 29.8 10.1 21.9 65.2 

Cambodia 94.4 97.5 3.7 6.7 29 81 

Egypt 89.1 85.9 36.8 16.7 48.5 75.7 

Ethiopia 99.4 69.2 37.6 0 23.9 54.7 

Ghana 99.3 88.8 14.6 9.6 23.9 71.1 

India 94.9 81.4 45 0 25.2 44.1 

Indonesia 84.8 85.4 4.9 38.8 35.4 87.9 

Jordan 65.7 99.3 24.3 28.8 57.7 94.9 

Kazakhstan 81.2 74.3 85.4 11.4 91.8 85.9 

Kenya 96.5 77.7 58.7 6 56.4 89.6 

Malarwi 99.4 93.5 5.9 3.2 31.2 94.9 

Nambia 78.7 91.9 0 0 42.7 79.5 

Nepal 98.8 84.3 32 0 15.8 71.5 

Nigeria 97.8 91.6 14.4 13.4 27.4 70.4 

Philippines 64.4 95.1 12.2 47.1 31 88 

Uganda 97.4 65.9 32.1 1.6 56.2 82.1 

Vietnam 93.2 95 36.1 5.3 37.9 85.8 

Zamibia 99.5 91.7 8.2 5 25.9 90.2 

Zimbabwe 96.7 92.5 8.7 2.4 49.9 94.8 

Pooled 87.9 87.4 29.6 15.1 41.6 80.1 

a Percentage of mothers who stated that they currently breast-feed and separately had fed their infants four 

categories of liquid or solid food in the past 24 hours by country for infants age 6 to 12 months old. 

Source: Marriott et al. (2007). 

Exposure Factors Handbook Page
 

September 2011 15-33 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Page Exposure Factors Handbook 

15-34 September 2011 

Table 15-29. Population Weighted Averages of Mothers Who Reported Selected Feeding Practices 

During the Previous 24 Hours 

Feeding Practices Infant Age 

0–6 months 6–12 months 

Percentage (weighted N) 

Current Breast-Feeding 96.6 (22,781) 87.9 (18,944) 

Gave Infant: 

 Water 

 Tinned, Powdered, or Other Milk 

 Commercial Formula 

 Other Liquids 

 Any Solid Food 

45.9 (10,767) 

11.9 (2,769) 

9.0 (1,261) 

15.1 (3,531) 

21.9 (5,131) 

87.4 (18,663) 

29.6 (6,283) 

15.1 (1,911) 

41.6 (8,902) 

80.1 (17,119) 

N = Number of infants. 

Source: Marriott et al. (2007). 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breast-Fed, 

NHANES III (1988–1994) 

Non-Hispanic White Non-Hispanic Black Mexican American 

Absolute Difference (%, SE)a 

White vs. Black 

White vs. 

Mexican 

American 

Characteristic N % (SE) N % (SE) N % (SE) % (SE) % (SE) 

All Infants 1,869 60.3 2.0 1,845 25.5 1.4 2,118 54.4 1.9 34.8 (2.0)b 6.0 (2.3)a 

Infant Sex 

Male 901 60.4 2.6 913 24.4 1.6 1,033 53.8 1.8 35.9 (2.9)b 6.6 (2.8)a 

Female 968 60.3 2.3 932 26.7 1.9 1,085 54.9 2.9 33.7 (2.6)b 5.4 (3.4)c 

Infant Birth Weight (g) 

<2,500 118 40.1 5.3 221 14.9 2.6 165 34.1 3.9 25.1 (5.8)b 5.9 (6.4)c 

≥2,500 1,738 62.1 2.1 1,584 26.8 1.6 1,838 55.7 2.0 35.3 (2.1)b 6.4 (2.5)a 

Maternal Age (years) 

<20 175 33.7 4.4 380 13.1 2.1 381 43.7 3.0 20.6 (4.8)b 

–10 (5.1)c 

20–24 464 48.3 3.0 559 22.0 2.0 649 54.8 2.6 26.4 (3.7)b 

–6.4 (4.2)c 

25–29 651 65.4 2.2 504 30.6 2.5 624 56.9 3.3 34.8 (3.1)b 8.6 (4.0)a 

≥30 575 71.9 2.7 391 36.1 2.3 454 59.6 2.8 35.8 (3.4)b 12.3 (3.4)b 

Household Head Education 

<High school 313 32.3 4.0 583 14.7 2.5 1,262 51.0 2.6 17.6 (5.0)b 

–18.8 (4.8)b 

High school 623 52.6 2.8 773 21.9 2.0 479 51.4 3.4 30.7 (3.2)b 1.2 (4.1)c 

Some college 397 63.8 2.3 317 37.2 3.5 226 68.0 5.2 26.6 (3.7)b 

–4.1 (5.6)c 

College 

graduate 

505 83.0 2.4 139 54.4 4.9 74 78.3 7.4 28.6 (5.3)b 4.6 (7.6)c 

Smoking During Pregnancy 

Yes 526 39.8 3.0 403 18.0 2.1 198 31.2 3.9 21.8 (3.7)b 8.6 (4.7)c 

No 1,334 68.2 2.0 1,429 27.8 1.7 1,917 56.7 1.9 40.4 (2.1)b 11.5 (2.5)b 

Maternal Body Mass Index 

<25.0 1,331 64.9 2.0 872 26.8 2.0 961 54.1 2.5 38.0 (2.5)b 10.8 (2.7)b 

25.0–29.9 283 50.9 3.4 484 24.1 3.2 534 57.8 2.1 26.8 (4.5)b 

–6.8 (4.1)c 

≥30 204 48.6 4.8 415 24.3 2.7 359 47.1 4.4 24.3 (5.3)b 1.5 (6.1)c 

Residence 

Metropolitan 762 67.2 3.0 943 32.0 1.9 1,384 56.1 2.0 35.3 (2.6)b 11.2 (2.9)b 

Rural 1,107 54.9 3.1 902 18.3 1.9 734 51.3 3.1 36.6 (2.7)b 3.6 (4.0)c 

Region 

Northeast 317 51.6 4.6 258 34.2 4.4 12 74.1 10.4 17.3 (3.6)b 

–22.5 (14.5)c 

Midwest 556 61.7 2.3 346 26.5 2.4 170 51.5 3.7 35.2 (3.3)b 10.2 (5.0)a 

South 748 52.7 2.7 1,074 19.4 2.0 694 42.7 3.5 33.3 (2.7)b 10 (4.6)a 

West 248 82.4 3.9 167 45.1 5.1 1,242 59.1 2.2 37.3 (7.1)b 23.4 (3.3)b 

Exposure Factors Handbook Page
 

September 2011 15-35 
 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breast-Fed, 

NHANES III (1988–1994) (continued) 

Non-Hispanic White Non-Hispanic Black Mexican American 

Absolute Difference (%, SE)a 

White vs. Black 

White vs. 

Mexican 

American 

Poverty Income 

Ratio (%) 

N % (SE) N % (SE) N % (SE) % (SE) % (SE) 

<100 257 38.5 4.2 905 18.2 1.9 986 48.2 2.8 20.3 (4.4)b 

–9.6 (4.7)a 

100 to <185 388 55.7 2.6 391 26.8 2.1 490 54.1 3.4 28.9 (3.5)b 1.5 (4.2)c 

185 to <350 672 61.9 2.5 294 32.0 3.0 288 64.7 4.7 30.0 (3.7)b 2.8 (5.3)c 

≥350 444 77.0 2.5 105 58.1 5.1 74 71.9 9.0 19.0 (5.6)b 5.2 (9.0)c 

Unknown 108 44.7 7.1 150 25.5 3.9 280 59.5 2.8 19.2 (7.9)a 

–14.8 (7.9)c 

a p <0.05. b p <0.01. c No statistical difference. 

N = Number of infants. 

SE = Standard error. 

Source: Li and Grummer-Strawn (2002). 

Page Exposure Factors Handbook 

15-36 September 2011 
Exposure Factors Handbook Page
 

September 2011 15-37 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any Human Milk at 

6 Months (NHANES III, 1988–1994) 

Absolute Difference (%, SE) 

Non-Hispanic White Non-Hispanic Black Mexican American White vs. Mexican White vs. Black American 

Characteristic N % (SE) No. % (SE) N % (SE) % (SE) % (SE) 

All Infants 1,863 26.8 1.6 1,842 8.5 0.9 2,112 23.1 1.4 18.3 (1.7)a 3.7 (2.1)b 

Infant Sex 

Male 900 27.6 2.3 912 8.5 1.1 1,029 22.3 1.6 19.1 (2.6)a 5.2 (2.6)c 

Female 963 26.1 1.8 930 8.6 1.1 1,083 24.0 2.0 17.5 (2.1)c 2.1 (2.7)b 

Infant Birth Weight (g) 

<2,500 118 10.9 3.1 221 4.2 1.8 165 15.2 4.7 6.7 (3.3)c 

–4.3 (5.7)b 

≥2,500 1,733 28.3 1.8 1,581 9.0 0.9 1,832 23.1 1.7 19.3 (1.8)a 5.2 (2.3)c 

Maternal Age (years) 

<20 174 10.2 2.9 380 4.7 1.4 380 11.6 1.7 5.5 (3.0)b 

–1.3 (3.8)b 

20–24 461 13.4 2.4 559 7.5 1.1 646 23.8 2.4 5.9 (2.5)c 

–10.4 (3.3)a 

25–29 651 29.3 2.6 503 10.9 2.0 624 24.6 2.6 18.4 (3.5)a 4.8 (3.6)b 

≥30 573 39.0 2.6 389 10.7 1.7 452 30.0 2.8 28.4 (3.3)a 9.0 (3.6)c 

Household Head Education 

<High school 312 14.6 3.8 582 4.4 1.2 1,258 20.7 1.4 10.2 (4.5)c 

–6.2 (4.1)b 

High school 622 19.9 1.7 771 5.0 1.0 478 22.4 2.5 14.9 (2.0)a 2.5 (3.1)b 

Some college 396 26.8 2.4 317 16.6 2.5 225 28.4 5.3 10.2 (3.5)a 

–1.6 (6.1)b 

College 

graduate 

502 42.2 2.9 139 21.1 3.2 74 45.5 7.3 21.1 (5.2)a 3.4 (7.6)b 

Smoking During Pregnancy 

Yes 524 11.3 1.5 402 4.3 1.1 198 9.3 2.2 7.0 (1.9)a 2.1 (2.7)b 

No 1,331 32.7 2.1 1,427 9.8 1.1 1,911 24.5 1.5 22.9 (2.3)a 8.1 (2.6)a 

Maternal Body Mass Index 

<25.0 1,326 29.6 1.8 871 8.9 1.2 959 21.9 2.1 20.7 (2.1)a 7.8 (2.7)a 

25.0–29.9 282 19.0 2.4 482 8.2 1.9 534 26.4 1.9 10.8 (3.2)a 7.4 (3.0)c 

≥30 204 20.4 4.1 415 7.3 1.6 357 17.2 3.0 13.1 (4.4)a 3.3 (5.2)b 

Residence 

Metropolitan 760 29.7 2.5 941 11.8 1.3 1,378 23.5 1.7 17.9 (2.4)a 6.1 (3.1)b 

Rural 1,103 24.6 2.4 901 4.9 0.9 734 22.5 2.8 19.7 (2.2)a 2.2 (3.4)b 

Region 

Northeast 316 21.0 2.2 258 9.7 1.8 12 43.6 16.0 11.3 (1.8)a 

–22.6 (16.5)b 

Midwest 553 28.8 2.1 344 9.8 2.4 170 18.2 4.7 19.0 (3.7)a 10.6 (6.2)b 

South 746 20.1 2.8 1,073 5.9 1.0 693 17.2 2.8 14.3 (2.8)a 2.9 (4.2)b 

West 248 42.7 4.7 167 19.3 3.3 1,237 25.9 1.4 23.4 (5.3)a 16.8 (5.1)a 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Page Exposure Factors Handbook 

15-38 September 2011 

Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any Human Milk at 

6 Months (NHANES III, 1988–1994) (continued) 

Absolute Difference (%,SE) 

Non-Hispanic White Non-Hispanic Black Mexican American White vs. Mexican White vs. Black American 

Poverty Income 

Ratio (%) 

N % (SE) No. % (SE) N % (SE) % (SE) % (SE) 

100 to <185 

185 to <350 

≥350

Unknown 

387 

670 

443 

108 

23.5 

30.4 

33.0 

13.3 

2.9 

2.7 

3.0 

3.8 

390 

293 

105 

149 

9.9 

10.0 

15.2 

6.4 

1.8 

2.4 

2.8 

2.9 

486 

287 

74 

280 

23.4 

27.6 

32.3 

26.7 

2.7 

4.4 

9.0 

4.5 

13.6 

20.4 

17.8 

7.0 

(3.9)a 

(4.0)a 

(4.2)a 

(5.3)b 

0 

2.9 

0.7 

–13.4 

(4.1)b 

(4.8)b 

(9.5)b 

(6.6)c 

a 

b 

c 

N 

SE 

Source: 

p < 0.01. 

No statistical difference. 

p < 0.05. 

= Number of individuals. 

= Standard error. 

Li and Grummer-Strawn (2002). 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Exposure Factors Handbook Page
 

September 2011 15-39 

Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breast-Fed at 4 Months 

(NHANES III, 1991–1994) 

Absolute Difference (%,SE) 

Non-Hispanic White Non-Hispanic Black Mexican American White vs. 

White vs. Black Mexican 

American 

Characteristic N % (SE) N % (SE) N % (SE) % (SE) % (SE) 

All Infants 824 22.6 1.7 906 8.5 1.5 957 20.4 1.4 14.1 (2.2)a 2.3 (1.6)b 

Infant Sex 

Male 

Female 

394 

430 

22.3 

23.0 

1.9 

2.2 

454 

452 

7.0 

10.0 

1.6 

2.2 

498 

459 

20.7 

20.0 

1.5 

1.8 

15.3 

12.9 

(2.6)a 

(3.0)a 

1.5 

3.0 

(1.8)b 

(2.1)b 

Infant Birth Weight (g) 

<2,500 

≥2,500 

50 

774 

15.2 

23.1 

7.1 

1.8 

118 

786 

7.0 

8.8 

2.3 

1.6 

66 

880 

5.6 

21.6 

1.8 

1.4 

8.2 

14.4 

(8.1)b 

(2.2)a 

9.5 

1.5 

(6.9)b 

(1.6)b 

Maternal Age (years) 

<20 76 6.6 3.2 172 6.4 2.1 170 12.1 2.5 0.2 (3.7)b 

–5.6 (3.8)b 

20–24 205 11.4 2.2 273 7.4 2.4 319 21.0 2.3 4.0 (2.7)b 

–9.6 (3.2)a 

25–29 271 21.6 2.3 254 8.6 2.5 256 22.1 2.5 13.0 (3.2)a 

–0.5 (3.2)b 

≥30 270 34.8 2.7 201 11.9 2.6 210 23.6 3.1 22.9 (4.2)a 11.1 (3.7)a 

Household Head Education 

<High school 146 9.5 3.5 256 2.0 0.7 563 19.7 1.8 7.5 (3.6)c 

–10.2 (4.0)c 

High school 277 14.5 2.7 406 7.1 2.1 222 18.8 3.6 7.4 (3.2)c 

–4.3 (4.7)b 

Some college 

College graduate 

175 

219 

30.8 

34.1 

3.8 

3.9 

141 

92 

17.4 

17.4 

3.0 

4.7 

120 

37 

21.0 

31.5 

3.9 

4.5 

13.4 

16.7 

(4.7)a 

(6.9)c 

9.8 

2.6 

(6.1)b 

(6.3)b 

Smoking During Pregnancy 

Yes 224 10.0 2.8 168 5.4 2.2 64 3.2 1.8 4.6 (3.7)b 6.8 (3.4)b 

No 596 27.2 2.1 730 9.4 1.9 892 21.7 1.5 17.8 (2.8)a 5.6 (2.0)c 

Maternal Body Mass Index 

<25.0 

25.0–29.9 

597 

117 

24.8 

19.7 

2.1 

4.3 

407 

230 

8.0 

8.6 

1.9 

1.9 

417 

261 

19.4 

23.1 

1.9 

3.4 

16.8 

11.1 

(3.0)a 

(4.6)c 

5.4 

–3.4 

(2.3)c 

(4.9)b 

≥30 91 15.4 3.8 230 9.0 2.9 184 15.9 2.3 6.4 (5.2)b 

–0.5 (4.6)b 

Residence 

Metropolitan 

Rural 

312 

512 

24.4 

21.3 

3 

1.8 

535 

371 

11.0 

4.2 

2.0 

1.3 

608 

349 

19.6 

22.3 

1.6 

3.3 

13.4 

17.1 

(3.5)a 

(1.8)a 

4.8 

–1.1 

(2.8)b 

(3.0)b 

Region 

Northeast 

Midwest 

South 

138 

231 

378 

20.0 

26.5 

14.1 

1.4 

3.2 

2.8 

131 

143 

574 

11.1 

12.6 

5.9 

2.9 

5.6 

1.4 

10 

98 

383 

9.4 

19.2 

15.9 

9.5 

4.1 

3.1 

8.8 

13.9 

8.2 

(2.2)a 

(7.6)b 

(1.9)a 

10.6 

7.4 

–1.8 

(8.7)b 

(3.7)b 

(3.7)b 

West 77 34.7 2.7 58 12.5 5.0 466 23.0 1.3 22.2 (5.4)a 11.7 (2.5) 
 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Page Exposure Factors Handbook 

15-40 September 2011 

Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breast-Fed at 4 Months 

(NHANES III, 1991–1994) (continued) 

Absolute Difference (%, SE) 

Non-Hispanic White Non-Hispanic Black Mexican American White vs. 

White vs. Black Mexican 

American 

Poverty Income 

Ratio (%) 

N % (SE) N % (SE) N % (SE) % (SE) % (SE) 

<100 

100 to <185 

185 to <350 

≥350

Unknown 

116 

166 

274 

235 

33 

13.1 

18.9 

25.1 

27.4 

16.5 

3.3 

3.2 

3.2 

4.1 

7.6 

448 

197 

145 

57 

59 

5.7 

10.6 

12.9 

12.8 

7.3 

1.6 

2.8 

4.3 

3.5 

3.7 

471 

234 

132 

37 

83 

18.4 

21.9 

26.4 

17.0 

16.1 

1.8 

4.1 

4.2 

5.0 

5.1 

7.4 

8.3 

12.2 

14.6 

9.2 

(3.5)c 

(3.3)c 

(5.0)c 

(5.0)a 

(8.6)b 

–5.3 

–3 

–1.3 

10.4 

0.4 

(3.1)b 

(6.1)b 

(4.1)b 

(5.2)b 

(9.5)b 

a 

b 

c 

N 

SE 

Source: 

p < 0.05. 

p < 0.01. 

No statistical difference. 

= Number of individuals. 

= Standard error. 

Li and Grummer-Strawn (2002). 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Exposure Factors Handbook Page
 

September 2011 15-41 

 

 

 

Table 15-33. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital 

and Infants at 5 or 6 Months of Age in the United States in 1989 and 1995, 

by Ethnic Background and Selected Demographic Variables 

Characteristic 

Percentage of Mothers Breast-Feeding 

In Hospital At 6 Months 

1989 1995 Changea 1989 1995 Changea 

All Infants 

White 

Black 

Hispanic 

52.2 

58.5 

23.0 

48.4 

59.7 

64.3 

37.0 

61.0 

14.4 

9.9 

60.9 

26.0 

18.1 

21.0 

6.4 

13.9 

21.6 

24.1 

11.2 

19.6 

19.3 

14.8 

75.0 

41.0 

Maternal Age (years) 

<20 

20 to 24 

25 to 29 

30 to 34 

35+ 

30.2 

45.2 

58.8 

65.5 

66.5 

42.8 

52.6 

63.1 

68.1 

70.0 

41.7 

16.4 

7.3 

4.0 

5.3 

5.6 

11.5 

21.1 

29.3 

34.0 

9.1 

14.6 

22.9 

29.0 

33.8 

62.5 

27.0 

8.5 

(1.0)b 

(0.6)b 

Total Family Income 

<$10,000 

$10,000 to $14,999 

$15,000 to $24,999 

≥25,000

31.8 

47.1 

54.7 

66.3 

41.8 

51.7 

58.8 

70.7 

31.4 

9.8 

7.5 

6.6 

8.2 

13.9 

18.9 

25.5 

11.4 

15.4 

19.8 

28.5 

39.0 

10.8 

4.8 

11.8 

Maternal Education 

Grade School 

High School 

College 

31.7 

42.5 

70.7 

43.8 

49.7 

74.4 

38.2 

16.9 

5.2 

11.5 

12.4 

28.8 

17.1 

15.0 

31.2 

48.7 

21.0 

8.3 

Maternal Employment 

Employed Full Time 

Employed Part Time 

Not Employed 

50.8 

59.4 

51.0 

60.7 

63.5 

58.0 

19.5 

6.9 

13.7 

8.9 

21.1 

21.6 

14.3 

23.4 

25.0 

60.7 

10.9 

15.7 

Birth Weight 

Low (≤2,500 g)

Normal 

36.2 

53.5 

47.7 

60.5 

31.8 

13.1 

9.8 

18.8 

12.6 

22.3 

28.6 

18.6 

Parity 

Primiparous 

Multiparous 

52.6 

51.7 

61.6 

57.8 

17.1 

11.8 

15.1 

21.1 

19.5 

23.6 

29.1 

11.8 

WIC Participationc 

Participant 

Non-participant 

34.2 

62.9 

46.6 

71.0 

36.3 

12.9 

8.4 

23.8 

12.7 

29.2 

51.2 

22.7 

U.S. Census Region 

New England 

Middle Atlantic 

East North Central 

West North Central 

South Atlantic 

East South Central 

West South Central 

Mountain 

Pacific 

52.2 

47.4 

47.6 

55.9 

43.8 

37.9 

46.0 

70.2 

70.3 

61.2 

53.8 

54.6 

61.9 

54.8 

44.1 

54.4 

75.1 

75.1 

17.2 

13.5 

14.7 

10.7 

25.1 

16.4 

18.3 

7.0 

6.8 

18.6 

16.8 

16.7 

18.4 

13.7 

11.5 

13.6 

28.3 

26.6 

22.2 

19.6 

18.9 

21.4 

18.6 

13.0 

17.0 

30.3 

30.9 

19.4 

16.7 

13.2 

16.3 

35.8 

13.0 

25.0 

7.1 

16.2 

a The percent change was calculated using the following formula: % breast-fed in 1984 – % breast-fed in 1989 ÷ % breast-fed in 1984. b Figures in parentheses indicate a decrease in the rate of breast-feeding from 1989 to 1995. c WIC indicates Women, Infants, and Children supplemental food program. 

Source: Ryan (1997). 
Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Page Exposure Factors Handbook 

15-42 September 2011 

Table 15-34. Percentage of Mothers Breast-Feeding Newborn Infants in the Hospital
 

and Infants at 6 and 12 Months of Age in the United States in 2003, 
 

by Ethnic Background and Selected Demographic Variables
 

Characteristic Percentage of Mothers Breast-Feeding 

In Hospital At 6 Months At 12 Months 

All Infants 

White 

Black 

Hispanic 

Asian 

Maternal Age (years)
 

<20 

20 to 24 

25 to 29 

30 to 34 

35+ 

Maternal Education
 

Any Grade School 

Any High School 

No College 

College 

Maternal Employment
 

Employed Full Time 

Employed Part Time 

Total Employed 

Not Employed 

Low Birth Weight <5 lbs 9oz 

Parity
 

Primiparous 

Multiparous 

WIC Participationa
 

Participant 

Non-participant 

U.S. Census Region
 

New England 

Middle Atlantic 

East North Central 

West North Central 

South Atlantic 

East South Central 

West South Central 

Mountain 

Pacific 

44 

53 

26 

33 

39 

28

40 

48 

50 

47

26 

35 

35 

55 

44 

49 

45 

43 

27 

48 

43 

32 

55 

52 

36 

44 

55 

42 

37 

37 

53 

50 

18 

20 

10 

15 

23 

9 

13 

20 

23 

23 

13 

12 

12 

24 

11 

19 

14 

21 

10 

17 

19 

11 

25 

22 

17 

17 

18 

16 

11 

15 

23 

24 

10
 

12
 

5
 

12
 

12
 

4
 

8
 

10
 

14
 

14
 

17
 

8
 

8
 

14
 

6
 

11
 

8
 

13
 

6
 

10
 

11
 

7
 

14
 

11
 

9
 

9
 

9
 

10
 

7
 

8
 

16
 

15
 

a WIC indicates Women, Infants, and Children supplemental food program. 

Source: Abbott Labs (2003). 
 

 

Exposure Factors Handbook 

Chapter 15—Human Milk Intake 

Table 15-35. Number of Meals per Day 

Age (months) 

Bottle-Fed Infants 

(meals/day)a 

Breast-Fed 

(meals/day)a 

1 5.4 (4–7) 

2 4.8 (4–6) 

3 4.7 (3–6) 

5.8 (5–7) 

5.3 (5–7) 

5.1 (4–8) 

a Data expressed as mean with range in parentheses. 

Source: Hofvander et al. (1982). 

Table 15-36. Comparison of Breast-Feeding Patterns Between Age and Groups (Mean ± SD) 

Breast-Feeding Episodes per Day 5.8 ± 2.6 6.8 ± 2.4 2.5 ± 2.0 

Total Time Breast-Feeding (minute/day) 65.2 ± 44.0 102.2 ± 51.4 31.2 ± 24.6 

Length of Breast-Feeding (minute/episode) 10.8 ± 6.1 14.2 ± 6.1 11.6 ± 5.6 

SD = Standard deviation. 

Source: Buckley (2001). 

Exposure Factors Handbook Page
 

September 2011 15-43 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

16. ACTIVITY FACTORS 

16.1. INTRODUCTION 

Individual or group activities are important 

determinants of potential exposure. Toxic chemicals 

introduced into the environment may not cause harm 

to an individual until an activity is performed that 

brings the individual into contact with those 

contaminants. An activity or time spent in a given 

activity will vary among individuals depending on 

culture, ethnicity, hobbies, location, sex, age, 

socioeconomic characteristics, and personal 

preferences. However, limited information is 

available regarding ethnic, cultural, and 

socioeconomic differences in individuals’ choice of 

activities or time spent in a given activity. Children 

are of special concern because certain activities and 

behaviors specific to children place them at a higher 

risk of exposure to certain environmental agents and 

expose them to higher levels of many chemicals 

(Chance and Harmsen, 1998). Trends associated with 

activity patterns include increases in the proportion of 

the population engaging in sedentary activities and 

decreases in physical activity in the home and related 

to work, including walking to work, as there has been 

a strong trend toward Americans living in the suburbs 

(Brownson et al., 2005). Recent trends in 

occupational mobility include the facts that average 

tenure increases directly with age, and that a large 

proportion of American workers show substantial job 

stability (U.S. Census Bureau, 2010). For population 

mobility, the U.S. Census Bureau reported that the 

national residential move rate increased to 12.5% in 

2009 following a record low of 11.9% in 2008 (U.S. 

Census Bureau, 2010). 

In calculating exposure, a person's average daily 

dose is determined from a combination of variables 

including the pollutant concentration, exposure 

duration, and frequency of exposure (see Chapter 1). 

These variables can be dependent on human activity 

patterns and time spent at each activity and/or 

location. 

Time activity data are generally obtained using 

recall questionnaires and diaries to record the 

person’s activities and microenvironments. Other 

methods include the use of videotaping and global 

positioning system technology to provide information 

on individuals’ locations (Elgethun et al., 2003; 

Phillips et al., 2001). 

Obtaining accurate information on time and 

activities can be challenging. This is especially true 

for children (Cohen Hubal et al., 2000). Children 

engage in more contact activities than adults; 

therefore, a much wider distribution of activities need 

to be considered when assessing children’s exposure 

(Cohen Hubal et al., 2000). Mouthing behavior, 

which includes all activities in which objects, 

including fingers, are touched by the mouth or put 

into the mouth are provided in Chapter 4. Chapter 7 

provides frequency and duration data for dermal 

(hand) contact. 

This chapter summarizes data on how much time 

individuals spend participating in various activities in 

various microenvironments and on the frequency of 

performing various activities. Information is also 

provided on occupational mobility and population 

mobility. The data in this chapter cover a wide range 

of activities and populations, arranged by age group 

when such data are available. One of the objectives 

of this handbook is to provide recommended 

exposure factor values using a consistent set of age 

groups. In this chapter, several studies are used as 

sources for activity pattern data. In some cases, the 

source data could be retrieved and analyzed using the 

standard age groupings recommended in Guidance 

for Monitoring and Assessing Childhood Exposures 

to Environmental Contaminants (U.S. EPA, 2005). In 

other cases, the original source data were not 

available, and the study results are presented here 

using the same age groups as the original study, 

whether or not they conform to the standard age 

groupings. 

The recommendations for activity factors are 

provided in the next section, along with a summary 

of the confidence ratings for these recommendations. 

The recommended values are based on key studies 

identified by U.S. Environmental Protection Agency 

(U.S. EPA) for this factor. Following the 

recommendations, key studies on activity patterns are 

summarized. Relevant data on activity patterns are 

also presented to provide the reader with added 

perspective on the current state-of-knowledge 

pertaining to activity patterns in adults and children. 

Additional information on microactivity patterns (i.e., 

hand-to-mouth, object-to-mouth, and dermal [hand] 

contact with surfaces and objects) is provided in 

Chapters 4 and 7. 

16.2. RECOMMENDATIONS 

16.2.1. Activity Patterns 

Assessors are commonly interested in 

quantitative information describing several types of 

time use data for adults and children including the 

following: time spent indoors and outdoors; time 

spent bathing, showering, and swimming; and time 

spent playing on various types of surfaces. 

Table 16-1 summarizes the recommended values for 

these factors. Note that, except for swimming, all 

activity factors are reported in units of minutes/day. 

Exposure Factors Handbook Page
 

November 2011 16-1 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-2 November 2011 

Time spent swimming is reported in units of

minutes/month. These data are based on 2 key studies 

presented in this chapter: a study of children’s

activity patterns in California (Wiley et al., 1991) and 

the National Human Activity Pattern Survey

(NHAPS) (U.S. EPA, 1996). Both mean and

95th percentile recommended values are provided. 

However, because these recommendations are based 

on short-term survey data, 95th percentile values may 

be misleading for estimating chronic (i.e., long-term) 

exposures and should be used with caution. Also, the 

upper percentile values for some activities are

truncated as a result of the maximum response

included in the survey (e.g., durations of more than 

120 minutes/day were reported as 121 minutes/day), 

and could not be further refined). Table 16-2 presents 

the confidence ratings for the recommendations. 

The recommendations for total time spent

indoors and the total time spent outdoors are based on 

the U.S. EPA re-analysis of the source data from 

Wiley et al. (1991) for children <1 year of age and 

U.S. EPA (1996) for childhood age groups >1 year of 

age. Although Wiley et al. (1991) is a study of 

California children and the sample size was very 

small for infants, it provides data for children’s 

activities for the younger age groups. Data from 

U.S. EPA (1996) are representative of the U.S.

general population. In some cases, however, the time 

spent indoors or outdoors would be better addressed 

on a site-specific basis since the times are likely to 

vary depending on the climate, residential setting 

(i.e., rural versus urban), personal traits (e.g., health 

status), and personal habits. For children >1 year of 

age, the recommended values for time spent indoors 

at a residence, duration of showering and bathing, 

time spent swimming, and time spent playing on 

sand, gravel, grass or dirt are based on a U.S. EPA 

re-analysis of the source data from U.S. EPA (1996). 

For adults 18 years and older, the recommended 

values are taken directly from the source document 

(U.S. EPA, 1996). 

16.2.2. Occupational Mobility 

Occupational mobility may be an important

factor in determining exposure. For example, the 

duration of exposure to occupationally-related 

contaminants, such as the chemicals used in an 

industrial or laboratory setting, will be directly

associated with the period of time an individual 

spends in the occupation. 

The median occupational tenure of the working 

population (109.1 million people) ages 16 years of 

age and older in January 1987 was 7.9 years for men 

and 5.4 years for women (Carey, 1988). Since the 

occupational tenure varies significantly according to 

age and sex, the recommended values are given by 5­

year age groups separately for males and females in 

Table 16-3. Section 16.4 provides occupational 

tenure for males and females combined. Part-time 

employment, race and the position held are important 

to consider in determining occupational tenure. These 

data are also presented in Section 16.4. Table 16-3 

also presents recommendations for occupational 

mobility rate, by age. This rate is the percentage of 

persons employed in an occupation who had 

voluntarily entered it from another occupation. The 

overall percent was 5.3 (Carey, 1990). The ratings 

indicating confidence in the occupational mobility 

recommendations are presented in Table 16-4. It 

should be noted that the recommended values are not 

for use in evaluating job tenure. These data can be 

used for determining time spent in an occupation and 

not for time spent at a specific job site. 

16.2.3. Population Mobility 

An assessment of population mobility can assist 

in determining the length of time a household is 

exposed in a particular location. For example, the 

duration of exposure to site-specific contamination, 

such as a polluted stream from which a family fishes 

or contaminated soil on which children play or 

vegetables are grown, will be directly related to the 

period of time residents live near the contaminated 

site. 

There are two key studies from which the 

population mobility recommendations were derived: 

the U.S. Census Bureau American Housing Survey, 

(U.S. Census Bureau, 2008a) and Johnson and Capel 

(1992). The U.S. Bureau of Census (2008a) provides 

data on current residence time and Johnson and Capel 

(1992) provide data on residential occupancy period. 

Table 16-5 presents the recommendations for 

population mobility. Table 16-6 presents the 

confidence ratings for these recommendations. 

The 50th and 90th percentiles for current 

residence time from the U.S. Census Bureau (2008a) 

are 8 years and 32 years, respectively. The mean and 

90th percentile for residential occupancy period from 

Johnson and Capel (1992) are 12 years and 26 years, 

respectively. 
 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-1. Recommended Values for Activity Patternsa 

Age Group Mean 95th Percentile Source 

Time Indoors (total) 

minutes/day 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <65 years 

≥65 years 

1,440 

1,432 

1,414 

1,301 

1,353 

1,316 

1,278 

1,244 

1,260 

1,248 

1,159 

1,142 

-

-

-

-

-

-

-

-

-

-

-

-

U.S. EPA analysis of source data from Wiley et al. (1991) for 

age groups from birth to <12 months. Average for boys and 

girls, whole population. See Table 16-14. 

U.S. EPA re-analysis of source data from U.S. EPA (1996) for 

age groups from 1 to <21 years, whole population. See Table 

16-21. 

Adults, ≥18 years (U.S. EPA, 1996). Total minutes/24 hours 

(1,440) minus time outdoors, doersb only. See Table 16-22. 

Time Outdoors (total) 

minutes/day 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <65 years 

≥65 years 

0 

8 

26 

139 

36 

76 

107 

132 

100 

102 

281 

298 

-

-

-

-

-

-

-

-

-

-

-

-

U.S. EPA analysis of source data from Wiley et al. (1991) for 

age groups from birth to <12 months. Average for boys and 

girls, whole population. See Table 16-14. 

U.S. EPA re-analysis of source data from U.S. EPA (1996) for 

age groups from 1 to <21 years, whole population. See Table 

16-21. 

Adults, ≥18 years (U.S. EPA, 1996). Sum of minutes spent 

outdoors away from the residence and minutes spent outdoors 

at the residence. Doersb only. See Table 16-22. 

Time Indoors (at residence) 

minutes/day 

Birth to <1year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <65 years 

≥65 years 

1,108 

1,065 

979 

957 

893 

889 

833 

948 

1,175 

1,440 

1,440 

1,296 

1,355 

1,275 

1,315 

1,288 

1,428 

1,440 

Children, Birth to <21 years: U.S. EPA re-analysis of source 

data from U.S. EPA (1996). Doersb only. See Table 16-15. 

Adults, ≥18 years (U.S. EPA, 1996). Doersb only. See 

Table 16-16. 

Showering 

minutes/day 

Birth to <1year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

15 

20 

22 

17 

18 

18 

20 

-

-

44 

34 

41 

40 

45 

U.S. EPA re-analysis of source data from 

U.S. EPA (1996). Doersb only. See Table 16-29. 

Exposure Factors Handbook Page
 

November 2011 16-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-1. Recommended Values for Activity Patterns (continued) 

Age Group Mean 95th Percentile Source 

Bathing 

minutes/day 

Birth to <1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

19 

23 

23 

24 

24 

25 

33 

30 

32 

45 

60 

46 

43 

60 

U.S. EPA re-analysis of source data from 

U.S. EPA (1996). Doersb only. See Table 16-29. 

Bathing/Showering 

minutes/day 

18 to <65 years 

≥65 years 

17 

17 

-

- U.S. EPA (1996). Doersb only. See Table 16-30. 

Swimming 

minutes/month 

Birth to <1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <65 years 

≥65 years 

96 

105 

116 

137 

151 

139 

145 

45c 

40c 

-

-

181 

181 

181 

181 

181 

181 

181 

Children, Birth to <21 years: U.S. EPA re-analysis of source 

data from U.S. EPA (1996). Doersb only. See Table 16-40. 

Adults, ≥18 years (U.S. EPA, 1996). Doersb only. See 

Table 16-42. 

Playing on Sand/Gravel 

minutes/day 

Birth to <1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <65 years 

≥65 years 

18 

43 

53 

60 

67 

67 

83 

0c 

0c 

-

121 

121 

121 

121 

121 

-

121 

-

Children, <21 years: U.S. EPA re-analysis of source data from 

U.S. EPA (1996). Doersb only. See Table 16-43. 

Adults, ≥18 years (U.S. EPA, 1996). Doersb only. See 

Table 16-44. 

Playing on Grass 

minutes/day 

Birth to <1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <65 years 

≥65 years 

52 

68 

62 

79 

73 

75 

60 

60c 

121c 

-

121 

121 

121 

121 

121 

-

121 

-

Children, <21 years: U.S. EPA re-analysis of source data from 

U.S. EPA (1996). Doersb only. See Table 16-43. 

Adults, ≥18 years (U.S. EPA, 1996). Doersb only. See 

Table 16-44. 

Page Exposure Factors Handbook 

16-4 November 2011 
c 

Table 16-1. Recommended Values for Activity Patterns (continued) 

Age Group Mean 95th Percentile Source 

Playing on Dirt 

minutes/day 

Birth to <1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to <65 years 

≥65 years 

33 

56 

47 

63 

63 

49 

30 

0c 

0c 

-

121 

121 

121 

121 

120 

-

120 

-

Children, <21 years: U.S. EPA re-analysis of source data from 

U.S. EPA (1996). Doers

b only. See Table 16-43. 

Adults, ≥18 years (U.S. EPA, 1996). Doers

b only. See 

Table 16-44. 

- Percentiles were not calculated for sample sizes less than 10 or in cases where the mean was calculated by summing 

the means from multiple locations or activities. a	 These activities are averaged over seasons. b	 Doers are those respondents who engaged or participated in the activity. 

Median value, mean not available in U.S. EPA (1996). 

Note: All activities are reported in units of minutes/day, except swimming, which is reported in units of minutes/month. 

There are 1,440 minutes in a day. Time indoors and outdoors may not add up to 1,440 minutes due to activities that 

could not be classified as either indoors or outdoors. 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-5 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-2. Confidence in Recommendations for Activity Patterns 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodologies and data analyses were adequate. For the 

reanalysis of U.S. EPA (1996) study data, responses were weighted; 

however, adult data were not reanalyzed. The California children's 

activity pattern survey design (Wiley et al., 1991) and NHAPS (U.S. 

EPA, 1996) consisted of large overall sample sizes that varied with 

age. Data were collected via questionnaires and interviews. 

Measurement or recording error may have occurred since the diaries 

were based on 24 hour recall. The sample sizes for some age groups 

were small for some activity factors. The upper ends of the 

distributions were truncated for some factors. The data were based on 

short-term data. 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The key studies focused on activities of children and adults. 

U.S. EPA (1996) was a nationally representative survey of the U.S. 

population and the reanalysis was weighted; the Wiley et al. (1991) 

survey was conducted in California and it was not representative of 

the U.S. population. 

The Wiley et al. (1991) study was conducted between April 1989 and 

February 1990; the U.S. EPA (1996) study was conducted between 

October 1992 and September 1994. 

Data were collected for a 24-hour period. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The original studies are widely available to the public; U.S. EPA 

analysis of the original raw data from U.S. EPA (1996) is available 

upon request. 

The methodologies were clearly presented; enough information was 

included to reproduce the results. 

Quality assurance methods were not well described in study reports. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Variability was characterized across various age categories of 

children and adults. 

The studies were based on short term recall data, and the upper ends 

of the distributions were truncated. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The original studies received a high level of peer review. The 

re-analysis of the U.S. EPA (1996) data to conform to the 

standardized age categories was not peer-reviewed. 

There were 2 key studies. 

Medium 

Overall Rating Medium for 

the mean; low 

for upper 

percentile 

Page Exposure Factors Handbook 

16-6 November 2011 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-3. Recommended Values for Occupational Mobility 

Age Group 

Median Tenure 

(years) 

Men 

Median Tenure 

(years) 

Women Source 

All ages, ≥16 years 

16 to 24 years 

25 to 29 years 

30 to 34 years 

35 to 39 years 

40 to 44 years 

45 to 49 years 

50 to 54 years 

55 to 59 years 

60 to 64 years 

65 to 69 years 

≥70 years 

7.9 

2.0 

4.6 

7.6 

10.4 

13.8 

17.5 

20.0 

21.9 

23.9 

26.9 

30.5 

5.4 

1.9 

4.1 

6.0 

7.0 

8.0 

10.0 

10.8 

12.4 

14.5 

15.6 

18.8 

(Carey, 1988). See Table 16-103 

Age Group 

Occupational Mobility Ratea 

(percent) Source 

16 to 24 years 

25 to 34 years 

35 to 44 years 

45 to 54 years 

55 to 64 years 

≥64 years 

Total, ≥16 years 

12.7 

6.6 

4.0 

1.9 

1.0 

0.3 

5.3 

(Carey, 1990). See Table 16-107 

a Occupational mobility rate = percentage of persons employed in an occupation who had voluntarily entered it from another occupation. 

Exposure Factors Handbook Page
 

November 2011 16-7 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-4. Confidence in Recommendations for Occupational Mobility 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

Both studies are based on the U.S. Census Bureau’s Current 

Population Survey which uses valid methodologies and 

approaches and is representative of the U.S. population with 

sample sizes of approximately 50,000 a month. Both studies 

are secondary analyses based on supplemental data to the 

January, 1987, Current Population Survey (a U.S. Census 

publication). 

Much of the original study data is not available. Only median 

values are reported. There is minimal concern about sampling 

and non-sampling error and non-response bias as in all surveys 

based on statistical samples. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

Occupational tenure was the focus of both key studies. 

The data are statistically representative of the U.S. population. 

The data were collected over 20 years ago in 1986 and 1987. It 

is questionable whether the results would be the same if current 

data were analyzed based on changes in the economy that have 

occurred since the study was conducted. 

Data were collected in 1986–1987. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The studies are widely available to the public. The Current 

Population Survey January, 1987: Occupational Mobility and 

Job Tenure data are available from the U.S. Census Bureau. 

Results can be reproduced and methodology can be followed 

and evaluated. 

Quality assurance methods were not well described. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

The study provided averages according to sex, race, and 

education; age averages and percentiles were provided. 

The studies are based on recall data. 

High 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The studies received a high level of peer review. 

There are 2 key studies based on the same data source. 

Medium 

Overall Rating Medium 

Table 16-5. Recommended Values for Population Mobility 

Mean 

95th 

Percentile Source 

Residential Occupancy Period 12 years 33 years (Johnson and Capel, 1992). 

See Table 16-108. 

Current Residence Time 13 years 46 years (U.S. Census Bureau, 2008a). See 

Table 16-111. 

Page Exposure Factors Handbook 

16-8 November 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-6. Confidence in Recommendations for Population Mobility 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

Both key studies are based on U.S. Census Bureau studies 

which used valid data collection methodologies and approaches 

and are representative of the U.S. population. 

Data do not account for each member of the household; values 

are more realistic estimates for the individual’s total residence 

time than the average time a household has been living at its 

current residence. The moving process was modeled in 

Johnson and Capel (1992) .For the mean and percentile 

calculations of U.S. Census Bureau (2008a) data, an even 

distribution was assumed within different ranges which may 

bias the statistics. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The Census data provided length of time at current residence. 

The other study used modeling to estimate total time. 

The sample surveyed was statistically representative of the 

U.S. population. 

The data were collected in 2007 and 1985–1987, and reported 

in 2008 and 1992, respectively. 

Data were collected throughout the calendar year. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The studies are widely available to the public. 

Results can be reproduced or methodology can be followed and 

evaluated. 

Quality assurance is discussed in the documentation on the 

U.S. Census Bureau studies. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

The study provided data by age and sex. Variability across 

several geographic regions was noted. Type of ownership was 

also addressed. 

The U.S. Census Bureau data was truncated at 65 years. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The studies received high levels of peer review and appear in 

publications. 

The 2 studies produced similar results. 

High 

Overall Rating Medium 

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Exposure Factors Handbook 

Chapter 16—Activity Factors
 

16.3. ACTIVITY PATTERNS 

16.3.1. Key Activity Pattern Studies 

16.3.1.1.	 Wiley et al. (1991)—Study of Children’s 

Activity Patterns 

The California Study of Children's Activity 

Patterns survey (Wiley et al., 1991) provided 

estimates of the time children spent in various 

activities and locations (microenvironments) on a 

typical day. The sample population consisted of 

1,200 children, under 12 years of age, selected from 

English-speaking households using Random Digit 

Dial (RDD) methods. This represented a survey 

response rate of 77.9%. One child was selected from 

each household. If the selected child was less than 

9 years old, the adult in the household who spent the 

most time with the child responded. However, if the 

selected child was between 9 and 11 years old, that 

child responded. The population was also stratified to 

provide representative estimates for major regions of 

the state. The survey questionnaire included a time 

diary which provided information on the children's 

activity and location patterns based on a 24-hour 

recall period. In addition, the survey questionnaire 

included questions about potential exposure to 

sources of indoor air pollution (e.g., presence of 

smokers) on the diary day, and the sociodemographic characteristics of children and adult 

respondents. The questionnaires and the time diaries 

were administered via a computer-assisted telephone 

interviewing (CATI) technology (Wiley et al., 1991). 

The telephone interviews were conducted during 

April 1989 to February 1990 over 4 seasons: spring 

(April to June 1989), summer (July to September 

1989), fall (October to December 1989), and winter 

(January to February 1990). 

The data obtained from the survey interviews 

resulted in 10 major activity categories, 113 detailed 

activity codes, 6 major categories of locations, and 

63 detailed location codes. The time respondents 

under 12 years of age spent in the 10 activity 

categories (plus a “don’t know” or non-coded activity 

category) are presented in Table 16-7. For each of the 

10 activity categories, this table presents the mean 

duration for all survey participants, the percentage of 

respondents who reported participating in the activity 

(i.e., percent doers), and the mean, median, and 

maximum duration for only those survey respondents 

who engaged in the activity (i.e., doers). It also 

includes the detailed activity with the highest mean 

duration of time for each activity category. The 

activity category with the highest time expenditure 

was personal needs and care, with a mean of 

794 minutes/day (13.2 hours/day). Night sleep was 

the detailed activity that had the highest mean 

duration in that activity category. The activity 

category “don't know” had a mean duration of about 

2 minutes/day and only 4% of the respondents 

reported missing activity time. 

Table 16-8 presents the mean time spent in the 

10 activity categories by age and sex. Because the 

original source data were available, U.S. EPA 

re-analyzed the data according to the standardized 

age categories used in this handbook. Differences 

between activity patterns in boys and girls tended to 

be small. Table 16-9 presents the mean time spent in 

the 10 activity categories grouped by season and 

geographic region in the state of California. There 

were seasonal differences for 5 activity categories: 

personal needs and care, education, 

entertainment/social, recreation, and 

communication/passive leisure. Time expenditure 

differences in various regions of the state were 

minimal for childcare, work-related, goods/services, 

personal needs and care, education, 

entertainment/social, and recreation. 

Table 16-10 presents the distribution of time 

across 6 location categories. The mean duration for 

all survey participants, the percent of respondents 

engaging in the activity (i.e., percent doers); the 

mean, median, and maximum duration for doers only; 

and the detailed locations with the highest average 

time expenditure are shown. For all survey 

respondents, the largest mean amount of time spent 

was at home (1,078 minutes/day); 99% of 

respondents spent time at home (mean of 

1,086 minutes/day for these individuals only). 

Table 16-11 and Table 16-12 show the average time 

spent in the 6 locations grouped by age and sex, and 

season and region, respectively. Again, because the 

original source data were available, the age 

categories used by Wiley et al. (1991) have been 

replaced in Table 16-11 by the standardized age 

categories used in this handbook. There were 

relatively large differences among the age groups in 

time expenditure for educational settings (see 

Table 16-11). There were small differences in time 

expenditure at the 6 locations by region, but time 

spent in school decreased in the summer months 

compared with other seasons (see Table 16-12). 

Table 16-13 shows the average time children 

spent in proximity to gasoline fumes and gas oven 

fumes. In general, the sampled children spent more 

time closer to gasoline fumes than to gas oven fumes. 

The age categories in Table 16-13 have been 

modified to conform to the standardized categories 

used in this handbook. 

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The U.S. EPA estimated the total time indoors 

and outdoors using the data from the Wiley et al. 

(1991) study. Activities performed indoors were 

assumed to include household work, child care, 

personal needs and care, education, and 

communication/passive leisure. The average times 

spent in these indoor activities and half the time spent 

in each activity which could have occurred either 

indoors or outdoors (i.e., work-related, 

goods/services, organizational activities, 

entertainment/social, don’t know/not coded) were 

summed. Table 16-14 summarizes the results of this 

analysis using the standard age groups. 

A limitation of this study is that the sampling 

population was restricted to only English-speaking 

households; therefore, the data obtained do not 

represent the diverse population group present in 

California. Another limitation is that time use values 

obtained from this survey were based on short-term 

recall (24-hour) data; therefore, the data set obtained 

may be biased. Other limitations are as follows: the 

survey was conducted in California and is not 

representative of the national population, and the 

significance of the observed differences in the data 

obtained (i.e., sex, age, seasons, and regions) were 

not tested statistically. An advantage of this study is 

that time expenditure in various activities and 

locations were presented for children grouped by age, 

sex, and season. Also, potential exposures of 

respondents to pollutants were explored in the 

survey. Another advantage is the use of the CATI 

program in obtaining time diaries, which allows 

automatic coding of activities and locations onto a 

computer tape, and allows activities forgotten by 

respondents to be inserted into their appropriate 

position during interviewing. 

16.3.1.2.	 U.S. EPA (1996) —Descriptive Statistics 

Tables From a Detailed Analysis of the 

National Human Activity Pattern Survey 

(NHAPS) Data 

U.S. EPA (1996) analyzed data collected by the 

National Human Activity Pattern Survey. This survey 

was conducted by U.S. EPA and is the largest and 

most current human activity pattern survey available 

(U.S. EPA, 1996). Data for 9,386 respondents in the 

48 contiguous United States were collected via 

minute-by-minute 24-hour diaries. NHAPS was 

conducted from October 1992 through September 

1994 by the University of Maryland’s Survey 

Research Center using CATI technology to collect 

24-hour retrospective diaries and answers to a 

number of personal and exposure related questions 

from each respondent. Detailed data were collected 

for a maximum of 82 different possible locations, and 

a maximum of 91 different activities. Participants 

were selected using a RDD method. The response 

rate was 63% overall. If the chosen respondent was a 

child less than 10 years of age, an adult in the 

household gave a proxy interview. Each participant 

was asked to recount their entire daily routine from 

midnight to midnight immediately previous to the 

day that they were interviewed. The survey collected 

information on duration and frequency of selected 

activities and of the time spent in selected 

microenvironments. In addition, demographic 

information was collected for each respondent to 

allow for statistical summaries to be generated 

according to specific groups of the U.S. population 

(i.e., by sex, age, race, employment status, census 

region, season, etc.). Saturdays and Sundays were 

over sampled to ensure an adequate weekend sample. 

For children, the source data from U.S. EPA for 

selected locations, both indoors and outdoors, and 

activities have been reviewed and re-analyzed by 

U.S. EPA to conform to the age categories 

recommended in Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood Exposures 

to Environmental Contaminants (U.S. EPA, 2005). 

This analysis was weighted according to geographic, 

socioeconomic, time/season, and other demographic 

factors to ensure that results were representative of 

the U.S. population. The weighted sample matched 

the 1990 U.S. census population for each sex, age 

group, census region, and the day-of-week and 

seasonal responses were equally distributed. 

Table 16-15 through Table 16-64 provide data 

from the NHAPS study. Because no data were 

available on subjects’ age in months, age groups less 

than 1 year old were consolidated into a single group. 

These tables provide statistics for 24-hour cumulative 

time spent (mean, minimum, percentiles, and 

maximum) in selected locations or engaging in 

selected activities. The original analysis generated 

statistics for the subset of the survey population that 

reported being in the location or doing the activity in 

question (i.e., doers only). For the reanalysis, 

statistics were calculated for the entire survey 

population (i.e., whole population) and for doers 

only. When the sample size was 10 persons or fewer, 

percentile values were not calculated. 

Re-analyzed data are presented for the time 

children, aged birth to less than 21 years, spent in 

selected locations both indoors and outdoors and 

doing various selected activities. Each children only 

table is followed by a table for the whole population 

which presents data for specific populations (i.e., by 

sex, age, race, ethnicity, employment, education, 

Census region, day of the week, season, asthma 

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Chapter 16—Activity Factors
 

status, and bronchitis/emphysema status) and 

includes the time adults, aged 18 years and older, 

spent in various locations and doing various 

activities. Table 16-15 and Table 16-16 present data 

for time spent in rooms of the house (e.g., kitchen, 

bathroom, bedroom, and garage), and all rooms 

combined, for children and by demographic 

characteristics (including adulthood) respectively. 

Table 16-17 and Table 16-18 present data for time 

spent in other indoor locations (e.g., restaurants, 

indoors at school, and grocery/convenience stores). 

Table 16-19 and Table 16-20 present data for the 

time survey participants spent outdoors on school 

grounds/playgrounds, parks or golf courses, or pool 

rivers, or lakes. 

Table 16-21 provides data on time spent in 

indoor and outdoor environments for children birth to 

<21 years of age. The U.S. EPA estimated the time 

spent indoors by adding the average times spent 

indoors at the respondents’ home (kitchen, living 

room, bathroom, etc.), at other houses, and inside 

other locations such as school, restaurants, etc. Time 

outdoors was estimated by adding the average time 

spent outdoors at the respondents’ pool and yard, 

others’ pool and yard, and outside other locations 

such as sidewalk, street, neighborhood, parking lot, 

service station/gas station, school grounds, park/golf 

course, pool, river, lake, farm, etc. Table 16-22 

provides data on time spent in outdoor and indoor 

environments for adults aged 18 years and older. The 

average time spent outdoors was estimated by 

summing the average time spent outdoors away from 

the residence and the average time spent outdoors at 

the residence. Note that these averages are for doers 

only and thus over-estimate the total time spent in the 

environments for the population. 

Table 16-23 and Table 16-24 present data for the 

time spent in various types of vehicles and mass 

transit (i.e., car, truck/van, bus, trains, airplanes), and 

in all vehicles combined. Table 16-25 and 

Table 16-26 present data for the time children and 

adults spent in various major activity categories (e.g., 

sleeping, napping, eating, attending school, outdoor 

recreation, active sports, exercise, and walking). 

Table 16-27 presents data for activities associated 

with time spent working. 

Table 16-28 through Table 16-36 provide data 

related to showering and bathing. Data on 

handwashing activities are in Table 16-37 and 

Table 16-38. Table 16-39 and Table 16-40 provide 

data for children on monthly swimming (in a 

freshwater pool) frequency and swimming duration, 

respectively. Table 16-41 and Table 16-42 provide 

data by demographic characteristics (including 

adulthood) on monthly swimming (in a freshwater 

pool) frequency and swimming duration, 

respectively. Table 16-43 provides data on the time 

children spent playing on dirt, sand/gravel, or grass, 

and Table 16-44 displays these data by demographic 

characteristics (including adulthood). 

Table 16-45 and Table 16-46 provide data on the 

number of minutes spent near excessive dust. 

Table 16-47 and Table 16-48 provide information on 

frequency of sweeping or vacuuming. Table 16-49 

through Table 16-51 provide information on time 

spent in the presence of smokers and time spent 

smoking. Table 16-52 through Table 16-64 provide 

information on activities that may be related to 

specific sources of pollution (e.g., time spent near 

open flames, time spent near heavy traffic, frequency 

of use of dishwashers and washing machines). For 

this data set, the authors’ original age categories for 

children were used because the methodology used to 

generate these data could not be reproduced. 

The advantages of the NHAPS data set are that it 

is representative of the U.S. population. The 

reanalysis done by U.S. EPA to get estimates for 

childhood age groups that correspond to the 

Guidance on Selecting Age Groups for Monitoring 

and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005) was 

weighted and thus the results presented are balanced 

geographically, seasonally, and for day/time. Also, 

the NHAPS is inclusive of all ages, sexes, and races. 

A disadvantage of the study is that for the standard 

age categories, the number of respondents is small for 

the “doers” of many activities. In addition, the 

durations exceeding 60, 120, and 181 minutes were 

not collected for some activities. Therefore, the actual 

time spent at the high end of the distribution for these 

activities could not be accurately estimated. In 

addition, some of the activities were not necessarily 

mutually exclusive (e.g., time spent in active sports 

likely overlaps with exercise time). 

16.3.2. Relevant Activity Pattern Studies 

16.3.2.1. Hill (1985)—Patterns of Time Use 

Hill (1985) investigated the total amount of time 

American adults spend in 1 year performing various 

activities and the variation in time use across 

3 different dimensions: demographic characteristics, 

geographical location, and seasonal characteristics. In 

this study, time estimates were based on data 

collected from time diaries in 4 waves (1/season) of a 

survey conducted in the fall of 1975 through the fall 

of 1976 for the 1975–1976 Time Allocation Study. 

The sampling periods included 2 weekdays, 

1 Saturday and 1 Sunday. The information gathered 

was in response to the survey question “What were 

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you doing?” The survey also provided information on 

secondary activities (i.e., respondents performing 

more than 1 activity at the same time). Hill (1985) 

analyzed time estimates from 971 individuals for 

10 broad categories of activities based on data 

collected from 87 activities. These estimates included 

seasonal variation in time use patterns and 

comparisons of time use patterns for different days of 

the week. 

Analysis of the 1975–1976 survey data revealed 

very small regional differences in time use among the 

broad activity patterns (Hill, 1985). The weighted 

mean hours/week spent performing the 10 major 

activity categories presented by region are shown in 

Table 16-65. Table 16-66 presents the time spent per 

day, by the day of the week for the 10 major activity 

categories. Adult time use was dominated in 

descending order by personal care (including sleep), 

market work, passive leisure, and housework. 

Collectively, these activities represent about 80% of 

available time (Hill, 1985). 

According to Hill (1985), sleep (included in 

personal care) was the single most dominant activity 

averaging about 56.3 hours/week. Television 

watching (included in passive leisure) averaged about 

21.8 hours/week, and housework activities averaged 

about 14.7 hours/week. Weekdays were 

predominantly market-work oriented. Weekends 

(Saturday and Sunday) were predominantly devoted 

to household tasks (“sleeping in,” socializing, and 

active leisure) (Hill, 1985). Table 16-67 presents the 

mean time spent performing these 10 groups of 

activities during each wave of interview (fall, winter, 

spring, and summer). Adjustments were made to the 

data to assure equal distributions of weekdays, 

Saturdays, and Sundays (Hill, 1985). The data 

indicate that the time periods adults spent performing 

market work, child care, shopping, organizational 

activities, and active leisure were fairly constant 

throughout the year (Hill, 1985). The mean hours 

spent per week in performing the 10 major activity 

patterns are presented by sex in Table 16-68. These 

data indicate that time use patterns determined by 

data collected for the mid-1970's survey show sex 

differences. Men spent more time on activities related 

to labor market work and education, and women 

spent more time on household work activities. 

A limitation associated with this study is that the 

time use data were obtained from an old survey 

conducted in the mid-1970s. Because of fairly rapid 

changes in American society, applying these data to 

current exposure assessments may result in some 

biases. Another limitation is that time use data were 

not presented for children. An advantage of this study 

is that time diaries were kept and data were not based 

on recall. The former approach may result in a more 

accurate data set. Another advantage of this study is 

that the survey is seasonally balanced since it was 

conducted throughout the year and the data are from 

a large survey sample. 

16.3.2.2.	 Timmer et al. (1985)—How Children Use 

Time 

Timmer et al. (1985) conducted a study using the 

data obtained on children's time use from a 1981– 

1982 panel study. Data were obtained for 389 

children between 3 and 17 years of age. Data were 

collected using a time diary and a standardized 

interview. The time diary involved children reporting 

their activities beginning at 12:00 a.m. the previous 

night, the duration and location of each activity, the 

presence of another individual, and whether they 

were performing other activities at the same time. 

The standardized interview was administered to the 

children to gather information about their 

psychological, intellectual (using reading 

comprehension tests), and emotional well-being; their 

hopes and goals; their family environment; and their 

attitudes and beliefs. 

For preschool children, parents provided 

information about the child's previous day's activities. 

Children in first through third grades completed the 

time diary with their parents’ assistance and, in 

addition, completed reading tests. Children in 4th 

grade and above provided their own diary 

information and participated in the interview. Parents 

were asked to assess their children's socioemotional 

and intellectual development, and a survey form was 

sent to a teacher of each school-age child to evaluate 

their socioemotional and intellectual development. 

The activity descriptor codes used in this study were 

developed by Juster et al. (1983). 

The mean time spent performing major activities 

on weekdays and weekends by age, sex, and type of 

day is presented in Table 16-69. On weekdays, 

children spend about 40% of their time sleeping, 20% 

in school, and 10% eating, and performing personal 

care activities (Timmer et al., 1985). The data in 

Table 16-69 indicate that girls spent more time than 

boys performing household work and personal care 

activities and less time playing sports. Also, the 

children spent most of their free time watching 

television. 

Table 16-70 presents the mean time children 

spent during weekdays and weekends performing 

major activities by 5 different age groups. The 

significant effects of each variable (i.e., age and sex) 

are also shown. Older children spent more time 

performing household and market work, studying, 

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and watching television and less time eating, 

sleeping, and playing. The authors estimated that, on 

average, boys spent 19.4 hours a week and girls spent 

17.8 hours/week watching television. 

U.S. EPA estimated the total time indoors and 

outdoors using the Timmer et al. (1985) data. 

Activities performed indoors were assumed to 

include household work, personal care, eating, 

sleeping, attending school, studying, attending 

church, watching television, and engaging in 

household conversations. The average times spent in 

these indoor activities and half the time spent in each 

activity which could have occurred indoors or 

outdoors (e.g., market work, sports, hobbies, art 

activities, playing, reading, and other passive leisure) 

were summed. Table 16-71 summarizes the results of 

this analysis by age group and day of the week. 

A limitation associated with this study is that it 

was conducted in 1981. It is likely that activity 

patterns of children have changed from 1981 to the 

present. Thus, the application of these data to current 

exposure assessments may bias their results. Another 

limitation is that the data do not provide overall 

annual estimates of children’s time use since data 

were collected only during the time of the year when 

children attended school and not during school 

vacations. An advantage of this survey is that diary 

recordings of activity patterns were kept and the data 

obtained were not based entirely on recall. Another 

advantage is that parents assisted younger children 

with keeping their diaries and with interviews, 

minimizing any bias that may have been created by 

having younger children record their own data. 

16.3.2.3.	 Robinson and Thomas (1991)—Time 

Spent in Activities, Locations, and 

Microenvironments: A CaliforniaNational Comparison 

Robinson and Thomas (1991) reviewed and 

compared data from the 1987–1988 California Air 

Resources Board (CARB) time-activity study for 

California residents and from a similar 1985 national 

study, Americans’ Use of Time, conducted at the 

University of Maryland. Both studies used the diary 

approach to collect data. Time-use patterns were 

collected for individuals aged 12 years and older. 

Telephone interviews based on the RDD procedure 

were conducted for 1,762 and 2,762 respondents for 

the CARB study and the national study, respectively. 

Robinson and Thomas (1991) defined a set of 

16 microenvironments based on the activity and 

location codes employed in the 2 studies. The mean 

durations of time spent in the 16 microenvironments 

by age, are presented in Table 16-72. In both studies, 

children and adults spent the majority of their time 

sleeping, and engaging in leisure and work/studyrelated activities. 

Table 16-73 shows the mean time spent in the 

10 major activities by sex and for all respondents 

between the ages of 18-64 years. Table 16-74 

presents the mean time spent at 3 major locations for 

the CARB and national study grouped by total 

sample and sex, ages 18-64 years. The mean duration 

of time spent in locations for total sample population, 

12 years and older, across 3 types of locations is 

presented in Table 16-75 for both studies. 

The limitations associated with the Robinson and 

Thomas (1991) study are that the CARB survey was 

performed in California only and may not be 

representative of the U.S. population as a whole, and 

the studies were conducted in the 1980s and activity 

patterns may have changed over time. Another 

limitation is that the data are based on short-term 

studies. Finally, the available data could not be 

re-analyzed to conform to the standardized age 

categories used in this handbook. 

16.3.2.4.	 Funk et al. (1998)—Quantifying the 

Distribution of Inhalation Exposure in 

Human Populations: Distribution of Time 

Spent by Adults, Adolescents, and 

Children at Home, at Work, and at School 

Funk et al. (1998) used the data from the CARB 

study to determine distributions of exposure time by 

tracking the time spent participating in daily activities 

for male and female children, adolescents, and adults. 

CARB performed 2 studies from 1987 to 1990; the 

first was focused on adults (18 years and older) and 

adolescents (12 to 17 years old), and the second 

focused on children (6 to 11 years old). The targeted 

groups were non-institutionalized English speaking 

Californians with telephones in their residences. 

Individuals were contacted by telephone and asked to 

account for every minute within the previous 24 

hours, including the amount of time spent on an 

activity and the location of the activity. The surveys 

were conducted on different days of the week as well 

as different seasons of the year. 

Using the location descriptors provided in the 

CARB study, Funk et al. (1998) categorized the 

activities into 2 groups, “at home” (any activity at 

principal residence) and “away.” Each activity was 

assigned to 1 of 3 inhalation rate levels (low, 

moderate, or high) based on the level of exertion 

expected from the activity. Ambiguous activities 

were assigned to moderate inhalation rate levels. 

Among the adolescents and children studied, means 

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were determined for the aggregate age groups. 

Sample sizes are shown in Table 16-76. 

Funk et al. (1998) used several statistical 

methods, such as Chi-square, Kolmogorov-Smirnov, 

and Anderson-Darling, to determine whether the time 

spent in an activity group had a known distribution. 

Most of the activities performed by all individuals 

were assigned a low or moderate inhalation rate (see 

Table 16-77). 

The aggregate time periods spent at home in 

each activity are shown in Table 16-78. Aggregate 

time spent at home performing different activities 

was compared between sexes. There were no 

significant differences between adolescent males and 

females in any of the activity groups (see 

Table 16-79). There were significant differences 

between males and females among adults in all 

activity groups except for the low activity group (see 

Table 16-58). In children, ages 6 to 11 years, 

differences between sex and age were observed at the 

low inhalation rate levels. There were significant 

differences (p < 0.05) between 2 age groups (6 to 

8 years, and 9 to 11 years) and sex at the moderate 

inhalation rate level (see Table 16-80). 

A limitation of this study was that large 

proportions of the respondents in the study did not 

participate in high-inhalation rate-level activities. The 

Funk et al. (1998) study was based on data from 

1 geographic location, collected more than a decade 

ago. Thus, it may not be representative of current 

activities among the general population of the United 

States. 

16.3.2.5.	 Cohen Hubal et al. (2000)—Children’s 

Exposure Assessment: A Review of 

Factors Influencing Children’s Exposure 

and the Date Available to Characterize 

and Assess That Exposure 

Cohen Hubal et al. (2000) reviewed available 

data from the Consolidated Human Activity Database 

[CHAD, U.S. EPA (2009)], including activity pattern 

data, to characterize and assess environmental 

exposures to children. Data from the 2 key studies in 

this chapter (U.S. EPA, 1996; Wiley et al., 1991) are 

included in CHAD. CHAD was developed by the 

U.S. EPA’s National Exposure Research Laboratory 

to provide access to existing human activity pattern 

data for use in exposure and risk assessment efforts. 

It is available online at 

http://www.epa.gov/chadnet1/. Data from twelve 

activity pattern studies conducted at the city, state, 

and national levels are included in CHAD. CHAD 

contains both the original raw data from each study 

and data modified based on predefined format 

requirements. Modifications made to data included: 

recoding of variables to fit into them a common 

activity/location code system, and standardization of 

time diaries to an exact 24-hour length. Detailed 

information on the coding system and the studies 

included in CHAD is available in the CHAD User 

Manual, available at 

http://oaspub.epa.gov/chad/CHAD_Datafiles$.startup 

#Manual, and in McCurdy et al. (2000). 

A total of 144 activity codes and 115 location 

codes were used in CHAD (Mccurdy et al., 2000). 

Although some participants in a study conducted 

multiple activities, many activities were only 

conducted within a few studies. The same is true for 

activity locations. The selection of exposure 

estimates for a particular activity or particular 

location should be based on study parameters that 

closely relate to the exposure scenario being 

assessed. The maximum amount of time, on average, 

within a majority of the studies was sleeping or 

taking a nap, while the maximum amount of time 

spent at a particular location was at home or at work, 

depending on the study. 

Many of the limitations of CHAD data arise 

from the incorporation of multiple studies into the 

time diary functions specified in CHAD. Activities 

and locations were coded similarly to the NHAPS 

study; studies with differing coding systems were 

modified to fit the NHAPS codes. In some cases start 

times and end times from a study had to be adjusted 

to fit a 24-hour period. Respondents were not 

randomly distributed in CHAD. For example, some 

cities or states were over sampled because entire 

studies were carried out in those places. Other studies 

excluded large groups of people such as smokers, or 

non-English speakers, or people without telephones. 

Many surveys were age restricted, or they 

preferentially sampled certain target groups. As a 

result, users are cautioned against using random 

individuals in CHAD to represent the U.S. population 

as a whole (Stallings et al., 2002). 

CHAD contains 3,009 person-days of 

macroactivity data for 2,640 children less than 

12 years of age (Cohen Hubal et al., 2000) (see 

Table 16-81). The number of hours these children 

spent in various microenvironments are shown in 

Table 16-82 and the time they spent in various 

activities indoors at home is shown in Table 16-83. 

Cohen Hubal et al. (2000) noted that CHAD 

contains approximately “140 activity codes and 

110 location codes, but the data generally are not 

available for all activity locations for any single 

respondent. In fact, not all of the codes were used for 

most of the studies. Even though many codes are 

used in macroactivity studies, many of the activity 

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codes do not adequately capture the richness of what 

children actually do. They are much too broadly 

defined and ignore many child-oriented behaviors. 

Thus, there is a need for more and better-focused 

research into children’s activities.” 

U.S. EPA updated the analysis performed by 

Cohen Hubal et al. (2000) using CHAD data 

downloaded in 2000, sorted according to the age 

groups recommended in Guidance on Selecting Age 

Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. 

EPA, 2005). Table 16-84 and Table 16-85 show the 

results. In this analysis, individual study participants 

within CHAD whose behavior patterns were 

measured over multiple days were treated as multiple 

1-day activity patterns. This is a potential source of 

error or bias in the results because a single individual 

may contribute multiple data sets to the aggregate 

population being studied. 

Advantages of the CHAD database are that it 

includes data from 12 activity pattern studies and is a 

fairly comprehensive tool for cohort development 

and for simulating individuals within exposure 

assessments. However, because the database is 

comprised of separate studies, issues such as quality 

assurance and consistency between the studies are 

difficult to assess. In addition, current human activity 

pattern surveys do not collect data on microactivities 

that are important to understanding exposures, 

especially for children, nor do they discriminate 

sufficiently among activities important to developing 

energy expenditure estimates. 

16.3.2.6.	 Wong et al. (2000)—Adult Proxy 

Responses to a Survey of Children’s 

Dermal Soil Contact Activities 

Wong et al. (2000) conducted telephone surveys 

to gather information on children’s activity patterns 

as related to dermal contact with soil during outdoor 

play on bare dirt or mixed grass and dirt surfaces. 

This study, the second Soil Contact Survey (SCS-II), 

was a follow-up to the initial Soil Contact Survey 

(SCS-I), conducted in 1996, that primarily focused on 

assessing adult behavior related to dermal contact 

with soil and dust (Garlock et al., 1999). As part of 

SCS-I, information was gathered on the behavior of 

children under the age of 18 years, however, the 

questions were limited to clothing choices and the 

length of time between soil contact and hand 

washing. Questions were posed for SCS-II to further 

define children’s outdoor activities and hand washing 

and bathing frequency. For both soil contact surveys 

households were randomly phoned in order to obtain 

nationally representative results. The adult 

respondents were questioned as surrogates for 

1 randomly chosen child under the age of 18 residing 

within the household. 

In the SCS-II, of 680 total adult respondents with 

a child in their household, 500 (73.5%) reported that 

their child played outdoors on bare dirt or mixed 

grass and dirt surfaces (identified as “players”). 

Those children that reportedly did not play outdoors 

(“non-players”) were typically very young (≤1 year) 

or relatively older (≥14 years). Of the 500 children 

that played outdoors, 497 played outdoors in warm 

weather months (April through October) and 390 

were reported to play outdoors during cold weather 

months (November through March). These results are 

presented in Table 16-86. The frequency 

(days/week), duration (hours/day), and total 

hours/week spent playing outdoors was determined 

for those children identified as “players” (see 

Table 16-87). The responses indicated that children 

spent a relatively high percentage of time outdoors 

during the warmer months, and a lesser amount of 

time outdoors in cold weather. The median play 

frequency reported was 7 days/week in warm weather 

and 3 days/week in cold weather. Median play 

duration was 3 hours/day in warm weather and 1 

hour/day during cold weather months. 

Adult respondents were then questioned as to 

how many times per day their child washed his/her 

hands and how many times the child bathed or 

showered per week, during both warm and cold 

weather months. This information provided an 

estimate of the time between skin contact with soil 

and removal of soil by washing (i.e., exposure time). 

Hand washing and bathing frequencies for child 

players are reported in Table 16-88. Based on these 

results, hand washing occurred a median of 4 times 

per day during both warm and cold weather months. 

The median frequency for baths and showers was 

estimated to be 7 times per week for both warm and 

cold weather. 

Based on reported household incomes, the 

respondents sampled in SCS-II tended to have higher 

incomes than that of the general population. This may 

be explained by the fact that phone surveys cannot 

sample households without telephones. Additional 

uncertainty or error in the study results may have 

occurred as a result of the use of surrogate 

respondents. Adult respondents were questioned 

regarding child activities that may have occurred in 

prior seasons, introducing the chance of recall error. 

In some instances, a respondent did not know the 

answer to a question or refused to answer. 

Table 16-89 compares mean play duration data from 

SCS-II to similar activities identified in NHAPS 

(U.S. EPA, 1996). Table 16-90 compares the number 

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of times per day a child washed his or her hands, 

based on data from SCS-II and NHAPS. As indicated 

in Table 16-89 and Table 16-90, where comparison is 

possible, NHAPS and SCS-II results showed 

similarities in observed behaviors. 

An advantage of this study includes the fact that 

a random household survey was conducted to obtain 

nationally representative results. A limitation of the 

study is that questions were limited to clothing 

choices and the length of time between soil contact 

and hand washing. In addition, the participants were 

questioned about events from prior seasons, which 

may have introduced recall error. 

16.3.2.7.	 Graham and McCurdy (2004)— 

Developing Meaningful Cohorts for 

Human Exposure Models 

Graham and McCurdy (2004) used a statistical 

model (general linear model and analysis of variance 

[GLM/ANOVA]) to assess the significance of 

various factors in explaining variation in time spent 

outdoors, indoors and in motor vehicles. These 

factors, which are commonly used in developing 

cohorts for exposure modeling, included age, sex, 

weather, ethnicity, day type, and precipitation. 

Activity pattern data from CHAD, containing 30 or 

more records per day, were used in the analysis 

(Graham and Mccurdy, 2004). Data from the 2 key 

studies in this chapter (U.S. EPA, 1996; Wiley et al., 

1991) are included in CHAD. 

Table 16-91 presents data on time spent outdoors 

for people who spent >0 time outdoors (i.e., doers). 

Graham and McCurdy (2004) found that all the 

factors evaluated were significant (p < 0.001) in 

explaining differences in time spent outdoors 

(Graham and Mccurdy, 2004). An evaluation of sex 

differences in time spent outdoors by age cohorts was 

also conducted. Table 16-92 presents descriptive 

statistics and the results of the 2-sample 

Kolmogorov-Smirnov (K-S) test for this evaluation. 

As shown in Table 16-92, there were statistically 

significant sex differences in time spent outdoors 

starting with the 6 to 10 year old age category and 

continuing through all age groups, up to and 

including >64 years of age. In addition, Graham and 

McCurdy (2004) evaluated the effect of physical 

activity and concluded that this was the most 

important factor in explaining time spent outdoors. 

For time spent indoors (see Table 16-93), there were 

statistically significant effects for all the factors 

evaluated, with sex, weather, and day type being the 

most important variables. Regarding time spent in 

motor vehicles (see Table 16-94), precipitation was 

the only factor found to have no significant effects 

(Graham and Mccurdy, 2004). 

Based on the results of these analyses, Graham 

and McCurdy (2004) noted that “besides age and sex, 

other important attributes for defining cohorts are the 

physical activity level of individuals, weather factors 

such as daily maximum temperature in combination 

with months of the year, and combined 

weekday/weekend with employment status.” The 

authors also noted that even though the factors 

evaluated were found to be statistically significant in 

explaining differences in time spent outdoors, 

indoors, and in motor vehicles, “parameters such as 

lifestyle and life stages that are absent from CHAD 

might have reduced the amount of unexplained 

variance.” The authors recommended that, in 

defining cohorts for exposure modeling, age and sex 

should be used as ‘‘first-order’’ attributes, followed 

by physical activity level, daily maximum 

temperature, and day type (weekend/weekday or dayof-the-week/working status) (Graham and Mccurdy, 

2004). 

The CHAD database is a fairly comprehensive 

tool for cohort development and for simulating 

individuals within exposure assessments. However, 

the database is comprised of 12 separate studies, and 

because of this, issues such as quality assurance and 

consistency between the studies are difficult to 

assess. In addition, current human activity pattern 

surveys do not collect data on microactivities that are 

important to understanding exposures, especially for 

children, nor do they discriminate sufficiently among 

activities important to developing energy expenditure 

estimates. Other limitations of the CHAD database 

are described earlier in this chapter by Cohen Hubal 

et al. (2000) in Section 16.3.2.5. 

16.3.2.8.	 Juster et al. (2004)—Changing Times of 

American Youth: 1983–2003 

Juster et al. (2004) evaluated changes in time use 

patterns of children by comparing data collected in a 

1981–1982 pilot study of children ages 6 to 17 to 

data from the 2002–2003 Child Development 

Supplement (CDS) to the Panel Study of Income 

Dynamics (PSID). The 1981–1982 pilot study is the 

same study described in Timmer et al. (1985). The 

2002–2003 CDS gathered 24-hour time diary data on 

2,908 children ages 6 to 17; as was done in the 1997 

CDS, information was collected on 1 randomly 

selected weekday and 1 randomly selected weekend 

day (Juster et al., 2004). 

Table 16-95 and Table 16-96 present the mean 

time children spent (in minutes/day) performing 

major activities on weekdays and weekend days, 

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respectively, for the years 1981–1982 and

2002−2003. Table 16-97 shows the weekly time 

spent in these activities for the years 1981−1982 and 

2002–2003. Juster et al. (2004) noted that the time 

spent in school and studying increased while time 

spent in active sports and outdoors activities 

decreased during the period studied. 

An advantage of this survey is that diary 

recordings of activity patterns were kept and the data 

obtained were not based entirely on recall. Another 

advantage is that because parents assisted younger 

children with keeping their diaries and with 

interviews, minimizing any bias that may have been 

created by having younger children record their own 

data. A limitation associated with this study is that 

the data from the Timmer et al. (1985) study were 

collected in 1981 and it is likely that the activity 

patterns of children have changed from 1981 to the 

present. Another limitation is that the data from the 

CDS study do not provide overall annual estimates of 

children’s time use since data were collected only 

during the time of the year when children attended 

school and not during school vacations. 

16.3.2.9.	 Vandewater et al. (2004)—Linking 

Obesity and Activity Level With 

Children’s Television and Video Game 

Use 

Vandewater et al. (2004) evaluated children’s 

media use and participation in active and sedentary 

activities using 24-hour time-use diaries collected in 

1997, as part of the Child Development Supplement 

to the Panel Study of Income Dynamics. The PSID is 

an ongoing, longitudinal study of U.S. individuals 

and their families conducted by the Survey Research 

Center of the University of Michigan. In 1997, PSID 

families with children younger than 12 years of age 

completed the CDS and reported all activities 

performed by the children on 1 randomly selected 

weekday and 1 randomly selected weekend day. 

Since minorities, low-income families, and less 

educated individuals were oversampled in the PSID, 

sample weights were applied to the data (Vandewater 

et al., 2004). More information on the CDS can be 

found on-line at 

http://psidonline.isr.umich.edu/CDS/. 

Using time use diary data from 2,831 children 

participating in the CDS, Vandewater et al. (2004) 

estimated the time in minutes over the 2-day study 

period (i.e., sum of time spent on 1 weekday and 

1 weekend day) that children spent watching

television, playing games on video games consoles or 

computers, reading, and using computers for other 

purposes besides playing games. In addition, the time 

spent participating in highly active (i.e., playing 

sports), moderately active (i.e., fishing, boating,

camping, taking music lessons, and singing), and 

sedentary (i.e., using the phone, doing puzzles,

playing board games, and relaxing) activities was 

determined. Table 16-98 presents the means and 

standard deviations for the time spent in the selected 

activities by age and sex. 

A limitation of this study is that the survey was 

not designed for exposure assessment purposes.

Therefore, the time use data set may be biased. 

However, the survey provides a database of current 

information on various human activities. This 

information can be used to assess various exposure 

pathways and scenarios associated with these

activities. 

16.3.2.10.	 U.S. Department of Labor (2007)— 

American Time Use Survey, 2006 Results 

The American Time Use Study has been

conducted annually since 2003 by the U.S.

Department of Labor’s (DOL) Bureau of Labor

Statistics (U.S. Department of Labor, 2007). The 

purpose of the study is to collect “data on what 

activities people do during the day and how much 

time they spend doing them.” In 2006, the survey 

focused on “the time Americans worked, did

household activities, cared for household children, 

participated in educational activities, and engaged in 

leisure and sports activities.” Approximately 13,000 

individuals, 15 years of age and older, were

interviewed during 2006. Participants were randomly 

selected and interviewed using the CATI method and 

were asked to recall their activities on the day before 

the interview. The survey response rate was 55.1% 

(U.S. Department of Labor, 2007). Data were 

collected for all days of the week, including

weekends (i.e., 10% of the individuals were

interviewed about their activities on 1 of the 5 

weekdays, and 25% of the individuals were

interviewed about their activities on 1 of the

2 weekend days). Demographic information,

including age, sex, race/ethnicity, marital status, and 

educational level were also collected, and sample 

weights were applied to records to “reduce bias in the 

estimates due to differences in sampling and response 

rates across populations and days of the week.” Data 

were collected for 17 major activities, which were 

subsequently combined into 12 categories for

publication of the results. Table 16-99 provides 

information on the average amount of time spent in 

the 12 major time use categories by sex, age,

race/ethnicity, marital status, and educational level 

(U.S. Department of Labor, 2007). Estimates of time 
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use in sub-categories of the 12 major categories are 

presented in Table 16-100. The majority of time was 

spent engaging in personal care activities 

(9.41 hours/day) which included sleeping 

(8.63 hours/day), followed by leisure and sports 

activities (5.09 hours/day), and work activities 

(3.75 hours/day). Note that because these data are 

averaged over both weekdays and weekends for the 

entire year, the amount of time spent daily on 

work-related activities does not reflect that of a 

typical work day. 

Table 16-101 provides estimates of time use for 

all children ages 15 to 19 years by sex. It also 

provides a more detailed breakdown of the Leisure 

and Sports category for all children, ages 15 to 

19 years old. 

The limitation of this study is that it did not 

account for all activities during the day and therefore 

estimates about total time indoors and outdoors could 

not be calculated. The advantages are the large 

sample size, the representativeness of the sample, and 

the currency of the data. 

16.3.2.11.	 Nader et al. (2008)—Moderate-toVigorous Physical Activity From Ages 9 

to 15 Years 

Nader et al. (2008) conducted a longitudinal 

study of 1,032 children from ages 9 to 15 years. The 

purpose of the study was to determine the amount of 

time children 9 to 15 years of age engaged in 

moderate-to-vigorous physical activities (MVPA) 

and compare results with the recommendations 

issued by the U.S. Department of Health and Human 

Services and the U.S. Department of Agriculture 

(USDA, 2005) of a minimum of 60 minutes/day. 

Participants were recruited from university-based 

community hospitals located in Arkansas, California, 

Kansas, Massachusetts, Pennsylvania, Virginia, 

Washington, North Carolina, and Wisconsin. 

Children’s activity levels were recorded for 4 to 7 

days using an accelerometer, set so that it recorded 

minute-by-minute movement counts. The study 

participants included 517 boys and 515 girls. 

The study found that at age nine years, children 

engaged in 3 hours of MVPA/day. By age 15 years, 

the amount of time engaged in MVPA was dropped 

to 49 minutes/day on weekdays and 35 minutes/day 

on weekends. Boys spent 18 more minutes/day of 

MVPA than girls on weekdays and 13 more 

minutes/day on weekends. Estimates of the mean 

time spent in MVPA by various age groups are 

presented in Table 16-102. 

Advantages of this study include the fact that 

both weekdays and weekends were included in the 

study and the use of an accelerometer to measure 

physical activity. A limitation of the study is the fact 

that the sample of children was not nationally 

representative of the U.S. population. In addition, the 

study did not provide information about the amount 

of time spent at specific activities. 

16.4. OCCUPATIONAL MOBILITY 

16.4.1. Key Occupational Mobility Studies 

16.4.1.1.	 Carey (1988)—Occupational Tenure in 

1987: Many Workers Have Remained in 

Their Fields 

Carey (1988) presented median occupational and 

employer tenure for different age groups, sex, 

earnings, ethnicity, and educational attainment. 

Occupational tenure was defined as “the cumulative 

number of years a person worked in his or her current 

occupation, regardless of number of employers, 

interruptions in employment, or time spent in other 

occupations” (Carey, 1988). The information 

presented was obtained from supplemental data to the 

January 1987 Current Population Study, a U.S. 

Census Bureau publication. Carey (1988) did not 

present information on the survey design. 

The median occupational tenure by age and sex, 

race, and employment status are presented in 

Table 16-103, Table 16-104, and Table 16-105, 

respectively. The median occupational tenure of the 

working population (109.1 million people) 16 years 

of age and older in January of 1987 was 6.6 years 

(see Table 16-103). Table 16-103 also shows that 

median occupational tenure increased from 1.9 years 

for workers 16 to 24 years old to 21.9 years for 

workers 70 years and older. The median occupational 

tenure for men 16 years and older was higher (7.9 

years) than for women of the same age group (5.4 

years). Table 16-104 indicates that Whites had longer 

occupational tenure (6.7 years) than Blacks 

(5.8 years), and Hispanics (4.5 years). Full-time 

workers had more occupational tenure than part-time 

workers 7.2 years and 3.1 years, respectively (see 

Table 16-105). 

Table 16-106 presents the median occupational 

tenure among major occupational groups. The 

median tenure ranged from 4.1 years for service 

workers to 10.4 years for people employed in 

farming, forestry, and fishing. 

The strength of an individual's attachment to a 

specific occupation has been attributed to the 

individual's investment in education (Carey, 1988). 

Carey (1988) reported the median occupational 

tenure for the surveyed working population by age 

and educational level. Workers with 5 or more years 

of college had the highest median occupational tenure 

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of 10.1 years. Workers that were 65 years and older 

with 5 or more years of college had the highest 

occupational tenure level of 33.8 years. The median 

occupational tenure was 10.6 years for self-employed 

workers and 6.2 years for wage and salary workers 

(Carey, 1988). 

A limitation associated with this study is that the 

survey design employed in the data collection was 

not presented, though it can be found on the U.S. 

Census Bureau’s website. Therefore, the validity and 

accuracy of the data set cannot be determined. 

Another limitation is that only median values were 

reported in the study. An advantage of this study is 

that occupational tenure (years spent in a specific 

occupation) was obtained for various age groups by 

sex, ethnicity, employment status, and educational 

level. Another advantage of this study is that the data 

were based on a survey population which appears to 

represent the general U.S. population. 

16.4.1.2.	 Carey (1990)—Occupational Tenure, 

Employer Tenure, and Occupational 

Mobility 

Carey (1990) conducted another study that was 

similar in scope to the study of Carey (1988). The 

January 1987 Current Population Study was used. 

This study provided data on occupational mobility 

and employer tenure in addition to occupational 

tenure. Occupational tenure was defined in Carey 

(1988) as the “the cumulative number of years a 

person worked in his or her current occupation, 

regardless of number of employees, interruptions in 

employment, or time spent in other locations.” 

Employer tenure was defined as “the length of time a 

worker has been with the same employer,” while 

occupational mobility was defined as “the number of 

workers who change from 1 occupation to another” 

(Carey, 1990). Occupational mobility was measured 

by asking individuals who were employed in both 

January 1986 and January 1987 if they were doing 

the same kind of work in each of these months 

(Carey, 1990). Carey (1990) further analyzed the 

occupational mobility data and obtained information 

on entry and exit rates for occupations. These rates 

were defined as “the percentage of persons employed 

in an occupation who had voluntarily entered it from 

another occupation” and an exit rate was defined as 

“the percentage of persons employed in an 

occupation who had voluntarily left for a new 

occupation” (Carey, 1990). 

Table 16-107 shows the voluntary occupational 

mobility rates in January 1987 for workers 16 years 

and older. For all workers, the overall voluntary 

occupational mobility rate during that year was 5.3%. 

These data also show that younger workers left 

occupations at a higher rate than older workers. 

Carey (1990) reported that 10 million of the 100.1 

million individuals employed in January 1986 and in 

January 1987 had changed occupations during that 

period, resulting in an overall mobility rate of 9.9%. 

Executive, administrative, and managerial 

occupations had the highest entry rate of 5.3%, 

followed by administrative support (including 

clerical) at 4.9%. Sales had the highest exit rate of 

5.3% and service had the 2nd highest exit rate of 4.8% 

(Carey, 1990). In January 1987, the median employer 

tenure for all workers was 4.2 years. The median 

employee tenure was 12.4 years for those workers 

that were 65 years of age and older (Carey, 1990). 

Because the study was conducted by Carey 

(1990) in a manner similar to that of the previous 

study (Carey, 1988), the same advantages and 

disadvantages associated with Carey (1988) also 

apply to this data set. 

16.5. POPULATION MOBILITY 

16.5.1. Key Population Mobility Studies 

16.5.1.1.	 Johnson and Capel (1992)—A Monte 

Carlo Approach to Simulating Residential 

Occupancy Periods and Its Application to 

the General U.S. Population 

Johnson and Capel (1992) developed a 

methodology to estimate the distribution of the 

residential occupancy period (ROP) in the national 

population. ROP denotes the time (years) between a 

person moving into a residence and the time the 

person moves out or dies. The methodology used a 

Monte Carlo approach to simulate a distribution of 

ROP for 500,000 persons using data on population, 

mobility, and mortality. 

The methodology consisted of 6 steps. The 1st 

step defined the population of interest and 

categorized them by location, sex, age, sex, and race. 

Next the demographic groups were selected and the 

fraction of the specified population that fell into each 

group was developed using U.S. Census Bureau data. 

A mobility table was developed based on census data, 

which provided the probability that a person with 

specified demographics did not move during the 

previous year. The fifth step used data on vital 

statistics published by the National Center for Health 

Statistics and developed a mortality table which 

provided the probability that individuals with specific 

demographic characteristics would die during the 

upcoming year. As a final step, a computer based 

algorithm was used to apply a Monte Carlo approach 

to a series of persons selected at random from the 

population being analyzed. 

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Table 16-108 presents the results for residential 

occupancy periods for the total population, by sex. 

The estimated mean ROP for the total population was 

11.7 years. The distribution was skewed (Johnson 

and Capel, 1992): the 25th, 50th, and 75th percentiles 

were 3, 9, and 16 years, respectively. The 90th, 95th, 

and 99th percentiles were 26, 33, and 47 years, 

respectively. The mean ROP was 11.1 years for 

males and 12.3 years for females, and the median 

value was 8 years for males and 9 years for females. 

Descriptive statistics for groups defined by 

current ages were also calculated. These data, 

presented by sex, are shown in Table 16-109. The 

mean ROP increases from age 3 to age 12 years and 

there is a noticeable decrease at age 24 years. 

However, there is a steady increase from age 24 

through age 81 years. 

There are a few biases within this methodology 

that have been noted by the authors. The probability 

of not moving is estimated as a function only of sex 

and age. The Monte Carlo process assumes that this 

probability is independent of (1) the calendar year to 

which it is applied, and (2) the past history of the 

person being simulated. These assumptions, 

according to Johnson and Capel (1992), are not 

entirely correct. They believe that extreme values are 

a function of sample size and will, for the most part, 

increase as the number of simulated persons 

increases. 

16.5.1.2.	 U.S. Census Bureau (2008a)—American 

Housing Survey for the United States in 

2007 

This survey is a national sample of 

55,000 interviews in which data were collected from 

present owners, renters, Black householders, and 

Hispanic householders. The data reflect the number 

of years a unit has been occupied and represent all 

occupied housing units that the residents’ rented or 

owned at the time of the survey. 

The results of the survey pertaining to residence 

time of owner/renter occupied units in the United 

States are presented in Table 16-110. Using the data 

in Table 16-110, the percentages of householders 

living in houses for specified time ranges were 

determined and are presented in Table 16-111. Based 

on the U.S. Census Bureau data in Table 16-111, the 

50th percentile and the 90th percentile values were 

calculated for the number of years lived in the 

householder’s current house. These values were 

calculated by apportioning the total sample size 

(110,692 households) to the indicated percentile 

associated with the applicable range of years lived in 

the current home. Assuming an even distribution 

within the appropriate range, the 50th and 90th 

percentile values for years living in the current home 

were determined to be 8.0 and 32.0 years, 

respectively. Based on the above data, 8 and 32 years 

are assumed to best represent a central tendency 

estimate of length of residence and upper percentile 

estimate of residence time, respectively. 

A limitation associated with the above analysis is 

the assumption that there is an even distribution 

within the different ranges. As a result, the 50th and 

90th percentile values may be biased. 

16.5.2. Relevant Population Mobility Studies 

16.5.2.1.	 Israeli and Nelson (1992)—Distribution 

and Expected Time of Residence for U.S. 

Households 

In risk assessments, the average current 

residence time (time since moving into current 

residence) has often been used as a substitute for the 

average total residence time (time between moving 

into and out of a residence) (Israeli and Nelson, 

1992). Israeli and Nelson (1992) have estimated 

distributions of expected time of residence for U.S. 

households. Distributions and averages for both 

current and total residence times were calculated for 

several housing categories using the 1985 and 1987 

U.S. Census Bureau housing survey data. The total 

residence time distribution was estimated from 

current residence time data by modeling the moving 

process (Israeli and Nelson, 1992). Israeli and Nelson 

(1992) estimated the average total residence time for 

a household to be approximately 4.6 years or 1/6 of 

the expected life span (see Table 16-112). The 

maximal total residence time that a given fraction of 

households will live in the same residence is 

presented in Table 16-113. For example, only 5% of 

the individuals in the “All Households” category will 

live in the same residence for 23 years and 95% will 

move in less than 23 years. 

The authors note that the data presented are for 

the expected time a household will stay in the same 

residence. The data do not predict the expected 

residence time for each member of the household, 

which is generally expected to be smaller (Israeli and 

Nelson, 1992). These values are more realistic 

estimates for the individual total residence time, than 

the average time a household has been living at its 

current residence. The expected total residence time 

for a household is consistently less than the average 

current residence time. This is the result of greater 

weighting of short residence time when calculating 

the average total residence time than when 

calculating the average current residence time (Israeli 

and Nelson, 1992). When averaging total residence 

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over a time interval, frequent movers may appear 

several times, but when averaging current residence 

times, each household appears only once (Israeli and 

Nelson, 1992). According to Israeli and Nelson 

(1992), the residence time distribution developed by 

the model is skewed and the median values are 

considerably less than the means, which are less than 

the average current residence times. 

Advantages of this study are the large sample 

size and its representativeness to the U.S. population, 

since it was based on U.S. Census Bureau housing 

survey data. Several limitations of the study have 

been noted by Israeli and Nelson (1992) above. An 

additional limitation is the age of the study and the 

fact that the U.S. Census Bureau housing survey is 

based on recall data. 

16.5.2.2.	 National Association of Realtors (NAR) 

(1993)—The Home Buying and Selling 

Process 

The NAR survey was conducted by mailing a 

questionnaire to 15,000 home buyers throughout the 

United States who purchased homes during the 

second half of 1993. The survey was conducted in 

December 1993 and 1,763 usable responses were 

received, equaling a response rate of 12% (NAR, 

1993). Of the respondents, 41% were first time 

buyers. Home buyer names and addresses were 

obtained from Dataman Information Services (DIS). 

DIS compiles information on residential real estate 

transactions from more than 600 counties throughout 

the United States using courthouse deed records. 

Most of the 250 Metropolitan Statistical Areas are 

also covered in the DIS data compilation. 

The home buyers were questioned on the length 

of time they owned their previous home. The typical 

homebuyer (40%) was found to have lived in their 

previous home between 4 and 7 years (see 

Table 16-114). The survey results indicate that the 

average tenure of home buyers is 7.1 years based on 

an overall residence history of the respondents (NAR, 

1993). In addition, the median length of residence in 

respondents’ previous homes was found to be 6 years 

(see Table 16-115). 

The distances the respondents moved to their 

new homes were typically short distances. Data 

presented in Table 16-116 indicate that the mean 

distances range from 230 miles for new home buyers 

and 270 miles for repeat buyers to 110 miles for first 

time buyers and 190 for existing home buyers. 

Seventeen percent (17%) of respondents purchased 

homes over 100 miles from their previous homes and 

49% purchased homes less than 10 miles away. 

Advantages of this study are the large sample 

size and its representativeness to the U.S. population, 

since it was based on 15,000 home buyers throughout 

the United States. A limitation of the study is the fact 

that the data are over 17 years old. 

16.5.2.3.	 U.S. Census Bureau (2008b)—Current 

Population Survey 2007, Annual Social 

and Economic Supplement 

The Current Population Survey is conducted 

monthly by the U.S. Census Bureau. The sample is 

selected to be statistically representative of the 

civilian non-institutionalized U.S. population. The 

data presented in Table 16-117 and Table 16-118 are 

yearly averages for the year 2006–2007. 

Approximately 50,000 people are surveyed each 

month. 

Table 16-117 presents data on general mobility 

by demographic factors (i.e., sex, age, education, 

marital status, nativity, tenure, and poverty status). 

“Movers” are respondents who did not report living 

at the same residence 1 year earlier than the date of 

interview. Of the total number of respondents, 13% 

had moved residences. Of those, 65% moved within 

the same county. Table 16-118 presents data on these 

intercounty moves and shows that of these 

intercounty moves, over 60% moved less than 

200 miles. 

Advantages of this study are the large sample 

size, the currency of the data set, and its 

representativeness to the U.S. population. Limitations 

are that the study is based on recall data and that due 

to the Current Population Survey design, data for 

states are not as reliable as nationwide estimates. 

16.6. REFERENCES FOR CHAPTER 16 

Brownson, RC; Boehmer, TK; Luke, DA. (2005). 

Declining rates of physical activity in the 

United States: What are the contributors? 

Annu Rev Public Health 26: 421-443. 

http://dx.doi.org/10.1146/annurev.publhealth 

.26.021304.144437. 

Carey, M. (1990). Occupational tenure, employer 

tenure, and occupational mobility. Occup 

Outlook Q 34: 54-60. 

Carey, ML. (1988). Occupational tenure in 1987: 

Many workers have remained in their fields. 

Monthly Labor Review Online 111: 3. 

Chance, GW; Harmsen, E. (1998). Children are 

different: Environmental contaminants and 

children's health. Can J Public Health 89: 

S9-13, S10-15. 

Page Exposure Factors Handbook 

16-22 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cohen Hubal, EA; Sheldon, LS; Burke, JM; 

McCurdy, TR; Berry, MR; Rigas, ML; 

Zartarian, VG; Freeman, NC. (2000). 

Children's exposure assessment: A review of 

factors influencing children's exposure, and 

the data available to characterize and assess 

that exposure. Environ Health Perspect 108: 

475-486. 

Elgethun, K; Fenske, R; Yost, M; Palcisko, G. (2003). 

Time-location analysis for exposure 

assessment studies of children using a novel 

global positioning system instrument. 

Environ Health Perspect 111: 115-122. 

Funk, LM; Sedman, R; Beals, JAJ; Fountain, R. 

(1998). Quantifying the distribution of 

inhalation exposure in human populations: 2 

distributions of time spent by adults, 

adolescents, and children at home, at work, 

and at school. Risk Anal 18: 47-56. 

Garlock, TJ; Shirai, JH; Kissel, JC. (1999). Adult 

responses to a survey of soil contact-related 

behaviors. J Expo Anal Environ Epidemiol 

9: 134-142. 

Graham, SE; Mccurdy, T. (2004). Developing 

meaningful cohorts for human exposure 

models. J Expo Anal Environ Epidemiol 14: 

23-43. 

http://dx.doi.org/10.1038/sj.jea.7500293. 

Hill, MS. (1985). Patterns of time use. In FT Juster; 

FP Stafford (Eds.), Time, goods, and wellbeing (pp. 133–176). Ann Arbor, MI: 

University of Michigan. 

Israeli, M; Nelson, CB. (1992). Distribution and 

expected time of residence for US 

households. Risk Anal 12: 65-72. 

Johnson, T. (1989). Human activity patterns in 

Cincinnati, Ohio [final report]. (EN-6204). 

Palo Alto, CA: Electric Power Research 

Institute. 

Johnson, T; Capel, J. (1992). A Monte Carlo 

approach to simulating residential 

occupancy periods and its application to the 

general U.S. population [EPA Report]. 

(EPA-450/3-92-011). Research Triangle 

Park, NC: U.S. Environmental Protection 

Agency. 

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=2000MU7N.txt. 

Juster, FT; Hill, MS; Stafford, FP; Eccles Parsons, J. 

(1983). Time use longitudinal panel study, 

1975–1981. Ann Arbor, MI: of Michigan, 

Survey Research Center, Institute for Social 

Research. 

http://www.icpsr.umich.edu/icpsrweb/ICPS 

R/studies/09054. 

Juster, T; Ono, H; Stafford, F. (2004). Changing times 

of American youth: 1981–2003. Ann Arbor, 

MI: University of Michigan, Institute for 

Social Research. 

http://www.umich.edu/news/Releases/2004/ 

Nov04/teen_time_report.pdf. 

Mccurdy, T; Glen, G; Smith, L; Lakkadi, Y. (2000). 

The National Exposure Research 

Laboratory's consolidated human activity 

database. J Expo Sci Environ Epidemiol 10: 

566-578. 

Nader, PR; Bradley, RH; Houts, RM; Mcritchie, SL; 

O'Brien, M. (2008). Moderate-to-vigorous 

physical activity from ages 9 to 15 years. 

JAMA 300: 295-305. 

http://dx.doi.org/10.1001/jama.300.3.295. 

NAR (National Association of Realtors). (1993). The 

homebuying and selling process: 1993. In 

The Real Estate Business Series. 

Washington, DC: National Academy of 

Realtors. 

Phillips, ML; Hall, TA; Esmen, NA; Lynch, R; 

Johnson, DL. (2001). Use of global 

positioning system technology to track 

subject's location during environmental 

exposure sampling. J Expo Anal Environ 

Epidemiol 11: 207-215. 

http://dx.doi.org/10.1038/sj.jea.7500161. 

Robinson, JP; Thomas, J. (1991). Time spent in 

activities, locations, and microenvironments: 

a California-national comparison. Laurel, 

MD: General Sciences Corp. 

Stallings, C; Tippett, JA; Glen, G; Smith, L. (2002). 

CHAD user's guide: Extracting human 

activity information from CHAD on the PC. 

Research Triangle Park, NC: U.S. 

Environmental Protection Agency. 

http://www.epa.gov/chadnet1/reports/CHAD 

_Manual.pdf. 

Timmer, SG; Eccles, J; O'Brien, K. (1985). How 

children use time. In FT Juster; FP Stafford 

(Eds.), Time, goods, and well-being (pp. 

353-382). Ann Arbor, MI: Survey Research 

Center, Institute for Social Research, 

University of Michigan. 

U.S. Census Bureau. (2008a). American Housing 

Survey for the United States: 2007. 

Washington, DC: U.S. Government Printing 

Office. 

http://www.huduser.org/portal/datasets/ahs/a 

hsdata07.html. 

U.S.	 Census Bureau. (2008b). Current population 

survey, 2007 annual social and economic 

(ASEC) supplement. Washington, DC. 

Exposure Factors Handbook Page
 

November 2011 16-23 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-24 November 2011 

http://www.census.gov/apsd/techdoc/cps/cps 

mar07.pdf. 

U.S. Census Bureau. (2010). Current population 

survey, 2009 Annual Social and Economic 

(ASEC) supplement.

http://www.census.gov/apsd/techdoc/cps/cps 

mar09.pdf. 

U.S. Department of Labor. (2007). American time use 

survey – 2006. Results. News release, June 

28, 2007. Washington, DC: Bureau of Labor 

Statistics. 

http://www.bls.gov/news.release/archives/at 

us_06032008.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1996). Descriptive statistics from a detailed 

analysis of the National Human Activity 

Pattern Survey (NHAPS) responses. 

(EPA/600/R-96/148). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2009). Consolidated Human Activity 

Database. Available online at

http://www.epa.gov/chadnet1/ (accessed 

August 27, 2009). 

USDA (U.S. Department of Agriculture). (2005). 

Dietary guidelines for Americans, 2005. 

http://www.health.gov/dietaryguidelines/dga 

2005/document/pdf/DGA2005.pdf. 

Vandewater, EA; Shim, MS; Caplovitz, AG. (2004). 

Linking obesity and activity level with 

children's television and video game use. J 

Adolesc 27: 71-85. 

http://dx.doi.org/10.1016/j.adolescence.2003 

.10.003. 

Wiley, JA; Robinson, JP; Cheng, YT; Piazza, T; 

Stork, L; Pladsen, K. (1991). Study of 

children's activity patterns: Final report. 

(ARB-R-93/489). Sacramento, CA:

California Air Resources Board.

http://www.arb.ca.gov/research/apr/past/a73 

3-149a.pdf. 

Wong, EY; Shirai, JH; Garlock, TJ; Kissel, JC. 

(2000). Adult proxy responses to a survey of 

children's dermal soil contact activities. J 

Expo Anal Environ Epidemiol 10: 509-517. 
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-7. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity 

Categories, for All Respondents and Doers 

Activity Category 

Mean 

Duration 

(All) 

% 

Doersa 

Mean 

Duration 

(Doers)a 

Median 

Duration 

(Doers)a 

Maximum 

Duration 

(Doers)a 

Detailed Activity with 

Highest Average Minutes 

Work-relatedb 10 25 39 30 405 Eating at Work/School/Daycare 

Householdc 53 86 61 40 602 Travel to Household 

Childcared <1 <1 83 30 290 Other Child Care 

Good/Servicee 21 26 81 60 450 Errands 

Personal Needs and Caref 794 100 794 770 1,440 Night Sleep 

Educationg 110 35 316 335 790 School Classes 

Organizational Activitiesh 4 4 111 105 435 Attend Meetings 

Entertain/Sociali 15 17 87 60 490 Visiting with Others 

Recreationj 239 92 260 240 835 Games 

Communication/Passive 

Leisure k 192 93 205 180 898 TV Use 

Don’t know/Not coded 2 4 41 15 600 -

All Activities 1,440 - - - - - a Doers indicate the respondents who reported participating in each activity category. b Includes: travel to and during work/school; children’s paid work; eating at work/school/daycare; and accompanying or watching adult 

at work. c Includes: food preparation; meal cleanup; cleaning; clothes care; car and home repair/painting; building a fire; plant and pet care; and 

traveling to household. d Includes: baby and child care; helping/teaching children; talking and reading; playing while caring for children; medical care; travel 

related to child care; and other care. e Includes: shopping; medical appointments; obtaining personal care services (e.g., haircuts), government and financial services, and 

repairs; travel related to goods and services; and errands. f Includes: bathing, showering, and going to bathroom; medical care; help and care; meals; night sleep and daytime naps, dressing and 

grooming; and travel for personal care. g Includes: student and other classes; daycare; homework; library; and travel for education. h Includes: attending meetings and associated travel. i Includes: sports events; eating and amusements; movies and theater; visiting museums, zoos, art galleries, etc.; visiting others; parties 

and other social events; and travel to social activities. 

j Includes: active sports; leisure; hobbies; crafts; art; music/drama/dance; games; playing; and travel to leisure activities. k Includes: radio and television use; reading; conversation; paperwork; other passive leisure; and travel to passive leisure activities. 

Source: Wiley et al. (1991). 

Exposure Factors Handbook Page
 

November 2011 16-25 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-26 November 2011 

Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 

Ten Major Activity Categories, by Age and Sex 

Activity 

Categorya 

Boys 

Birth to 

1 Month 

1 to <3 

Months 

3 to <6 

Months 

6 to <12 

Months 

1 to <2 

Years 

2 to <3 

Years 

3 to <6 

Years 

6 to <11 

Years 

b 11 Years Birth to 11 

Years 

Work-related 

Household 

Childcare 

Goods/Services 

Personal Needs and Care 

Education 

Organizational Activities 

Entertainment/Social 

Recreation 

Communication/Passive 

Leisure 

Sample Sizes 

(Unweighted) 

0 

12 

0 

0 

910 

180c 

0 

0 

0 

338 

3 

0 

30 

0 

16 

1,143 

0 

0 

0 

0 

250 

7 

0 

49 

0 

14 

937 

75 

0 

0 

26 

339 

15 

1 

28 

0 

28 

919 

70 

0 

0 

104 

292 

31 

8 

35 

0 

27 

903 

33 

7 

8 

314 

106 

54 

9 

44 

0 

14 

889 

69 

0 

6 

304 

103 

62 

10 

44 

0 

28 

802 

67 

5 

15 

294 

175 

151 

12 

61 

0 

22 

726 

120 

11 

15 

265 

208 

239 

13 

63 

3 

24 

707 

120 

16 

43 

227 

226 

62 

11 

58 

2 

26 

802 

100 

6 

18 

228 

226 

624 

Activity 

Categorya 

Girls 

Birth to 1 

Month 

1 to <3 

Months 

3 to <6 

Months 

6 to <12 

Months 

1 to <2 

Years 

2 to <3 

Years 

3 to <6 

Years 

6 to <11 

Years 

b 11 Years Birth to 11 

Years 

Work-related 

Household 

Childcare 

Goods/Services 

Personal Needs and Care 

Education 

Organizational Activities 

Entertainment/Social 

Recreation 

Communication/Passive 

Leisure 

Sample Sizes 

(Unweighted) 

0 

28 

0 

0 

1,123 

0 

0 

0 

0 

290 

4 

0 

29 

0 

18 

1,115 

0 

0 

0 

0 

278 

10 

5 

23 

0 

14 

971 

110 

0 

0 

10 

308 

11 

1 

25 

0 

24 

922 

94 

0 

1 

147 

226 

23 

3 

45 

0 

24 

894 

25 

0 

13 

256 

179 

43 

22 

65 

0 

34 

858 

40 

2 

6 

305 

107 

50 

9 

49 

0 

31 

820 

81 

3 

16 

270 

161 

151 

10 

67 

2 

26 

747 

134 

8 

17 

224 

203 

225 

19 

78 

9 

15 

703 

151 

13 

52 

175 

225 

59 

11 

58 

2 

26 

802 

100 

6 

18 

228 

189 

576 a 

b 

c 

Note: 

Source: 

See Table 16-3 for a description of what is included in each activity category. 

The source data end at 11 years of age, so the 11 to <16 year category is truncated and the 16 to <21 year category is not i ncluded. 

The data for this age group and category are 2 values of 0 and 1 of 540. 

Column totals may not sum to 1,440 due to rounding. 

U.S. EPA analysis of source data used by Wiley et al. (1991). 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 

Ten Major Activity Categories, Grouped by Seasons and Regions 

Season Region of California 

Activity Categorya Winter Spring Summer Fall All Southern Rest of All 

(Jan–Mar) (Apr–June) (July–Sept) (Oct–Dec) Seasons Coast Bay Area State Regions 

Work-related 10 10 6 13 10 10 10 8 10 

Household 47 58 53 52 53 45 62 55 53 

Childcare <1 1 <1 <1 <1 <1 <1 1 <1 

Goods/Services 19 17 26 23 21 20 21 23 21 

Personal Needs and Care 799 774 815 789 794 799 785 794 794 

Education 124 137 49 131 110 109 115 109 110 

Organizational Activities 3 5 5 3 4 2 6 6 4 

Entertainment/Social 14 12 12 22 15 17 10 16 15 

Recreation 221 243 282 211 239 230 241 249 239 

Communication/ 

Passive Leisure 203 180 189 195 192 206 190 175 192 

Don’t know/Not coded <1 2 3 <1 2 1 1 3 2 

All Activitiesb 1,442 1,439 1,441 1,441 1,441 1,440 1,442 1,439 1,441 

Sample Sizes 

(Unweighted) 318 204 407 271 1,200 224 263 713 1,200 a See Table 16-3 for a description of what is included in each activity category. b The column totals may not be equal to 1,440 due to rounding. 

Source: Wiley et al. (1991). 

Table 16-10. Time (minutes/day) Children Under 12 Years of Age Spent in 

6 Major Location Categories, for All Respondents and Doers 

Location Category 

Mean 

Duration 

(All) 

% Doersa 

Mean 

Duration 

(Doers)a 

Median 

Duration 

(Doers)a 

Maximum 

Duration 

(Doers)a 

Detailed Location with 

Highest Average Time 

Home 1,078 99 1,086 1,110 1,440 Home – Bedroom 

School/Childcare 109 33 330 325 1,260 School or Daycare Facility 

Friend’s/Other’s House 80 32 251 144 1,440 Friend’s/Other’s House – Bedroom 

Stores, Restaurants, Shopping 

Places 24 35 69 50 475 Shopping Mall 

In-transit 69 83 83 60 1,111 Traveling in Car 

Other Locations 79 57 139 105 1,440 Park, Playground 

Don’t Know/Not Coded <1 1 37 30 90 -

All Locations 1,440 - - - - - a Doers indicate the respondents who reported participating in each activity category. 

Source: Wiley et al. (1991). 

Exposure Factors Handbook Page
 

November 2011 16-27 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-28 November 2011 

Table 16-11. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 

6 Location Categories, Grouped by Age and Sex 

Location Category 

Boys 

Birth to 

1 Month 

1 to <3 

Months 

3 to <6 

Months 

6 to <12 

Months 

1 to <2 2 to <3 

Years Years 

3 to <6 

Years 

6 to <11 

Years 11 Yearsa Birth to 11 Years 

Home 938 1,295 1,164 1,189 1,177 1,161 1,102 1,016 1,010 1,079 

School/Childcare 

Friend’s/Other’s House 

Stores, Restaurants, 

Shopping Places 

In-transit 

Other Locations 

Don’t Know/Not Coded 

Sample Sizes (Unweighted) 

0 

418 

0 

77 

7 

0 

3 

1 

40 

14 

51 

40 

0 

7 

26 

127 

21 

69 

33 

0 

15 

53 

63 

36 

63 

36 

0 

31 

73 

54 

29 

56 

52 

0 

54 

86 

69 

22 

61 

41 

0 

62 

79 

89 

24 

67 

78 

0 

151 

110 

110 

23 

64 

116 

0 

239 

99 

111 

20 

72 

127 

0 

62 

89 

95 

24 

65 

88 

0 

624 

Location Category 

Girls 

Birth to 1 

Month 

1 to <3 

Months 

3 to <6 

Months 

6 to <12 

Months 

1 to <2 

Years 

2 to <3 

Years 

3 to <6 

Years 

6 to <11 

Years 11 Yearsa Birth to 11 Years 

Home 

School/Childcare 

Friend’s/Other’s House 

Stores, Restaurants, 

Shopping Places 

In-transit 

Other Locations 

Don’t Know/Not Coded 

Sample Sizes (Unweighted) 

1,285 

0 

0 

0 

73 

83 

0 

4 

1,341 

0 

12 

13 

56 

19 

0 

10 

1,151 

109 

44 

20 

42 

73 

0 

11 

1,192 

99 

32 

15 

58 

43 

0 

23 

1,162 

56 

109 

21 

55 

38 

0 

43 

1,065 

61 

103 

40 

86 

86 

0 

50 

1,118 

78 

66 

32 

78 

67 

1 

151 

1,012 

116 

119 

25 

70 

97 

0 

225 

862 

128 

193 

24 

95 

137 

0 

59 

1,058 

95 

103 

27 

74 

84 

0 

576 a 

Note: 

Source: 

The source data end at 11 years of age, so the 11 to <16 year category is truncated and the 16 to <21 year category is not 

included. 

Column totals may not sum to 1,440 due to rounding. 

U.S. EPA analysis of source data used by Wiley et al. (1991). 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-29 

Table 16-12. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 

6 Location Categories, Grouped by Season and Region 

Location Category 

Season Region of California 

Winter 

(Jan–Mar) 

Spring 

(Apr–June) 

Summer 

(July–Sept) 

Fall 

(Oct–Dec) All Seasons 

Southern 

Coast 

Rest of 

Bay Area State All Regions 

Home 

School/Childcare 

Friend’s/Other’s House 

Stores, Restaurants, 

Shopping Places 

In transit 

Other Locations 

Don’t Know/Not Coded 

All Locationsa 

Sample Sizes 

(Unweighted N’s) 

1,091 

119 

69 

22 

75 

63 

<1 

1,439 

318 

1,042 

141 

75 

21 

75 

85 

<1 

1,439 

204 

1,097 

52 

108 

30 

60 

93 

<1 

1,440 

407 

1,081 

124 

69 

24 

65 

76 

<1 

1,439 

271 

1,078 

109 

80 

24 

69 

79 

<1 

1,439 

1,200 

1,078 

113 

73 

26 

71 

79 

<1 

1,439 

224 

1,078 

103 

86 

23 

73 

76 

<1 

1,440 

263 

1,078 

108 

86 

23 

63 

81 

<1 

1,440 

713 

1,078 

109 

80 

24 

69 

79 

<1 

1,439 

1,200 a 

Source: 

The column totals may not sum to 1,440 due to rounding. 

Wiley et al. (1991). 

 

 

 

 

 

Table 16-13. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 

Proximity to 2 Potential Sources of Exposure, Grouped by All Respondents, Age, and Sex 

Potential Exposures 

Boys 

Birth to 1 

Month 

1 to <3 

Months 

3 to <6 

Months 

6 to <12 

Months 

1 to <2 

Years 

2 to <3 

Years 

3 to <6 

Years 

6 to <11 

Years 11 Yearsa Birth to 11 Years 

Gasoline Fume 3 9 0 2 1 4 2 2 7 3 

Gas Oven Fume 0 0 2 2 1 3 0 1 0 1 

Sample Size 

(Unweighted N) 3 7 15 31 54 62 151 239 62 624 

Potential Exposure 

Girls 

Birth to 1 

Month 

1 to <3 

Months 

3 to <6 

Months 

6 to <12 

Months 

1 to <2 

Years 

2 to <3 

Years 

3 to <6 

Years 

6 to <11 

Years 11 Yearsa Birth to 11 Years 

Gasoline Fume 0 3 0 3 1 2 1 2 1 2 

Gas Oven Fume 0 0 0 0 0 3 2 1 0 1 

Sample Size 

(Unweighted N’) 4 10 11 23 43 50 151 225 59 576 a The source data end at 11 years of age, so the 11 to <16 year category is truncated and the 16 to <21 year category is not included. 

Source: U.S. EPA analysis of source data used by Wiley et al. (1991). 
 

c 

Table 16-14. Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors,
 

Grouped by Age and Sex
 

Boys Girls 

Age Group N Indoora Outdoor

b N Indoora Outdoorb 

Birth to <1 Month 3 1,440 0 4 1,440 0 

1 to <3 Months 7 1,432 8 10 1,431 9 

3 to <6 Months 15 1,407 33 11 1,421 19 

6 to <12 Months 31 1,322 118 23 1,280 160 

1 to <2 Years 54 1,101 339 43 1,164 276 

2 to <3 Years 62 1,121 319 50 1,102 338 

3 to <6 Years 151 1,117 323 151 1,140 300 

6 to <11 Years 239 1,145 295 225 1,183 255 

11 Years

c 62 1,166 274 59 1,215 225 

All Ages 624 1,181 258 576 1,181 258 a	 Time indoors was estimating by adding the average times spent performing indoor activities (household work, child care, personal 

needs and care, education, and communication/passive leisure) and half the time spent in each activity which could have occurred 

either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social, don’t know/not coded). b	 Time outdoors was estimated by adding the average time spent in recreation activities and half the time spent in each activity which 

could have occurred either indoors or outdoors (i.e., work-related, goods/services, organizational activities, entertainment/social, don’t 

know/not coded). 

The source data end at 11 years of age, so the 11 to <16 year category is truncated and the 16 to <21 year category is not included. 

N	 = Sample size. 

Note:	 Indoor and outdoor minutes/day may not sum to 1,440 minutes/day due to rounding. 

Source:	 U.S. EPA analysis of source data used by Wiley et al. (1991). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-30 November 2011 
Table 16-15. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined Whole 

Population and Doers Only, Children <21 Years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Kitchen―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

36 

56 

48 

47 

42 

37 

34 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

10 

40 

30 

30 

30 

24 

15 

70 

90 

75 

75 

60 

55 

50 

109 

132 

120 

105 

105 

90 

90 

125 

195 

146 

150 

135 

130 

130 

134 

232 

173 

180 

150 

180 

170 

158 

242 

188 

222 

196 

249 

195 

195 

392 

215 

362 

690 

450 

545 

Kitchen―Doers Only 

Birth to <1 

1 to <4 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

33 

76 

80 

252 

342 

323 

305 

69 

87 

70 

67 

61 

54 

54 

10 

10 

10 

2 

1 

1 

1 

10 

10 

10 

5 

2 

2 

2 

10 

13 

11 

10 

5 

4 

3 

13 

19 

15 

15 

10 

5 

5 

15 

30 

15 

15 

15 

10 

10 

30 

45 

30 

30 

30 

20 

20 

70 

70 

60 

60 

50 

40 

35 

90 

110 

105 

90 

79 

65 

65 

124 

173 

136 

133 

120 

114 

120 

133 

214 

155 

165 

145 

150 

159 

157 

240 

184 

210 

172 

218 

194 

176 

281 

195 

232 

229 

281 

209 

195 

392 

215 

362 

690 

450 

545 

Living Room/Family Room/Den―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

279 

172 

173 

164 

137 

170 

157 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

90 

25 

56 

45 

30 

36 

0 

210 

120 

138 

122 

95 

120 

120 

420 

279 

239 

240 

210 

240 

240 

666 

410 

346 

376 

322 

395 

370 

724 

533 

499 

476 

420 

570 

501 

788 

616 

599 

680 

547 

687 

690 

938 

652 

680 

742 

612 

774 

819 

1,180 

810 

1,125 

900 

695 

1,305 

1,080 

Living Room/Family Room/Den―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

54 

93 

105 

290 

403 

380 

352 

326 

219 

195 

202 

169 

209 

214 

25 

10 

1 

5 

5 

2 

5 

28 

15 

5 

8 

10 

10 

10 

31 

19 

10 

19 

10 

16 

15 

57 

25 

22 

30 

20 

30 

24 

90 

60 

34 

50 

30 

45 

40 

136 

90 

90 

90 

60 

85 

85 

268 

180 

150 

153 

130 

165 

165 

450 

310 

255 

270 

240 

275 

285 

686 

444 

377 

415 

349 

436 

440 

744 

540 

527 

498 

449 

594 

547 

789 

642 

603 

705 

579 

705 

720 

973 

667 

691 

778 

655 

776 

909 

1,180 

810 

1,125 

900 

695 

1,305 

1,080 

Dining Room―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

9 

19 

19 

17 

13 

11 

7 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

17 

30 

10 

5 

0 

0 

30 

60 

80 

60 

57 

33 

30 

70 

90 

105 

96 

70 

65 

45 

86 

176 

118 

133 

120 

119 

90 

96 

260 

146 

150 

135 

164 

112 

105 

315 

150 

300 

225 

390 

330 

Dining Room―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

9 

32 

34 

93 

126 

90 

67 

60 

72 

65 

65 

53 

59 

50 

15 

10 

15 

10 

5 

5 

5 

-

12 

15 

10 

5 

5 

5 

-

13 

15 

10 

5 

5 

7 

-

16 

18 

15 

6 

10 

15 

-

30 

29 

16 

15 

15 

15 

-

34 

30 

30 

30 

30 

20 

-

53 

60 

55 

45 

38 

35 

-

66 

90 

85 

60 

69 

60 

-

110 

105 

120 

98 

122 

90 

-

237 

134 

150 

135 

166 

124 

-

287 

150 

209 

150 

202 

135 

-

301 

150 

286 

196 

283 

201 

105 

315 

150 

300 

225 

390 

330 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-31 
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-15. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined Whole 

Population and Doers Only, Children <21 Years (continued) 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Bathroom―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

16 

26 

29 

22 

22 

20 

26 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

10 

0 

15 

20 

15 

15 

15 

20 

30 

30 

30 

30 

30 

30 

32 

40 

45 

60 

49 

45 

45 

59 

59 

60 

62 

65 

60 

60 

65 

81 

80 

138 

90 

81 

86 

105 

87 

239 

290 

120 

118 

97 

123 

90 

600 

345 

270 

535 

220 

547 

Bathroom―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

31 

77 

88 

240 

356 

335 

392 

32 

39 

38 

33 

31 

29 

31 

5 

6 

2 

1 

1 

1 

1 

7 

6 

3 

1 

2 

2 

2 

8 

8 

5 

2 

3 

2 

5 

10 

10 

12 

5 

5 

5 

5 

15 

15 

15 

11 

9 

6 

10 

18 

15 

15 

15 

15 

12 

15 

30 

30 

30 

30 

25 

20 

25 

40 

30 

45 

38 

35 

35 

40 

60 

57 

60 

60 

50 

50 

60 

78 

60 

70 

75 

60 

64 

72 

87 

176 

208 

112 

90 

90 

111 

89 

349 

319 

123 

180 

100 

135 

90 

600 

345 

270 

535 

220 

547 

Bedroom―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

749 

771 

701 

696 

653 

626 

588 

0 

0 

0 

0 

0 

0 

0 

0 

56 

5 

92 

0 

0 

0 

104 

340 

91 

210 

0 

20 

0 

468 

443 

419 

432 

304 

134 

60 

566 

559 

517 

540 

480 

403 

335 

653 

645 

618 

630 

585 

543 

475 

750 

808 

718 

695 

660 

645 

595 

863 

884 

835 

790 

735 

745 

720 

972 

975 

894 

875 

840 

860 

855 

1,092 

1,029 

931 

945 

906 

950 

960 

1,119 

1,190 

979 

1,033 

1,005 

1,027 

1,082 

1,179 

1,325 

990 

1,135 

1,096 

1,118 

1,146 

1,275 

1,440 

1,040 

1,440 

1,440 

1,277 

1,375 

Bedroom―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

61 

116 

116 

353 

486 

457 

463 

774 

785 

713 

704 

667 

638 

611 

435 

330 

30 

165 

120 

15 

15 

453 

362 

215 

210 

183 

55 

34 

470 

384 

266 

268 

261 

115 

100 

495 

450 

484 

464 

439 

179 

273 

590 

570 

520 

540 

513 

430 

395 

660 

656 

620 

630 

599 

550 

480 

750 

810 

720 

695 

660 

646 

600 

865 

885 

836 

790 

735 

750 

725 

975 

975 

896 

875 

843 

860 

859 

1,095 

1,030 

931 

945 

912 

951 

974 

1,119 

1,191 

981 

1,034 

1,005 

1,029 

1,090 

1,182 

1,328 

990 

1,137 

1,100 

1,122 

1,147 

1,275 

1,440 

1,040 

1,440 

1,440 

1,277 

1,375 

Garage―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

1 

0 

0 

1 

0 

2 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

19 

0 

34 

0 

0 

7 

0 

51 

0 

89 

0 

0 

165 

120 

240 

60 

Garage―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

1 

0 

0 

4 

3 

12 

4 

-

-

-

-

-

79 

-

89 

-

-

15 

30 

10 

10 

-

-

-

-

-

11 

-

-

-

-

-

-

11 

-

-

-

-

-

-

13 

-

-

-

-

-

-

16 

-

-

-

-

-

-

20 

-

-

-

-

-

-

40 

-

-

-

-

-

-

139 

-

-

-

-

-

-

183 

-

-

-

-

-

-

210 

-

-

-

-

-

-

228 

-

-

-

-

-

-

234 

-

89 

-

-

165 

120 

240 

60 

Page Exposure Factors Handbook 

16-32 November 2011 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-15. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined Whole 

Population and Doers Only, Children <21 Years (continued) 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

All Rooms Combined―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

1,091 

1,047 

971 

951 

873 

876 

819 

0 

0 

0 

0 

0 

0 

0 

391 

63 

66 

284 

0 

0 

0 

631 

377 

342 

402 

0 

117 

165 

742 

651 

640 

621 

420 

370 

375 

786 

705 

727 

716 

631 

575 

510 

943 

915 

852 

810 

758 

751 

645 

1,105 

1,050 

995 

930 

880 

871 

810 

1,258 

1,239 

1,120 

1,110 

1,005 

1,043 

995 

1,440 

1,440 

1,232 

1,245 

1,175 

1,215 

1,170 

1,440 

1,440 

1,295 

1,354 

1,275 

1,314 

1,287 

1,440 

1,440 

1,354 

1,440 

1,374 

1,440 

1,419 

1,440 

1,440 

1,369 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

All Rooms Combined—Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

62 

116 

117 

355 

486 

459 

473 

1,108 

1,065 

979 

957 

893 

889 

833 

630 

370 

30 

150 

190 

40 

85 

633 

399 

288 

352 

335 

141 

206 

658 

495 

551 

451 

389 

300 

321 

751 

674 

650 

634 

541 

441 

433 

821 

715 

746 

720 

655 

590 

525 

956 

923 

857 

810 

765 

758 

660 

1,108 

1,050 

1,005 

930 

885 

875 

815 

1,259 

1,243 

1,120 

1,110 

1,009 

1,046 

1,000 

1,440 

1,440 

1,232 

1,245 

1,177 

1,218 

1,170 

1,440 

1,440 

1,296 

1,355 

1,275 

1,315 

1,288 

1,440 

1,440 

1,355 

1,440 

1,385 

1,440 

1,420 

1,440 

1,440 

1,369 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

N = Sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes less than 10. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-33 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-34 November 2011 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only 

Kitchen 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

7,063 

2,988 

4,072 

3 

144 

335 

477 

396 

4,531 

1,180 

5,827 

641 

113 

119 

266 

97 

6,458 

497 

32 

76 

1,200 

2,965 

608 

2,239 

51 

1,346 

678 

2,043 

1,348 

933 

715 

1,645 

1,601 

2,383 

1,434 

4,849 

2,214 

1,938 

1,780 

1,890 

1,455 

6,510 

503 

50 

6,798 

207 

58 

6,671 

338 

54 

92.6 

75.0 

105.6 

40.0 

102.7 

73.7 

60.5 

55.0 

90.3 

131.4 

95.1 

79.4 

89.4 

69.1 

84.2 

90.3 

93.4 

83.9 

82.3 

88.4 

62.3 

77.7 

97.7 

126.9 

106.4 

63.9 

108.1 

107.2 

94.4 

91.9 

88.2 

99.6 

96.1 

86.3 

91.4 

90.1 

98.3 

96.6 

89.0 

89.3 

96.2 

92.4 

94.0 

104.4 

91.6 

122.5 

105.9 

91.8 

104.8 

117.9 

94.2 

80.8 

101.0 

31.2 

110.8 

54.4 

53.0 

58.1 

90.9 

119.6 

95.2 

92.0 

95.5 

60.8 

77.3 

113.6 

94.8 

82.9 

71.9 

118.6 

55.4 

77.5 

94.0 

115.8 

168.5 

62.3 

102.9 

102.3 

101.2 

92.1 

87.7 

99.7 

93.6 

87.1 

99.1 

92.2 

98.2 

100.3 

90.2 

91.0 

94.5 

93.6 

96.0 

143.7 

93.0 

111.4 

138.4 

92.6 

113.4 

142.4 

1.1 

1.5 

1.6 

18.0 

9.2 

3.0 

2.4 

2.9 

1.4 

3.5 

1.2 

3.6 

9.0 

5.6 

4.7 

11.5 

1.2 

3.7 

12.7 

13.6 

1.6 

1.4 

3.8 

2.4 

23.6 

1.7 

4.0 

2.3 

2.8 

3.0 

3.3 

2.5 

2.3 

1.8 

2.6 

1.3 

2.1 

2.3 

2.1 

2.1 

2.5 

1.2 

4.3 

20.3 

1.1 

7.7 

18.2 

1.1 

6.2 

19.4 

1 

1 

1 

15 

5 

5 

1 

1 

1 

3 

1 

2 

5 

2 

1 

5 

1 

1 

5 

5 

1 

1 

1 

1 

2 

1 

1 

1 

1 

2 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

7 

1 

4 

2 

1 

1 

2 

1,320 

840 

1,320 

75 

840 

392 

690 

450 

1,320 

825 

840 

1,320 

690 

315 

585 

880 

1,320 

675 

300 

880 

690 

840 

755 

1,320 

880 

880 

775 

840 

1,320 

840 

770 

840 

833 

880 

1,320 

1,320 

840 

1,320 

840 

880 

770 

1,320 

785 

880 

1,320 

657 

880 

1,320 

825 

880 

10 

10 

10 

15 

15 

15 

10 

5 

10 

15 

10 

10 

10 

7 

10 

7 

10 

10 

10 

7 

10 

10 

10 

12 

5 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

30 

30 

35 

15 

30 

30 

30 

15 

30 

49 

30 

30 

30 

30 

30 

30 

30 

30 

35 

30 

30 

30 

30 

45 

30 

30 

34 

35 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

45 

30 

30 

30 

30 

60 

55 

75 

30 

70 

60 

50 

36 

60 

100 

65 

60 

75 

55 

60 

60 

60 

60 

60 

60 

50 

60 

70 

95 

48 

50 

80 

75 

60 

60 

60 

70 

65 

60 

60 

60 

66 

65 

60 

60 

65 

60 

60 

60 

60 

100 

60 

60 

71 

76 

120 

90 

145 

75 

130 

100 

75 

65 

120 

172 

120 

100 

115 

90 

110 

90 

120 

110 

113 

90 

85 

100 

134 

175 

130 

85 

150 

150 

120 

120 

113 

130 

125 

115 

119 

119 

135 

120 

120 

120 

125 

120 

120 

120 

120 

155 

135 

120 

135 

160 

205 

155 

230 

75 

215 

140 

120 

125 

200 

275 

210 

175 

150 

150 

190 

190 

210 

180 

185 

190 

125 

165 

213 

270 

210 

130 

230 

235 

210 

200 

190 

210 

213 

190 

195 

195 

220 

210 

195 

195 

210 

205 

210 

195 

200 

255 

240 

200 

225 

240 

270 

215 

295 

75 

260 

180 

150 

155 

260 

360 

273 

230 

220 

195 

240 

275 

270 

240 

240 

240 

153 

225 

270 

342 

250 

165 

295 

300 

280 

261 

260 

300 

270 

245 

255 

255 

280 

285 

255 

255 

275 

270 

270 

240 

265 

360 

240 

265 

300 

275 

365 

300 

395 

75 

485 

225 

180 

240 

345 

490 

380 

275 

265 

210 

305 

480 

370 

315 

300 

480 

213 

300 

405 

470 

840 

235 

405 

415 

380 

330 

380 

390 

355 

330 

380 

360 

390 

390 

350 

362 

375 

365 

345 

713 

360 

415 

545 

360 

480 

545 

460 

392 

475 

75 

540 

240 

235 

340 

420 

620 

465 

380 

650 

315 

360 

880 

460 

415 

300 

880 

260 

376 

445 

545 

880 

285 

545 

500 

450 

410 

405 

465 

450 

420 

480 

450 

480 

485 

420 

430 

470 

450 

450 

880 

450 

620 

880 

445 

657 

880 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only 

(continued) 

Bathroom 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 6,661 35.0 48.8 0.6 1 870 5 15 25 40 60 90 137 255 

Sex Male 3,006 32.7 50.4 0.9 1 870 5 15 21 35 60 75 150 300 

Sex Female 3,653 36.9 47.4 0.8 1 665 5 15 30 45 70 90 135 240 

Sex Refused 2 27.5 3.5 2.5 25 30 25 25 28 30 30 30 30 30 

Age (years) - 122 43.9 67.0 6.1 2 530 5 15 30 45 85 120 300 360 

Age (years) 1 to 4 328 35.9 46.5 2.6 1 600 10 15 30 40 60 75 125 270 

Age (years) 5 to 11 490 31.0 38.6 1.7 1 535 5 15 27 35 53 60 100 200 

Age (years) 12 to 17 445 29.1 32.9 1.6 1 547 5 15 20 35 60 65 90 100 

Age (years) 18 to 64 4,486 34.5 46.1 0.7 1 665 5 15 25 40 60 90 135 250 

Age (years) >64 790 42.2 69.4 2.5 1 870 5 15 30 45 75 120 240 360 

Race White 5,338 34.3 48.6 0.7 1 870 5 15 25 40 60 85 135 255 

Race Black 711 36.9 39.6 1.5 1 460 5 15 30 45 70 98 135 186 

Race Asian 117 33.6 41.4 3.8 5 375 5 15 25 40 60 90 110 210 

Race Some Others 134 47.3 69.6 6.0 1 535 5 15 30 45 95 120 315 422 

Race Hispanic 283 38.6 61.5 3.7 1 546 5 15 24 45 60 80 270 425 

Race Refused 78 34.6 49.2 5.6 3 360 5 10 20 35 60 135 165 360 

Hispanic No 6,067 34.5 45.9 0.6 1 705 5 15 25 40 60 90 135 240 

Hispanic Yes 498 39.2 68.6 3.1 1 870 5 15 25 45 60 90 270 425 

Hispanic DK 33 44.4 72.3 12.6 5 422 10 15 30 45 60 120 422 422 

Hispanic Refused 63 44.1 95.2 12.0 3 665 5 10 20 35 60 150 360 665 

Employment - 1,240 32.0 39.7 1.1 1 600 5 15 30 35 60 70 100 180 

Employment Full Time 3,130 33.4 44.8 0.8 1 595 5 15 25 40 60 80 123 240 

Employment Part Time 583 35.5 43.9 1.8 1 430 5 15 29 45 60 90 140 270 

Employment Not Employed 1,661 40.2 61.6 1.5 1 870 5 15 30 45 75 110 210 340 

Employment Refused 47 34.7 54.8 8.0 3 360 5 15 25 30 55 75 360 360 

Education - 1,386 32.2 42.8 1.1 1 665 5 15 25 35 60 70 110 200 

Education < High School 522 40.9 64.5 2.8 1 870 5 15 30 45 70 100 240 350 

Education High School Graduate 1,857 35.8 50.2 1.2 1 600 5 15 25 40 63 90 135 270 

Education < College 1,305 36.1 44.1 1.2 1 540 5 15 25 45 70 95 150 225 

Education College Graduate 913 35.0 54.1 1.8 1 705 5 15 20 40 60 90 150 340 

Education Post Graduate 678 32.1 42.8 1.6 1 460 5 15 22 40 60 75 110 300 

Census Region Northeast 1,497 34.3 51.2 1.3 1 600 5 15 25 40 60 80 140 335 

Census Region Midwest 1,465 35.8 54.5 1.4 1 870 5 15 25 40 60 90 145 315 

Census Region South 2,340 35.1 42.0 0.9 1 510 5 15 30 40 60 90 135 214 

Census Region West 1,359 34.9 50.4 1.4 1 705 5 15 25 40 60 90 140 250 

Day Of Week Weekday 4,613 33.9 46.7 0.7 1 870 5 15 25 40 60 85 135 240 

Day Of Week Weekend 2,048 37.5 53.2 1.2 1 600 5 15 30 45 65 90 150 300 

Season Winter 1,853 37.0 50.7 1.2 1 665 5 15 30 42 65 90 150 270 

Season Spring 1,747 36.6 50.5 1.2 1 870 5 15 30 45 60 90 135 240 

Season Summer 1,772 32.8 44.5 1.1 1 570 5 15 25 38 60 80 135 210 

Season Fall 1,289 33.0 49.1 1.4 1 540 5 11 20 35 60 90 140 303 

Asthma No 6,132 34.9 48.8 0.6 1 870 5 15 25 40 60 90 135 255 

Asthma Yes 493 35.2 38.2 1.7 1 410 5 15 30 45 65 90 140 220 

Asthma DK 36 49.5 121.1 20.2 3 665 5 10 18 30 60 360 665 665 

Angina No 6,473 34.6 46.8 0.6 1 870 5 15 25 40 60 90 135 240 

Angina Yes 145 51.9 88.3 7.3 3 600 7 20 30 45 75 185 546 570 

Angina DK 43 44.9 111.2 17.0 3 665 5 10 15 30 50 110 665 665 

Bronchitis/Emphysema No 6,327 34.8 48.1 0.6 1 870 5 15 25 40 60 90 135 255 

Bronchitis/Emphysema Yes 296 36.8 47.5 2.8 1 600 5 15 30 44 60 90 180 250 

Bronchitis/Emphysema DK 38 54.6 122.7 19.9 3 665 5 10 17.5 30 110 360 665 665 

Exposure Factors Handbook Page
 

November 2011 16-35 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-36 November 2011 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only 

(continued) 

Bedroom 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 9,151 563.1 184.6 1.9 3 1,440 300 460 540 660 780 880 1,005 1,141 

Sex Male 4,157 549.6 183.0 2.8 3 1,440 285 450 540 640 780 860 980 1,095 

Sex Female 4,990 574.3 185.3 2.6 5 1,440 312 470 555 660 790 900 1,030 1,185 

Sex Refused 4 648.8 122.8 61.4 540 785 540 545 635 753 785 785 785 785 

Age (years) - 184 525.1 193.5 14.3 15 1,440 195 420 513 600 720 860 950 1,295 

Age (years) 1 to 4 488 742.0 167.1 7.6 30 1,440 489 635 740 840 930 990 1,095 1,200 

Age (years) 5 to 11 689 669.1 162.9 6.2 35 1,440 435 600 665 740 840 915 1,065 1,140 

Age (years) 12 to 17 577 636.2 210.9 8.8 15 1,375 165 542 645 750 875 970 1,040 1,210 

Age (years) 18 to 64 5,891 532.7 173.0 2.3 3 1,440 295 440 520 610 723 820 975 1,110 

Age (years) >64 1,322 550.8 172.0 4.7 15 1,440 315 475 540 610 735 840 1,000 1,140 

Race White 7,403 553.4 175.9 2.0 3 1,440 300 455 540 640 760 850 975 1,105 

Race Black 923 612.3 219.9 7.2 15 1,440 300 480 597 725 895 990 1,160 1,323 

Race Asian 153 612.3 187.4 15.2 25 1,285 345 510 600 705 830 950 1,005 1,245 

Race Some Others 174 590.7 200.2 15.2 15 1,405 300 464 580 700 830 960 1,050 1,152 

Race Hispanic 378 602.6 214.4 11.0 25 1,440 265 480 588 720 865 958 1,095 1,213 

Race Refused 120 555.8 198.6 18.1 30 1,405 285 440 534 630 763 875 1,290 1,295 

Hispanic No 8,326 560.9 182.6 2.0 3 1,440 300 460 540 650 780 870 1,000 1,140 

Hispanic Yes 684 597.4 206.3 7.9 15 1,440 300 480 585 713 840 958 1,095 1,200 

Hispanic DK 43 542.3 169.9 25.9 135 1,002 300 420 555 660 756 830 1,002 1,002 

Hispanic Refused 98 523.4 180.2 18.2 30 1,295 255 415 515 600 735 795 930 1,295 

Employment - 1,736 679.5 185.5 4.5 15 1,440 390 590 675 785 892 960 1,065 1,170 

Employment Full Time 3,992 513.5 157.6 2.5 3 1,440 283 435 510 585 680 765 890 1,000 

Employment Part Time 777 551.6 169.4 6.1 15 1,335 330 455 540 630 750 835 1,005 1,100 

Employment Not Employed 2,578 566.4 191.2 3.8 5 1,440 300 478 540 650 780 905 1,095 1,223 

Employment Refused 68 514.0 209.6 25.4 30 1,440 210 420 498 585 725 795 1,200 1,440 

Education - 1,925 668.3 188.8 4.3 15 1,440 360 575 663 780 885 960 1,060 1,170 

Education < High School 807 554.8 180.6 6.4 5 1,440 300 450 540 630 775 860 1,015 1,160 

Education High School Graduate 2,549 534.1 176.2 3.5 3 1,440 285 447 520 607 720 835 975 1,151 

Education < College 1,740 539.1 176.1 4.2 5 1,440 282 450 530 615 735 825 1,005 1,135 

Education College Graduate 1,223 526.0 164.9 4.7 15 1,404 300 445 515 600 713 785 965 1,070 

Education Post Graduate 907 525.2 160.6 5.3 3 1,355 315 445 510 600 690 780 950 1,095 

Census Region Northeast 2,037 561.5 185.3 4.1 5 1,440 300 457 540 655 781 885 1,020 1,139 

Census Region Midwest 2,045 552.4 179.2 4.0 3 1,440 280 450 540 643 765 860 965 1,035 

Census Region South 3,156 570.0 186.4 3.3 10 1,440 300 465 552 660 790 900 1,055 1,155 

Census Region West 1,913 564.9 186.4 4.3 5 1,440 305 460 540 660 793 875 995 1,152 

Day Of Week Weekday 6,169 552.6 174.5 2.2 3 1,440 325 450 539 635 760 855 975 1,130 

Day Of Week Weekend 2,982 584.9 202.4 3.7 3 1,440 223 480 570 690 825 920 1,055 1,170 

Season Winter 2,475 576.0 183.8 3.7 5 1,440 305 475 555 660 805 900 1,035 1,148 

Season Spring 2,365 559.0 176.7 3.6 15 1,440 315 455 540 655 770 855 960 1,095 

Season Summer 2,461 566.1 195.2 3.9 3 1,440 285 455 545 660 810 900 1,030 1,190 

Season Fall 1,850 547.2 179.9 4.2 3 1,440 270 450 538 630 750 850 960 1,100 

Asthma No 8,420 560.8 182.8 2.0 3 1,440 300 460 540 655 780 870 1,000 1,140 

Asthma Yes 671 593.8 201.5 7.8 30 1,440 300 475 580 690 835 946 1,060 1,327 

Asthma DK 60 543.1 218.4 28.2 30 1,295 223 423 540 605 760 983 1,275 1,295 

Angina No 8,836 564.2 183.9 2.0 3 1,440 300 460 540 660 785 880 1,005 1,140 

Angina Yes 244 535.5 203.9 13.1 20 1,440 215 450 523 613 770 840 1,135 1,230 

Angina DK 71 522.1 193.9 23.0 30 1,295 180 420 540 600 690 820 990 1,295 

Bronchitis/Emphysema No 8,660 563.1 184.2 2.0 3 1,440 300 460 540 660 780 880 1,005 1,141 

Bronchitis/Emphysema Yes 423 570.1 192.0 9.3 15 1,440 294 450 555 660 795 900 1,055 1,110 

Bronchitis/Emphysema DK 68 524.8 186.7 22.6 30 1,295 240 420 540 600 700 820 930 1,295 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-37 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only 

(continued) 

Garage 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 193 117.8 144.5 10.4 1 790 5 20 60 150 296 480 665 690 

Sex Male 120 144.1 162.6 14.8 2 790 10 30 94 183 315 518 675 690 

Sex Female 73 74.6 94.3 11.0 1 530 5 15 30 120 180 240 450 530 

Age (years) - 1 20.0 - - 20 20 20 20 20 20 20 20 20 20 

Age (years) 1 to 4 4 83.5 47.5 23.7 15 120 15 52 100 115 120 120 120 120 

Age (years) 5 to 11 6 63.3 63.4 25.9 10 165 10 25 30 120 165 165 165 165 

Age (years) 12 to 17 12 80.8 78.4 22.6 10 240 10 20 51 148 185 240 240 240 

Age (years) 18 to 64 130 134.5 165.1 14.5 1 790 5 20 68 180 360 526 675 690 

Age (years) >64 40 88.6 84.1 13.3 5 300 8 25 60 143 228 270 300 300 

Race White 165 109.5 127.5 9.9 1 690 5 20 60 135 240 315 526 675 

Race Black 12 205.0 219.5 63.4 5 570 5 38 90 405 530 570 570 570 

Race Asian 1 5.0 - - 5 5 5 5 5 5 5 5 5 5 

Race Some Others 6 186.3 308.4 125.9 10 790 10 18 30 240 790 790 790 790 

Race Hispanic 8 120.0 164.9 58.3 15 510 15 23 60 135 510 510 510 510 

Race Refused 1 120.0 - - 120 120 120 120 120 120 120 120 120 120 

Hispanic No 174 116.6 138.5 10.5 1 690 5 20 60 155 296 460 570 675 

Hispanic Yes 17 128.6 207.3 50.3 5 790 5 20 60 110 510 790 790 790 

Hispanic Refused 2 127.5 10.6 7.5 120 135 120 120 128 135 135 135 135 135 

Employment - 21 79.7 67.5 14.7 10 240 15 25 51 120 165 185 240 240 

Employment Full Time 85 145.3 175.2 19.0 1 790 5 20 65 180 405 530 675 790 

Employment Part Time 17 50.1 52.0 12.6 5 194 5 15 30 60 135 194 194 194 

Employment Not Employed 70 112.3 127.4 15.2 5 690 5 30 75 135 255 450 480 690 

Education - 22 76.5 67.6 14.4 10 240 10 20 51 120 165 185 240 240 

Education < High School 14 188.9 195.0 52.1 5 675 5 30 120 235 510 675 675 675 

Education High School Graduate 63 127.3 159.3 20.1 2 690 5 25 60 165 300 530 665 690 

Education < College 48 121.6 147.8 21.3 5 790 10 30 60 140 296 450 790 790 

Education College Graduate 25 118.2 145.8 29.2 5 480 5 20 60 120 405 460 480 480 

Education Post Graduate 21 75.9 88.1 19.2 1 300 2 10 30 120 195 260 300 300 

Census Region Northeast 23 137.2 159.5 33.2 5 510 15 30 60 195 460 510 510 510 

Census Region Midwest 42 131.4 166.4 25.7 10 690 20 40 88 120 260 665 690 690 

Census Region South 60 103.7 128.6 16.6 2 570 5 13 53 128 283 428 480 570 

Census Region West 68 115.3 139.7 16.9 1 790 5 20 73 153 300 315 530 790 

Day Of Week Weekday 116 128.7 159.0 14.8 1 790 5 25 60 165 315 510 665 690 

Day Of Week Weekend 77 101.4 118.4 13.5 2 675 10 20 60 120 240 300 526 675 

Season Winter 51 115.6 161.8 22.7 2 690 5 15 50 150 240 526 665 690 

Season Spring 59 136.8 163.3 21.3 5 790 10 30 90 165 315 570 675 790 

Season Summer 51 101.1 121.3 17.0 1 530 5 20 60 120 260 450 460 530 

Season Fall 32 112.9 110.2 19.5 5 480 10 25 85 158 240 315 480 480 

Asthma No 184 118.6 146.3 10.8 1 790 5 25 60 150 300 480 665 690 

Asthma Yes 9 101.1 102.6 34.2 5 270 5 15 60 180 270 270 270 270 

Angina No 187 118.2 146.2 10.7 1 790 5 20 60 150 300 480 665 690 

Angina Yes 6 104.2 78.6 32.1 10 220 10 25 110 150 220 220 220 220 

Bronchitis/Emphysema No 185 114.1 142.9 10.5 1 790 5 20 60 135 260 480 665 690 

Bronchitis/Emphysema Yes 8 201.9 163.6 57.9 15 450 15 60 178 338 450 450 450 450 
 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only (continued) 

Basement 

Category Population Group N Mean SD SE Min Max 

Percentiles 

5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

274 

132 

141 

1 

3 

8 

25 

26 

170 

42 

248 

15 

2 

3 

1 

5 

263 

6 

1 

4 

57 

107 

22 

85 

3 

65 

15 

78 

48 

39 

29 

90 

123 

35 

26 

178 

96 

80 

65 

79 

50 

253 

20 

1 

269 

3 

2 

265 

8 

1 

142.2 

160.4 

125.7 

60.0 

171.7 

94.8 

135.4 

97.5 

151.3 

143.8 

133.8 

183.8 

135.0 

468.7 

30.0 

263.2 

139.0 

185.0 

185.0 

271.3 

115.6 

149.1 

115.0 

158.0 

151.7 

129.5 

169.9 

159.4 

160.6 

146.7 

73.1 

115.6 

129.0 

188.0 

234.4 

135.3 

154.8 

144.5 

174.2 

142.4 

96.4 

143.1 

124.7 

245.0 

141.4 

201.7 

152.5 

139.0 

233.8 

245.0 

162.9 

180.7 

143.3 

-

122.7 

55.7 

145.9 

113.1 

172.7 

173.5 

154.1 

165.5 

106.1 

455.7 

-

173.1 

161.7 

197.3 

-

198.8 

124.2 

178.6 

114.8 

176.3 

110.3 

133.4 

203.5 

188.7 

184.2 

150.8 

66.3 

118.7 

146.9 

205.8 

247.7 

159.4 

169.3 

147.0 

196.8 

180.7 

83.1 

164.2 

151.0 

-

163.7 

122.1 

130.8 

161.0 

214.2 

-

9.8 

15.7 

12.1 

-

70.8 

19.7 

29.2 

22.2 

13.2 

26.8 

9.8 

42.7 

75.0 

263.1 

-

77.4 

10.0 

80.6 

-

99.4 

16.5 

17.3 

24.5 

19.1 

63.7 

16.6 

52.5 

21.4 

26.6 

24.1 

12.3 

12.5 

13.2 

34.8 

48.6 

11.9 

17.3 

16.4 

24.4 

20.3 

11.7 

10.3 

33.8 

-

10.0 

70.5 

92.5 

9.9 

75.7 

-

1 

1 

2 

60 

30 

28 

15 

1 

1 

5 

1 

12 

60 

20 

30 

60 

1 

15 

185 

60 

1 

1 

10 

5 

30 

1 

5 

5 

2 

10 

1 

5 

2 

10 

1 

1 

5 

5 

1 

1 

5 

1 

1 

245 

1 

65 

60 

1 

20 

245 

931 

931 

810 

60

245 

180 

705 

515 

810 

931 

810 

515 

210 

931 

30

540 

931 

555 

185 

540 

705 

810 

535 

931 

245 

705 

605 

810 

931 

555 

245 

555 

765 

931 

810 

810 

931 

630 

931 

765 

332 

931 

510 

245 

931 

300 

245 

931 

605 

245 

10 

10 

10 

60 

30 

28 

15 

10 

5 

10 

10 

12 

60 

20 

30 

60 

10 

15 

185 

60 

12 

5 

25 

10 

30 

15 

5 

5 

10 

10 

10 

10 

10 

28 

1 

10 

10 

14 

5 

5 

10 

10 

6 

245 

10 

65 

60 

10 

20 

245 

30 

40 

30 

60 

30 

48 

60 

30 

30 

40 

30 

40 

60 

20 

30 

231 

30 

30 

185 

150 

40 

30 

60 

35 

30 

45 

30 

40 

25 

30 

30 

40 

30 

45 

30 

30 

50 

30 

60 

30 

30 

35 

16 

245 

30 

65 

60 

30 

68 

245 

90 

90 

75 

60 

240 

90 

105 

60 

90 

90 

90 

150 

135 

455 

30 

240 

90 

150 

185 

243 

90 

75 

78 

120 

180 

90 

90 

90 

120 

70 

60 

73 

90 

110 

165 

83 

98 

90 

105 

85 

60 

90 

73 

245 

90 

240 

153 

90 

180 

245 

180 

203 

175 

60 

245 

138 

140 

150 

210 

170 

168 

270 

210 

931 

30 

245 

180 

210 

185 

393 

150 

210 

150 

210 

245 

160 

255 

195 

203 

210 

100 

150 

180 

255 

325 

180 

190 

221 

210 

150 

145 

180 

178 

245 

180 

300 

245 

180 

375 

245 

330 

490 

265 

60

245 

180 

270 

240 

410 

330 

315 

450 

210 

931 

30

540 

330 

555 

185 

540 

240 

450 

185 

330 

245 

270 

565 

420 

400 

450 

210 

250 

270 

450 

705 

315 

450 

315 

490 

455 

240 

330 

383 

245 

330 

300 

245 

330 

605 

245 

535 

565 

420 

60

245 

180 

420 

275 

555 

455 

510 

515 

210 

931 

30

540 

510 

555 

185 

540 

420 

540 

290 

600 

245 

420 

605 

720 

600 

510 

210 

400 

510 

720 

720 

535 

540 

480 

555 

605 

255 

540 

510 

245 

535 

300 

245 

515 

605 

245 

705 

720 

705 

60 

245 

180 

705 

515 

720 

931 

705 

515 

210 

931 

30 

540 

705 

555 

185 

540 

515 

720 

535 

720 

245 

535 

605 

765 

931 

555 

245 

540 

605 

931 

810 

720 

600 

610 

810 

720 

301 

705 

510 

245 

705 

300 

245 

705 

605 

245 

765 

765 

720 

60 

245 

180 

705 

515 

765 

931 

720 

515 

210 

931 

30 

540 

765 

555 

185 

540 

705 

765 

535 

931 

245 

705 

605 

810 

931 

555 

245 

555 

630 

931 

810 

765 

931 

630 

931 

765 

332 

765 

510 

245 

765 

300 

245 

765 

605 

245 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-38 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-39 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only 

(continued) 

Utility/Laundry Room 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 458 73.2 71.9 3.4 1 510 5 25 60 100 150 200 300 360 

Sex Male 70 78.4 95.7 11.4 1 510 5 20 60 90 168 345 360 510 

Sex Female 388 72.3 66.8 3.4 2 510 5 28 60 105 150 190 240 330 

Age (years) - 6 65.8 34.4 14.0 25 120 25 40 60 90 120 120 120 120 

Age (years) 1 to 4 3 75.0 116.9 67.5 5 210 5 5 10 210 210 210 210 210 

Age (years) 5 to 11 3 105.7 168.4 97.2 2 300 2 2 15 300 300 300 300 300 

Age (years) 12 to 17 8 55.5 77.1 27.3 1 240 1 17 33 53 240 240 240 240 

Age (years) 18 to 64 362 73.6 73.9 3.9 2 510 5 20 60 105 150 195 325 405 

Age (years) >64 76 72.6 58.1 6.7 2 345 10 30 60 90 150 180 245 345 

Race White 400 69.2 65.8 3.3 2 510 5 25 60 90 150 180 258 353 

Race Black 35 100.5 103.2 17.5 1 510 5 20 60 135 240 300 510 510 

Race Asian 4 82.5 37.7 18.9 30 120 30 60 90 105 120 120 120 120 

Race Some Others 6 86.7 27.9 11.4 60 120 60 65 78 120 120 120 120 120 

Race Hispanic 10 95.9 78.8 24.9 4 225 4 20 105 120 218 225 225 225 

Race Refused 3 170.0 264.2 152.5 15 475 15 15 20 475 475 475 475 475 

Hispanic No 435 72.1 69.9 3.4 1 510 5 25 60 90 150 190 300 360 

Hispanic Yes 20 81.7 63.0 14.1 4 225 5 40 60 120 183 218 225 225 

Hispanic DK 1 55.0 - - 55 55 55 55 55 55 55 55 55 55 

Hispanic Refused 2 247.5 321.7 227.5 20 475 20 20 248 475 475 475 475 475 

Employment - 12 76.8 107.8 31.1 1 300 1 4 23 135 240 300 300 300 

Employment Full Time 206 69.2 78.4 5.5 2 510 5 20 60 90 135 203 360 405 

Employment Part Time 51 72.2 62.5 8.8 2 225 5 15 55 120 150 180 225 225 

Employment Not Employed 187 77.7 63.8 4.7 5 475 10 30 60 115 150 180 245 345 

Employment Refused 2 76.0 104.7 74.0 2 150 2 2 76 150 150 150 150 150 

Education - 17 72.0 90.9 22.0 1 300 1 10 35 90 240 300 300 300 

Education < High School 51 71.8 49.4 6.9 15 245 20 30 60 90 120 180 195 245 

Education High School Graduate 163 71.6 71.6 5.6 2 510 6 30 60 90 140 180 325 405 

Education < College 107 77.2 71.7 6.9 2 475 5 20 60 120 155 200 225 240 

Education College Graduate 60 74.0 77.3 10.0 5 510 10 27 60 98 154 190 203 510 

Education Post Graduate 60 71.3 79.9 10.3 5 360 5 18 60 90 155 263 360 360 

Census Region Northeast 105 80.9 84.6 8.3 2 510 5 25 60 120 180 225 345 360 

Census Region Midwest 116 64.9 63.3 5.9 2 475 5 15 60 90 135 155 215 240 

Census Region South 151 72.7 69.5 5.7 1 510 10 30 60 90 150 210 245 330 

Census Region West 86 75.9 69.9 7.5 4 405 5 30 60 115 150 180 360 405 

Day Of Week Weekday 322 68.6 66.7 3.7 1 510 5 23 60 90 140 180 240 345 

Day Of Week Weekend 136 84.1 82.1 7.0 5 510 10 30 60 120 180 240 360 405 

Season Winter 145 75.2 81.0 6.7 1 510 5 17 60 90 165 215 360 475 

Season Spring 89 81.9 83.0 8.8 5 510 10 30 60 100 180 240 405 510 

Season Summer 132 69.3 60.8 5.3 2 360 5 25 60 120 135 155 240 325 

Season Fall 92 67.3 58.6 6.1 3 345 10 22 60 90 125 180 245 345 

Asthma No 432 73.8 73.2 3.5 1 510 5 25 60 105 150 200 325 360 

Asthma Yes 26 64.2 44.8 8.8 10 200 10 25 60 90 120 130 200 200 

Angina No 440 72.1 70.2 3.3 1 510 5 25 60 100 150 185 270 360 

Angina Yes 16 103.1 109.9 27.5 5 360 5 30 60 138 345 360 360 360 

Angina DK 2 72.5 17.7 12.5 60 85 60 60 73 85 85 85 85 85 

Bronchitis/emphysema No 428 73.3 73.5 3.6 1 510 5 24 60 105 150 200 325 360 

Bronchitis/emphysema Yes 30 72.4 43.5 7.9 10 200 15 45 60 90 125 150 200 200 
 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only (continued) 

Indoors in a Residence (all rooms) 

Category Population Group N Mean SD SE Min Max 

Percentiles 

5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

9,343 

4,269 

5,070 

4 

187 

498 

700 

588 

6,022 

1,348 

7,556 

941 

157 

181 

382 

126 

8,498 

696 

46 

103 

1,768 

4,068 

797 

2,639 

71 

1,963 

829 

2,602 

1,788 

1,240 

921 

2,068 

2,087 

3,230 

1,958 

6,286 

3,057 

2,513 

2,424 

2,522 

1,884 

8,591 

689 

63 

9,019 

249 

75 

8,840 

432 

71 

1,001.4 

945.9 

1,048.1 

1,060.0 

1,001.1 

1,211.6 

1,005.1 

969.5 

947.9 

1,174.6 

999.4 

1,016.0 

983.5 

996.1 

1,009.4 

1,019.7 

1,000.4 

1,009.8 

1,097.9 

984.1 

1,053.3 

881.0 

982.4 

1,158.0 

995.1 

1,044.5 

1,093.4 

1,008.1 

974.3 

939.5 

943.7 

1,003.4 

1,001.7 

999.0 

1,002.8 

965.7 

1,074.8 

1,034.9 

977.9 

980.5 

1,014.8 

999.1 

1,027.4 

1,025.7 

997.8 

1,125.5 

1,024.1 

997.7 

1,070.5 

1,045.5 

275.1 

273.5 

267.9 

135.6 

279.9 

218.7 

222.3 

241.8 

273.0 

229.3 

275.7 

272.5 

254.7 

268.3 

281.8 

276.6 

275.4 

270.8 

286.7 

269.5 

248.5 

259.2 

243.1 

233.8 

268.1 

251.9 

278.6 

279.3 

272.6 

275.0 

274.3 

278.4 

280.6 

270.2 

274.0 

272.6 

265.7 

278.2 

267.2 

274.0 

277.5 

274.4 

284.4 

264.3 

274.1 

281.4 

285.1 

274.8 

273.8 

273.0 

2.8 

4.2 

3.8 

67.8 

20.5 

9.8 

8.4 

10.0 

3.5 

6.2 

3.2 

8.9 

20.3 

19.9 

14.4 

24.6 

3.0 

10.3 

42.3 

26.6 

5.9 

4.1 

8.6 

4.6 

31.8 

5.7 

9.7 

5.5 

6.4 

7.8 

9.0 

6.1 

6.1 

4.8 

6.2 

3.4 

4.8 

5.6 

5.4 

5.5 

6.4 

3.0 

10.8 

33.3 

2.9 

17.8 

32.9 

2.9 

13.2 

32.4 

8 

8 

30 

900 

265 

270 

190 

95 

8 

60 

8 

190 

30 

10 

55 

270 

8 

55 

401 

270 

95 

8 

255 

60 

445 

95 

150 

30 

10 

30 

8 

30 

8 

10 

30 

30 

8 

30 

10 

8 

30 

8 

190 

445 

8 

180 

150 

8 

205 

445 

1,440 

1,440 

1,440 

1,200 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

575 

540 

620 

900 

565 

795 

686 

585 

540 

760 

570 

600 

600 

604 

555 

575 

575 

585 

645 

565 

675 

515 

600 

735 

575 

660 

630 

565 

570 

528 

540 

570 

565 

585 

575 

567 

615 

590 

580 

555 

589 

576 

555 

630 

575 

660 

560 

575 

585 

565 

795 

750 

840 

950 

799 

1,065 

845 

812 

750 

1,030 

795 

815 

810 

805 

810 

840 

795 

810 

835 

810 

870 

715 

820 

1,015 

810 

855 

870 

803 

775 

745 

750 

795 

790 

800 

800 

770 

895 

825 

780 

785 

805 

795 

825 

840 

795 

925 

840 

795 

868 

845 

985 

900 

1,050 

1,070 

955 

1,260 

975 

950 

900 

1,210 

980 

1,000 

930 

975 

1,005 

975 

980 

1,000 

1,173 

950 

1,030 

835 

970 

1,190 

940 

1,020 

1,130 

995 

930 

885 

900 

980 

989 

970 

1,000 

911 

1,105 

1,015 

955 

960 

997 

980 

1,025 

960 

975 

1,185 

975 

975 

1,110 

975 

1,235 1,395 1,440 

1,160 1,350 1,430 

1,280 1,420 1,440 

1,170 1,200 1,200 

1,230 1,440 1,440 

1,410 1,440 1,440 

1,165 1,334 1,412.5 

1,155 1,310 1,405 

1,165 1,350 1,428 

1,375 1,440 1,440 

1,235 1,395 1,440 

1,245 1,410 1,440 

1,180 1,355 1,420 

1,198 1,380 1,440 

1,250 1,410 1,440 

1,255 1,440 1,440 

1,235 1,395 1,440 

1,230 1,405 1,440 

1,355 1,440 1,440 

1,200 1,375 1,440 

1,255 1,413 1,440 

1,046 1,290 1,385 

1,170 1,320 1,380 

1,350 1,440 1,440 

1,255 1,440 1,440 

1,254 1,410 1,440 

1,345 1,440 1,440 

1,245 1,400 1,440 

1,205 1,371 1,436 

1,165 1,335 1,428 

1,155 1,350 1,410 

1,245 1,405 1,440 

1,250 1,390 1,440 

1,228 1,400 1,440 

1,230 1,390 1,440 

1,190 1,380 1,440 

1,290 1,420 1,440 

1,285 1,432 1,440 

1,185 1,370 1,435 

1,201 1,365 1,440 

1,260 1,405 1,440 

1,230 1,393 1,440 

1,260 1,430 1,440 

1,315 1,410 1,440 

1,230 1,391 1,440 

1,380 1,440 1,440 

1,305 1,425 1,440 

1,230 1,395 1,440 

1,293 1,440 1,440 

1,320 1,440 1,440 

1,440 

1,440 

1,440 

1,200 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,200 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

1,440 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-40 November 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-41 

Table 16-16. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined, Doers Only (continued) - = Indicates missing data. 

DK = The respondent replied “don’t know”. 

Refused = Refused data. 

N = Doer sample size. 

Mean = Mean 24-hour cumulative number of minutes for doers. 

SD = Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-17. Time Spent (minutes/day) at Selected Indoor Locations Whole Population and Doers Only, 

Children <21 years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Restaurants―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

13 

7 

9 

7 

6 

10 

35 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

20 

45 

30 

45 

21 

15 

35 

105 

69 

62 

62 

52 

45 

60 

240 

105 

88 

92 

90 

85 

90 

380 

194 

102 

111 

120 

110 

137 

466 

330 

120 

120 

130 

180 

315 

645 

Restaurants―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

10 

15 

17 

43 

57 

78 

135 

85 

58 

63 

57 

54 

59 

126 

10 

5 

20 

4 

5 

2 

1 

-

6 

21 

7 

5 

3 

4 

-

8 

22 

9 

6 

7 

5 

-

12 

24 

10 

10 

10 

10 

-

21 

28 

16 

15 

18 

17 

-

33 

45 

30 

30 

30 

30 

-

55 

60 

45 

45 

45 

60 

-

83 

80 

90 

60 

65 

170 

-

99 

102 

120 

107 

102 

334 

-

110 

116 

120 

124 

141 

437 

-

116 

118 

122 

140 

223 

537 

-

118 

119 

126 

158 

283 

546 

330 

120 

120 

130 

180 

315 

645 

School―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

4 

13 

23 

75 

187 

201 

131 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

397 

420 

308 

0 

0 

0 

416 

444 

459 

430 

0 

22 

193 

540 

480 

495 

495 

46 

156 

414 

569 

552 

578 

566 

100 

453 

503 

589 

601 

630 

629 

165 

665 

545 

630 

665 

855 

855 

School―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

2 

8 

11 

71 

235 

229 

171 

-

-

251 

379 

396 

409 

367 

60 

5 

10 

5 

5 

15 

15 

-

-

10 

23 

64 

38 

22 

-

-

10 

34 

129 

96 

31 

-

-

10 

110 

195 

132 

90 

-

-

10 

160 

305 

290 

185 

-

-

83 

228 

370 

395 

270 

-

-

269 

418 

400 

420 

388 

-

-

388 

540 

435 

450 

440 

-

-

510 

570 

480 

495 

525 

-

-

528 

590 

540 

559 

576 

-

-

538 

615 

612 

631 

726 

-

-

542 

627 

643 

696 

801 

165 

665 

545 

630 

665 

855 

855 

Grocery/Convenience Stores, Other Stores, and Malls―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

39 

16 

18 

17 

14 

18 

36 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

30 

0 

0 

0 

0 

0 

15 

98 

62 

60 

62 

49 

54 

120 

178 

87 

86 

111 

101 

122 

230 

224 

146 

133 

189 

167 

204 

402 

241 

202 

250 

223 

225 

300 

484 

250 

255 

360 

420 

320 

413 

960 

Grocery/Convenience Stores, Other Stores, and Malls―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

21 

23 

27 

64 

91 

104 

146 

88 

81 

80 

96 

76 

82 

120 

5 

5 

10 

5 

3 

1 

2 

5 

7 

11 

5 

3 

2 

4 

5 

9 

13 

5 

5 

5 

5 

5 

17 

20 

16 

5 

10 

5 

24 

30 

33 

23 

14 

10 

10 

30 

55 

45 

50 

20 

20 

22 

55 

65 

60 

73 

60 

45 

60 

130 

93 

82 

116 

110 

120 

149 

190 

152 

120 

204 

170 

199 

330 

235 

205 

234 

236 

230 

300 

456 

244 

235 

313 

339 

255 

359 

517 

247 

245 

337 

382 

262 

383 

562 

250 

255 

360 

420 

320 

413 

960 

N = Sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes less than 10. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-42 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only 

Restaurant 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 2,059 94.5 119.9 2.6 1 925 10 30 60 95 185 351 548 660 

Sex Male 986 87.5 114.2 3.6 1 900 10 30 60 90 160 305 550 660 

Sex Female 1,073 101.0 124.7 3.8 1 925 10 40 60 105 230 380 540 670 

Age (years) - 30 126.1 138.2 25.2 15 495 30 45 60 150 398 490 495 495 

Age (years) 1 to 4 61 62.7 47.7 6.1 4 330 10 35 55 85 115 120 130 330 

Age (years) 5 to 11 84 56.7 38.1 4.2 5 180 10 30 45 85 120 120 140 180 

Age (years) 12 to 17 122 69.8 78.4 7.1 2 455 10 30 45 65 165 250 325 360 

Age (years) 18 to 64 1,503 101.2 131.2 3.4 1 925 10 30 60 105 211 400 570 675 

Age (years) >64 259 83.6 83.5 5.2 3 750 19 45 60 90 150 215 315 520 

Race White 1,747 91.7 114.7 2.7 1 925 10 30 60 95 175 320 535 640 

Race Black 148 102.8 141.3 11.6 3 805 5 30 60 95 295 430 555 735 

Race Asian 37 81.3 78.9 13.0 15 480 18 30 60 90 135 200 480 480 

Race Some Others 30 145.2 194.8 35.6 5 765 10 45 83 120 433 750 765 765 

Race Hispanic 78 123.0 156.8 17.8 10 700 15 40 60 110 375 585 660 700 

Race Refused 19 123.8 127.6 29.3 20 480 20 30 70 210 330 480 480 480 

Hispanic No 1,911 92.9 117.6 2.7 1 925 10 30 60 95 180 330 542 645 

Hispanic Yes 129 116.7 148.0 13.0 1 765 15 40 60 115 360 435 660 700 

Hispanic DK 5 76.0 134.3 60.1 5 315 5 10 10 40 315 315 315 315 

Hispanic Refused 14 114.5 134.7 36.0 30 480 30 30 60 90 330 480 480 480 

Employment - 263 62.3 57.9 3.6 2 455 10 30 45 80 120 140 273 330 

Employment Full Time 1,063 105.5 142.4 4.4 1 925 10 35 60 105 235 485 630 735 

Employment Part Time 208 122.6 144.8 10.0 1 805 5 33 65 123 320 441 595 660 

Employment Not Employed 515 76.3 61.4 2.7 3 490 15 40 60 90 145 195 260 315 

Employment Refused 10 135.0 133.5 42.2 30 425 30 60 83 135 378 425 425 425 

Education - 299 72.2 79.6 4.6 1 548 10 30 50 85 130 250 360 480 

Education < High School 132 134.8 171.8 15.0 5 925 10 30 60 152 375 535 700 750 

Education High School Graduate 590 99.4 136.3 5.6 3 910 10 35 60 90 203 435 645 680 

Education < College 431 94.9 114.9 5.5 1 770 10 35 60 105 180 340 550 640 

Education College Graduate 359 89.5 104.1 5.5 1 765 10 35 60 100 165 295 490 570 

Education Post Graduate 248 95.0 109.4 6.9 3 765 15 40 60 115 180 260 560 675 

Census Region Northeast 409 94.4 113.6 5.6 2 765 15 35 60 100 210 330 507 585 

Census Region Midwest 504 96.9 120.9 5.4 1 805 10 30 60 105 190 340 560 675 

Census Region South 680 92.7 125.1 4.8 2 910 10 30 60 90 195 365 550 650 

Census Region West 466 94.9 116.9 5.4 1 925 10 30 60 110 175 375 535 640 

Day Of Week Weekday 1,291 97.3 128.8 3.6 1 925 10 30 60 93 210 377 555 700 

Day Of Week Weekend 768 89.8 103.2 3.7 1 770 10 36 60 105 155 280 510 620 

Season Winter 524 97.7 125.7 5.5 3 875 15 35 60 105 178 351 595 685 

Season Spring 559 91.6 109.7 4.6 2 925 10 35 60 95 180 360 505 555 

Season Summer 556 95.1 123.0 5.2 1 910 10 30 60 94 210 360 555 675 

Season Fall 420 93.6 121.7 5.9 1 900 10 30 60 95 185 325 540 653 

Asthma No 1,903 94.1 117.4 2.7 1 910 10 35 60 100 180 330 545 653 

Asthma Yes 150 96.3 143.6 11.7 4 925 10 30 46 90 238 485 590 670 

Asthma DK 6 196.3 220.9 90.2 30 480 30 30 79 480 480 480 480 480 

Angina No 1,998 94.9 120.7 2.7 1 925 10 30 60 100 190 355 550 660 

Angina Yes 50 69.0 53.6 7.6 3 340 15 45 60 90 105 120 286 340 

Angina DK 11 140.3 171.3 51.6 30 480 30 30 70 120 480 480 480 480 

Bronchitis/Emphysema No 1,945 93.7 117.7 2.7 1 910 10 30 60 97 180 335 548 653 

Bronchitis/Emphysema Yes 104 96.1 130.1 12.8 5 925 15 30 60 90 235 360 500 620 

Bronchitis/Emphysema DK 10 232.8 288.2 91.1 10 875 10 30 79 480 678 875 875 875 

Exposure Factors Handbook Page
 

November 2011 16-43 
 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Indoors at Bar/Nightclub/Bowling Alley 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

352 

213 

139 

4 

4 

8 

313 

23 

297 

25 

8 

7 

10 

5 

327 

20 

2 

3 

12 

223 

43 

70 

4 

13 

28 

117 

95 

55 

44 

83 

88 

91 

90 

192 

160 

93 

83 

99 

77 

331 

18 

3 

345 

5 

2 

333 

17 

2 

175.8 

174.3 

178.1 

158.8 

98.8 

151.3 

180.2 

141.2 

173.6 

205.4 

169.9 

197.3 

121.3 

246.6 

177.1 

144.9 

142.5 

261.0 

133.8 

182.4 

201.2 

146.3 

176.3 

146.5 

218.0 

177.8 

205.3 

141.8 

131.4 

179.3 

169.8 

175.7 

178.5 

167.5 

185.9 

182.7 

186.1 

160.3 

176.4 

176.3 

169.4 

160.0 

177.0 

82.0 

210.0 

177.3 

148.6 

165.0 

132.2 

133.2 

131.2 

98.0 

57.5 

77.7 

136.7 

85.2 

132.6 

126.6 

153.3 

187.6 

52.3 

127.2 

134.5 

85.1 

31.8 

171.9 

73.6 

138.3 

155.5 

97.4 

115.1 

84.2 

170.2 

130.1 

152.8 

92.8 

90.2 

137.0 

126.2 

132.0 

135.5 

133.5 

130.4 

131.7 

147.6 

130.7 

117.2 

133.7 

109.0 

124.9 

132.8 

47.2 

127.3 

133.3 

108.5 

190.9 

7.0 

9.1 

11.1 

49.0 

28.8 

27.5 

7.7 

17.8 

7.7 

25.3 

54.2 

70.9 

16.5 

56.9 

7.4 

19.0 

22.5 

99.2 

21.2 

9.3 

23.7 

11.6 

57.6 

23.3 

32.2 

12.0 

15.7 

12.5 

13.6 

15.0 

13.5 

13.8 

14.3 

9.6 

10.3 

13.7 

16.2 

13.1 

13.4 

7.4 

25.7 

72.1 

7.1 

21.1 

90.0 

7.3 

26.3 

135.0 

3 

5 

3 

75 

45 

50 

3 

5 

3 

50 

5 

70 

5 

73 

3 

5 

120 

73 

45 

5 

5 

3 

45 

45 

60 

3 

5 

10 

30 

5 

5 

3 

5 

5 

3 

5 

5 

3 

15 

3 

60 

60 

3 

5 

120 

3 

50 

30 

870 

870 

630 

300 

170 

270 

870 

328 

870 

540 

479 

615 

198 

410 

870 

440 

165 

410 

270 

870 

615 

479 

300 

300 

870 

630 

650 

417 

400 

650 

615 

870 

605 

650 

870 

650 

870 

630 

615 

870 

530 

300 

870 

120 

300 

870 

530 

300 

30 

30 

30 

75 

45 

50 

30 

30 

30 

60 

5 

70 

5 

73 

30 

38 

120 

73 

45 

30 

45 

30 

45 

45 

75 

25 

30 

20 

30 

45 

30 

35 

30 

30 

45 

40 

30 

30 

30 

30 

60 

60 

30 

5 

120 

30 

50 

30 

90 

90 

95 

98 

53 

80 

90 

75 

90 

120 

38 

110 

105 

180 

90 

110 

120 

73 

60 

90 

90 

73 

83 

60 

120 

90 

105 

75 

60 

89 

90 

90 

85 

80 

108 

87 

90 

75 

100 

90 

105 

60 

90 

75 

120 

90 

110 

30 

150 

140 

150 

130 

90 

160 

150 

135 

140 

180 

175 

135 

118 

270 

150 

120 

143 

300 

135 

150 

150 

123 

180 

150 

175 

150 

180 

120 

110 

140 

148 

148 

153 

120 

165 

150 

140 

120 

165 

150 

135 

120 

150 

90 

210 

150 

120 

165 

223 

220 

225 

220 

145 

205 

225 

180 

220 

240 

225 

185 

160 

300 

225 

160 

165 

410 

178 

228 

270 

180 

270 

185 

235 

225 

240 

205 

178 

240 

212 

225 

225 

210 

228 

240 

230 

189 

220 

225 

210 

300 

225 

120 

300 

225 

175 

300 

328 

340 

300 

300 

170 

270 

370 

240 

328 

417 

479 

615 

179 

410 

340 

222 

165 

410 

225 

340 

455 

255 

300 

270 

420 

360 

462 

265 

265 

328 

299 

270 

407 

340 

322 

410 

380 

285 

299 

340 

270 

300 

340 

120 

300 

340 

210 

300 

487 

479 

530 

300 

170 

270 

498 

325 

487 

498 

479 

615 

198 

410 

489 

343 

165 

410 

270 

525 

520 

328 

300 

300 

568 

489 

590 

340 

290 

489 

487 

462 

479 

520 

475 

455 

498 

530 

410 

487 

530 

300 

487 

120 

300 

487 

530 

300 

570 

568 

600 

300 

170 

270 

590 

328 

590 

540 

479 

615 

198 

410 

590 

440 

165 

410 

270 

600 

615 

462 

300 

300 

870 

540 

615 

410 

400 

630 

568 

570 

590 

590 

568 

560 

570 

605 

600 

590 

530 

300 

590 

120 

300 

590 

530 

300 

615 

615 

605 

300 

170 

270 

615 

328 

630 

540 

479 

615 

198 

410 

615 

440 

165 

410 

270 

630 

615 

479 

300 

300 

870 

570 

650 

417 

400 

650 

615 

870 

605 

605 

630 

650 

870 

630 

615 

615 

530 

300 

615 

120 

300 

615 

530 

300 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-44 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Indoors at School 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 1,224 343.4 179.1 5.1 1 995 10 210 395 454 540 585 660 723 

Sex Male 581 358.6 167.7 7.0 1 995 30 255 400 450 540 600 690 778 

Sex Female 643 329.6 187.9 7.4 1 855 5 180 390 455 540 582 640 683 

Age (years) - 18 314.1 230.9 54.4 5 713 5 165 248 520 625 713 713 713 

Age (years) 1 to 4 43 288.5 217.6 33.2 5 665 10 60 269 500 580 595 665 665 

Age (years) 5 to 11 302 396.3 109.2 6.3 5 665 170 365 403 445 535 565 625 640 

Age (years) 12 to 17 287 402.6 125.5 7.4 15 855 120 383 420 450 500 565 710 778 

Age (years) 18 to 64 550 295.4 207.3 8.8 1 995 5 104 300 460 553 612 683 785 

Age (years) >64 24 187.7 187.0 38.2 2 585 3 45 120 328 480 510 585 585 

Race White 928 348.5 180.5 5.9 1 995 10 213 400 458 545 600 665 723 

Race Black 131 339.8 169.3 14.8 2 855 15 230 390 445 510 580 624 645 

Race Asian 39 332.4 179.9 28.8 5 840 20 190 365 450 560 580 840 840 

Race Some Others 36 363.6 155.6 25.9 10 820 105 273 366 458 502 598 820 820 

Race Hispanic 76 294.0 175.7 20.2 2 565 10 143 363 432 495 525 540 565 

Race Refused 14 279.7 221.3 59.1 5 681 5 60 260 440 625 681 681 681 

Hispanic No 1,082 344.9 179.6 5.5 1 995 10 210 395 455 540 598 665 730 

Hispanic Yes 127 333.0 173.8 15.4 2 820 15 200 390 445 500 565 600 630 

Hispanic DK 5 293.0 244.7 109.4 3 562 3 65 415 420 562 562 562 562 

Hispanic Refused 10 329.5 180.1 56.9 5 625 5 200 350 445 538 625 625 625 

Employment - 616 390.3 130.2 5.2 5 855 115 365 410 450 525 570 640 665 

Employment Full Time 275 331.3 222.0 13.4 1 995 5 115 405 510 575 625 690 755 

Employment Part Time 138 280.9 174.8 14.9 1 800 10 160 285 412 480 537 660 683 

Employment Not Employed 190 258.7 199.5 14.5 1 855 5 60 263 410 528 572 778 840 

Employment Refused 5 166.0 179.1 80.1 5 440 5 5 180 200 440 440 440 440 

Education - 679 388.9 132.8 5.1 5 855 100 360 410 450 525 580 640 710 

Education < High School 24 233.3 179.6 36.7 1 540 2 30 298 374 460 465 540 540 

Education High School Graduate 114 186.6 193.6 18.1 1 785 4 20 108 295 480 580 645 690 

Education < College 173 281.4 209.9 16.0 1 995 5 120 255 425 550 640 820 855 

Education College Graduate 93 300.4 208.7 21.6 1 755 5 115 320 470 540 580 730 755 

Education Post Graduate 141 373.5 193.4 16.3 1 683 15 250 442 510 575 615 655 680 

Census Region Northeast 261 345.7 181.5 11.2 1 995 11 210 385 455 535 620 710 855 

Census Region Midwest 290 334.4 176.7 10.4 1 730 10 180 390 440 530 585 645 683 

Census Region South 427 354.0 178.5 8.6 1 855 10 235 415 462 540 575 640 755 

Census Region West 246 332.8 180.3 11.5 1 820 15 195 378 440 555 595 681 713 

Day Of Week Weekday 1,179 346.8 177.5 5.2 1 995 10 222 395 455 540 585 655 723 

Day Of Week Weekend 45 252.0 198.5 29.6 20 820 40 105 180 360 555 632 820 820 

Season Winter 392 369.3 164.4 8.3 1 855 20 285 405 457 545 600 680 710 

Season Spring 353 355.1 165.5 8.8 1 855 12 250 400 455 535 575 636 713 

Season Summer 207 316.8 196.4 13.6 2 995 10 125 365 445 557 585 640 723 

Season Fall 272 311.0 195.3 11.8 1 855 5 120 365 445 540 595 660 778 

Asthma No 1,095 342.8 179.2 5.4 1 995 10 200 390 455 540 585 660 723 

Asthma Yes 124 350.7 178.8 16.1 1 855 10 250 402 445 535 605 645 800 

Asthma DK 5 287.0 190.7 85.3 5 445 5 180 365 440 445 445 445 445 

Angina No 1,209 344.6 178.9 5.1 1 995 10 210 395 455 540 595 660 723 

Angina Yes 9 205.8 169.5 56.5 15 510 15 90 180 275 510 510 510 510 

Angina DK 6 292.2 178.9 73.0 5 480 5 180 324 440 480 480 480 480 

Bronchitis/Emphysema No 1,175 344.8 178.8 5.2 1 995 10 212 395 455 540 595 660 730 

Bronchitis/Emphysema Yes 42 306.7 188.2 29.0 3 632 10 120 378 444 465 580 632 632 

Bronchitis/Emphysema DK 7 315.4 163.7 61.9 5 440 5 180 378 440 440 440 440 440 

Exposure Factors Handbook Page
 

November 2011 16-45 
 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Office or Factory 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

1,975 

1,012 

963 

49 

12 

14 

19 

1,749 

132 

1,612 

191 

42 

28 

74 

28 

1,805 

138 

7 

25 

43 

1,535 

164 

213 

20 

80 

104 

631 

462 

415 

283 

465 

439 

666 

405 

1,759 

216 

531 

470 

550 

424 

1,845 

114 

16 

1,931 

26 

18 

1,873 

86 

16 

394.0 

410.8 

376.3 

438.9 

31.6 

100.9 

145.4 

419.0 

145.8 

387.6 

413.9 

428.0 

480.9 

394.5 

482.9 

393.5 

393.6 

262.6 

470.0 

121.3 

455.6 

293.0 

77.6 

449.2 

225.1 

329.5 

396.9 

393.1 

437.2 

396.9 

399.1 

389.3 

408.6 

369.1 

406.8 

289.6 

390.7 

385.2 

393.5 

408.4 

395.0 

371.7 

437.0 

395.7 

265.5 

392.3 

395.6 

356.4 

403.9 

230.8 

233.5 

226.7 

232.6 

25.6 

155.1 

181.1 

218.4 

194.0 

232.0 

218.0 

216.8 

200.9 

237.8 

246.1 

229.6 

238.6 

242.1 

258.8 

178.0 

200.3 

197.0 

123.0 

184.8 

248.5 

264.4 

228.1 

228.8 

205.2 

232.2 

226.2 

229.1 

228.2 

240.4 

225.2 

249.1 

231.7 

240.7 

224.5 

226.6 

230.4 

231.3 

272.1 

229.7 

246.8 

282.6 

230.0 

236.1 

289.5 

5.2 

7.3 

7.3 

33.2 

7.4 

41.5 

41.6 

5.2 

16.9 

5.8 

15.8 

33.4 

38.0 

27.6 

46.5 

5.4 

20.3 

91.5 

51.8 

27.1 

5.1 

15.4 

8.4 

41.3 

27.8 

25.9 

9.1 

10.6 

10.1 

13.8 

10.5 

10.9 

8.8 

11.9 

5.4 

16.9 

10.1 

11.1 

9.6 

11.0 

5.4 

21.7 

68.0 

5.2 

48.4 

66.6 

5.3 

25.5 

72.4 

1 

1 

1 

10 

5 

2 

1 

1 

1 

1 

1 

10 

40 

1 

30 

1 

1 

1 

17 

1 

1 

1 

1 

30 

1 

2 

1 

1 

1 

2 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

3 

5 

1 

5 

5 

1 

5 

5 

1,440 

1,440 

855 

900 

90 

580 

625 

1,440 

705 

1,440 

1,037 

780 

795 

840 

997 

1,440 

840 

610 

860 

685 

1,440 

750 

705 

675 

860 

930 

997 

1,440 

900 

860 

930 

997 

1,440 

900 

997 

1,440 

997 

1,440 

1,037 

840 

1,440 

840 

860 

1,440 

650 

860 

1,440 

800 

860 

9 

10 

5 

20 

5 

2 

1 

10 

3 

6 

10 

30 

75 

5 

30 

10 

5 

1 

30 

2 

15 

10 

3 

60 

3 

5 

10 

5 

10 

5 

10 

8 

10 

5 

10 

3 

10 

5 

9 

10 

8 

10 

5 

10 

9 

5 

8 

10 

5 

180 

225 

120 

299 

13 

10 

10 

273 

10 

150 

268 

285 

348 

230 

373 

180 

180 

12 

311 

10 

400 

95 

10 

334 

15 

51 

210 

210 

325 

175 

215 

180 

225 

95 

237 

30 

180 

120 

200 

239 

185 

120 

233 

195 

15 

30 

195 

75 

30 

485 

495 

480 

500 

25 

33 

50 

500 

40 

480 

485 

492 

540 

493 

533 

483 

498 

245 

525 

40 

510 

343 

30 

523 

105 

389 

492 

480 

510 

480 

485 

480 

498 

470 

495 

283 

480 

480 

483 

500 

490 

463 

520 

490 

175 

490 

490 

428 

490 

550 

565 

540 

555 

45 

178 

240 

555 

205 

550 

540 

553 

583 

560 

608 

550 

560 

540 

615 

178 

570 

480 

90 

550 

470 

553 

550 

540 

570 

565 

550 

550 

555 

550 

555 

495 

550 

553 

540 

567 

550 

540 

588 

550 

490 

550 

550 

540 

583 

630 

645 

600 

675 

60 

195 

510 

630 

495 

628 

635 

660 

715 

645 

818 

630 

644 

610 

810 

307 

644 

525 

215 

645 

608 

640 

615 

615 

640 

640 

625 

630 

630 

630 

630 

600 

625 

630 

614 

640 

630 

630 

780 

630 

630 

780 

630 

620 

780 

675 

710 

645 

780 

90 

580 

625 

680 

540 

675 

720 

745 

780 

720 

860 

675 

675 

610 

818 

580 

700 

555 

305 

675 

675 

705 

675 

660 

690 

675 

675 

670 

675 

675 

675 

670 

675 

695 

675 

675 

675 

675 

860 

675 

645 

860 

675 

660 

860 

765 

780 

710 

900 

90 

580 

625 

765 

640 

750 

803 

780 

795 

765 

997 

755 

765 

610 

860 

685 

775 

585 

570 

675 

780 

765 

760 

770 

750 

780 

765 

750 

760 

760 

755 

800 

755 

775 

753 

750 

760 

800 

860 

760 

650 

860 

760 

720 

860 

818 

855 

750 

900 

90 

580 

625 

818 

675 

800 

900 

780 

795 

840 

997 

810 

795 

610 

860 

685 

837 

615 

640 

675 

860 

855 

800 

820 

800 

818 

840 

800 

840 

800 

810 

900 

835 

837 

810 

770 

810 

837 

860 

811 

650 

860 

818 

800 

860 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-46 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Schools, Churches, Hospitals, and Public Buildings 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 2,932 274.3 205.9 3.8 1 1,440 20 95 221 430 540 615 725 805 

Sex Male 1,234 285.1 206.7 5.9 1 1,440 30 110 255 425 540 620 745 840 

Sex Female 1,698 266.5 205.1 5.0 1 1,440 20 90 200 430 540 610 713 800 

Age (years) - 50 269.0 221.0 31.3 5 1,030 30 100 193 400 590 625 872 1,030 

Age (years) 1 to 4 98 233.0 235.8 23.8 1 1,440 5 60 150 390 545 595 900 1,440 

Age (years) 5 to 11 391 351.2 149.6 7.6 5 665 70 245 389 440 535 562 625 645 

Age (years) 12 to 17 355 366.3 161.2 8.6 1 935 60 260 415 446 502 605 710 805 

Age (years) 18 to 64 1,653 267.7 221.2 5.4 1 1,440 15 87 190 450 570 655 760 855 

Age (years) >64 385 151.1 128.6 6.6 5 710 21 60 115 195 340 435 525 615 

Race White 2,310 268.2 204.3 4.3 1 1,440 20 90 210 429 540 612 705 765 

Race Black 332 303.5 207.1 11.4 1 1,440 35 135 285 440 540 630 775 1,000 

Race Asian 61 295.0 199.4 25.5 5 900 30 135 240 425 535 565 840 900 

Race Some Others 57 314.7 203.5 27.0 10 967 30 135 360 455 525 598 820 967 

Race Hispanic 141 283.9 229.8 19.4 2 1,440 11 100 237 430 525 630 840 940 

Race Refused 31 257.8 192.5 34.6 5 681 5 120 240 430 495 625 681 681 

Hispanic No 2,654 271.3 203.6 4.0 1 1,440 20 94 215 425 540 612 712 800 

Hispanic Yes 240 306.4 230.8 14.9 1 1,440 20 110 288 445 568 695 840 940 

Hispanic DK 13 279.4 230.7 64.0 35 760 35 65 235 420 562 760 760 760 

Hispanic Refused 25 286.6 175.4 35.1 5 625 55 145 255 440 495 565 625 625 

Employment - 821 343.5 171.1 6.0 1 1,440 55 190 393 441 520 570 645 713 

Employment Full Time 1,029 300.3 239.8 7.5 1 1,440 15 90 215 510 610 685 775 900 

Employment Part Time 293 251.3 199.3 11.6 1 1,030 20 85 200 387 525 610 800 880 

Employment Not Employed 775 176.4 148.4 5.3 1 855 15 60 121 250 400 475 570 641 

Employment Refused 14 212.9 147.7 39.5 5 440 5 120 190 305 430 440 440 440 

Education - 917 340.3 172.6 5.7 1 1,440 45 190 390 440 525 580 645 713 

Education < High School 166 172.6 138.0 10.7 1 735 27 70 124 235 375 465 525 640 

Education High School Graduate 617 207.3 199.0 8.0 1 1,440 15 60 135 295 510 585 690 785 

Education < College 520 247.5 213.6 9.4 1 1,000 15 85 165 420 553 640 760 855 

Education College Graduate 351 261.6 214.3 11.4 1 1,005 15 85 180 450 560 625 750 800 

Education Post Graduate 361 319.1 236.2 12.4 1 1,440 30 110 290 510 615 683 765 900 

Census Region Northeast 645 272.7 211.6 8.3 1 1,440 25 90 215 420 545 630 735 855 

Census Region Midwest 686 275.4 207.2 7.9 1 1,440 30 88 239 425 540 615 745 850 

Census Region South 1,036 278.4 201.0 6.2 1 1,440 20 110 230 440 535 600 690 778 

Census Region West 565 267.4 207.2 8.7 1 1,440 15 100 200 420 555 620 712 820 

Day Of Week Weekday 2,091 309.8 212.6 4.6 1 1,440 15 115 340 460 565 632 750 855 

Day Of Week Weekend 841 186.0 156.9 5.4 1 1,440 40 85 140 230 385 525 640 735 

Season Winter 847 296.6 201.2 6.9 1 1,440 30 120 285 444 545 615 710 770 

Season Spring 805 276.8 204.6 7.2 1 1,440 30 110 220 420 535 600 725 840 

Season Summer 667 254.1 209.7 8.1 1 1,015 20 80 180 420 550 630 738 890 

Season Fall 613 262.4 207.3 8.4 1 1,005 14 75 210 425 540 615 712 778 

Asthma No 2,689 273.2 207.3 4.0 1 1,440 20 94 217 430 540 615 725 820 

Asthma Yes 229 288.0 191.6 12.7 1 855 25 120 275 435 533 605 645 800 

Asthma DK 14 270.0 171.2 45.8 5 565 5 145 280 430 445 565 565 565 

Angina No 2,836 277.1 206.4 3.9 1 1,440 20 100 230 430 540 615 725 805 

Angina Yes 78 176.4 172.8 19.6 5 890 28 60 120 195 480 575 625 890 

Angina DK 18 258.3 165.6 39.0 3 565 3 145 270 378 480 565 565 565 

Bronchitis/Emphysema No 2,794 277.0 207.3 3.9 1 1,440 20 95 228 430 540 615 726 840 

Bronchitis/Emphysema Yes 121 212.6 166.3 15.1 10 662 30 90 145 375 445 490 605 630 

Bronchitis/Emphysema DK 17 275.8 163.4 39.6 5 565 5 145 305 415 440 565 565 565 

Exposure Factors Handbook Page
 

November 2011 16-47 
 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Malls, Grocery Stores, or Other Stores 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

2,697 

1,020 

1,677 

50 

110 

129 

140 

1,871 

397 

2,234 

237 

37 

52 

110 

27 

2,476 

188 

12 

21 

372 

1,170 

285 

854 

16 

420 

206 

792 

583 

411 

285 

622 

601 

871 

603 

1,721 

976 

683 

679 

759 

576 

2,480 

208 

9 

2,607 

74 

16 

2,553 

130 

14 

115.0 

120.2 

111.8 

139.4 

90.0 

77.7 

88.7 

125.9 

88.6 

111.6 

123.0 

158.9 

150.2 

133.1 

124.7 

114.4 

126.1 

49.4 

122.4 

86.9 

136.8 

134.1 

91.2 

98.9 

88.3 

128.9 

126.3 

129.8 

117.9 

78.2 

110.2 

108.2 

127.9 

107.9 

117.5 

110.6 

111.7 

115.8 

113.1 

120.2 

116.2 

101.1 

85.1 

116.0 

90.8 

62.7 

115.7 

104.8 

71.1 

141.0 

157.1 

130.1 

137.6 

77.9 

68.0 

101.4 

156.8 

88.5 

139.4 

152.3 

151.7 

146.7 

138.3 

131.1 

141.8 

133.2 

37.7 

138.5 

86.3 

176.7 

147.7 

87.2 

110.0 

91.9 

155.7 

158.9 

149.5 

144.1 

95.7 

134.9 

133.1 

155.8 

130.7 

148.9 

125.7 

134.0 

142.2 

147.5 

138.9 

142.4 

125.0 

79.6 

142.1 

103.9 

68.1 

141.7 

131.3 

66.9 

2.7 

4.9 

3.2 

19.5 

7.4 

6.0 

8.6 

3.6 

4.4 

3.0 

9.9 

24.9 

20.3 

13.2 

25.2 

2.9 

9.7 

10.9 

30.2 

4.5 

5.2 

8.8 

3.0 

27.5 

4.5 

10.8 

5.6 

6.2 

7.1 

5.7 

5.4 

5.4 

5.3 

5.3 

3.6 

4.0 

5.1 

5.5 

5.4 

5.8 

2.9 

8.7 

26.5 

2.8 

12.1 

17.0 

2.8 

11.5 

17.9 

1 

1 

1 

15 

5 

3 

1 

1 

1 

1 

2 

2 

5 

1 

10 

1 

1 

2 

10 

1 

1 

2 

1 

10 

1 

2 

1 

1 

1 

1 

1 

2 

1 

1 

1 

1 

2 

1 

1 

1 

1 

1 

33 

1 

2 

2 

1 

5 

20 

1,080 

840 

1,080 

660 

420 

320 

530 

1,080 

655 

1,080 

800 

600 

660 

720 

515 

1,080 

720 

122 

515 

660 

1,080 

540 

585 

357 

660 

1,080 

960 

800 

720 

630 

755 

840 

1,080 

840 

1,080 

840 

840 

720 

1,080 

840 

1,080 

600 

290 

1,080 

630 

290 

1,080 

613 

290 

10 

5 

10 

20 

10 

5 

5 

10 

10 

10 

10 

14 

14 

10 

10 

10 

10 

2 

20 

5 

10 

6 

10 

10 

5 

10 

5 

10 

10 

10 

5 

10 

10 

10 

10 

5 

10 

10 

5 

10 

10 

5 

33 

10 

15 

2 

10 

10 

20 

30 

30 

30 

45 

40 

30 

20 

30 

30 

30 

25 

50 

65 

35 

30 

30 

30 

18 

33 

30 

30 

30 

30 

32 

29 

30 

30 

30 

30 

25 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

55 

30 

37 

30 

30 

25 

35 

60 

60 

60 

93 

65 

60 

45 

60 

60 

60 

60 

105 

103 

90 

60 

60 

90 

48 

60 

60 

60 

65 

60 

53 

60 

75 

60 

70 

60 

50 

60 

60 

60 

60 

60 

65 

60 

60 

60 

60 

60 

60 

58 

60 

64 

55 

60 

60 

57 

135 

130 

135 

180 

105 

110 

124 

150 

120 

130 

135 

220 

180 

195 

207 

132 

173 

70 

180 

120 

150 

186 

120 

115 

120 

150 

150 

165 

135 

90 

130 

130 

155 

120 

135 

135 

135 

130 

125 

160 

135 

120 

60 

135 

105 

60 

135 

135 

70 

285 

375 

255 

339 

210 

180 

223 

360 

180 

265 

370 

410 

280 

310 

300 

285 

270 

105 

290 

206 

480 

400 

195 

290 

210 

330 

365 

345 

290 

160 

280 

250 

320 

255 

320 

255 

255 

300 

300 

295 

288 

245 

290 

290 

150 

110 

285 

193 

110 

482 

530 

400 

420 

250 

225 

318 

525 

255 

495 

480 

480 

588 

450 

380 

495 

450 

122 

380 

255 

562 

480 

255 

357 

263 

500 

524 

510 

515 

250 

465 

440 

520 

430 

510 

380 

420 

500 

510 

480 

495 

420 

290 

495 

190 

290 

481 

505 

290 

570 

609 

550 

565 

359 

255 

384 

600 

400 

570 

600 

600 

600 

535 

515 

570 

540 

122 

515 

360 

640 

520 

360 

357 

384 

570 

600 

563 

600 

450 

563 

560 

600 

550 

586 

560 

568 

588 

570 

550 

575 

545 

290 

570 

510 

290 

570 

575 

290 

640 

658 

600 

660 

360 

280 

413 

658 

470 

640 

613 

600 

660 

540 

515 

640 

610 

122 

515 

384 

690 

540 

420 

357 

420 

605 

660 

651 

640 

555 

600 

645 

660 

600 

650 

608 

660 

645 

610 

640 

640 

550 

290 

640 

630 

290 

640 

609 

290 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-48 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Indoors at a Gym/Health Club 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 364 129.7 104.3 5.5 5 686 30 60 110 155 240 320 525 600 

Sex Male 176 147.2 115.6 8.7 5 686 30 78 120 175 285 360 533 660 

Sex Female 188 113.2 89.9 6.6 5 660 30 60 93 135 200 279 420 560 

Age (years) - 6 202.5 227.9 93.0 30 560 30 55 75 420 560 560 560 560 

Age (years) 1 to 4 5 156.0 29.9 13.4 105 180 105 160 160 175 180 180 180 180 

Age (years) 5 to 11 28 105.3 69.5 13.1 5 325 30 58 83 141 165 270 325 325 

Age (years) 12 to 17 39 165.4 122.1 19.5 15 660 30 90 138 206 330 440 660 660 

Age (years) 18 to 64 254 123.1 98.8 6.2 5 686 30 60 100 150 210 295 475 600 

Age (years) >64 32 141.4 114.2 20.2 10 533 30 60 103 173 292 340 533 533 

Race White 307 134.3 109.4 6.2 5 686 30 65 110 164 255 330 533 600 

Race Black 30 117.7 75.4 13.8 5 320 10 60 115 145 235 285 320 320 

Race Asian 10 75.2 36.5 11.5 30 145 30 54 60 95 133 145 145 145 

Race Some Others 11 112.9 69.1 20.8 25 270 25 65 90 153 179 270 270 270 

Race Hispanic 4 83.8 42.7 21.3 40 140 40 53 78 115 140 140 140 140 

Race Refused 2 57.5 3.5 2.5 55 60 55 55 58 60 60 60 60 60 

Hispanic No 345 132.0 105.9 5.7 5 686 30 65 110 160 240 325 533 600 

Hispanic Yes 17 90.1 58.8 14.3 5 255 5 60 90 115 140 255 255 255 

Hispanic Refused 2 57.5 3.5 2.5 55 60 55 55 58 60 60 60 60 60 

Employment - 72 139.6 103.3 12.2 5 660 30 76 120 165 265 330 440 660 

Employment Full Time 176 131.2 112.5 8.5 5 686 30 60 110 150 240 330 560 660 

Employment Part Time 40 129.3 92.8 14.7 25 420 35 60 95 168 285 325 420 420 

Employment Not Employed 75 117.9 91.3 10.5 5 533 25 60 90 145 230 285 475 533 

Employment Refused 1 40.0 - - 40 40 40 40 40 40 40 40 40 40 

Education - 81 136.9 99.7 11.1 5 660 30 75 120 164 215 325 440 660 

Education < High School 9 110.6 97.7 32.6 10 300 10 30 80 165 300 300 300 300 

Education High School Graduate 61 128.5 110.0 14.1 5 660 25 75 105 145 210 310 525 660 

Education < College 71 145.6 129.1 15.3 5 600 35 65 110 170 285 533 560 600 

Education College Graduate 81 122.0 99.5 11.1 15 686 30 60 98 135 220 285 420 686 

Education Post Graduate 61 115.6 76.9 9.8 10 415 40 60 90 145 225 265 320 415 

Census Region Northeast 83 140.5 107.2 11.8 20 660 40 70 120 170 240 330 600 660 

Census Region Midwest 62 127.0 88.7 11.3 5 440 25 60 113 170 285 300 340 440 

Census Region South 118 125.7 107.0 9.9 5 660 15 60 105 150 240 330 533 540 

Census Region West 101 127.0 108.5 10.8 5 686 50 60 92 135 225 292 525 560 

Day Of Week Weekday 281 121.3 96.6 5.8 5 686 30 60 98 145 210 295 475 560 

Day Of Week Weekend 83 158.1 123.7 13.6 5 660 30 77 120 180 285 415 600 660 

Season Winter 127 139.8 108.3 9.6 5 686 25 75 120 177 240 330 533 660 

Season Spring 85 141.5 115.2 12.5 10 600 30 65 102 164 285 340 560 600 

Season Summer 81 109.9 87.4 9.7 5 525 30 60 90 130 160 310 440 525 

Season Fall 71 119.9 99.0 11.7 20 660 30 56 98 150 215 295 420 660 

Asthma No 333 132.4 106.8 5.9 5 686 30 62 110 160 255 325 533 600 

Asthma Yes 28 100.1 69.4 13.1 5 330 25 60 86 118 210 230 330 330 

Asthma DK 3 101.7 55.8 32.2 60 165 60 60 80 165 165 165 165 165 

Angina No 357 130.5 105.0 5.6 5 686 30 62 110 155 240 325 525 600 

Angina Yes 4 90.0 47.6 23.8 60 160 60 60 70 120 160 160 160 160 

Angina DK 3 81.7 65.3 37.7 30 155 30 30 60 155 155 155 155 155 

Bronchitis/Emphysema No 352 130.7 104.8 5.6 5 686 30 61 110 158 240 320 525 600 

Bronchitis/Emphysema Yes 10 97.3 92.8 29.4 10 330 10 45 77 120 245 330 330 330 

Bronchitis/Emphysema DK 2 107.5 67.2 47.5 60 155 60 60 108 155 155 155 155 155 

Exposure Factors Handbook Page
 

November 2011 16-49 
 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Indoors at an Auto Repair Shop/Gas Station 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

Yes 

No 

Yes 

153 

105 

48 

3 

4 

5 

7 

118 

16 

130 

12 

5 

3 

3 

148 

5 

16 

84 

16 

35 

2 

18 

16 

51 

32 

19 

17 

29 

48 

43 

33 

121 

32 

28 

44 

52 

29 

145 

8 

149 

4 

146 

7 

190.7 

241.5 

79.6 

161.7 

40.0 

22.0 

153.9 

223.8 

58.1 

195.5 

149.7 

173.0 

15.0 

350.0 

188.9 

243.0 

84.2 

283.6 

104.2 

65.9 

17.5 

95.1 

327.2 

233.4 

253.5 

72.9 

49.0 

247.3 

230.9 

165.7 

115.0 

204.6 

137.9 

177.1 

189.6 

171.7 

239.4 

191.3 

179.9 

191.0 

177.5 

189.0 

225.0 

234.5 

250.3 

144.5 

115.6 

50.2 

21.7 

205.1 

249.3 

96.9 

237.5 

203.3 

231.2 

10.0 

330.1 

233.7 

279.7 

146.7 

263.8 

147.4 

94.7 

17.7 

153.9 

301.2 

243.1 

252.8 

126.3 

73.4 

257.1 

251.6 

211.6 

198.9 

244.9 

184.2 

258.1 

223.3 

223.8 

251.4 

235.3 

234.8 

235.3 

235.7 

235.0 

240.0 

19.0 

24.4 

20.9 

66.7 

25.1 

9.7 

77.5 

23.0 

24.2 

20.8 

58.7 

103.4 

5.8 

190.6 

19.2 

125.1 

36.7 

28.8 

36.8 

16.0 

12.5 

36.2 

75.3 

34.0 

44.7 

29.0 

17.8 

47.7 

36.3 

32.3 

34.6 

22.3 

32.6 

48.8 

33.7 

31.0 

46.7 

19.5 

83.0 

19.3 

117.9 

19.4 

90.7 

1 

2 

1 

90 

10 

5 

3 

1 

2 

1 

2 

5 

5 

15 

1 

15 

3 

3 

5 

1 

5 

3 

5 

2 

2 

1 

5 

2 

1 

3 

5 

1 

2 

2 

2 

1 

5 

1 

5 

1 

5 

1 

5 

930 

930 

595 

295 

115 

60 

505 

930 

358 

930 

565 

525 

25 

675 

930 

675 

505 

930 

390 

432 

30 

505 

930 

748 

700 

508 

235 

930 

700 

675 

675 

930 

540 

930 

645 

680 

748 

930 

600 

930 

510 

930 

555 

5 

5 

3 

90 

10 

5 

3 

5 

2 

5 

2 

5 

5 

15 

5 

15 

3 

5 

5 

2 

5 

3 

5 

5 

5 

1 

5 

3 

5 

5 

5 

5 

3 

5 

5 

3 

8 

5 

5 

5 

5 

5 

5 

15 

15 

10 

90 

13 

15 

5 

15 

15 

15 

7 

15 

5 

15 

15 

15 

13 

18 

13 

15 

5 

10 

60 

20 

15 

5 

10 

30 

18 

15 

10 

15 

15 

15 

15 

10 

35 

15 

5 

15 

10 

15 

5 

60 

115 

15 

100 

18 

15 

55 

75 

20 

60 

75 

25 

15 

360 

60 

150 

18 

230 

18 

30 

18 

18 

278 

120 

157 

20 

15 

120 

75 

50 

15 

60 

40 

30 

80 

30 

95 

60 

38 

60 

98 

58 

95 

360 

495 

70 

295 

68 

15 

390 

480 

43 

390 

229 

295 

25 

675 

370 

360 

70 

540 

188 

90 

30 

79 

615 

480 

518 

90 

35 

432 

510 

358 

100 

390 

200 

355 

385 

348 

445 

360 

375 

360 

345 

360 

510 

565 

600 

295 

295 

115 

60 

505 

600 

225 

588 

495 

525 

25 

675 

565 

675 

390 

630 

359 

160 

30 

390 

675 

565 

595 

295 

225 

600 

600 

555 

505 

595 

505 

595 

565 

540 

605 

565 

600 

585 

510 

585 

555 

645 

675 

485 

295 

115 

60 

505 

675 

358 

645 

565 

525 

25 

675 

630 

675 

505 

680 

390 

358 

30 

505 

930 

675 

680 

508 

235 

748 

680 

595 

645 

675 

510 

700 

600 

675 

695 

645 

600 

645 

510 

645 

555 

695 

700 

595 

295 

115 

60 

505 

700 

358 

700 

565 

525 

25 

675 

700 

675 

505 

748 

390 

432 

30 

505 

930 

695 

700 

508 

235 

930 

700 

675 

675 

700 

540 

930 

645 

675 

748 

700 

600 

700 

510 

700 

555 

748 

748 

595 

295 

115 

60 

505 

748 

358 

748 

565 

525 

25 

675 

748 

675 

505 

930 

390 

432 

30 

505 

930 

748 

700 

508 

235 

930 

700 

675 

675 

748 

540 

930 

645 

680 

748 

748 

600 

748 

510 

748 

555 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-50 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Indoors at the Laundromat 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 40 99.3 85.2 13.5 2 500 5 55 91 120 153 238 500 500 

Gender Male 9 150.2 146.8 48.9 2 500 2 115 120 150 500 500 500 500 

Gender Female 31 84.5 51.8 9.3 5 265 5 50 80 115 137 155 265 265 

Age (years) 5 to 11 3 80.7 17.9 10.3 60 92 60 60 90 92 92 92 92 92 

Age (years) 18 to 64 33 101.2 91.7 16.0 2 500 5 50 90 120 155 265 500 500 

Age (years) > 64 4 97.5 63.6 31.8 5 150 5 60 118 135 150 150 150 150 

Race White 31 102.2 93.8 16.9 2 500 5 50 90 120 155 265 500 500 

Race Black 6 75.7 50.3 20.5 5 130 5 34 85 115 130 130 130 130 

Race Hispanic 3 116.7 30.6 17.6 90 150 90 90 110 150 150 150 150 150 

Hispanic No 37 97.9 88.2 14.5 2 500 5 50 90 120 155 265 500 500 

Hispanic Yes 3 116.7 30.6 17.6 90 150 90 90 110 150 150 150 150 150 

Employment - 3 80.7 17.9 10.3 60 92 60 60 90 92 92 92 92 92 

Employment Full Time 20 97.6 104.7 23.4 2 500 4 42 84 115 143 328 500 500 

Employment Part Time 4 127.5 91.9 45.9 75 265 75 78 85 178 265 265 265 265 

Employment Not Employed 13 97.4 60.9 16.9 5 210 5 45 115 137 150 210 210 210 

Education - 3 80.7 17.9 10.3 60 92 60 60 90 92 92 92 92 92 

Education < High School 6 95.0 53.3 21.8 5 150 5 60 113 130 150 150 150 150 

Education High School Graduate 17 101.4 64.4 15.6 5 265 5 59 90 120 210 265 265 265 

Education < College 6 91.5 56.4 23.0 10 155 10 34 115 120 155 155 155 155 

Education College Graduate 7 126.4 168.2 63.6 5 500 5 45 70 110 500 500 500 500 

Education Post Graduate 1 2.0 - - 2 2 2 2 2 2 2 2 2 2 

Census Region Northeast 6 168.7 166.5 68.0 45 500 45 75 126 140 500 500 500 500 

Census Region Midwest 8 94.0 60.3 21.3 5 210 5 58 94 118 210 210 210 210 

Census Region South 18 85.9 61.8 14.6 2 265 2 50 76 115 155 265 265 265 

Census Region West 8 82.5 52.9 18.7 5 150 5 35 100 118 150 150 150 150 

Day Of Week Weekday 25 103.3 100.7 20.1 2 500 5 50 90 115 155 265 500 500 

Day Of Week Weekend 15 92.5 52.7 13.6 10 210 10 60 92 130 150 210 210 210 

Season Winter 11 86.5 58.0 17.5 2 210 2 45 80 120 140 210 210 210 

Season Spring 12 85.6 71.7 20.7 5 265 5 35 74 120 130 265 265 265 

Season Summer 12 118.7 125.8 36.3 5 500 5 55 101 113 137 500 500 500 

Season Fall 5 113.8 48.4 21.7 34 155 34 115 115 150 155 155 155 155 

Asthma No 37 95.5 83.9 13.8 2 500 5 50 90 120 150 210 500 500 

Asthma Yes 3 146.3 106.5 61.5 59 265 59 59 115 265 265 265 265 265 

Angina No 40 99.3 85.2 13.5 2 500 5 55 91 120 153 238 500 500 

Bronchitis/Emphysema No 35 92.3 84.3 14.3 2 500 5 50 90 115 130 210 500 500 

Bronchitis/Emphysema Yes 5 148.0 83.3 37.2 30 265 30 140 150 155 265 265 265 265 

Exposure Factors Handbook Page
 

November 2011 16-51 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-52 November 2011 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Indoors at Work (Non-Specific) 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 137 393.9 242.6 20.7 5 979 15 180 440 555 662 810 940 960 

Gender Male 96 435.3 244.0 24.9 10 979 20 245 473 598 765 840 960 979 

Gender Female 41 297.2 212.4 33.2 5 780 15 90 280 495 550 590 780 780 

Age (years) - 4 568.8 394.7 197.4 90 940 90 248 623 890 940 940 940 940 

Age (years) 1 to 4 2 200.0 70.7 50.0 150 250 150 150 200 250 250 250 250 250 

Age (years) 5 to 11 4 33.8 11.1 5.5 20 45 20 25 35 43 45 45 45 45 

Age (years) 12 to 17 2 207.5 166.2 117.5 90 325 90 90 208 325 325 325 325 325 

Age (years) 18 to 64 121 409.7 230.9 21.0 5 979 15 240 450 560 660 793 850 960 

Age (years) > 64 4 293.8 289.5 144.7 10 610 10 50 278 538 610 610 610 610 

Race White 113 397.9 235.2 22.1 5 979 15 210 450 555 660 780 940 960 

Race Black 13 379.2 286.5 79.5 10 850 10 85 405 510 810 850 850 850 

Race Some Others 1 405.0 - - 405 405 405 405 405 405 405 405 405 405 

Race Hispanic 9 314.8 266.2 88.7 30 793 30 95 245 440 793 793 793 793 

Race Refused 1 840.0 - - 840 840 840 840 840 840 840 840 840 840 

Hispanic No 121 388.7 242.1 22.0 5 979 15 180 405 550 660 795 940 960 

Hispanic Yes 12 361.1 242.1 69.9 30 793 30 138 370 510 660 793 793 793 

Hispanic DK 2 585.0 35.4 25.0 560 610 560 560 585 610 610 610 610 610 

Hispanic Refused 2 717.5 173.2 122.5 595 840 595 595 718 840 840 840 840 840 

Employment - 8 118.8 113.9 40.3 20 325 20 35 68 200 325 325 325 325 

Employment Full Time 97 440.7 237.6 24.1 10 979 15 300 480 585 690 815 960 979 

Employment Part Time 21 341.2 188.2 41.1 30 795 115 240 330 435 590 610 795 795 

Employment Not Employed 9 250.6 218.6 72.9 5 630 5 95 150 360 630 630 630 630 

Employment Refused 2 425.0 586.9 415.0 10 840 10 10 425 840 840 840 840 840 

Education - 11 234.1 266.3 80.3 20 840 20 40 150 325 610 840 840 840 

Education < High School 12 460.4 181.7 52.5 115 795 115 330 495 558 615 795 795 795 

Education High School Graduate 50 409.6 273.7 38.7 5 979 15 150 463 619 735 940 970 979 

Education < College 29 368.9 237.6 44.1 10 850 10 160 405 510 660 765 850 850 

Education College Graduate 22 405.7 184.2 39.3 90 815 150 240 375 540 595 645 815 815 

Education Post Graduate 13 443.7 218.1 60.5 10 793 10 360 500 585 630 793 793 793 

Census Region Northeast 22 405.5 193.8 41.3 15 765 90 320 398 540 660 662 765 765 

Census Region Midwest 26 418.6 250.9 49.2 10 940 13 180 473 610 690 780 940 940 

Census Region South 58 379.7 233.2 30.6 5 979 10 150 420 540 619 810 815 979 

Census Region West 31 391.7 289.5 52.0 10 960 20 90 405 630 795 850 960 960 

Day Of Week Weekday 121 401.8 242.5 22.0 5 979 15 210 450 560 660 810 940 960 

Day Of Week Weekend 16 334.3 243.3 60.8 13 795 13 98 340 495 690 795 795 795 

Season Winter 42 390.8 241.5 37.3 10 960 30 175 405 550 660 765 960 960 

Season Spring 34 361.3 237.0 40.6 10 840 30 150 360 525 660 815 840 840 

Season Summer 41 400.9 262.9 41.1 5 979 13 210 450 570 690 810 979 979 

Season Fall 20 441.8 219.4 49.1 10 793 13 285 490 620 661 728 793 793 

Asthma No 124 393.2 237.3 21.3 5 960 20 180 440 553 660 795 850 940 

Asthma Yes 13 400.9 300.2 83.2 10 979 10 240 320 590 793 979 979 979 

Angina No 133 397.7 243.3 21.1 5 979 15 190 440 555 662 810 940 960 

Angina Yes 3 266.7 255.8 147.7 90 560 90 90 150 560 560 560 560 560 

Angina DK 1 280.0 - - 280 280 280 280 280 280 280 280 280 280 

Bronchitis/Emphysema No 131 397.1 242.0 21.1 5 979 20 180 440 555 662 810 940 960 

Bronchitis/Emphysema Yes 5 333.4 299.4 133.9 10 619 10 13 460 565 619 619 619 619 

Bronchitis/Emphysema DK 1 280.0 - - 280 280 280 280 280 280 280 280 280 280 
 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-53 

Table 16-18. Time Spent (minutes/day) at Selected Indoor Locations, Doers Only (continued) 

Indoors at Dry Cleaners 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 34 82.0 151.7 26.0 2 515 5 5 10 90 325 500 

Gender Male 11 105.5 166.0 50.1 2 515 2 5 10 103 325 515 

Gender Female 23 70.8 146.8 30.6 5 500 5 5 10 35 300 485 

Age (years) - 1 485.0 - - 485 485 485 485 485 485 485 485 

Age (years) 1 to 4 2 20.0 21.2 15.0 5 35 5 5 20 35 35 35 

Age (years) 18 to 64 28 61.0 120.9 22.9 2 515 5 5 10 55 300 325 

Age (years) > 64 3 185.0 273.4 157.8 10 500 10 10 45 500 500 500 

Race White 25 70.7 143.7 28.7 2 515 5 5 10 35 300 485 

Race Black 7 131.4 199.0 75.2 5 500 5 10 20 325 500 500 

Race Some Others 1 10.0 - - 10 10 10 10 10 10 10 10 

Race Hispanic 1 91.0 - - 91 91 91 91 91 91 91 91 

Hispanic No 31 83.8 158.5 28.5 2 515 5 5 10 45 325 500 

Hispanic Yes 3 63.7 46.5 26.8 10 91 10 10 90 91 91 91 

Employment - 2 20.0 21.2 15.0 5 35 5 5 20 35 35 35 

Employment Full Time 25 83.1 151.8 30.4 2 515 5 5 10 90 325 485 

Employment Part Time 1 500.0 - - 500 500 500 500 500 500 500 500 

Employment Not Employed 6 28.5 33.9 13.9 5 91 5 10 10 45 91 91 

Education - 2 20.0 21.2 15.0 5 35 5 5 20 35 35 35 

Education < High School 4 234.0 209.2 104.6 45 500 45 68 196 400 500 500 

Education High School Graduate 8 84.1 165.0 58.3 5 485 5 13 18 62 485 485 

Education < College 6 146.3 220.3 90.0 5 515 5 10 12 325 515 515 

Education College Graduate 12 13.5 24.2 7.0 2 90 2 5 5 10 10 90 

Education Post Graduate 2 50.0 63.6 45.0 5 95 5 5 50 95 95 95 

Census Region Northeast 8 110.0 187.3 66.2 5 485 5 5 10 180 485 485 

Census Region Midwest 10 19.1 30.1 9.5 5 103 5 5 8 20 62 103 

Census Region South 8 197.0 212.0 74.9 15 515 15 30 93 400 515 515 

Census Region West 8 17.8 29.4 10.4 2 90 2 5 10 10 90 90 

Day Of Week Weekday 23 94.0 172.8 36.0 2 515 5 5 10 90 485 500 

Day Of Week Weekend 11 57.1 96.0 28.9 5 325 5 5 10 95 103 325 

Season Winter 12 74.6 158.1 45.6 5 485 5 5 10 13 325 485 

Season Spring 4 44.5 41.7 20.8 10 103 10 15 33 74 103 103 

Season Summer 8 20.3 32.0 11.3 2 95 2 5 5 23 95 95 

Season Fall 10 155.4 205.7 65.1 5 515 5 13 55 300 508 515 

Asthma No 32 86.7 155.2 27.4 2 515 5 5 12 91 325 500 

Asthma Yes 2 7.5 3.5 2.5 5 10 5 5 7.5 10 10 10 

Angina No 33 83.9 153.6 26.7 2 515 5 5 10 90 325 500 

Angina Yes 1 20.0 - - 20 20 20 20 20 20 20 20 

Bronchitis/Emphysema No 33 84.1 153.5 26.7 2 515 5 5 10 90 325 500 

Bronchitis/Emphysema Yes 1 15.0 - - 15 15 15 15 15 15 15 15 

515 

515 

500 

485 

35 

515 

500 

515 

500 

10 

91 

515 

91 

35 

515 

500 

91 

35 

500 

485 

515 

90 

95 

485 

103 

515 

90 

515 

325 

485 

103 

95 

515 

515 

10 

515 

20 

515 

15 

515 

515 

500 

485 

35 

515 

500 

515 

500 

10 

91 

515 

91 

35 

515 

500 

91 

35 

500 

485 

515 

90 

95 

485 

103 

515 

90 

515 

325 

485 

103 

95 

515 

515 

10 

515 

20 

515 

15 

- = Indicates missing data. 

DK = The respondent replied “don’t know”. 

Refused = Refused data. 

N = Doer sample size. 

SD = Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 
 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-19. Time Spent (minutes/day) in Selected Outdoor Locations Whole Population and Doers Only, 

Children <21 Years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

School Grounds/Playground―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

2 

0 

4 

5 

8 

10 

8 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

10 

20 

0 

0 

0 

0 

0 

60 

80 

50 

0 

0 

50 

64 

121 

120 

135 

53 

0 

131 

127 

170 

160 

180 

140 

0 

175 

625 

315 

570 

510 

School Grounds/Playground―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

1 

0 

5 

12 

52 

62 

34 

-

-

-

138 

80 

72 

116 

140 

-

10 

20 

10 

3 

10 

-

-

-

22 

10 

4 

10 

-

-

-

24 

10 

5 

10 

-

-

-

31 

10 

5 

13 

-

-

-

42 

15 

5 

18 

-

-

-

59 

30 

21 

46 

-

-

-

118 

59 

53 

95 

-

-

-

138 

106 

95 

161 

-

-

-

150 

169 

149 

201 

-

-

-

364 

217 

178 

305 

-

-

-

521 

280 

217 

418 

-

-

-

573 

298 

360 

464 

140 

-

175 

625 

315 

570 

510 

Parks or Golf Courses―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

3 

3 

12 

10 

16 

19 

22 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

24 

71 

72 

114 

150 

45 

0 

126 

163 

328 

265 

381 

63 

25 

246 

220 

483 

452 

546 

85 

360 

755 

585 

665 

1,065 

870 

Parks or Golf Courses―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

3 

2 

7 

26 

34 

38 

47 

-

-

-

144 

236 

237 

225 

30 

30 

21 

25 

25 

15 

1 

-

-

-

26 

30 

15 

7 

-

-

-

28 

35 

15 

14 

-

-

-

31 

43 

15 

15 

-

-

-

44 

52 

27 

24 

-

-

-

63 

73 

86 

60 

-

-

-

113 

123 

164 

160 

-

-

-

165 

394 

266 

308 

-

-

-

273 

568 

470 

557 

-

-

-

388 

644 

851 

633 

-

-

-

505 

662 

954 

677 

-

-

-

545 

663 

1,010 

773 

85 

360 

755 

585 

665 

1,065 

870 

Pool, River, or Lake―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

0 

1 

12 

5 

9 

4 

8 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

14 

0 

0 

0 

0 

0 

0 

228 

85 

220 

60 

145 

0 

0 

352 

163 

295 

160 

240 

0 

118 

435 

630 

375 

235 

570 

Pool, River, or Lake―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

0 

1 

6 

9 

24 

16 

22 

-

-

-

-

178 

121 

179 

-

118 

95 

45 

25 

58 

20 

-

-

-

-

26 

58 

22 

-

-

-

-

27 

59 

24 

-

-

-

-

32 

59 

31 

-

-

-

-

46 

60 

40 

-

-

-

-

75 

60 

55 

-

-

-

-

155 

85 

125 

-

-

-

-

294 

206 

238 

-

-

-

-

319 

225 

415 

-

-

-

-

359 

228 

548 

-

-

-

-

370 

232 

564 

-

-

-

-

373 

234 

567 

-

118 

435 

630 

375 

235 

570 

- = Indicates missing data. 

N = Doer sample size. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-54 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only 

Outdoors on School Grounds/Playground 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 259 98.4 110.1 6.8 1 690 5 30 70 120 208 300 540 570 

Sex Male 0.136 118.0 126.4 10.8 1 690 10 35 85 149 255 370 555 625 

Sex Female 123 76.7 83.9 7.6 1 570 5 20 51 120 180 225 270 440 

Age (years) - 2 275.0 374.8 265.0 10 540 10 10 275 540 540 540 540 540 

Age (years) 1 to 4 9 85.0 61.1 20.4 10 175 10 30 65 140 175 175 175 175 

Age (years) 5 to 11 64 88.0 95.6 12.0 5 625 10 30 60 120 170 220 315 625 

Age (years) 12 to 17 76 78.7 88.2 10.1 3 570 5 25 55 105 165 225 370 570 

Age (years) 18 to 64 101 119.8 127.6 12.7 1 690 5 30 85 165 240 360 540 555 

Age (years) >64 7 65.0 47.3 17.9 5 150 5 30 60 95 150 150 150 150 

Race White 208 98.2 106.5 7.4 1 690 9 30 70 125 190 281 510 555 

Race Black 23 128.4 157.5 32.9 5 570 5 25 67 170 300 540 570 570 

Race Asian 6 59.0 66.1 27.0 10 179 10 10 35 85 179 179 179 179 

Race Some Others 7 70.0 59.7 22.6 10 180 10 10 60 105 180 180 180 180 

Race Hispanic 15 83.7 103.0 26.6 1 370 1 10 30 120 228 370 370 370 

Hispanic No 225 102.6 113.7 7.6 3 690 9 30 70 125 210 300 540 570 

Hispanic Yes 32 71.2 79.9 14.1 1 370 1 13 33 110 150 228 370 370 

Hispanic DK 2 57.5 31.8 22.5 35 80 35 35 58 80 80 80 80 80 

Employment - 143 80.2 88.0 7.4 3 625 9 25 55 115 160 215 315 570 

Employment Full Time 48 130.3 127.2 18.4 1 555 10 40 85 180 300 360 555 555 

Employment Part Time 24 129.7 158.9 32.4 3 690 10 35 85 144 228 510 690 690 

Employment Not Employed 42 95.4 94.8 14.6 1 440 5 30 80 120 180 235 440 440 

Employment Refused 2 322.5 307.6 217.5 105 540 105 105 323 540 540 540 540 540 

Education - 162 86.6 94.6 7.4 3 625 10 27 60 120 170 220 370 570 

Education < High School 11 124.8 171.9 51.8 1 540 1 5 45 180 345 540 540 540 

Education High School Graduate 33 113.6 110.7 19.3 3 555 5 30 90 160 240 290 555 555 

Education < College 19 129.8 147.4 33.8 5 510 5 33 70 210 440 510 510 510 

Education College Graduate 19 122.1 149.9 34.4 5 690 5 50 85 125 235 690 690 690 

Education Post Graduate 15 102.9 98.1 25.3 1 360 1 30 75 125 235 360 360 360 

Census Region Northeast 66 106.0 115.2 14.2 5 690 10 30 85 150 190 281 540 690 

Census Region Midwest 53 86.1 109.2 15.0 3 540 5 20 50 115 190 290 510 540 

Census Region South 82 85.5 92.4 10.2 1 570 5 30 60 115 180 255 360 570 

Census Region West 58 119.3 125.6 16.5 1 625 10 30 85 160 235 440 555 625 

Day Of Week Weekday 205 87.0 105.5 7.4 1 625 5 25 55 115 180 240 540 555 

Day Of Week Weekend 54 141.5 117.1 15.9 10 690 25 67 113 180 290 345 440 690 

Season Winter 53 72.2 102.0 14.0 1 555 3 20 35 85 130 315 440 555 

Season Spring 88 108.6 96.5 10.3 5 540 10 45 85 148 215 255 510 540 

Season Summer 65 116.4 137.9 17.1 5 690 10 30 75 135 270 360 625 690 

Season Fall 53 85.5 96.2 13.2 5 540 5 20 55 120 180 235 345 540 

Asthma No 237 100.9 113.2 7.4 1 690 5 30 70 120 215 315 540 570 

Asthma Yes 22 70.9 62.0 13.2 5 179 10 15 45 145 160 165 179 179 

Angina No 254 99.1 110.8 7.0 1 690 5 30 69 120 208 300 540 570 

Angina Yes 5 61.2 53.4 23.9 1 130 1 15 70 90 130 130 130 130 

Bronchitis/Emphysema No 248 100.6 111.6 7.1 1 690 5 30 71 125 210 300 540 570 

Bronchitis/Emphysema Yes 10 52.7 45.4 14.4 9 160 9 22 44 60 125 160 160 160 

Bronchitis/Emphysema DK 1 15.0 0.0 0.0 15 15 15 15 15 15 15 15 15 15 

Exposure Factors Handbook Page
 

November 2011 16-55 
 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoor Playing 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

-

Full Time 

Part Time 

Not Employed 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

Yes 

No 

Yes 

59 

26 

33 

1 

4 

9 

1 

40 

4 

50 

2 

1 

1 

5 

51 

8 

15 

15 

7 

22 

15 

5 

10 

18 

8 

3 

17 

12 

15 

15 

42 

17 

10 

10 

31 

8 

56 

3 

58 

1 

55 

4 

97.4 

108.2 

88.8 

170.0 

83.3 

148.3 

15.0 

92.1 

52.5 

93.9 

86.5 

100.0 

30.0 

149.0 

93.3 

123.1 

123.5 

67.2 

87.7 

103.2 

123.5 

57.0 

148.5 

74.7 

75.4 

58.3 

114.1 

78.6 

109.7 

81.2 

86.8 

123.5 

66.5 

135.3 

92.4 

108.0 

94.8 

145.0 

97.0 

120.0 

90.1 

198.5 

95.4 

94.8 

96.4 

-

89.7 

144.3 

-

86.4 

15.0 

90.2 

37.5 

-

-

164.9 

89.7 

130.2 

124.4 

30.9 

54.1 

110.1 

124.4 

6.7 

150.5 

45.2 

35.5 

24.7 

103.3 

32.4 

109.5 

107.7 

79.2 

126.0 

46.3 

114.7 

95.0 

115.7 

91.5 

173.9 

96.1 

-

87.1 

157.5 

12.4 

18.6 

16.8 

-

44.8 

48.1 

-

13.7 

7.5 

12.8 

26.5 

-

-

73.7 

12.6 

46.0 

32.1 

8.0 

20.5 

23.5 

32.1 

3.0 

47.6 

10.6 

12.5 

14.2 

25.0 

9.3 

28.3 

27.8 

12.2 

30.6 

14.6 

36.3 

17.1 

40.9 

12.2 

100.4 

12.6 

-

11.7 

78.8 

5 

15 

5 

170 

15 

5 

15 

20 

30 

5 

60 

100 

30 

20 

5 

20 

5 

20 

30 

25 

5 

45 

30 

20 

30 

30 

15 

30 

30 

5 

5 

25 

5 

45 

5 

25 

5 

30 

5 

120 

5 

60 

435 

360 

435 

170 

210 

360 

15 

435 

60 

420 

113 

100 

30 

435 

420 

435 

360 

135 

194 

435 

360 

60 

435 

194 

120 

75 

360 

150 

420 

435 

360 

435 

150 

435 

420 

360 

435 

345 

435 

120 

435 

420 

15 

15 

5 

170 

15 

5 

15 

28 

30 

15 

60 

100 

30 

20 

15 

20 

5 

20 

30 

30 

5 

45 

30 

20 

30 

30 

15 

30 

30 

5 

15 

25 

5 

45 

15 

25 

15 

30 

15 

120 

15 

60 

45 

60 

45 

170 

20 

55 

15 

53 

45 

45 

60 

100 

30 

60 

45 

60 

15 

45 

60 

45 

15 

60 

60 

45 

45 

30 

60 

60 

30 

20 

30 

45 

30 

60 

45 

30 

45 

30 

45 

120 

45 

90 

60 

75 

60 

170 

54 

60 

15 

65 

60 

60 

87 

100 

30 

110 

60 

90 

60 

60 

60 

60 

60 

60 

95 

60 

75 

70 

70 

65 

60 

60 

60 

60 

60 

108 

60 

68 

60 

60 

60 

120 

60 

157 

110 

135 

100 

170 

147 

280 

15 

103 

60 

100 

113 

100 

30 

120 

100 

115 

210 

85 

110 

105 

210 

60 

135 

95 

107 

75 

120 

98 

135 

105 

100 

120 

105 

165 

100 

142 

108 

345 

105 

120 

100 

307 

210 

280 

150 

170 

210 

360 

15 

143 

60 

202 

113 

100 

30 

435 

194 

435 

345 

113 

194 

150 

345 

60 

428 

150 

120 

75 

345 

113 

280 

165 

165 

420 

135 

303 

210 

360 

194 

345 

210 

120 

170 

420 

360 

345 

420 

170 

210 

360 

15 

307 

60 

345 

113 

100 

30 

435 

345 

435 

360 

135 

194 

420 

360 

60 

435 

194 

120 

75 

360 

150 

420 

435 

280 

435 

150 

435 

345 

360 

360 

345 

360 

120 

345 

420 

420 

360 

435 

170 

210 

360 

15 

435 

60 

390 

113 

100 

30 

435 

360 

435 

360 

135 

194 

435 

360 

60 

435 

194 

120 

75 

360 

150 

420 

435 

360 

435 

150 

435 

420 

360 

420 

345 

420 

120 

360 

420 

435 

360 

435 

170 

210 

360 

15 

435 

60 

420 

113 

100 

30 

435 

420 

435 

360 

135 

194 

435 

360 

60 

435 

194 

120 

75 

360 

150 

420 

435 

360 

435 

150 

435 

420 

360 

435 

345 

435 

120 

435 

420 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-56 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors at a Park/Golf Course 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

<College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

506 

291 

214 

1 

10 

21 

54 

52 

314 

55 

441 

19 

8 

16 

20 

2 

469 

34 

1 

2 

128 

201 

41 

132 

4 

140 

32 

108 

93 

83 

50 

106 

124 

136 

140 

276 

230 

83 

163 

192 

68 

466 

38 

2 

494 

9 

3 

490 

14 

2 

198.6 

205.8 

187.7 

420.0 

122.4 

149.9 

207.6 

238.5 

197.8 

189.0 

205.3 

114.5 

185.6 

171.3 

169.5 

75.0 

202.7 

154.8 

10.0 

75.0 

208.2 

195.8 

213.5 

190.9 

130.0 

202.7 

180.8 

219.7 

191.6 

203.5 

157.8 

184.9 

194.6 

218.8 

192.9 

196.0 

201.7 

209.1 

168.5 

219.6 

198.7 

192.1 

284.5 

75.0 

197.9 

247.8 

170.0 

197.0 

273.1 

75.0 

190.2 

183.1 

199.4 

-

60.2 

176.3 

184.5 

242.2 

185.9 

182.9 

195.3 

103.7 

233.4 

154.2 

135.8 

63.6 

193.6 

135.0 

-

63.6 

209.6 

189.0 

215.6 

166.0 

106.8 

204.7 

207.8 

197.2 

171.2 

183.1 

166.6 

177.4 

188.7 

211.5 

179.4 

189.3 

191.8 

195.2 

159.1 

199.9 

217.9 

178.8 

288.7 

63.6 

189.8 

235.3 

170.6 

184.6 

339.1 

63.6 

8.5 

10.7 

13.6 

-

19.0 

38.5 

25.1 

33.6 

10.5 

24.7 

9.3 

23.8 

82.5 

38.6 

30.4 

45.0 

8.9 

23.2 

-

45.0 

18.5 

13.3 

33.7 

14.5 

53.4 

17.3 

36.7 

19.0 

17.8 

20.1 

23.6 

17.2 

16.9 

18.1 

15.2 

11.4 

12.6 

21.4 

12.5 

14.4 

26.4 

8.3 

46.8 

45.0 

8.5 

78.4 

98.5 

8.3 

90.6 

45.0 

1 

1 

5 

420 

30 

21 

25 

15 

1 

10 

1 

15 

30 

30 

30 

30 

1 

15 

10 

30 

15 

8 

20 

1 

30 

15 

30 

10 

1 

5 

10 

1 

10 

10 

5 

5 

1 

15 

8 

5 

1 

1 

30 

30 

1 

35 

30 

1 

20 

30 

1,065 

1,015 

1,065 

420 

225 

755 

665 

1,065 

1,015 

735 

1,065 

425 

665 

560 

555 

120 

1,065 

555 

10

120 

1,065 

1,015 

870 

810 

280 

1,065 

995 

1,015 

870 

930 

735 

1,065 

1,015 

930 

870 

1,015 

1,065 

1,065 

930 

1,015 

995 

1,015 

1,065 

120 

1,065 

730 

360 

1,065 

995 

120 

20 

25 

15 

420 

30 

25 

35 

15 

20 

20 

20 

15 

30 

30 

33 

30 

20 

30 

10

30 

25 

25 

20 

15 

30 

21 

30 

20 

15 

23 

20 

20 

30 

20 

18 

20 

20 

30 

20 

20 

20 

20 

35 

30 

20 

35 

30 

20 

20 

30 

60 

60 

55 

420 

60 

50 

70 

60 

60 

30 

60 

30 

33 

58 

77 

30 

60 

60 

10 

30 

60 

60 

60 

60 

60 

60 

30 

78 

60 

60 

45 

60 

60 

60 

58 

60 

60 

60 

50 

65 

60 

60 

90 

30 

60 

60 

30 

60 

75 

30 

135 

150 

120 

420 

120 

85 

125 

148 

150 

120 

150 

90 

48 

120 

145 

75 

135 

138 

10 

75 

120 

135 

132 

160 

105 

120 

110 

163 

150 

145 

75 

124 

135 

150 

131 

145 

130 

165 

120 

155 

118 

135 

170 

75 

135 

120 

120 

145 

100 

75 

270 

285 

250 

420 

160 

150 

275 

338 

270 

300 

275 

155 

315 

235 

205 

120 

270 

175 

10 

120 

275 

270 

260 

270 

200 

270 

245 

281 

275 

270 

255 

240 

255 

325 

273 

253 

280 

275 

235 

290 

280 

270 

390 

120 

270 

330 

360 

270 

280 

120 

465 

510 

435 

420 

202 

360 

555 

590 

440 

510 

480 

240 

665 

405 

373 

120 

480 

310 

10

120 

555 

450 

540 

420 

280 

499 

385 

545 

440 

450 

338 

450 

420 

525 

430 

510 

455 

440 

360 

535 

555 

450 

870 

120 

459 

730 

360 

455 

930 

120 

590 748 870 

590 730 755 

590 870 930 

420 420 420 

225 225 225 

425 755 755 

635 660 665 

840 915 1,065 

580 748 870 

570 590 735 

605 795 915 

425 425 425 

665 665 665 

560 560 560 

495 555 555 

120 120 120 

605 755 915 

555 555 555 

10 10 10 

120 120 120 

645 840 915 

570 748 930 

660 870 870 

525 730 735 

280 280 280 

640 840 915 

570 995 995 

625 730 810 

510 748 870 

590 795 930 

555 703 735 

574 635 660 

590 735 995 

720 840 915 

575 755 810 

625 748 840 

580 810 915 

660 795 1,065 

510 570 755 

630 840 915 

735 810 995 

580 700 755 

995 1,065 1,065 

120 120 120 

590 755 915 

730 730 730 

360 360 360 

585 735 840 

995 995 995 

120 120 120 

Exposure Factors Handbook Page
 

November 2011 16-57 
 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors at a Pool/River/Lake 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

283 

152 

131 

6 

14 

29 

22 

187 

25 

246 

12 

4 

5 

12 

4 

259 

20 

4 

66 

119 

26 

69 

3 

73 

18 

69 

62 

37 

24 

61 

41 

111 

70 

165 

118 

30 

77 

151 

25 

262 

17 

4 

272 

8 

3 

266 

14 

3 

209.6 

229.8 

186.0 

175.0 

250.6 

175.4 

128.3 

224.5 

194.2 

201.6 

380.6 

265.0 

237.0 

161.0 

243.8 

208.9 

210.9 

243.8 

176.9 

210.7 

217.0 

238.9 

141.7 

172.9 

267.6 

213.2 

233.3 

230.9 

172.7 

220.7 

219.2 

182.2 

237.6 

188.8 

238.6 

173.2 

206.5 

219.7 

201.4 

209.0 

238.8 

121.3 

205.9 

359.4 

141.7 

211.0 

197.1 

141.7 

185.7 

202.7 

161.3 

157.0 

177.5 

117.9 

94.4 

203.8 

161.8 

182.3 

231.9 

247.1 

129.9 

131.7 

208.6 

187.8 

160.1 

208.6 

131.3 

176.1 

199.9 

236.2 

52.5 

130.0 

159.4 

224.1 

192.4 

187.3 

197.0 

172.4 

257.2 

161.3 

181.8 

179.9 

190.4 

181.7 

163.6 

196.8 

189.7 

188.2 

162.0 

59.2 

185.2 

178.8 

52.5 

189.1 

131.5 

52.5 

11.0 

16.4 

14.1 

64.1 

47.4 

21.9 

20.1 

14.9 

32.4 

11.6 

66.9 

123.5 

58.1 

38.0 

104.3 

11.7 

35.8 

104.3 

16.2 

16.1 

39.2 

28.4 

30.3 

15.2 

37.6 

27.0 

24.4 

30.8 

40.2 

22.1 

40.2 

15.3 

21.7 

14.0 

17.5 

33.2 

18.6 

16.0 

37.9 

11.6 

39.3 

29.6 

11.2 

63.2 

30.3 

11.6 

35.2 

30.3 

5 

10 

5 

60 

90 

25 

40 

5 

20 

5 

20 

30 

70 

20 

90 

5 

20 

90 

25 

10 

20 

5 

90 

20 

40 

10 

5 

14 

20 

30 

10 

5 

25 

10 

5 

20 

15 

5 

20 

5 

15 

60 

5 

60 

90 

5 

15 

90 

1,440 

1,440 

645 

480 

630 

390 

420 

1,440 

525 

1,440 

690 

505 

435 

390 

550 

1,440 

540 

550 

630 

900 

670 

1,440 

195 

630 

600 

1,440 

690 

645 

900 

900 

1,440 

670 

690 

1,440 

900 

630 

690 

1,440 

670 

1,440 

570 

195 

1,440 

690 

195 

1,440 

440 

195 

25 

30 

20 

60 

90 

30 

58 

20 

30 

25 

20 

30 

70 

20 

90 

25 

29 

90 

40 

20 

30 

20 

90 

30 

40 

20 

30 

20 

25 

30 

20 

20 

40 

30 

20 

20 

30 

26 

45 

25 

15 

60 

25 

60 

90 

25 

15 

90 

60 

83 

60 

85 

130 

60 

60 

60 

60 

60 

178 

53 

220 

53 

115 

60 

88 

115 

70 

65 

60 

65 

90 

70 

145 

60 

65 

70 

45 

60 

60 

60 

90 

60 

75 

40 

80 

65 

70 

60 

105 

75 

60 

288 

90 

60 

90 

90 

150 

174 

135 

115 

168 

145 

83 

150 

115 

145 

450 

263 

225 

113 

168 

150 

155 

168 

143 

150 

120 

145 

140 

140 

248 

145 

150 

173 

113 

180 

120 

118 

180 

125 

188 

103 

180 

155 

105 

150 

225 

115 

145 

340 

140 

150 

173 

140 

296 

305 

280 

195 

370 

293 

210 

320 

277 

285 

563 

478 

235 

265 

373 

295 

338 

373 

235 

298 

320 

370 

195 

225 

375 

285 

360 

400 

240 

325 

280 

280 

300 

255 

350 

270 

288 

300 

310 

295 

350 

168 

291 

435 

195 

296 

300 

195 

480 

510 

440 

480 

560 

365 

225 

511 

480 

440 

615 

505 

435 

375 

550 

480 

451 

550 

370 

510 

570 

510 

195 

370 

525 

511 

550 

505 

370 

390 

480 

420 

548 

420 

555 

493 

480 

445 

510 

480 

525 

195 

480 

690 

195 

480 

370 

195 

570 

600 

550 

480 

630 

375 

235 

615 

510 

560 

690 

505 

435 

390 

550 

585 

526 

550 

420 

600 

580 

630 

195 

420 

600 

670 

580 

630 

480 

510 

600 

525 

615 

511 

630 

585 

555 

580 

510 

580 

570 

195 

570 

690 

195 

580 

440 

195 

670 

690 

630 

480 

630 

390 

420 

690 

525 

670 

690 

505 

435 

390 

550 

670 

540 

550 

560 

645 

670 

690 

195 

560 

600 

690 

615 

645 

900 

670 

1,440 

630 

690 

615 

690 

630 

670 

630 

670 

670 

570 

195 

645 

690 

195 

670 

440 

195 

690 

900 

630 

480 

630 

390 

420 

900 

525 

690 

690 

505 

435 

390 

550 

690 

540 

550 

630 

670 

670 

1,440 

195 

630 

600 

1,440 

690 

645 

900 

900 

1,440 

645 

690 

670 

690 

630 

690 

900 

670 

690 

570 

195 

690 

690 

195 

690 

440 

195 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-58 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors on a Sidewalk, Street, or in the Neighborhood 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

896 

409 

487 

15 

30 

75 

74 

580 

122 

727 

87 

11 

18 

42 

11 

807 

79 

1 

9 

176 

384 

74 

255 

7 

198 

56 

223 

172 

138 

109 

202 

193 

298 

203 

642 

254 

210 

242 

276 

168 

832 

57 

7 

857 

33 

6 

855 

34 

7 

85.8 

108.8 

66.5 

72.5 

54.8 

110.8 

52.6 

94.3 

59.4 

85.7 

89.2 

88.7 

80.6 

71.4 

122.9 

87.5 

67.8 

2.0 

100.8 

79.2 

102.2 

74.4 

70.0 

45.1 

74.9 

131.2 

100.2 

77.2 

76.3 

78.2 

89.1 

87.9 

79.9 

89.1 

86.7 

83.5 

73.5 

97.9 

84.0 

86.6 

86.1 

85.6 

48.9 

86.2 

81.7 

52.0 

84.8 

117.7 

46.3 

133.8 

168.1 

91.9 

69.4 

52.7 

116.8 

74.8 

153.9 

61.5 

136.5 

132.7 

114.0 

106.0 

110.8 

117.7 

136.1 

110.3 

-

115.9 

96.3 

169.5 

113.9 

94.0 

36.6 

92.3 

247.3 

146.9 

128.8 

106.6 

121.3 

132.3 

153.3 

125.5 

127.9 

143.9 

104.2 

144.3 

137.2 

123.1 

131.9 

129.5 

193.1 

28.0 

134.9 

117.4 

29.3 

132.3 

176.4 

27.5 

4.5 

8.3 

4.2 

17.9 

9.6 

13.5 

8.7 

6.4 

5.6 

5.1 

14.2 

34.4 

25.0 

17.1 

35.5 

4.8 

12.4 

-

38.6 

7.3 

8.7 

13.2 

5.9 

13.8 

6.6 

33.0 

9.8 

9.8 

9.1 

11.6 

9.3 

11.0 

7.3 

9.0 

5.7 

6.5 

10.0 

8.8 

7.4 

10.2 

4.5 

25.6 

10.6 

4.6 

20.4 

11.9 

4.5 

30.3 

10.4 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

2 

10 

1 

2 

1 

1 

2 

2 

1 

1 

1 

1 

2 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

2 

1 

1 

2 

1 

3 

2 

1,440 

1,440 

580 

290 

235 

540 

435 

1,440 

380 

1,440 

565 

405 

420 

525 

310 

1,440 

615 

2

310 

540 

1,440 

795 

615 

90 

540 

1,440 

795 

675 

600 

710 

735 

1,440 

710 

795 

1,440 

565 

1,440 

795 

690 

710 

795 

1,440 

90 

1,440 

465 

90 

1,440 

735 

90 

2 

3 

1 

1 

2 

5 

2 

2 

2 

2 

2 

2 

10 

1 

2 

2 

1 

2

2 

2 

3 

1 

1 

2 

2 

1 

5 

1 

3 

5 

3 

2 

2 

1 

2 

2 

1 

4 

4 

2 

2 

1 

2

2 

1 

2

2 

8 

2 

15 

20 

15 

40 

10 

20 

15 

15 

20 

15 

10 

30 

20 

20 

40 

15 

15 

2

40 

15 

15 

15 

15 

4 

15 

15 

20 

10 

20 

20 

15 

15 

15 

20 

15 

25 

15 

25 

15 

15 

15 

15 

30

15 

17 

40

15 

30 

32 

40 

45 

35 

55 

43 

65 

30 

40 

40 

41 

35 

45 

40 

40 

60 

45 

30 

2

60 

45 

41 

43 

40 

40 

41 

40 

45 

30 

45 

45 

45 

30 

35 

45 

40 

45 

33 

45 

45 

40 

40 

35 

60

40 

45 

60

40 

45 

40 

90 

120 

75 

90 

78 

178 

60 

83 

75 

90 

120 

120 

75 

75 

290 

90 

62 

2 

90 

110 

75 

86 

85 

90 

90 

118 

95 

75 

70 

60 

90 

85 

75 

105 

80 

90 

60 

120 

90 

90 

90 

90 

60 

90 

60 

60 

85 

120 

60 

223 

330 

152 

120 

125 

240 

125 

278 

120 

215 

324 

149 

240 

135 

300 

225 

140 

2

310 

200 

330 

180 

152 

90 

185 

465 

275 

180 

205 

200 

235 

240 

185 

210 

223 

220 

160 

240 

200 

240 

225 

180 

90

223 

250 

90

225 

215 

90 

405 

525 

255 

290 

158 

410 

200 

480 

190 

405 

426 

405 

420 

290 

310 

410 

300 

2

310 

260 

525 

255 

270 

90 

240 

710 

480 

435 

310 

330 

410 

355 

420 

300 

426 

310 

270 

435 

420 

405 

418 

235 

90

410 

380 

90

405 

690 

90 

565 

615 

435 

290 

235 

465 

338 

600 

235 

570 

540 

405 

420 

525 

310 

565 

525 

2 

310 

435 

600 

390 

380 

90 

435 

735 

600 

570 

485 

560 

530 

565 

532 

570 

585 

440 

560 

570 

525 

600 

565 

260 

90 

565 

465 

90 

560 

735 

90 

615 

710 

465 

290 

235 

540 

435 

690 

270 

675 

565 

405 

420 

525 

310 

600 

615 

2 

310 

465 

710 

795 

485 

90 

465 

1,440 

680 

600 

565 

570 

570 

600 

680 

615 

680 

480 

710 

675 

580 

615 

600 

1,440 

90 

615 

465 

90 

600 

735 

90 

Exposure Factors Handbook Page
 

November 2011 16-59 
 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

At Home in the Yard or Other Areas Outside the House 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

2,308 

1,198 

1,107 

3 

27 

151 

271 

157 

1,301 

401 

1,966 

173 

21 

37 

83 

28 

2,122 

153 

10 

23 

581 

807 

166 

739 

15 

615 

236 

618 

381 

251 

207 

473 

456 

832 

547 

1,453 

855 

399 

787 

796 

326 

2,129 

166 

13 

2,228 

63 

17 

2,191 

105 

12 

137.6 

158.4 

114.9 

183.3 

167.4 

135.3 

150.6 

113.2 

136.4 

141.1 

139.0 

128.4 

101.2 

183.5 

106.1 

152.3 

137.7 

125.0 

213.8 

176.7 

137.5 

131.1 

126.1 

146.1 

198.0 

136.3 

161.0 

144.7 

128.8 

123.0 

127.1 

137.7 

138.9 

136.5 

138.2 

126.9 

155.7 

112.2 

149.7 

143.7 

124.5 

137.7 

131.6 

188.5 

136.5 

158.7 

199.1 

138.8 

104.4 

207.5 

144.1 

160.0 

120.9 

60.3 

164.5 

111.5 

135.1 

117.7 

147.9 

155.2 

145.5 

144.6 

88.5 

161.9 

96.8 

151.0 

144.3 

134.3 

192.2 

156.6 

125.6 

150.7 

134.1 

149.7 

239.0 

125.7 

186.5 

144.9 

141.2 

135.8 

150.0 

132.8 

155.7 

146.7 

139.9 

131.6 

161.7 

136.0 

139.2 

155.9 

130.5 

144.4 

136.0 

192.1 

141.1 

216.3 

191.3 

145.0 

111.3 

192.2 

3.0 

4.6 

3.6 

34.8 

31.7 

9.1 

8.2 

9.4 

4.1 

7.8 

3.3 

11.0 

19.3 

26.6 

10.6 

28.5 

3.1 

10.9 

60.8 

32.6 

5.2 

5.3 

10.4 

5.5 

61.7 

5.1 

12.1 

5.8 

7.2 

8.6 

10.4 

6.1 

7.3 

5.1 

6.0 

3.5 

5.5 

6.8 

5.0 

5.5 

7.2 

3.1 

10.6 

53.3 

3.0 

27.3 

46.4 

3.1 

10.9 

55.5 

1 

1 

1 

120 

2 

5 

2 

2 

1 

1 

1 

1 

12 

2 

2 

5 

1 

1 

3 

5 

2 

1 

1 

1 

5 

2 

2 

1 

1 

1 

1 

1 

2 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

5 

1 

2 

5 

1 

1 

5 

1,290 

1,290 

1,065 

240 

600 

630 

1,250 

660 

1,080 

1,290 

1,290 

1,250 

360 

750 

610 

600 

1,290 

750 

585 

600 

1,250 

1,080 

1,080 

1,290 

660 

1,250 

1,290 

840 

1,080 

750 

1,065 

750 

1,290 

1,080 

750 

1,250 

1,290 

1,080 

915 

1,290 

720 

1,290 

670 

600 

1,290 

1,080 

600 

1,290 

553 

600 

10 

10 

5 

120 

5 

25 

20 

5 

5 

10 

10 

5 

15 

3 

5 

5 

10 

5 

3 

5 

15 

5 

10 

10 

5 

15 

10 

5 

5 

10 

5 

10 

10 

10 

5 

5 

10 

5 

10 

10 

10 

10 

10 

5 

10 

5 

5 

10 

5 

5 

40 

60 

30 

120 

60 

60 

60 

30 

30 

45 

40 

30 

35 

84 

35 

60 

40 

30 

60 

60 

60 

30 

30 

45 

30 

60 

45 

40 

35 

30 

30 

45 

45 

35 

36 

35 

45 

30 

60 

45 

35 

40 

30 

60 

41 

30 

35 

45 

30 

60 

90 

120 

75 

190 

120 

90 

120 

80 

90 

90 

90 

95 

90 

120 

75 

98 

90 

85 

145 

160 

110 

80 

78 

100 

120 

105 

105 

100 

85 

75 

78 

90 

90 

90 

90 

90 

110 

60 

120 

99 

88 

90 

90 

90 

90 

75 

120 

90 

60 

140 

180 

198 

150 

240 

230 

180 

190 

150 

180 

180 

180 

180 

125 

270 

145 

210 

180 

150 

380 

240 

180 

175 

180 

185 

465 

180 

195 

195 

175 

160 

150 

185 

180 

180 

180 

165 

210 

140 

195 

180 

160 

180 

165 

300 

180 

180 

325 

180 

145 

330 

320 

360 

285 

240 

395 

305 

310 

240 

330 

302 

330 

270 

210 

380 

240 

360 

320 

270 

503 

360 

300 

307 

300 

360 

600 

300 

390 

360 

300 

300 

320 

317 

300 

310 

330 

300 

360 

300 

338 

330 

300 

315 

345 

480 

315 

420 

480 

320 

270 

480 

420 

500 

360 

240 

600 

345 

405 

405 

435 

465 

435 

390 

240 

553 

270 

510 

420 

435 

585 

510 

370 

450 

360 

465 

660 

370 

510 

479 

400 

390 

435 

420 

440 

420 

460 

395 

475 

380 

430 

450 

380 

420 

450 

600 

420 

485 

600 

430 

360 

600 

570 

627 

450 

240 

600 

450 

553 

462 

570 

598 

570 

462 

360 

750 

330 

600 

570 

575 

585 

600 

480 

600 

450 

585 

660 

480 

765 

555 

585 

575 

570 

532 

575 

570 

570 

553 

630 

540 

555 

610 

510 

570 

553 

600 

570 

1,065 

600 

570 

415 

600 

660 

730 

560 

240 

600 

480 

570 

610 

715 

660 

670 

745 

360 

750 

610 

600 

670 

630 

585 

600 

570 

745 

485 

655 

660 

570 

915 

660 

720 

690 

630 

600 

690 

730 

630 

610 

745 

690 

660 

715 

655 

690 

610 

600 

660 

1,080 

600 

690 

475 

600 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-60 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors in Parking Lot 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 226 70.7 126.7 8.4 1 910 2 10 20 60 190 309 510 580 

Gender Male 106 100.3 167.2 16.2 1 910 5 15 30 110 315 495 580 720 

Gender Female 120 44.6 64.8 5.9 1 295 1 5 20 47 168 188 248 285 

Age (years) - 3 135.0 195.0 112.6 15 360 15 15 30 360 360 360 360 360 

Age (years) 1 to 4 11 39.8 38.4 11.6 5 110 5 10 20 90 90 110 110 110 

Age (years) 5 to 11 5 62.0 63.7 28.5 5 170 5 30 45 60 170 170 170 170 

Age (years) 12 to 17 12 93.8 90.8 26.2 5 248 5 18 52 163 238 248 248 248 

Age (years) 18 to 64 182 70.0 132.7 9.8 1 910 2 10 20 60 190 309 550 720 

Age (years) > 64 13 74.5 127.9 35.5 1 465 1 10 25 60 180 465 465 465 

Race White 180 72.1 128.3 9.6 1 910 2 10 21 64 205 302 510 720 

Race Black 18 102.4 167.8 39.5 2 580 2 6 28 130 495 580 580 580 

Race Asian 3 21.7 7.6 4.4 15 30 15 15 20 30 30 30 30 30 

Race Some Others 5 50.0 46.1 20.6 5 115 5 10 45 75 115 115 115 115 

Race Hispanic 17 25.7 39.4 9.5 1 165 1 10 10 20 60 165 165 165 

Race Refused 3 135.0 195.0 112.6 15 360 15 15 30 360 360 360 360 360 

Hispanic No 196 69.3 114.1 8.1 1 720 2 10 24 68 190 295 495 580 

Hispanic Yes 25 42.9 103.3 20.7 1 510 1 5 10 20 75 165 510 510 

Hispanic DK 2 465.0 629.3 445.0 20 910 20 20 465 910 910 910 910 910 

Hispanic Refused 3 135.0 195.0 112.6 15 360 15 15 30 360 360 360 360 360 

Employment - 26 55.6 59.9 11.7 5 238 5 15 30 90 145 170 238 238 

Employment Full Time 117 83.3 155.1 14.3 1 910 2 10 20 60 240 495 580 720 

Employment Part Time 37 75.4 114.7 18.9 1 465 1 5 21 90 180 450 465 465 

Employment Not Employed 43 37.1 46.8 7.1 1 210 1 10 20 60 90 134 210 210 

Employment Refused 3 135.0 195.0 112.6 15 360 15 15 30 360 360 360 360 360 

Education - 33 69.7 85.6 14.9 1 360 5 15 30 90 180 248 360 360 

Education < High School 16 73.3 176.8 44.2 2 720 2 8 23 33 165 720 720 720 

Education High School Graduate 83 83.0 124.4 13.7 1 580 5 10 25 90 215 315 495 580 

Education < College 49 75.9 162.7 23.2 1 910 2 10 20 60 210 450 910 910 

Education College Graduate 23 48.8 107.2 22.3 1 510 2 5 10 30 130 135 510 510 

Education Post Graduate 22 35.5 54.5 11.6 1 185 1 5 15 30 115 180 185 185 

Census Region Northeast 56 57.4 82.6 11.0 1 495 1 13 28 75 135 180 295 495 

Census Region Midwest 48 73.4 118.6 17.1 1 550 5 10 25 63 248 315 550 550 

Census Region South 75 57.9 106.4 12.3 1 720 2 7 20 50 185 238 360 720 

Census Region West 47 104.3 189.9 27.7 3 910 5 10 20 90 450 510 910 910 

Day Of Week Weekday 154 64.9 136.7 11.0 1 910 2 7 20 43 180 450 550 720 

Day Of Week Weekend 72 83.3 101.7 12.0 1 465 5 15 35 113 240 309 360 465 

Season Winter 45 50.5 64.7 9.6 2 309 5 15 30 63 130 180 309 309 

Season Spring 57 82.9 131.2 17.4 1 495 1 10 20 90 240 465 495 495 

Season Summer 75 72.0 146.2 16.9 1 910 2 10 20 60 205 315 580 910 

Season Fall 49 73.1 133.2 19.0 1 720 1 10 20 75 205 295 720 720 

Asthma No 204 63.0 109.4 7.7 1 720 2 10 20 60 180 248 495 510 

Asthma Yes 18 149.7 238.5 56.2 1 910 1 15 45 145 580 910 910 910 

Asthma DK 4 110.0 166.9 83.4 15 360 15 23 33 198 360 360 360 360 

Angina No 217 69.3 127.1 8.6 1 910 2 10 20 60 185 309 510 580 

Angina Yes 5 99.6 83.1 37.1 35 238 35 40 75 110 238 238 238 238 

Angina DK 4 113.8 164.8 82.4 15 360 15 23 40 205 360 360 360 360 

Bronchitis/Emphysema No 211 65.6 114.2 7.9 1 720 2 10 20 60 180 295 495 550 

Bronchitis/Emphysema Yes 11 142.4 266.0 80.2 1 910 1 10 40 180 240 910 910 910 

Bronchitis/Emphysema DK 4 146.3 160.8 80.4 15 360 15 23 105 270 360 360 360 360 

Exposure Factors Handbook Page
 

November 2011 16-61 
 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors at a Service Station or Gas Station 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

No 

Yes 

191 

90 

101 

1 

3 

3 

11 

157 

16 

170 

11 

1 

3 

5 

1 

179 

12 

16 

110 

26 

38 

1 

18 

16 

46 

58 

30 

23 

33 

48 

68 

42 

122 

69 

56 

54 

51 

30 

174 

16 

1 

184 

7 

181 

10 

50.6 

73.5 

30.2 

86.0 

6.7 

66.7 

7.8 

54.2 

47.8 

50.9 

80.7 

5.0 

16.7 

10.2 

10.0 

53.1 

13.9 

18.8 

55.8 

34.7 

40.2 

790.0 

17.8 

103.0 

85.7 

41.8 

36.6 

10.0 

59.7 

28.6 

49.9 

69.8 

58.4 

36.8 

37.5 

80.1 

46.5 

28.8 

53.5 

15.8 

100.0 

46.8 

150.7 

47.1 

113.5 

125.5 

150.0 

94.9 

-

2.9 

98.3 

4.5 

135.6 

69.5 

124.0 

191.4 

-

20.2 

7.6 

-

129.2 

23.0 

43.2 

136.8 

71.8 

77.0 

-

40.7 

164.1 

162.9 

121.1 

111.6 

6.4 

149.2 

77.6 

134.0 

135.5 

145.1 

79.0 

100.6 

157.5 

137.7 

58.9 

130.8 

25.7 

-

120.6 

206.8 

124.0 

142.9 

9.1 

15.8 

9.4 

-

1.7 

56.7 

1.4 

10.8 

17.4 

9.5 

57.7 

-

11.7 

3.4 

-

9.7 

6.6 

10.8 

13.0 

14.1 

12.5 

-

9.6 

41.0 

24.0 

15.9 

20.4 

1.3 

26.0 

11.2 

16.2 

20.9 

13.1 

9.5 

13.4 

21.4 

19.3 

10.8 

9.9 

6.4 

-

8.9 

78.2 

9.2 

45.2 

1 

1 

2 

86 

5 

5 

1 

2 

5 

2 

4 

5 

5 

1 

10 

2 

1 

1 

2 

3 

4 

790 

1 

5 

3 

2 

2 

5 

2 

2 

1 

4 

2 

1 

2 

1 

2 

3 

1 

2 

100 

1 

10 

1 

5 

790 

645 

790 

86 

10 

180 

15 

790 

240 

790 

645 

5 

40 

20 

10 

790 

86 

180 

645 

355 

380 

790 

180 

520 

645 

790 

570 

30 

600 

510 

790 

520 

790 

390 

600 

645 

790 

295 

790 

110 

100 

790 

510 

790 

380 

5 

5 

5 

86 

5 

5 

1 

5 

5 

5 

4 

5 

5 

1 

10 

5 

1 

1 

5 

5 

5 

790 

1 

5 

5 

4 

4 

5 

3 

5 

5 

5 

5 

4 

4 

5 

5 

5 

5 

2 

100 

5 

10 

5 

5 

5 

5 

5 

86 

5 

5 

5 

5 

10 

5 

5 

5 

5 

5 

10 

5 

5 

5 

5 

5 

5 

790 

5 

10 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

100 

5 

15 

5 

10 

10 

10 

10 

86 

5 

15 

5 

10 

18 

10 

5 

5 

5 

10 

10 

10 

8 

8 

10 

10 

10 

790 

8 

15 

10 

13 

7 

10 

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86 

10 

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15 

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790 

15 

140 

85 

20 

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15 

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380 

15 

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105 

325 

44 

86 

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108 

140 

5 

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15 

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99 

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790 

15 

365 

380 

60 

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85 

368 

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790 

520 

645 

390 

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645 

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295 

645 

110 

100 

645 

510 

645 

380 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-62 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors at a Construction Site 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 143 437.1 242.1 20.2 1 1190 10 240 510 600 675 740 930 985 

Gender Male 130 461.5 232.5 20.4 1 1190 10 300 523 600 689 745 930 985 

Gender Female 13 192.8 202.8 56.2 5 630 5 60 135 165 535 630 630 630 

Age (years) - 1 510.0 - - 510 510 510 510 510 510 510 510 510 510 

Age (years) 1 to 4 2 240.0 254.6 180.0 60 420 60 60 240 420 420 420 420 420 

Age (years) 12 to 17 1 10.0 - - 10 10 10 10 10 10 10 10 10 10 

Age (years) 18 to 64 133 444.5 243.0 21.1 1 1190 10 240 520 600 687 745 930 985 

Age (years) > 64 6 396.7 188.8 77.1 60 560 60 300 460 540 560 560 560 560 

Race White 125 430.9 247.4 22.1 5 1190 10 240 510 600 687 740 930 985 

Race Black 10 430.1 233.3 73.8 1 630 1 170 550 585 615 630 630 630 

Race Some Others 2 492.5 60.1 42.5 450 535 450 450 493 535 535 535 535 535 

Race Hispanic 3 501.7 170.3 98.3 305 600 305 305 600 600 600 600 600 600 

Race Refused 3 618.3 166.5 96.1 510 810 510 510 535 810 810 810 810 810 

Hispanic No 129 426.2 247.1 21.8 1 1190 10 180 510 600 665 735 930 985 

Hispanic Yes 9 496.1 166.4 55.5 240 765 240 410 505 600 765 765 765 765 

Hispanic DK 2 577.5 180.3 127.5 450 705 450 450 578 705 705 705 705 705 

Hispanic Refused 3 635.0 156.1 90.1 510 810 510 510 585 810 810 810 810 810 

Employment - 3 163.3 223.7 129.1 10 420 10 10 60 420 420 420 420 420 

Employment Full Time 127 456.8 236.2 21.0 1 1190 15 285 520 605 690 745 930 985 

Employment Part Time 6 495.8 171.4 70.0 155 600 155 510 555 600 600 600 600 600 

Employment Not Employed 7 146.6 162.8 61.5 5 430 5 6 60 300 430 430 430 430 

Education - 4 250.0 251.8 125.9 10 510 10 35 240 465 510 510 510 510 

Education < High School 12 500.8 227.0 65.5 60 930 60 375 525 593 735 930 930 930 

Education High School Graduate 68 482.2 229.0 27.8 5 1190 20 395 523 593 720 780 985 1,190 

Education < College 41 417.7 241.0 37.6 1 745 10 170 520 615 645 687 745 745 

Education College Graduate 14 372.4 247.3 66.1 15 660 15 120 440 585 643 660 660 660 

Education Post Graduate 4 92.5 137.3 68.6 5 295 5 8 35 178 295 295 295 295 

Census Region Northeast 28 481.7 238.3 45.0 5 985 6 358 533 650 695 740 985 985 

Census Region Midwest 30 344.0 231.0 42.2 5 810 10 120 342 525 638 660 810 810 

Census Region South 57 474.0 248.3 32.9 1 1190 10 410 535 615 720 765 780 1190 

Census Region West 28 417.1 226.3 42.8 15 930 60 235 500 570 630 656 930 930 

Day Of Week Weekday 121 455.1 238.5 21.7 5 1190 15 285 525 600 687 745 930 985 

Day Of Week Weekend 22 338.0 243.0 51.8 1 705 5 60 408 525 600 645 705 705 

Season Winter 34 418.5 268.4 46.0 1 1190 5 155 505 570 645 695 1190 1,190 

Season Spring 33 412.2 223.5 38.9 10 810 60 230 490 570 635 740 810 810 

Season Summer 46 477.7 221.4 32.6 10 985 60 325 515 630 705 745 985 985 

Season Fall 30 423.2 264.2 48.2 5 930 6 135 533 585 700 780 930 930 

Asthma No 137 437.2 243.5 20.8 1 1190 10 240 510 600 675 745 930 985 

Asthma Yes 6 435.7 226.0 92.2 60 690 60 354 440 630 690 690 690 690 

Angina No 139 439.1 242.3 20.6 1 1190 10 240 510 600 687 745 930 985 

Angina Yes 4 367.3 256.3 128.1 10 570 10 182 445 553 570 570 570 570 

Bronchitis/Emphysema No 140 433.3 240.0 20.3 1 1190 10 240 510 600 670 738 810 930 

Bronchitis/Emphysema Yes 3 616.3 328.7 189.8 354 985 354 354 510 985 985 985 985 985 

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November 2011 16-63 
 

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Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-64 November 2011 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors at a Restaurant/Picnic 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 64 81.0 114.7 14.3 3 540 5 13 30 108 165 270 540 540 

Gender Male 31 111.8 148.9 26.7 5 540 5 20 60 150 270 540 540 540 

Gender Female 33 52.1 57.7 10.0 3 210 3 8 30 80 135 180 210 210 

Age (years) 1 to 4 6 57.5 61.4 25.1 5 160 5 15 30 105 160 160 160 160 

Age (years) 5 to 11 5 112.8 202.6 90.6 5 473 5 6 20 60 473 473 473 473 

Age (years) 12 to 17 6 60.0 55.4 22.6 5 150 5 30 35 105 150 150 150 150 

Age (years) 18 to 64 46 84.8 116.9 17.2 3 540 5 10 50 120 180 270 540 540 

Age (years) > 64 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 

Race White 54 76.0 105.0 14.3 3 540 5 15 30 105 165 270 473 540 

Race Black 4 57.8 83.1 41.6 5 180 5 6 23 110 180 180 180 180 

Race Asian 1 75.0 - - 75 75 75 75 75 75 75 75 75 75 

Race Some Others 2 97.5 31.8 22.5 75 120 75 75 98 120 120 120 120 120 

Race Hispanic 2 20.0 14.1 10.0 10 30 10 10 20 30 30 30 30 30 

Race Refused 1 540.0 - - 540 540 540 540 540 540 540 540 540 540 

Hispanic No 60 81.8 117.5 15.2 3 540 5 13 30 108 173 372 540 540 

Hispanic Yes 4 68.8 66.6 33.3 10 160 10 20 53 118 160 160 160 160 

Employment - 17 74.7 114.2 27.7 5 473 5 15 30 105 160 473 473 473 

Employment Full Time 37 70.8 67.9 11.2 3 270 5 15 55 120 165 210 270 270 

Employment Part Time 4 42.0 32.0 16.0 3 75 3 17 45 68 75 75 75 75 

Employment Not Employed 6 187.8 272.8 111.4 5 540 5 7 18 540 540 540 540 540 

Education - 18 70.7 112.1 26.4 3 473 3 6 30 105 160 473 473 473 

Education < High School 1 540.0 - - 540 540 540 540 540 540 540 540 540 540 

Education High School Graduate 11 56.2 84.5 25.5 3 270 3 10 20 60 165 270 270 270 

Education < College 10 108.6 164.6 52.1 5 540 5 7 30 150 353 540 540 540 

Education College Graduate 11 68.6 59.5 18.0 10 210 10 20 55 110 120 210 210 210 

Education Post Graduate 13 70.3 53.5 14.8 6 180 6 15 75 80 140 180 180 180 

Census Region Northeast 19 88.1 116.2 26.7 3 473 3 10 60 120 270 473 473 473 

Census Region Midwest 15 102.6 140.7 36.3 3 540 3 15 45 165 210 540 540 540 

Census Region South 16 48.6 47.3 11.8 5 140 5 9 30 93 120 140 140 140 

Census Region West 14 85.4 138.7 37.1 10 540 10 15 30 75 160 540 540 540 

Day Of Week Weekday 35 51.2 52.7 8.9 3 180 3 15 30 75 150 165 180 180 

Day Of Week Weekend 29 117.0 154.2 28.6 5 540 5 10 60 135 473 540 540 540 

Season Winter 8 79.4 75.2 26.6 10 210 10 20 53 135 210 210 210 210 

Season Spring 14 138.4 172.8 46.2 5 540 5 30 65 180 473 540 540 540 

Season Summer 28 71.0 105.1 19.9 3 540 3 8 35 100 150 160 540 540 

Season Fall 14 44.6 52.2 14.0 5 165 5 10 20 60 150 165 165 165 

Asthma No 61 82.1 117.2 15.0 3 540 5 10 30 110 165 270 540 540 

Asthma Yes 3 58.3 40.7 23.5 30 105 30 30 40 105 105 105 105 105 

Angina No 63 82.2 115.2 14.5 3 540 5 15 30 110 165 270 540 540 

Angina Yes 1 5.0 - - 5 5 5 5 5 5 5 5 5 5 

Bronchitis/Emphysema No 63 81.7 115.5 14.6 3 540 5 10 30 110 165 270 540 540 

Bronchitis/Emphysema Yes 1 40.0 - - 40 40 40 40 40 40 40 40 40 40 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors at a Farm 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 128 252.7 232.5 20.6 5 955 20 75 177 428 600 730 855 933 

Gender Male 86 305.2 251.4 27.1 5 955 29 90 230 500 660 780 933 955 

Gender Female 42 145.2 137.2 21.2 5 600 20 50 105 210 265 482 600 600 

Age (years) - 1 510.0 - - 510 510 510 510 510 510 510 510 510 510 

Age (years) 1 to 4 3 121.7 52.5 30.3 70 175 70 70 120 175 175 175 175 175 

Age (years) 5 to 11 7 111.3 77.0 29.1 25 264 25 50 100 130 264 264 264 264 

Age (years) 12 to 17 9 157.8 85.4 28.5 29 265 29 90 175 265 265 265 256 265 

Age (years) 18 to 64 91 296.7 252.2 26.4 5 955 20 80 230 500 635 780 933 955 

Age (years) > 64 17 133.8 134.2 32.5 5 495 5 50 85 160 360 495 495 495 

Race White 120 260.2 236.2 21.6 5 955 20 75 180 473 608 745 855 933 

Race Black 4 58.8 30.9 15.5 25 85 25 33 63 85 85 85 85 85 

Race Some Others 2 165.0 21.2 15.0 150 180 150 150 165 180 180 180 180 180 

Race Hispanic 2 277.5 222.7 157.5 120 435 120 120 278 435 435 435 435 435 

Hispanic No 123 252.6 234.8 21.2 5 955 20 70 178 420 600 730 855 933 

Hispanic Yes 4 297.5 189.1 94.6 120 485 120 135 293 460 485 485 485 485 

Hispanic Refused 1 85.0 - - 85 85 85 85 85 85 85 85 85 85 

Employment - 19 134.9 77.7 17.8 25 265 25 86 120 180 264 265 265 265 

Employment Full Time 73 314.8 258.1 30.2 5 955 20 85 240 525 660 780 933 955 

Employment Part Time 11 283.0 183.6 55.4 45 525 45 150 230 490 495 525 525 525 

Employment Not Employed 24 152.9 184.0 37.6 5 825 5 35 90 205 280 495 825 825 

Employment Refused 1 20.0 - - 20 20 20 20 20 20 20 20 20 20 

Education - 20 137.2 76.3 17.1 25 265 27 88 120 180 262 265 265 265 

Education < High School 12 305.0 211.1 60.9 30 635 30 98 325 493 510 635 635 635 

Education High School Graduate 50 314.5 280.3 39.6 5 955 20 85 215 525 745 855 944 955 

Education < College 25 186.6 166.0 33.2 5 555 15 60 155 255 482 525 555 555 

Education College Graduate 12 290.4 242.9 70.1 30 615 30 68 203 530 600 615 615 615 

Education Post Graduate 9 229.4 246.1 82.0 5 780 5 80 150 210 780 780 780 780 

Census Region Northeast 11 238.2 299.1 90.2 5 955 5 30 100 490 520 955 955 955 

Census Region Midwest 42 202.3 196.6 30.3 15 780 20 654 125 265 510 635 780 780 

Census Region South 57 279.7 239.3 31.7 5 933 25 85 195 482 635 760 825 933 

Census Region West 18 293.7 242.3 57.1 5 855 5 120 220 525 615 855 855 855 

Day Of Week Weekday 78 276.9 243.8 27.6 5 955 15 85 180 485 615 780 933 955 

Day Of Week Weekend 50 215.0 210.6 29.8 5 855 25 60 120 290 525 700 793 855 

Season Winter 32 205.3 207.7 36.7 5 955 22 78 120 245 495 540 955 955 

Season Spring 40 224.4 213.3 33.7 5 825 25 60 153 343 525 625 825 825 

Season Summer 43 276.1 247.8 37.8 5 933 20 70 230 435 660 760 933 933 

Season Fall 13 379.2 264.9 73.5 15 780 15 200 280 600 730 780 780 780 

Asthma No 120 257.0 235.2 21.5 5 955 21 75 180 428 608 745 855 933 

Asthma Yes 8 188.5 188.5 66.6 5 500 5 700 110 322 500 500 500 500 

Angina No 127 253.0 233.4 20.7 5 955 20 75 175 435 600 730 855 933 

Angina Yes 1 210.0 - - 210 210 210 210 210 210 210 210 210 210 

Bronchitis/Emphysema No 125 256.2 233.9 20.9 5 955 22 75 178 435 600 730 855 933 

Bronchitis/Emphysema Yes 3 106.7 95.7 55.3 5 195 5 5 120 195 195 195 195 195 

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November 2011 16-65 
 

 

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Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-66 November 2011 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

At Home in the Outdoor Pool or Spa 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 85 115.4 103.7 11.2 1 450 15 34 90 150 255 360 450 450 

Gender Male 34 113.7 106.8 18.3 5 450 10 45 75 150 258 360 450 450 

Gender Female 51 116.4 102.7 14.4 1 450 15 30 90 178 240 360 390 450 

Age (years) - 2 60.0 63.6 45.0 15 105 15 15 60 105 105 105 105 105 

Age (years) 1 to 4 9 85.6 86.3 28.8 15 255 15 30 60 75 255 255 255 255 

Age (years) 5 to 11 15 164.2 104.0 26.8 25 450 25 105 140 185 300 450 450 450 

Age (years) 12 to 17 5 97.0 53.8 24.1 40 180 40 60 100 105 180 180 180 180 

Age (years) 18 to 64 44 117.6 112.7 17.0 4 450 15 32 83 155 297 360 450 450 

Age (years) > 64 10 78.9 85.3 27.0 1 258 1 20 53 90 227 258 258 258 

Race White 75 120.9 107.7 12.4 1 450 15 34 90 180 258 360 450 450 

Race Black 5 66.0 59.7 26.7 10 150 10 20 45 105 150 150 150 150 

Race Some Others 1 105.0 - - 105 105 105 105 105 105 105 105 105 105 

Race Hispanic 2 112.5 53.0 37.5 75 150 75 75 113 150 150 150 150 150 

Race Refused 2 37.5 31.8 22.5 15 60 15 15 38 60 60 60 60 60 

Hispanic No 78 116.8 104.6 11.8 1 450 10 34 90 160 255 360 450 450 

Hispanic Yes 5 123.0 108.4 48.5 30 300 30 60 75 150 300 300 300 300 

Hispanic Refused 2 37.5 31.8 22.5 15 60 15 15 38 60 60 60 60 60 

Employment - 29 128.2 97.0 18.0 15 450 20 60 105 178 255 300 450 450 

Employment Full Time 27 111.9 102.5 19.7 4 390 10 30 90 150 297 360 390 390 

Employment Part Time 2 237.5 300.5 212.5 25 450 25 25 238 450 450 450 450 450 

Employment Not Employed 26 99.0 94.8 18.6 1 360 5 30 68 130 240 258 360 360 

Employment Refused 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 

Education - 30 124.4 97.5 17.8 15 450 15 60 105 178 250 300 450 450 

Education < High School 8 109.4 155.3 54.9 5 450 5 15 38 158 450 450 450 450 

Education High School Graduate 15 150.0 130.5 33.7 1 390 1 45 105 240 360 390 390 390 

Education < College 17 80.5 66.7 16.2 4 240 4 30 75 90 225 240 240 240 

Education College Graduate 9 120.6 107.3 35.8 15 297 15 30 85 180 297 297 297 297 

Education Post Graduate 6 81.7 42.0 17.2 30 135 30 60 68 130 135 135 135 135 

Census Region Northeast 23 135.3 113.5 23.7 1 450 10 40 100 225 245 297 450 450 

Census Region Midwest 16 64.6 63.6 15.9 4 255 4 25 53 83 135 255 255 255 

Census Region South 23 114.7 78.5 16.4 15 390 20 60 105 150 185 210 390 390 

Census Region West 23 131.2 129.3 27.0 15 450 25 30 75 195 360 360 450 450 

Day Of Week Weekday 56 114.5 106.7 14.3 1 450 5 30 90 155 255 390 450 450 

Day Of Week Weekend 29 117.0 99.5 18.5 10 360 20 45 85 150 297 360 360 360 

Season Winter 10 118.9 159.4 50.4 4 450 4 20 30 135 405 450 450 450 

Season Spring 24 97.4 74.6 15.2 10 360 30 53 80 120 180 195 360 360 

Season Summer 47 124.5 104.3 15.2 1 450 15 40 90 185 255 300 450 450 

Season Fall 4 105.8 107.5 53.7 30 258 30 30 68 182 258 258 258 258 

Asthma No 73 109.9 105.5 12.3 1 450 10 30 75 140 255 360 450 450 

Asthma Yes 11 160.5 82.4 24.8 85 360 85 90 150 225 225 360 360 360 

Asthma DK 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 

Angina No 84 116.5 103.7 11.3 1 450 15 37 90 155 255 360 450 450 

Angina DK 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 

Bronchitis/Emphysema No 78 115.7 101.8 11.5 1 450 10 40 90 150 255 360 450 450 

Bronchitis/Emphysema Yes 6 126.7 137.8 56.3 15 360 15 25 68 225 360 360 360 360 

Bronchitis/Emphysema DK 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Waiting on a Bus, Train, etc. Stop 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 151 18.7 18.8 1.5 1 128 4 7 15 20 40 45 67 120 

Gender Male 61 16.3 18.0 2.3 1 120 4 5 11 20 30 45 65 120 

Gender Female 90 20.3 19.2 2.0 1 128 4 10 15 30 43 60 75 128 

Age (years) - 2 21.0 5.7 4.0 17 25 17 17 21 25 25 25 25 25 

Age (years) 1 to 4 2 8.0 9.9 7.0 1 15 1 1 8 15 15 15 15 15 

Age (years) 5 to 11 32 12.5 10.7 1.9 2 45 2 5 10 15 20 43 45 45 

Age (years) 12 to 17 50 13.8 11.5 1.6 1 74 3 5 10 20 23 30 53 75 

Age (years) 18 to 64 54 25.5 25.6 3.5 1 128 5 10 15 30 60 67 120 128 

Age (years) > 64 11 27.3 13.5 4.1 5 45 5 20 30 40 45 45 45 45 

Race White 115 18.3 18.0 1.7 1 128 4 5 15 22 40 45 67 75 

Race Black 21 17.5 12.0 2.6 1 45 3 10 15 23 35 40 45 45 

Race Asian 3 10.0 5.0 2.9 5 15 5 5 10 15 15 15 15 15 

Race Some Others 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 

Race Hispanic 10 29.8 35.8 11.3 5 120 5 10 17 20 93 120 120 120 

Race Refused 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 

Hispanic No 136 18.1 17.1 1.5 1 128 4 6 15 23 40 45 67 75 

Hispanic Yes 13 25.2 32.4 9.0 1 120 1 10 15 20 65 120 120 120 

Hispanic DK 1 20.0 - - 20 20 20 20 20 20 20 20 20 20 

Hispanic Refused 1 15.0 - - 15 15 15 15 15 15 15 15 15 15 

Employment - 79 13.2 11.4 1.3 1 75 2 5 10 15 23 35 45 75 

Employment Full Time 31 24.9 24.8 4.5 1 128 5 10 15 30 45 65 128 128 

Employment Part Time 15 31.7 31.5 8.1 5 120 5 10 17 45 67 120 120 120 

Employment Not Employed 26 20.6 12.7 2.5 5 45 5 10 20 30 40 45 45 45 

Education - 87 12.9 11.0 1.2 1 75 3 5 10 15 23 30 45 75 

Education < High School 6 32.5 11.7 4.8 15 45 15 25 33 45 45 45 45 45 

Education High School Graduate 25 23.6 24.6 4.9 5 120 5 10 15 30 45 67 120 120 

Education < College 9 28.3 19.2 6.4 10 60 10 10 20 45 60 60 60 60 

Education College Graduate 16 33.8 31.1 7.8 5 128 5 10 30 38 65 128 128 128 

Education Post Graduate 8 14.9 8.4 3.0 1 30 1 41 15 19 30 30 30 30 

Census Region Northeast 63 20.5 23.4 3.0 1 128 3 6 15 22 40 65 120 128 

Census Region Midwest 27 17.5 13.1 2.5 3 60 4 5 15 20 35 35 60 60 

Census Region South 39 19.8 16.7 2.7 4 75 5 10 15 28 45 65 75 75 

Census Region West 22 13.2 11.3 2.4 1 45 1 5 10 15 30 30 45 45 

Day Of Week Weekday 128 17.8 19.0 1.7 1 128 3 6 15 20 35 45 75 120 

Day Of Week Weekend 23 23.8 17.0 3.5 5 65 5 10 20 35 45 60 65 65 

Season Winter 55 19.9 15.6 2.1 1 75 2 10 15 25 43 60 65 75 

Season Spring 43 17.2 20.7 3.2 1 120 4 5 10 20 33 45 120 120 

Season Summer 28 24.0 25.5 4.8 5 128 5 10 15 33 45 67 128 128 

Season Fall 25 12.7 9.9 2.0 1 45 4 5 10 15 20 35 45 45 

Asthma No 139 18.8 18.8 1.6 1 128 3 10 15 20 40 45 75 120 

Asthma Yes 10 20.0 20.5 6.5 4 65 4 5 12 30 55 65 65 65 

Asthma DK 2 7.5 3.5 2.5 5 10 5 5 8 10 10 10 10 10 

Angina No 151 18.7 18.8 1.5 1 128 4 7 15 20 40 45 67 120 

Bronchitis/Emphysema No 145 18.7 19.0 1.6 1 128 4 6 15 20 40 45 75 120 

Bronchitis/Emphysema Yes 6 19.8 13.6 5.5 9 45 9 10 16 23 45 45 45 45 

Exposure Factors Handbook Page
 

November 2011 16-67 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-68 November 2011 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors Near a Vehicle 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 2825 79.9 143.8 2.7 1 1440 2 10 30 65 200 465 600 675 

Gender Male 1388 111.2 185.0 5.0 1 1440 3 11 31 90 430 570 675 735 

Gender Female 1436 49.5 75.9 2.0 1 790 2 10 25 60 120 180 290 420 

Gender Refused 1 20.0 - - 20 20 20 20 20 20 20 20 20 20 

Age (years) - 51 64.4 90.9 12.7 1 510 4 20 40 65 125 290 360 510 

Age (years) 1 to 4 102 46.0 59.5 5.9 1 420 2 10 30 60 105 160 192 245 

Age (years) 5 to 11 230 55.9 86.5 5.7 1 540 2 10 20 60 170 215 360 465 

Age (years) 12 to 17 313 40.9 55.7 3.1 1 435 3 10 21 45 100 160 220 260 

Age (years) 18 to 64 1787 96.4 169.1 4.0 1 1440 2 10 30 75 325 539 645 720 

Age (years) > 64 342 57.6 85.3 4.6 1 560 4 10 30 60 120 205 450 510 

Race White 2275 81.8 148.4 3.1 1 1440 2 10 30 68 210 480 600 695 

Race Black 278 78.4 130.7 7.8 1 645 2 10 30 70 190 435 580 600 

Race Asian 51 42.4 61.7 8.6 1 405 2 10 28 60 85 120 150 405 

Race Some Others 50 73.1 113.0 16.0 1 535 2 15 40 60 168 420 493 535 

Race Hispanic 136 55.1 100.2 8.6 1 600 2 10 25 55 110 170 525 600 

Race Refused 35 124.4 186.9 31.6 4 810 10 20 40 120 360 565 810 810 

Hispanic No 2552 79.8 143.0 2.8 1 1440 2 10 30 65 200 457 600 665 

Hispanic Yes 230 68.1 126.0 8.3 1 765 2 10 30 60 148 410 565 615 

Hispanic DK 13 185.3 321.3 89.1 2 985 2 10 25 100 705 985 985 985 

Hispanic Refused 30 129.8 198.3 36.2 10 810 10 20 40 98 435 585 810 810 

Employment - 632 47.0 68.8 2.7 1 540 2 10 23 55 120 180 265 360 

Employment Full Time 1169 114.9 193.0 5.6 1 1440 2 10 30 90 485 570 690 740 

Employment Part Time 254 67.1 114.3 7.2 1 795 2 10 30 63 165 280 510 600 

Employment Not Employed 751 56.8 84.9 3.1 1 690 2 10 30 60 130 210 360 465 

Employment Refused 19 96.9 185.8 42.6 5 790 5 20 30 90 360 790 790 790 

Education - 702 47.1 70.2 2.6 1 540 2 10 24 55 120 180 265 360 

Education < High School 222 105.8 193.7 13.0 1 1440 4 10 30 90 365 540 720 735 

Education High School Graduate 702 113.2 185.8 7.0 1 1410 2 10 35 90 455 555 665 740 

Education < College 537 87.9 157.3 6.8 1 985 2 10 30 70 240 540 635 705 

Education College Graduate 367 70.9 117.9 6.2 1 660 2 10 30 68 170 325 565 600 

Education Post Graduate 295 55.2 86.9 5.1 1 710 3 10 30 60 120 200 362 560 

Census Region Northeast 749 75.7 130.6 4.8 1 985 3 10 30 70 179 375 570 665 

Census Region Midwest 586 77.4 141.2 5.8 1 1440 2 10 30 60 210 390 560 645 

Census Region South 836 86.4 160.3 5.5 1 1410 2 10 30 62 240 525 643 710 

Census Region West 654 78.2 138.3 5.4 1 985 2 10 30 65 180 435 570 615 

Day Of Week Weekday 2018 84.2 155.6 3.5 1 1440 2 10 30 65 215 515 625 705 

Day Of Week Weekend 807 68.8 108.2 3.8 1 705 2 10 30 65 180 310 465 540 

Season Winter 703 70.9 141.8 5.3 1 1440 2 10 26 60 160 365 570 643 

Season Spring 791 80.5 135.5 4.8 1 810 2 10 30 74 215 435 570 645 

Season Summer 819 84.2 150.3 5.3 1 985 2 10 30 70 210 510 615 705 

Season Fall 512 84.0 148.3 6.6 1 930 2 10 30 70 225 510 600 690 

Asthma No 2596 80.4 143.2 2.8 1 1410 2 10 30 65 205 475 600 675 

Asthma Yes 205 75.1 157.2 11.0 1 1440 2 10 30 65 160 309 580 690 

Asthma DK 24 62.1 78.5 16.0 5 360 5 18 35 68 98 225 360 360 

Angina No 2726 79.6 144.3 2.8 1 1440 2 10 30 65 196 465 600 687 

Angina Yes 76 92.4 139.4 16.0 1 570 3 10 35 91 354 465 535 570 

Angina DK 23 68.7 91.2 19.0 5 360 10 20 40 75 98 330 360 360 

Bronchitis/Emphysema No 2684 79.4 142.8 2.8 1 1440 2 10 30 65 197 465 600 665 

Bronchitis/Emphysema Yes 115 93.8 175.4 16.4 1 985 2 10 30 90 225 465 735 985 

Bronchitis/Emphysema DK 26 61.6 72.2 14.2 5 360 7 27 40 75 110 180 360 360 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Outdoors Other Than Near a Residence or Vehicle Such as Parks, Golf Courses, or Farms 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 1383 200.2 202.7 5.5 1 1440 10 60 130 276 510 600 748 915 

Gender Male 789 223.5 208.7 7.4 1 1440 20 60 150 315 540 635 765 900 

Gender Female 593 168.7 190.0 7.8 1 1440 10 40 105 238 420 540 700 930 

Gender Refused 1 420.0 - - 420 420 420 420 420 420 420 420 420 420 

Age (years) - 19 183.4 160.4 36.8 10 540 10 60 140 220 510 540 540 540 

Age (years) 1 to 4 54 164.6 177.3 24.1 1 980 10 60 120 175 370 560 630 980 

Age (years) 5 to 11 159 171.3 177.9 14.1 5 1210 15 55 115 221 405 574 660 725 

Age (years) 12 to 17 175 156.9 174.4 13.2 5 1065 10 45 100 210 385 570 735 915 

Age (years) 18 to 64 858 219.4 215.1 7.3 1 1440 10 60 150 310 540 635 780 933 

Age (years) > 64 118 181.9 180.2 16.6 5 900 20 55 113 280 480 570 600 735 

Race White 1186 202.6 203.4 5.9 1 1440 14 60 135 280 510 615 750 930 

Race Black 81 185.8 195.1 21.7 1 765 5 40 108 240 540 585 690 765 

Race Asian 20 169.5 189.1 42.3 10 665 10 33 95 230 478 585 665 665 

Race Some Others 30 187.5 161.8 29.5 10 560 10 60 120 270 438 535 560 560 

Race Hispanic 57 158.3 203.3 26.9 1 1305 5 30 110 228 370 435 555 1305 

Race Refused 9 380.0 250.6 83.5 30 810 30 195 435 540 810 810 810 810 

Hispanic No 1267 202.6 203.4 5.7 1 1440 10 60 130 280 510 615 748 915 

Hispanic Yes 103 163.9 185.2 18.2 1 1305 10 30 115 228 400 511 555 555 

Hispanic DK 4 67.5 59.2 29.6 10 145 10 23 58 113 145 145 145 145 

Hispanic Refused 9 330.0 259.5 86.5 30 810 30 140 210 510 810 810 810 810 

Employment - 383 163.8 176.8 9.0 1 1210 10 51 110 215 385 560 665 915 

Employment Full Time 555 228.5 219.4 9.3 1 1305 14 60 150 335 545 645 825 955 

Employment Part Time 126 202.6 211.7 18.9 3 1440 10 60 125 280 510 580 690 700 

Employment Not Employed 309 191.5 189.3 10.8 1 1440 10 50 125 275 480 565 690 735 

Employment Refused 10 254.0 240.9 76.2 30 810 30 105 168 280 675 810 810 810 

Education - 429 163.9 175.5 8.5 1 1210 10 55 115 210 385 560 665 840 

Education < High School 83 264.5 255.5 28.0 1 1305 30 60 180 480 555 600 1100 1305 

Education High School Graduate 313 228.6 228.2 12.9 3 1440 10 60 160 310 570 690 855 990 

Education < College 250 218.0 203.0 12.8 1 1440 10 60 153 330 510 555 715 765 

Education College Graduate 185 207.3 190.2 14.0 1 930 20 60 128 285 505 600 690 795 

Education Post Graduate 123 163.6 173.0 15.6 1 900 10 45 90 240 385 480 735 780 

Census Region Northeast 279 196.8 208.4 12.5 1 1305 10 60 130 265 480 590 900 1130 

Census Region Midwest 309 196.7 211.6 12.0 1 1440 10 50 120 270 510 635 740 900 

Census Region South 468 198.4 195.1 9.0 1 933 15 60 120 285 510 600 748 825 

Census Region West 327 208.7 200.5 11.1 1 1440 15 60 150 285 525 580 725 855 

Day Of Week Weekday 851 184.0 197.9 6.8 1 1440 10 45 119 240 490 585 735 900 

Day Of Week Weekend 532 226.0 207.6 9.0 1 1440 20 69 155 320 525 630 810 915 

Season Winter 241 175.7 192.7 12.4 1 1065 10 35 93 253 450 585 750 810 

Season Spring 412 185.8 174.5 8.6 5 980 15 60 130 240 473 555 665 740 

Season Summer 508 225.0 220.7 9.8 1 1440 15 60 150 305 540 630 840 990 

Season Fall 222 196.5 213.6 14.3 1 1130 10 35 120 280 540 600 780 900 

Asthma No 1283 196.6 196.9 5.5 1 1440 10 60 125 270 495 600 730 855 

Asthma Yes 93 244.3 263.3 27.3 5 1440 15 60 150 350 530 810 1100 1440 

Asthma DK 7 270.7 274.4 103.7 30 810 30 60 195 450 810 810 810 810 

Angina No 1352 199.0 202.3 5.5 1 1440 10 60 130 270 510 600 740 915 

Angina Yes 25 238.6 206.0 41.2 1 730 5 60 210 340 465 690 730 730 

Angina DK 6 290.8 276.0 112.7 30 810 30 140 203 360 810 810 810 810 

Bronchitis/Emphysema No 1326 199.8 200.8 5.5 1 1440 10 60 130 275 500 600 735 900 

Bronchitis/Emphysema Yes 51 206.4 239.8 33.6 5 1100 10 50 110 305 540 700 930 1100 

Bronchitis/Emphysema DK 6 233.3 294.0 120.0 15 810 15 30 168 210 810 810 810 810 

Exposure Factors Handbook Page
 

November 2011 16-69 
 

 

 

 

 

 

 

 

Table 16-20. Time Spent (minutes/day) in Selected Outdoor Locations, Doers Only (continued) 

Cumulative Outdoors (outside the residence) 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 3,124 154.0 158.3 2.8 1 1,290 5 40 105 210 362 480 610 715 

Sex Male 1,533 174.9 173.7 4.4 1 1,290 10 60 120 240 420 540 680 745 

Sex Female 1,588 133.5 138.8 3.5 1 1,065 5 30 90 190 325 415 525 610 

Sex Refused 3 340.0 140.0 80.8 240 500 240 240 280 500 500 500 500 500 

Age (years) - 40 164.0 179.6 28.4 2 720 4 40 108 213 430 600 720 720 

Age (years) 1 to 4 201 195.7 163.7 11.5 3 715 30 75 135 270 430 535 625 699 

Age (years) 5 to 11 353 187.6 158.6 8.4 4 1,250 20 80 150 265 365 479 600 720 

Age (years) 12 to 17 219 135.3 137.0 9.3 1 720 5 35 100 190 300 452 545 610 

Age (years) 18 to 64 1,809 144.2 155.1 3.6 1 1,080 5 30 90 199 360 470 600 715 

Age (years) >64 502 156.4 168.3 7.5 1 1,290 5 36 110 210 375 485 645 735 

Race White 2,622 156.8 160.2 3.1 1 1,290 5 45 105 215 375 485 625 720 

Race Black 255 141.6 153.2 9.6 1 1,250 5 30 95 195 330 420 535 645 

Race Asian 34 115.8 135.6 23.2 1 480 5 20 60 150 360 450 480 480 

Race Some Others 53 167.0 149.0 20.5 3 750 5 60 130 238 320 475 553 750 

Race Hispanic 125 117.3 128.9 11.5 1 720 5 30 70 150 270 355 590 610 

Race Refused 35 187.1 163.8 27.7 5 600 5 60 170 240 450 510 600 600 

Hispanic No 2,857 153.8 158.4 3.0 1 1,290 5 40 105 210 362 480 610 720 

Hispanic Yes 222 146.4 154.1 10.3 1 750 5 30 113 200 345 480 640 690 

Hispanic DK 15 191.5 178.3 46.0 15 585 15 40 140 380 420 585 585 585 

Hispanic Refused 30 212.5 165.3 30.2 5 600 5 60 180 345 458 510 600 600 

Employment - 774 175.8 156.1 5.6 1 1,250 15 60 125 245 380 480 610 705 

Employment Full Time 1,110 141.3 159.9 4.8 1 1,080 5 30 85 195 359 490 660 745 

Employment Part Time 240 134.7 140.8 9.1 1 1,080 5 30 90 183 333 423 485 525 

Employment Not Employed 978 156.1 159.2 5.1 1 1,290 5 40 115 220 375 480 610 701 

Employment Refused 22 152.7 209.8 44.7 5 660 5 15 60 125 555 600 660 660 

Education - 825 174.1 156.2 5.4 1 1,250 15 60 125 240 380 480 610 699 

Education < High School 306 171.9 188.4 10.8 1 1,290 7 45 120 240 405 510 765 855 

Education High School Graduate 837 153.6 154.8 5.4 1 840 5 35 105 215 380 480 598 701 

Education < College 527 143.4 157.1 6.8 1 1,080 5 30 90 195 360 465 615 720 

Education College Graduate 355 126.9 142.6 7.6 1 750 5 30 80 170 300 415 615 690 

Education Post Graduate 274 130.5 151.0 9.1 1 1,065 5 30 75 180 325 465 570 660 

Census Region Northeast 635 148.0 143.7 5.7 1 750 5 35 105 215 345 450 575 610 

Census Region Midwest 639 156.0 169.2 6.7 1 1,290 5 45 102 210 360 500 655 750 

Census Region South 1,120 158.6 165.2 4.9 1 1,080 5 40 110 210 390 495 640 745 

Census Region West 730 150.6 149.6 5.5 1 855 5 36 105 213 360 465 575 660 

Day Of Week Weekday 1,933 141.2 149.0 3.4 1 1,250 5 31 90 190 345 452 598 698 

Day Of Week Weekend 1,191 174.9 170.4 4.9 1 1,290 10 50 120 260 400 500 660 745 

Season Winter 548 114.0 138.1 5.9 1 1,080 5 25 60 150 280 380 540 690 

Season Spring 1,034 171.9 159.4 5.0 1 990 10 60 120 240 390 495 645 730 

Season Summer 1,098 168.3 168.2 5.1 1 1,290 5 50 120 235 400 510 630 715 

Season Fall 444 126.5 140.7 6.7 1 960 5 30 75 163 313 420 575 655 

Asthma No 2,869 154.5 159.2 3.0 1 1,290 5 40 105 210 365 480 615 720 

Asthma Yes 236 145.8 145.5 9.5 1 885 5 45 105 190 360 450 575 610 

Asthma DK 19 182.4 181.0 41.5 1 600 1 60 120 300 480 600 600 600 

Angina No 3,023 153.2 156.3 2.8 1 1,290 5 40 105 210 360 479 610 707 

Angina Yes 76 172.9 222.3 25.5 2 1,080 5 30 69 253 465 660 1,065 1,080 

Angina DK 25 195.0 170.4 34.1 5 600 5 60 150 300 465 480 600 600 

Bronchitis/Emphysema No 2,968 154.9 158.8 2.9 1 1,290 5 40 105 210 367 480 615 715 

Bronchitis/Emphysema Yes 139 129.4 142.5 12.1 1 855 5 30 75 175 327 415 553 735 

Bronchitis/Emphysema DK 17 206.8 179.8 43.6 5 600 5 60 170 300 480 600 600 600 

-

DK 

Refused 

= Indicates missing data. 

= The respondent replied “don’t know”. 

= Refused data. 

N 

SD 

= Doer sample size. 

= Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-70 November 2011 
 

Table 16-21. Mean Time Spent (minutes/day) Inside and Outside, by Age Category, Children <21 years 

Age (years) N Average Indoor Minutes

a Average Outdoor Minutesb Average Unclassified Minutesc 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

25 

90 

131 

360 

511 

449 

493 

1,353 

1,353 

1,316 

1,278 

1,244 

1,260 

1,248 

44 

36 

76 

107 

132 

100 

102 

43 

51 

48 

54 

64 

80 

90 a Time indoors was estimating by adding the average times spent indoors at the respondents’ home (kitchen, living room, bathroom, 

etc.), at other houses, and inside other locations such as school, restaurants, etc. b Time outdoors was estimated by adding the average time spent outdoors at the respondents’ pool and yard, others’ pool and yard, and 

outside other locations such as sidewalk, street, neighborhood, parking lot, service station/gas station, school grounds, park/golf course, 

pool, river, lake, farm, etc. c Includes time spent in vehicles or in activities that could not be assigned an indoor or outdoor location. 

N = Sample size. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Table 16-22. Mean Time Spent (minutes/day) Outside and Inside, Adults 18 Years and 

Older, Doers Only
 

Time Outdoors 

Time Outdoors away from Time Outdoors
 

Age (years) Residencea at Residencea Total Time Outdoors

b
 

Mean 95th Percentile Mean 95th Percentile Mean 95th Percentile 

18 to 64 144.2 470 136.4 435 281 ­

>64 156.5 485 141.1 465 298 ­

Time Indoors 

Age (years) Total Minutes/24 hours Total Time Outdoors Total Time Indoors

c 

Mean Mean
 

18 to 64 1,440 281 1,159
 

>64 1,440 298 1,142
 a	 For additional statistics see Table 16-26. b	 Total Time Outdoors was calculated by summing the time spent outdoors away from the 

residence and the time outdoors at the residence. 

Source:	 U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-71 
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-23. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined Whole Population and 

Doers Only, Children <21 Years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Car―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

36 

41 

33 

43 

37 

39 

61 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

8 

10 

20 

20 

20 

15 

15 

40 

49 

60 

50 

60 

55 

55 

90 

107 

98 

90 

117 

102 

99 

155 

171 

151 

126 

155 

146 

150 

195 

208 

246 

163 

221 

185 

254 

249 

220 

336 

187 

272 

212 

302 

321 

235 

390 

215 

620 

630 

900 

380 

Car―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

35 

68 

73 

227 

317 

286 

364 

65 

72 

54 

67 

58 

64 

81 

2 

5 

4 

4 

1 

1 

2 

5 

8 

4 

4 

2 

3 

9 

7 

10 

4 

5 

2 

5 

10 

10 

10 

8 

7 

5 

5 

10 

14 

15 

10 

10 

10 

10 

17 

20 

30 

24 

25 

20 

20 

30 

40 

58 

42 

45 

40 

40 

60 

73 

85 

65 

88 

82 

75 

105 

159 

147 

118 

150 

127 

122 

180 

203 

186 

141 

180 

163 

193 

210 

218 

323 

181 

267 

202 

279 

275 

227 

363 

197 

327 

300 

338 

334 

235 

390 

215 

620 

630 

900 

380 

Truck (Pickup or Van)―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

2 

2 

14 

5 

7 

9 

11 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

14 

0 

15 

15 

25 

0 

0 

31 

30 

45 

59 

90 

0 

52 

124 

60 

95 

153 

150 

42 

81 

201 

114 

110 

181 

190 

110 

90 

955 

245 

240 

352 

445 

Truck (Pickup or Van)―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

1 

5 

15 

34 

69 

62 

70 

-

-

109 

53 

48 

67 

78 

110 

20 

10 

1 

1 

5 

5 

-

-

10 

2 

4 

5 

5 

-

-

10 

4 

6 

5 

5 

-

-

10 

8 

10 

5 

10 

-

-

11 

10 

10 

7 

11 

-

-

15 

16 

15 

15 

22 

-

-

30 

30 

30 

35 

54 

-

-

53 

59 

65 

89 

115 

-

-

188 

117 

110 

180 

170 

-

-

434 

207 

124 

185 

213 

-

-

746 

222 

151 

258 

238 

-

-

851 

233 

186 

299 

304 

110 

90 

955 

245 

240 

352 

445 

Bus―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

0 

0 

1 

2 

11 

16 

6 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

15 

0 

0 

0 

0 

0 

50 

60 

0 

0 

0 

0 

0 

70 

89 

45 

0 

0 

0 

30 

90 

119 

108 

0 

0 

25 

47 

110 

148 

135 

0 

0 

120 

80 

140 

370 

225 

Bus―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

0 

0 

2 

14 

115 

130 

41 

-

-

-

40 

49 

58 

75 

-

-

30 

15 

5 

7 

10 

-

-

-

16 

5 

10 

12 

-

-

-

16 

6 

10 

14 

-

-

-

18 

14 

10 

20 

-

-

-

21 

17 

15 

25 

-

-

-

30 

25 

30 

30 

-

-

-

33 

43 

54 

60 

-

-

-

49 

67 

71 

100 

-

-

-

67 

90 

101 

135 

-

-

-

74 

107 

131 

175 

-

-

-

77 

120 

159 

193 

-

-

-

79 

122 

175 

209 

-

-

120 

80 

140 

370 

225 

Page Exposure Factors Handbook 

16-72 November 2011 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-23. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined Whole Population and 

Doers Only, Children <21 Years (continued) 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

All Vehicles―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

39 

44 

50 

50 

57 

67 

84 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

15 

15 

25 

20 

28 

30 

30 

40 

45 

62 

60 

60 

60 

65 

85 

85 

120 

113 

98 

120 

122 

124 

155 

180 

171 

151 

151 

167 

155 

206 

239 

208 

246 

203 

238 

212 

291 

328 

220 

336 

214 

272 

289 

383 

382 

235 

390 

955 

620 

630 

900 

675 

All Vehicles―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

37 

72 

86 

261 

417 

383 

428 

66 

72 

69 

68 

68 

82 

94 

2 

5 

4 

1 

1 

1 

5 

5 

9 

4 

4 

2 

5 

8 

8 

10 

5 

6 

4 

5 

10 

10 

10 

10 

10 

10 

10 

15 

16 

20 

10 

13 

14 

16 

20 

20 

30 

26 

30 

25 

30 

40 

46 

60 

45 

46 

55 

60 

75 

75 

85 

83 

85 

90 

99 

120 

151 

143 

128 

150 

130 

177 

190 

202 

178 

166 

190 

161 

235 

240 

217 

316 

212 

261 

240 

314 

345 

226 

362 

326 

309 

306 

392 

386 

235 

390 

955 

620 

630 

900 

675 

N = Sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes less than 10. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-73 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-74 November 2011 

Table 16-24. Time Spent (minutes/day) in Selected Vehicles, Other Mass Transit, and All Vehicles Combined, 

Doers Only 

Car 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 6,560 87.4 88.2 1.1 1 1,280 10 34 63 110 175 240 345 450 

Sex Male 2,852 90.7 97.3 1.8 1 1,280 10 30 63 115 185 254 360 526 

Sex Female 3,706 84.9 80.4 1.3 1 878 10 35 64 110 165 220 335 420 

Sex Refused 2 30.0 14.1 10.0 20 40 20 20 30 40 40 40 40 40 

Age (years) - 120 94.0 90.2 8.2 7 593 10 38 72 120 180 223 435 450 

Age (years) 1 to 4 297 63.0 56.8 3.3 2 390 10 25 45 80 135 180 235 270 

Age (years) 5 to 11 449 64.6 81.1 3.8 1 900 5 20 40 85 145 175 310 345 

Age (years) 12 to 17 393 64.8 71.0 3.6 1 630 9 20 41 80 136 185 300 380 

Age (years) 18 to 64 4,489 93.8 92.3 1.4 1 1,280 13 40 70 120 184 250 360 495 

Age (years) >64 812 83.5 79.4 2.8 4 780 10 30 60 110 165 225 315 405 

Race White 5,337 87.6 89.7 1.2 1 1,280 10 31 64 110 175 240 360 460 

Race Black 640 86.8 74.3 2.9 1 690 10 35 65 115 180 240 305 330 

Race Asian 117 78.8 66.3 6.1 5 360 20 35 60 95 135 225 320 330 

Race Some Others 121 87.7 84.5 7.7 3 540 10 30 60 120 180 250 330 345 

Race Hispanic 265 90.1 101.5 6.2 2 825 15 35 65 100 165 235 465 620 

Race Refused 80 82.4 73.3 8.2 5 420 12 30 60 120 168 230 315 420 

Hispanic No 5,987 87.5 87.6 1.1 1 1,280 10 35 65 110 175 240 345 440 

Hispanic Yes 477 88.5 97.2 4.5 2 825 10 30 60 103 180 240 388 595 

Hispanic DK 29 63.9 73.1 13.6 5 325 6 20 40 60 187 200 325 325 

Hispanic Refused 67 86.1 78.4 9.6 5 420 14 30 60 120 180 239 315 420 

Employment - 1,124 64.2 72.3 2.2 1 900 5 20 45 81 136 180 270 345 

Employment Full Time 3,134 93.6 92.2 1.6 2 1,280 15 40 70 120 180 242 360 490 

Employment Part Time 632 90.1 82.0 3.3 2 878 10 40 70 117 175 230 330 384 

Employment Not Employed 1,629 90.4 90.2 2.2 1 780 10 35 60 115 195 250 365 465 

Employment Refused 41 97.2 84.0 13.1 10 330 15 30 75 120 220 290 330 330 

Education - 1,260 66.5 72.3 2.0 1 900 6 21 45 85 145 187 270 350 

Education < High School 434 86.0 82.1 3.9 5 620 10 35 60 115 165 210 360 455 

Education High School Graduate 1,805 91.8 91.1 2.1 1 870 10 38 65 115 190 255 385 465 

Education < College 1,335 93.2 94.3 2.6 2 1,280 10 36 70 120 180 250 380 460 

Education College Graduate 992 95.7 95.5 3.0 4 840 14 40 73 120 185 250 370 580 

Education Post Graduate 734 91.5 82.0 3.0 4 905 20 40 75 115 175 235 330 380 

Census Region Northeast 1,412 85.8 83.8 2.2 1 780 10 33 60 110 170 240 330 410 

Census Region Midwest 1,492 89.1 86.6 2.2 4 825 10 35 65 113 180 250 360 465 

Census Region South 2,251 88.3 89.3 1.9 1 900 10 34 65 115 175 235 338 490 

Census Region West 1,405 85.9 92.2 2.5 2 1,280 10 30 60 110 175 235 345 435 

Day Of Week Weekday 4,427 83.9 85.0 1.3 1 905 10 30 60 105 165 225 330 440 

Day Of Week Weekend 2,133 94.7 94.0 2.0 1 1,280 10 35 70 120 190 265 360 455 

Season Winter 1,703 83.5 82.1 2.0 1 870 10 30 60 105 165 230 350 425 

Season Spring 1,735 88.6 91.5 2.2 1 905 10 30 60 110 180 250 380 480 

Season Summer 1,767 88.0 86.5 2.1 1 900 10 35 65 115 170 235 330 450 

Season Fall 1,355 90.1 93.2 2.5 1 1,280 10 35 70 115 170 240 335 545 

Asthma No 6,063 87.4 88.0 1.1 1 1,280 10 34 63 110 175 240 350 450 

Asthma Yes 463 88.2 92.1 4.3 4 870 15 34 64 110 165 245 345 505 

Asthma DK 34 78.4 57.4 9.8 10 239 10 30 71 100 160 220 239 239 

Angina No 6,368 87.5 88.7 1.1 1 1,280 10 34 64 110 175 240 350 450 

Angina Yes 154 82.2 68.6 5.5 8 365 10 30 60 115 162 214 285 320 

Angina DK 38 89.6 72.9 11.8 10 360 10 35 74 120 180 239 360 360 

Bronchitis/Emphysema No 6,224 87.6 88.9 1.1 1 1,280 10 34 62 110 175 240 350 450 

Bronchitis/Emphysema Yes 300 85.6 76.2 4.4 1 505 10 35 69 109 185 238 305 435 

Bronchitis/Emphysema DK 36 81.1 63.1 10.5 5 239 10 30 71 120 175 220 239 239 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-75 

Table 16-24. Time Spent (minutes/day) in Selected Vehicles, Other Mass Transit, and All Vehicles Combined, 

Doers Only (continued) 

Truck (Pick-up/Van) 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 1,172 85.3 95.9 2.8 1 955 10 30 60 110 180 240 395 478 

Sex Male 760 91.1 105.4 3.8 1 955 10 30 60 115 190 265 450 620 

Sex Female 412 74.6 74.2 3.7 1 510 10 25 55 95 165 220 300 355 

Age (years) - 13 110.8 129.2 35.8 10 450 10 35 60 90 300 450 450 450 

Age (years) 1 to 4 41 80.8 154.3 24.1 1 955 10 15 35 70 206 210 955 955 

Age (years) 5 to 11 89 47.6 44.2 4.7 1 240 7 15 30 65 110 130 180 240 

Age (years) 12 to 17 80 66.8 71.1 7.9 5 352 6 15 37 94 180 223 265 352 

Age (years) 18 to 64 859 91.4 98.0 3.3 2 750 10 30 60 115 189 260 440 555 

Age (years) >64 90 79.0 82.4 8.7 10 453 12 30 49 105 185 265 390 453 

Race White 1,022 84.7 96.2 3.0 1 955 10 30 60 110 180 235 390 510 

Race Black 68 91.3 98.5 11.9 6 453 14 28 63 106 220 295 450 453 

Race Asian 3 138.3 63.3 36.6 90 210 90 90 115 210 210 210 210 210 

Race Some Others 20 67.2 48.5 10.8 5 165 8 25 63 103 137 155 165 165 

Race Hispanic 48 92.8 99.3 14.3 5 440 10 28 60 120 224 330 440 440 

Race Refused 11 88.2 110.8 33.4 10 390 10 30 60 65 190 390 390 390 

Hispanic No 1,069 85.1 95.6 2.9 1 955 10 30 60 110 180 240 390 478 

Hispanic Yes 87 89.1 100.8 10.8 5 630 5 29 60 115 210 230 440 630 

Hispanic DK 5 58.0 36.2 16.2 20 97 20 20 68 85 97 97 97 97 

Hispanic Refused 11 85.9 111.6 33.7 10 390 10 30 35 65 190 390 390 390 

Employment - 205 60.2 86.4 6.0 1 955 7 15 30 75 146 185 240 265 

Employment Full Time 642 93.3 101.4 4.0 4 750 10 30 60 120 192 270 450 555 

Employment Part Time 97 89.4 89.0 9.0 2 460 6 30 60 120 190 270 450 460 

Employment Not Employed 217 83.0 85.8 5.8 5 655 10 30 60 110 180 235 300 355 

Employment Refused 11 96.4 114.3 34.5 10 390 10 30 35 170 190 390 390 390 

Education - 230 64.0 86.9 5.7 1 955 7 15 35 85 160 206 245 352 

Education < High School 119 90.5 81.7 7.5 5 453 14 35 60 120 195 280 295 450 

Education High School Graduate 392 87.6 94.7 4.8 2 675 10 30 60 115 185 255 450 510 

Education < College 238 92.0 111.8 7.2 4 750 10 30 60 110 190 290 555 655 

Education College Graduate 127 85.2 74.6 6.6 5 370 15 30 60 110 180 230 345 355 

Education Post Graduate 66 112.4 118.0 14.5 10 650 10 35 80 135 220 412 445 650 

Census Region Northeast 170 85.4 104.2 8.0 2 695 10 20 50 110 186 260 445 630 

Census Region Midwest 268 91.2 94.4 5.8 1 750 10 30 60 119 205 245 390 460 

Census Region South 491 87.3 100.1 4.5 4 955 10 30 60 111 180 235 445 595 

Census Region West 243 74.7 81.3 5.2 5 478 10 23 52 90 160 235 395 440 

Day Of Week Weekday 796 80.1 90.6 3.2 1 750 10 30 55 101 170 230 375 510 

Day Of Week Weekend 376 96.3 105.5 5.4 2 955 12 30 61 120 192 280 430 460 

Season Winter 322 78.5 91.6 5.1 1 955 10 29 51 95 170 220 355 445 

Season Spring 300 92.5 100.2 5.8 1 695 10 30 60 120 208 268 443 549 

Season Summer 323 86.1 99.3 5.5 2 750 10 30 60 110 180 233 430 595 

Season Fall 227 84.2 90.9 6.0 5 675 10 30 60 105 165 265 395 465 

Asthma No 1,092 85.3 93.5 2.8 1 750 10 30 60 110 184 240 412 478 

Asthma Yes 72 83.6 125.3 14.8 5 955 10 20 46 115 170 235 395 955 

Asthma DK 8 101.9 129.7 45.8 10 390 10 20 60 128 390 390 390 390 

Angina No 1,142 84.9 95.2 2.8 1 955 10 30 60 110 180 235 395 475 

Angina Yes 20 93.4 116.0 25.9 5 555 8 38 70 103 141 351 555 555 

Angina DK 10 118.5 128.6 40.7 10 390 10 30 60 190 340 390 390 390 

Bronchitis/Emphysema No 1,128 85.5 96.6 2.9 1 955 10 30 60 110 180 240 412 478 

Bronchitis/Emphysema Yes 35 77.8 60.5 10.2 5 240 5 30 60 120 165 220 240 240 

Bronchitis/Emphysema DK 9 93.3 123.9 41.3 10 390 10 20 60 65 390 390 390 390 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-76 November 2011 

Table 16-24. Time Spent (minutes/day) in Selected Vehicles, Other Mass Transit, and All Vehicles Combined, 

Doers Only (continued) 

Bus 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 469 74.6 93.5 4.3 2 945 10 30 55 90 125 180 435 570 

Sex Male 219 77.3 104.1 7.0 5 945 10 30 55 90 135 180 460 570 

Sex Female 250 72.4 83.3 5.3 2 640 15 30 55 90 120 175 420 501 

Age (years) - 14 145.0 167.2 44.7 10 605 10 60 100 140 435 605 605 605 

Age (years) 1 to 4 5 56.0 40.2 18.0 15 120 15 30 55 60 120 120 120 120 

Age (years) 5 to 11 133 48.4 29.4 2.6 5 140 10 25 43 67 90 110 120 122 

Age (years) 12 to 17 143 59.4 46.3 3.9 7 370 10 30 54 75 110 135 179 225 

Age (years) 18 to 64 147 96.6 128.4 10.6 2 945 10 30 60 110 180 405 640 690 

Age (years) >64 27 132.0 144.6 27.8 10 570 20 45 73 130 435 460 570 570 

Race White 311 70.1 89.5 5.1 2 945 10 30 54 80 120 147 405 501 

Race Black 101 85.2 92.4 9.2 5 570 15 35 60 110 140 185 460 468 

Race Asian 15 58.0 58.5 15.1 5 175 5 20 20 120 155 175 175 175 

Race Some Others 14 107.1 176.5 47.2 20 690 20 30 43 100 225 690 690 690 

Race Hispanic 24 65.5 71.5 14.6 15 370 20 30 43 87 90 120 370 370 

Race Refused 4 168.0 196.2 98.1 10 435 10 21 114 315 435 435 435 435 

Hispanic No 415 72.8 86.1 4.2 2 945 10 30 55 90 125 165 420 468 

Hispanic Yes 46 83.9 138.9 20.5 7 690 15 30 38 85 145 370 690 690 

Hispanic DK 2 47.5 10.6 7.5 40 55 40 40 48 55 55 55 55 55 

Hispanic Refused 6 137.8 159.6 65.2 10 435 10 32 78 195 435 435 435 435 

Employment - 274 54.0 39.4 2.4 5 370 10 29 50 70 100 120 150 179 

Employment Full Time 95 122.6 168.8 17.3 5 945 10 30 60 120 405 570 690 945 

Employment Part Time 34 83.3 79.3 13.6 2 468 10 40 60 100 135 185 468 468 

Employment Not Employed 61 80.3 69.2 8.9 5 460 10 30 65 120 135 165 205 460 

Employment Refused 5 167.4 169.9 76.0 10 435 10 32 165 195 435 435 435 435 

Education - 295 55.3 45.0 2.6 5 435 10 29 49 70 100 120 155 225 

Education < High School 25 120.4 124.3 24.9 10 570 30 45 90 135 195 405 570 570 

Education High School Graduate 57 111.6 116.7 15.5 10 501 20 45 73 120 225 435 468 501 

Education < College 38 108.8 133.4 21.6 10 640 20 40 75 120 195 605 640 640 

Education College Graduate 30 84.6 128.1 23.4 2 690 5 30 60 90 130 300 690 690 

Education Post Graduate 24 110.5 199.2 40.7 5 945 10 29 60 102 125 460 945 945 

Census Region Northeast 145 77.1 75.4 6.3 7 435 15 30 60 95 135 180 435 435 

Census Region Midwest 102 69.7 103.3 10.2 2 945 10 30 55 85 120 125 175 468 

Census Region South 142 71.7 82.8 7.0 5 570 10 30 50 80 135 180 460 501 

Census Region West 80 81.8 124.3 13.9 5 690 13 30 42 90 128 298 640 690 

Day Of Week Weekday 426 70.6 84.6 4.1 2 690 10 30 50 85 120 165 435 501 

Day Of Week Weekend 43 114.7 152.2 23.2 10 945 20 45 90 120 180 300 945 945 

Season Winter 158 78.3 98.1 7.8 5 690 10 30 58 90 125 180 435 605 

Season Spring 140 61.6 53.5 4.5 2 460 10 30 50 75 120 138 205 225 

Season Summer 94 86.6 116.7 12.0 5 945 10 30 60 95 155 225 435 945 

Season Fall 77 76.2 107.5 12.3 5 640 10 30 50 80 125 175 570 640 

Asthma No 413 76.4 96.8 4.8 2 945 10 30 55 90 125 180 435 570 

Asthma Yes 50 55.4 39.3 5.6 5 195 10 30 48 71 115 135 165 195 

Asthma DK 6 111.5 161.5 65.9 10 435 10 32 46 100 435 435 435 435 

Angina No 459 73.4 91.3 4.3 2 945 10 30 55 90 125 179 420 570 

Angina Yes 4 168.8 182.7 91.3 20 435 20 60 110 278 435 435 435 435 

Angina DK 6 109.5 162.4 66.3 10 435 10 30 41 100 435 435 435 435 

Bronchitis/Emphysema No 442 74.8 94.3 4.5 2 945 10 30 55 90 125 180 435 570 

Bronchitis/Emphysema Yes 19 58.2 39.9 9.1 10 155 10 30 55 65 125 155 155 155 

Bronchitis/Emphysema DK 8 104.6 137.9 48.8 10 435 10 29 68 100 435 435 435 435 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-77 

Table 16-24. Time Spent (minutes/day) in Selected Vehicles, Other Mass Transit, and All Vehicles Combined, 

Doers Only (continued) 

Train/Subway/Rapid Transit 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 116 97.8 136.3 12.7 1 810 5 28 60 120 189 415 690 720 

Gender Male 62 91.6 119.4 15.2 5 720 10 24 60 120 180 240 480 720 

Gender Female 54 104.8 154.3 21.0 1 810 2 30 60 120 195 480 690 810 

Age (years) - 8 191.9 256.8 90.8 20 810 20 55 118 180 810 810 810 810 

Age (years) 1 to 4 2 92.5 38.9 27.5 65 120 65 65 93 120 120 120 120 120 

Age (years) 5 to 11 3 166.7 271.4 156.7 5 480 5 5 15 480 480 480 480 480 

Age (years) 12 to 17 2 100.0 56.6 40.0 60 140 60 60 100 140 140 140 140 140 

Age (years) 18 to 64 92 85.0 106.5 11.1 1 720 5 30 60 105 175 240 480 720 

Age (years) > 64 9 122.7 219.5 73.2 10 690 10 10 24 120 690 690 690 690 

Race White 64 89.5 139.7 17.5 1 720 5 22 55 74 195 380 690 720 

Race Black 26 131.4 168.4 33.0 5 810 10 35 118 135 195 480 810 810 

Race Asian 3 79.7 17.0 9.8 60 90 60 60 89 90 90 90 90 90 

Race Some Others 4 71.3 47.8 23.8 30 140 30 43 58 100 140 140 140 140 

Race Hispanic 16 88.6 98.9 24.7 5 415 5 20 70 113 165 415 415 415 

Race Refused 3 85.0 56.3 32.5 20 120 20 20 115 120 120 120 120 120 

Hispanic No 89 101.3 149.7 15.9 1 810 5 25 60 120 195 480 720 810 

Hispanic Yes 22 87.0 85.6 18.2 5 415 10 40 70 120 130 165 415 415 

Hispanic DK 2 79.5 34.6 24.5 55 104 55 55 80 104 104 104 104 104 

Hispanic Refused 3 85.0 56.3 32.5 20 120 20 20 115 120 120 120 120 120 

Employment - 7 126.4 163.6 61.8 5 480 5 15 65 140 480 480 480 480 

Employment Full Time 76 98.5 128.2 14.7 1 720 5 30 60 120 189 380 690 720 

Employment Part Time 10 61.7 46.4 14.7 5 160 5 15 58 89 125 160 160 160 

Employment Not Employed 21 101.7 186.2 40.6 1 810 10 10 55 90 165 415 810 810 

Employment Refused 2 107.5 123.7 87.5 20 195 20 20 108 195 195 195 195 195 

Education - 10 122.0 140.0 44.3 5 480 5 20 93 140 338 480 480 480 

Education < High School 6 181.8 311.8 127.3 1 810 1 5 70 135 810 810 810 810 

Education High School Graduate 30 89.4 109.2 19.9 1 480 2 30 60 120 178 415 480 480 

Education < College 26 125.7 189.6 37.2 10 720 10 20 60 120 380 690 720 720 

Education College Graduate 24 66.5 50.3 10.3 5 180 10 25 55 103 125 175 180 180 

Education Post Graduate 20 74.2 59.4 13.3 10 240 13 30 60 97 165 215 240 240 

Census Region Northeast 72 111.8 134.6 15.9 10 810 20 49 63 123 189 415 690 810 

Census Region Midwest 14 64.2 109.5 29.3 2 380 2 10 23 50 240 380 380 380 

Census Region South 15 75.7 121.1 31.3 1 480 1 10 30 90 160 480 480 480 

Census Region West 15 83.5 179.4 46.3 5 720 5 10 30 75 120 720 720 720 

Day Of Week Weekday 96 101.6 127.2 13.0 1 720 10 30 60 120 195 415 690 720 

Day Of Week Weekend 20 79.4 176.6 39.5 2 810 4 8 33 60 120 465 810 810 

Season Winter 26 138.2 196.3 38.5 5 810 10 30 80 130 240 720 810 810 

Season Spring 29 77.3 89.5 16.6 2 480 5 25 60 105 135 175 480 480 

Season Summer 37 106.1 140.7 23.1 5 690 10 30 60 120 195 480 690 690 

Season Fall 24 65.9 82.2 16.8 1 380 1 15 43 83 160 180 380 380 

Asthma No 106 94.2 122.9 11.9 1 720 5 30 60 120 180 380 480 690 

Asthma Yes 7 146.6 294.0 111.1 1 810 1 10 30 90 810 810 810 810 

Asthma DK 3 111.7 87.8 50.7 20 195 20 20 120 195 195 195 195 195 

Angina No 112 96.5 137.9 13.0 1 810 5 28 60 118 175 415 690 720 

Angina DK 4 132.5 82.9 41.5 20 195 20 70 158 195 195 195 195 195 

Bronchitis/Emphysema No 112 98.2 138.0 13.0 1 810 5 30 60 120 180 415 690 720 

Bronchitis/Emphysema Yes 1 10.0 - - 10 10 10 10 10 10 10 10 10 10 

Bronchitis/Emphysema DK 3 111.7 87.8 50.7 20 195 20 20 120 195 195 195 195 195 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-78 November 2011 

Table 16-24. Time Spent (minutes/day) in Selected Vehicles, Other Mass Transit, and All Vehicles Combined, 

Doers Only (continued) 

Airplane 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 53 234.0 203.7 28.0 10 900 15 70 210 300 480 660 900 900 

Gender Male 28 241.3 231.0 43.7 15 900 20 65 210 293 555 900 900 900 

Gender Female 25 225.9 172.6 34.5 10 660 15 110 210 300 480 510 660 660 

Age (years) - 3 175.0 145.7 84.1 15 300 15 15 210 300 300 300 300 300 

Age (years) 12 to 17 3 113.3 118.6 68.5 15 245 15 15 80 245 245 245 245 245 

Age (years) 18 to 64 42 226.4 194.0 29.9 10 900 20 60 203 300 480 555 900 900 

Age (years) > 64 5 405.4 292.4 130.8 195 900 195 210 287 435 900 900 900 900 

Race White 44 241.1 215.6 32.5 10 900 15 65 210 300 510 660 900 900 

Race Black 7 199.3 134.4 50.8 15 435 15 110 210 255 435 435 435 435 

Race Asian 1 60.0 - - 60 60 60 60 60 60 60 60 60 60 

Race Hispanic 1 340.0 - - 340 340 340 340 340 340 340 340 340 340 

Hispanic No 51 234.7 206.2 28.9 10 900 15 60 210 300 480 660 900 900 

Hispanic Yes 2 215.0 176.8 125.0 90 340 90 90 215 340 340 340 340 340 

Employment - 3 113.3 118.6 68.5 15 245 15 15 80 245 245 245 245 245 

Employment Full Time 33 212.4 194.0 33.8 15 900 20 60 180 285 480 555 900 900 

Employment Part Time 3 510.0 375.9 217.0 150 900 150 150 480 900 900 900 900 900 

Employment Not Employed 13 259.4 168.4 46.7 10 660 10 195 225 300 435 660 660 660 

Employment Refused 1 150.0 - - 150 150 150 150 150 150 150 150 150 150 

Education - 4 122.5 98.5 49.3 15 245 15 48 115 198 245 245 245 245 

Education < High School 4 111.3 179.6 89.8 10 380 10 13 28 210 380 380 380 380 

Education High School Graduate 9 253.9 191.0 63.7 15 660 15 195 270 285 660 660 660 660 

Education < College 13 293.8 170.8 47.4 20 555 20 180 300 435 510 555 555 555 

Education College Graduate 15 194.8 114.0 29.4 45 480 45 90 210 255 287 480 480 480 

Education Post Graduate 8 305.0 375.1 132.6 20 900 20 45 138 578 900 900 900 900 

Census Region Northeast 17 254.7 234.8 57.0 15 900 15 70 245 380 510 900 900 900 

Census Region Midwest 17 235.1 234.3 56.8 15 900 15 60 195 287 660 900 900 900 

Census Region South 9 212.8 103.6 34.5 15 340 15 150 255 270 340 340 340 340 

Census Region West 10 216.0 181.7 57.5 10 555 10 45 203 240 518 555 555 555 

Day Of Week Weekday 37 258.9 192.8 31.7 15 900 15 150 230 305 510 660 900 900 

Day Of Week Weekend 16 176.4 222.8 55.7 10 900 10 38 95 263 360 900 900 900 

Season Winter 17 216.3 172.8 41.9 20 660 20 60 210 275 480 660 660 660 

Season Spring 14 191.8 160.5 42.9 15 555 15 90 150 230 435 555 555 555 

Season Summer 17 230.9 222.2 53.9 10 900 10 60 245 300 480 900 900 900 

Season Fall 5 423.0 294.4 131.7 180 900 180 240 285 510 900 900 900 900 

Asthma No 51 224.8 201.5 28.2 10 900 15 60 210 287 480 660 900 900 

Asthma Yes 2 467.5 123.7 87.5 380 555 380 380 468 555 555 555 555 555 

Angina No 51 233.7 207.6 29.1 10 900 15 60 210 300 480 660 900 900 

Angina Yes 2 241.0 65.1 46.0 195 287 195 195 241 287 287 287 287 287 

Bronchitis/Emphysema No 51 231.6 206.7 28.9 10 900 15 60 210 300 480 660 900 900 

Bronchitis/Emphysema Yes 2 295.0 120.2 85.0 210 380 210 210 295 380 380 380 380 380 
 

 

 

 

 

 

 

Table 16-24. Time Spent (minutes/day) in Selected Vehicles, Other Mass Transit, and All Vehicles Combined, Doers Only (continued) 

All Vehicles Combined 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 7,743 97.3 104.9 1.2 1 1,440 12 40 70 120 190 270 425 570 

Sex Male 3,603 103.7 119.7 2.0 1 1,440 10 40 70 120 205 295 478 655 

Sex Female 4,138 91.7 89.8 1.4 1 995 12 40 70 115 180 240 385 465 

Sex Refused 2 30.0 14.1 10.0 20 40 20 20 30 40 40 40 40 40 

Age (years) - 144 117.0 129.1 10.8 5 810 20 40 80 143 210 435 593 660 

Age (years) 1 to 4 335 68.1 75.5 4.1 1 955 10 30 47 85 150 200 245 270 

Age (years) 5 to 11 571 71.0 77.6 3.2 1 900 10 25 51 90 140 171 275 360 

Age (years) 12 to 17 500 81.5 79.8 3.6 1 790 10 30 60 100 166 233 345 405 

Age (years) 18 to 64 5,286 104.0 111.1 1.5 1 1,440 15 43 75 120 200 285 450 620 

Age (years) >64 907 90.9 93.9 3.1 4 900 10 35 60 120 190 258 400 460 

Race White 6,288 97.2 107.2 1.4 1 1,440 10 40 70 120 190 270 425 595 

Race Black 766 98.7 91.3 3.3 2 810 15 45 75 120 195 265 390 485 

Race Asian 133 83.4 74.9 6.5 5 540 20 35 70 105 150 210 330 360 

Race Some Others 144 96.2 94.0 7.8 3 690 10 40 70 128 180 250 345 540 

Race Hispanic 319 101.7 110.4 6.2 2 825 20 41 70 120 190 335 465 620 

Race Refused 93 93.6 90.1 9.3 10 480 15 30 65 120 205 255 420 480 

Hispanic No 7,050 97.1 104.8 1.2 1 1,440 10 40 70 120 190 270 420 566 

Hispanic Yes 578 100.0 109.0 4.5 2 825 15 40 70 120 190 285 480 630 

Hispanic DK 34 73.0 68.3 11.7 5 325 6 25 60 97 175 200 325 325 

Hispanic Refused 81 98.9 95.3 10.6 10 480 15 30 65 130 220 255 420 480 

Employment - 1,388 73.6 77.8 2.1 1 955 10 30 55 90 150 195 275 382 

Employment Full Time 3,732 105.8 116.2 1.9 4 1,440 16 45 75 124 198 290 475 660 

Employment Part Time 720 98.8 95.0 3.5 2 960 10 45 75 120 195 260 380 470 

Employment Not Employed 1,849 96.6 99.5 2.3 1 995 10 37 65 120 200 275 420 526 

Employment Refused 54 120.3 108.6 14.8 10 480 20 35 88 190 290 330 390 480 

Education - 1,550 76.4 78.9 2.0 1 955 10 30 60 95 155 201 303 385 

Education < High School 561 100.8 120.2 5.1 5 1,440 15 40 70 120 180 265 460 620 

Education High School Graduate 2,166 101.6 107.6 2.3 1 1,210 12 40 70 120 210 286 445 570 

Education < College 1,556 103.2 110.1 2.8 2 1,280 15 40 75 120 195 285 460 630 

Education College Graduate 1,108 104.5 109.5 3.3 4 1,215 15 45 75 125 200 280 450 675 

Education Post Graduate 802 101.9 108.7 3.8 4 1,357 20 45 76 120 195 270 365 480 

Census Region Northeast 1,662 98.6 106.6 2.6 1 1,215 15 40 70 120 190 275 425 570 

Census Region Midwest 1,759 101.2 114.6 2.7 1 1,440 10 40 70 120 205 290 435 595 

Census Region South 2,704 96.1 97.7 1.9 1 955 13 40 70 120 190 250 420 558 

Census Region West 1,618 93.7 103.7 2.6 2 1,280 10 35 65 115 180 260 420 540 

Day Of Week Weekday 5,289 94.4 101.4 1.4 1 1,215 10 40 66 115 180 260 435 575 

Day Of Week Weekend 2,454 103.4 111.9 2.3 1 1,440 13 40 75 125 205 280 420 540 

Season Winter 2,037 94.3 101.4 2.2 1 1,080 10 35 65 116 190 270 425 544 

Season Spring 2,032 99.6 110.5 2.5 1 1,440 12 40 70 120 200 275 440 546 

Season Summer 2,090 97.8 103.8 2.3 1 1,357 10 40 70 120 190 260 415 558 

Season Fall 1,584 97.4 103.7 2.6 1 1,280 14 40 70 120 180 265 420 620 

Asthma No 7,152 97.3 104.6 1.2 1 1,440 10 40 70 120 190 270 425 570 

Asthma Yes 544 97.2 110.8 4.8 4 955 17 40 65 117 180 255 460 705 

Asthma DK 47 100.0 95.2 13.9 10 480 10 30 75 120 220 239 480 480 

Angina No 7,516 97.3 105.2 1.2 1 1,440 11 40 70 120 190 270 425 570 

Angina Yes 172 93.1 93.1 7.1 8 615 15 30 65 120 185 280 420 540 

Angina DK 55 108.9 99.7 13.4 10 480 20 35 75 150 235 360 390 480 

Bronchitis/Emphysema No 7,349 97.6 106.1 1.2 1 1,440 10 40 70 120 190 270 425 580 

Bronchitis/Emphysema Yes 342 91.0 79.3 4.3 2 505 15 40 70 115 195 240 325 460 

Bronchitis/Emphysema DK 52 98.9 93.8 13.0 5 480 10 30 74 145 195 239 390 480 

-

DK 

Refused 

= Indicates missing data. 

= The respondent replied “don’t know

= Refused data. 

”. 

N 

SD 

= Doer sample size. 

= Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-79 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only, Children <21 

Years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Sleeping/Napping―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

782 

779 

716 

681 

613 

569 

537 

485 

360 

270 

0 

120 

0 

0 

519 

483 

365 

480 

295 

320 

239 

546 

510 

470 

510 

390 

376 

295 

579 

579 

523 

539 

458 

415 

360 

613 

627 

594 

573 

510 

450 

390 

668 

700 

635 

630 

570 

510 

450 

762 

780 

708 

675 

625 

558 

525 

873 

855 

805 

735 

660 

630 

615 

1,011 

925 

870 

795 

720 

705 

690 

1,080 

962 

917 

840 

750 

762 

750 

1,121 

987 

937 

893 

831 

809 

840 

1,144 

1,098 

944 

916 

868 

907 

906 

1,175 

1,320 

990 

1,110 

945 

1,015 

1,317 

Sleeping/Napping―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

356 

497 

465 

480 

782 

779 

716 

683 

613 

571 

538 

485 

360 

270 

420 

120 

150 

85 

519 

483 

365 

491 

295 

341 

252 

546 

510 

470 

510 

390 

379 

299 

579 

579 

523 

540 

458 

415 

360 

613 

627 

594 

578 

510 

450 

390 

668 

700 

635 

630 

570 

510 

450 

762 

780 

708 

675 

625 

560 

525 

873 

855 

805 

738 

660 

630 

615 

1,011 

925 

870 

795 

720 

705 

690 

1,080 

962 

917 

840 

750 

762 

751 

1,121 

987 

937 

893 

831 

809 

840 

1,144 

1,098 

944 

916 

868 

907 

906 

1,175 

1,320 

990 

1,110 

945 

1,015 

1,317 

Eating―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

117 

98 

92 

78 

65 

52 

52 

0 

0 

15 

0 

0 

0 

0 

6 

10 

15 

0 

0 

0 

0 

12 

10 

15 

0 

0 

0 

0 

36 

29 

20 

15 

10 

0 

0 

45 

40 

30 

28 

20 

10 

0 

73 

60 

60 

45 

35 

30 

20 

110 

90 

89 

75 

60 

45 

40 

145 

120 

120 

105 

88 

74 

65 

194 

167 

157 

135 

115 

100 

105 

224 

206 

176 

150 

139 

120 

135 

334 

233 

198 

180 

155 

146 

192 

345 

244 

208 

217 

176 

162 

210 

345 

270 

270 

265 

255 

205 

630 

Eating―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

62 

117 

118 

349 

480 

432 

426 

118 

99 

92 

80 

67 

56 

59 

10 

10 

15 

2 

5 

2 

2 

16 

10 

15 

10 

10 

5 

5 

23 

12 

15 

15 

10 

7 

9 

40 

30 

20 

20 

15 

10 

10 

46 

40 

30 

30 

20 

20 

15 

77 

60 

60 

45 

40 

30 

30 

110 

90 

89 

75 

60 

50 

45 

148 

120 

120 

105 

90 

75 

75 

195 

167 

157 

135 

115 

100 

105 

224 

206 

176 

150 

140 

125 

144 

335 

234 

198 

180 

157 

148 

197 

345 

244 

208 

218 

179 

163 

210 

345 

270 

270 

265 

255 

205 

630 

Attending School Full-Time―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

11 

28 

65 

73 

183 

187 

117 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

390 

409 

270 

0 

0 

334 

392 

435 

445 

408 

0 

204 

502 

510 

460 

464 

445 

83 

546 

564 

558 

525 

487 

489 

265 

594 

618 

581 

570 

500 

551 

550 

665 

710 

630 

645 

595 

825 

Attending School Full-Time—Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

3 

9 

20 

71 

234 

217 

162 

-

-

385 

366 

389 

401 

347 

60 

20 

20 

30 

60 

10 

20 

-

-

37 

37 

125 

86 

46 

-

-

53 

66 

164 

108 

78 

-

-

103 

128 

211 

270 

126 

-

-

119 

165 

311 

343 

195 

-

-

226 

203 

370 

385 

270 

-

-

458 

395 

390 

415 

370 

-

-

520 

510 

425 

440 

420 

-

-

576 

558 

460 

467 

459 

-

-

632 

583 

497 

485 

519 

-

-

679 

615 

570 

505 

567 

-

-

694 

627 

600 

548 

609 

550 

665 

710 

630 

645 

595 

825 

Page Exposure Factors Handbook 

16-80 November 2011 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only, Children <21 

Years (continued) 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Outdoor Recreation―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

0 

0 

4 

6 

7 

6 

6 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

15 

60 

142 

142 

103 

0 

0 

28 

172 

226 

191 

189 

0 

0 

370 

630 

574 

465 

570 

Outdoor Recreation―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

0 

0 

4 

11 

17 

22 

13 

-

-

-

207 

204 

138 

228 

-

-

15 

30 

60 

5 

30 

-

-

-

30 

60 

5 

35 

-

-

-

30 

60 

5 

41 

-

-

-

30 

60 

5 

57 

-

-

-

30 

66 

11 

77 

-

-

-

60 

120 

60 

130 

-

-

-

150 

165 

126 

180 

-

-

-

240 

245 

180 

300 

-

-

-

585 

351 

234 

420 

-

-

-

608 

403 

411 

480 

-

-

-

621 

506 

446 

534 

-

-

-

626 

540 

456 

552 

-

-

370 

630 

574 

465 

570 

Active Sports―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

15 

20 

27 

40 

51 

53 

35 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

30 

60 

74 

0 

60 

68 

110 

135 

172 

168 

145 

90 

131 

180 

242 

272 

245 

180 

131 

180 

257 

330 

371 

309 

285 

143 

201 

319 

408 

435 

425 

386 

155 

270 

390 

630 

975 

1,065 

565 

Active Sports―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

13 

24 

26 

97 

175 

179 

117 

75 

96 

124 

149 

146 

137 

143 

25 

10 

15 

15 

2 

5 

5 

26 

15 

18 

20 

12 

5 

15 

26 

19 

20 

29 

15 

15 

15 

28 

30 

26 

30 

20 

15 

20 

31 

33 

30 

30 

30 

30 

30 

40 

60 

41 

60 

60 

60 

60 

60 

73 

98 

120 

110 

115 

120 

90 

131 

179 

180 

193 

180 

180 

132 

180 

253 

315 

312 

261 

272 

143 

201 

314 

354 

393 

314 

371 

150 

240 

360 

559 

450 

442 

501 

153 

255 

375 

625 

522 

533 

519 

155 

270 

390 

630 

975 

1,065 

565 

Exercise―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

13 

2 

1 

3 

5 

5 

8 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

30 

60 

122 

25 

0 

0 

100 

70 

151 

354 

30 

0 

54 

137 

114 

176 

670 

150 

60 

525 

450 

245 

300 

Exercise―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

2 

4 

1 

7 

20 

28 

41 

-

-

-

-

124 

75 

99 

-

-

-

-

15 

20 

15 

-

-

-

-

17 

21 

15 

-

-

-

-

19 

23 

15 

-

-

-

-

25 

27 

25 

-

-

-

-

30 

30 

30 

-

-

-

-

60 

42 

40 

-

-

-

-

100 

60 

90 

-

-

-

-

146 

101 

145 

-

-

-

-

226 

128 

180 

-

-

-

-

284 

148 

240 

-

-

-

-

384 

194 

260 

-

-

-

-

417 

219 

280 

-

-

-

-

450 

245 

300 

Exposure Factors Handbook Page
 

November 2011 16-81 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-25. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only, Children <21 

Years (continued) 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Walking―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

63 

118 

118 

357 

497 

466 

481 

6 

2 

3 

3 

4 

10 

8 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

9.2 

0 

10 

4 

14 

30 

20 

29 

10 

17 

20 

30 

55 

45 

64 

40 

45 

35 

40 

79 

90 

104 

58 

54 

60 

55 

130 

127 

160 

60 

60 

60 

170 

190 

410 

Walking―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

9 

9 

19 

44 

118 

190 

128 

-

-

19 

20 

18 

25 

30 

4 

4 

1 

1 

1 

1 

1 

-

-

1 

1 

1 

1 

1 

-

-

1 

1 

1 

1 

2 

-

-

2 

1 

2 

2 

2 

-

-

2 

2 

2 

3 

3 

-

-

7 

5 

5 

5 

5 

-

-

10 

15 

10 

14 

18 

-

-

28 

30 

25 

30 

32 

-

-

51 

56 

40 

60 

62 

-

-

56 

60 

51 

78 

120 

-

-

58 

60 

65 

134 

148 

-

-

59 

60 

94 

154 

175 

160 

60 

60 

60 

170 

190 

410 

N = Sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes less than 10. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-82 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only 

Sleeping/Napping 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

9,362 

4,283 

5,075 

4 

185 

499 

702 

588 

6,041 

1,347 

7,576 

940 

156 

181 

383 

126 

8,514 

700 

45 

103 

1,771 

4,085 

798 

2,638 

70 

1,966 

832 

2,604 

1,791 

1,245 

924 

2,068 

2,096 

3,234 

1,964 

6,303 

3,059 

2,514 

2,431 

2,533 

1,884 

8,608 

692 

62 

9,039 

249 

74 

8,860 

432 

70 

526.3 

523.3 

528.7 

645.0 

502.3 

732.4 

625.1 

563.7 

496.9 

517.1 

523.6 

541.3 

537.1 

528.8 

538.0 

523.4 

525.2 

540.1 

527.5 

521.6 

636.6 

487.2 

502.8 

520.3 

513.7 

625.6 

515.4 

505.4 

496.6 

492.5 

486.7 

523.1 

520.8 

529.0 

530.9 

511.1 

557.5 

534.9 

526.8 

527.7 

512.2 

525.1 

540.1 

544.2 

526.8 

513.7 

511.4 

526.5 

521.7 

521.2 

134.4 

135.2 

133.7 

123.7 

125.4 

124.3 

100.7 

110.8 

123.0 

117.5 

129.5 

162.7 

118.1 

142.3 

148.9 

143.7 

133.2 

147.1 

139.3 

138.9 

128.5 

118.9 

117.4 

125.5 

136.5 

134.0 

135.7 

123.0 

119.9 

117.6 

110.4 

133.7 

127.6 

135.7 

140.0 

131.8 

134.4 

134.7 

130.5 

139.5 

131.1 

133.6 

143.6 

141.0 

134.2 

137.7 

146.3 

134.3 

138.5 

131.9 

1.4 

2.1 

1.8 

61.8 

9.2 

5.6 

3.8 

4.6 

1.6 

3.2 

1.5 

5.3 

9.5 

10.6 

7.6 

12.8 

1.4 

5.6 

20.8 

13.7 

3.1 

1.9 

4.2 

2.4 

16.3 

3.0 

4.7 

2.4 

2.8 

3.3 

3.6 

2.9 

2.8 

2.4 

3.2 

1.7 

2.4 

2.7 

2.6 

2.8 

3.0 

1.4 

5.5 

17.9 

1.4 

8.7 

17.0 

1.4 

6.7 

15.8 

30 

30 

30 

540 

195 

270 

120 

150 

30 

30 

30 

60 

300 

60 

60 

180 

30 

60 

195 

240 

120 

30 

60 

30 

210 

120 

30 

30 

60 

75 

105 

55 

30 

30 

60 

30 

30 

55 

30 

30 

60 

30 

30 

300 

30 

60 

30 

30 

80 

210 

1,430 

1,295 

1,430 

780 

908 

1,320 

1,110 

1,015 

1,420 

1,430 

1,430 

1,415 

920 

905 

1,125 

1,140 

1,430 

1,125 

842 

930 

1,320 

1,420 

1,005 

1,430 

930 

1,420 

1,317 

1,430 

1,350 

1,404 

1,295 

1,420 

1,215 

1,430 

1,404 

1,430 

1,420 

1,404 

1,175 

1,430 

1,420 

1,430 

1,404 

1,035 

1,420 

1,430 

930 

1,430 

1,110 

930 

345 

330 

350 

540 

330 

540 

480 

395 

330 

345 

350 

315 

345 

300 

315 

330 

345 

320 

345 

330 

440 

325 

330 

345 

320 

420 

300 

330 

315 

330 

345 

345 

330 

345 

345 

330 

360 

355 

345 

330 

330 

345 

330 

330 

345 

300 

300 

345 

300 

300 

445 

435 

450 

540 

420 

655 

570 

484 

420 

450 

445 

424 

468 

420 

450 

420 

445 

450 

420 

420 

555 

420 

435 

450 

420 

540 

435 

420 

420 

420 

420 

435 

440 

450 

450 

420 

480 

450 

445 

435 

430 

445 

450 

465 

445 

445 

420 

445 

420 

450 

510 

510 

510 

630 

480 

720 

630 

550 

480 

510 

510 

530 

540 

525 

540 

510 

510 

540 

515 

510 

630 

480 

495 

510 

490 

628 

510 

495 

480 

480 

480 

510 

510 

510 

510 

495 

540 

520 

510 

510 

505 

510 

538 

535 

510 

510 

510 

510 

510 

510 

600 

600 

600 

750 

555 

810 

680 

630 

555 

570 

600 

630 

600 

630 

630 

600 

600 

630 

659 

590 

705 

540 

570 

590 

570 

699 

585 

570 

565 

540 

540 

600 

598 

600 

600 

570 

630 

600 

600 

600 

570 

600 

618 

600 

600 

595 

600 

600 

600 

600 

690 

690 

690 

780 

655 

900 

725 

705 

630 

660 

690 

738 

690 

720 

720 

720 

690 

720 

690 

720 

802 

628 

645 

660 

697 

790 

670 

659 

630 

629 

615 

690 

690 

699 

690 

670 

720 

700 

690 

699 

660 

690 

715 

720 

690 

660 

720 

690 

705 

690 

760 

765 

750 

780 

745 

930 

780 

750 

705 

720 

750 

823 

735 

769 

765 

780 

750 

778 

710 

780 

860 

685 

720 

720 

780 

855 

750 

720 

690 

690 

660 

760 

745 

765 

769 

745 

780 

780 

750 

765 

735 

750 

780 

780 

760 

735 

780 

760 

765 

745 

850 925 

860 925 

840 925 

780 780 

865 900 

1,005 1,110 

840 875 

810 900 

780 868 

780 860 

840 900 

940 1,020 

840 870 

810 842 

870 930 

870 930 

855 925 

843 915 

842 842 

865 870 

930 975 

770 840 

780 860 

800 885 

900 930 

926 975 

860 900 

780 840 

779 845 

775 900 

725 800 

860 930 

840 870 

855 925 

862 940 

840 920 

870 925 

870 930 

840 900 

840 930 

840 900 

840 915 

900 945 

930 1,035 

855 925 

795 845 

840 930 

850 924 

840 930 

840 930 

Exposure Factors Handbook Page
 

November 2011 16-83 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Eating or Drinking 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

8,627 

3,979 

4,644 

4 

157 

492 

680 

538 

5,464 

1,296 

7,049 

808 

148 

168 

345 

109 

7,861 

639 

41 

86 

1,695 

3,684 

715 

2,472 

61 

1,867 

758 

2,363 

1,612 

1,160 

867 

1,916 

1,928 

2,960 

1,823 

5,813 

2,814 

2,332 

2,222 

2,352 

1,721 

7,937 

635 

55 

8,318 

243 

66 

8,169 

397 

61 

74.9 

75.8 

74.1 

60.0 

75.3 

93.5 

68.5 

55.9 

71.9 

91.7 

77.0 

59.9 

80.4 

66.0 

68.7 

74.2 

75.6 

68.3 

60.4 

68.9 

72.2 

70.6 

72.2 

83.9 

71.0 

70.9 

72.3 

74.9 

73.9 

78.5 

82.8 

78.3 

75.8 

71.4 

76.0 

71.2 

82.5 

76.1 

76.3 

73.5 

73.3 

75.2 

71.4 

69.3 

74.6 

85.0 

75.7 

74.7 

80.7 

67.0 

54.8 

56.2 

53.6 

21.2 

50.1 

52.9 

39.0 

35.0 

55.1 

62.7 

55.7 

46.6 

47.8 

52.1 

51.9 

60.8 

55.2 

50.2 

37.1 

55.5 

44.9 

55.1 

55.4 

59.1 

61.0 

45.4 

57.4 

57.1 

56.5 

55.4 

59.7 

59.2 

51.4 

55.1 

53.0 

52.0 

59.5 

56.4 

55.2 

53.3 

54.3 

54.8 

55.0 

56.6 

54.4 

63.5 

67.3 

54.3 

65.2 

47.7 

0.6 

0.9 

0.8 

10.6 

4.0 

2.4 

1.5 

1.5 

0.7 

1.7 

0.7 

1.6 

3.9 

4.0 

2.8 

5.8 

0.6 

2.0 

5.8 

6.0 

1.1 

0.9 

2.1 

1.2 

7.8 

1.1 

2.1 

1.2 

1.4 

1.6 

2.0 

1.4 

1.2 

1.0 

1.2 

0.7 

1.1 

1.2 

1.2 

1.1 

1.3 

0.6 

2.2 

7.6 

0.6 

4.1 

8.3 

0.6 

3.3 

6.1 

1 

1 

2 

30 

10 

2 

5 

2 

1 

5 

1 

2 

2 

7 

2 

8 

1 

2 

5 

8 

2 

1 

2 

2 

8 

2 

2 

1 

2 

1 

2 

1 

1 

2 

2 

1 

2 

2 

1 

1 

2 

1 

2 

8 

1 

2 

5 

1 

2 

8 

900 

900 

640 

75 

315 

345 

255 

210 

900 

750 

900 

505 

305 

525 

435 

410 

900 

435 

150 

410 

345 

900 

509 

750 

385 

375 

460 

900 

525 

640 

750 

750 

435 

900 

500 

900 

630 

640 

630 

750 

900 

900 

460 

335 

900 

500 

435 

900 

460 

230 

15 

15 

15 

30 

15 

20 

15 

10 

15 

20 

15 

15 

15 

15 

12 

20 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

15 

35 

39 

34 

45 

30 

60 

40 

30 

30 

50 

40 

30 

45 

30 

30 

30 

35 

30 

30 

30 

40 

30 

30 

45 

30 

38 

30 

35 

30 

40 

40 

37 

40 

30 

35 

33 

40 

39 

35 

35 

30 

35 

30 

30 

35 

45 

30 

35 

30 

30 

60 

60 

60 

68 

65 

90 

65 

50 

60 

80 

64 

50 

73 

60 

60 

60 

60 

60 

55 

60 

65 

60 

60 

75 

55 

60 

60 

60 

60 

65 

70 

65 

64 

60 

60 

60 

70 

65 

60 

60 

60 

60 

60 

60 

60 

75 

60 

60 

60 

60 

96 

96 

98 

75 

100 

120 

90 

75 

90 

120 

100 

75 

107 

83 

90 

90 

100 

90 

90 

90 

90 

90 

90 

110 

90 

90 

90 

96 

90 

105 

110 

103 

100 

90 

100 

90 

110 

96 

100 

95 

95 

100 

90 

90 

95 

115 

90 

95 

110 

90 

140 

140 

140 

75 

145 

160 

120 

105 

135 

165 

145 

119 

150 

120 

125 

130 

140 

120 

120 

115 

133 

135 

135 

150 

120 

130 

135 

140 

145 

145 

150 

145 

140 

135 

150 

130 

150 

140 

145 

135 

140 

140 

133 

120 

140 

160 

150 

140 

150 

120 

175 

180 

170 

75 

150 

190 

143 

125 

170 

200 

180 

140 

160 

135 

165 

180 

175 

155 

130 

155 

150 

165 

170 

185 

145 

150 

180 

175 

175 

180 

185 

180 

175 

165 

180 

165 

190 

175 

178 

170 

175 

175 

170 

210 

175 

180 

195 

170 

180 

155 

215 

210 

225 

75 

195 

225 

165 

150 

220 

270 

225 

200 

200 

190 

195 

290 

220 

195 

150 

210 

195 

225 

230 

235 

235 

190 

230 

220 

230 

220 

240 

240 

210 

210 

210 

210 

240 

240 

220 

210 

210 

215 

225 

215 

210 

285 

215 

210 

285 

215 

270 

270 

270 

75 

285 

270 

195 

170 

270 

295 

270 

225 

200 

200 

225 

315 

270 

225 

150 

410 

210 

270 

260 

285 

385 

210 

315 

270 

275 

265 

270 

285 

255 

270 

240 

250 

297 

275 

275 

260 

232 

270 

285 

335 

265 

330 

435 

260 

360 

230 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-84 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Working in a Main Job 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 3,259 475.9 179.1 3.1 1 1,440 120 395 500 570 660 740 840 930 

Sex Male 1,733 492.3 187.0 4.5 1 1,440 120 417 510 595 690 770 890 955 

Sex Female 1,526 457.3 167.7 4.3 2 1,440 120 390 485 543 620 690 785 850 

Age (years) - 80 472.4 183.3 20.5 5 940 118 378 483 560 673 850 900 940 

Age (years) 1 to 4 3 16.7 11.5 6.7 10 30 10 10 10 30 30 30 30 30 

Age (years) 5 to 11 10 150.4 185.8 58.8 2 550 2 10 68 264 448 550 550 550 

Age (years) 12 to 17 38 293.2 180.7 29.3 5 840 15 185 269 390 510 675 840 840 

Age (years) 18 to 64 2,993 484.8 173.1 3.2 1 1,440 140 420 505 570 660 745 840 930 

Age (years) >64 135 366.1 208.7 18.0 5 990 30 185 395 500 600 660 840 940 

Race White 2,630 477.5 179.0 3.5 1 1,440 120 400 500 570 660 735 845 933 

Race Black 343 466.6 176.0 9.5 5 1,037 105 390 490 550 655 735 880 990 

Race Asian 57 464.1 177.3 23.5 5 870 45 390 493 553 660 750 780 870 

Race Some Others 56 477.4 181.7 24.3 45 855 75 415 510 570 680 765 780 855 

Race Hispanic 125 465.9 185.3 16.6 2 840 95 360 485 580 720 750 825 840 

Race Refused 48 492.1 191.6 27.7 50 957 120 410 508 575 810 840 957 957 

Hispanic No 2,980 475.4 179.2 3.3 1 1,440 120 395 500 570 660 740 850 940 

Hispanic Yes 221 481.5 174.3 11.7 2 1,106 150 405 505 580 670 740 825 840 

Hispanic DK 12 529.6 146.2 42.2 295 757 295 425 554 610 710 757 757 757 

Hispanic Refused 46 468.5 201.3 29.7 10 860 115 350 498 585 780 818 860 860 

Employment - 47 257.9 202.8 29.6 2 840 5 65 245 390 540 625 840 840 

Employment Full Time 2,679 504.4 164.8 3.2 1 1,440 180 450 510 582 675 750 855 950 

Employment Part Time 395 364.6 159.4 8.0 5 945 80 250 365 480 540 600 675 795 

Employment Not Employed 112 270.9 216.0 20.4 4 990 9 83 245 378 600 675 795 870 

Employment Refused 26 513.6 155.5 30.5 170 840 225 440 510 570 778 790 840 840 

Education - 108 343.0 211.9 20.4 2 860 10 177 343 510 610 675 840 840 

Education < High School 217 473.5 216.7 14.7 4 1,440 85 360 485 568 710 795 940 1,080 

Education High School Graduate 1,045 482.0 180.6 5.6 1 1,440 120 405 500 565 670 765 890 979 

Education < College 795 475.6 174.0 6.2 2 1,440 140 409 495 563 648 750 825 905 

Education College Graduate 627 484.5 159.8 6.4 5 1,005 120 424 510 570 645 720 765 815 

Education Post Graduate 467 483.0 169.6 7.8 1 945 125 400 510 590 660 730 810 860 

Census Region Northeast 721 476.0 180.8 6.7 1 1,440 120 405 495 570 669 740 890 950 

Census Region Midwest 755 477.0 182.2 6.6 2 1,440 120 395 495 570 660 750 825 940 

Census Region South 1,142 478.2 176.7 5.2 1 1,440 105 405 505 570 660 735 840 900 

Census Region West 641 470.4 177.8 7.0 5 1,080 120 390 500 570 657 730 850 880 

Day Of Week Weekday 2,788 487.9 166.2 3.1 1 1,440 155 425 505 570 660 740 840 930 

Day Of Week Weekend 471 405.2 229.5 10.6 2 1,440 30 245 415 555 670 770 870 960 

Season Winter 864 475.8 172.8 5.9 5 1,440 150 390 495 570 660 735 835 900 

Season Spring 791 473.0 195.4 6.9 1 1,440 75 390 495 570 670 765 850 915 

Season Summer 910 477.2 179.9 6.0 1 1,215 120 400 500 565 670 750 890 979 

Season Fall 694 477.7 166.0 6.3 2 1,005 130 405 510 570 645 720 780 840 

Asthma No 3,042 477.0 177.0 3.2 1 1,440 120 400 500 570 660 740 840 930 

Asthma Yes 195 453.4 204.2 14.6 5 1,440 45 345 480 550 668 793 855 979 

Asthma DK 22 523.2 217.0 46.3 170 1,215 225 430 500 565 780 860 1,215 1,215 

Angina No 3,192 475.7 178.4 3.2 1 1,440 120 395 500 570 660 740 840 930 

Angina Yes 44 472.1 200.7 30.3 10 990 60 386 500 573 679 730 990 990 

Angina DK 23 507.4 230.3 48.0 80 1,215 170 430 500 565 780 860 1,215 1,215 

Bronchitis/Emphysema No 3,120 476.5 178.2 3.2 1 1,440 120 400 500 570 660 740 840 930 

Bronchitis/Emphysema Yes 116 447.0 189.4 17.6 5 985 30 368 480 558 644 720 800 855 

Bronchitis/Emphysema DK 23 535.2 226.3 47.2 170 1,215 225 430 500 600 860 875 1,215 1,215 

Exposure Factors Handbook Page
 

November 2011 16-85 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Attending Full Time School 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

884 

468 

416 

7 

56 

297 

271 

247 

6 

665 

92 

33 

29 

58 

7 

771 

103 

4 

6 

608 

49 

89 

135 

3 

666 

14 

54 

100 

24 

26 

186 

200 

322 

176 

858 

26 

302 

287 

125 

170 

784 

96 

4 

875 

4 

5 

851 

27 

6 

358.5 

369.3 

346.4 

232.1 

365.0 

387.8 

392.3 

292.2 

203.3 

362.9 

351.8 

346.3 

337.8 

345.3 

285.0 

359.6 

353.1 

315.5 

348.3 

386.5 

206.6 

304.7 

325.3 

270.0 

385.0 

267.1 

238.5 

303.4 

238.4 

302.8 

351.6 

358.1 

373.9 

338.3 

363.7 

189.5 

375.1 

353.4 

332.4 

357.0 

358.0 

363.0 

363.8 

358.6 

382.5 

333.6 

359.1 

340.1 

357.2 

130.3 

123.2 

137.1 

148.1 

199.2 

98.0 

85.0 

154.6 

147.4 

128.5 

129.6 

156.0 

148.1 

124.0 

157.0 

130.8 

126.4 

167.8 

140.6 

107.3 

133.6 

134.8 

161.0 

147.2 

107.9 

129.3 

141.1 

170.6 

145.9 

144.1 

127.0 

123.9 

139.7 

120.5 

126.0 

158.4 

118.5 

133.7 

142.1 

132.8 

130.7 

127.9 

162.6 

130.5 

87.7 

140.5 

130.4 

132.7 

121.5 

4.4 

5.7 

6.7 

56.0 

26.6 

5.7 

5.2 

9.8 

60.2 

5.0 

13.5 

24.2 

27.5 

16.3 

59.4 

4.7 

12.5 

83.9 

57.4 

4.4 

19.1 

14.3 

13.9 

85.0 

4.2 

34.6 

19.2 

17.1 

29.8 

28.3 

9.3 

8.8 

7.8 

9.1 

4.3 

31.1 

6.8 

7.9 

12.7 

10.2 

4.7 

13.1 

81.3 

4.4 

43.9 

62.8 

4.5 

25.5 

49.6 

1 

20 

1 

10 

20 

60 

10 

1 

75 

1 

40 

90 

58 

30 

60 

1 

30 

65 

150 

10 

5 

25 

1 

185 

10 

5 

58 

1 

25 

10 

60 

5 

10 

1 

1 

15 

5 

10 

40 

1 

1 

20 

120 

1 

255 

120 

1 

30 

120 

840 

840 

710 

495 

710 

645 

605 

840 

480 

825 

710 

840 

553 

565 

440 

840 

630 

416 

445 

710 

502 

695 

840 

440 

710 

415 

785 

840 

565 

535 

825 

645 

840 

630 

840 

465 

695 

840 

630 

785 

840 

695 

450 

840 

455 

460 

840 

605 

440 

95 

120 

75 

10 

30 

170 

200 

60 

75 

107 

70 

120 

70 

85 

60 

100 

85 

65 

150 

165 

15 

90 

60 

185 

160 

5 

60 

60 

30 

95 

120 

88 

60 

120 

120 

20 

150 

90 

70 

120 

95 

95 

120 

95 

255 

120 

95 

60 

120 

300 

320 

263 

180 

173 

360 

375 

180 

120 

310 

287 

225 

212 

260 

150 

300 

269 

221 

185 

361 

115 

210 

215 

185 

360 

175 

125 

185 

135 

210 

268 

308 

330 

263 

310 

60 

330 

290 

217 

285 

295 

334 

280 

300 

330 

270 

300 

305 

350 

390 

390 

385 

210 

428 

390 

405 

289 

153 

392 

388 

365 

360 

378 

290 

390 

385 

391 

435 

400 

180 

295 

340 

440 

400 

310 

212 

273 

200 

300 

375 

393 

405 

375 

390 

120 

395 

390 

375 

380 

390 

390 

443 

390 

410 

378 

390 

365 

397 

435 

435 

430 

320 

530 

435 

435 

400 

240 

435 

433 

435 

445 

430 

440 

435 

425 

410 

440 

440 

305 

395 

420 

440 

440 

357 

330 

415 

360 

461 

420 

425 

450 

410 

435 

300 

440 

430 

425 

430 

435 

428 

448 

435 

435 

440 

435 

435 

440 

483 

485 

480 

495 

595 

485 

460 

480 

480 

485 

465 

500 

502 

480 

440 

483 

483 

415 

445 

485 

430 

480 

500 

440 

485 

385 

400 

526 

430 

500 

483 

470 

500 

465 

485 

460 

495 

475 

470 

510 

485 

475 

450 

483 

455 

460 

485 

450 

440 

550 

555 

535 

495 

628 

555 

485 

535 

480 

550 

526 

565 

540 

510 

440 

550 

510 

415 

445 

550 

461 

500 

605 

440 

550 

415 

480 

614 

460 

502 

520 

528 

565 

540 

550 

465 

550 

500 

550 

565 

550 

540 

450 

550 

455 

460 

550 

460 

440 

600 

595 

600 

495 

665 

600 

510 

645 

480 

600 

645 

840 

553 

510 

440 

600 

595 

415 

445 

595 

502 

585 

785 

440 

595 

415 

480 

760 

565 

535 

600 

578 

625 

555 

600 

465 

612 

570 

600 

605 

595 

645 

450 

600 

455 

460 

600 

605 

440 

640 

645 

628 

495 

710 

630 

555 

785 

480 

630 

710 

840 

553 

565 

440 

645 

600 

415 

445 

625 

502 

695 

825 

440 

625 

415 

785 

833 

565 

535 

785 

602 

645 

600 

640 

465 

640 

710 

600 

645 

630 

695 

450 

640 

455 

460 

640 

605 

440 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-86 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Indoor Playing 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 188 105.0 82.7 6.0 2 510 20 55 90 128 190 270 390 435 

Gender Male 65 117.0 97.1 12.0 10 510 20 60 90 135 255 300 435 510 

Gender Female 123 99.5 73.8 6.7 2 420 20 55 76 120 190 225 340 375 

Age (years) - 3 127.0 47.3 27.3 90 180 90 90 110 180 180 180 180 180 

Age (years) 1 to 4 11 130.0 80.2 24.2 15 270 15 60 115 180 255 270 270 270 

Age (years) 5 to 11 11 93.6 64.3 19.4 30 195 30 30 60 175 180 195 195 195 

Age (years) 12 to 17 4 82.5 45.0 22.5 30 120 30 45 90 120 120 120 120 120 

Age (years) 18 to 64 149 103.0 86.0 7.1 2 510 20 55 76 120 190 292 420 435 

Age (years) > 64 10 124.0 76.4 24.2 20 270 20 75 100 150 248 270 270 270 

Race White 153 110.0 84.3 6.8 2 510 20 60 90 130 190 270 390 435 

Race Black 13 95.0 84.8 23.5 15 255 15 30 60 180 220 255 255 255 

Race Asian 5 71.0 56.8 25.4 10 150 10 30 60 105 150 150 150 150 

Race Some Others 7 108.0 96.5 36.5 30 300 30 55 60 175 300 300 300 300 

Race Hispanic 8 68.4 46.4 16.4 42 180 42 45 50 68 180 180 180 180 

Race Refused 2 64.0 65.1 46.0 18 110 18 18 64 110 110 110 110 110 

Hispanic No 172 107.0 83.9 6.4 2 510 20 60 90 133 190 270 390 435 

Hispanic Yes 15 88.1 71.4 18.4 42 300 42 45 60 100 180 300 300 300 

Hispanic Refused 1 110.0 - - 110 110 110 110 110 110 110 110 110 110 

Employment - 26 108.0 69.9 13.7 15 270 30 55 105 160 195 255 270 270 

Employment Full Time 74 102.0 95.0 11.0 2 510 15 45 70 125 195 300 435 510 

Employment Part Time 20 124.0 74.0 16.6 30 340 36 60 120 165 200 280 340 340 

Employment Not Employed 68 102.0 76.0 9.2 15 420 30 60 85 120 180 245 390 420 

Education - 27 108.0 68.6 13.2 15 270 30 55 110 160 195 255 270 270 

Education < High School 16 89.4 58.8 14.7 20 220 20 53 60 125 180 220 220 220 

Education High School Graduate 59 102.0 83.6 10.9 2 435 20 55 75 135 180 340 375 435 

Education < College 33 112.0 97.7 17.0 10 510 20 55 90 120 190 300 510 510 

Education College Graduate 37 125.0 96.1 15.8 15 420 15 60 105 155 270 390 420 420 

Education Post Graduate 16 72.5 40.4 10.1 10 150 10 38 65 103 120 150 150 150 

Census Region Northeast 46 110.0 94.4 13.9 2 420 20 60 75 120 245 375 420 420 

Census Region Midwest 40 111.0 75.8 12.0 15 340 18 50 95 175 193 256 340 340 

Census Region South 64 100.0 73.0 9.1 10 435 30 53 88 128 180 225 270 435 

Census Region West 38 102.0 92.2 15.0 10 510 18 60 60 120 180 300 510 510 

Day Of Week Weekday 128 99.4 71.0 6.3 2 435 20 55 90 120 180 245 300 340 

Day Of Week Weekend 60 118.0 13.0 13.3 15 510 30 60 90 150 245 383 420 510 

Season Winter 49 130.0 99.2 14.2 18 420 20 60 105 180 300 375 420 420 

Season Spring 36 85.7 55.7 9.3 2 270 20 45 78 113 155 180 270 270 

Season Summer 47 92.7 77.0 11.2 10 435 30 45 60 120 180 195 435 435 

Season Fall 56 107.0 82.7 11.0 10 510 15 60 90 128 195 255 270 510 

Asthma No 174 107.0 84.1 6.4 2 510 20 55 90 130 190 270 390 435 

Asthma Yes 13 88.5 66.4 18.4 20 245 20 30 75 120 180 245 245 245 

Asthma DK 1 110.0 - - 110 110 110 110 110 110 110 110 110 110 

Angina No 184 104.0 80.7 6.0 2 510 20 55 90 123 190 270 375 435 

Angina Yes 3 210.0 167.0 96.4 60 390 60 60 180 390 390 390 390 390 

Angina DK 1 110.0 - - 110 110 110 110 110 110 110 110 110 110 

Bronchitis/emphysema No 177 107.0 83.5 6.3 2 510 20 60 90 130 190 270 390 435 

Bronchitis/emphysema Yes 10 80.1 72.5 22.9 10 245 10 30 60 76 208 245 245 245 

Bronchitis/emphysema DK 1 110.0 - - 110 110 110 110 110 110 110 110 110 110 

Exposure Factors Handbook Page
 

November 2011 16-87 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Traveling on a Bicycle/Skate Board/Rollerskate 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

DK 

No 

Yes 

DK 

115 

82 

33 

2 

2 

18 

33 

53 

7 

98 

7 

2 

4 

3 

1 

106 

8 

1 

52 

27 

7 

27 

2 

56 

3 

18 

18 

11 

9 

20 

24 

26 

45 

83 

32 

20 

46 

34 

15 

95 

18 

2 

114 

1 

109 

5 

1 

45.1 

43.2 

49.9 

15.0 

20.0 

40.3 

32.0 

53.2 

74.0 

46.7 

41.1 

6.0 

47.5 

33.3 

20.0 

45.9 

38.4 

20.0 

33.8 

56.9 

40.9 

55.5 

55.0 

33.4 

98.3 

41.6 

42.9 

89.8 

57.2 

42.1 

39.1 

64.7 

38.4 

44.6 

46.5 

38.6 

34.8 

61.7 

47.9 

48.5 

29.3 

25.0 

45.3 

20.0 

45.1 

50.0 

20.0 

53.4 

56.1 

46.2 

7.1 

14.1 

53.0 

27.9 

62.9 

67.3 

56.9 

21.7 

1.4 

23.6 

25.2 

-

55.2 

23.3 

-

38.3 

76.9 

24.8 

54.3 

49.5 

36.9 

77.8 

49.0 

35.0 

111.3 

38.4 

35.1 

47.5 

87.0 

32.6 

56.0 

46.5 

45.0 

35.0 

72.2 

55.7 

57.2 

24.2 

7.1 

53.5 

-

53.9 

49.6 

-

5.1 

6.2 

8.0 

5.0 

10.0 

12.5 

4.9 

8.6 

25.4 

5.7 

8.2 

1.0 

11.8 

14.5 

-

5.4 

8.2 

-

5.3 

14.8 

9.4 

10.4 

35.0 

4.9 

44.9 

11.6 

8.3 

33.6 

12.8 

7.8 

9.7 

17.1 

4.9 

6.2 

8.2 

10.1 

5.2 

12.4 

14.4 

5.9 

5.7 

5.0 

5.0 

-

5.2 

22.2 

-

1 

1 

5 

10 

10 

1 

2 

5 

23 

1 

5

5

30 

10 

20

1 

10 

20 

1 

5 

10 

5 

20 

1 

25 

5 

5 

15 

5 

5 

2 

1 

5 

5 

1 

1 

5 

2 

2 

1 

5

20

1 

20

1 

5 

20 

400 

400 

205 

20 

30 

195 

115 

400 

205 

400 

65 

7

80 

60 

20

400 

80 

20 

195 

400 

90 

205 

90 

195 

180 

205 

120 

400 

110 

102 

180 

400 

151 

400 

195 

205 

195 

400 

180 

400 

90 

30

400 

20

400 

115 

20 

5 

5 

5 

10 

10 

1 

5 

5 

23 

5 

5 

5 

30 

10 

20 

5 

10 

20 

2 

5 

10 

5 

20 

2 

25 

5 

5 

15 

5 

5 

5 

2 

5 

5 

2 

4 

5 

5 

2 

5 

5 

20 

5 

20 

5 

5 

20 

11 

10 

15 

10 

10 

10 

10 

20 

25 

11 

25 

5 

30 

10 

20 

10 

24 

20 

10 

15 

30 

20 

20 

10 

25 

15 

20 

25 

20 

10 

10 

15 

18 

15 

10 

13 

10 

20 

10 

15 

7 

20 

11 

20 

15 

10 

20 

30 

28 

45 

15 

20 

15 

25 

30 

35 

30 

50 

6

40 

30 

20 

30 

30 

20 

20 

30 

35 

30 

55 

20 

90 

30 

30 

53 

60 

33 

19 

33 

30 

30 

33 

28 

23 

43 

20 

30 

33 

25 

30 

20 

30 

30 

20 

60 

50 

60 

20 

30 

55 

45 

65 

110 

60 

60 

7

65 

60 

20 

60 

55 

20 

48 

60 

46 

90 

90 

45 

180 

46 

60 

90 

90 

78 

58 

75 

50 

60 

75 

48 

46 

90 

75 

60 

40 

30 

60 

20 

60 

90 

20 

102 

90 

105 

20 

30 

151 

65 

105 

205 

110 

65 

7

80 

60 

20 

105 

80 

20 

65 

115 

90 

165 

90 

65 

180 

100 

115 

165 

110 

95 

90 

195 

80 

90 

110 

75 

80 

115 

151 

110 

60 

30 

102 

20 

102 

115 

20 

151 

120 

165 

20 

30 

195 

102 

165 

205 

165 

65 

7

80 

60 

20 

151 

80 

20 

115 

120 

90 

180 

90 

115 

180 

205 

120 

400 

110 

101 

165 

205 

115 

151 

120 

148 

90 

165 

180 

165 

90 

30 

151 

20 

151 

115 

20 

195 

195 

205 

20 

30 

195 

115 

180 

205 

205 

65 

7

80 

60 

20 

195 

80 

20 

151 

400 

90 

205 

90 

151 

180 

205 

120 

400 

110 

102 

180 

400 

151 

205 

195 

205 

195 

400 

180 

205 

90 

30 

195 

20 

195 

115 

20 

205 

400 

205 

20 

30 

195 

115 

400 

205 

400 

65 

7 

80 

60 

20 

205 

80 

20 

195 

400 

90 

205 

90 

195 

180 

205 

120 

400 

110 

102 

180 

400 

151 

400 

195 

205 

195 

400 

180 

400 

90 

30 

205 

20 

205 

115 

20 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-88 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Outdoor Recreation 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 253 211.2 185.5 11.7 5 1,440 20 60 165 300 480 574 670 690 

Sex Male 140 231.8 207.4 17.5 5 1,440 18 68 177 330 503 600 690 735 

Sex Female 112 183.7 150.2 14.2 5 645 20 60 150 255 380 525 585 630 

Sex Refused 1 420.0 - - 420 420 420 420 420 420 420 420 420 420 

Age (years) - 2 337.5 201.5 142.5 195 480 195 195 338 480 480 480 480 480 

Age (years) 1 to 4 13 166.5 177.1 49.1 15 630 15 30 130 180 370 630 630 630 

Age (years) 5 to 11 21 206.1 156.2 34.1 30 585 60 90 165 245 360 574 585 585 

Age (years) 12 to 17 27 155.1 128.3 24.7 5 465 5 60 135 225 420 420 465 465 

Age (years) 18 to 64 158 223.6 193.0 15.4 5 1,440 30 80 173 310 505 585 690 690 

Age (years) >64 32 211.1 206.6 36.5 5 735 5 30 171 375 495 600 735 735 

Race White 225 209.8 182.7 12.2 5 1,440 20 60 165 300 460 570 670 690 

Race Black 16 233.9 231.3 57.8 5 690 5 43 150 450 585 690 690 690 

Race Asian 3 203.3 262.2 151.4 30 505 30 30 75 505 505 505 505 505 

Race Some Others 2 327.5 130.8 92.5 235 420 235 235 328 420 420 420 420 420 

Race Hispanic 4 77.5 53.9 27.0 20 150 20 43 70 113 150 150 150 150 

Race Refused 3 308.3 209.4 120.9 180 550 180 180 195 550 550 550 550 550 

Hispanic No 238 211.8 187.1 12.1 5 1,440 20 60 165 300 480 585 690 690 

Hispanic Yes 12 175.5 149.1 43.0 15 511 15 70 150 255 340 511 511 511 

Hispanic Refused 3 308.3 209.4 120.9 180 550 180 180 195 550 550 550 550 550 

Employment - 60 177.1 150.0 19.4 5 630 13 60 148 230 395 520 585 630 

Employment Full Time 104 210.7 153.4 15.0 5 670 30 83 180 294 419 511 600 645 

Employment Part Time 19 205.3 204.0 46.8 30 690 30 60 150 180 570 690 690 690 

Employment Not Employed 68 244.4 245.0 29.7 5 1,440 15 60 180 375 525 690 735 1,440 

Employment Refused 2 187.5 10.6 7.5 180 195 180 180 188 195 195 195 195 195 

Education - 64 176.7 145.3 18.2 5 630 15 60 153 225 370 465 585 630 

Education < High School 22 259.4 178.0 37.9 5 600 30 105 248 380 525 600 600 600 

Education High School Graduate 59 238.2 229.0 29.8 15 1,440 20 90 175 310 511 670 690 1,440 

Education < College 54 218.1 172.2 23.4 5 690 25 65 173 345 460 550 570 690 

Education College Graduate 31 224.7 193.1 34.7 20 690 30 60 150 325 505 645 690 690 

Education Post Graduate 23 157.6 178.2 37.2 5 735 10 50 80 200 370 480 735 735 

Census Region Northeast 52 189.6 160.9 22.3 5 690 30 60 163 232 370 574 670 690 

Census Region Midwest 54 212.1 228.4 31.1 5 1,440 20 60 178 280 419 600 735 1,440 

Census Region South 84 217.3 175.3 19.1 5 645 15 63 150 348 495 525 600 645 

Census Region West 63 220.3 179.7 22.6 10 690 30 75 165 280 545 585 690 690 

Day Of Week Weekday 129 197.2 195.3 17.2 5 1,440 15 60 150 275 465 525 670 735 

Day Of Week Weekend 124 225.8 174.3 15.6 5 690 20 85 180 310 480 600 690 690 

Season Winter 31 196.6 165.5 29.7 5 585 5 60 165 280 440 550 585 585 

Season Spring 75 198.9 161.7 18.7 5 690 25 75 180 270 465 545 670 690 

Season Summer 102 228.2 204.2 20.2 5 1,440 30 75 180 325 459 585 690 690 

Season Fall 45 203.5 193.8 28.9 5 735 20 60 120 330 505 574 735 735 

Asthma No 232 208.2 187.7 12.3 5 1,440 20 60 159 294 480 585 690 690 

Asthma Yes 19 250.2 166.6 38.2 15 570 15 80 255 350 525 570 570 570 

Asthma DK 2 187.5 10.6 7.5 180 195 180 180 188 195 195 195 195 195 

Angina No 245 206.8 184.9 11.8 5 1,440 20 60 160 288 480 570 670 690 

Angina Yes 6 399.2 151.2 61.7 285 690 285 310 345 420 690 690 690 690 

Angina DK 2 187.5 10.6 7.5 180 195 180 180 188 195 195 195 195 195 

Bronchitis/Emphysema No 238 212.2 189.2 12.3 5 1,440 20 60 165 300 495 585 690 690 

Bronchitis/Emphysema Yes 13 196.3 122.2 33.9 5 370 5 117 160 310 340 370 370 370 

Bronchitis/Emphysema DK 2 187.5 10.6 7.5 180 195 180 180 188 195 195 195 195 195 

Exposure Factors Handbook Page
 

November 2011 16-89 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Active Sport 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

1,384 

753 

629 

2 

23 

105 

247 

215 

642 

152 

1,139 

109 

30 

35 

59 

12 

1,250 

120 

4 

10 

561 

375 

87 

352 

9 

610 

86 

233 

178 

165 

112 

333 

254 

479 

318 

902 

482 

316 

423 

425 

220 

1,266 

105 

13 

1,343 

33 

8 

1,331 

43 

10 

124.0 

136.8 

108.6 

142.5 

108.7 

115.8 

148.9 

137.5 

120.3 

88.0 

126.0 

113.4 

89.9 

135.4 

116.3 

120.0 

124.5 

121.2 

113.8 

102.0 

137.1 

117.6 

116.2 

112.5 

99.4 

137.7 

101.0 

116.8 

115.8 

116.2 

106.4 

132.0 

116.9 

119.5 

128.1 

115.5 

139.9 

115.6 

130.8 

129.5 

112.3 

122.5 

144.8 

105.0 

125.5 

72.1 

86.9 

124.1 

130.0 

84.0 

112.8 

120.8 

100.6 

38.9 

78.6 

98.9 

126.6 

124.5 

110.4 

80.2 

116.2 

96.8 

79.2 

112.2 

91.3 

86.6 

113.5 

110.8 

57.5 

72.1 

120.8 

107.3 

87.6 

110.0 

77.2 

121.2 

99.7 

116.8 

100.3 

97.9 

97.9 

129.1 

101.9 

108.7 

108.8 

97.8 

135.2 

115.2 

105.0 

115.1 

118.3 

109.6 

145.8 

110.4 

113.6 

74.0 

41.1 

113.2 

112.7 

39.8 

3.0 

4.4 

4.0 

27.5 

16.4 

9.6 

8.1 

8.5 

4.4 

6.5 

3.4 

9.3 

14.5 

19.0 

11.9 

25.0 

3.2 

10.1 

28.8 

22.8 

5.1 

5.5 

9.4 

5.9 

25.7 

4.9 

10.8 

7.7 

7.5 

7.6 

9.2 

7.1 

6.4 

5.0 

6.1 

3.3 

6.2 

6.5 

5.1 

5.6 

8.0 

3.1 

14.2 

30.6 

3.1 

12.9 

14.5 

3.1 

17.2 

12.6 

1 1,130 

1 1,130 

1 1,065 

115 170 

5 290 

10 630 

2 975 

5 1,065 

1 1,130 

1 380 

1 1,130 

5 440 

5 310 

15 553 

1 520 

40 300 

1 1,130 

1 630 

60 185 

40 290 

2 1,065 

5 1,130 

1 450 

1 600 

30 280 

2 1,065 

10 570 

1 1,130 

1 525 

1 600 

5 375 

1 1,130 

5 570 

1 975 

1 625 

1 650 

1 1,130 

1 1,065 

5 650 

1 625 

1 1,130 

1 1,130 

1 1,065 

30 450 

1 1,130 

5 330 

40 155 

1 1,130 

10 553 

40 155 

15 

20 

15 

115 

30 

30 

20 

15 

15 

15 

15 

10 

10 

20 

15 

40 

15 

15 

60 

40 

20 

20 

15 

10 

30 

20 

15 

20 

15 

15 

10 

15 

18 

15 

25 

15 

20 

15 

30 

15 

15 

15 

15 

30 

15 

5 

40 

15 

30 

40 

50 

60 

38 

115 

40 

45 

60 

60 

45 

30 

50 

45 

30 

60 

45 

60 

45 

50 

68 

60 

60 

45 

60 

30 

45 

60 

30 

45 

45 

50 

40 

60 

45 

45 

55 

45 

59 

45 

60 

45 

43 

45 

60 

60 

50 

30 

60 

50 

45 

60 

90 

105 

75 

143 

90 

90 

120 

110 

90 

60 

90 

86 

60 

105 

115 

95 

90 

90 

105 

83 

110 

90 

95 

70 

90 

110 

60 

85 

90 

90 

60 

100 

90 

90 

93 

90 

100 

85 

105 

95 

78 

90 

110 

60 

90 

50 

75 

90 

110 

75 

165 

180 

150 

170 

155 

159 

188 

180 

160 

120 

165 

150 

145 

195 

145 

130 

165 

148 

160 

105 

180 

155 

160 

150 

120 

180 

135 

150 

160 

150 

143 

170 

150 

160 

175 

150 

180 

155 

175 

178 

144 

162 

180 

90 

165 

60 

115 

165 

165 

105 

267 

285 

240 

170 

220 

250 

320 

265 

250 

220 

270 

240 

215 

270 

240 

290 

270 

240 

185 

215 

285 

240 

235 

270 

280 

285 

225 

240 

270 

250 

270 

275 

255 

265 

295 

240 

300 

240 

270 

290 

240 

266 

300 

165 

270 

180 

155 

267 

270 

148 

330 

375 

300 

170 

225 

330 

390 

375 

330 

285 

340 

332 

235 

330 

305 

300 

330 

335 

185 

290 

370 

305 

285 

330 

280 

370 

270 

300 

340 

310 

330 

345 

315 

330 

330 

300 

380 

305 

330 

375 

290 

330 

390 

450 

332 

275 

155 

330 

340 

155 

435 

500 

370 

170 

290 

345 

510 

470 

450 

315 

452 

430 

310 

553 

345 

300 

435 

520 

185 

290 

452 

380 

355 

475 

280 

470 

510 

420 

418 

380 

360 

485 

430 

410 

500 

395 

500 

370 

435 

462 

460 

430 

553 

450 

440 

330 

155 

435 

553 

155 

525 

558 

435 

170 

290 

390 

558 

520 

525 

330 

530 

435 

310 

553 

520 

300 

515 

553 

185 

290 

558 

525 

450 

520 

280 

558 

570 

530 

475 

450 

375 

558 

440 

462 

525 

485 

565 

475 

515 

530 

565 

515 

565 

450 

525 

330 

155 

520 

553 

155 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-90 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Exercise 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 564 77.4 70.4 3.0 4 670 15 30 60 100 150 195 275 420 

Sex Male 262 84.7 75.8 4.7 5 670 20 30 60 117 165 205 285 450 

Sex Female 302 71.1 64.9 3.7 4 525 15 30 60 90 125 175 265 360 

Age (years) - 10 76.5 74.0 23.4 15 270 15 30 60 90 188 270 270 270 

Age (years) 1 to 4 11 127.3 187.2 56.4 15 670 15 30 60 150 160 670 670 670 

Age (years) 5 to 11 26 132.5 126.3 24.8 15 525 25 60 90 180 275 450 525 525 

Age (years) 12 to 17 35 67.8 41.6 7.0 15 180 20 30 60 100 120 150 180 180 

Age (years) 18 to 64 407 77.6 63.6 3.2 4 480 20 30 60 100 145 185 265 300 

Age (years) >64 75 54.9 44.5 5.1 6 195 10 25 40 70 120 150 193 195 

Race White 480 78.0 71.5 3.3 4 670 15 30 60 100 150 194 285 450 

Race Black 34 74.7 44.7 7.7 15 250 15 45 60 105 120 130 250 250 

Race Asian 10 46.3 25.0 7.9 15 95 15 30 42 60 83 95 95 95 

Race Some Others 14 80.2 73.9 19.8 30 275 30 30 48 90 179 275 275 275 

Race Hispanic 19 63.0 60.7 13.9 15 265 15 30 45 60 160 265 265 265 

Race Refused 7 128.6 130.5 49.3 30 360 30 55 60 270 360 360 360 360 

Hispanic No 516 76.9 70.1 3.1 4 670 15 30 60 99 145 193 275 420 

Hispanic Yes 38 76.6 59.5 9.7 15 265 20 30 60 110 160 250 265 265 

Hispanic DK 3 65.0 69.5 40.1 20 145 20 20 30 145 145 145 145 145 

Hispanic Refused 7 128.6 130.5 49.3 30 360 30 55 60 270 360 360 360 360 

Employment - 72 99.0 111.6 13.2 15 670 20 30 60 120 180 275 525 670 

Employment Full Time 300 72.7 55.6 3.2 5 460 20 30 60 90 130 180 240 291 

Employment Part Time 50 86.0 83.6 11.8 10 420 20 30 60 92 168 300 390 420 

Employment Not Employed 139 72.7 63.4 5.4 4 480 10 30 60 90 135 195 240 265 

Employment Refused 3 113.3 135.8 78.4 30 270 30 30 40 270 270 270 270 270 

Education - 83 102.0 111.0 12.2 15 670 25 30 60 120 205 275 525 670 

Education < High School 21 58.2 66.1 14.4 10 300 10 28 30 60 90 165 300 300 

Education High School Graduate 124 81.0 63.0 5.7 4 298 15 30 60 115 179 205 250 265 

Education < College 104 80.9 70.2 6.9 15 480 20 30 60 113 150 170 240 420 

Education College Graduate 110 73.6 62.5 6.0 5 460 20 30 60 98 130 180 285 297 

Education Post Graduate 122 60.9 38.4 3.5 5 240 15 30 60 80 110 127 165 185 

Census Region Northeast 130 88.4 77.6 6.8 10 450 15 30 60 120 200 240 297 420 

Census Region Midwest 101 63.6 44.3 4.4 10 300 15 30 60 89 115 120 170 215 

Census Region South 177 75.3 71.6 5.4 5 525 15 30 60 90 150 185 298 480 

Census Region West 156 79.6 75.3 6.0 4 670 20 30 60 104 130 183 270 460 

Day Of Week Weekday 426 73.1 63.9 3.1 4 670 15 30 60 90 130 180 240 298 

Day Of Week Weekend 138 90.8 86.6 7.4 6 525 15 30 60 120 200 265 420 460 

Season Winter 150 67.4 49.9 4.1 8 285 15 30 60 90 128 175 213 240 

Season Spring 140 74.9 55.4 4.7 10 360 18 30 60 90 148 181 220 298 

Season Summer 192 93.2 91.3 6.6 5 670 20 30 63 120 180 250 450 525 

Season Fall 82 63.3 63.3 7.0 4 460 15 30 45 75 120 135 300 460 

Asthma No 523 76.6 70.2 3.1 4 670 15 30 60 100 150 185 265 420 

Asthma Yes 37 78.2 51.5 8.5 20 275 20 45 65 100 120 200 275 275 

Asthma DK 4 175.0 167.0 83.5 10 360 10 35 165 315 360 360 360 360 

Angina No 553 77.3 69.4 2.9 4 670 15 30 60 100 145 193 265 420 

Angina Yes 7 27.3 19.6 7.4 6 60 6 10 25 45 60 60 60 60 

Angina DK 4 188.8 150.4 75.2 60 360 60 63 168 315 360 360 360 360 

Bronchitis/Emphysema No 542 77.1 69.5 3.0 4 670 15 30 60 100 145 185 265 420 

Bronchitis/Emphysema Yes 17 64.6 60.6 14.7 10 275 10 30 50 63 120 275 275 275 

Bronchitis/Emphysema DK 5 157.0 149.6 66.9 15 360 15 60 80 270 360 360 360 360 

Exposure Factors Handbook Page
 

November 2011 16-91 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Walking 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

Refused 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

1,639 

755 

883 

1 

38 

58 

155 

223 

944 

221 

1,289 

175 

36 

30 

88 

21 

1,467 

144 

10 

18 

431 

561 

153 

482 

12 

472 

138 

366 

288 

210 

165 

507 

321 

423 

388 

1,182 

457 

412 

459 

475 

293 

1,504 

120 

15 

1,578 

44 

17 

1,553 

67 

19 

29.7 

32.5 

27.3 

20.0 

29.5 

24.3 

18.2 

25.8 

31.8 

33.8 

29.6 

34.8 

26.6 

23.8 

23.1 

33.2 

29.9 

26.8 

30.2 

35.7 

22.8 

31.0 

26.9 

35.5 

18.4 

22.7 

42.7 

29.3 

32.5 

29.8 

34.6 

34.9 

29.3 

25.0 

28.2 

29.3 

30.7 

32.3 

28.9 

26.6 

32.2 

29.6 

29.7 

36.2 

29.5 

29.0 

46.6 

29.7 

27.0 

35.4 

41.6 

48.3 

34.8 

-

23.7 

26.3 

21.0 

32.4 

45.0 

49.3 

43.7 

39.7 

24.7 

21.2 

21.1 

33.0 

41.0 

48.7 

28.8 

34.8 

28.0 

43.8 

37.1 

49.4 

13.5 

27.6 

71.9 

41.6 

39.3 

38.8 

44.6 

45.3 

46.9 

37.7 

35.0 

39.2 

47.4 

47.7 

41.5 

31.3 

46.7 

42.0 

38.3 

27.8 

41.5 

36.1 

63.1 

42.1 

31.9 

31.4 

1.0 

1.8 

1.2 

-

3.9 

3.5 

1.7 

2.2 

1.5 

3.3 

1.2 

3.0 

4.1 

3.9 

2.2 

7.2 

1.1 

4.1 

9.1 

8.2 

1.3 

1.8 

3.0 

2.3 

3.9 

1.3 

6.1 

2.2 

2.3 

2.7 

3.5 

2.0 

2.6 

1.8 

1.8 

1.1 

2.2 

2.4 

1.9 

1.4 

2.7 

1.1 

3.5 

7.2 

1.0 

5.4 

15.3 

1.1 

3.9 

7.2 

1 

1 

1 

20 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

4 

1 

1 

2 

8 

1 

1 

1 

1 

5 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

5 

1 

2 

5 

1 

1 

3 

540 

540 

360 

20

100 

160 

170 

190 

410 

540 

540 

250 

100 

60 

100 

150 

410 

540 

80 

150 

190 

365 

295 

540 

55 

190 

540 

410 

295 

300 

360 

365 

540 

410 

285 

540 

410 

365 

540 

270 

410 

540 

250 

90 

540 

150 

270 

540 

165 

110 

2 

2 

2 

20

2 

2 

1 

2 

2 

2 

2 

2 

1 

1 

2 

8 

2 

2 

2 

8 

2 

2 

2 

2 

5 

2 

3 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

5

2 

4 

5 

2 

2 

3 

6 

7 

6 

20 

10 

10 

5 

6 

6 

10 

6 

10 

10 

6 

6 

15 

6 

6 

10 

15 

5 

7 

5 

10 

10 

5 

7 

5 

10 

8 

10 

10 

6 

5 

8 

7 

5 

6 

6 

6 

8 

6 

5 

10 

6 

6 

10 

6 

5 

10 

16 

20 

15 

20

25 

15 

10 

15 

19 

20 

15 

20 

20 

17 

15 

20 

16 

15 

18 

25 

13 

16 

15 

20 

17 

13 

20 

18 

20 

19 

20 

20 

15 

10 

15 

18 

15 

20 

16 

15 

20 

16 

15 

30

16 

15 

30 

16 

16 

30 

39 

40 

35 

20

40 

35 

25 

30 

40 

45 

35 

50 

30 

43 

37 

40 

40 

35 

55 

55 

30 

40 

35 

50 

20 

30 

50 

35 

45 

40 

45 

45 

31 

30 

40 

40 

35 

39 

35 

35 

45 

36 

40 

60

38 

36 

60 

38 

40 

60 

65 

70 

60 

20

60 

60 

40 

60 

70 

73 

65 

75 

60 

60 

50 

65 

65 

60 

78 

65 

55 

70 

60 

75 

30 

55 

115 

65 

75 

60 

80 

75 

60 

60 

60 

65 

60 

75 

60 

60 

61 

65 

70 

75

65 

60 

90 

65 

60 

90 

95 

100 

94 

20

80 

60 

60 

100 

110 

95 

100 

125 

78 

60 

60 

65 

100 

70 

80 

150 

65 

100 

92 

120 

55 

65 

145 

100 

100 

90 

95 

107 

105 

80 

90 

92 

120 

120 

90 

85 

105 

95 

118 

90

95 

115 

270 

95 

90 

110 

151 

170 

140 

20

100 

70 

65 

135 

171 

155 

160 

160 

100 

60 

92 

150 

155 

100 

80 

150 

131 

180 

135 

150 

55 

130 

360 

150 

160 

140 

180 

170 

160 

135 

140 

145 

171 

180 

146 

123 

155 

152 

135 

90

151 

150 

270 

151 

130 

110 

190 

270 

171 

20 

100 

160 

100 

151 

250 

180 

225 

194 

100 

60 

100 

150 

194 

135 

80 

150 

151 

250 

165 

250 

55 

151 

365 

240 

180 

225 

200 

250 

180 

171 

180 

180 

200 

250 

180 

160 

295 

190 

150 

90 

190 

150 

270 

194 

165 

110 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-92 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Housekeepinga 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 1,943 118.8 113.4 2.6 1 810 10 40 90 165 270 345 465 540 

Sex Male 370 109.4 116.5 6.1 1 810 10 30 60 150 270 360 425 560 

Sex Female 1,573 121.0 112.5 2.8 1 790 15 45 90 165 270 345 465 540 

Age (years) - 47 146.0 121.3 17.7 10 480 10 45 115 240 300 375 480 480 

Age (years) 1 to 4 11 74.1 69.4 20.9 10 270 10 40 60 90 90 270 270 270 

Age (years) 5 to 11 54 42.9 34.1 4.6 1 180 5 20 30 53 80 120 150 180 

Age (years) 12 to 17 72 78.1 75.5 8.9 1 300 5 28 60 105 210 240 285 300 

Age (years) 18 to 64 1,316 120.4 113.7 3.1 1 810 15 40 90 165 270 360 465 525 

Age (years) >64 443 128.2 118.9 5.7 3 790 10 55 90 180 270 345 540 570 

Race White 1,649 119.1 112.2 2.8 1 790 10 40 90 165 265 340 465 540 

Race Black 137 116.6 109.4 9.3 1 490 5 30 90 150 300 358 480 484 

Race Asian 32 98.8 100.5 17.8 15 425 15 30 60 128 265 345 425 425 

Race Some Others 26 82.4 56.4 11.1 5 210 15 40 60 115 185 190 210 210 

Race Hispanic 71 112.6 129.3 15.3 5 660 8 30 60 135 270 465 518 660 

Race Refused 28 189.3 176.2 33.3 10 810 20 53 148 248 420 465 810 810 

Hispanic No 1,771 117.4 110.6 2.6 1 790 10 40 90 165 265 335 425 525 

Hispanic Yes 134 121.7 129.6 11.2 5 660 10 35 85 135 270 470 540 658 

Hispanic DK 15 146.9 127.9 33.0 10 510 10 30 120 210 240 510 510 510 

Hispanic Refused 23 191.1 180.3 37.6 10 810 20 45 150 255 390 420 810 810 

Employment - 138 65.6 68.8 5.9 1 375 5 25 45 80 180 240 285 300 

Employment Full Time 673 106.6 102.4 3.9 1 655 10 30 70 145 240 325 413 490 

Employment Part Time 193 124.7 117.5 8.5 1 660 15 45 90 180 270 390 480 540 

Employment Not Employed 925 132.7 119.4 3.9 3 790 15 55 105 180 295 370 484 600 

Employment Refused 14 236.8 208.2 55.6 10 810 10 120 183 300 430 810 810 810 

Education - 171 82.2 96.9 7.4 1 810 5 30 45 105 220 270 300 375 

Education < High School 246 140.7 125.4 8.0 3 715 10 60 120 180 300 400 540 660 

Education High School Graduate 677 125.1 120.5 4.6 2 790 15 45 90 175 270 375 490 610 

Education < College 433 112.9 100.1 4.8 1 570 10 40 90 150 240 320 420 470 

Education College Graduate 245 107.3 102.2 6.5 1 585 15 30 60 150 240 328 405 465 

Education Post Graduate 171 130.8 118.0 9.0 5 655 15 60 90 180 280 390 495 540 

Census Region Northeast 464 119.2 116.4 5.4 2 790 10 35 90 165 245 330 480 655 

Census Region Midwest 413 117.9 112.6 5.5 1 715 10 34 88 165 255 345 480 525 

Census Region South 648 119.9 116.2 4.6 1 810 10 40 90 165 285 370 435 540 

Census Region West 418 117.7 106.6 5.2 5 720 15 40 90 165 255 340 420 470 

Day Of Week Weekday 1,316 113.2 111.9 3.1 1 790 10 30 75 150 255 330 470 550 

Day Of Week Weekend 627 130.6 115.6 4.6 1 810 15 55 90 180 290 370 435 525 

Season Winter 470 111.4 100.6 4.6 1 810 10 45 85 160 240 290 390 480 

Season Spring 451 122.6 114.0 5.4 3 720 15 40 90 180 270 360 465 540 

Season Summer 563 111.8 114.5 4.8 1 690 10 30 75 135 255 365 465 610 

Season Fall 459 131.3 122.4 5.7 1 790 15 45 90 180 300 390 480 560 

Asthma No 1,789 118.5 112.1 2.6 1 790 10 40 90 165 270 345 465 540 

Asthma Yes 140 115.7 115.8 9.8 5 690 10 37 67 150 278 378 470 480 

Asthma DK 14 189.3 208.6 55.7 10 810 10 45 123 255 340 810 810 810 

Angina No 1,853 117.7 112.3 2.6 1 790 13 40 90 160 265 345 465 540 

Angina Yes 75 122.9 103.8 12.0 5 394 5 30 90 210 270 320 370 394 

Angina DK 15 234.7 204.0 52.7 10 810 10 120 240 300 480 810 810 810 

Bronchitis/Emphysema No 1,816 118.1 112.9 2.7 1 790 10 40 90 160 270 355 465 540 

Bronchitis/Emphysema Yes 107 118.7 102.9 10.0 5 480 10 30 90 180 255 290 465 470 

Bronchitis/Emphysema DK 20 188.5 176.4 39.5 5 810 8 85 155 240 320 575 810 810 

Exposure Factors Handbook Page
 

November 2011 16-93 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Food Preparation 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

4278 

1342 

2936 

94 

24 

60 

131 

3173 

796 

3584 

377 

62 

66 

132 

57 

3960 

254 

20 

44 

210 

1988 

419 

1626 

35 

291 

450 

1449 

954 

659 

475 

953 

956 

1452 

917 

2995 

1283 

1174 

1038 

1147 

919 

3948 

300 

30 

4091 

149 

38 

4024 

216 

38 

52.4 

37.8 

59.0 

52.0 

56.5 

25.2 

21.7 

52.1 

60.5 

51.6 

57.0 

54.0 

50.6 

58.8 

53.1 

51.8 

59.0 

55.0 

58.6 

27.2 

45.5 

53.9 

63.6 

53.5 

31.7 

61.3 

58.8 

52.0 

46.2 

46.0 

52.3 

53.2 

53.4 

49.9 

50.1 

57.7 

50.6 

54.4 

51.3 

53.5 

52.0 

57.1 

47.6 

52.2 

56.8 

54.0 

52.0 

56.9 

62.4 

52.9 

42.1 

55.9 

43.2 

60.4 

29.7 

37.7 

52.9 

54.7 

53.3 

52.3 

41.8 

53.2 

49.7 

49.3 

52.6 

56.7 

53.2 

53.3 

40.5 

46.7 

55.4 

57.7 

66.8 

42.6 

53.2 

56.7 

52.2 

48.1 

48.7 

53.2 

51.8 

53.5 

52.7 

50.0 

58.8 

48.6 

54.5 

54.2 

54.5 

53.2 

49.4 

44.8 

53.0 

48.2 

60.4 

53.1 

46.7 

61.7 

0.8 

1.2 

1.0 

4.5 

12.3 

3.8 

3.3 

0.9 

1.9 

0.9 

2.7 

5.3 

6.6 

4.3 

6.5 

0.8 

3.6 

11.9 

8.0 

2.8 

1.0 

2.7 

1.4 

11.3 

2.5 

2.5 

1.5 

1.7 

1.9 

2.2 

1.7 

1.7 

1.4 

1.7 

0.9 

1.6 

1.4 

1.7 

1.6 

1.8 

0.8 

2.9 

8.2 

0.8 

4.0 

9.8 

0.8 

3.2 

10.0 

1 

1 

1 

5 

5 

1 

1 

1 

1 

1 

1 

2 

1 

2 

2 

1 

2 

6 

2 

1 

1 

2 

1 

2 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

2 

1 

1 

2 

1 

3 

2 

555 

480 

555 

215 

240 

120 

385 

555 

525 

555 

390 

210 

295 

315 

210 

555 

420 

240 

210 

385 

480 

520 

555 

340 

385 

555 

520 

525 

515 

375 

480 

520 

555 

515 

555 

420 

480 

525 

555 

520 

555 

272 

195 

555 

340 

240 

555 

240 

240 

5 

5 

5 

5 

5 

2 

2 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

8 

5 

2 

5 

5 

5 

2 

2 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

2 

5 

5 

2 

20 

13 

25 

20 

23 

5 

5 

20 

25 

19 

20 

20 

15 

24 

20 

20 

20 

25 

28 

5 

15 

20 

29 

20 

5 

30 

22 

20 

15 

15 

20 

20 

16 

15 

19 

20 

18 

20 

20 

20 

20 

21 

10 

20 

25 

10 

20 

20 

20 

35 

30 

45 

40 

30 

11 

10 

35 

45 

35 

40 

50 

34 

53 

40 

35 

45 

45 

38 

15 

30 

40 

45 

30 

15 

45 

45 

35 

30 

30 

40 

35 

35 

31 

35 

40 

35 

39 

35 

37 

35 

45 

33 

35 

45 

33 

35 

45 

43 

65 

50 

75 

60 

75 

30 

30 

65 

80 

65 

75 

70 

70 

80 

60 

65 

75 

60 

80 

30 

60 

65 

90 

60 

37 

90 

75 

65 

60 

60 

60 

65 

70 

60 

60 

75 

65 

70 

60 

67 

65 

75 

60 

65 

80 

60 

65 

85 

90 

115 

80 

120 

110 

150 

60 

55 

110 

120 

110 

120 

105 

115 

110 

120 

111 

120 

113 

150 

60 

90 

105 

125 

120 

75 

120 

120 

110 

100 

95 

110 

120 

120 

105 

105 

130 

110 

120 

110 

120 

110 

120 

118 

115 

120 

120 

110 

120 

150 

150 

105 

155 

150 

180 

107 

70 

145 

150 

145 

150 

130 

150 

135 

180 

145 

155 

180 

180 

90 

130 

125 

170 

195 

120 

150 

155 

150 

125 

135 

140 

150 

150 

135 

132 

180 

135 

150 

137 

155 

145 

160 

120 

150 

135 

240 

145 

150 

240 

210 

150 

224 

195 

240 

120 

90 

210 

240 

210 

210 

175 

210 

225 

195 

205 

240 

240 

210 

120 

180 

205 

240 

340 

155 

197 

240 

210 

180 

200 

205 

210 

195 

225 

180 

240 

195 

224 

208 

200 

210 

199 

195 

210 

180 

240 

210 

198 

240 

265 

210 

272 

215 

240 

120 

90 

265 

270 

265 

240 

210 

295 

285 

210 

255 

315 

240 

210 

180 

240 

255 

275 

340 

195 

225 

310 

245 

224 

270 

255 

265 

245 

265 

240 

300 

240 

265 

300 

265 

265 

240 

195 

265 

210 

240 

265 

210 

240 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-94 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Food Cleanup 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 1143 33.0 40.4 1.2 1 825 8 15 30 35 60 85 120 135 

Gender Male 204 27.5 20.4 1.4 1 180 10 15 25 30 50 60 80 85 

Gender Female 939 34.2 43.4 1.4 1 825 5 15 30 35 60 90 120 150 

Age (years) - 24 31.0 28.0 5.7 10 120 10 15 30 30 60 105 120 120 

Age (years) 1 to 4 5 41.6 48.0 21.5 3 120 3 15 15 55 120 120 120 120 

Age (years) 5 to 11 9 28.4 21.6 7.2 1 75 1 15 30 30 75 75 75 75 

Age (years) 12 to 17 28 26.8 20.6 3.9 2 90 5 13 20 30 60 65 90 90 

Age (years) 18 to 64 808 31.3 27.1 1.0 1 330 10 15 30 30 60 80 120 120 

Age (years) > 64 269 38.8 67.4 4.1 1 825 5 15 30 40 60 105 130 270 

Race White 976 33.0 41.7 1.3 1 825 8 15 30 35 60 84 120 130 

Race Black 82 33.3 28.6 3.2 5 180 10 15 30 30 65 90 120 180 

Race Asian 11 27.1 22.0 6.6 3 75 3 15 15 30 60 75 75 75 

Race Some Others 17 29.7 34.8 8.4 5 150 5 10 15 30 60 150 150 150 

Race Hispanic 42 35.6 39.9 6.2 3 255 10 15 30 40 50 60 255 255 

Race Refused 15 34.0 28.2 7.3 5 90 5 10 30 60 90 90 90 90 

Hispanic No 1057 32.7 40.4 1.2 1 825 5 15 30 35 60 85 120 130 

Hispanic Yes 68 38.9 44.9 5.4 3 270 10 15 30 40 60 120 255 270 

Hispanic DK 6 24.2 9.7 4.0 10 35 10 15 28 30 35 35 35 35 

Hispanic Refused 12 26.7 18.3 5.3 5 60 5 13 25 33 60 60 60 60 

Employment - 39 28.2 25.8 4.1 1 120 2 15 15 30 65 90 120 120 

Employment Full Time 432 28.4 22.7 1.1 2 255 8 15 25 30 50 60 90 120 

Employment Part Time 134 28.9 21.3 1.8 3 150 10 15 25 30 60 60 95 100 

Employment Not Employed 528 38.2 53.8 2.3 1 825 5 15 30 45 60 105 120 250 

Employment Refused 10 28.0 21.9 6.9 10 60 10 10 18 55 60 60 60 60 

Education - 59 27.3 23.0 3.0 1 120 3 10 20 30 60 75 90 120 

Education < High School 135 41.9 58.6 5.0 2 570 5 15 30 45 85 120 180 270 

Education High School Graduate 445 33.3 45.8 2.2 1 825 10 15 30 30 60 90 120 120 

Education < College 259 33.6 30.0 1.9 5 255 10 15 30 45 60 85 105 150 

Education College Graduate 142 27.7 21.8 1.8 1 180 10 15 23 30 50 60 90 120 

Education Post Graduate 103 28.9 34.5 3.4 3 330 5 15 25 30 50 60 60 120 

Census Region Northeast 295 32.6 28.3 1.7 3 270 5 15 30 40 60 90 120 120 

Census Region Midwest 252 28.5 22.7 1.4 1 210 5 15 30 30 50 60 85 120 

Census Region South 343 35.9 52.5 2.8 1 825 10 15 30 40 65 90 120 180 

Census Region West 253 34.0 46.5 2.9 3 570 10 15 27 30 60 75 120 255 

Day Of Week Weekday 782 32.2 43.6 1.6 1 825 8 15 30 30 60 75 120 120 

Day Of Week Weekend 361 34.7 32.4 1.7 5 270 8 15 30 40 60 90 120 180 

Season Winter 303 33.2 51.8 3.0 1 825 8 15 30 30 60 85 120 120 

Season Spring 245 30.3 26.1 1.7 2 250 10 15 30 30 60 65 105 120 

Season Summer 293 33.2 29.9 1.7 2 270 5 15 30 40 60 90 120 135 

Season Fall 302 34.9 45.4 2.6 1 570 8 15 30 40 60 90 120 180 

Asthma No 1047 32.8 40.4 1.2 1 825 6 15 30 35 60 85 120 120 

Asthma Yes 91 36.0 41.0 4.3 2 255 8 15 30 40 60 90 250 255 

Asthma DK 5 26.0 20.7 9.3 10 60 10 10 20 30 60 60 60 60 

Angina No 1092 33.0 41.0 1.2 1 825 8 15 30 35 60 85 120 150 

Angina Yes 45 32.3 22.9 3.4 5 120 5 15 30 45 60 60 120 120 

Angina DK 6 43.3 41.8 17.1 10 120 10 10 30 60 120 120 120 120 

Bronchitis/Emphysema No 1065 31.8 28.2 0.9 1 330 8 15 30 35 60 80 120 120 

Bronchitis/Emphysema Yes 71 50.9 118.4 14.1 3 825 5 15 29 35 70 105 570 825 

Bronchitis/Emphysema DK 7 38.1 41.1 15.5 2 120 2 10 30 60 120 120 120 120 

Exposure Factors Handbook Page
 

November 2011 16-95 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Cleaning House 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

1910 

351 

1559 

45 

11 

49 

67 

1307 

431 

1614 

139 

32 

26 

73 

26 

1740 

134 

14 

22 

128 

673 

195 

901 

13 

161 

234 

665 

432 

247 

171 

454 

406 

636 

414 

1287 

623 

464 

445 

546 

455 

1764 

133 

13 

1826 

70 

14 

1791 

100 

19 

114.8 

100.4 

118.1 

136.2 

74.1 

42.6 

78.7 

115.6 

125.1 

115.9 

108.7 

97.7 

80.5 

99.8 

179.6 

114.2 

110.1 

136.1 

180.7 

64.5 

100.9 

119.4 

129.6 

235.0 

81.4 

135.7 

121.9 

108.3 

101.1 

126.1 

117.0 

114.1 

114.4 

113.8 

108.3 

128.2 

105.6 

114.2 

109.9 

130.7 

114.3 

114.7 

180.8 

113.7 

120.4 

230.0 

113.9 

118.1 

182.6 

111.7 

110.4 

111.7 

114.1 

69.4 

35.2 

79.4 

111.6 

118.3 

111.3 

106.8 

101.1 

58.1 

110.7 

176.9 

110.0 

115.8 

131.6 

177.3 

66.8 

99.9 

115.6 

118.0 

218.9 

98.1 

121.6 

118.8 

100.5 

96.6 

118.9 

117.3 

111.0 

112.9 

104.2 

108.5 

116.9 

98.3 

109.8 

113.7 

122.1 

110.1 

117.5 

214.5 

110.6 

103.1 

210.9 

111.0 

104.4 

179.3 

2.6 

5.9 

2.8 

17.0 

20.9 

5.0 

9.7 

3.1 

5.7 

2.8 

9.1 

17.9 

11.4 

13.0 

34.7 

2.6 

10.0 

35.2 

37.8 

5.9 

3.8 

8.3 

3.9 

60.7 

7.7 

8.0 

4.6 

4.8 

6.1 

9.1 

5.5 

5.5 

4.5 

5.1 

3.0 

4.7 

4.6 

5.2 

4.9 

5.7 

2.6 

10.2 

59.5 

2.6 

12.3 

56.4 

2.6 

10.4 

41.1 

1 

1 

1 

10 

10 

1 

1 

1 

3 

1 

1 

15 

5 

5 

10 

1 

5 

10 

10 

1 

1 

1 

3 

10 

1 

3 

2 

1 

1 

5 

2 

1 

1 

5 

1 

1 

1 

3 

1 

1 

1 

5 

10 

1 

5 

10 

1 

5 

5 

810 

810 

790 

480 

270 

180 

300 

810 

790 

790 

490 

425 

210 

548 

810 

790 

658 

510 

810 

300 

655 

660 

790 

810 

810 

715 

790 

570 

525 

655 

790 

720 

810 

720 

790 

810 

810 

720 

690 

790 

790 

690 

810 

790 

394 

810 

790 

480 

810 

10 

10 

15 

10 

10 

5 

5 

15 

10 

10 

5 

15 

10 

10 

20 

10 

10 

10 

20 

5 

10 

15 

15 

10 

5 

10 

15 

10 

15 

15 

10 

10 

10 

15 

10 

15 

10 

15 

10 

15 

10 

10 

10 

14 

5 

10 

10 

8 

5 

30 

30 

40 

55 

40 

20 

20 

30 

45 

35 

30 

30 

35 

30 

30 

30 

34 

30 

45 

23 

30 

45 

50 

120 

28 

50 

40 

30 

30 

45 

30 

30 

30 

40 

30 

45 

30 

30 

30 

45 

30 

33 

45 

30 

30 

120 

30 

33 

50 

80 

60 

90 

105 

60 

30 

55 

85 

90 

85 

80 

60 

60 

60 

135 

80 

60 

93 

138 

45 

60 

85 

95 

180 

45 

115 

90 

85 

60 

90 

90 

80 

80 

83 

70 

90 

75 

75 

71 

90 

83 

64 

120 

80 

90 

210 

80 

90 

150 

150 

120 

160 

180 

90 

53 

105 

150 

170 

155 

135 

128 

115 

120 

240 

150 

135 

210 

240 

78 

120 

175 

180 

255 

100 

180 

160 

149 

127 

180 

164 

150 

150 

160 

150 

180 

150 

165 

135 

180 

150 

150 

240 

150 

190 

255 

150 

180 

240 

255 

240 

255 

297 

90 

90 

240 

270 

250 

255 

270 

265 

185 

210 

390 

255 

240 

240 

340 

180 

240 

265 

285 

450 

225 

297 

270 

240 

240 

280 

240 

240 

270 

240 

240 

290 

240 

240 

245 

300 

255 

270 

340 

255 

263 

480 

255 

263 

340 

335 

310 

340 

320 

270 

120 

240 

350 

340 

330 

358 

345 

190 

345 

465 

330 

360 

510 

390 

240 

310 

390 

360 

810 

265 

390 

360 

315 

315 

390 

330 

325 

360 

330 

315 

370 

285 

340 

365 

390 

330 

390 

810 

330 

320 

810 

340 

298 

810 

465 

400 

465 

480 

270 

180 

285 

435 

540 

435 

480 

425 

210 

470 

810 

435 

480 

510 

810 

270 

410 

480 

480 

810 

300 

540 

484 

420 

390 

495 

480 

475 

435 

400 

465 

435 

360 

465 

465 

480 

450 

470 

810 

465 

370 

810 

450 

468 

810 

525 

495 

540 

480 

270 

180 

300 

510 

570 

540 

484 

425 

210 

548 

810 

525 

548 

510 

810 

285 

480 

540 

570 

810 

375 

560 

610 

470 

465 

540 

655 

495 

525 

470 

540 

525 

465 

525 

548 

560 

525 

480 

810 

525 

394 

810 

540 

475 

810 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-96 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Clothes Care 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 893 79.5 73.4 2.5 2 535 10 30 60 118 175 210 300 375 

Gender Male 117 72.2 67.0 6.2 5 360 7 20 60 90 150 210 300 335 

Gender Female 776 80.6 74.2 2.7 2 535 10 30 60 120 180 225 300 375 

Age (years) - 10 59.5 34.8 11.0 15 120 15 25 60 90 105 120 120 120 

Age (years) 1 to 4 4 70.0 94.3 47.1 5 210 5 18 33 123 210 210 210 210 

Age (years) 5 to 11 11 39.0 33.9 10.2 2 92 2 5 30 60 90 92 92 92 

Age (years) 12 to 17 21 37.5 39.4 8.6 3 150 5 10 20 60 80 120 150 150 

Age (years) 18 to 64 702 80.5 74.4 2.8 2 535 10 28 60 120 180 210 300 360 

Age (years) > 64 145 85.5 73.5 6.1 2 375 10 30 60 120 180 245 300 375 

Race White 737 80.1 73.4 2.7 2 535 10 30 60 118 175 223 300 375 

Race Black 99 68.6 65.3 6.6 5 300 5 15 45 110 165 210 240 300 

Race Asian 7 107.9 48.8 18.4 60 210 60 80 90 120 210 210 210 210 

Race Some Others 10 62.4 39.1 12.4 18 120 18 21 65 90 120 120 120 120 

Race Hispanic 33 92.9 78.0 13.6 5 265 5 20 90 150 210 225 265 265 

Race Refused 7 100.7 166.0 62.7 15 475 15 20 45 60 475 475 475 475 

Hispanic No 836 78.2 72.3 2.5 2 535 10 30 60 115 165 210 300 360 

Hispanic Yes 51 91.2 71.2 10.0 5 265 5 20 90 150 190 225 225 265 

Hispanic DK 3 118.3 62.5 36.1 55 180 55 55 120 180 180 180 180 180 

Hispanic Refused 3 185.0 251.9 145.5 20 475 20 20 60 475 475 475 475 475 

Employment - 34 43.4 46.3 7.9 2 210 3 10 30 60 92 150 210 210 

Employment Full Time 402 73.4 73.7 3.7 2 535 5 20 60 100 155 223 300 360 

Employment Part Time 116 80.7 68.5 6.4 2 335 10 30 68 118 180 225 240 330 

Employment Not Employed 336 89.8 75.2 4.1 2 475 10 35 60 120 185 235 300 375 

Employment Refused 5 87.4 74.7 33.4 2 180 2 45 60 150 180 180 180 180 

Education - 43 47.5 48.2 7.4 2 210 5 10 30 60 92 150 210 210 

Education < High School 102 86.5 60.0 5.9 10 265 15 38 65 120 175 210 240 245 

Education High School Graduate 337 85.2 82.3 4.5 2 535 10 30 60 120 180 240 375 445 

Education < College 193 85.9 78.5 5.6 2 475 5 21 60 120 190 240 300 375 

Education College Graduate 127 67.8 57.0 5.1 5 260 10 20 60 90 150 190 225 225 

Education Post Graduate 91 68.4 64.7 6.8 5 360 5 20 60 90 145 210 245 360 

Census Region Northeast 222 76.9 67.9 4.6 2 535 10 30 60 120 150 200 245 300 

Census Region Midwest 201 78.4 76.0 5.4 2 475 5 20 60 115 170 210 265 420 

Census Region South 304 81.8 75.7 4.3 5 450 10 30 60 115 170 235 330 375 

Census Region West 166 79.8 73.4 5.7 2 405 5 20 60 120 180 223 300 360 

Day Of Week Weekday 607 75.9 72.9 3.0 2 475 5 25 60 105 160 210 300 375 

Day Of Week Weekend 286 87.2 73.8 4.4 5 535 10 30 65 120 180 223 300 335 

Season Winter 254 82.3 80.2 5.0 2 475 7 23 60 120 190 225 330 445 

Season Spring 213 86.1 79.3 5.4 2 450 10 30 60 120 180 240 335 375 

Season Summer 259 76.7 68.3 4.2 2 535 8 30 60 115 154 190 240 360 

Season Fall 167 71.0 60.5 4.7 3 300 5 25 60 105 150 195 240 300 

Asthma No 829 79.5 74.0 2.6 2 535 10 30 60 118 180 225 300 360 

Asthma Yes 62 79.9 65.3 8.3 5 375 10 30 67 120 154 180 200 375 

Asthma DK 2 45.0 21.2 15.0 30 60 30 30 45 60 60 60 60 60 

Angina No 867 79.5 73.5 2.5 2 535 10 30 60 120 178 210 300 375 

Angina Yes 22 81.6 75.8 16.2 5 335 10 30 60 120 155 195 335 335 

Angina DK 4 60.0 24.5 12.2 30 90 30 45 60 75 90 90 90 90 

Bronchitis/emphysema No 834 78.5 73.6 2.5 2 535 8 25 60 115 170 210 300 375 

Bronchitis/emphysema Yes 58 94.6 68.9 9.1 5 335 15 60 78 120 190 240 300 335 

Bronchitis/emphysema DK 1 60.0 0.0 0.0 60 60 60 60 60 60 60 60 60 60 

Exposure Factors Handbook Page
 

November 2011 16-97 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-98 November 2011 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Doing Dishes/Laundry 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 1865 61.8 68.9 1.6 1 825 10 20 30 80 150 190 

Gender Male 324 46.1 50.2 2.8 1 360 10 15 30 60 120 135 

Gender Female 1541 65.1 71.8 1.8 1 825 10 20 35 90 150 200 

Age (years) - 32 43.8 46.5 8.2 10 225 10 15 30 55 90 150 

Age (years) 1 to 4 10 49.3 66.5 21.0 3 210 3 5 23 55 165 210 

Age (years) 5 to 11 20 34.3 28.8 6.4 1 92 2 15 30 58 83 91 

Age (years) 12 to 17 47 32.7 30.6 4.5 2 150 5 10 20 45 65 90 

Age (years) 18 to 64 1371 63.2 67.1 1.8 1 565 10 20 30 90 150 198 

Age (years) > 64 385 63.4 79.7 4.1 1 825 9 20 35 80 135 195 

Race White 1560 62.2 69.5 1.8 1 825 10 20 30 85 148 190 

Race Black 170 57.8 60.0 4.6 5 390 5 17 30 75 150 180 

Race Asian 19 56.7 51.7 11.9 3 210 3 15 30 90 120 210 

Race Some Others 25 46.0 41.4 8.3 5 150 10 15 30 80 120 120 

Race Hispanic 71 69.0 75.6 9.0 3 325 5 20 35 105 200 225 

Race Refused 20 60.8 104.2 23.3 5 475 8 15 30 60 128 305 

Hispanic No 1732 61.3 68.2 1.6 1 825 10 20 30 80 140 180 

Hispanic Yes 112 68.3 71.5 6.8 3 325 5 20 30 103 180 225 

Hispanic DK 7 75.7 66.5 25.2 10 180 10 15 55 150 180 180 

Hispanic Refused 14 62.5 122.3 32.7 5 475 5 15 25 35 120 475 

Employment - 73 35.3 37.4 4.4 1 210 3 15 20 50 80 120 

Employment Full Time 776 57.0 63.4 2.3 2 565 10 20 30 70 125 180 

Employment Part Time 214 63.7 64.8 4.4 2 340 10 15 30 90 151 205 

Employment Not Employed 789 68.5 76.3 2.7 1 825 10 25 40 90 158 210 

Employment Refused 13 58.2 59.4 16.5 10 180 10 10 30 100 150 180 

Education - 99 37.5 38.7 3.9 1 210 3 10 30 55 90 120 

Education < High School 216 69.8 70.0 4.8 2 570 10 27 45 90 151 195 

Education High School Graduate 683 67.4 76.7 2.9 1 825 10 20 40 90 150 205 

Education < College 422 64.3 72.3 3.5 2 475 10 20 30 85 155 210 

Education College Graduate 262 51.4 49.4 3.1 1 260 10 15 30 70 120 158 

Education Post Graduate 183 53.7 60.2 4.5 3 360 5 15 30 60 120 190 

Census Region Northeast 471 59.5 60.1 2.8 2 565 10 20 35 75 135 180 

Census Region Midwest 405 60.3 68.2 3.4 1 480 5 15 30 75 150 198 

Census Region South 602 65.8 75.1 3.1 1 825 10 20 35 90 150 210 

Census Region West 387 59.8 69.6 3.5 2 570 10 15 30 70 150 210 

Day Of Week Weekday 1270 59.5 68.8 1.9 1 825 9 20 30 75 138 190 

Day Of Week Weekend 595 66.6 68.9 2.8 5 565 10 20 40 90 150 210 

Season Winter 503 65.4 79.5 3.5 1 825 10 20 30 90 150 210 

Season Spring 438 62.8 67.8 3.2 2 450 10 20 35 75 150 190 

Season Summer 510 61.7 62.8 2.8 2 565 10 20 40 90 140 180 

Season Fall 414 56.5 63.1 3.1 1 570 8 15 30 65 130 195 

Asthma No 1712 62.0 69.6 1.7 1 825 10 20 30 85 150 195 

Asthma Yes 147 60.9 60.6 5.0 2 375 10 20 30 76 151 180 

Asthma DK 6 36.7 41.8 17.1 10 120 10 10 25 30 120 120 

Angina No 1790 62.1 69.2 1.6 1 825 10 20 30 85 150 190 

Angina Yes 66 54.8 63.0 7.8 5 335 9 25 30 60 120 200 

Angina DK 9 55.6 44.2 14.7 10 120 10 30 30 90 120 120 

Bronchitis/Emphysema No 1746 60.5 65.3 1.6 1 565 10 20 30 80 140 190 

Bronchitis/Emphysema Yes 112 82.7 109.5 10.3 3 825 5 20 58 103 170 240 

Bronchitis/Emphysema DK 7 46.7 51.4 19.4 2 120 2 10 30 120 120 120 

255 

210 

270 

225 

210 

92 

150 

245 

285 

270 

235 

210 

150 

275 

475 

250 

270 

180 

475 

150 

240 

240 

285 

180 

180 

245 

285 

285 

200 

245 

210 

240 

270 

270 

245 

275 

300 

285 

240 

230 

270 

250 

120 

255 

315 

120 

250 

360 

120 

335 

260 

340 

225 

210 

92 

150 

335 

375 

335 

240 

210 

150 

325 

475 

335 

275 

180 

475 

210 

335 

275 

375 

180 

210 

315 

405 

360 

225 

330 

285 

285 

360 

345 

330 

340 

360 

335 

270 

270 

335 

255 

120 

335 

335 

120 

325 

570 

120 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Animal Care 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 764 48.2 65.0 2.4 1 760 5 10 30 60 120 155 230 312 

Gender Male 282 57.3 81.8 4.9 1 760 5 15 30 65 120 180 308 340 

Gender Female 482 42.8 52.2 2.4 1 450 3 10 29 60 105 140 187 273 

Age (years) - 13 37.5 38.6 10.7 2 135 2 5 30 55 80 135 135 135 

Age (years) 1 to 4 9 59.2 44.3 14.8 3 140 3 30 60 90 140 140 140 140 

Age (years) 5 to 11 27 47.3 43.1 8.3 2 179 8 15 38 65 120 150 179 179 

Age (years) 12 to 17 49 55.2 68.3 9.8 3 308 5 10 25 90 175 180 308 308 

Age (years) 18 to 64 530 45.9 66.6 2.9 1 760 3 10 30 60 109 150 230 280 

Age (years) > 64 136 54.8 64.5 5.5 1 383 5 15 30 60 135 180 340 340 

Race White 696 47.8 62.0 2.4 1 760 4 10 30 60 120 155 240 312 

Race Black 26 37.6 39.8 7.8 1 145 1 10 25 45 120 120 145 145 

Race Asian 5 30.4 21.9 9.8 10 60 10 15 20 47 60 60 60 60 

Race Some Others 12 100.0 193.6 55.9 5 690 5 18 30 65 205 690 690 690 

Race Hispanic 17 37.8 45.0 10.9 5 180 5 15 30 35 120 180 180 180 

Race Refused 8 73.8 58.5 20.7 5 180 5 33 55 115 180 180 180 180 

Hispanic No 712 47.8 61.5 2.3 1 760 4 10 30 60 120 151 230 308 

Hispanic Yes 39 50.9 112.8 18.1 2 690 3 10 20 35 120 180 690 690 

Hispanic DK 6 50.0 77.1 31.5 10 205 10 10 15 45 205 205 205 205 

Hispanic Refused 7 67.9 62.0 23.4 5 180 5 20 60 120 180 180 180 180 

Employment - 86 51.2 56.8 6.1 2 308 5 15 30 70 120 175 240 308 

Employment Full Time 376 44.9 71.5 3.7 1 760 3 10 25 60 90 145 240 340 

Employment Part Time 60 48.9 56.3 7.3 3 230 5 13 20 60 153 177 205 230 

Employment Not Employed 233 52.5 59.4 3.9 1 383 5 15 30 60 120 180 273 330 

Employment Refused 9 38.9 53.9 18.0 5 180 5 20 30 30 180 180 180 180 

Education - 98 52.3 57.0 5.8 2 308 5 15 30 70 140 180 240 308 

Education < High School 63 51.5 68.1 8.6 1 383 5 15 30 60 120 225 273 383 

Education High School Graduate 231 52.9 75.8 5.0 1 760 5 10 30 70 120 165 245 330 

Education < College 150 40.6 49.2 4.0 1 280 4 10 20 55 98 155 205 230 

Education College Graduate 121 51.3 79.2 7.2 1 690 3 15 30 60 110 135 340 340 

Education Post Graduate 101 38.7 40.1 4.0 1 240 5 12 30 57 80 105 150 185 

Census Region Northeast 171 39.8 44.9 3.4 1 273 3 10 25 60 90 120 205 245 

Census Region Midwest 181 49.7 58.7 4.4 1 330 4 14 30 60 120 180 240 312 

Census Region South 247 51.4 75.0 4.8 1 760 5 15 30 60 120 165 308 383 

Census Region West 165 50.3 72.6 5.6 1 690 3 10 30 60 120 155 210 340 

Day Of Week Weekday 527 46.6 66.5 2.9 1 760 4 10 30 60 115 155 195 280 

Day Of Week Weekend 237 51.7 61.7 4.0 1 383 5 15 30 60 120 180 273 330 

Season Winter 221 44.6 66.4 4.5 1 690 4 10 25 55 95 160 225 245 

Season Spring 201 53.0 60.4 4.3 1 340 5 15 30 60 120 175 240 330 

Season Summer 216 51.4 76.4 5.2 1 760 5 15 30 64 120 165 240 383 

Season Fall 126 41.1 45.4 4.0 1 280 3 10 25 60 110 135 180 180 

Asthma No 705 48.4 65.5 2.5 1 760 4 10 30 60 120 155 225 308 

Asthma Yes 57 45.4 60.5 8.0 1 330 5 10 30 55 105 195 240 330 

Asthma DK 2 45.0 21.2 15.0 30 60 30 30 45 60 60 60 60 60 

Angina No 734 47.8 64.3 2.4 1 760 5 10 30 60 120 155 225 280 

Angina Yes 27 58.7 85.6 16.5 2 340 3 15 30 60 135 330 340 340 

Angina DK 3 35.0 22.9 13.2 15 60 15 15 30 60 60 60 60 60 

Bronchitis/emphysema No 718 48.4 65.6 2.4 1 760 4 10 30 60 120 160 230 308 

Bronchitis/emphysema Yes 43 45.4 58.5 8.9 2 330 5 10 30 55 90 150 330 330 

Bronchitis/emphysema DK 3 42.7 15.5 9.0 30 60 30 30 38 60 60 60 60 60 

Exposure Factors Handbook Page
 

November 2011 16-99 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Car Repair and Maintenance 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

DK 

-

Full Time 

Part Time 

Not Employed 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

Yes 

DK 

No 

Yes 

145 

110 

35 

1 

1 

1 

8 

114 

20 

112 

19 

2 

6 

6 

133 

10 

2 

10 

77 

12 

46 

13 

17 

50 

31 

20 

14 

28 

31 

45 

41 

79 

66 

49 

39 

35 

22 

137 

8 

139 

5 

1 

140 

5 

123.4 

135.6 

85.1 

60.0 

150.0 

300.0 

106.9 

130.3 

83.5 

139.6 

85.8 

10.0 

43.3 

58.0 

123.6 

98.8 

232.5 

130.5 

122.1 

123.2 

124.1 

120.0 

185.9 

111.5 

138.2 

93.3 

103.4 

130.8 

149.8 

106.8 

116.7 

108.5 

141.2 

130.7 

136.7 

121.5 

86.7 

117.7 

221.9 

125.7 

51.0 

165.0 

122.3 

155.0 

147.2 

152.7 

122.4 

-

-

-

163.8 

156.5 

68.4 

158.7 

93.5 

7.1 

42.4 

51.6 

145.0 

153.4 

321.7 

156.9 

150.2 

138.8 

147.0 

139.5 

224.4 

128.3 

169.2 

99.3 

97.6 

163.7 

173.2 

131.4 

132.2 

125.9 

168.5 

167.7 

156.0 

137.7 

87.5 

139.6 

235.6 

149.2 

72.9 

-

145.7 

203.3 

12.2 

14.6 

20.7 

-

-

-

57.9 

14.7 

15.3 

15.0 

21.5 

5.0 

17.3 

21.1 

12.6 

48.5 

227.5 

49.6 

17.1 

40.1 

21.7 

38.7 

54.4 

18.1 

30.4 

22.2 

26.1 

30.9 

31.1 

19.6 

20.6 

14.2 

20.7 

24.0 

25.0 

23.3 

18.7 

11.9 

83.3 

12.7 

32.6 

-

12.3 

90.9 

5 

5 

5 

60 

150 

300 

20 

5 

10 

5 

5 

5 

5 

5 

5 

5 

5 

20 

5 

8 

5 

15 

5 

5 

5 

10 

5 

8 

10 

5 

5 

5 

5 

5 

5 

5 

5 

5 

15 

5 

5 

165 

5 

5 

700 

700 

690 

60

150 

300 

505 

700 

300 

700 

300 

15

120 

120 

700 

520 

460 

505 

700 

495 

690 

505 

670 

690 

700 

300 

300 

690 

670 

700 

505 

690 

700 

690 

700 

505 

300 

700 

670 

700 

180 

165 

700 

460 

5 

5 

5 

60 

150 

300 

20 

5 

13 

10 

5 

5 

5 

5 

5 

5 

5 

20 

5 

8 

10 

15 

5 

5 

10 

10 

5 

10 

10 

5 

5 

5 

10 

5 

5 

5 

8 

5 

15 

5 

5 

165 

5 

5 

30 

30 

15 

60 

150 

300 

30 

30 

30 

30 

20 

5 

10 

13 

30 

30 

5 

30 

30 

40 

30 

30 

30 

30 

30 

15 

30 

30 

45 

30 

30 

15 

45 

30 

45 

30 

10 

30 

30 

30 

15 

165 

30 

10 

60 

85 

45 

60 

150 

300 

45 

78 

70 

90 

60 

10 

33 

45 

80 

45 

233 

53 

60 

73 

90 

60 

90 

68 

85 

45 

75 

60 

90 

60 

60 

60 

83 

60 

85 

60 

70 

60 

150 

75 

20 

165 

68 

30 

150 

170 

120 

60 

150 

300 

90 

165 

120 

175 

95 

15 

60 

120 

150 

120 

460 

150 

165 

150 

120 

120 

220 

120 

180 

135 

120 

200 

120 

120 

120 

150 

150 

165 

150 

150 

120 

120 

365 

150 

35 

165 

135 

270 

300 

300 

180 

60 

150 

300 

505 

300 

150 

300 

300 

15 

120 

120 

300 

320 

460 

403 

300 

270 

300 

300 

555 

270 

280 

285 

300 

300 

350 

240 

300 

280 

495 

350 

300 

300 

240 

300 

670 

300 

180 

165 

300 

460 

495 

505 

270 

60 

150 

300 

505 

520 

240 

520 

300 

15 

120 

120 

495 

520 

460 

505 

520 

495 

480 

505 

670 

350 

600 

300 

300 

520 

600 

300 

460 

350 

555 

600 

555 

480 

270 

495 

670 

505 

180 

165 

500 

460 

670 

600 

690 

60 

150 

300 

505 

670 

300 

670 

300 

15 

120 

120 

670 

520 

460 

505 

670 

495 

690 

505 

670 

585 

700 

300 

300 

690 

670 

700 

505 

480 

670 

690 

700 

505 

300 

600 

670 

670 

180 

165 

670 

460 

690 

670 

690 

60 

150 

300 

505 

690 

300 

690 

300 

15 

120 

120 

690 

520 

460 

505 

700 

495 

690 

505 

670 

690 

700 

300 

300 

690 

670 

700 

505 

690 

700 

690 

700 

505 

300 

690 

670 

690 

180 

165 

690 

460 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-100 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) 

Other Repairs 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 288 184.8 184.1 10.8 2 1080 10 37 120 300 425 525 690 840 

Gender Male 200 205.0 187.7 13.3 2 1080 10 60 150 328 460 555 680 810 

Gender Female 88 138.8 167.8 17.9 3 900 5 18 73 193 360 425 750 900 

Age (years) - 1 540.0 - - 540 540 540 540 540 540 540 540 540 540 

Age (years) 5 to 11 3 66.7 55.1 31.8 10 120 10 10 70 120 120 120 120 120 

Age (years) 12 to 17 14 119.5 103.4 27.6 15 345 15 30 90 180 285 345 345 345 

Age (years) 18 to 64 221 198.5 192.9 13.0 2 1080 10 45 120 325 434 570 750 840 

Age (years) > 64 49 141.9 146.9 21.0 2 526 10 30 75 209 390 480 526 526 

Race White 264 186.4 184.9 11.4 2 1080 10 37 120 300 430 525 670 840 

Race Black 13 150.4 208.0 57.7 10 750 10 30 90 120 390 750 750 750 

Race Asian 3 321.7 89.5 51.7 270 425 270 270 270 425 425 425 425 425 

Race Some Others 3 173.7 165.2 95.4 45 360 45 45 116 360 360 360 360 360 

Race Hispanic 4 127.5 122.8 61.4 10 290 10 35 105 220 290 290 290 290 

Race Refused 1 75.0 - - 75 75 75 75 75 75 75 75 75 75 

Hispanic No 278 184.9 184.5 11.1 2 1,080 10 35 120 300 425 525 690 840 

Hispanic Yes 9 160.6 180.7 60.2 10 575 10 60 60 210 575 575 575 575 

Hispanic DK 1 375.0 - - 375 375 375 375 375 375 375 375 375 375 

Employment - 17 110.2 97.4 23.6 10 345 10 30 90 180 285 345 345 345 

Employment Full Time 140 200.0 206.0 17.4 5 1080 9 60 120 298 470 600 840 900 

Employment Part Time 27 168.0 153.7 29.6 5 490 10 25 120 302 390 434 490 490 

Employment Not Employed 102 183.3 169.1 16.7 2 670 10 30 120 315 420 480 526 600 

Employment Refused 2 61.0 83.4 59.0 2 120 2 2 61 120 120 120 120 120 

Education - 18 110.7 94.6 22.3 10 345 10 30 90 180 285 345 345 345 

Education < High School 23 214.3 215.0 44.8 15 900 30 45 120 360 480 490 900 900 

Education High School Graduate 90 194.4 196.5 20.7 3 840 5 30 133 300 447 575 780 840 

Education < College 64 202.2 200.8 25.1 2 1,080 10 33 130 355 420 480 600 1,080 

Education College Graduate 54 169.0 154.5 21.0 5 525 10 60 98 270 425 490 510 525 

Education Post Graduate 39 172.9 174.2 27.9 2 690 7 38 120 270 420 600 690 690 

Census Region Northeast 55 166.2 181.3 24.5 3 840 5 30 75 210 415 525 600 840 

Census Region Midwest 77 188.9 170.2 19.4 10 780 15 60 120 315 420 460 670 780 

Census Region South 89 202.3 212.3 22.5 2 1,080 10 30 120 315 480 570 900 1,080 

Census Region West 67 172.2 161.7 19.8 2 750 7 60 120 243 340 526 690 750 

Day Of Week Weekday 188 178.2 171.9 12.5 2 780 10 43 110 300 430 490 600 750 

Day Of Week Weekend 100 197.2 205.4 20.5 3 1,080 5 33 145 297 420 585 870 990 

Season Winter 62 167.1 172.1 21.9 3 600 5 15 90 300 445 490 540 600 

Season Spring 65 203.1 216.6 26.9 5 900 10 45 120 300 480 670 840 900 

Season Summer 95 180.4 182.0 18.7 2 1,080 10 60 120 290 390 510 750 1,080 

Season Fall 66 189.7 164.6 20.3 2 600 10 55 120 330 420 435 600 600 

Asthma No 264 180.3 183.7 11.3 2 1080 10 37 120 289 420 525 690 840 

Asthma Yes 24 234.2 185.3 37.8 5 670 10 45 210 353 480 510 670 670 

Angina No 281 179.7 175.3 10.5 2 900 10 30 120 295 420 490 670 780 

Angina Yes 6 448.3 370.0 151.1 90 1,080 90 100 410 600 1,080 1,080 1,080 1,080 

Angina DK 1 45.0 - - 45 45 45 45 45 45 45 45 45 45 

Bronchitis/emphysema No 276 184.7 185.6 11.2 2 1,080 10 37 120 299 430 526 690 840 

Bronchitis/emphysema Yes 12 187.9 152.6 44.0 5 405 5 45 165 350 360 405 405 405 

Exposure Factors Handbook Page
 

November 2011 16-101 
 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) b Yardwork/Maintenance

Category Population Group N Mean SD SE Min Max 

Percentiles 

5 25 50 75 90 95 98 99 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day Of Week 

Day Of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Asthma 

Angina 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

Refused 

No 

Yes 

DK 

Refused 

-

Full Time 

Part Time 

Not Employed 

Refused 

-

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

DK 

No 

Yes 

DK 

No 

Yes 

DK 

1,414 

804 

610 

20 

12 

26 

54 

1,015 

287 

1,249 

77 

13 

26 

37 

12 

1,331 

65 

8 

10 

92 

664 

121 

526 

11 

105 

160 

465 

305 

211 

168 

291 

314 

438 

371 

878 

536 

289 

438 

458 

229 

1,311 

98 

5 

1,360 

42 

12 

1,352 

57 

5 

147.7 

174.8 

111.9 

181.9 

93.2 

96.2 

116.0 

150.2 

149.3 

151.5 

114.5 

140.0 

117.2 

102.1 

177.1 

148.7 

106.2 

248.8 

203.5 

106.8 

146.7 

134.5 

157.8 

211.6 

113.5 

158.5 

151.4 

152.8 

145.4 

142.2 

140.5 

145.1 

152.7 

149.6 

140.9 

158.9 

139.4 

162.2 

137.9 

150.0 

147.0 

149.3 

312.0 

145.3 

192.6 

257.1 

148.5 

114.7 

312.0 

148.2 

160.2 

122.0 

170.3 

80.8 

85.5 

116.8 

154.5 

133.8 

150.2 

127.1 

150.1 

110.6 

113.5 

190.8 

148.0 

127.4 

206.5 

200.1 

101.8 

155.5 

130.8 

147.0 

198.7 

113.9 

164.8 

147.0 

157.0 

138.8 

147.8 

139.6 

143.2 

156.4 

149.3 

140.8 

159.2 

151.7 

150.5 

140.3 

153.4 

147.1 

155.8 

230.0 

145.1 

203.4 

216.7 

148.5 

121.4 

230.0 

3.9 

5.6 

4.9 

38.1 

23.3 

16.8 

15.9 

4.8 

7.9 

4.3 

14.5 

41.6 

21.7 

18.7 

55.1 

4.1 

15.8 

73.0 

63.3 

10.6 

6.0 

11.9 

6.4 

59.9 

11.1 

13.0 

6.8 

9.0 

9.6 

11.4 

8.2 

8.1 

7.5 

7.8 

4.8 

6.9 

8.9 

7.2 

6.6 

10.1 

4.1 

15.7 

102.9 

3.9 

31.4 

62.6 

4.0 

16.1 

102.9 

1 

2 

1 

5 

5 

5 

3 

1 

2 

1 

2 

5 

5 

5 

30 

1 

5 

5 

60 

3 

1 

2 

2 

2 

2 

2 

3 

2 

1 

2 

3 

2 

2 

1 

1 

2 

1 

3 

2 

2 

1 

5 

60 

1 

5 

5 

1 

5 

60 

1,080 

1,080 

900 

600 

285 

330 

505 

1,080 

810 

1,080 

750 

425 

380 

565 

600 

1,080 

575 

585 

600 

505 

1,080 

554 

810 

600 

600 

900 

840 

1,080 

625 

690 

840 

780 

1,080 

750 

810 

1,080 

690 

900 

1,080 

720 

1,080 

670 

600 

900 

1,080 

600 

1,080 

460 

600 

5 

10 

5 

10 

5 

5 

5 

5 

10 

5 

5 

5 

5 

5 

30 

5 

5 

5 

60 

5 

5 

5 

10 

2 

5 

8 

5 

5 

5 

5 

5 

10 

5 

5 

5 

5 

5 

10 

5 

5 

5 

5 

60 

5 

15 

5 

5 

5 

60 

45 

60 

30 

60 

30 

39 

30 

35 

60 

45 

20 

15 

30 

20 

60 

45 

20 

90 

60 

32 

35 

30 

60 

60 

33 

45 

50 

45 

40 

30 

40 

55 

45 

40 

40 

50 

30 

60 

40 

40 

45 

30 

120 

45 

60 

53 

45 

30 

120 

100 

120 

75 

116 

83 

60 

90 

100 

120 

105 

65 

85 

88 

60 

98 

105 

60 

190 

120 

77 

90 

90 

120 

120 

79 

111 

110 

95 

105 

90 

90 

95 

111 

104 

93 

117 

75 

120 

90 

97 

100 

90 

300 

100 

143 

233 

105 

60 

300 

205 

250 

145 

240 

133 

120 

150 

210 

205 

210 

165 

210 

178 

120 

215 

209 

120 

420 

300 

148 

203 

200 

220 

375 

150 

210 

210 

210 

225 

180 

200 

195 

205 

210 

190 

225 

195 

220 

180 

210 

200 

210 

480 

200 

255 

473 

205 

135 

480 

360 

415 

278 

468 

178 

210 

285 

360 

330 

360 

285 

360 

290 

255 

510 

360 

255 

585 

555 

240 

360 

317 

370 

465 

285 

413 

345 

360 

330 

340 

330 

360 

375 

350 

345 

380 

360 

360 

310 

390 

355 

445 

600 

355 

465 

510 

360 

340 

600 

470 

510 

360 

570 

285 

300 

385 

480 

420 

480 

355 

425 

360 

300 

600 

465 

300 

585 

600 

330 

490 

390 

480 

600 

360 

493 

460 

473 

465 

470 

450 

445 

480 

480 

460 

510 

480 

480 

440 

480 

465 

480 

600 

465 

485 

600 

470 

375 

600 

570 

600 

465 

600 

285 

330 

450 

585 

525 

575 

405 

425 

380 

565 

600 

570 

565 

585 

600 

450 

575 

490 

595 

600 

450 

595 

575 

600 

525 

570 

525 

560 

585 

575 

560 

600 

565 

570 

555 

600 

570 

670 

600 

570 

1,080 

600 

570 

405 

600 

655 

670 

510 

600 

285 

330 

505 

670 

630 

660 

750 

425 

380 

565 

600 

660 

575 

585 

600 

505 

690 

495 

655 

600 

505 

810 

690 

630 

533 

630 

600 

655 

635 

690 

625 

690 

600 

700 

630 

655 

635 

670 

600 

655 

1,080 

600 

660 

460 

600 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-102 November 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-103 

Table 16-26. Time Spent (minutes/day) in Selected Activities, Doers Only (continued) -

DK 

Refused 

N 

SD 

SE 

Min 

Max 

a 

b 

Source: 

= Indicates missing data. 

= The respondent replied “don’t know”. 

= Refused data. 

= Doer sample size. 

= Standard deviation. 

= Standard error. 

= Minimum number of minutes. 

= Maximum number of minutes. 

Includes cleaning house, other repairs, and household work. 

Includes car repair services, other repairs services, outdoor cleaning, car repair maintenance, other repairs, plant care, other household work, domestic 

crafts, domestic arts. 

U.S. EPA (1996). 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

Table 16-27. Number of Hours Spent Working (hours/week) 

Working for Pay 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 4,896 0 0 0 12 33 40 50 60 61 61 61 61 

Gender Male 2,466 0 0 0 18 40 40 53 61 61 61 61 61 

Gender Female 2,430 0 0 0 6 28 40 43 55 60 61 61 61 

Age (years) 1 to 4 0 - - - - - - - - - - - -

Age (years) 5 to 11 0 - - - - - - - - - - - -

Age (years) 12 to 17 14 0 0 0 1 9 19 24 26 31 31 31 31 

Age (years) 18 to 64 4,625 0 0 0 15 35 40 50 60 61 61 61 61 

Age (years) > 64 181 0 0 0 0 5 21 40 50 61 61 61 61 

Race White 3,990 0 0 0 10 32 40 50 60 61 61 61 61 

Race Black 499 0 0 0 18 35 40 46 60 61 61 61 61 

Race Asian 76 0 0 0 7 37 40 50 61 61 61 61 61 

Race Some Others 87 0 0 0 0 30 40 50 60 61 61 61 61 

Race Hispanic 194 0 0 0 15 32 40 48 60 60 61 61 61 

Hispanic No 4,494 0 0 0 12 33 40 50 60 61 61 61 61 

Hispanic Yes 341 0 0 0 8 32 40 50 60 61 61 61 61 

Employment Full Time 4,094 0 0 0 30 40 40 50 60 61 61 61 61 

Employment Part Time 802 0 0 0 0 10 20 30 38 40 61 61 61 

Employment Not Employed 0 - - - - - - - - - - - -

Education < High School 308 0 0 0 1 21 40 48 61 61 61 61 61 

Education High School Graduate 1,598 0 0 0 12 32 40 48 60 61 61 61 61 

Education < College 1,251 0 0 0 15 30 40 50 60 61 61 61 61 

Education College Graduate 954 0 0 0 16 40 40 50 60 61 61 61 61 

Education Post Graduate 716 0 0 0 10 35 40 50 60 61 61 61 61 

Census Region Northeast 1,096 0 0 0 14 32 40 50 60 61 61 61 61 

Census Region Midwest 1,118 0 0 0 12 32 40 50 60 61 61 61 61 

Census Region South 1,675 0 0 0 12 35 40 50 60 61 61 61 61 

Census Region West 1,007 0 0 0 9 30 40 50 60 61 61 61 61 

Day of Week Weekday 3,306 0 0 0 10 33 40 50 60 61 61 61 61 

Day of Week Weekend 1,590 0 0 0 12 33 40 48 60 61 61 61 61 

Season Winter 1,306 0 0 0 10 32 40 50 60 61 61 61 61 

Season Spring 1,197 0 0 0 15 35 40 50 60 61 61 61 61 

Season Summer 1,343 0 0 0 3 33 40 48 60 61 61 61 61 

Season Fall 1,050 0 0 0 15 32 40 50 60 61 61 61 61 

Asthma No 4,,579 0 0 0 12 34 40 50 60 61 61 61 61 

Asthma Yes 302 0 0 0 9 30 40 48 60 61 61 61 61 

Angina No 4,811 0 0 0 12 34 40 50 60 61 61 61 61 

Angina Yes 66 0 0 0 0 20 40 44 60 61 61 61 61 

Bronchitis/Emphysema No 4,699 0 0 0 12 33 40 50 6 61 61 61 61 

Bronchitis/Emphysema Yes 182 0 0 0 6 30 40 48 60 61 61 61 61 

Page Exposure Factors Handbook 

16-104 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

Table 16-27. Number of Hours Spent Working (hours/week) (continued) 

Number of Hours Spent Working for Pay Between 6PM and 6AM 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 4,894 0 0 0 0 0 0 8 30 45 61 61 61 

Gender Male 2,465 0 0 0 0 0 0 10 35 50 61 61 61 

Gender Female 2,429 0 0 0 0 0 0 5 20 39 61 61 61 

Age (years) 1 to 4 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 5 to 11 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 12 to 17 14 0 0 0 0 0 5 20 24 25 25 25 25 

Age (years) 18 to 64 4,623 0 0 0 0 0 0 8 30 42 61 61 61 

Age (years) > 64 181 0 0 0 0 0 0 0 20 61 61 61 61 

Race White 3,989 0 0 0 0 0 0 8 25 40 61 61 61 

Race Black 499 0 0 0 0 0 0 10 40 61 61 61 61 

Race Asian 75 0 0 0 0 0 0 12 30 61 61 61 61 

Race Some Others 87 0 0 0 0 0 0 7 25 45 61 61 61 

Race Hispanic 194 0 0 0 0 0 0 15 35 48 61 61 61 

Hispanic No 4,492 0 0 0 0 0 0 8 27 40 61 61 61 

Hispanic Yes 341 0 0 0 0 0 0 13 35 50 61 61 61 

Employment Full Time 4,092 0 0 0 0 0 0 8 30 45 61 61 61 

Employment Part Time 802 0 0 0 0 0 0 6 20 35 61 61 61 

Employment Not Employed 0 0 0 0 0 0 0 0 0 0 0 0 0 

Education < High School 308 0 0 0 0 0 0 11 50 61 61 61 61 

Education High School Graduate 1,597 0 0 0 0 0 0 8 35 50 61 61 61 

Education < College 1,251 0 0 0 0 0 0 9 26 40 60 61 61 

Education College Graduate 953 0 0 0 0 0 0 8 20 40 61 61 61 

Education Post Graduate 716 0 0 0 0 0 0 7 20 30 61 61 61 

Census Region Northeast 1,096 0 0 0 0 0 0 7 24 40 61 61 61 

Census Region Midwest 1,118 0 0 0 0 0 0 10 30 42 61 61 61 

Census Region South 1,674 0 0 0 0 0 0 7 30 48 61 61 61 

Census Region West 1,006 0 0 0 0 0 0 10 30 47 61 61 61 

Day of Week Weekday 3,306 0 0 0 0 0 0 8 30 48 61 61 61 

Day of Week Weekend 1,588 0 0 0 0 0 0 7 28 40 61 61 61 

Season Winter 1,305 0 0 0 0 0 0 8 28 40 61 61 61 

Season Spring 1,197 0 0 0 0 0 0 8 30 48 61 61 61 

Season Summer 1,342 0 0 0 0 0 0 9 30 48 61 61 61 

Season Fall 1,050 0 0 0 0 0 0 7 25 40 61 61 61 

Asthma No 4,578 0 0 0 0 0 0 8 30 45 61 61 61 

Asthma Yes 301 0 0 0 0 0 0 8 28 36 61 61 61 

Angina No 4,809 0 0 0 0 0 0 8 30 44 61 61 61 

Angina Yes 66 0 0 0 0 0 0 7 36 40 61 61 61 

Bronchitis/Emphysema No 45,697 0 0 0 0 0 0 8 30 43 61 61 61 

Bronchitis/Emphysema Yes 182 0 0 0 0 0 0 10 40 50 61 61 61 

Exposure Factors Handbook Page
 

November 2011 16-105 
 

 

 

 

 

Table 16-27. Number of Hours Spent Working (hours/week) (continued) 

Number of Hours Worked in a Week That Was Outdoors (hours/week) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 4,891 0 0 0 0 0 0 1 30 50 61 61 61 

Gender Male 2,463 0 0 0 0 0 0 16 42 60 61 61 61 

Gender Female 2,428 0 0 0 0 0 0 0 2 12 55 61 61 

Age (years) 1 to 4 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 5 to 11 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 12 to 17 14 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 18 to 64 4,621 0 0 0 0 0 0 1 30 50 61 61 61 

Age (years) > 64 181 0 0 0 0 0 0 2 29 60 61 61 61 

Race White 3,986 0 0 0 0 0 0 2 30 50 61 61 61 

Race Black 499 0 0 0 0 0 0 0 25 48 61 61 61 

Race Asian 75 0 0 0 0 0 0 0 3 30 40 61 61 

Race Some Others 87 0 0 0 0 0 0 1 17 40 48 61 61 

Race Hispanic 194 0 0 0 0 0 0 2 30 50 61 61 61 

Hispanic No 4,489 0 0 0 0 0 0 1 30 48 61 61 61 

Hispanic Yes 341 0 0 0 0 0 0 2 35 60 61 61 61 

Employment Full Time 4,090 0 0 0 0 0 0 2 35 50 61 61 61 

Employment Part Time 801 0 0 0 0 0 0 0 15 30 61 61 61 

Employment Not Employed 0 0 0 0 0 0 0 0 0 0 0 0 0 

Education < High School 308 0 0 0 0 0 0 17 55 61 61 61 61 

Education High School Graduate 1,594 0 0 0 0 0 0 6 40 60 61 61 61 

Education < College 1,251 0 0 0 0 0 0 1 30 46 61 61 61 

Education College Graduate 953 0 0 0 0 0 0 0 20 35 50 61 61 

Education Post Graduate 716 0 0 0 0 0 0 0 4 15 60 61 61 

Census Region Northeast 1,094 0 0 0 0 0 0 0 25 40 61 61 61 

Census Region Midwest 1,117 0 0 0 0 0 0 0 30 50 61 61 61 

Census Region South 1,674 0 0 0 0 0 0 2 32 55 61 61 61 

Census Region West 1,006 0 0 0 0 0 0 2 33 50 61 61 61 

Day of Week Weekday 3,305 0 0 0 0 0 0 1 32 50 61 61 61 

Day of Week Weekend 1,586 0 0 0 0 0 0 1 30 48 61 61 61 

Season Winter 1,305 0 0 0 0 0 0 0 25 50 61 61 61 

Season Spring 1,195 0 0 0 0 0 0 2 30 50 61 61 61 

Season Summer 1,341 0 0 0 0 0 0 2 36 50 61 61 61 

Season Fall 1,050 0 0 0 0 0 0 0 30 45 61 61 61 

Asthma No 4,576 0 0 0 0 0 0 1 30 50 61 61 61 

Asthma Yes 300 0 0 0 0 0 0 0 31 50 61 61 61 

Angina No 4,806 0 0 0 0 0 0 1 30 50 61 61 61 

Angina Yes 66 0 0 0 0 0 0 4 35 50 61 61 61 

Bronchitis/Emphysema No 4,694 0 0 0 0 0 0 1 30 50 61 61 61 

Bronchitis/Emphysema Yes 182 0 0 0 0 0 0 2 30 60 61 61 61 

- Signifies missing data. 

N = Doer sample size. 

Note: A value of "61" for number of hours signifies that more than 60 hours were spent. Percentiles are the 

percentage of doers below or equal to a given number of hours. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-106 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-28. Number of Showers Taken per Day, by Children <21 Years 

Showers per Day Age (years) N 0 1 2 3 Don’t Know 

Birth to <1 37 36 1 0 0 0 

1 to <2 53 48 5 0 0 0 

2 to <3 67 54 10 2 0 1 

3 to <6 187 153 25 7 1 1 

6 to <11 245 122 95 25 1 2 

11 to <16 258 51 150 53 3 1 

16 to <21 232 23 147 57 5 0 

N = Number of respondents. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-107 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-29. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately After Bathing and 

Showering, Children <21 Years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Duration of Bath (minutes) 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

26 

37 

48 

125 

89 

38 

17 

19 

23 

23 

24 

24 

25 

33 

5 

10 

1 

5 

5 

5 

10 

5 

10 

2.9 

5 

5 

6 

11 

5 

10 

5 

5 

5 

6 

12 

6 

10 

7 

6 

10 

10 

14 

8 

10 

10 

10 

10 

10 

18 

10 

15 

15 

15 

15 

16 

20 

18 

20 

20 

25 

20 

20 

30 

28 

30 

30 

30 

30 

30 

45 

30 

30 

30 

35 

31 

40 

60 

30 

32 

45 

60 

46 

43 

60 

45 

41 

60 

60 

60 

60 

61 

53 

43 

60 

61 

60 

61 

61 

60 

45 

60 

61 

61 

61 

61 

Duration in Bathroom Immediately Following a Bath (minutes) 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

26 

37 

48 

125 

89 

38 

17 

2 

3 

4 

4 

4 

9 

11 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

0 

1 

2 

0 

0 

0 

0 

0 

1 

3 

0 

1 

0 

1 

1 

2 

5 

1 

2 

1.5 

2 

3 

5 

10 

3 

5 

5 

5 

5 

14 

10 

9 

5 

10 

10 

10 

20 

19 

10 

6 

15 

15 

10 

26 

29 

10 

10 

15 

15 

16 

33 

39 

10 

10 

18 

19 

21 

36 

42 

10 

10 

20 

30 

30 

40 

45 

Sum of Duration in Bath and in Bathroom Immediately Following Bath (minutes) 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

26 

37 

48 

125 

89 

38 

17 

22 

26 

26 

28 

28 

33 

45 

6 

10 

6 

5 

6 

7 

15 

7 

10 

7 

6 

6 

8 

15 

8 

11 

8 

7 

9 

10 

16 

9 

12 

10 

10 

10 

12 

17 

10 

16 

14 

12 

13 

16 

21 

12 

17 

16 

18 

20 

23 

30 

19 

30 

23 

30 

25 

31 

40 

29 

32 

34 

32 

33 

41 

60 

32 

35 

45 

48 

41 

52 

73 

38 

41 

50 

60 

60 

64 

77 

55 

46 

60 

66 

63 

70 

82 

63 

48 

61 

69 

71 

70 

83 

70 

50 

61 

76 

80 

70 

85 

Duration of Shower (minutes) 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

1 

5 

12 

33 

119 

204 

207 

15 

20 

22 

17 

18 

18 

20 

15 

5 

5 

3 

4 

3 

3 

-

-

5 

4 

5 

4 

5 

-

-

5 

4 

5 

5 

5 

-

-

5 

5 

5 

5 

5 

-

-

6 

5 

7 

6 

8 

-

-

14 

10 

10 

10 

10 

-

-

20 

15 

15 

15 

15 

-

-

30 

20 

20 

20 

30 

-

-

30 

30 

30 

30 

40 

-

-

44 

34 

41 

40 

45 

-

-

53 

47 

57 

50 

60 

-

-

57 

54 

60 

60 

60 

15 

30 

60 

60 

60 

60 

61 

Duration in Shower Room Immediately Following a Shower (minutes) 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

1 

5 

12 

33 

119 

204 

207 

1 

10 

5 

7 

6 

8 

8 

1 

0 

0 

0 

0 

0 

0 

-

-

0 

0 

0 

0 

0 

-

-

0 

1 

0 

0 

0 

-

-

1 

2 

0 

0 

0 

-

-

1 

2 

1 

1 

1 

-

-

1 

3 

2 

3 

3 

-

-

4 

5 

5 

5 

5 

-

-

6 

10 

10 

10 

10 

-

-

10 

15 

13 

19 

15 

-

-

12 

20 

16 

30 

20 

-

-

14 

22 

26 

40 

30 

-

-

14 

23 

30 

45 

39 

1 

45 

15 

25 

30 

60 

61 

Sum of Shower Duration and Time Spent in Shower Room Immediately Following Shower (minutes) 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

1 

5 

12 

33 

119 

204 

207 

16 

30 

27 

24 

24 

26 

28 

16 

6 

6 

8 

5 

4 

4 

-

-

6 

8 

6 

5 

5 

-

-

7 

8 

6 

7 

7 

-

-

8 

8 

8 

10 

10 

-

-

11 

8 

10 

11 

10 

-

-

19 

13 

15 

15 

15 

-

-

21 

25 

20 

22 

25 

-

-

33 

30 

30 

35 

35 

-

-

44 

40 

43 

50 

50 

-

-

56 

45 

50 

60 

60 

-

-

65 

57 

61 

65 

74 

-

-

67 

64 

68 

70 

89 

16 

60 

70 

70 

90 

70 

121 

N = Doer sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes less than 10. 

Note: A value of “61” was used for any shower, bath, or bathroom stay longer than 60 minutes. A value of “121” for the sum of shower 

duration and time spent in bathroom following shower (or the sum of bath duration and time spent in bathroom following bath) signifies 

that more than 120 minutes were spent. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-108 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

Table 16-30. Mean Time Spent (minutes/day) and Bathing/Showering, Adults 18 Years and 

Older, Doers Only 

Median Time Spent in 

Mean No. Baths/Showers per Shower/Bathb Time Spent in Shower/Bathc 

Age (years) Daya (minutes/bath) (minutes/day) 

18 to 64 1.27 13.5 17.1 

>64 1.14 15.0 17.1 a	 For additional statistics see Table 16-30. Calculated by averaging the reported number of 

baths/showers taken per day (truncated at 11), by the number of respondents. Respondents 

responding Missing and Don’t Know were excluded (N = 5). b For additional statistics see Table 16-31. c Calculated by multiplying the mean number of showers/baths per day by the median time 

spent in shower/bath. 

Source:	 U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-109 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-31. Number of Times Respondent Took Shower, Doers Only 

Category N - 1 2 3 4 5 8 10 11+ DK 

All 3,594 2 2,747 802 30 1 1 1 1 4 

Sex 

Male 1,720 - 1,259 436 21 1 - - - 1 

Female 1,872 2 1,486 366 9 - 1 1 1 3 

Refused 2 - 2 - - - - - - -

Age (years) 

- 64 - 46 17 - - - - - -

1 to 4 41 - 30 9 1 - - - - -

5 to 11 140 - 112 26 1 - - - - -

12 to 17 270 - 199 65 6 - - - - -

18 to 64 2,650 1 1,983 636 21 - - - - 3 

>64 429 1 377 49 1 - - - - 1 

Race 

White 2,911 2 2,323 562 17 - 1 - - 4 

Black 349 - 199 140 7 1 - 1 - -

Asian 64 - 49 14 1 - - - - -

Some Others 65 - 40 23 2 - - - - -

Hispanic 162 - 103 56 2 - - - 1 -

Refused 43 - 33 7 1 - - - - -

Hispanic 

No 3,269 2 2,521 711 24 1 1 1 - 4 

Yes 277 - 190 81 5 - - - 1 -

DK 17 - 13 4 - - - - - -

Refused 31 - 23 6 1 - - - - -

Employment 

- 439 - 330 99 8 - - - - -

Full Time 1,838 1 1,361 454 17 - - - 1 2 

Part Time 328 1 261 65 - - 1 - - -

Not Employed 967 - 780 177 5 1 - 1 - 2 

Refused 22 - 15 7 - - - - - -

Education 

- 515 - 382 121 9 - - - - -

< High School 297 - 240 54 2 - - - - 1 

High School Graduate 1,042 1 789 243 5 - 1 1 - 1 

< College 772 1 589 176 4 - - - 1 -

College Graduate 576 - 434 133 7 1 - - - 1 

Post Graduate 392 - 313 75 3 - - - - 1 

Census Region 

Northeast 828 - 622 196 7 - - - - -

Midwest 756 - 621 131 3 - - - - -

South 1,246 1 893 334 14 1 - - - 3 

West 764 1 611 141 6 - 1 1 1 1 

Day Of Week 

Weekday 2,481 - 1,889 563 17 1 1 1 1 4 

Weekend 1,113 2 858 239 13 - - - - -

Season 

Winter 941 - 732 198 9 - - - - 1 

Spring 889 - 674 205 7 - - - 1 -

Summer 1,003 - 735 254 10 1 - - - 2 

Fall 761 2 606 145 4 - 1 1 - 1 

Asthma 

No 3,312 2 2,543 730 25 1 1 1 1 4 

Yes 261 - 189 67 5 - - - - -

DK 21 - 15 5 - - - - - -

Angina 

No 3,481 1 2,653 730 25 1 1 1 1 4 

Yes 261 - 189 67 5 - - - - -

DK 22 - 17 4 - - - - - -

5 

2 

3 

-

1 

1 

1 

-

2 

-

2 

1 

-

-

-

2 

4 

-

-

1 

2 

2 

-

1 

-

3 

-

1 

1 

-

-

3 

1 

-

1 

4 

1 

1 

2 

1 

1 

4 

-

1 

4 

-

1 

Page Exposure Factors Handbook 

16-110 November 2011 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-111
 

Table 16-31. Number of Times Respondent Took Shower, Doers Only (continued) 

Category N - 1 2 3 4 5 8 10 11+ DK 

Bronchitis/Emphysema 

No 3,419 2 2,620 758 27 1 1 1 1 4 

Yes 154 - 112 39 3 - - - - -

DK 21 - 15 5 - - - - - -

4 

-

1 

- = Indicates missing data. 

DK = The respondent replied “don’t know”. 

Refused = Refused data. 

N = Doer sample size. 

SD = Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

 

Table 16-32. Time Spent (minutes) Showering and in Shower Room Immediately After Showering 

(minutes/shower) 

Duration of Shower 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day of Week 

Day of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

Full Time 

Part Time 

Not Employed 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

Yes 

No 

Yes 

3,547 

1,707 

1,838 

40 

139 

268 

2,634 

408 

2,873 

344 

64 

65 

161 

3,226 

276 

1,828 

324 

940 

289 

1,030 

760 

574 

389 

821 

745 

1,220 

761 

2,447 

1,100 

929 

875 

992 

751 

3,274 

257 

3,445 

84 

3,379 

151 

3 

3 

3 

5 

3 

5 

3 

3 

3 

4 

1 

3 

3 

3 

3 

3 

2 

3 

4 

2 

3 

3 

2 

4 

3 

3 

2 

3 

3 

3 

3 

2 

3 

3 

3 

3 

3 

3 

3 

4 

4 

4 

5 

4 

5 

3 

3 

4 

4 

3 

3 

4 

4 

4 

4 

3 

3 

5 

3 

5 

3 

3 

5 

4 

3 

3 

4 

4 

4 

4 

3 

4 

4 

4 

4 

4 

4 

4 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

4 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

4 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5

5 

5 

5 

5 

7 

5 

5 

5 

6

5

10 

6 

5 

6

5 

5 

5 

8 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5 

5

5 

5

5 

5

5 

5 

10 

10 

10 

5

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

7 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

10 

15 

15 

15 

10

15 

15 

15 

10 

13 

20 

15 

15 

15 

15 

15 

15 

12 

15 

15 

15 

12 

10 

10 

15 

10 

15 

10 

15 

15 

15 

15 

15 

12

15 

15 

15 

15 

15 

15 

20 

20 

20 

18 

20 

25 

20 

20 

20 

20 

20 

20 

20 

20 

23 

20 

20 

20 

20 

20 

20 

20 

15 

20 

20 

20 

15 

20 

20 

20 

20 

20 

20 

20 

20 

20 

15 

20 

20 

30 

30 

30 

30 

30 

35 

30 

30 

30 

40

30 

45 

40 

30 

39

30 

30 

30 

30 

30 

30 

25 

25 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

30 

40 

30 

30 

30 

30 

35 

30 

40 

50 

40 

45 

30 

30 

30 

60 

40 

60 

45 

30 

45 

30 

30 

40 

40 

40 

30 

30 

30 

32 

30 

40 

30 

35 

40 

40 

40 

40 

30 

32 

50 

35 

30 

35 

40 

50 

45 

60 

60 

60 

60 

45 

45 

45 

60 

48 

60 

60 

45 

60 

45 

45 

60 

60 

60 

45 

40 

45 

50 

45 

60 

45 

48 

60 

60 

60 

45 

40 

45 

60 

50 

40 

50 

48 

60 

60 

60 

60 

60 

60 

60 

60 

60 

61

61

61 

61 

60 

61

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

60 

48 

60 

60 

60 

45 

60 

60 

61 

61 

61 

60 

60 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

60 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

45 

61 

61 

Page Exposure Factors Handbook 

16-112 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

 

 

 

 

Table 16-32. Time Spent (minutes) Showering and in Shower Room Immediately After Showering 

(minutes/shower) (continued) 

Duration in Shower Room Immeditately Following a Shower (minutes) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 3,533 0 0 0 1 3 5 10 20 30 40 50 61 

Gender Male 1,698 0 0 0 1 3 5 10 15 20 30 30 61 

Gender Female 1,833 0 0 0 1 3 5 12 20 30 45 60 61 

Age (years) 1 to 4 41 0 0 0 0 1 5 10 15 20 45 45 45 

Age (years) 5 to 11 137 0 0 0 1 2 5 10 15 20 30 30 60 

Age (years) 12 to 17 2,619 0 0 0 1 3 5 10 20 30 40 52 61 

Age (years) 18 to 64 2,619 0 0 0 1 3 5 10 20 30 40 52 61 

Age (years) > 64 409 0 0 0 1 4 5 10 20 30 35 45 60 

Race White 2,872 0 0 0 1 3 5 10 20 30 40 50 61 

Race Black 341 0 0 0 1 3 5 10 20 25 30 45 60 

Race Asian 64 0 0 0 0 2 5 10 15 20 30 60 60 

Race Some Others 62 0 0 0 0 3 5 10 30 35 45 52 52 

Race Hispanic 156 0 0 0 1 3 5 10 20 25 40 60 60 

Hispanic No 3,221 0 0 0 1 3 5 10 20 30 40 50 61 

Hispanic Yes 269 0 0 0 1 3 5 10 20 25 45 60 60 

Employment Full Time 1,818 0 0 0 1 3 5 10 20 30 35 50 60 

Employment Part Time 323 0 0 0 1 3 5 10 20 30 45 50 60 

Employment Not Employed 938 0 0 0 1 3 5 10 20 30 45 60 61 

Education < High School 283 0 0 0 1 3 5 15 20 30 45 45 61 

Education High School Graduate 1,025 0 0 0 1 3 5 10 20 30 45 60 61 

Education < College 761 0 0 0 1 3 5 10 20 30 35 50 61 

Education College Graduate 573 0 0 1 1 3 5 10 20 30 35 45 60 

Education Post Graduate 387 0 0 0 1 2 5 10 20 30 30 45 60 

Census Region Northeast 822 0 0 0 1 3 5 10 20 25 40 50 60 

Census Region Midwest 737 0 0 0 1 3 5 10 20 30 35 45 60 

Census Region South 1,220 0 0 0 1 3 5 10 20 30 40 45 61 

Census Region West 754 0 0 0 1 2 5 10 20 30 30 60 61 

Day of Week Weekday 2,438 0 0 0 1 3 5 10 20 30 40 50 61 

Day of Week Weekend 1,095 0 0 0 1 3 5 10 20 30 40 50 61 

Season Winter 930 0 0 0 1 4 5 10 20 30 40 45 61 

Season Spring 876 0 0 0 1 2 5 10 20 30 45 60 61 

Season Summer 978 0 0 0 1 3 5 10 20 30 30 50 61 

Season Fall 749 0 0 0 1 3 5 10 20 25 40 53 61 

Asthma No 3,260 0 0 0 1 3 5 10 20 30 38 50 61 

Asthma Yes 259 0 0 0 1 3 5 13 20 30 40 45 61 

Angina No 3,429 0 0 0 1 3 5 10 20 30 40 50 61 

Angina Yes 88 0 0 0 2 3 8.5 15 20 30 30 45 45 

Bronchitis/Emphysema No 3,366 0 0 0 1 3 5 10 20 30 40 50 61 

Bronchitis/Emphysema Yes 152 0 0 0 1 2.5 5 10 20 30 30 45 60 

N = Doer sample size. 

Note: Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for number of 

minutes signifies that more than 60 minutes were spent. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-113
 
 

 

 

Table 16-33. Number of Baths Given or Taken in One Day by Number of Respondents 

Number of Baths/Day 

Category N 1 2 3 4 5 6 7 10 11 15 DK 

All 649 459 144 20 9 4 2 1 1 1 3 5 

Gender 

Male 159 117 33 5 1 - 1 1 - - 1 -

Female 490 342 111 15 8 4 1 - 1 1 2 5 

Age (years) 

- 9 8 1 - - - - - - - - -

18 to 64 491 322 127 20 9 4 2 1 1 1 2 2 

> 64 149 129 16 - - - - - - - 1 3 

Race 

White 487 364 92 13 7 2 1 - - 1 2 5 

Black 106 68 29 5 1 - 1 1 1 - - -

Asian 12 5 5 - 1 - - - - - 1 -

Some Others 12 7 4 1 - - - - - - - -

Hispanic 26 10 13 1 - 2 - - - - - -

Refused 6 5 1 - - - - - - - - -

Hispanic 

No 600 430 127 19 9 2 2 1 1 1 3 5 

Yes 40 21 16 1 - 2 - - - - - -

DK 6 5 1 - - - - - - - - -

Ref 3 3 - - - - - - - - - -

Employment 

- 1 1 - - - - - - - - - -

Full Time 283 183 76 12 5 - 2 1 1 1 1 1 

Part Time 76 56 17 1 1 1 - - - - - -

Not Employed 287 217 51 7 3 3 - - - - 2 4 

Refused 2 2 - - - - - - - - - -

Education 

- 4 4 - - - - - - - - - -

< High School 96 66 19 3 2 2 - - - - 1 3 

High School Graduate 235 167 54 8 2 - 1 1 - - - 2 

< College 163 112 38 6 2 2 1 - - 1 1 -

College Graduate 102 68 28 3 2 - - - 1 - - -

Post Graduate 49 42 5 - 1 - - - - - 1 -

Census Region 

Northeast 137 100 25 3 4 1 1 - - 1 - 2 

Midwest 151 116 29 4 1 - - - 1 - - -

South 255 164 70 9 2 3 1 1 - - 2 3 

West 106 79 20 4 2 - - - - - 1 -

Day of Week 

Weekday 415 299 89 10 4 2 2 1 1 1 2 4 

Weekend 234 160 55 10 5 2 - - - - 1 1 

Season 

Winter 178 124 37 10 1 3 - - - - 1 2 

Spring 160 126 27 4 1 - - 1 - - - 1 

Summer 174 112 49 4 3 1 1 - 1 - 2 1 

Fall 137 97 31 2 4 - 1 - - 1 - 1 

Asthma 

No 596 424 129 19 7 4 2 1 1 1 3 5 

Yes 52 34 15 1 2 - - - - - - -

DK 1 1 - - - - - - - - - -

Angina 

No 620 435 141 19 9 4 2 1 1 1 3 4 

Yes 26 22 2 1 - - - - - - - 1 

DK 3 2 1 - - - - - - - - -

Bronchitis/Emphysema 

No 610 429 137 20 9 4 2 1 1 1 2 4 

Yes 36 27 7 - - - - - - - 1 1 

DK 3 3 - - - - - - - - - -

- = Indicates missing data. 

DK = The respondent replied “don't know”. 

N = Doer sample size. 

Refused = Refused data. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-114 November 2011 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-34. Time Spent (minutes) Giving and Taking the Bath(s) and in Bathroom Immediately After 

Bathing (minutes/bath) 

Duration of Bath (minutes/bath) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 631 2 5 5 10 15 20 30 45 60 61 61 61 

Gender Male 155 1 4 5 6 10 15 30 45 60 61 61 61 

Gender Female 476 3 5 5 10 15 20 30 45 60 61 61 61 

Age (years) 18 to 64 485 2 5 5 10 15 20 30 60 60 61 61 61 

Age (years) > 64 139 3 5 5 5 10 15 20 40 60 61 61 61 

Race White 476 1 4 5 10 10 20 30 45 60 61 61 61 

Race Black 102 5 5 9 10 15 23 40 60 61 61 61 61 

Race Asian 12 10 10 10 10 15 20 28 30 40 40 40 40 

Race Some Others 12 5 5 5 10 15 28 30 40 61 61 61 61 

Race Hispanic 25 2 2 5 5 10 20 45 61 61 61 61 61 

Hispanic No 584 2 5 5 10 15 20 30 45 60 61 61 61 

Hispanic Yes 39 2 2 5 5 10 20 30 60 61 61 61 61 

Employment Full Time 279 1 4 5 10 15 20 30 45 60 61 61 61 

Employment Part Time 75 3 4 5 10 10 20 30 35 40 60 60 60 

Employment Not Employed 275 2 5 5 10 10 20 30 60 60 61 61 61 

Education < High School 89 1 5 10 10 15 20 35 60 61 61 61 61 

Education High School Graduate 229 5 5 5 10 12 20 30 45 60 61 61 61 

Education < College 159 1 2 5 6 10 20 30 45 60 61 61 61 

Education College Graduate 102 5 5 8 10 15 20 30 45 60 60 60 61 

Education Post Graduate 49 1 1 5 5 10 15 25 40 45 60 60 60 

Census Region Northeast 132 1 5 5 6 10 15 30 45 60 61 61 61 

Census Region Midwest 149 2 4 5 7 10 20 30 30 60 61 61 61 

Census Region South 246 3 5 10 10 15 20 35 60 60 61 61 61 

Census Region West 104 5 5 5 10 11 20 30 45 60 61 61 61 

Day of Week Weekday 403 2 5 5 10 15 20 30 45 60 61 61 61 

Day of Week Weekend 228 4 5 5 10 10 20 30 60 60 61 61 61 

Season Winter 173 2 5 5 10 10 20 30 45 60 61 61 61 

Season Spring 154 1 3 5 10 10 20 30 45 60 61 61 61 

Season Summer 171 5 5 5 10 10 20 30 60 60 61 61 61 

Season Fall 133 4 5 8 10 15 20 30 45 60 61 61 61 

Asthma No 580 2 5 5 10 12 20 30 45 60 61 61 61 

Asthma Yes 51 4 5 5 10 15 20 30 60 61 61 61 61 

Angina No 606 2 5 5 10 15 20 30 45 60 61 61 61 

Angina Yes 23 5 5 5 5 10 15 30 40 45 60 60 60 

Bronchitis/Emphysema No 595 2 5 5 10 10 20 30 45 60 61 61 61 

Bronchitis/Emphysema Yes 34 5 5 8 15 15 20 30 45 45 60 60 60 

Exposure Factors Handbook Page
 

November 2011 16-115
 
 

 

 

 

Table 16-34. Time Spent (minutes) Giving and Taking the Bath(s) and in Bathroom Immediately After 

Bathing (minutes/bath) (continued) 

Duration in Bathroom Immediately After the Bath(s) (minutes/bath) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 624 0 0 0 0 2 5 10 20 30 45 55 61 

Gender Male 153 0 0 0 0 2 5 10 12 20 30 35 45 

Gender Female 471 0 0 0 0 2 5 10 20 30 45 60 61 

Age (years) 18 to 64 484 0 0 0 0 2 5 10 15 25 40 50 61 

Age (years) > 64 133 0 0 0 1 5 10 15 30 35 55 60 60 

Race White 465 0 0 0 0 2 5 10 18 30 45 58 61 

Race Black 104 0 0 0 0 2 5 10 20 30 40 45 45 

Race Asian 12 0 0 0 0 2 5 8 10 20 20 20 20 

Race Some Others 12 0 0 0 0 0 3 8 10 15 15 15 15 

Race Hispanic 26 0 0 0 0 1 5 10 25 25 61 61 61 

Hispanic No 575 0 0 0 0 2 5 10 20 30 40 50 61 

Hispanic Yes 40 0 0 0 0 1 5 10 23 25 61 61 61 

Employment Full Time 277 0 0 0 0 2 5 10 15 20 30 30 45 

Employment Part Time 75 0 0 0 0 3 5 10 15 25 35 40 40 

Employment Not Employed 269 0 0 0 0 2 5 10 25 35 58 60 61 

Education < High School 86 0 0 0 0 5 10 15 30 35 61 61 61 

Education High School Graduate 229 0 0 0 0 2 5 10 15 30 40 45 58 

Education < College 159 0 0 0 0 2 5 10 15 30 45 60 60 

Education College Graduate 100 0 0 0 0 2 5 10 19 25 30 38 45 

Education Post Graduate 47 0 0 0 0 1 5 10 15 20 30 30 30 

Census Region Northeast 129 0 0 0 0 2 5 10 20 30 30 30 60 

Census Region Midwest 146 0 0 0 0 2 5 10 15 25 50 60 60 

Census Region South 246 0 0 0 0 3 5 10 20 30 45 55 61 

Census Region West 103 0 0 0 0 1 5 10 20 20 30 45 58 

Day of Week Weekday 398 0 0 0 0 2 5 10 18 30 40 50 61 

Day of Week Weekend 226 0 0 0 0 3 5 10 20 30 45 60 61 

Season Winter 175 0 0 0 1 3 5 10 20 30 58 61 61 

Season Spring 152 0 0 0 0 2 5 10 20 30 40 45 60 

Season Summer 165 0 0 0 0 2 5 10 15 20 30 45 50 

Season Fall 132 0 0 0 0 2 5 10 15 20 45 55 60 

Asthma No 572 0 0 0 0 2 5 10 20 30 45 58 61 

Asthma Yes 51 0 0 0 0 1 5 10 15 30 30 45 45 

Angina No 597 0 0 0 0 2 5 10 20 30 45 58 61 

Angina Yes 24 0 0 0 1 5 5 10 15 30 55 55 55 

Bronchitis/Emphysema No 588 0 0 0 0 2 5 10 20 30 45 58 61 

Bronchitis/Emphysema Yes 33 0 0 0 0 2 5 10 30 40 45 45 45 

N = Doer sample size. 

Note:	 Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for number of minutes signifies 

that more than 60 minutes were spent. 

Source:	 U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-116 November 2011 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-35. Time Spent Altogether in the Shower or Bathtub and in the Bathroom Immediately Following a 

Shower or Bath (minutes/bath) 

Duration in Shower or Bathtub (minutes/bath) 

Percentiles 

Group Name Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 4,252 3 4 5 5 10 15 20 30 35 60 60 121 

Gender Male 1,926 3 4 5 5 10 15 20 30 30 60 60 121 

Gender Female 2,325 3 4 5 5 10 15 20 30 40 60 75 121 

Age (years) 1 to 4 198 1 5 5 10 15 20 30 45 60 120 120 120 

Age (years) 5 to 11 263 4 5 5 10 13 20 30 30 60 90 120 121 

Age (years) 12 to 17 239 4 4 5 7 10 15 30 30 45 60 60 120 

Age (years) 18 to 64 2,904 3 4 5 5 10 14 20 30 30 50 60 121 

Age (years) > 64 567 2 3 5 5 10 15 20 30 30 45 60 120 

Race White 3,425 3 4 5 5 10 15 20 30 30 60 60 121 

Race Black 446 4 4 5 6 10 15 25 30 45 75 120 121 

Race Asian 74 5 5 5 7 10 15 15 30 30 60 90 90 

Race Some Others 78 5 5 5 7 10 15 30 30 45 60 60 60 

Race Hispanic 178 1 3 5 7 10 15 20 30 45 90 100 120 

Hispanic No 3,861 3 4 5 5 10 15 20 30 35 60 60 121 

Hispanic Yes 328 1 3 5 5 10 15 20 30 45 60 90 120 

Employment Full Time 1,974 3 4 5 5 10 10 20 30 30 45 60 121 

Employment Part Time 395 3 3 5 5 10 15 20 30 30 45 60 60 

Employment Not Employed 1,161 2 3 5 5 10 15 20 30 35 60 60 121 

Education < High School 376 1 4 5 5 10 15 25 30 45 60 90 121 

Education High School Graduate 1,242 3 4 5 5 10 15 20 30 30 60 60 121 

Education < College 862 3 4 5 5 10 15 20 30 30 45 60 120 

Education College Graduate 554 3 3 5 5 10 10 15 30 30 45 90 120 

Education Post Graduate 449 3 4 5 5 8 10 15 20 30 45 60 121 

Census Region Northeast 920 4 4 5 5 10 15 20 30 35 60 100 121 

Census Region Midwest 947 3 4 5 5 10 15 20 30 30 45 60 120 

Census Region South 1,497 3 4 5 5 10 15 20 30 45 60 75 121 

Census Region West 888 3 3 5 5 10 15 20 30 30 45 60 121 

Day of Week Weekday 2,858 3 4 5 5 10 15 20 30 30 60 60 121 

Day of Week Weekend 1,394 3 4 5 5 10 15 20 30 40 60 75 121 

Season Winter 1,116 3 4 5 5 10 15 20 30 35 60 60 121 

Season Spring 1,130 3 4 5 5 10 15 20 30 40 60 90 121 

Season Summer 1,154 3 4 5 5 10 15 20 30 40 60 60 121 

Season Fall 852 3 5 5 5 10 15 20 30 30 60 60 121 

Asthma No 3,911 3 4 5 5 10 15 20 30 30 60 60 121 

Asthma Yes 325 3 4 5 5 10 15 20 30 45 60 120 121 

Angina No 4,117 3 4 5 5 10 15 20 30 35 60 60 121 

Angina Yes 111 3 4 5 5 10 15 20 30 30 45 45 60 

Bronchitis/Emphysema No 4,025 3 4 5 5 10 15 20 30 30 60 60 121 

Bronchitis/Emphysema Yes 205 1 3 5 5 10 15 20 30 45 60 120 121 

Exposure Factors Handbook Page
 

November 2011 16-117
 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

 

 

 

 

 

 

Table 16-35. Time Spent Altogether in the Shower or Bathtub and in the Bathroom Immediately Following a
 

Shower or Bath (minutes/bath) (continued)
 

Duration in Bathroom Immediately Following a Shower or Bath (minutes/bath) 

Percentiles 

Group Name Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 4,182 0 0 0 1 4 5 15 20 30 40 60 121 

Gender Male 1,897 0 0 0 1 3 5 10 15 20 30 40 121 

Gender Female 2,284 0 0 0 1 5 10 15 30 30 45 60 121 

Age (years) 1 to 4 196 0 0 0 0 0 2 5 10 15 20 35 45 

Age (years) 5 to 11 260 0 0 0 0 2 5 10 15 15 30 35 120 

Age (years) 12 to 17 238 0 0 0 2 5 5 10 20 30 45 45 60 

Age (years) 18 to 64 2,866 0 0 0 1 5 10 15 20 30 45 60 121 

Age (years) > 64 548 0 0 0 1 4 10 15 20 30 40 60 120 

Race White 3,372 0 0 0 1 4 5 15 20 30 40 60 121 

Race Black 438 0 0 0 0 4 6 15 30 30 60 60 60 

Race Asian 74 0 0 0 0 2 5 10 20 30 35 45 45 

Race Some Others 76 0 0 0 1 5 10 15 20 25 30 60 60 

Race Hispanic 176 0 0 1 1 3 5 10 20 30 30 30 60 

Hispanic No 3,797 0 0 0 1 4 5 15 20 30 45 60 121 

Hispanic Yes 325 0 0 0 1 3 5 10 20 30 30 30 60 

Employment Full Time 1,949 0 0 0 1 5 10 15 20 30 40 60 121 

Employment Part Time 392 0 0 0 2 5 10 15 25 30 45 60 120 

Employment Not Employed 1,129 0 0 0 1 5 10 15 20 30 45 60 121 

Education < High School 358 0 0 0 1 5 10 15 30 30 60 90 121 

Education High School Graduate 1,220 0 0 0 1 5 10 15 25 30 45 60 121 

Education < College 847 0 0 0 1 5 10 15 20 30 30 60 121 

Education College Graduate 550 0 0 1 2 5 10 15 20 30 45 45 60 

Education Post Graduate 446 0 0 0 1 5 8 15 20 30 30 50 120 

Census Region Northeast 907 0 0 0 1 5 5 10 20 30 30 45 121 

Census Region Midwest 929 0 0 0 1 5 5 15 20 30 45 60 121 

Census Region South 1,472 0 0 0 1 4 5 15 20 30 40 60 121 

Census Region West 874 0 0 0 1 3 5 10 20 30 45 45 60 

Day of Week Weekday 2,802 0 0 0 1 4 5 10 20 30 35 50 121 

Day of Week Weekend 1,380 0 0 0 1 4 8 15 20 30 45 60 121 

Season Winter 1,090 0 0 0 1 5 7 15 20 30 45 60 121 

Season Spring 1,119 0 0 0 1 3 5 10 20 30 45 50 120 

Season Summer 1,129 0 0 0 1 3 5 10 20 30 40 52 120 

Season Fall 844 0 0 0 1 5 8 15 20 30 35 60 121 

Asthma No 3,845 0 0 0 1 4 5 15 20 30 40 60 121 

Asthma Yes 322 0 0 0 0 3 5 10 20 30 60 90 121 

Angina No 4,052 0 0 0 1 4 5 15 20 30 40 60 121 

Angina Yes 108 0 0 0 0 5 6 13 20 30 30 30 60 

Bronchitis/emphysema No 3,961 0 0 0 1 4 5 15 20 30 40 60 121 

Bronchitis/emphysema Yes 201 0 0 0 0 4 10 10 30 30 60 88 121 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers below
 

or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-118 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page 

November 2011 16-119 

 

 

 

 

 

 

 

Table 16-36. Time Spent (minutes/day) Bathing and Showering, Doers Only a 

Percentiles 

Group Name Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 6,416 26.1 29.7 0.4 1 705 5 10 20 30 50 60 90 120 

Sex Male 2,930 24.2 31.0 0.6 1 705 5 10 20 30 45 60 75 100 

Sex Female 3,484 27.6 28.4 0.5 1 555 5 10 20 30 60 75 105 135 

Sex Refused 2 20.0 14.1 10.0 10 30 10 10 20 30 30 30 30 30 

Age (years) - 114 29.0 39.0 3.7 2 300 5 10 20 30 60 60 105 275 

Age (years) 1 to 4 330 30.0 19.4 1.1 1 170 10 15 30 31 55 60 85 90 

Age (years) 5 to 11 438 25.8 35.3 1.7 1 690 5 15 20 30 45 60 60 75 

Age (years) 12 to 17 444 23.1 18.7 0.9 1 210 5 10 18 30 45 60 65 90 

Age (years) 18 to 64 4,383 25.4 27.2 0.4 1 555 5 10 20 30 50 60 90 120 

Age (years) >64 707 29.9 44.5 1.7 1 705 5 10 20 30 60 85 120 150 

Race White 5,117 25.0 28.5 0.4 1 705 5 10 20 30 45 60 90 115 

Race Black 707 31.5 31.6 1.2 1 295 5 15 22 40 60 80 120 170 

Race Asian 112 28.2 29.8 2.8 5 270 5 15 20 30 60 75 90 90 

Race Some Others 122 30.2 27.3 2.5 1 240 8 15 28 35 50 60 100 150 

Race Hispanic 280 28.8 39.3 2.3 2 546 5 15 20 32 55 63 90 155 

Race Refused 78 27.6 40.3 4.6 3 275 5 10 15 30 60 100 195 275 

Hispanic No 5,835 25.9 28.5 0.4 1 705 5 10 20 30 50 60 90 120 

Hispanic Yes 486 28.8 40.6 1.8 2 570 5 15 20 30 50 60 90 140 

Hispanic DK 33 25.8 16.8 2.9 5 65 10 15 20 30 55 65 65 65 

Hispanic Refused 62 24.3 37.2 4.7 3 275 5 10 15 25 30 60 105 275 

Employment - 1,189 26.1 26.4 0.8 1 690 5 15 20 30 45 60 75 90 

Employment Full Time 3,095 24.1 25.1 0.5 1 555 5 10 15 30 45 60 85 110 

Employment Part Time 558 24.8 23.2 1.0 1 295 5 10 20 30 46 60 90 110 

Employment Not Employed 1,528 30.3 39.9 1.0 1 705 5 10 20 30 60 85 120 155 

Employment Refused 46 30.4 45.2 6.7 3 275 5 10 15 30 55 105 275 275 

Education - 1,330 25.7 26.4 0.7 1 690 5 15 20 30 45 60 75 90 

Education < High School 474 33.3 53.0 2.4 1 570 5 15 21 33 60 85 110 300 

Education High School Graduate 1,758 25.8 23.6 0.6 1 270 5 10 20 30 50 60 90 120 

Education < College 1,288 26.4 27.0 0.8 1 255 5 10 20 30 55 75 105 150 

Education College Graduate 897 25.4 34.8 1.2 1 705 5 10 15 30 50 65 105 135 

Education Post Graduate 669 22.8 23.1 0.9 1 257 5 10 15 30 45 60 85 100 

Census Region Northeast 1,444 25.0 24.3 0.6 1 360 5 10 20 30 50 60 90 105 

Census Region Midwest 1,402 24.6 30.3 0.8 1 570 5 10 15 30 45 60 85 115 

Census Region South 2,266 27.4 26.1 0.5 1 300 5 15 20 30 55 65 100 135 

Census Region West 1,304 26.5 38.8 1.1 1 705 5 10 20 30 48 60 90 133 

Day Of Week Weekday 4,427 25.3 30.3 0.5 1 705 5 10 20 30 45 60 90 115 

Day Of Week Weekend 1,989 27.9 28.2 0.6 1 555 5 15 20 30 60 68 100 130 

Season Winter 1,796 26.9 26.9 0.6 1 546 5 11 20 30 50 60 90 110 

Season Spring 1,645 28.6 41.1 1.0 1 705 5 15 20 30 60 70 115 150 

Season Summer 1,744 23.9 20.7 0.5 1 270 5 10 20 30 45 60 80 100 

Season Fall 1,231 24.7 25.6 0.7 1 340 5 10 17 30 50 60 95 120 

Asthma No 5,912 26.1 30.0 0.4 1 705 5 10 20 30 50 60 90 120 

Asthma Yes 468 26.5 23.0 1.1 1 210 5 15 20 30 46 60 100 120 

Asthma DK 36 23.1 44.1 7.3 3 275 5 10 15 25 30 30 275 275 

Angina No 6,243 26.0 29.0 0.4 1 705 5 10 20 30 50 60 90 120 

Angina Yes 131 31.1 49.5 4.3 5 546 5 15 25 30 50 60 105 131 

Angina DK 42 22.2 40.9 6.3 3 275 5 10 15 25 30 30 275 275 

Bronchitis/Emphysema No 6,112 26.1 29.9 0.4 1 705 5 10 20 30 50 60 90 120 

Bronchitis/Emphysema Yes 268 27.2 22.2 1.4 1 150 5 13 20 30 60 60 95 131 

Bronchitis/Emphysema DK 36 22.5 44.1 7.3 3 275 5 10 15 23 30 30 275 275 

-

DK 

Refused 

= Indicates missing data. 

= The respondent replied “don’t know”. 

= Refused data. 

N 

SD 

= Doer sample size. 

= Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

a Includes baby and child care, personal care services, washing and personal hygiene (bathing, showering, etc.). 

Source: U.S. EPA (1996). 
 

Table 16-37. Number of Times Washing the Hands at Specified Daily Frequencies, Children <21 Years 

Number of Times/Day Age (years) N 0 1–2 3–5 6–9 10–19 20–29 30+ DK 

Birth to <1 37 2 15 12 2 1 1 0 4 

1 to <2 53 7 8 23 8 4 0 2 1 

2 to <3 67 0 15 39 10 0 1 0 2 

3 to <6 187 2 37 101 27 10 1 2 7 

6 to <11 245 2 47 131 34 16 3 1 11 

11 to <16 258 8 37 128 49 22 5 2 7 

16 to <21 232 0 23 115 47 38 4 3 2 

N = Number of respondents. 

DK = Respondents answered “don’t know.” 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-120 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

 

 

 

 

 

Table 16-38. Number of Times Washing the Hands at Specified Daily Frequencies, Doers Only 

Number of Times/Day 

N – 0–0 1–2 3–5 6–9 10–19 20–29 30+ DK 

All 4,663 38 34 311 1,692 1,106 892 223 178 189 

Sex 

Male 2,163 16 19 218 975 487 286 59 49 54 

Female 2,498 22 15 92 716 619 606 164 129 135 

Refused 2 - - 1 1 - - - - ­

Age (years) - 84 8 - 1 25 15 11 4 5 15 

1 to 4 263 - 15 62 125 35 11 2 3 10 

5 to 11 348 1 5 61 191 48 21 4 2 15 

12 to 17 326 3 6 46 159 64 30 7 2 9 

18 to 64 2,972 18 7 131 1,029 760 640 168 143 76 

>64 670 8 1 10 163 184 179 38 23 64 

Race 

White 3,774 21 28 251 1,377 902 740 181 140 134 

Black 463 6 2 30 149 120 85 19 23 29 

Asian 77 1 - 5 29 19 12 4 1 6 

Some Others 96 - 1 10 39 16 15 8 5 2 

Hispanic 193 1 3 14 78 42 31 10 5 9 

Refused 60 9 - 1 20 7 9 1 4 9 

Hispanic

No 4,244 27 29 276 1,536 1,022 823 205 164 162 

Yes 347 2 5 33 130 76 57 17 10 17 

DK 26 - - 1 12 4 5 1 1 2 

Refused 46 9 - 1 14 4 7 - 3 8 

Employment - 926 4 26 165 471 145 61 13 7 34 

Full Time 2,017 12 4 96 707 525 406 116 103 48 

Part Time 379 - - 13 142 101 86 10 15 12 

Not Employed 1,309 18 4 36 365 327 334 83 52 90 

Refused 32 4 - 1 7 8 5 1 1 5 

Education - 1,021 13 26 174 507 158 74 13 12 44 

< High School 399 2 - 8 120 96 88 26 24 35 

High School Graduate 1,253 12 4 56 391 318 298 70 47 57 

< College 895 2 3 28 284 246 197 59 48 28 

College Graduate 650 6 - 23 238 174 139 28 27 15 

Post Graduate 445 3 1 22 152 114 96 27 20 10 

Census Region

Northeast 1,048 9 6 68 404 243 195 55 38 30 

Midwest 1,036 5 7 68 373 251 212 41 38 41 

South 1,601 14 11 108 559 379 299 79 66 86 

West 978 10 10 67 356 233 186 48 36 32 

Day of Week

Weekday 3,156 34 22 199 1,103 764 599 155 147 133 

Weekend 1,507 4 12 112 589 342 293 68 31 56 

Season 

Winter 1,264 6 10 91 507 286 223 55 51 35 

Spring 1,181 13 9 78 406 283 238 60 44 50 

Summer 1,275 15 9 78 443 315 232 65 48 70 

Fall 943 4 6 64 336 222 199 43 35 34 

Asthma 

No 4,287 28 32 283 1,562 1,024 819 207 165 167 

Yes 341 1 2 26 126 77 69 16 10 14 

DK 35 9 - 2 4 5 4 - 3 8 

Angina

No 4,500 28 34 306 1,652 1,069 851 218 171 171 

Yes 125 2 - 3 32 34 36 5 3 10 

DK 38 8 - 2 8 3 5 - 4 8 

Bronchitis/Emphysema

No 4,424 27 33 302 1,627 1,040 835 213 172 175 

Yes 203 3 1 7 57 61 55 10 3 6 

DK 36 8 - 2 8 5 2 - 3 8 

- = Indicates missing data. 

DK = The respondent replied “don’t know”. 

Refused = Refused data. 

N = Doer sample size. 

SD = Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-121 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-122 November 2011 

Table 16-39. Number of Times Swimming in a Month in Freshwater Swimming Pool, Children <21 Years 

Age 

(year) N Times/Month 

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 

Birth to <1 

1to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

10 

8 

18 

45 

76 

66 

50 

1 

2 

3 

5 

15 

19 

6 

4 

3 

4 

7 

10 

10 

6 

1 

1 

1 

6 

5 

6 

2 

0 

0 

0 

5 

5 

3 

6 

0 

1 

1 

2 

5 

5 

6 

2 

0 

1 

1 

3 

4 

2 

0 

0 

0 

1 

1 

1 

2 

0 

1 

1 

2 

3 

3 

1 

0 

0 

1 

0 

0 

1 

0 

1 

0 

2 

2 

6 

4 

5 

0 

0 

0 

0 

0 

0 

1 

0 

0 

2 

0 

5 

1 

1 

0 

0 

0 

1 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

0 

1 

5 

7 

2 

0 

0 

0 

0 

0 

2 

0 

0 

Age 

(year) N Times/Month 

18 20 23 24 25 26 28 29 30 32 40 42 45 50 60 DK 

Birth to <1 

1to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

10 

8 

18 

45 

76 

66 

50 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

2 

3 

2 

6 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

0 

1 

1 

0 

1 

0 

0 

0 

0 

0 

0 

2 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

1 

0 

0 

3 

3 

2 

3 

0 

0 

0 

1 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

0 

0 

1 

0 

N 

DK 

Source: 

= Doer sample size. 

= Respondents answered “don’t know.” 

U.S. EPA re-analysis of source data from U.S. EPA (1996). 

 

 

 

Table 16-40. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool, Children <21 Years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

10 

7 

18 

42 

72 

65 

50 

96 

105 

116 

137 

151 

139 

145 

6 

45 

15 

6 

8 

4 

2 

-

-

16 

8 

13 

8 

3 

-

-

17 

9 

17 

11 

5 

-

-

19 

12 

30 

20 

25 

-

-

27 

40 

60 

30 

39 

-

-

60 

83 

150 

90 

124 

-

-

120 

181 

181 

181 

181 

-

-

181 

181 

181 

181 

181 

-

-

181 

181 

181 

181 

181 

-

-

181 

181 

181 

181 

181 

-

-

181 

181 

181 

181 

181 

-

-

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

N = Doer sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes of 10 or fewer. 

Note: A value of 181 for number of minutes signifies that more than 180 minutes were spent. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-123 

Table 16-41. Number of Times Swimming in a Month in Freshwater Swimming Pool, Doers Only 

N 

Times/Month 

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 

All 

Sex 

Male 

Female 

Refused 

Age (years) 

-

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

Race 

White 

Black 

Asian 

Some Others 

Hispanic

Refused 

Hispanic

No 

Yes 

DK 

Refused 

Employment -

Full Time 

Part Time 

Not Employed

Refused 

Education -

< High School

High School Graduate

<College

College Graduate

Post Graduate 

Census Region

Northeast 

Midwest 

South 

West 

Day of Week

Weekday

Weekend 

Season 

Winter 

Spring

Summer 

Fall 

Asthma 

No 

Yes 

DK 

Angina

No 

Yes 

DK 

Bronchitis/Emphysema 

No 

Yes 

DK 

653 

300 

352 

1 

8 

63 

100 

84 

360 

38 

555 

30 

13 

12 

35 

8 

591 

55 

2 

5 

243 

240 

43 

122 

5 

257 

16 

112 

104 

93 

71 

136 

130 

235 

152 

445 

208 

62 

174 

363 

54 

590 

56 

7 

639 

8 

6 

621 

26 

6 

147 

62 

85 

-

2 

11 

16 

21 

86 

11 

126 

8 

3 

2 

5 

3 

135 

10 

-

2 

47 

56 

13 

30 

1 

51 

2 

28 

29 

22 

15 

32 

35 

46 

34 

97 

50 

19 

55 

61 

12 

132 

14 

1 

143 

3 

1 

138 

8 

1 

94 

47 

47 

-

2 

14 

15 

13 

48 

2 

74 

7 

2 

-

8 

3 

81 

11 

-

2 

41 

38 

2 

12 

1 

43 

2 

15 

11 

12 

11 

15 

21 

36 

22 

67 

27 

12 

25 

45 

12 

81 

11 

2 

90 

1 

3 

91 

1 

2 

73 

37 

36 

-

1 

7 

7 

7 

50 

1 

64 

1 

2 

2 

4 

-

68 

5 

-

-

21 

38 

4 

10 

-

21 

3 

16 

11 

14 

8 

10 

17 

29 

17 

52 

21 

5 

19 

41 

8 

67 

5 

1 

73 

-

-

71 

2 

-

47 

20 

27 

-

1 

3 

9 

4 

27 

3 

44 

-

-

2 

1 

-

44 

2 

1 

-

17 

15 

3 

12 

-

18 

-

11 

2 

10 

6 

16 

8 

13 

10 

36 

11 

3 

13 

29 

2 

43 

4 

-

47 

-

-

45 

1 

1 

42 

16 

26 

-

1 

3 

6 

8 

22 

2 

32 

2 

1 

1 

6 

-

35 

6 

1 

-

15 

13 

8 

6 

-

17 

3 

6 

9 

2 

5 

9 

6 

15 

12 

25 

17 

1 

9 

26 

6 

38 

3 

1 

41 

1 

-

40 

2 

-

26 

17 

9 

-

1 

4 

4 

4 

11 

2 

25 

-

-

-

1 

-

25 

1 

-

-

12 

10 

-

3 

1 

12 

1 

5 

2 

3 

3 

4 

7 

12 

3 

15 

11 

2 

7 

15 

2 

25 

1 

-

26 

-

-

25 

1 

-

11 

5 

6 

-

-

1 

2 

2 

5 

1 

10 

-

1 

-

-

-

10 

1 

-

-

5 

3 

1 

2 

-

5 

1 

1 

3 

-

1 

1 

2 

7 

1 

9 

2 

-

3 

8 

-

10 

1 

-

10 

1 

-

10 

1 

-

26 

9 

17 

-

-

3 

4 

3 

14 

2 

23 

1 

1 

-

1 

-

25 

1 

-

-

10 

8 

1 

7 

-

11 

1 

1 

7 

2 

4 

4 

4 

10 

8 

14 

12 

6 

7 

12 

1 

24 

2 

-

26 

-

-

24 

1 

1 

2 

2 

-

-

-

1 

-

1 

-

-

2 

-

-

-

-

-

2 

-

-

-

2 

-

-

-

-

2 

-

-

-

-

-

-

-

2 

-

1 

1 

-

-

2 

-

2 

-

-

2 

-

-

2 

-

-

38 

16 

22 

-

-

4 

7 

8 

18 

1 

36 

-

1 

-

1 

-

36 

2 

-

-

18 

10 

4 

6 

-

19 

-

5 

4 

5 

5 

13 

9 

10 

6 

24 

14 

2 

8 

27 

1 

37 

1 

-

37 

-

1 

38 

-

-

3 

2 

1 

-

-

-

-

-

3 

-

1 

2 

-

-

-

-

3 

-

-

-

-

1 

2 

-

-

-

1 

1 

1 

-

-

1 

-

2 

-

2 

1 

1 

-

2 

-

3 

-

-

3 

-

-

2 

1 

-

27 

13 

14 

-

-

2 

5 

1 

15 

4 

23 

-

1 

-

3 

-

24 

3 

-

-

8 

8 

2 

9 

-

8 

-

5 

7 

6 

1 

8 

4 

8 

7 

18 

9 

3 

7 

14 

3 

25 

2 

-

27 

-

-

27 

-

-

2 

1 

1 

-

-

1 

-

-

1 

-

2 

-

-

-

-

-

1 

1 

-

-

1 

1 

-

-

-

1 

-

-

-

-

1 

1 

1 

-

-

2 

-

-

-

2 

-

2 

-

-

2 

-

-

2 

-

-

2 

-

1 

1 

-

1 

-

-

1 

-

2 

-

-

-

-

-

2 

-

-

-

1 

1 

-

-

-

1 

-

1 

-

-

-

2 

-

-

-

2 

-

-

-

2 

-

2 

-

-

2 

-

-

2 

-

-

27 

16 

11 

-

-

2 

11 

2 

10 

2 

21 

2 

-

4 

-

-

24 

3 

-

-

15 

6 

1 

5 

-

15 

-

3 

3 

4 

2 

4 

6 

9 

8 

21 

6 

-

2 

24 

1 

22 

5 

-

26 

1 

-

25 

2 

-

2 

1 

1 

-

-

-

2 

-

-

-

1 

1 

-

-

-

-

2 

-

-

-

2 

-

-

-

-

2 

-

-

-

-

-

-

-

2 

-

1 

1 

-

1 

1 

-

2 

-

-

2 

-

-

2 

-

-
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-41. Number of Times Swimming in a Month in Freshwater Swimming Pool, Doers Only (continued) 

Times/Month 

18 20 23 24 25 26 28 29 30 31 32 40 42 45 50 60 DK 

All 2 25 1 1 9 2 1 1 26 2 1 2 2 1 1 2 5 

Sex 

Male 

Female 

Refused 

-

2 

-

10 

15 

-

-

1 

-

-

1 

-

4 

5 

-

2 

-

-

1 

-

-

-

1 

-

10 

16 

-

2 

-

-

1 

-

-

1 

1 

-

1 

1 

-

-

1 

-

-

1 

-

-

2 

-

4 

1 

-

Age (years) -

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

-

-

-

1 

-

1 

-

2 

3 

4 

15 

1 

-

-

-

-

1 

-

-

-

1 

-

-

-

-

-

2 

-

7 

-

-

-

-

1 

1 

-

-

-

-

-

1 

-

-

1 

-

-

-

-

-

2 

5 

2 

15 

2 

-

-

-

-

2 

-

-

1 

-

-

-

-

-

-

-

-

2 

-

-

-

-

-

1 

1 

-

-

-

-

1 

-

-

-

1 

-

-

-

-

-

-

1 

-

1 

-

-

-

1 

3 

1 

Race 

White 

Black 

Asian 

Some Others 

Hispanic

Refused 

2 

-

-

-

-

-

19 

3 

1 

-

1 

1 

1 

-

-

-

-

-

1 

-

-

-

-

-

9 

-

-

-

-

-

2 

-

-

-

-

-

1 

-

-

-

-

-

1 

-

-

-

-

-

19 

3 

-

-

3 

1 

2 

-

-

-

-

-

1 

-

-

-

-

-

2 

-

-

-

-

-

2 

-

-

-

-

-

-

-

-

-

1 

-

-

-

-

1 

-

-

2 

-

-

-

-

-

5 

-

-

-

-

-

Hispanic

No 

Yes 

DK 

Refused 

2 

-

-

-

23 

1 

-

1 

1 

-

-

-

1 

-

-

-

9 

-

-

-

2 

-

-

-

1 

-

-

-

1 

-

-

-

20 

6 

-

-

2 

-

-

-

1 

-

-

-

2 

-

-

-

2 

-

-

-

-

1 

-

-

1 

-

-

-

2 

-

-

-

4 

1 

-

-

Employment -

Full Time 

Part Time 

Not Employed

Refused 

1 

-

-

1 

-

9 

8 

-

7 

1 

-

-

-

1 

-

1 

-

-

-

-

2 

5 

1 

1 

-

1 

-

-

1 

-

-

1 

-

-

-

1 

-

-

-

-

9 

10 

1 

6 

-

-

2 

-

-

-

1 

-

-

-

-

-

2 

-

-

-

-

1 

-

1 

-

-

1 

-

-

-

1 

-

-

-

-

1 

-

-

1 

-

1 

2 

-

1 

1 

Education -

< High School

High School Graduate

< College

College Graduate

Post Graduate 

1 

-

-

-

-

1 

11 

1 

6 

3 

2 

2 

-

-

-

1 

-

-

1 

-

-

-

-

-

2 

-

1 

4 

2 

-

2 

-

-

-

-

-

-

-

-

-

-

1 

1 

-

-

-

-

-

9 

1 

4 

4 

3 

5 

-

-

-

-

2 

-

1 

-

-

-

-

-

-

-

-

-

2 

-

-

-

1 

-

1 

-

-

-

-

1 

-

-

1 

-

-

-

-

-

1 

-

1 

-

-

-

1 

-

1 

2 

1 

-

Census Region

Northeast 

Midwest 

South 

West 

-

-

2 

-

7 

4 

7 

7 

-

-

1 

-

-

-

1 

-

2 

1 

4 

2 

1 

-

-

1 

-

-

1 

-

-

-

1 

-

2 

4 

9 

11 

1 

-

1 

-

-

-

-

1 

1 

-

1 

-

1 

1 

-

-

-

-

-

1 

-

-

1 

-

-

-

1 

1 

1 

-

4 

-

Day of Week

Weekday

Weekend 

1 

1 

18 

7 

1 

- 1 - 7 2 

1 

1 

1 

- -1 

19 

7 -2 

1 

- 1 1 -2 

1 

- 1 - 2 - 4 1 

Season 

Winter 

Spring

Summer 

Fall 

1 

-

1 

-

3 

8 

10 

4 

-

-

1 

-

-

-

1 

-

-

2 

7 

-

1 

-

1 

-

1 

-

-

-

-

-

1 

-

-

3 

21 

2 

1 

-

1 

-

-

-

1 

-

-

-

2 

-

1 

1 

-

-

-

-

1 

-

-

1 

-

-

-

1 

1 

-

-

2 

3 

-

Asthma 

No 

Yes 

DK 

2 

-

-

21 

3 

1 

1 

-

-

1 

-

-

9 

-

-

1 

1 

-

1 

-

-

1 

-

-

23 

2 

1 

2 

-

-

1 

-

-

2 

-

-

2 

-

-

1 

-

-

-

1 

-

2 

-

-

5 

-

-

Angina

No 

Yes 

DK 

2 

-

-

24 

-

1 

1 

-

-

1 

-

-

9 

-

-

2 

-

-

1 

-

-

1 

-

-

26 

-

-

2 

-

-

1 

-

-

2 

-

-

1 

1 

-

1 

-

-

1 

-

-

2 

-

-

5 

-

-

Bronchitis/Emphysema

No 

Yes 

DK 

2 

-

-

22 

2 

1 

1 

-

-

1 

-

-

9 

-

-

2 

-

-

1 

-

-

1 

-

-

23 

3 

-

2 

-

-

1 

-

-

2 

-

-

2 

-

-

1 

-

-

1 

-

-

2 

-

-

4 

1 

-

- = Indicates missing data. 

DK = The respondent replied “don’t know”. 

Refused = Refused data. 

N = Doer sample size. 

SD = Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-124 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-125 

Table 16-42. Time Spent (minutes/month) in Freshwater Swimming Pool, Doers Only 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day of Week 

Day of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

Full Time 

Part Time 

Not Employed 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

Yes 

No 

Yes 

640 

295 

345 

60 

95 

83 

357 

38 

548 

27 

13 

12 

34 

580 

54 

237 

43 

121 

16 

111 

102 

92 

71 

134 

127 

227 

152 

434 

206 

60 

171 

356 

53 

578 

55 

626 

8 

608 

26 

2 

3 

2 

3 

2 

4 

2 

5 

2 

10 

4 

2 

3 

2 

3 

3 

2 

2 

1 

3 

3 

2 

5 

4 

5 

2 

2 

2 

4 

2 

2 

3 

2 

2 

2 

2 

15 

3 

2 

3 

4 

3 

3 

3 

5 

3 

5 

3 

10 

4 

2 

3 

3 

5 

4 

2 

2 

1 

5 

3 

3 

10 

8 

5 

3 

3 

3 

5 

3 

4 

3 

10 

3 

3 

3 

15 

3 

2 

10 

8 

10 

8 

20 

15 

5 

8 

10 

15 

4 

2 

5 

10 

5 

5 

5 

8 

1 

8 

5 

10 

10 

10 

10 

5 

5 

8 

10 

5 

5 

10 

10 

10 

4 

10 

15 

10 

5 

15 

10 

15 

15 

30 

20 

10 

10 

15 

30 

20 

15 

10 

15 

15 

10 

15 

10 

2 

10 

10 

15 

10 

15 

15 

15 

10 

10 

15 

13 

10 

15 

10 

15 

10 

15 

15 

15 

5 

30 

30 

30 

20 

45 

40 

20 

30 

30 

60 

30 

25 

20 

30 

30 

20 

20 

20 

13 

30 

20 

23 

20 

30 

30 

30 

20 

30 

30 

30 

20 

30 

20 

30 

30 

30 

25 

30 

15 

60 

45 

60 

43 

60 

60 

45 

40 

45 

60 

60 

60 

60 

60 

53 

45 

30 

45 

30 

60 

30 

43 

30 

45 

45 

60 

45 

60 

60 

53 

40 

60 

45 

55 

60 

60 

43 

60 

43 

90 

90 

90 

120 

120 

120 

60 

60 

90 

150 

60 

150 

120 

90 

120 

60 

90 

60 

61 

90 

60 

61 

60 

120 

90 

120 

61 

90 

90 

90 

60 

120 

70 

90 

120 

90 

75 

90 

60 

180 

180 

180 

180 

180 

180 

120 

120 

180 

181 

120 

181 

180 

180 

180 

150 

120 

120 

181 

180 

120 

150 

70 

180 

150 

180 

120 

180 

180 

120 

120 

180 

180 

180 

180 

180 

120 

180 

181 

181 

181 

181 

181 

181 

181 

181 

120 

181 

181 

181 

181 

181 

181 

181 

181 

181 

180 

181 

181 

120 

181 

120 

181 

180 

181 

180 

181 

181 

181 

180 

181 

181 

181 

181 

181 

120 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

180 

181 

180 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

120 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

120 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

181 

120 

181 

181 

N 

Note: 

Source: 

= Doer sample size. 

A Value of 181 for number of minutes signifies that more than 180 minutes were spent. 

U.S. EPA (1996). 
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-43. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population and Doers 

Only, Children <21 Years 

Age (years) N Mean Min Percentiles Max 1 2 5 10 25 50 75 90 95 98 99 

Playing on Dirt―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

11 

37 

61 

179 

98 

35 

7 

15 

20 

18 

29 

28 

25 

9 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

1 

-

10 

10 

20 

59 

60 

30 

-

20 

84 

60 

120 

120 

77 

-

71 

121 

120 

121 

121 

120 

-

101 

121 

121 

121 

121 

120 

-

111 

121 

121 

121 

121 

121 

-

121 

121 

121 

121 

121 

121 

30 

Playing on Dirt―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

5 

13 

24 

82 

44 

18 

2 

33 

56 

47 

63 

63 

49 

30 

2 

5 

5 

1 

2 

1 

30 

-

5 

5 

1 

3 

2 

-

-

5 

5 

1 

5 

2 

-

-

5 

5 

1 

10 

4 

-

-

6 

7 

6 

15 

9 

-

-

10 

15 

30 

30 

19 

-

-

45 

30 

60 

60 

30 

-

-

120 

60 

120 

120 

60 

-

-

121 

121 

121 

121 

120 

-

-

121 

121 

121 

121 

120 

-

-

121 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

121 

121 

121 

121 

121 

121 

30 

Playing on Sand/Gravel―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

10 

37 

58 

186 

101 

36 

8 

4 

17 

24 

30 

30 

30 

42 

0 

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

-

-

0 

0 

0 

0 

0 

-

-

0 

0 

0 

0 

0 

-

-

0 

0 

0 

0 

0 

-

-

0 

0 

0 

0 

0 

-

-

0 

0 

2 

0 

0 

-

-

30 

30 

60 

60 

38 

-

-

60 

120 

120 

120 

120 

-

-

84 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

20 

121 

121 

121 

121 

121 

121 

Playing on Sand/Gravel―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

2 

15 

26 

93 

46 

16 

4 

18 

43 

53 

60 

67 

67 

83 

15 

5 

1 

3 

5 

1 

30 

-

5 

1 

3 

7 

3 

-

-

5 

1 

3 

10 

5 

-

-

5 

1 

5 

11 

12 

-

-

7 

3 

8 

15 

15 

-

-

15 

10 

25 

30 

26 

-

-

30 

30 

60 

60 

60 

-

-

60 

120 

90 

120 

120 

-

-

103 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

20 

121 

121 

121 

121 

121 

121 

Playing on Grass―Whole Population 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

11 

38 

59 

180 

99 

36 

8 

43 

62 

55 

69 

62 

67 

45 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

-

0 

0 

0 

0 

0 

0 

-

0 

9 

1 

0 

0 

1 

-

2 

16 

15 

28 

20 

30 

-

30 

60 

30 

60 

60 

60 

-

73 

120 

120 

121 

120 

120 

-

121 

121 

121 

121 

121 

121 

-

121 

121 

121 

121 

121 

121 

-

121 

121 

121 

121 

121 

121 

-

121 

121 

121 

121 

121 

121 

-

121 

121 

121 

121 

121 

121 

120 

Playing on Grass―Doers Only 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

9 

35 

53 

157 

85 

32 

6 

52 

68 

62 

79 

73 

75 

60 

1 

5 

1 

1 

1 

1 

15 

-

7 

2 

2 

5 

5 

-

-

8 

3 

2 

9 

10 

-

-

10 

3 

10 

11 

23 

-

-

15 

5 

15 

17 

30 

-

-

25 

20 

60 

30 

30 

-

-

60 

60 

70 

60 

60 

-

-

120 

120 

121 

120 

120 

-

-

121 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

-

121 

121 

121 

121 

121 

-

121 

121 

121 

121 

121 

121 

120 

N = Sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes of 10 or fewer. 

Note: A value of “121” for number of minutes signifies that more than 120 minutes were spent. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996) 

Page Exposure Factors Handbook 

16-126 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-44. Number of Minutes Spent Playing or Working on Selected Outdoor Surfaces, Doers Only 

Dirt (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day of Week 

Day of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

Full Time 

Part Time 

Not Employed 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

No 

Yes 

647 

326 

320 

205 

185 

38 

214 

2

528 

60 

5 

16 

36 

574 

69 

138 

25 

52 

17 

67 

62 

51 

18 

118 

116 

250 

163 

406 

241 

93 

230 

245 

79 

590 

56 

646 

627 

20 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0

0 

0 

30 

0 

1 

0 

1 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

0 

0 

0 

0 

10 

0 

0 

0 

30 

30 

30 

30 

30 

30 

15 

0

30 

30 

30 

20 

60 

30 

30 

15 

10 

10 

60 

10 

15 

15 

0 

30 

20 

30 

60 

30 

30 

45 

30 

30 

10 

30 

60 

30 

30 

38 

100 

120 

60 

120 

120 

60 

60 

0

120 

74 

121 

40 

120 

90 

120 

60 

60 

60 

121 

60 

60 

30 

60 

60 

60 

90 

121 

88 

120 

121 

105 

90 

60 

110 

60 

100 

120 

60 

121 

121 

121 

121 

121 

120 

120 

0

121 

120 

121 

60 

121 

121 

121 

120 

60 

60 

121 

88 

60 

60 

120 

121 

120 

121 

121 

121 

121 

121 

121 

121 

120 

121 

121 

121 

121 

90.5 

121 

121 

121 

121 

121 

120 

121 

0

121 

121 

121 

60 

121 

121 

121 

121 

121 

121 

121 

120 

121 

121 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

120 

121 

0

121 

121 

121 

60 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

120 

121 

0 

121 

121 

121 

60 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

Exposure Factors Handbook Page
 

November 2011 16-127 
 

Table 16-44. Number of Minutes Spent Playing on Selected Outdoor Surfaces, Doers Only (continued) 

Sand or Gravel (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day of Week 

Day of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Bronchitis/emphysema 

Bronchitis/emphysema 

Male 

Female 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

Full Time 

Part Time 

Not Employed 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

No 

Yes 

659 

334 

324 

203 

193 

40 

219 

2

534 

64 

5 

15 

39 

583 

72 

140 

27 

53 

17 

69 

64 

50 

20 

116 

122 

256 

165 

410 

249 

97 

232 

250 

80 

600 

58 

659 

638 

21 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

0 

3 

0 

0 

0

0 

0 

30 

0 

15 

0 

2 

0 

10 

0 

0 

0 

0 

0 

15 

0 

0 

0 

0 

0 

0 

5 

1 

0 

0 

0 

3 

0 

0 

30 

45 

45 

60 

30 

60 

45 

45 

0

50 

15 

60 

60 

60 

45 

60 

45 

60 

30 

60 

30 

38 

30 

60 

60 

30 

45 

60 

40 

60 

45 

53 

60 

30 

45 

60 

45 

45 

60 

120 

120 

120 

120 

121 

120 

120 

0

120 

120 

121 

121 

121 

120 

120 

105 

121 

120 

121 

121 

120 

60 

120 

120 

60 

120 

121 

120 

121 

120 

120 

120 

105 

120 

120 

120 

120 

121 

121 

121 

121 

121 

121 

121 

121 

0

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

60 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

0

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

0

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

0 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-128 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-44. Number of Minutes Spent Playing on Selected Outdoor Surfaces, Doers Only (continued) 

Grass (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 

Sex 

Sex 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day of Week 

Day of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

>64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

Full Time 

Part Time 

Not Employed 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

No 

Yes 

657 

327 

329 

206 

185 

39 

221 

3 

532 

65 

5 

16 

37 

581 

72 

141 

27 

55 

20 

69 

64 

51 

19 

119 

120 

252 

166 

412 

245 

95 

231 

250 

81 

600 

56 

656 

636 

21 

0 

0 

0 

0 

0 

0 

0 

30 

0 

0 

10 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

30 

0 

0 

10 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

30 

0 

0 

10 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

30 

0 

3 

10 

0 

0 

0 

0 

0 

0 

5 

5 

0 

0 

1 

0 

0 

8 

1 

0 

0 

1 

0 

1 

2 

0 

0 

0 

0 

0 

0 

20 

20 

15 

15 

30 

30 

20 

30 

20 

20 

30 

10 

30 

20 

10 

20 

15 

23 

30 

15 

18 

30 

25 

30 

30 

20 

10 

15 

30 

4 

30 

30 

10 

20 

23 

20 

20 

30 

60 

60 

60 

60 

60 

60 

60 

121 

60 

58 

30 

60 

60 

60 

35 

60 

60 

60 

60 

60 

47 

60 

60 

60 

60 

60 

45 

60 

60 

30 

60 

60 

35 

60 

60 

60 

60 

60 

120 

121 

120 

120 

121 

120 

120 

121 

121 

90 

30 

120 

110 

121 

100 

121 

120 

121 

121 

121 

60 

121 

121 

121 

121 

120 

120 

120 

121 

120 

121 

121 

120 

120 

120.5 

120 

120 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

Exposure Factors Handbook Page
 

November 2011 16-129 
 

 

 

Table 16-44. Number of Minutes Spent Playing on Selected Outdoor Surfaces, Doers Only (continued) 

Working With Soil in a Garden or Other Circumstances (hours/month) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 4,572 0 0 0 0 0 0 3 15 40 88 160 320 

Gender Male 2,125 0 0 0 0 0 0 3 20 50 150 230 320 

Gender Female 2,445 0 0 0 0 0 0 2 12 30 60 90 320 

Age (years) 1 to 4 256 0 0 0 0 0 0 1 7 20 60 120 150 

Age (years) 5 to 11 341 0 0 0 0 0 0 2 10 20 50 60 320 

Age (years) 12 to 17 321 0 0 0 0 0 0 1 5 10 40 60 200 

Age (years) 18 to 64 2,935 0 0 0 0 0 0 3 16 40 90 200 320 

Age (years) > 64 646 0 0 0 0 0 0 3 25 60 90 160 300 

Race White 3,715 0 0 0 0 0 0 3 16 40 88 160 320 

Race Black 454 0 0 0 0 0 0 0 8 30 60 160 320 

Race Asian 76 0 0 0 0 0 0 2 6 15 24 40 40 

Race Some Others 94 0 0 0 0 0 0 2 15 60 150 200 200 

Race Hispanic 187 0 0 0 0 0 0 2 12 25 90 320 320 

Hispanic No 4,179 0 0 0 0 0 0 3 15 40 80 180 320 

Hispanic Yes 336 0 0 0 0 0 0 2 15 32 90 120 320 

Employment Full Time 1,999 0 0 0 0 0 0 4 20 45 144 240 320 

Employment Part Time 375 0 0 0 0 0 0 3 12 32 90 120 320 

Employment Not Employed 1,270 0 0 0 0 0 0 3 20 45 64 100 320 

Education < High School 381 0 0 0 0 0 0 2 16 60 120 160 320 

Education High School Grad 1,228 0 0 0 0 0 0 4 20 50 120 200 320 

Education < College 884 0 0 0 0 0 0 4 20 40 90 240 320 

Education College Grad. 649 0 0 0 0 0 0 3 16 40 70 100 320 

Education Post Grad. 443 0 0 0 0 0 0 5 20 40 61 90 320 

Census Region Northeast 1,031 0 0 0 0 0 0 1 10 30 90 120 320 

Census Region Midwest 1,013 0 0 0 0 0 0 2 10 30 60 120 320 

Census Region South 1,566 0 0 0 0 0 0 3 18 40 90 180 320 

Census Region West 962 0 0 0 0 0 0 5 20 50 90 200 320 

Day of Week Weekday 3,094 0 0 0 0 0 0 3 15 40 80 160 320 

Day of Week Weekend 1,478 0 0 0 0 0 0 3 15 40 90 150 320 

Season Winter 1,255 0 0 0 0 0 0 0 4 12 50 90 320 

Season Spring 1,152 0 0 0 0 0 0 5 20 45 110 200 320 

Season Summer 1,236 0 0 0 0 0 0 5 25 50 96 160 320 

Season Fall 929 0 0 0 0 0 0 3 10 30 88 180 320 

Asthma No 4,217 0 0 0 0 0 0 3 15 40 90 160 320 

Asthma Yes 335 0 0 0 0 0 0 2 12 30 60 80 320 

Angina No 4,426 0 0 0 0 0 0 3 15 40 88 160 320 

Angina Yes 121 0 0 0 0 0 0 2 7 24 60 110 120 

Bronchitis/Emphysema No 4,352 0 0 0 0 0 0 3 15 40 88 180 320 

Bronchitis/Emphysema Yes 198 0 0 0 0 0 0 1 7 24 60 80 100 

N = Doer sample size. 

NOTE: A value of “121” for number of minutes signifies that more than 120 minutes were spent. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-130 November 2011 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-45. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air, Children <21 Years 

Age (years) N Mean Min Percentiles 

1 2 5 10 25 50 75 90 95 98 99 Max 

Birth to <1 

1 to <2 

2 to <3 

3 to <6 

6 to <11 

11 to <16 

16 to <21 

2 

5 

1 

15 

12 

14 

14 

63 

44 

121 

63 

60 

53 

65 

5 

0 

121 

0 

0 

0 

2 

-

-

-

0 

0 

0 

2 

-

-

-

1 

0 

0 

3 

-

-

-

1 

1 

1 

4 

-

-

-

2 

2 

2 

7 

-

-

-

8 

5 

6 

16 

-

-

-

60 

45 

38 

53 

-

-

-

121 

121 

113 

121 

-

-

-

121 

121 

121 

121 

-

-

-

121 

121 

121 

121 

-

-

-

121 

121 

121 

121 

-

-

-

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

121 

N = Doer sample size. 

Min = Minimum. 

Max = Maximum. 

- = Percentiles were not calculated for sample sizes of 10 or fewer. 

Note: A value of “121” for number of minutes signifies that more than 120 minutes were spent. 

Source: U.S. EPA re-analysis of source data from U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-131 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

 

 

Table 16-46. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air, Doers Only 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 679 0 2 5 7 30 121 121 121 121 121 121 121 

Sex Male 341 1 2 5 8 30 121 121 121 121 121 121 121 

Sex Female 338 0 2 5 5 30 121 121 121 121 121 121 121 

Age (years) 1 to 4 22 0 0 0 2 5 75 121 121 121 121 121 121 

Age (years) 5 to 11 50 0 1 2 4 15 75 121 121 121 121 121 121 

Age (years) 12 to 17 52 0 1 2 5 5 20 120 121 121 121 121 121 

Age (years) 18 to 64 513 2 5 5 10 30 121 121 121 121 121 121 121 

Age (years) >64 38 2 2 2 5 35 106 121 121 121 121 121 121 

Race White 556 0 2 5 8 30 121 121 121 121 121 121 121 

Race Black 66 1 3 5 5 20 121 121 121 121 121 121 121 

Race Asian 7 20 20 20 20 60 90 121 121 121 121 121 121 

Race Some Others 15 5 5 5 10 60 120 121 121 121 121 121 121 

Race Hispanic 29 3 3 5 7 20 121 121 121 121 121 121 121 

Hispanic No 611 0 2 5 5 30 121 121 121 121 121 121 121 

Hispanic Yes 57 0 3 3 10 30 121 121 121 121 121 121 121 

Employment Full Time 368 2 5 7 15 38 121 121 121 121 121 121 121 

Employment Part Time 66 0 2 5 5 20 120 121 121 121 121 121 121 

Employment Not Employed 122 0 2 5 8 30 121 121 121 121 121 121 121 

Education < High School 52 2 5 5 7 35 121 121 121 121 121 121 121 

Education High School Graduate 199 0 0 5 10 30 121 121 121 121 121 121 121 

Education < College 140 5 5 10 20 60 121 121 121 121 121 121 121 

Education College Graduate 82 1 2 5 15 30 121 121 121 121 121 121 121 

Education Post Graduate 76 3 5 5 10 38 121 121 121 121 121 121 121 

Census Region Northeast 138 0 0 5 5 20 121 121 121 121 121 121 121 

Census Region Midwest 145 2 2 5 10 30 121 121 121 121 121 121 121 

Census Region South 227 1 2 5 5 30 121 121 121 121 121 121 121 

Census Region West 169 0 3 5 10 30 120 121 121 121 121 121 121 

Day of Week Weekday 471 0 1 5 7 30 121 121 121 121 121 121 121 

Day of Week Weekend 208 2 2 5 5 30 121 121 121 121 121 121 121 

Season Winter 154 0 0 5 5 30 121 121 121 121 121 121 121 

Season Spring 193 0 1 3 5 20 121 121 121 121 121 121 121 

Season Summer 193 2 2 5 10 30 121 121 121 121 121 121 121 

Season Fall 139 3 5 5 10 30 121 121 121 121 121 121 121 

Asthma No 606 0 2 5 5 30 121 121 121 121 121 121 121 

Asthma Yes 73 0 3 5 10 30 121 121 121 121 121 121 121 

Angina No 662 0 2 5 7 30 121 121 121 121 121 121 121 

Angina Yes 15 3 3 3 30 60 121 121 121 121 121 121 121 

Bronchitis/Emphysema No 637 0 2 5 7 30 121 121 121 121 121 121 121 

Bronchitis/Emphysema Yes 41 0 0 5 5 30 121 121 121 121 121 121 121 

N = Doer sample size.
 

Note: A value of “121” for number of minutes signifies that more than 120 minutes were spent.
 

Source: U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-132 November 2011 
Exposure Factors Handbook Page 

November 2011 16-133 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-47. Number of Times Floors Were Swept or Vacuumed at Specified Frequencies by the Number of 

Respondents 

Number of Times 

N Almost Every Day 3-5/week 1-2/week 1-2/month < Often Never DK 

All 4,663 921 1,108 2,178 373 48 10 25 

Gender 

Male 2,163 415 520 976 201 27 5 19 

Female 2,498 505 588 1,201 172 21 5 6 

Refused 2 1 0 1 0 0 0 0 

Age (years) - 84 16 11 41 12 3 0 1 

1 to 4 263 96 74 88 4 0 0 1 

5 to 11 348 115 107 120 6 0 0 0 

12 to 17 326 82 83 144 15 2 0 0 

18 to 64 2,972 524 723 1,420 252 34 6 13 

> 64 670 88 110 365 84 9 4 10 

Race 

White 3,774 641 879 1,868 324 36 8 18 

Black 463 167 115 150 19 5 2 5 

Asian 77 11 15 39 8 3 0 1 

Some Others 96 26 29 32 8 1 0 0 

Hispanic 193 68 61 55 7 2 0 0 

Refused 60 8 9 34 7 1 0 1 

Hispanic

No 4,244 799 988 2,035 345 43 9 25 

Yes 347 106 107 110 21 3 0 0 

DK 26 8 3 11 2 1 1 0 

Refused 46 8 10 22 5 1 0 0 

Employment - 926 290 267 342 24 2 0 1 

Full Time 2,017 291 486 1,018 184 27 2 9 

Part Time 379 82 82 177 34 1 0 3 

Not Employed 1,309 256 263 626 127 18 8 11 

Refused 32 2 10 15 4 0 0 1 

Education - 1,021 314 285 384 31 4 0 3 

< High School 399 110 91 162 20 6 2 8 

High School Graduate 1,253 269 302 591 69 12 3 7 

< College 895 130 223 438 93 8 2 1 

College Graduate 650 64 132 346 93 9 3 3 

Post Graduate 445 34 75 257 67 9 0 3 

Census Region

Northeast 1,048 236 230 484 83 8 2 5 

Midwest 1,036 156 249 527 86 10 2 6 

South 1,601 376 403 707 93 11 2 9 

West 978 153 226 460 111 19 4 5 

Day of Week

Weekday 3156 631 765 1,458 248 33 5 16 

Weekend 1507 290 343 720 125 15 5 9 

Season 

Winter 1,264 268 309 557 105 15 2 8 

Spring 1,181 217 286 560 96 12 3 7 

Summer 1,275 251 312 596 94 13 1 8 

Fall 943 185 201 465 78 8 4 2 

Asthma 

No 4,287 821 1,013 2,030 351 39 10 23 

Yes 341 95 88 133 17 7 0 1 

DK 35 5 7 15 5 2 0 1 

Angina

No 4,500 892 1,080 2,098 352 44 10 24 

Yes 125 21 23 63 16 2 0 0 

DK 38 8 5 17 5 2 0 1 

Bronchitis/emphysema

No 4,424 871 1,064 2,063 349 44 9 24 

Yes 203 45 39 99 17 2 1 0 

DK 36 5 5 16 7 2 0 1 

N = Sample size. 

DK = The respondent replied “don't know.” 

- = Indicates missing data. 

Refused = respondent refused to answer. 

Source: U.S. EPA (1996). 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-134 November 2011 

Table 16-48. Number of Days Since the Floor Area in the Home Was Swept or Vacuumed by the Number of 

Respondents 

Number of Days Since That Area Was Swept-Vacuumed 

SweptVacuumed >2 

N 0 Yes'day 1 2 3 4 5 6 7 8 10 14 Weeks DK 

All 9,386 8,112 550 278 189 85 63 31 17 26 2 1 5 16 11 

Gender 

Male 4,294 3,688 245 136 100 35 37 19 8 10 1 0 3 7 5 

Female 5,088 4,421 304 142 89 50 26 12 9 16 1 1 2 9 6 

Refused 4 3 1 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 

- 187 180 1 0 3 1 0 0 0 0 0 0 0 1 1 

1 to 4 499 67 199 93 54 24 19 17 9 7 0 1 2 6 1 

5 to 11 703 393 121 70 50 23 22 8 2 4 1 0 2 2 5 

12 to 17 589 533 30 12 6 3 0 0 1 2 0 0 0 2 0 

18 to 64 6,059 5,,592 198 102 76 34 22 6 5 13 1 0 1 5 4 

> 64 1,349 1347 1 1 0 0 0 0 0 0 0 0 0 0 0 

Race 

White 7,591 6,586 398 232 152 72 55 29 14 24 2 1 5 13 8 

Black 945 825 72 18 17 7 3 1 2 0 0 0 0 0 0 

Asian 157 138 5 6 2 2 1 0 0 1 0 0 0 1 1 

Some Others 182 141 21 7 9 2 1 0 0 0 0 0 0 1 0 

Hispanic 385 300 52 15 9 2 2 0 1 1 0 0 0 1 2 

Refused 126 122 2 0 0 0 1 1 0 0 0 0 0 0 0 

Hispanic 

No 8,534 7,421 460 248 170 80 57 29 15 24 2 1 5 14 8 

Yes 702 549 88 29 17 5 4 2 2 2 0 0 0 1 3 

Dk 47 42 1 1 1 0 1 0 0 0 0 0 0 1 0 

Refused 103 100 1 0 1 0 1 0 0 0 0 0 0 0 0 

Employment 

- 1,773 974 349 175 112 50 41 25 12 13 1 1 4 9 7 

Full Time 4,096 3,826 96 64 50 21 18 6 4 6 1 0 0 4 0 

Part Time 802 741 28 10 8 6 2 0 0 4 0 0 1 1 1 

Not Employed 2,644 2502 77 29 18 8 2 0 1 3 0 0 0 1 3 

Refused 71 ,69 0 0 1 0 0 0 0 0 0 0 0 1 0 

Education 

- 1,968 1,162 353 175 114 50 41 25 12 13 1 1 4 10 7 

< High School 834 793 24 13 2 1 0 0 0 0 0 0 0 0 1 

High School Graduate 2,612 2,447 76 39 26 9 7 1 2 0 1 0 0 2 2 

< College 1,801 1,681 55 25 18 10 6 0 1 3 0 0 0 2 0 

College Graduate 1,247 1,155 28 19 17 10 5 3 1 7 0 0 0 1 1 

Post Graduate 924 874 14 7 12 5 4 2 1 3 0 0 1 1 0 

Census Region 

Northeast 2,075 1,793 129 65 35 18 4 9 9 6 0 0 0 5 2 

Midwest 2,102 1,826 108 59 47 21 17 7 2 6 2 1 2 2 2 

South 3,243 2,805 193 87 75 26 27 8 3 8 0 0 2 5 4 

West 1,966 1,688 120 67 32 20 15 7 3 6 0 0 1 4 3 

Day of Week 

Weekday 6,316 5,487 366 160 125 57 51 18 13 15 2 1 4 11 6 

Weekend 3,070 2,625 184 118 64 28 12 13 4 11 0 0 1 5 5 

Season 

Winter 2,524 2,144 162 79 61 27 17 7 3 13 0 0 1 5 5 

Spring 2,438 2,112 121 90 48 19 19 9 7 4 0 0 2 5 2 

Summer 2,536 2,187 167 68 41 26 19 12 3 3 0 1 2 4 3 

Fall 1,888 1,669 100 41 39 13 8 3 4 6 2 0 0 2 1 

Asthma 

No 8,629 7,455 502 262 171 80 59 30 13 22 2 1 5 16 11 

Yes 694 596 48 15 17 5 4 1 4 4 0 0 0 0 0 

Dk 63 61 0 1 1 0 0 0 0 0 0 0 0 0 0 
 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-135 

Table 16-48. Number of Days Since the Floor Area in the Home Was Swept or Vacuumed by the Number of 

Respondents (continued) 

Number of Days Since That Area Was Swept-Vacuumed 

N 0 

SweptVacuumed 

Yes'day 1 2 3 4 5 6 7 8 10 14 

>2 

Weeks DK 

Angina 

No 

Yes 

Dk 

9,061 

250 

75 

7,793 

246 

73 

547 

2 

1 

277 

1 

0 

189 

0 

0 

83 

1 

1 

63 

0 

0 

31 

0 

0 

17 

0 

0 

26 

0 

0 

2 

0 

0 

1 

0 

0 

5 

0 

0 

16 

0 

0 

11 

0 

0 

Bronchitis/emphysema 

No 

Yes 

Dk 

8,882 

433 

71 

7,645 

397 

70 

536 

13 

1 

268 

10 

0 

182 

7 

0 

84 

1 

0 

61 

2 

0 

31 

0 

0 

17 

0 

0 

25 

1 

0 

2 

0 

0 

1 

0 

0 

5 

0 

0 

15 

1 

0 

10 

1 

0 

N = Sample size. 

DK = The respondent replied “don't know.” 

- = Indicates missing data. 

Refused = Respondent refused to answer. 

Source: U.S. EPA (1996). 
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-49. Time Spent (minutes/day) With Smokers Present, Children <21 Years 

Age 

(year) N Mean SD SE Min Percentiles 

5 25 50 75 90 95 98 99 Max 

1 to 4 

5 to 11 

12 to 17 

155 367 325 26 5 30 90 273 570 825 1,010 1,140 1,305 

224 318 314 21 1 25 105 190 475 775 1,050 1,210 1,250 

256 246 244 15 1 10 60 165 360 595 774 864 1,020 

1,440 

1,440 

1,260 

N 

SD 

SE 

Min 

Max 

Source: 

= Doer sample size. 

= Standard deviation. 

= Standard error. 

= Minimum. 

= Maximum. 

U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-136 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page 

November 2011 16-137 

 

 

 

 

 

 

 

Table 16-50. Time Spent (minutes/day) With Smokers Present, Doers Only 

Percentiles 

Category Population Group N Mean SD SE Min Max 5 25 50 75 90 95 98 99 

All 4,005 381.5 300.5 4.7 1 1,440 30 120 319 595 815 925 1,060 1,170 

Sex Male 1,967 411.4 313.0 7.1 1 1,440 30 135 355 638 855 965 1,105 1,217 

Sex Female 2,035 352.8 285.1 6.3 1 1,440 29 105 285 545 780 870 995 1,110 

Sex Refused 3 283.3 188.2 108.6 105 480 105 105 265 480 480 480 480 480 

Age (years) - 54 386.3 305.4 41.6 5 1,440 25 105 370 555 780 995 995 1,440 

Age (years) 1 to 4 155 366.6 324.5 26.1 5 1,440 30 90 273 570 825 1,010 1,140 1,305 

Age (years) 5 to 11 224 318.1 314.0 21.0 1 1,440 25 105 190 475 775 1,050 1,210 1,250 

Age (years) 12 to 17 256 245.8 243.6 15.2 1 1,260 10 60 165 360 595 774 864 1,020 

Age (years) 18 to 64 2,976 403.1 299.4 5.5 2 1,440 30 135 355 625 830 930 1,047 1,150 

Age (years) >64 340 342.7 292.2 15.8 5 1,440 30 100 240 540 798 880 1,015 1,205 

Race White 3,279 389.2 303.0 5.3 1 1,440 30 120 330 610 825 930 1,060 1,190 

Race Black 395 360.0 288.0 14.5 2 1,440 22 118 300 538 775 905 1,080 1,160 

Race Asian 48 262.1 209.9 30.3 5 800 10 64 213 413 560 630 800 800 

Race Some Others 79 420.7 339.2 38.2 10 1,328 30 135 310 655 885 1,140 1,305 1,328 

Race Hispanic 165 292.6 250.2 19.5 5 1,095 15 75 220 475 660 800 845 945 

Race Refused 39 393.5 325.3 52.1 25 1,110 30 115 290 655 865 1,040 1,110 1,110 

Hispanic No 3,666 384.9 301.2 5.0 1 1,440 30 120 324 600 822 930 1,060 1,170 

Hispanic Yes 288 336.2 280.9 16.6 1 1,440 20 115 252 512 760 850 1,010 1,260 

Hispanic DK 18 369.8 371.5 87.6 15 1,440 15 90 220 600 760 1,440 1,440 1,440 

Hispanic Refused 33 403.4 322.8 56.2 25 1,110 30 120 325 655 840 1,040 1,110 1,110 

Employment - 624 301.7 295.5 11.8 1 1,440 15 75 190 450 735 900 1,140 1,230 

Employment Full Time 2,042 405.9 296.3 6.6 2 1,440 30 135 365 625 835 925 1,005 1,110 

Employment Part Time 381 378.0 291.1 14.9 5 1,440 30 135 325 585 805 915 1,080 1,245 

Employment Not Employed 935 383.8 308.7 10.1 3 1,440 30 120 310 600 825 930 1,110 1,290 

Employment Refused 23 342.0 254.2 53.0 25 925 30 120 325 450 715 885 925 925 

Education - 704 308.6 292.8 11.0 1 1,440 15 88 205 465 741 900 1,095 1,217 

Education < High School 377 497.7 317.8 16.4 2 1,440 40 225 465 775 905 990 1,120 1,369 

Education High School Graduate 1,315 425.7 301.7 8.3 3 1,440 30 155 390 650 840 928 1,060 1,202 

Education < College 829 388.8 295.8 10.3 5 1,435 30 135 330 600 810 930 1,050 1,155 

Education College Graduate 473 325.9 272.7 12.5 2 1,140 30 90 240 499 735 860 990 1,035 

Education Post Graduate 307 282.5 257.1 14.7 3 1,205 20 60 200 430 665 810 900 983 

Census Region Northeast 932 369.5 287.7 9.4 2 1,440 30 120 314 565 800 892 990 1,095 

Census Region Midwest 938 384.1 304.8 10.0 2 1,440 29 120 320 600 825 930 1,080 1,140 

Census Region South 1,409 404.0 308.5 8.2 1 1,440 30 130 345 630 840 943 1,090 1,205 

Census Region West 726 349.9 292.0 10.8 1 1,440 30 110 274 541 800 900 1,045 1,180 

Day Of Week Weekday 2,661 374.7 296.2 5.7 1 1,440 30 120 315 578 810 915 1,045 1,150 

Day Of Week Weekend 1,344 394.9 308.5 8.4 1 1,440 30 120 322 625 833 940 1,110 1,260 

Season Winter 1,046 374.2 304.2 9.4 1 1,440 25 115 295 590 815 925 1,080 1,170 

Season Spring 1,034 384.8 301.6 9.4 2 1,440 30 120 320 610 810 900 1,105 1,215 

Season Summer 1,059 385.1 300.4 9.2 2 1,440 30 120 330 591 840 940 1,040 1,130 

Season Fall 866 382.0 295.1 10.0 2 1,440 30 120 324 590 810 915 1,030 1,150 

Asthma No 3,687 378.8 298.4 4.9 1 1,440 30 120 315 591 810 915 1,050 1,170 

Asthma Yes 298 416.9 324.0 18.8 5 1,440 20 135 343 652 870 1,015 1,202 1,335 

Asthma DK 20 350.0 304.3 68.0 25 995 28 60 290 540 795 902.5 995 995 

Angina No 3,892 380.9 299.5 4.8 1 1,440 30 120 320 595 815 920 1,060 1,170 

Angina Yes 87 404.3 345.1 37.0 2 1,380 30 120 270 703 910 1,015 1,320 1,380 

Angina DK 26 390.6 300.4 58.9 25 995 30 115 343 670 780 790 995 995 

Bronchitis/Emphysema No 3,749 378.7 298.6 4.9 1 1,440 30 120 315 590 810 915 1,060 1,170 

Bronchitis/Emphysema Yes 236 431.2 326.8 21.3 5 1,380 30 150 363 680 892 980 1,205 1,260 

Bronchitis/Emphysema DK 20 326.3 291.1 65.1 10 995 18 85 223 540 755 888 995 995 

-

DK 

Refused 

= Indicates missing data. 

= The respondent replied “don’t know”. 

= Refused data. 

N 

SD 

= Doer sample size. 

= Standard deviation. 

SE = Standard error. 

Min = Minimum number of minutes. 

Max = Maximum number of minutes. 

Source: U.S. EPA (1996). 
 

Table 16-51. Number of Minutes Spent Smoking and Smoking Cigars or Pipe Tobacco (minutes/day) 

Smoking 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day of Week 

Day of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/emphysema 

Bronchitis/emphysema 

Male 

Female 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

Full Time 

Part Time 

Not Employed 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

Yes 

No 

Yes 

9,386 

4,294 

5,088 

499 

703 

589 

6,059 

1,349 

7,591 

945 

157 

182 

385 

8,534 

702 

4,096 

802 

2,644 

834 

2,612 

1,801 

1,247 

924 

2,075 

2,102 

3,243 

1,966 

6,316 

3,070 

2,524 

2,438 

2,536 

1,888 

8,629 

694 

9,061 

250 

8,882 

433 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

5 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

50 

240 

310 

180 

75 

82 

130 

345 

10 

250 

225 

60 

255 

175 

243 

175 

360 

295 

145 

420 

390 

288 

135 

60 

259 

255 

275 

140 

225 

260 

210 

240 

235 

285 

240 

270 

240 

125 

235 

405 

615 

685 

545 

455 

370 

377 

675 

340 

630 

540 

375 

680 

481 

625 

518 

687 

630 

555 

790 

710 

630 

480 

380 

610 

630 

655 

510 

595 

651 

600 

626 

600 

630 

610 

668 

615 

615 

605 

810 

795 930 1,035 1,440 

840 983 1,095 1,440 

725 870 960 1,440 

735 975 1,095 1,440 

625 975 1,140 1,440 

542 810 864 1,260 

830 950 1,045 1,440 

622 825 910 1,440 

805 940 1,035 1,440 

715 910 1,071 1,440 

494 565 790 800 

815 1,140 1,305 1,328 

652 813 845 1,095 

800 940 1,035 1,440 

680 850 920 1,440 

835 945 1,005 1,440 

793 930 1,054 1,440 

768 915 1,045 1,440 

880 1,004 1,105 1,440 

840 956 1,060 1,440 

805 945 1,045 1,435 

660 860 970 1,140 

595 795 860 1,205 

775 915 990 1,440 

810 945 1,054 1,440 

810 950 1,060 1,440 

710 885 990 1,440 

780 925 1,015 1,440 

810 950 1,080 1,440 

790 930 1,034 1,440 

785 920 1,060 1,440 

810 940 1,020 1,440 

791 945 1,020 1,440 

790 928 1,020 1,440 

855 1,020 1,170 1,440 

795 930 1,034 1,440 

835 1,008 1,125 1,380 

785 928 1,020 1,440 

900 1,040 1,205 1,380 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-138 November 2011 
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-51. Number of Minutes Spent Smoking and Smoking Cigars or Pipe Tobacco (minutes/day) 

(continued) 

Smoking Cigars or Pipe Tobacco 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 57 2 3 3 10 20 60 61 61 61 61 61 

Gender Male 53 3 5 10 10 20 60 61 61 61 61 61 

Gender Female 4 2 2 2 2 3 9 38 61 61 61 61 

Age (years) 5 to 11 1 15 15 15 15 15 15 15 15 15 15 15 

Age (years) 12 to 17 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 18 to 64 43 2 2 3 10 15 45 61 61 61 61 61 

Age (years) > 64 13 15 15 15 20 45 60 61 61 61 61 61 

Race White 50 2 3 3 10 20 60 61 61 61 61 61 

Race Black 4 10 10 10 10 10 15 25 30 30 30 30 

Race Some Others 0 0 0 0 0 0 0 0 0 0 0 0 

Race Hispanic 3 30 30 30 30 30 45 61 61 61 61 61 

Hispanic No 52 2 3 3 10 20 60 61 61 61 61 61 

Hispanic Yes 5 10 10 10 10 30 40 45 61 61 61 61 

Employment Full Time 37 2 2 3 10 20 60 61 61 61 61 61 

Employment Part Time 3 3 3 3 3 3 10 10 10 10 10 10 

Employment Not Employed 16 15 15 15 20 38 60 61 61 61 61 61 

Education < High School 2 45 45 45 45 45 53 61 61 61 61 61 

Education High School Graduate 22 2 2 10 10 15 45 61 61 61 61 61 

Education < College 16 3 3 3 3 25 60 61 61 61 61 61 

Education College Graduate 10 5 5 5 8 20 30 61 61 61 61 61 

Education Post Graduate 6 20 20 20 20 30 53 61 61 61 61 61 

Census Region Northeast 17 10 10 10 20 20 61 61 61 61 61 61 

Census Region Midwest 19 2 2 2 3 15 30 60 61 61 61 61 

Census Region South 11 10 10 10 10 10 45 61 61 61 61 61 

Census Region West 10 10 10 10 10 30 60 61 61 61 61 61 

Day of Week Weekday 37 2 2 3 10 20 60 61 61 61 61 61 

Day of Week Weekend 20 3 3 7 10 20 38 61 61 61 61 61 

Season Winter 16 3 3 3 10 15 25 60 61 61 61 61 

Season Spring 16 2 2 2 5 15 61 61 61 61 61 61 

Season Summer 18 10 10 10 20 30 60 61 61 61 61 61 

Season Fall 7 3 3 3 3 10 60 61 61 61 61 61 

Asthma No 54 2 3 10 10 20 60 61 61 61 61 61 

Asthma Yes 3 3 3 3 3 3 5 60 60 60 60 60 

Angina No 55 2 3 3 10 20 60 61 61 61 61 61 

Angina Yes 2 60 60 60 60 60 61 61 61 61 61 61 

Bronchitis/emphysema No 56 2 3 3 10 20 60 61 61 61 61 61 

Bronchitis/emphysema Yes 1 60 60 60 60 60 60 60 60 60 60 60 

61 

61 

61 

15 

0 

61 

61 

61 

30 

0 

61 

61 

61 

61 

10 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

61 

60 

61 

61 

61 

60 

N = Doer sample size. 

Note: Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-139 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

 

 

 

 

 

Table 16-52. Number of Minutes Spent (at home) Working or Being Near Food While Fried, Grilled, or
 

Barbequed (minutes/day)
 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 1,055 0 1 2 5 10 20 30 105 121 121 121 121 

Gender Male 485 0 1 2 5 10 20 30 90 121 121 121 121 

Gender Female 570 0 0 2 5 10 20 30 120 121 121 121 121 

Age (years) 1 to 4 35 0 0 2 2 5 20 30 45 60 60 60 60 

Age (years) 5 to 11 82 0 0 0 2 5 15 30 60 90 121 121 121 

Age (years) 12 to 17 82 0 0 2 4 10 20 45 60 90 121 121 121 

Age (years) 18 to 64 747 0 2 3 5 10 20 40 120 121 121 121 121 

Age (years) > 64 96 0 1 3 5 10 20 30 60 120 121 121 121 

Race White 848 0 1 2 5 10 20 30 105 121 121 121 121 

Race Black 115 2 2 5 5 10 20 30 61 121 121 121 121 

Race Asian 18 0 0 0 0 5 10 20 121 121 121 121 121 

Race Some Others 16 5 5 5 5 13 20 45 121 121 121 121 121 

Race Hispanic 48 0 0 5 5 15 30 60 90 121 121 121 121 

Hispanic No 960 0 1 2 5 10 20 30 90 121 121 121 121 

Hispanic Yes 84 0 1 2 5 10 20 60 121 121 121 121 121 

Employment Full Time 506 1 2 3 5 10 20 45 121 121 121 121 121 

Employment Part Time 95 0 1 2 5 10 15 40 90 121 121 121 121 

Employment Not Employed 252 0 1 3 5 10 20 30 90 121 121 121 121 

Education < High School 96 0 1 2 5 10 23 53 121 121 121 121 121 

Education High School Graduate 318 0 2 5 5 10 20 30 120 121 121 121 121 

Education < College 208 0 2 3 5 10 20 35 121 121 121 121 121 

Education College Graduate 135 1 1 2 5 10 20 30 90 121 121 121 121 

Education Post Graduate 83 0 2 5 5 10 15 30 60 121 121 121 121 

Census Region Northeast 198 0 2 3 5 10 15 30 90 121 121 121 121 

Census Region Midwest 248 0 0 4 5 10 20 30 121 121 121 121 121 

Census Region South 399 0 1 2 5 10 20 40 90 121 121 121 121 

Census Region West 210 0 0 2 5 7 15 30 60 121 121 121 121 

Day of Week Weekday 662 0 1 3 5 10 20 30 90 121 121 121 121 

Day of Week Weekend 393 0 1 2 5 10 20 30 120 121 121 121 121 

Season Winter 267 0 2 2 5 10 20 30 60 121 121 121 121 

Season Spring 296 0 0 3 5 10 20 45 120 121 121 121 121 

Season Summer 299 0 0 3 5 10 20 30 90 121 121 121 121 

Season Fall 193 0 0 2 5 10 20 30 121 121 121 121 121 

Asthma No 960 0 1 3 5 10 20 30 90 121 121 121 121 

Asthma Yes 92 0 0 2 5 15 30 60 121 121 121 121 121 

Angina No 1,032 0 1 2 5 10 20 30 95 121 121 121 121 

Angina Yes 19 0 0 0 5 15 30 30 121 121 121 121 121 

Bronchitis/Emphysema No 1,005 0 1 2 5 10 20 30 90 121 121 121 121 

Bronchitis/Emphysema Yes 47 0 0 3 5 10 30 60 121 121 121 121 121 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers below
 

or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-140 November 2011 
 

 

 

Table 16-53. Number of Minutes Spent (at home) Working or Being Near Open Flames Including Barbeque
 

Flames (minutes/day)
 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 479 0 0 1 2 10 20 60 121 121 121 121 121 

Gender Male 252 0 0 1 2 10 20 60 121 121 121 121 121 

Gender Female 227 0 0 2 2 10 20 30 121 121 121 121 121 

Age (years) 1 to 4 14 0 0 0 0 5 10 30 121 121 121 121 121 

Age (years) 5 to 11 29 0 0 0 0 5 15 30 90 121 121 121 121 

Age (years) 12 to 17 28 0 0 1 2 10 23 43 60 60 90 90 90 

Age (years) 18 to 64 372 0 0 1 3 10 20 60 121 121 121 121 121 

Age (years) > 64 31 2 2 2 4 5 17 30 120 121 121 121 121 

Race White 407 0 0 1 2 10 20 45 121 121 121 121 121 

Race Black 31 0 0 0 2 5 20 30 60 121 121 121 121 

Race Asian 5 5 5 5 5 20 40 121 121 121 121 121 121 

Race Some Others 8 10 10 10 10 11 23 60 121 121 121 121 121 

Race Hispanic 22 2 2 3 5 5 30 60 120 121 121 121 121 

Hispanic No 436 0 0 1 2 10 20 43 121 121 121 121 121 

Hispanic Yes 36 2 2 3 5 11 60 90 121 121 121 121 121 

Employment Full Time 262 0 0 1 2 10 20 60 121 121 121 121 121 

Employment Part Time 44 0 0 1 4 5 15 53 121 121 121 121 121 

Employment Not Employed 99 0 1 2 3 10 20 40 120 121 121 121 121 

Education < High School 27 2 2 2 3 5 20 60 121 121 121 121 121 

Education High School Graduate 130 0 0 2 3 10 20 60 121 121 121 121 121 

Education < College 92 0 0 1 2 10 30 90 121 121 121 121 121 

Education College Graduate 95 0 1 2 5 10 20 40 121 121 121 121 121 

Education Post Graduate 55 0 0 0 2 10 20 40 121 121 121 121 121 

Census Region Northeast 124 0 0 1 3 10 15 30 121 121 121 121 121 

Census Region Midwest 112 0 0 2 3 10 20 45 121 121 121 121 121 

Census Region South 149 0 0 1 2 5 20 60 121 121 121 121 121 

Census Region West 94 0 0 1 2 10 20 60 121 121 121 121 121 

Day of Week Weekday 284 0 0 1 3 10 15 30 121 121 121 121 121 

Day of Week Weekend 195 0 0 1 2 10 30 60 121 121 121 121 121 

Season Winter 142 0 0 0 2 10 20 60 121 121 121 121 121 

Season Spring 115 0 1 2 3 10 20 60 120 121 121 121 121 

Season Summer 137 0 0 2 3 10 20 45 121 121 121 121 121 

Season Fall 85 1 1 1 3 10 20 40 121 121 121 121 121 

Asthma No 443 0 0 1 2 10 20 45 121 121 121 121 121 

Asthma Yes 35 0 0 3 3 15 30 120 121 121 121 121 121 

Angina No 461 0 0 1 2 10 20 45 121 121 121 121 121 

Angina Yes 15 2 2 2 2 10 15 60 121 121 121 121 121 

Bronchitis/Emphysema No 461 0 0 1 2 10 20 45 121 121 121 121 121 

Bronchitis/Emphysema Yes 16 3 3 3 5 13 38 106 121 121 121 121 121 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers
 

below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-141 
 

 

 

 

Table 16-54. Number of Minutes Spent Running, Walking, or Standing Alongside a Road With Heavy Traffic 

(minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 401 0 1 2 2 5 15 30 60 121 121 121 121
 

Gender Male 202 1 1 2 3 5 18 45 120 121 121 121 121
 

Gender Female 198 0 0 1 2 5 10 30 60 120 121 121 121
 

Age (years) 1 to 4 12 1 1 1 2 4 8 30 60 60 60 60 60
 

Age (years) 5 to 11 20 1 1 2 2 5 6 13 25 60 90 90 90
 

Age (years) 12 to 17 27 0 0 2 2 4 5 30 60 90 120 120 120
 

Age (years) 18 to 64 304 0 1 1 2 5 15 30 90 121 121 121 121
 

Age (years) > 64 31 2 2 2 4 5 20 45 60 121 121 121 121
 

Race White 306 0 1 2 2 5 15 30 110 121 121 121 121
 

Race Black 51 0 0 1 1 3 7 30 50 60 60 121 121
 

Race Asian 10 3 3 3 4 5 8 15 18 20 20 20 20
 

Race Some Others 7 2 2 2 2 5 10 45 121 121 121 121 121
 

Race Hispanic 24 2 2 2 3 10 18 40 60 60 120 120 120
 

Hispanic No 356 0 1 1 2 5 15 30 90 121 121 121 121
 

Hispanic Yes 43 1 1 2 2 5 10 30 60 120 121 121 121
 

Employment Full Time 214 0 1 1 2 5 15 30 120 121 121 121 121
 

Employment Part Time 50 0 1 2 2 5 15 30 90 121 121 121 121
 

Employment Not Employed 76 0 1 2 3 6 15 30 60 110 120 121 121
 

Education < High School 18 4 4 4 5 6 10 15 30 121 121 121 121
 

Education High School Graduate 106 1 1 2 2 5 15 60 121 121 121 121 121
 

Education < College 84 0 0 1 3 6 20 40 120 121 121 121 121
 

Education College Graduate 79 0 1 1 2 5 15 30 60 90 121 121 121
 

Education Post Graduate 50 1 1 2 2 5 10 20 53 90 120 120 120
 

Census Region Northeast 129 1 1 2 2 5 20 50 120 121 121 121 121
 

Census Region Midwest 83 0 0 1 2 5 10 20 60 121 121 121 121
 

Census Region South 105 0 0 1 2 5 15 30 90 121 121 121 121
 

Census Region West 84 1 2 2 3 5 15 30 60 120 121 121 121
 

Day of Week Weekday 303 0 0 2 2 5 15 30 60 120 121 121 121
 

Day of Week Weekend 98 1 1 2 3 5 15 30 121 121 121 121 121
 

Season Winter 104 0 0 1 2 5 10 20 60 110 121 121 121
 

Season Spring 114 1 1 2 2 6 20 60 120 121 121 121 121
 

Season Summer 104 0 1 2 2 5 10 30 60 121 121 121 121
 

Season Fall 79 0 1 2 3 5 20 35 120 121 121 121 121
 

Asthma No 370 0 1 2 2 5 15 30 60 121 121 121 121
 

Asthma Yes 31 0 0 1 2 5 15 30 120 121 121 121 121
 

Angina No 393 0 1 2 2 5 15 30 90 121 121 121 121
 

Angina Yes 8 2 2 2 2 7 18 30 60 60 60 60 60
 

Bronchitis/Emphysema No 378 0 1 1 2 5 15 30 60 121 121 121 121
 

Bronchitis/Emphysema Yes 22 2 2 5 5 5 18 30 121 121 121 121 121
 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers
 

below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-142 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

Table 16-55. Number of Minutes Spent in a Car, Van, Truck, or Bus in Heavy Traffic (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 1,197 1 2 5 5 10 20 60 120 121 121 121 121
 

Gender Male 534 1 2 4 5 10 20 60 120 121 121 121 121
 

Gender Female 663 1 2 5 5 10 25 60 120 121 121 121 121
 

Age (years) 1 to 4 33 4 4 5 5 10 15 30 60 60 121 121 121
 

Age (years) 5 to 11 63 1 2 5 5 10 20 45 60 120 121 121 121
 

Age (years) 12 to 17 52 3 3 4 5 9 13 28 90 120 120 121 121
 

Age (years) 18 to 64 889 1 2 5 5 10 25 60 120 121 121 121 121
 

Age (years) > 64 139 3 3 5 5 15 30 60 121 121 121 121 121
 

Race White 959 1 2 4 5 10 25 60 120 121 121 121 121
 

Race Black 133 2 3 5 5 10 20 40 90 120 121 121 121
 

Race Asian 20 5 5 5 5 11 20 30 45 53 60 60 60
 

Race Some Others 24 5 5 10 10 13 30 60 90 120 121 121 121
 

Race Hispanic 55 1 2 5 5 10 20 60 120 121 121 121 121
 

Hispanic No 1,097 1 2 5 5 10 20 60 120 121 121 121 121
 

Hispanic Yes 95 1 2 5 5 10 20 90 121 121 121 121 121
 

Employment Full Time 659 1 2 5 5 10 30 60 120 121 121 121 121
 

Employment Part Time 108 2 2 4 5 10 20 49 121 121 121 121 121
 

Employment Not Employed 279 1 2 5 5 10 30 60 120 121 121 121 121
 

Education < High School 81 0 3 5 10 10 20 40 121 121 121 121 121
 

Education High School Graduate 352 1 2 5 5 10 30 60 120 121 121 121 121
 

Education < College 276 1 2 3 5 15 30 60 120 121 121 121 121
 

Education College Graduate 176 1 2 4 5 13 30 60 120 121 121 121 121
 

Education Post Graduate 150 2 2 5 5 10 20 60 98 120 121 121 121
 

Census Region Northeast 229 2 2 4 5 10 20 60 120 121 121 121 121
 

Census Region Midwest 263 2 2 5 5 10 30 45 120 121 121 121 121
 

Census Region South 429 1 2 5 5 10 30 60 120 121 121 121 121
 

Census Region West 276 1 2 5 5 10 20 60 120 121 121 121 121
 

Day of Week Weekday 927 1 2 5 5 10 20 60 120 121 121 121 121
 

Day of Week Weekend 270 2 2 5 5 10 25 60 120 121 121 121 121
 

Season Winter 286 1 2 5 5 10 20 60 120 121 121 121 121
 

Season Spring 317 1 2 5 5 10 30 60 120 121 121 121 121
 

Season Summer 312 1 3 5 5 10 30 60 120 121 121 121 121
 

Season Fall 282 2 2 4 5 10 20 45 120 121 121 121 121
 

Asthma No 1,108 1 2 5 5 10 20 60 120 121 121 121 121
 

Asthma Yes 89 2 2 5 5 10 30 60 121 121 121 121 121
 

Angina No 1,159 1 2 5 5 10 20 60 120 121 121 121 121
 

Angina Yes 35 0 0 5 5 10 30 70 121 121 121 121 121
 

Bronchitis/emphysema No 1,130 2 2 5 5 10 20 60 120 121 121 121 121
 

Bronchitis/emphysema Yes 64 1 1 2 5 10 28 51 120 121 121 121 121
 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers
 

below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-143 
 

 

 

 

Table 16-56. Number of Minutes Spent in a Parking Garage or Indoor Parking Lot (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 294 0 1 1 2 3 5 10 30 60 121 121 121 

Gender Male 138 1 1 1 2 4 5 15 60 121 121 121 121 

Gender Female 156 0 1 1 2 3 5 10 20 40 60 120 121 

Age (years) 1 to 4 8 0 0 0 0 2 4 5 10 10 10 10 10 

Age (years) 5 to 11 15 1 1 1 2 3 5 10 45 60 60 60 60 

Age (years) 12 to 17 20 0 0 1 2 2 8 15 45 91 121 121 121 

Age (years) 18 to 64 229 1 1 2 2 5 5 10 30 60 121 121 121 

Age (years) > 64 18 0 0 0 2 3 5 15 45 90 90 90 90 

Race White 208 1 1 2 2 3 5 10 30 60 121 121 121 

Race Black 34 0 0 1 1 5 5 15 20 30 30 30 30 

Race Asian 15 2 2 2 2 2 10 60 120 121 121 121 121 

Race Some Others 7 3 3 3 3 3 5 15 121 121 121 121 121 

Race Hispanic 28 1 1 1 2 5 10 20 60 120 121 121 121 

Hispanic No 251 0 1 1 2 3 5 10 30 60 120 121 121 

Hispanic Yes 39 1 1 1 3 5 10 30 121 121 121 121 121 

Employment Full Time 171 1 1 1 2 3 5 10 30 60 121 121 121 

Employment Part Time 23 2 2 5 5 5 5 10 30 60 121 121 121 

Employment Not Employed 58 0 1 1 2 4 10 20 40 120 121 121 121 

Education < High School 13 0 0 0 5 5 10 10 30 121 121 121 121 

Education High School Graduate 58 1 1 1 2 3 10 30 90 121 121 121 121 

Education < College 54 1 1 2 2 4 5 15 40 120 120 121 121 

Education College Graduate 72 1 1 2 2 5 5 10 15 60 120 121 121 

Education Post Graduate 50 1 1 2 2 5 5 10 13 20 40 60 60 

Census Region Northeast 53 2 2 2 2 5 6 10 30 90 121 121 121 

Census Region Midwest 59 0 0 1 2 3 5 10 30 60 121 121 121 

Census Region South 92 1 1 2 2 4 5 10 30 60 121 121 121 

Census Region West 90 0 1 1 2 4 5 15 45 60 121 121 121 

Day of Week Weekday 208 0 1 1 2 3 5 10 30 60 121 121 121 

Day of Week Weekend 86 1 1 2 2 5 7 15 30 60 121 121 121 

Season Winter 67 0 1 1 2 3 5 10 20 30 120 121 121 

Season Spring 78 0 1 1 2 3 6 15 60 120 121 121 121 

Season Summer 85 0 1 2 2 5 5 15 30 90 121 121 121 

Season Fall 64 1 1 2 2 5 5 10 30 45 121 121 121 

Asthma No 263 1 1 2 2 3 5 10 30 60 121 121 121 

Asthma Yes 30 0 0 1 1 4 7 10 30 121 121 121 121 

Angina No 291 0 1 1 2 4 5 10 30 60 121 121 121 

Angina Yes 2 3 3 3 3 3 47 90 90 90 90 90 90 

Bronchitis/emphysema No 281 0 1 1 2 3 5 10 30 60 121 121 121 

Bronchitis/emphysema Yes 12 2 2 2 5 5 6 10 60 120 120 120 120 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers
 

below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-144 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

Table 16-57. Number of Minutes Spent Walking Outside to a Car in the Driveway or Outside Parking Areas 

(minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 3,303 0 0 0 0 2 5 10 20 30 60 121 121
 

Gender Male 1,511 0 0 0 0 2 4 10 20 30 60 121 121
 

Gender Female 1,791 0 0 0 0 2 5 10 20 30 60 60 121
 

Age (years) 1 to 4 132 0 0 0 0 2 2 5 15 20 30 60 121
 

Age (years) 5 to 11 245 0 0 0 0 1 2 5 15 30 45 80 121
 

Age (years) 12 to 17 202 0 0 0 0 1 5 10 20 30 30 60 121
 

Age (years) 18 to 64 2,303 0 0 0 0 2 5 10 20 30 60 120 121
 

Age (years) > 64 373 0 0 0 1 2 5 10 15 30 30 88 121
 

Race White 2,756 0 0 0 0 2 5 10 20 30 60 120 121
 

Race Black 279 0 0 0 0 1 3 5 10 20 30 45 88
 

Race Asian 53 0 0 0 0 1 3 10 15 30 32 45 45
 

Race Some Others 63 0 0 0 0 2 5 10 30 30 60 120 120
 

Race Hispanic 127 0 0 1 1 2 5 10 20 60 120 121 121
 

Hispanic No 3,029 0 0 0 0 2 5 10 20 30 60 120 121
 

Hispanic Yes 235 0 0 0 0 2 5 10 20 60 120 121 121
 

Employment Full Time 1,613 0 0 0 0 2 5 10 20 30 60 120 121
 

Employment Part Time 312 0 0 0 1 2 5 10 20 45 120 121 121
 

Employment Not Employed 785 0 0 0 0 2 5 10 20 30 60 60 121
 

Education < High School 241 0 0 0 0 2 4 10 20 30 110 121 121
 

Education High School Graduate 935 0 0 0 0 2 5 10 20 30 60 121 121
 

Education < College 680 0 0 0 1 2 5 10 20 30 60 120 121
 

Education College Graduate 445 0 0 0 0 2 5 10 20 30 60 60 121
 

Education Post Graduate 381 0 0 0 1 2 5 10 15 25 30 120 121
 

Census Region Northeast 680 0 0 0 0 2 5 10 15 30 60 90 121
 

Census Region Midwest 763 0 0 0 1 2 5 10 15 30 60 120 121
 

Census Region South 1,149 0 0 0 0 2 4 10 20 30 60 90 121
 

Census Region West 711 0 0 0 0 2 5 10 20 30 60 120 121
 

Day of Week Weekday 2,209 0 0 0 0 2 5 10 20 30 60 120 121
 

Day of Week Weekend 1,094 0 0 0 0 2 5 10 20 30 60 120 121
 

Season Winter 855 0 0 0 0 1 4 10 15 30 30 100 121
 

Season Spring 890 0 0 0 0 2 5 10 20 30 100 120 121
 

Season Summer 903 0 0 0 0 2 4 10 20 30 60 60 121
 

Season Fall 655 0 0 0 1 2 5 10 15 30 45 110 121
 

Asthma No 3,063 0 0 0 0 2 5 10 20 30 60 120 121
 

Asthma Yes 234 0 0 0 1 2 5 10 15 30 120 121 121
 

Angina No 3,219 0 0 0 0 2 5 10 20 30 60 120 121
 

Angina Yes 72 0 0 0 0 2 5 10 15 30 45 110 110
 

Bronchitis/Emphysema No 3,132 0 0 0 0 2 5 10 20 30 60 120 121
 

Bronchitis/Emphysema Yes 162 0 0 0 0 2 5 10 20 30 110 121 121
 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers
 

below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-145 
 

 

 

 

 

Table 16-58. Number of Minutes Spent Running or Walking Outside Other Than to the Car (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 1,273 1 1 3 5 15 45 120 121 121 121 121 121
 

Gender Male 605 2 2 5 10 20 60 121 121 121 121 121 121
 

Gender Female 668 0 1 2 5 15 30 116 121 121 121 121 121
 

Age (years) 1 to 4 82 3 3 5 10 30 120 121 121 121 121 121 21
 

Age (years) 5 to 11 149 4 5 5 10 30 120 121 121 121 121 121 21
 

Age (years) 12 to 17 110 5 5 5 10 15 60 121 121 121 121 121 121
 

Age (years) 18 to 64 772 0 1 2 5 15 30 120 121 121 121 121 121
 

Age (years) > 64 143 1 1 2 5 15 30 60 121 121 121 121 121
 

Race White 1,051 1 1 3 5 15 45 121 121 121 121 121 121
 

Race Black 111 0 1 3 5 15 35 120 121 121 121 121 121
 

Race Asian 21 2 2 10 10 15 30 70 120 121 121 121 121
 

Race Some Others 23 5 5 10 15 20 60 121 121 121 121 121 121
 

Race 5:hispanic 55 2 3 8 10 20 40 90 121 121 121 121 121
 

Hispanic No 1,156 1 1 3 5 15 45 120 121 121 121 121 121
 

Hispanic Yes 99 1 2 2 10 20 60 121 121 121 121 121 121
 

Employment Full Time 517 0 1 2 5 15 30 120 121 121 121 121 121
 

Employment Part Time 112 1 2 2 5 15 30 90 121 121 121 121 121
 

Employment Not Employed 300 1 1 3 5 15 30 120 121 121 121 121 121
 

Education < High School 97 0 1 3 5 15 30 90 121 121 121 121 121
 

Education High School Graduate 287 0 0 2 5 15 30 120 121 121 121 121 121
 

Education < College 234 1 1 2 5 15 30 120 121 121 121 121 121
 

Education College Graduate 153 1 2 5 10 20 45 120 121 121 121 121 121
 

Education Post Graduate 138 1 1 3 5 15 38 90 121 121 121 121 121
 

Census Region Northeast 265 1 1 3 5 20 45 120 121 121 121 121 121
 

Census Region Midwest 286 1 2 5 5 15 40 121 121 121 121 121 121
 

Census Region South 412 1 1 3 5 15 45 121 121 121 121 121 121
 

Census Region West 310 1 1 3 6 15 45 120 121 121 121 121 121
 

Day of Week Weekday 843 1 1 3 5 15 40 120 121 121 121 121 121
 

Day of Week Weekend 430 1 2 4 5 20 60 121 121 121 121 121 21
 

Season Winter 312 0 2 2 5 10 43 90 121 121 121 121 21
 

Season Spring 403 1 2 4 10 20 60 121 121 121 121 121 121
 

Season Summer 396 1 1 3 10 20 55 121 121 121 121 121 21
 

Season Fall 162 1 1 2 5 15 30 120 121 121 121 121 121
 

Asthma No 1,162 1 1 3 5 15 45 120 121 121 121 121 21
 

Asthma Yes 105 2 4 5 6 15 45 121 121 121 121 121 21
 

Angina No 1,240 1 1 3 5 15 45 120 121 121 121 121 121
 

Angina Yes 25 1 1 5 5 15 45 121 121 121 121 121 121
 

Bronchitis/Emphysema No 1,204 1 1 3 5 15 45 120 121 121 121 121 121
 

Bronchitis/Emphysema Yes 62 1 2 4 5 15 30 120 121 121 121 121 121
 

N = Doer sample size.
 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. Percentiles are the percentage of doers
 

below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-146 November 2011 
Exposure Factors Handbook Page 

November 2011 16-147 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-59. Number of Times Washing Dishes by Hand at Specified Frequencies by the Number of 

Respondents 

Number of Times/Week 

N - Almost Every Day 3-5/Week 1-2/Week <1-2/Week DK 

All 3,626 1 2,600 490 326 197 12 

Gender 

Male 1,554 - 982 264 183 117 8 

Female 2,071 1 1,618 225 143 80 4 

Refused 1 - - 1 - - -

Age (years) 

- 65 - 51 6 2 6 -

1 to 4 1 - - - 1 - -

5 to 11 103 - 12 14 33 44 -

12 to 17 228 - 57 45 69 56 1 

18 to 64 2,642 1 1,979 379 201 76 6 

> 64 587 - 501 46 20 15 5 

Race 

White 2,928 1 2,114 391 257 157 8 

Black 385 - 261 61 40 21 2 

Asian 61 - 48 6 3 4 -

Some Others 67 - 44 9 9 5 -

Hispanic 147 - 108 17 12 8 2 

Refused 38 - 25 6 5 2 -

Hispanic 

No 3,322 1 2,383 454 296 178 10 

Yes 258 - 185 32 25 14 2 

DK 21 - 16 - 3 2 -

Refused 25 - 16 4 2 3 -

Employment 

- 328 - 71 57 102 97 1 

Full Time 1,765 - 1,282 284 145 50 4 

Part Time 349 - 270 44 17 15 3 

Not Employed 1,165 1 965 104 60 31 4 

Refused 19 - 12 1 2 4 -

Education 

- 386 - 101 65 107 112 1 

< High School 354 - 298 26 15 12 3 

High School Graduate 1,106 1 856 140 74 30 5 

< College 796 - 606 116 57 16 1 

College Graduate 591 - 445 86 47 13 -

Post Graduate 393 - 294 57 26 14 2 

Census Region 

Northeast 832 - 636 90 60 43 3 

Midwest 811 - 569 114 81 45 2 

South 1,214 1 840 175 124 70 4 

West 769 - 555 111 61 39 3 

Day of Week 

Weekday 2,474 - 1,759 335 236 136 8 

Weekend 1,152 1 841 155 90 61 4 

Season 

Winter 985 - 691 138 90 63 3 

Spring 902 1 648 117 85 46 5 

Summer 987 - 705 132 92 55 3 

Fall 752 - 556 103 59 33 1 

Asthma 

No 3,345 1 2,407 455 290 183 9 

Yes 263 - 179 33 34 14 3 

DK 18 - 14 2 2 - -

Angina 

No 3,501 - 2,499 475 321 194 12 

Yes 105 1 86 11 5 2 -

DK 20 - 15 4 - 1 -

Bronchitis/Emphysema 

No 3438 1 2,459 460 314 192 12 

Yes 1,69 - 126 27 11 5 -

DK 19 - 15 3 1 - -
 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-148 November 2011 

Table 16-59. Number of Times Washing Dishes by Hand at Specified Frequencies by the Number of 

Respondents (continued) - = Indicates missing data. 

DK = The respondent replied “don't know”. 

Refused = Refused data. 

N = Sample size. 

Source: U.S. EPA (1996). 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-60. Number of Times Using a Dishwasher at Specified Frequencies by the Number of Respondents 

Number of Times/Week 

Total N - Almost Every Day 3-5/Week 1-2/Week <1-2/Week DK 

All 2,635 1 557 678 529 824 46 

Gender 

Male 1,235 - 259 282 247 417 30 

Female 1,399 1 298 396 282 406 16 

Refused 1 - - - - 1 ­

Age (years) 

- 35 - 4 13 11 6 1 

1 to 4 145 - 9 4 3 118 11 

5 to 11 211 - 14 8 15 157 17 

12 to 17 206 - 27 33 31 113 2 

18 to 64 1,718 - 438 512 397 360 11 

> 64 320 1 65 108 72 70 4 

Race 

White 2,267 1 504 603 487 637 35 

Black 163 - 19 32 19 90 3 

Asian 54 - 7 8 7 31 1 

Some Others 45 - 9 8 1 24 3 

Hispanic 84 - 13 15 12 40 4 

Refused 22 - 5 12 3 2 ­

Hispanic 

No 2,444 1 524 635 504 739 41 

Yes 164 - 27 32 21 79 5 

DK 11 - 2 2 2 5 ­

Refused 16 - 4 9 2 1 ­

Employment 

- 552 - 49 45 46 382 30 

Full Time 1,191 - 276 359 298 249 9 

Part Time 204 - 48 70 46 38 2 

Not Employed 678 1 181 200 136 155 5 

Refused 10 - 3 4 3 - ­

Education 

- 593 - 55 51 55 400 32 

< High School 124 1 29 27 26 41 ­

High School Graduate 582 - 153 173 114 132 10 

< College 560 - 144 181 117 117 1 

College Graduate 446 - 105 134 126 80 1 

Post Graduate 330 - 71 112 91 54 2 

Census Region 

Northeast 538 - 133 144 95 159 7 

Midwest 514 - 116 130 110 152 6 

South 953 - 200 251 169 312 21 

West 630 1 108 153 155 201 12 

Day of Week 

Weekday 1,768 1 378 466 341 549 33 

Weekend 867 - 179 212 188 275 13 

Season 

Winter 711 - 144 175 149 223 20 

Spring 664 1 122 181 132 214 14 

Summer 721 - 157 185 134 239 6 

Fall 539 - 134 137 114 148 6 

Asthma 

No 2,439 1 521 622 492 765 38 

Yes 189 - 35 54 35 58 7 

DK 7 - 1 2 2 1 1 

Angina 

No 2,570 1 538 664 512 809 46 

Yes 60 - 19 11 16 14 ­

DK 5 - - 3 1 1 ­

Bronchitis/Emphysema 

No 2,533 1 540 646 504 796 46 

Yes 93 - 16 27 23 27 ­

DK 9 - 1 5 2 1 ­

- = Indicates missing data. 

DK = The respondent replied “don't know”. 

Refused = Refused data. 

N = Sample size. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-149 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-150 November 2011 

Table 16-61. Number of Times for Washing Clothes in a Washing Machine at Specified Frequencies by the 

Number of Respondents 

Number of Times/Week 

Total N - Almost Every Day 3-5 /Day 1-2/week <1/week Never DK 

All 4,663 404 566 1,033 1,827 331 465 37 

Gender 

Male 2,163 212 211 458 811 154 300 17 

Female 2,498 191 355 575 1,015 177 165 20 

Refused 2 1 - - 1 - - -

Age (years) 

- 84 3 6 11 47 3 2 12 

1 to 4 263 261 - - - - 1 1 

5 to 11 348 101 2 4 16 15 206 4 

12 to 17 326 1 22 29 83 67 124 -

18 to 64 2,972 31 489 832 1,328 197 83 12 

> 64 670 7 47 157 353 49 49 8 

Race 

White 3,774 316 499 883 1,445 246 370 15 

Black 463 39 33 72 207 52 55 5 

Asian 77 4 1 12 39 13 8 -

Some Others 96 16 10 15 36 8 11 -

Hispanic 193 29 19 41 77 10 17 -

Refused 60 - 4 10 23 2 4 17 

Hispanic 

No 4,244 342 528 950 1,674 307 424 19 

Yes 347 59 31 69 130 20 38 -

DK 26 2 3 6 10 3 2 -

Refused 46 1 4 8 13 1 1 18 

Employment 

- 926 366 23 32 97 76 327 5 

Full Time 2,017 21 305 569 929 119 66 8 

Part Time 379 6 64 101 166 29 13 -

Not Employed 1,309 10 170 326 628 105 58 12 

Refused 32 1 4 5 7 2 1 12 

Education 

- 1,021 367 33 37 129 89 343 23 

< High School 399 3 61 88 178 40 27 2 

High School Graduate 1,253 14 218 367 548 55 47 4 

< College 895 3 126 261 432 51 19 3 

College Graduate 650 12 78 171 321 57 9 2 

Post Graduate 445 5 50 109 219 39 20 3 

Census Region 

Northeast 1,048 84 119 216 454 81 87 7 

Midwest 1,036 88 108 229 408 78 121 4 

South 1,601 147 229 376 557 97 182 13 

West 978 85 110 212 408 75 75 13 

Day of Week 

Weekday 3,156 257 407 697 1,217 232 320 26 

Weekend 1,507 147 159 336 610 99 145 11 

Season 

Winter 1,264 121 157 273 472 101 129 11 

Spring 1,181 122 135 259 464 82 113 6 

Summer 1,275 102 163 280 484 88 142 16 

Fall 943 59 111 221 407 60 81 4 

Asthma 

No 4,287 371 522 951 1,700 303 421 19 

Yes 341 32 42 79 118 26 43 1 

DK 35 1 2 3 9 2 1 17 

Angina 

No 4,500 403 555 993 1,759 321 451 18 

Yes 125 - 8 37 58 7 13 2 

DK 38 1 3 3 10 3 1 17 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-61. Number of Times for Washing Clothes in a Washing Machine at Specified Frequencies by the 

Number of Respondents (continued) 

Number of Times/Week 

Total N - Almost Every Day 3-5 /Day 1-2/week <1/week Never DK 

Bronchitis/emphysema 

No 

Yes 

DK 

-

DK 

Refused 

N 

4,424 

203 

36 

= Indicates missing data. 

= The respondent replied “don't know”. 

= Refused data. 

= Sample size. 

397 

7 

-

549 

15 

2 

979 

51 

3 

1,724 

92 

11 

315 

14 

2 

441 

23 

1 

19 

1 

17 

Source: U.S. EPA (1996). 

Exposure Factors Handbook Page
 

November 2011 16-151 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-152 November 2011 

Table 16-62. Number of Loads of Laundry Washed in a Washing Machine at Home by the Number of 

Respondents 

Number of Loads/Day 

N 1 2 3 4 5 6 7 8 9 10 >10 DK 

All 1,762 582 604 303 123 55 27 11 12 1 5 1 38 

Gender 

Male 678 219 241 120 41 17 8 - - 1 1 - 30 

Female 1,083 363 363 183 82 38 19 10 12 - 4 1 8 

Refused 1 - - - - - - 1 - - - - -

Age (years) 

- 30 9 14 2 3 1 - - - - - - 1 

1 to 4 109 29 36 24 12 5 2 - - - 1 - -

5 to 11 141 38 55 28 8 6 2 1 - 1 1 - 1 

12 to 17 127 39 52 22 10 1 1 - 1 - - - 1 

18 to 64 1,161 385 376 209 80 35 22 9 11 - 3 1 30 

> 64 194 82 71 18 10 7 - 1 - - - - 5 

Race 

White 1,511 513 519 254 101 48 23 11 12 1 3 - 26 

Black 112 27 41 23 11 4 1 - - - 1 - 4 

Asian 22 7 4 3 5 - - - - - - - 3 

Some Others 31 8 12 5 1 1 1 - - - - - 3 

Hispanic 68 18 24 15 5 2 2 - - - 1 - 1 

Refused 18 9 4 3 - - - - - - - 1 1 

Hispanic 

No 1,615 536 556 271 115 50 24 11 12 1 4 - 35 

Yes 126 38 42 26 8 5 3 - - - 1 - 3 

DK 6 - 2 4 - - - - - - - - -

Refused 15 8 4 2 - - - - - - - 1 -

Employment 

- 369 102 143 71 29 12 5 1 1 1 2 - 2 

Full Time 734 259 244 128 42 20 10 5 4 - 2 - 20 

Part Time 160 58 53 23 10 8 3 - 1 - - - 4 

Not Employed 482 158 158 79 41 15 8 5 6 - 1 1 10 

Refused 17 5 6 2 1 - 1 - - - - - 2 

Education 

- 413 118 160 77 32 12 6 1 1 1 2 - 3 

< High School 133 44 44 22 10 4 3 2 - - - - 4 

High School Graduate 508 175 166 85 35 18 8 3 4 - - - 14 

< College 321 105 101 61 25 9 3 2 5 - 2 1 7 

College Graduate 212 83 68 32 11 8 4 - 1 - - - 5 

Post Graduate 175 57 65 26 10 4 3 3 1 - 1 - 5 

Census Region 

Northeast 367 111 146 57 23 13 7 2 1 - - - 7 

Midwest 406 125 123 76 42 14 5 3 6 1 - 1 10 

South 628 205 228 110 39 17 6 6 4 - 3 - 10 

West 361 141 107 60 19 11 9 - 1 - 2 - 11 

Day of Week 

Weekday 1,172 418 409 194 62 29 17 7 7 1 1 1 26 

Weekend 590 164 195 109 61 26 10 4 5 - 4 - 12 

Season 

Winter 458 154 159 73 31 14 6 3 4 1 3 1 9 

Spring 465 154 159 87 28 10 10 3 2 - 1 - 11 

Summer 482 158 166 85 38 11 8 4 3 - 1 - 8 

Fall 357 116 120 58 26 20 3 1 3 - - - 10 

Asthma 

No 1615 548 545 274 105 50 27 11 12 1 5 1 36 

Yes 140 31 56 28 18 5 - - - - - - 2 

DK 7 3 3 1 - - - - - - - - -

Angina 

No 1,710 564 592 294 113 54 26 11 12 1 5 1 37 

Yes 40 14 9 7 8 1 1 - - - - - -

DK 12 4 3 2 2 - - - - - - - 1 

Bronchitis/Emphysema 

No 1,658 544 572 285 112 53 26 10 12 1 5 1 37 

Yes 96 36 28 16 11 2 1 1 - - - - 1 

DK 8 2 4 2 - - - - - - - - -
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-153 

Table 16-62. Number of Loads of Laundry Washed in a Washing Machine at Home by the Number of 

Respondents (continued) - = Indicates missing data. 

DK = The respondent replied “don't know”. 

Refused = Refused data. 

N = Sample size. 

Source: U.S. EPA (1996). 
 

 

 

Table 16-63. Range of the Number of Times an Automobile or Motor Vehicle Was Started in a Garage or 

Carport at Specified Daily Frequencies by the Number of Respondents 

Times/day 

N 1-2 3-5 6-9 10+ DK 

All 2,009 1321 559 78 17 34 

Gender 

Male 939 588 290 40 7 14 

Female 1,070 733 269 38 10 20 

Age(years) - 20 13 2 1 1 3 

1 to 4 111 68 39 2 2 ­ 5 to 11 150 93 49 6 - 2 

12 to 17 145 86 42 12 1 4 

18 to 64 1,287 840 367 50 12 18 

> 64 296 221 60 7 1 7 

Race 

White 1,763 1,164 486 69 17 27
 Black 110 70 31 4 - 5
 Asian 46 34 10 2 - ­ Some Others 24 19 5 - - ­ Hispanic 55 26 24 3 - 2
 Refused 11 8 3 - - ­

Hispanic

No 1,879 1,239 519 74 17 30
 Yes 111 68 35 4 - 4
 DK 12 9 3 - - ­ Refused 7 5 2 - - ­

Employment - 398 241 127 20 3 7 

Full Time 919 610 253 35 9 12 

Part Time 149 93 48 4 2 2 

Not Employed 536 372 129 19 3 13 

Refused 7 5 2 - - ­

Education - 427 262 134 21 4 6 

< High School 84 59 17 2 1 5 

High School Graduate 464 336 107 13 2 6 

< College 440 304 107 20 5 4 

College Graduate 326 201 106 10 2 7 

Post Graduate 268 159 88 12 3 6 

Census Region

Northeast 289 213 64 8 2 2
 Midwest 541 360 142 29 2 8
 South 702 430 221 27 8 16
 West 477 318 132 14 5 8
 

Day of Week

Weekday 1,383 903 386 63 11 20
 Weekend 626 418 173 15 6 14
 

Season 

Winter 567 396 136 20 5 10 

Spring 518 336 141 25 5 11 

Summer 525 313 178 18 6 10 

Fall 399 276 104 15 1 3 

Asthma 

No 1,861 1,228 514 70 17 32 

Yes 146 92 44 8 - 2 

DK 2 1 1 - - ­

Angina

No 1,959 1,288 545 76 17 33 

Yes 48 33 12 2 - 1 

DK 2 - 2 - - ­

Bronchitis/Emphysema

No 

Yes 

DK 

-

DK 

= Indicates missing data. 

= Respondent replied “don't know”. 

1,922 

84 

3 

1,266 

54 

1 

532 

25 

2 

74 

4 

-

17 

-

-

33 

1 

-

Refused = Refused data. 

N = Doer sample size. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-154 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Table 16-64. Time Spent at Home While the Windows or Outside Door Were Left Open (minutes/day) 

Windows Left Open 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 

Gender 

Gender 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Age (years) 

Race 

Race 

Race 

Race 

Race 

Hispanic 

Hispanic 

Employment 

Employment 

Employment 

Education 

Education 

Education 

Education 

Education 

Census Region 

Census Region 

Census Region 

Census Region 

Day of Week 

Day of Week 

Season 

Season 

Season 

Season 

Asthma 

Asthma 

Angina 

Angina 

Bronchitis/Emphysema 

Bronchitis/Emphysema 

Male 

Female 

1 to 4 

5 to 11 

12 to 17 

18 to 64 

> 64 

White 

Black 

Asian 

Some Others 

Hispanic 

No 

Yes 

Full Time 

Part Time 

Not Employed 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

Northeast 

Midwest 

South 

West 

Weekday 

Weekend 

Winter 

Spring 

Summer 

Fall 

No 

Yes 

No 

Yes 

No 

Yes 

1,960 

893 

1,067 

99 

159 

101 

1,282 

282 

1,558 

208 

47 

44 

80 

1,775 

156 

822 

190 

576 

163 

542 

408 

247 

216 

498 

390 

494 

578 

1,285 

675 

308 

661 

680 

311 

1,809 

145 

1,902 

49 

1,850 

100 

2 

5 

2 

0 

3 

2 

6 

1 

2 

3 

10 

1 

2 

2 

20 

5 

1 

5 

1 

2 

5 

15 

10 

3 

5 

1 

2 

3 

2 

1 

10 

10 

3 

2 

5 

3 

1 

2 

5 

10 

10 

10 

1 

10 

5 

16 

5 

10 

10 

10 

1 

20 

10 

20 

15 

7 

10 

6 

10 

15 

15 

10 

10 

10 

6 

10 

10 

10 

2 

20 

30 

5 

10 

10 

10 

1 

10 

15 

30 

30 

30 

10 

20 

24 

60 

30 

30 

30 

16 

60 

30 

30 

30 

30 

30 

60 

30 

60 

30 

60 

30 

30 

60 

30 

30 

30 

30 

10 

60 

180 

30 

30 

60 

30 

24 

30 

35 

180 

180 

119 

180 

60 

180 

180 

180 

180 

180 

180 

90 

60 

180 

180 

180 

60 

180 

90 

180 

119 

100 

180 

119 

180 

90 

180 

180 

119 

24 

180 

180 

60 

180 

118 

180 

30 

180 

180 

360 

360 

360 

180 

360 

360 

360 

360 

360 

360 

360 

180 

360 

360 

180 

360 

180 

360 

360 

360 

360 

360 

360 

360 

360 

360 

360 

360 

360 

180 

360 

600 

180 

360 

360 

360 

180 

360 

480 

840 

840 

840 

600 

600 

600 

840 

840 

840 

840 

600 

600 

600 

840 

840 

840 

840 

840 

840 

840 

840 

840 

840 

840 

840 

600 

840 

840 

840 

360 

600 

961 

600 

840 

840 

840 

961 

840 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

961 

Exposure Factors Handbook Page
 

November 2011 16-155 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

 

 

 

 

 

Table 16-64. Time Spent at Home While the Windows or Outside Door Were Left Open (minutes/day) 

(continued) 

Outside Door Left Open 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

All 1,170 0 1 5 10 60 180 600 600 721 721 721 721 

Gender Male 505 0 1 3 10 60 180 600 600 721 721 721 721 

Gender Female 665 1 1 5 10 60 180 600 600 721 721 721 721 

Age (years) 1 to 4 68 0 0 2 10 30 180 360 721 721 721 721 721 

Age (years) 5 to 11 109 0 1 3 10 60 180 600 600 600 721 721 721 

Age (years) 12 to 17 79 0 1 3 5 60 180 360 600 721 721 721 721 

Age (years) 18 to 64 718 1 1 3 10 60 180 600 600 721 721 721 721 

Age (years) > 64 180 1 1 10 20 180 360 600 721 721 721 721 721 

Race White 968 0 1 5 10 60 180 600 600 721 721 721 721 

Race Black 100 1 3 6 13 60 180 600 600 600 661 721 721 

Race Asian 23 1 1 2 60 180 360 600 600 721 721 721 721 

Race Some Others 22 1 1 1 15 30 180 600 600 721 721 721 721 

Race Hispanic 45 0 0 5 5 45 180 360 600 600 721 721 721 

Hispanic No 1,073 0 1 3 10 60 180 600 600 721 721 721 721 

Hispanic Yes 81 0 1 5 10 45 180 360 600 600 721 721 721 

Employment Full Time 451 1 1 3 10 60 180 600 600 721 721 721 721 

Employment Part Time 93 0 3 5 15 60 180 600 600 721 721 721 721 

Employment Not Employed 362 1 1 5 10 60 360 600 600 721 721 721 721 

Education < High School 96 1 1 2 11 75 360 600 600 721 721 721 721 

Education High School Graduate 309 1 3 5 10 60 180 600 600 721 721 721 721 

Education < College 225 0 1 3 10 60 180 600 600 721 721 721 721 

Education College Graduate 150 0 1 1 15 60 180 600 600 721 721 721 721 

Education Post Graduate 124 2 2 3 5 30 180 600 600 721 721 721 721 

Census Region Northeast 223 1 2 5 10 90 180 600 600 721 721 721 721 

Census Region Midwest 221 0 0 2 10 60 180 600 600 721 721 721 721 

Census Region South 361 1 1 5 10 60 180 360 600 600 721 721 721 

Census Region West 365 0 1 5 15 60 180 600 600 721 721 721 721 

Day of Week Weekday 732 0 1 5 10 60 180 600 600 721 721 721 721 

Day of Week Weekend 438 1 1 5 10 60 180 600 600 721 721 721 721 

Season Winter 184 0 0 2 3 10 60 180 600 600 600 600 600 

Season Spring 407 1 1 5 20 180 360 600 600 721 721 721 721 

Season Summer 385 0 2 10 30 180 360 600 721 721 721 721 721 

Season Fall 194 1 1 2 10 30 180 360 600 600 600 600 600 

Asthma No 1,072 0 1 5 10 60 180 600 600 721 721 721 721 

Asthma Yes 97 1 1 3 6 30 180 600 600 721 721 721 721 

Angina No 1,133 0 1 5 10 60 180 600 600 721 721 721 721 

Angina Yes 36 1 1 3 10 105 360 360 600 721 721 721 721 

Bronchitis/emphysema No 1,105 0 1 3 10 60 180 600 600 721 721 721 721 

Bronchitis/emphysema Yes 63 5 5 10 10 90 180 600 600 600 721 721 721 

N = Doer sample size.
 

Note: Values of "180", "360", "600","840" and "961" for number of minutes signify that 2-4 hours, 4-8 hours, 8-12 hours, 12-16 hours,
 

and more than 16 hours, respectively, were spent. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: U.S. EPA (1996). 

Page Exposure Factors Handbook 

16-156 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

 

 

 

c 

Table 16-65. Mean Time Spent (hours/week)a in Ten Major Activity Categories Grouped by Regions 

Totalb 

N = 975 

West North Central Northeast South 

Mean SDc 

Activity N = 200 N = 304 N = 185 N = 286 

Activity Category 

Market Work 23.44 29.02 27.34 24.21 26.15 23.83 

House/yard work 14.64 14.17 14.29 15.44 14.66 12.09 

Child care 2.50 2.82 2.32 2.66 2.62 5.14 

Services/shop 5.22 5.64 4.92 4.72 5.15 5.40 

Personal care 79.23 76.62 78.11 79.38 78.24 12.70 

Education 2.94 1.43 0.95 1.45 1.65 6.34 

Organizations 3.42 2.97 2.45 2.68 2.88 5.40 

Social entertainment 8.26 8.42 8.98 8.22 8.43 8.17 

Active leisure 5.94 5.28 4.77 5.86 5.49 7.81 

Passive leisure 22.47 21.71 23.94 23.47 22.80 13.35 

Total Time 168.00 168.00 168.00 168.00 168.00 0.09 

a Weighted for day of week, panel loss (not defined in report), and correspondence to Census. Data may not add to totals shown due to 

rounding. b N = surveyed population. 

SD = standard deviation. 

Source: Hill (1985). 

Exposure Factors Handbook Page
 

November 2011 16-157 
 

Table 16-66. Total Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by Type of Day 

Time Duration (minutes/day) 

Weekday Saturday Sunday 

[Na = 831] [N = 831] [N = 831] 

Activity Category 

Market Work 288.0 (257.7)

b 97.9 (211.9) 58.0 (164.8) 

House/Yardwork 126.3 (119.3) 160.5 (157.2) 124.5 (133.3) 

Child Care 26.6 (50.9) 19.4 (51.5) 24.8 (61.9) 

Services/Shopping 48.7 (58.7) 64.4 (92.5) 21.6 (49.9) 

Personal Care 639.2 (114.8) 706.8 (169.8) 734.3 (156.5) 

Education 16.4 (64.4) 5.4 (38.1) 7.3 (48.0) 

Organizations 21.1 (49.7) 18.4 (75.2) 58.5 (104.5) 

Social Entertainment 54.9 (69.2) 1,114.1 (156.0) 110.0 (151.2) 

Active Leisure 37.9 (71.11) 61.4 (126.5) 64.5 (120.6) 

Passive Leisure 181.1 (121.9) 191.8 (161.6) 236.5 (167.1) 

Total Time 1,440 1,440 1,440 

a N = Number of respondents. b ( ) = Numbers in parentheses are standard deviations. 

Source: Hill (1985). 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

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16-158 November 2011 
 

 

Table 16-67. Mean Time Spent (minutes/day) in Ten Major Activity Categories During 4 Waves of Interviewsa 

Fall 

(Nov. 1, 1975)b 

N = 861 

Spring 

(June 1, 1976)b 

N = 861 

Spring 

(June 1, 1976)b 

N = 861 

Summer 

(Sept. 21, 1976)b 

N = 861 

Range of Standard 

Deviations 

Activity Category Wave 1 Wave 2 Wave 3 Wave 4 

Market work 222.94 226.53 210.44 230.92 272–287 

House/yard work 133.16 135.58 143.10 119.95 129–156 

Child care 25.50 22.44 25.51 21.07 49–58 

Services/shop 48.98 44.09 44.61 47.75 76–79 

Personal care 652.95 678.14 688.27 674.85 143–181 

Education 22.79 12.57 2.87 10.76 32–93 

Organizations 25.30 22.55 23.21 29.91 68–87 

Social entertainment 63.87 67.11 83.90 72.24 102–127 

Active leisure 42.71 47.46 46.19 42.30 96–105 

Passive leisure 210.75 183.48 171.85 190.19 144–162 

Total Time 1,440.00 1,440.00 1,440.00 1,440.00 -­

a Weighted for day of week, panel loss (not defined in report), and correspondence to Census. b Dates by which 50% of the interviews for each wave were taken. 

Source: Hill (1985). 

 

 

 

 

Table 16-68. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Sexa 

Time Duration (hours/week) 

Men Women Men and Women 

N = 140 N = 561 N = 971 

Activity Category 

Market work 35.8 (23.6)b 17.9 (20.7) 26.2 (23.8) 

House/yard 8.5 (9.0) 20.0 (11.9) 14.7 (12.1) 

Child care 1.2 (2.5) 3.9 (6.4) 2.6 (5.2) 

Services/shop 3.9 (4.5) 6.3 (5.9) 5.2 (5.4) 

Personal care 77.3 (13.0) 79.0 (12.4) 78.2 (12.7) 

Education 2.3 (7.7) 1.1 (4.8) 1.7 (6.4) 

Organizations 2.5 (5.5) 3.2 (5.3) 2.9 (5.4) 

Social entertainment 7.9 (8.3) 8.9 (8.0) 8.4 (8.2) 

Active leisure 5.9 (8.2) 5.2 (7.4) 5.5 (7.8) 

Passive leisure 22.8 (14.1) 22.7 (12.7) 22.8 (13.3) 

Total time 168.1 168.1 168.1 

a Detailed components of activities (87) are presented in Table 1A-4 of the original study. b ( ) = Numbers in parentheses are standard deviations. 

Source: Hill (1985). 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

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Exposure Factors Handbook 

Chapter 16—Activity Factors
 

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16-160 November 2011 

Table 16-69. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex , and Type of Day 

Activity 

Age (3 to 11 years) Age (12 to 17 years) 

Weekday Weekend Weekday Weekend 

Boy Girl Boy Girl 

(N = 118) (N = 111) (N = 118) (N = 111) 

Boy Girl Boy Girl 

(N = 77) (N = 83) (N = 77) (N = 83) 

Market Work 

Household Work 

Personal Care 

Eating 

Sleeping 

School 

Studying 

Church 

Visiting 

Sports 

Outdoors 

Hobbies 

Art Activities 

Playing 

TV 

Reading 

Household Conversations 

Other Passive Leisure 

Unknown 

Percent of Time Accounted for by 

Activities Above 

16 

17 

43 

81 

584 

252 

14 

7 

16 

25 

10 

3 

4 

137 

117 

9 

10 

9 

22 

94 

0 

21 

44 

78 

590 

259 

19 

4 

9 

12 

7 

1 

4 

115 

128 

7 

11 

14 

25 

92 

7 

32 

42 

78 

625 

-

4 

53 

23 

33 

30 

3 

4 

177 

181 

12 

14 

16 

20 

93 

4 

43 

50 

84 

619 

-

9 

61 

37 

23 

23 

4 

4 

166 

122 

10 

9 

17 

29 

89 

23 

16 

48 

73 

504 

314 

29 

3 

17 

52 

10 

7 

12 

37 

143 

10 

21 

21 

14 

93 

21 

40 

71 

65 

478 

342 

37 

7 

25 

37 

10 

4 

6 

13 

108 

13 

30 

14 

17 

92 

58 

46 

35 

58 

550 

-

25 

40 

46 

65 

36 

4 

11 

35 

187 

12 

24 

43 

10 

88 

25 

89 

76 

75 

612 

-

25 

36 

53 

26 

19 

7 

9 

24 

140 

19 

30 

33 

4 

89 

N 

-

Source: 

= Sample size. 

= No data 

Timmer et al. (1985). 
 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-70. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for 5 Different Age Groups 

Activity 

Weekday Weekend Significant 

Effect Age (years) Age (years) a

3–5 6–8 9–11 12–14 15–17 3–5 6–8 9–11 12–14 15–17 

Market Work - 14 8 14 28 - 4 10 29 48 

Personal Care 41 49 40 56 60 47 45 44 60 51 A, S, AxS (F > M) 

Household Work 14 15 18 27 34 17 27 51 72 60 A, S, AxS (F > M) 

Eating 82 81 73 69 67 81 80 78 68 65 A 

Sleeping 630 595 548 473 499 634 641 596 604 562 A 

School 137 292 315 344 314 - - - - -

Studying 2 8 29 33 33 1 2 12 15 30 A 

Church 4 9 9 9 3 55 56 53 32 37 A 

Visiting 14 15 10 21 20 10 8 13 22 56 A (Weekend Only) 

Sports 5 24 21 40 46 3 30 42 51 37 A, S (M > F) 

Outdoor Activities 4 9 8 7 11 8 23 39 25 26 

Hobbies 0 2 2 4 6 1 5 3 8 3 

Art Activities 5 4 3 3 12 4 4 4 7 10 

Other Passive Leisure 9 1 2 6 4 6 10 7 10 18 A 

Playing 218 111 65 31 14 267 180 92 35 21 A, S (M > F) 

TV 111 99 146 142 108 122 136 185 169 157 A, S, AxS (M > F) 

Reading 5 5 9 10 12 4 9 10 10 18 A 

Being Read to 2 2 0 0 0 3 2 0 0 0 A 

Unknown 30 14 23 25 7 52 7 14 4 9 A a Effects are significant for weekdays and weekends, unless otherwise specified. A = age effect, p < 0.05, for both weekdays and 

weekend activities; S = sex effect p < 0.05, F > M, M > F = females spend more time than males, or vice versa; and AxS = age by sex 

interaction, p < 0.05. 

- = No data. 

Source: Timmer et al. (1985). 

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November 2011 16-161 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

 

 

 

 

 

 

Table 16-71. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week 

Indoorsa	 Outdoorsb 

Age Group Weekday Weekend Weekday Weekend 

3 to 5 years	 19.4 18.9 2.5 3.1 

6 to 8 years	 20.7 18.6 1.8 2.5 

9 to 11 years	 20.8 18.6 1.3 2.3 

12 to 14 years	 20.7 18.5 1.6 1.9 

15 to 17 years	 19.9 17.9 1.4 2.3 a	 Time indoors was estimated by adding the average times spent performing indoor activities (household work, personal care, eating, 

sleeping, attending school, studying, attending church, watching television, and engaging in conversation) and half the time spent in 

each activity which could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing, reading, 

and other passive leisure). b	 Time outdoors was estimated by adding the average time spent in outdoor activities and half the time spent in each activity which 

could have occurred either indoors or outdoors (i.e., market work, sports, hobbies, art activities, playing, reading, and other passive 

leisure). 

Source:	 Adapted from Timmer et al. (1985). 

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Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-163 

 

 

 

 

 

 

Table 16-72. Mean Time Spent (minutes/day) in Various Microenvironments by Age Group (years) for the
 

National and California Surveys
 

National Data 

Mean Duration (Standard Error) 

Microenvironment Age 12–17 Age 18–24 Age 24–44 Age 45–64 Age 65+ 

N = 340a N = 340 N = 340 N = 340 N = 340 Doerb Doer Doer Doer Doer 

Autoplaces 2 (1) 73 7 (2) 137 2 (1) 43 4 (1) 73 4 (2) 57 

Restaurant/bar 9 (2) 60 28 (3) 70 25 (3) 86 19 (2) 67 20 (5) 74 

In-vehicle/internal combustion 79 (7) 88 103 (8) 109 94 (4) 101 82 (5) 91 62 (5) 80 

In-vehicle/other 0 (0) 12 1 (1) 160 1 (0) 80 1 (1) 198 1 (1) 277 

Physical/outdoors 32 (8) 130 17 (4) 110 19 (4) 164 7 (1) 79 15 (4) 81 

Physical/indoors 15 (3) 87 8 (2) 76 7 (1) 71 7 (2) 77 7 (1) 51 

Work/study-residence 22 (4) 82 19 (6) 185 16 (2) 181 9 (2) 169 5 (3) 297 

Work/study-other 159 (14) 354 207 (20) 391 220 (11) 422 180 (13) 429 35 (6) 341 

Cooking 11 (3) 40 18 (2) 39 38 (2) 57 43 (3) 64 50 (5) 65 

Other activities/kitchen 53 (4) 64 42 (3) 55 70 (4) 86 90 (6) 101 108 (9) 119 

Chores/child 91 (7) 92 124 (9) 125 133 (6) 134 121 (6) 122 119 (7) 121 

Shop/errands 26 (4) 68 31 (4) 65 33 (2) 66 33 (3) 67 35 (5) 69 

Other/outdoors 70 (13) 129 34 (4) 84 48 (6) 105 60 (7) 118 82 (13) 140 

Social/cultural 87 (10) 120 100 (12) 141 56 (3) 94 73 (6) 116 85 (8) 122 

Leisure-eat/indoors 237 (16) 242 181 (11) 189 200 (8) 208 238 (11) 244 303 (20) 312 

Sleep/indoors 548 (31) 551 511 (26) 512 479 (14) 480 472 (15) 472 507 (26) 509 

CARB Data 

Mean Duration (Standard Error) 

Microenvironment Age 12–17 Age 18–24 Age 24–44 Age 45–64 Age 65+ 

N = 340a N = 340 N = 340 N = 340 N = 340 Doer Doer Doer Doer Doer 

Autoplaces 16 (8) 124 16 (4) 71 25 (9) 114 20 (5) 94 9 (2) 53 

Restaurant/bar 16 (4) 44 40 (8) 98 44 (5) 116 31 (4) 82 25 (7) 99 

In-vehicle/internal combustion 78 (11) 89 111 (13) 122 98 (5) 111 100 (11) 117 63 (8) 89 

In-vehicle/other 1 (0) 19 3 (1) 60 5 (2) 143 2 (1) 56 2 (1) 53 

Physical/outdoors 32 (7) 110 13 (3) 88 17 (3) 128 14 (3) 123 15 (4) 104 

Physical/indoors 20 (4) 65 5 (2) 77 6 (1) 61 5 (1) 77 3 (1) 48 

Work/study-residence 25 (5) 76 30 (11) 161 7 (2) 137 10 (3) 139 5 (3) 195 

Work/study-other 196 (30) 339 201 (24) 344 215 (14) 410 173 (20) 429 30 (11) 336 

Cooking 3 (1) 19 14 (2) 40 32 (2) 59 31 (3) 68 41 (7) 69 

Other activities/kitchen 31 (4) 51 31 (5) 55 43 (3) 65 62 (6) 91 97 (14) 119 

Chores/child 72 (11) 77 79 (8) 85 110 (6) 119 99 (8) 109 123 (15) 141 

Shop/errands 14 (3) 50 35 (7) 71 33 (4) 71 32 (3) 77 35 (5) 76 

Other/outdoors 58 (8) 78 80 (15) 130 68 (8) 127 76 (12) 134 55 (7) 101 

Social/cultural 63 (14) 109 65 (10) 110 50 (5) 122 50 (5) 107 49 (7) 114 

Leisure-eat/indoors 260 (27) 270 211 (19) 234 202 (9) 215 248 (15) 261 386 (34) 394 

Sleep/indoors 557 (44) 560 506 (30) 510 487 (17) 491 485 (23) 491 502 (31) 502 a All N’s are weighted number.
 b Doer = Respondents who reported participating in each activity/location spent in microenvironments.
 

Source: Robinson and Thomas (1991). 
 

Table 16-73. Mean Time Spent in Ten Major Activity Categories Grouped by Total Sample 

and Sex for the CARB and National Studies (age 18–64 years) 

Time Duration (minutes/day) 

CARB National CARB National 

Activity Category (1987–1988) (1985) 

Total Sample 

(1987–1988) 

Men Women Men 

(1985) 

Women 

Na = 1,359 N = 1,980 N = 639 N = 720 N = 921 N = 1,059 

Paid Work 273 252 346 200 323 190 

Household Work 102 118 68 137 79 155 

Child Care 23 25 12 36 11 43 

Obtaining Goods and Services 61 55 48 73 44 62 

Personal Needs and Care 642 642 630 655 636 645 

Education and Training 22 19 25 20 21 16 

Organizational Activities 12 17 11 13 12 20 

Entertainment/Social Activities 60 62 57 55 64 62 

Recreation 43 50 53 31 69 43 

Communication 202 196 192 214 197 194 a N = total diary days. 

Source: Robinson and Thomas (1991). 

 

 

Table 16-74. Total Mean Time Spent at 3 Major Locations Grouped by Total Sample and Sex 

for the CARB and National Study (age 18–64 years) 

Locationa 

At Home 

Away From Home 

Travel 

Not Ascertained 

CARB 

(1987–1988) 

National 

(1985) 

Total Sample 

Na = 1,359 N = 1,980 

892 954 

430 384 

116 94 

2 8 

Total Time 1,440 1,440 

CARB 

(1987–1988) 

Men Women 

N = 39 N = 720 

822 963 

487 371 

130 102 

1 4 

1,440 1,440 

National 

(1985) 

Men Women 

N = 921 N = 1,059 

886 1,022 

445 324 

101 87 

8 7 

1,440 1,440 a N = total diary days. 

Source: Robinson and Thomas (1991). 

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Chapter 16—Activity Factors 

 

 

 

 

 

c 

Table 16-75. Mean Time Spent at 3 Locations for Both CARB and National Studies 

(ages 12 years and older) 

Mean Duration (minutes/day)
 

Location Category CARB National
 

(N = 1,762)a SEb (N = 2,762)a SE 

Indoor 1,255c 28 1,279c 21 

Outdoor 86d 5 74d 4 

In-Vehicle 98d 4 87d 2 

Total Time Spent 1,440 1,440 

a N = Weighted Number – National sample population was weighted to obtain a ratio of 46.5 males and 53.5 females, in equal 

proportion for each day of the week, and for each quarter of the year. b SE = Standard error of mean. 

Difference between the mean values for the CARB and national studies is not statistically significant. d Difference between the mean values for the CARB and national studies is statistically significant at the 0.05 level. 

Source: Robinson and Thomas (1991). 

 

Table 16-76. Sample Sizes for Sex and Age Groups 

Age Group Group Sample Size Age Range 

Adults Men 724 ≥18 years 

Women 855 ≥18 years 

Adolescents Male 98 12–17 years 

Female 85 12–17 years 

Childrena Young male 145 6–8 years 

Young female 124 6–8 years 

Old male 156 9–11 years 

Old female 160 9–11 years 

a 

Source: 

Children under the age of 6 are excluded for the present study (too few responses in CARB study). 

Funk et al. (1998). 

Exposure Factors Handbook Page
 

November 2011 16-165 
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-77. Assignment of At Home Activities to Inhalation Rate Levels for All Individuals 

Children Adolescent and Adult 

Low Moderate Low Moderate High 

Watching child care 

Night sleep 

Watch personal care 

Homework 

Radio use 

TV use 

Records/tapes 

Reading books 

Reading magazines 

Reading newspapers 

Letters/writing 

Other leisure 

Homework/watch TV 

Reading/TV 

Reading/listen music 

Paperwork 

Outdoor cleaning 

Food Preparation 

Metal clean-up 

Cleaning house 

Clothes care 

Car/boat repair 

Home repair 

Plant care 

Other household 

Pet care 

Baby care 

Child care 

Helping/teaching 

Talking/reading 

Indoor playing 

Outdoor playing 

Medical child care 

Washing, hygiene 

Medical care 

Help and care 

Meals at home 

Dressing 

Visiting at home 

Hobbies 

Domestic crafts 

Art 

Music/dance/drama 

Indoor dance 

Conservations 

Painting room/home 

Building fire 

Washing/dressing 

Outdoor play 

Playing/eating 

Playing/talking 

Playing/watch TV 

TV/eating 

TV/something else 

Reading book/eating 

Read magazine/eat 

Read newspaper/eat 

Night sleep 

Naps/resting 

Doing homework 

Radio use 

TV use 

Records/tapes 

Read books 

Read magazines 

Writing/paperwork 

Other passive leisure 

Food preparation 

Food clean-up 

Cleaning house 

Clothes care 

Car care 

Household repairs 

Plant care 

Animal care 

Other household 

Baby care 

Child care 

Helping/teaching 

Talking/reading 

Indoor playing 

Outdoor playing 

Medical child care 

Washing 

Medical care 

Help and care 

Meals at home 

Dressing/grooming 

Not ascertained 

Visiting at home 

Hobbies 

Domestic crafts 

Art 

Music/drama/dance 

Games 

Computer use 

Conversations 

Outdoor cleaning 

Source: Funk et al. (1998). 

Page Exposure Factors Handbook 

16-166 November 2011 
 

 c 

Table 16-78. Aggregate Time Spent (minutes/day) at Home in Activity Groupsa 

Activity Group Mean 

Adult 

SD Mean 

Adolescent 

SD Mean 

Children 

SD 

Low 702 214 789 230 823 153 

Moderate 257 183 197 131 241b 136 

High 9 38 1 11 3 17 

Highparticipants c 92 83 43 72 58 47 a Time spent engaging in all activities embodied by inhalation rate category (minutes/day). b Significantly different from adolescents (p < 0.05). 

Participants in high inhalation rate level activities (i.e., doers). 

SD = Standard deviation. 

Source: Funk et al. (1998). 

 c 

Table 16-79. Comparison of Mean Time Spent (minutes/day) at Home, by Sexa 

Male Female 

Activity Group Mean SD Mean SD 

Adults 

Low 691 226 714 200 

Moderate 190 150 323b 189 

High 14 50 4b 18 c Highparticipants 109 97 59b 40 

Adolescents 

Low 775 206 804 253 

Moderate 181 126 241 134 

High 2 16 0 0 

a Time spent engaging in all activities embodied by inhalation rate category (minutes/day). b Significantly different from male (p < 0.05). 

Participants in high inhalation rate activities (i.e., doers). 

SD = Standard deviation. 

Source: Funk et al. (1998). 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-167 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-168 November 2011 

a Table 16-80. Comparison of Mean Time Spent (minutes/day) at Home, by Sex and Age for Children 

Activity Group 

Male Female 

6 to 8 Years 9 to 11 Years 6 to 8 Years 9 to 11 Years 

Mean SD Mean SD Mean SD Mean SD 

Low 806 134 860 157 828 155 803 162 

Moderate 259 135 198 111 256 141 247 146 

High 3 17 7 27 1 9 2 10 b Highparticipant 77 59 70 54 68 11 30 23 a Time spent engaging in all activities embodied by inhalation rate category (minutes/day). b Participants in high inhalation rate activities (i.e., doers). 

SD = Standard deviation. 

Source : Funk et al. (1998). 

 

 

 

 

 

 

 

Table 16-81. Number of Person-Days/Individualsa for Children Less Than 12 Years in CHAD Database 

Age Group All Studies Californiab Cincinnatic NHAPS-Air NHAPS-Water 

0 Years 223/199 104 36/12 39 44 

0 to 6 Months - 50 15/5 - -

6 to 12 Months - 54 21/7 - -

1 Year 259/238 97 31/11 64 67 

12 to 18 Months - 57 - - -

18 to 24 Months - 40 - - -

2 Years 317/264 112 81/28 57 67 

3 Years 278/242 113 54/18 51 60 

4 Years 259/232 91 41/14 64 63 

5 Years 254/227 98 40/14 52 64 

6 Years 237/199 81 57/19 59 40 

7 Years 243/213 85 45/15 57 56 

8 Years 259/226 103 49/17 51 55 

9 Years 229/195 90 51/17 42 46 

10 Years 224/199 105 38/13 39 42 

11 Years 227/206 121 32/11 44 30 

Total 3,009/2,640 1,200 556/187 619 634 a The number of person-days of data are the same as the number of individuals for all studies except for the Cincinnati 

study. Since up to 3 days of activity pattern data were obtained from each participant in this study, the number of persondays of data is approximately 3 times the number of individuals. b The California study referred to in this table is the Wiley et al. (1991) study. c The Cincinnati study referred to in this table is the Johnson (1989) study. 

- = No data. 

Source: Cohen Hubal et al. (2000). 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-169 

Table 16-82. Time Spent (hours/day) in Various Microenvironments, by Age 

Age (years) Average Time ± Standard Deviation (Percent > 0 Hours) 

Indoors at Home Outdoors at Home Indoors at School Outdoors at Park In Vehicle 

0 19.6 ± 4.3 (99) 1.4 ± 1.5 (20) 3.5 ± 3.7 (2) 1.6 ± 1.5 (9) 1.2 ± 1.0 (65) 

1 19.5 ± 4.1 (99) 1.6 ± 1.3 (35) 3.4 ± 3.8 (5) 1.9 ± 2.7 (10) 1.1 ± 0.9 (66) 

2 17.8 ± 4.3 (100) 2.0 ± 1.7 (46) 6.2 ± 3.3 (9) 2.0 ± 1.7 (17) 1.2 ± 1.5 (76) 

3 18.0 ± 4.2 (100) 2.1 ± 1.8 (48) 5.7 ± 2.8 (14) 1.5 ± 0.9 (17) 1.4 ± 1.9 (73) 

4 17.3 ± 4.3 (100) 2.4 ± 1.8 (42) 4.9 ± 3.2 (16) 2.3 ± 1.9 (20) 1.1 ± 0.8 (78) 

5 16.3 ± 4.0 (99) 2.5 ± 2.1 (52) 5.4 ± 2.5 (39) 1.6 ± 1.5 (28) 1.3 ± 1.8 (80) 

6 16.0 ± 4.2 (98) 2.6 ± 2.2 (48) 5.8 ± 2.2 (34) 2.1 ± 2.4 (32) 1.1 ± 0.8 (79) 

7 15.5 ± 3.9 (99) 2.6 ± 2.0 (48) 6.3 ± 1.3 (40) 1.5 ± 1.0 (28) 1.1 ± 1.1 (77) 

8 15.6 ± 4.1 (99) 2.1 ± 2.5 (44) 6.2 ± 1.1 (41) 2.2 ± 2.4 (37) 1.3 ± 2.1 (82) 

9 15.2 ± 4.3 (99) 2.3 ± 2.8 (49) 6.0 ± 1.5 (39) 1.7 ± 1.5 (34) 1.2 ± 1.2 (76) 

10 16.0 ± 4.4 (96) 1.7 ± 1.9 (40) 5.9 ± 1.5 (39) 2.2 ± 2.3 (40) 1.1 ± 1.1 (82) 

11 14.9 ± 4.6 (98) 1.9 ± 2.3 (45) 5.9 ± 1.5 (41) 2.0 ± 1.7 (44) 1.6 ± 1.9 (74) 

Source: Cohen Hubal et al. (2000). 

Table 16-83. Mean Time Children Spent (hours/day) Doing Various Macroactivities While Indoors at Home 

Mean Time (Percent > 0 Hours) Age 

(years) Eat Sleep or Nap Shower or 

Bath Play Games Watch TV or Listen to Radio 

Read, Write, 

Homework 

Think, Relax, 

Passive 

0 1.9 (96) 12.6 (99) 0.4 (44) 4.3 (29) 1.1 (9) 0.4 (4) 3.3 (62) 

1 1.5 (97) 12.1 (99) 0.5 (56) 3.9 (68) 1.8 (41) 0.6 (19) 2.3 (20) 

2 1.3 (92) 11.5 (100) 0.5 (53) 2.5 (59) 2.1 (69) 0.6 (27) 1.4 (18) 

3 1.2 (95) 11.3 (99) 0.4 (53) 2.6 (59) 2.6 (81) 0.8 (27) 1.0 (19) 

4 1.1 (93) 10.9 (100) 0.5 (52) 2.6 (54) 2.5 (82) 0.7 (31) 1.1 (17) 

5 1.1 (95) 10.5 (98) 0.5 (54) 2.0 (49) 2.3 (85) 0.8 (31) 1.2 (19) 

6 1.1 (94) 10.4 (98) 0.4 (49) 1.9 (35) 2.3 (82) 0.9 (38) 1.1 (14) 

7 1.0 (93) 9.9 (99) 0.4 (56) 2.1 (38) 2.5 (84) 0.9 (40) 0.6 (10) 

8 0.9 (91) 10.0 (96) 0.4 (51) 2.0 (35) 2.7 (83) 1.0 (45) 0.7 (7) 

9 0.9 (90) 9.7 (96) 0.5 (43) 1.7 (28) 3.1 (83) 1.0 (44) 0.9 (17) 

10 1.0 (86) 9.6 (94) 0.4 (43) 1.7 (38) 3.5 (79) 1.5 (47) 0.6 (10) 

11 0.9 (89) 9.3 (94) 0.4 (45) 1.9 (27) 3.1 (85) 1.1 (47) 0.6 (10) 

Source: Cohen Hubal et al. (2000). 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-170 November 2011 

Table 16-84. Time Children Spent (hours/day) in Various Microenvironments, by Age Recast Into New 

Standard Age Categories 

Age Group N 

Indoors at Home Outdoors at Home Indoors at School Outdoors at Park In Vehicle 

Mean % 

Time Doing 

% 

Mean Time Doing 

% 

Mean Time Doing 

% 

Mean Time Doing 

% 

Mean Time Doing 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

123 

33 

120 

287 

728 

765 

2,110 

3,283 

2,031 

1,005 

19.6 

20.9 

19.6 

19.1 

19.2 

18.2 

17.3 

15.7 

15.5 

14.6 

98 

100 

100 

99 

99 

99 

100 

99 

97 

98 

1.7 

1.8 

0.8 

1.1 

1.4 

1.8 

1.9 

1.9 

1.7 

1.4 

21 

9 

8 

15 

34 

38 

43 

40 

30 

20 

4.3 

0.2 

7.8 

7.6 

6.4 

6.8 

5.9 

6.5 

6.6 

5.7 

3 

3 

7 

8 

9 

12 

26 

44 

45 

33 

1.3 

1.6 

1.3 

1.8 

1.5 

2.1 

1.6 

2.1 

2.6 

3.1 

3 

9 

6 

5 

5 

7 

10 

17 

15 

10 

1.3 

1.3 

1.1 

1.3 

1.1 

1.3 

1.3 

1.1 

1.3 

1.7 

63 

27 

14 

14 

27 

28 

29 

29 

42 

90 

N 

Source: 

= Sample size. 

Based on data source (CHAD) used by Cohen Hubal et al. (2000). 

Table 16-85. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home Recast Into 

New Standard Age Categories 

Age Group N 

Eat Sleep or Nap Shower or Bath Play Game Watch TV/ 

Listen to Radio 

Read, Write, 

Homework 

Think, Relax, 

Passive 

Mean 

Time 

% 

Doing 

Mean 

Time 

% 

Doing 

Mean 

Time 

% 

Doing 

Mean 

Time 

% 

Doing 

Mean 

Time 

% 

Doing 

Mean 

Time 

% 

Doing 

Mean 

Time 

% 

Doing 

Birth to <1 month 123 2.2 98 13.0 100 0.5 41 5.0 53 1.3 8 0.7 2 2.7 48 

1 to <3 months 33 2.4 100 14.8 100 0.4 24 0.7 6 1.6 15 0.0 0 3.5 79 

3 to <6 months 120 2.0 100 13.5 100 0.5 9 1.3 31 1.0 21 1.1 3 2.5 59 

6 to <12 months 287 1.8 100 12.9 100 0.4 11 1.1 30 1.3 25 0.5 4 2.5 35 

1 to <2 years 728 1.7 99 12.5 100 0.5 21 3.2 45 1.8 52 0.6 13 1.4 26 

2 to <3 years 765 1.5 98 12.0 100 0.5 22 2.6 45 2.0 77 0.6 18 0.8 30 

3 to <6 years 2,110 1.4 99 11.2 100 0.5 38 2.5 38 2.3 86 0.7 25 0.8 28 

6 to <11 years 3,283 1.2 98 10.2 100 0.4 54 2.0 28 2.6 84 1.0 43 0.8 20 

11 to <16 years 2,031 1.1 94 9.7 98 0.4 50 1.8 18 3.0 85 1.4 45 0.8 20 

16 to <21 years 1,005 1.0 84 8.9 98 0.4 45 1.9 5 3.2 73 2.2 37 1.3 24 

N = Sample size. 

Source: Based on data source (CHAD) used by Cohen Hubal et al. (2000). 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-171 

Table 16-86. Number and Percentage of Respondents With Children and Those Reporting 

Outdoor Playa Activities in Both Warm and Cold Weather 

Source 

Respondents with 

Children Child Playera Child Non-Player 

Warm 

Weather b Player

Cold 

Weather 

Player 

Player in Both Seasons 

N N % N % N N % 

SCS-II base 197 128 65.0 69 35.0 127 100 50.8 

SCS-II over sample 483 372 77.0 111 23.0 370 290 60.0 

Total 680 500 73.5 180 26.5 497 390 57.4 a “Play” and “player” refer specifically to participation in outdoor play on bare dirt or mixed grass and dirt. b Does not include three “Don’t know/refused” responses regarding warm weather play. 

N = Sample size. 

Source: Wong et al. (2000). 

Table 16-87. Play Frequency and Duration for All Child Players (from SCS-II data) 

Cold Weather Warm Weather 

Statistic Frequency Duration Total Frequency Duration Total 

(days/week) (hours/day) (hours/week) (days/week) (hours/day) (hours/week) 

N 372 374 373 488 479 480 

5th Percentile 1 1 1 2 1 4 

50th Percentile 3 1 5 7 3 20 

95th Percentile 7 4 20 7 8 50 

N = Sample size. 

Source: Wong et al. (2000). 

Table 16-88. Hand Washing and Bathing Frequency for All Child Players (from SCS-II data) 

Cold Weather Warm Weather 

Statistic Hand Washing Bathing Hand Washing Bathing 

(times/day) (times/week) (times/day) (times/week) 

N 329 388 433 494 

5th Percentile 2 2 2 3 

50th Percentile 4 7 4 7 

95th Percentile 10 10 12 14 

N = Sample size. 

Source: Wong et al. (2000). 
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-89. NHAPS and SCS-II Play Durationa Comparison (children only) 

Data Source 

Mean Play Duration 

(minutes/day) χ

2 testb 

Cold Weather Warm Weather Total 

NHAPS 114 109 223 

p < 0.0001 SCS-II 102 206 308 a Selected previous day activities in NHAPS; average day outdoor play on bare dirt or mixed grass and dirt in SCS-II. b 2×2 Chi-square test for contingency between NHAPS and SCS-II. 

Source: Wong et al. (2000). 

Table 16-90. NHAPS and SCS-II Hand Wash Frequencya Comparison (children only) 

Data 

Source Season 

Percentb Reporting Frequency (times/day) of: 

χ

2 testc 

0 1–2 3–5 6–9 10–19 20–29 30+ “Don’t 

Know” 

NHAPS Cold 3 18 51 17 7 1 1 3 

p = 0.06 SCS-II Cold 1 16 50 11 7 1 0 15 

NHAPS Warm 3 18 51 15 7 2 1 4 

p = 0.001 SCS-II Warm 0 12 46 16 10 1 0 13 a Selected previous day activities in NHAPS; average day outdoor play on bare dirt or mixed grass and dirt in SCS-II. b Results are reported as percentage of total for clarity. Incidence data were used in statistical tests. c 2×2 Chi-square test for contingency between NHAPS and SCS-II. 

Source: Wong et al. (2000). 

Page Exposure Factors Handbook 

16-172 November 2011 
 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-91. Time Spent (minutes/day) Outdoors 

Based on CHAD Data (doers only)a 

Age Group N Time Spent Outdoors COV(%) Participationb (%) Minimum Median Maximum Mean SD 

<1 month 57 2 60 700 99 124 125 47 

1 to 2 months 5 4 60 225 102 90 89 36 

3 to 5 months 27 10 90 510 114 98 86 23 

6 to 11 months 91 5 60 450 91 76 84 33 

1 year 389 1 75 1,035 102 99 97 58 

2 years 448 1 100 550 134 108 80 64 

3 to 5 years 1,336 1 120 972 146 117 80 68 

6 to 10 years 2,216 1 120 1,440 162 144 89 71 

11 to 15 years 1,423 1 110 1,440 154 163 106 73 

16 to 17 years 356 1 85 1,083 129 145 112 81 

18 to 20 years 351 1 70 788 132 155 118 72 

21 to 44 years 3,660 1 61 1,305 131 165 126 62 

45 to 64 years 1,914 1 69 1,015 135 162 120 62 

>64 years 1,002 1 65 840 118 130 110 57 a Only data for individuals that spent >0 time outdoors and had 30 or more records are included in the analysis. b Participation rates or percent of sample days in the study spending some time (>0 minutes per day) outdoors. The mean time spent 

outdoors for the age group may be obtained by multiplying the participation rate by the mean time shown above. 

SD = Standard deviation. 

COV = Coefficient of variation (SD/mean × 100). 

Source: Graham and McCurdy (2004). 

Exposure Factors Handbook Page
 

November 2011 16-173 
November 201

Exposure Factors Handbook 

Table 16-92. Comparison of Daily Time Spent Outdoors (minutes/day), Considering Sex and Age Cohort (doers only)a

Age Group Sex N Time Spent Outdoors in Minutes COV (%) K-S Testb

Minimum Median Maximum Mean SD Dn χ

2

 p Reject H0

<1 month 

1 to 2 months 

3 to 5 months 

6 to 11 months 

1 year 

2 years 

3 to 5 years 

6 to 10 years 

11 to 15 years 

16 to 17 years 

18 to 20 years 

21 to 44 years 

45 to 64 years 

>64 years 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

Male 

 Female 

35 

22 

4 

1 

20 

7 

53 

38 

184 

205 

232 

216 

723 

612 

1,228 

987 

779 

640 

168 

188 

184 

167 

1,702 

1,956 

839 

1,075 

396 

605 

7 

2 

4 

225 

10 

50 

10 

5 

1 

4 

1 

2 

1 

2 

1 

2 

1 

1 

2 

1 

2 

1 

1 

1 

1 

1 

2 

1 

69 

58 

58 

225 

86 

140 

60 

68 

80 

70 

105 

90 

120 

120 

132 

115 

125 

90 

113 

68 

95 

50 

82 

55 

91 

58 

118 

60 

700 

333 

165 

225 

210 

510 

450 

270 

1,035 

511 

550 

525 

972 

701 

1,440 

1,380 

1,440 

1,371

810 

1,083 

788 

606 

1,005 

1,305 

1,015 

930 

840 

630 

116 

73 

71 

225 

89 

187 

95 

86 

110 

95 

136 

131 

146 

144 

173 

148 

171 

 134 

151 

109 

162 

99 

164 

103 

178 

102 

164 

88 

144 

78 

68 

- 

56 

153 

83 

67 

114 

82 

105 

111 

119 

113 

148 

138 

169 

153 

147 

141 

176 

119 

191 

133 

193 

124 

156 

98 

125 

106 

95 

0 

63 

81 

87 

77 

104 

86 

77 

84 

81 

78 

86 

93 

99 

114 

97 

127 

109 

120 

117 

129 

109 

121 

96 

111 

0.24 

0.42 

0.07 

0.07 

0.09 

0.04 

0.09 

0.17 

0.19 

0.20 

0.14 

0.18 

0.25 

0.90Χ 0.3964 

 

Cannot Test 

0.96 0.3158 

 

1.00 0.3200 

 

0.71 0.6896 

 

1.00 0.2705 

 

0.74 0.6465 

 

2.05 0.0004 

 

3.12 <0.0001 

 

1.80 0.0030 

 

1.84 0.0023 

 

4.23 <0.0001 

 

3.90 <0.0001 

 

3.81 <0.0001 

 

No 

No 

No 

No 

No 

No 

Yes 

Yes 

Yes 

Yes 

Yes 

Yes 

Yes 

a

b

- 

SD 

COV 

Source: 

Only data for individuals that spent >0 time outdoors and had 30 or more records are included in the analysis. 

The 2-sample Kolmogoroz-Smirnov (K-S) test H0 is that the distribution of variable 1 is the same as variable 2, using Dn

= 0.050. 

Data no avait lable. 

= Standard deviation. 

= Coefficient of variation (SD/mean × 100). 

Graham and McCurdy (2004). 

 (test statistic) and a χ

2 test statistic at α

1 

Chapter 16—Activity F

16-17

P

4

age

actors 

Exposure Factors Handbook 
 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-93. Time Spent (minutes/day) Indoors 

Based on CHAD Data (doers only)a 

Age Group N Time Spent Indoors COV (%) Participationb (%) Minimum Median Maximum Mean SD 

<1 month 121 490 1,380 1,440 1,336 137 10 100.0 

1 to 2 months 14 1,125 1,380 1,440 1,348 105 8 100.0 

3 to 5 months 115 840 1,385 1,440 1,359 93 7 100.0 

6 to 11 months 278 840 1,370 1,440 1,353 81 6 100.0 

1 year 668 315 1,350 1,440 1,324 107 8 100.0 

2 years 700 290 1,319 1,440 1,286 138 11 100.0 

3 to 5 years 1,977 23 1,307 1,440 1,276 136 11 100.0 

6 to 10 years 3,118 7 1,292 1,440 1,256 153 12 100.0 

11 to 15 years 1,939 69 1,300 1,440 1,255 160 13 99.8 

16 to 17 years 438 161 1,296 1,440 1,251 171 14 100.0 

18 to 20 years 485 512 1,310 1,440 1,242 180 15 100.0 

21 to 44 years 5,872 60 1,317 1,440 1,259 176 14 100.0 

45 to 64 years 3,073 23 1,320 1,440 1,262 172 14 100.0 

>64 years 1,758 600 1,350 1,440 1,310 141 11 100.0 a Only data for individuals that spent >0 time indoors and had 30 or more records are included in the analysis. b Participation rates or percent of sample days in the study spending some time (>0 minutes/day) indoors. The mean time spent indoors 

for the age group may be obtained by multiplying the participation rate (as a decimal) by the mean time shown above. 

N = Sample size. 

SD = Standard deviation. 

COV = Coefficient of variation (SD/mean × 100). 

Source: Graham and McCurdy (2004). 

Exposure Factors Handbook Page
 

November 2011 16-175 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-94. Time Spent (minutes/day) in Motor Vehicles 

Based on CHAD Data (doers only)a 

Age Group N Time Spent in Motor Vehicle COV (%) Participationb (%) Minimum Median Maximum Mean SD 

<1 month 80 2 68 350 86 68 79 66 

1 to 2 months 9 20 83 105 67 32 48 64 

3 to 5 months 75 13 60 335 71 49 69 65 

6 to 11 months 226 4 51 425 62 47 76 81 

1 year 515 1 52 300 67 50 76 77 

2 years 581 2 54 955 73 76 104 83 

3 to 5 years 1,702 1 55 1,389 70 70 99 86 

6 to 10 years 2,766 1 58 1,214 71 68 95 89 

11 to 15 years 1,685 1 60 825 76 74 97 87 

16 to 17 years 400 4 73 1,007 92 90 98 91 

18 to 20 years 449 4 76 852 109 106 98 93 

21 to 44 years 5,429 1 80 1,440 105 100 96 92 

45 to 64 years 2,739 1 75 1,357 102 105 103 89 

>64 years 1,259 4 60 798 86 85 99 72 a Only data for individuals that spent >0 time in motor vehicles and had 30 or more records are included in the analysis. b Participation rates or percent of sample days in the study spending some time (>0 minutes/day) in motor vehicles. The mean time spent 

in motor vehicles for the age group may be obtained by multiplying the participation rate (as a decimal) by the mean time shown 

above. 

N = Sample size. 

SD = Standard deviation. 

COV = Coefficient of variation (SD/mean × 100). 

Source: Graham and McCurdy (2004). 

Page Exposure Factors Handbook 

16-176 November 2011 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Exposure Factors Handbook Page
 

November 2011 16-177 

Table 16-95. Mean Time Spent (minutes/day) in Various Activity Categories, by Age—Weekday 

(children only) 

Activity Category 

2002–2003 1981–1982 

12 to 14 

6 to 8 years 9 to 11 years years 

15 to 17 

years 6 to 8 years 9 to 11 years 

12 to 14 

years 

15 to 17 

years 

Market work 

Household work 

Personal care 

Eating 

Sleeping, naps 

School 

Studying 

Church 

Visiting, socializing 

Sports 

Outdoor Activities 

Hobbies 

Art Activities 

Television 

Other passive leisure 

Playing 

Reading 

Being read to 

Computer activities 

Missing data 

0 

25 

68 

60 

607 

406 

29 

4 

16 

10 

6 

1 

8 

94 

9 

74 

11 

2 

6 

4 

0 

32 

66 

57 

583 

398 

39 

5 

25 

17 

6 

1 

7 

106 

10 

56 

12 

1 

10 

8 

1 

38 

68 

54 

542 

395 

49 

5 

25 

33 

4 

1 

7 

111 

24 

45 

11 

0 

25 

4 

22 

39 

73 

49 

515 

352 

50 

3 

53 

33 

6 

2 

4 

115 

39 

35 

7 

0 

38 

6 

-

15 

49 

81 

595 

292 

8 

9 

-

24 

9 

2 

4 

99 

-

111 

5 

-

-

-

-

18 

40 

73 

548 

315 

29 

9 

-

21 

8 

2 

3 

146 

-

65 

9 

-

-

-

-

27 

56 

69 

473 

344 

33 

9 

-

40 

7 

4 

3 

142 

-

31 

10 

-

-

-

28 

34 

60 

67 

499 

314 

33 

3 

-

46 

11 

6 

12 

108 

-

14 

12 

-

-

-

-

Source: 

Data not provided. 

Juster et al. (2004). 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-178 November 2011 

Table 16-96. Mean Time Spent (minutes/day) in Various Activity Categories, by Age—Weekend Day 

(children only) 

Activity Category 

2002–2003 1981–1982 

6 to 8 

years 

9 to 11 12 to 14 

years years 

15 to 17 

years 

6 to 8 

years 

9 to 11 

years 

12 to 14 

years 

15 to 17 

years 

Market work 

Household work 

Personal care 

Eating 

Sleeping, naps 

School 

Studying 

Church 

Visiting, socializing 

Sports 

Outdoor Activities 

Hobbies 

Art Activities 

Television 

Other passive leisure 

Playing 

Reading 

Being read to 

Computer activities 

Missing data 

0 

81 

78 

89 

666 

3 

5 

41 

61 

23 

12 

2 

11 

155 

14 

163 

14 

1 

12 

9 

0 

91 

72 

80 

644 

6 

9 

37 

66 

40 

12 

1 

7 

184 

15 

134 

15 

1 

19 

8 

9 

100 

73 

69 

633 

7 

20 

36 

58 

40 

12 

4 

9 

181 

40 

148 

13 

0 

39 

9 

39 

79 

77 

64 

629 

7 

24 

30 

91 

27 

11 

5 

6 

162 

54 

59 

7 

0 

58 

11 

-

27 

45 

80 

641 

-

2 

56 

-

30 

23 

5 

4 

136 

-

180 

9 

-

-

-

-

51 

44 

78 

596 

-

12 

53 

-

42 

39 

3 

4 

185 

-

92 

10 

-

-

-

-

72 

60 

68 

604 

-

15 

32 

-

51 

25 

8 

7 

169 

-

35 

10 

-

-

-

48 

60 

51 

65 

562 

-

30 

37 

-

37 

26 

3 

10 

157 

-

21 

18 

-

-

-

-

Source: 

Data not provided. 

Juster et al. (2004). 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-97. Mean Time Spent (minutes/week) in 

Various Activity Categories for Children, Ages 6 to 17 Years 

Activity Category 2002–2003 1981–1982 

Market work 53 126 

Household work 343 223 

Personal care 493 356 

Eating 426 508 

Sleeping, naps 4,092 3,758 

School 1,947 1,581 

Studying 238 158 

Church 94 125 

Visiting, socializing 287 132 

Sports 179 244 

Outdoor Activities 50 100 

Hobbies 12 27 

Art Activities 48 40 

Television 876 944 

Other passive leisure 166 39 

Playing 485 440 

Reading 77 69 

Being read to 5 3 

Computer activities 165 0 

Missing data 45 1,206 

Source: Juster et al. (2004). 

Exposure Factors Handbook Page
 

November 2011 16-179 
 

Table 16-98. Time Spent (minutes/2-day period) a inVarious Activities by Children Participating in 

the Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement (CDS) 

Age Group Boys (N = 1,444) Girls (N = 1,387) 

Meana Standard Deviation Meana Standard Deviation 

Television Use 

 1 to 5 years 

 6 to 8 years 

 9 to 12 years 

Electronic Game Use 

 1 to 5 years 

 6 to 8 years 

 9 to 12 years 

Computer Use 

 1 to 5 years 

 6 to 8 years 

 9 to 12 years b Print Use

 1 to 5 years 

 6 to 8 years 

 9 to 12 years 

Highly Active Activitiesc 

 1 to 5 years 

 6 to 8 years 

 9 to 12 years 

Moderately Active Activitiesd 

 1 to 5 years 

 6 to 8 years 

 9 to 12 years 

Sedentary Activitiese 

 1 to 5 years 

 6 to 8 years 

 9 to 12 years 

197 

263 

251 

8 

44 

57 

7 

13 

27 

21 

20 

19 

42 

107 

137 

55 

31 

40 

55 

75 

110 

168 

165 

185 

38 

113 

102 

28 

43 

71 

32 

37 

47 

74 

123 

149 

81 

65 

73 

71 

77 

109 

184 

239 

266 

5 

14 

18 

7 

8 

15 

23 

20 

29 

34 

62 

63 

59 

37 

46 

54 

80 

122 

163 

159 

194 

40 

39 

47 

35 

28 

43 

34 

32 

56 

78 

92 

88 

92 

69 

89 

71 

84 

111 a 

b 

c 

d 

e 

N 

Source: 

Means represent minutes spent in each activity over a 2-day period (1 weekday and 1 weekend day). 

Print use represents time spent using print media including reading and being read to. 

Includes all sport activities such as basketball, soccer, swimming, running or bicycling. 

Includes activities such as singing, camping, taking music lessons, fish ing, and boating. 

Includes activities such as playing board games, doing puzzles, talking on the phone, and relaxing. 

= Sample size. 

Vanderwater et al., 2004. 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-180 November 2011 
 

 

 

 

 

 

 

 

Chapter 16—Exposure Factors Handbook

Activity Factors

Exposure Factors Handbook PageNovember 2011 16-181

Table 16-99. Annual Average Time Spent (hours/day) on Various Activities According to Age, Race, Ethnicity, Marital Status, and Educational Level 

(ages 15 years and over) 

Characteristic Personal 

Carea 

Eating and 

Drinkingb 

Household 

Activityc 

Purchasing 

Goods and 

Servicesd 

Caring for and 

Helping 

Household 

Membere 

Caring for and 

Helping 

Non-Household 

Memberf 

Working on 

WorkRrelated 

Activityg 

Educational 

Activityh 

Organizational Civic 

and Religious 

Activityi 

Leisure and 

Sportj 

Telephone Call, 

Mail, and Emailk 

Other Activity 

Not Elsewhere 

Classifiedl 

Age (years) 

15+ 

15 to 19 

20 to 24 

25 to 34 

35 to 44 

45 to 54 

55 to 64 

65 to 74 

75+ 

9.41 

10.30 

9.64 

9.31 

9.12 

9.10 

9.19 

9.68 

9.83 

1.23 

1.07 

1.21 

1.19 

1.18 

1.17 

1.31 

1.44 

1.50 

1.79 

0.76 

1.05 

1.55 

1.87 

1.97 

2.11 

2.64 

2.32 

0.81 

0.56 

0.67 

0.81 

0.87 

0.82 

0.91 

0.93 

0.80 

0.53 

0.15 

0.51 

1.07 

0.98 

0.36 

0.16 

0.13 

0.12 

0.21 

0.21 

0.20 

0.12 

0.19 

0.24 

0.28 

0.30 

0.21 

3.75 

1.39 

4.23 

4.77 

4.96 

5.06 

3.80 

0.94 

0.34 

0.49 

3.29 

0.80 

0.39 

0.15 

0.09 

0.04 

0.05 

0.06 

0.30 

0.34 

0.21 

0.16 

0.30 

0.29 

0.39 

0.38 

0.43 

5.09 

5.40 

5.03 

4.30 

4.09 

4.52 

5.41 

6.97 

7.82 

0.19 

0.33 

0.19 

0.14 

0.13 

0.17 

0.18 

0.24 

0.30 

0.21 

0.22 

0.24 

0.17 

0.16 

0.20 

0.20 

0.29 

0.27 

Sex 

Male 

Female 

9.21 

9.59 

1.25 

1.22 

1.33 

2.23 

0.64 

0.96 

0.33 

0.71 

0.18 

0.24 

4.53 

3.02 

0.45 

0.53 

0.29 

0.31 

5.47 

4.72 

0.12 

0.26 

0.20 

0.22 

Race/Ethnicity 

White 

Black 

Hispanic/Latino 

9.30 

10.08 

9.67 

1.28 

0.87 

1.18 

1.85 

1.38 

1.85 

0.81 

0.75 

0.77 

0.53 

0.46 

0.60 

0.21 

0.20 

0.15 

3.76 

3.54 

3.92 

0.47 

0.43 

0.69 

0.29 

0.37 

0.23 

5.09 

5.49 

4.63 

0.18 

0.25 

0.13 

0.21 

0.18 

0.18 

Marital Status 

Married 

Other 

9.12 

9.75 

1.28 

1.18 

2.09 

1.43 

0.88 

0.72 

0.75 

0.25 

0.21 

0.22 

4.08 

3.34 

0.11 

0.94 

0.33 

0.27 

4.79 

5.45 

0.14 

0.25 

0.21 

0.20 

Education 

< High School grad 

HS grad, no college 

Some college 

BS or higher 

9.86 

9.42 

9.21 

8.94 

1.10 

1.19 

1.24 

1.41 

2.38 

2.05 

1.94 

1.77 

0.80 

0.76 

0.92 

0.91 

0.50 

0.46 

0.58 

0.71 

0.20 

0.25 

0.23 

0.18 

2.57 

3.58 

4.25 

4.72 

0.04 

0.07 

0.22 

0.22 

0.25 

0.28 

0.29 

0.37 

6.01 

5.57 

4.76 

4.33 

0.10 

0.15 

0.19 

0.22 

0.17 

0.21 

0.18 

0.23 

a Includes sleeping, bathing, dressing, health-related self-care, and personal and private activities. b Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent purchasing meals, snacks, or beverages. c Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and renovation. d Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair salons, barbershops, day spas, tanning salons), household services (e.g., 

housecleaning, lawn care and landscaping, pet care, dry cleaning, vehicle maintenance, construction), and government services (e.g., applying for food stamps, government required licenses, or paying fines). e Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading to child or adult, attending to health care needs, dropping off, picking up, or 

waiting for children). f Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with children, reading to child or adult, attending to health care needs, dropping off, 

picking up or waiting for children). Does not include activities done through a volunteer organization. g Includes time spent as part of the job, income-generating activities, or job search activities. Also includes travel time for work-related activities. h Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities, except sports. i Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through participating in religious or spiritual activities (e.g., church choir, youth groups, 

praying). j Includes sports, exercise, and recreation. This category is broken down into subcategories for the 15 to 19 years old age category. k Includes telephone use, mail, and e-mail. Does not include communications related to purchase of goods and services or those related to work or volunteering. l Includes residual activities that could not be coded or where information was missing. 

Source: DOL (2007). 
Exposure Factors Handbook 

Chapter 16 - Activity Factors
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 16-100. Annual Average Time Use by the U.S. Civilian Population, Ages 15 Years and Older 

hours/day 

Activity Total Male Female Weekday Weekend and Holiday 

Personal Carea 9.41 9.21 9.59 9.12 10.08 

sleeping 8.63 8.56 8.69 8.33 9.32 

Eating and Drinkingb 1.23 1.25 1.22 1.18 1.37 

Household Activitiesc 1.79 1.33 2.23 1.66 2.11 

housework 0.61 0.25 0.95 0.57 0.70 

food preparation/cleanup 0.53 0.29 0.75 0.51 0.57 

lawn and garden care 0.20 0.26 0.14 0.16 0.27 

household management 0.13 0.11 0.14 0.12 0.15 

Purchasing Goods and Servicesd 0.81 0.64 0.96 0.76 0.93 

consumer goods purchase 0.40 0.29 0.51 0.34 0.53 

professional/personal goods purchase 0.09 0.06 0.11 0.10 0.04 

Caring for and Helping Household Memberse 0.53 0.33 0.71 0.56 0.45 

caring for household children 0.41 0.24 0.57 0.43 0.37 

Caring for and Helping Non-Household Membersf 0.21 0.18 0.24 0.19 0.26 

caring for non-household adults 0.07 0.07 0.08 0.06 0.11 

Working on Work-related Activitiesg 3.75 4.53 3.02 4.77 1.36 

Working 3.40 4.10 2.74 4.33 1.23 

Educational Activitiesh 0.49 0.45 0.53 0.63 0.16 

attending classes 0.30 0.29 0.32 0.42 0.04 

homework and research 0.15 0.12 0.17 0.16 0.10 

Organizational Civic and Religious Activitiesi 0.30 0.29 0.31 0.20 0.53 

religious and spiritual activities 0.12 0.11 0.13 0.04 0.30 

volunteering (organizational and civic activities) 0.13 0.13 0.13 0.13 0.15 

Leisure and Sportsj 5.09 5.47 4.72 4.54 6.37 

socializing and communicating 0.76 0.71 0.80 0.60 1.11 

watching TV 2.58 2.80 2.36 2.35 3.10 

sports, exercise, recreation 0.28 0.38 0.18 0.26 0.33 

Telephone Calls, Mail, and E-mailk 0.19 0.12 0.26 0.20 0.17 

Other Activities not Elsewhere Classifiedl 0.21 0.20 0.22 0.20 0.22 a Includes sleeping, bathing, dressing, health-related self-care, and personal and private activities. b Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent 

purchasing meals, snacks, or beverages. c Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and 

renovation. d	 Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair 

salons, barbershops, day spas, tanning salons), household services (e.g., housecleaning, lawn care and landscaping, pet care, dry 

cleaning, vehicle maintenance, construction), and government services (e.g., applying for food stamps, government required licenses or 

paying fines). e	 Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading to 

child or adult, attending to health care needs, dropping off, picking up or waiting for children). f	 Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with 

children, reading to child or adult, attending to health care needs, dropping off, picking up or waiting for children). Does not include 

activities done through a volunteer organization. g Includes time spent as part of the job, income-generating activities, or job search activities. Also includes travel time for work-related 

activities. h Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities, 

except sports. i Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through 

participating in religious or spiritual activities (e.g., church choir, youth groups, praying). 

j Includes sports, exercise, and recreation. This category is broken down into subcategories for the 15 to 19 years old age category. k Includes telephone use, mail and e-mail. Does not include communications related to purchase of goods and services or those related to 

work or volunteering. l Includes residual activities that could not be coded or where information was missing. 

Source:	 DOL (2007). 

Page Exposure Factors Handbook 

16-16-182 November 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 16-101. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years 

Activity Male 

hours/day 

Female All 

Personal Carea 10.26 10.34 10.30 

Eating and Drinkingb 1.02 1.11 1.07 

Household Activities

c 0.61 0.92 0.76 

Purchasing Goods and Services

d 0.38 0.74 0.56 

Caring for and Helping Household Members

e 0.10 0.19 0.15 

Caring for and Helping Non-Household Members

f 0.20 0.23 0.21 

Working on Work-related Activities

g 1.53 1.24 1.39 

Educational Activities

h 3.08 3.51 3.29 

Organizational Civic and Religious Activities

i 0.34 0.33 0.34 

Leisure and Sports

j 6.02 4.75 5.40 

total leisure and sports – weekdays - - 4.85 

total leisure and sports – weekends - - 6.68 

sports, exercise, recreation – weekdays - - 0.58 

sports, exercise, recreation – weekends/holidays - - 0.69 

socializing and communicating – weekdays - - 0.76 

socializing and communicating, – weekends/holidays - - 1.32 

watching TV – weekdays - - 1.96 

watching TV – weekends/holidays - - 2.45 

reading – weekdays - - 0.11 

reading – weekends/holidays - - 0.11 

relaxing, thinking – weekdays - - 0.15 

relaxing, thinking – weekends/holidays - - 0.13 

playing games, computer use for leisure – weekdays - - 0.69 

playing games, computer use for leisure – weekends/holidays - - 1.00 

other sports/leisure including travel – weekdays - - 0.61 

other sports/leisure including travel – weekends/holidays - - 0.98 

Telephone Calls, Mail, and E-mail

k 0.24 0.42 0.33 

Other Activities not Elsewhere Classifiedl 0.23 0.21 0.22 a	 Includes sleeping, bathing, dressing, health-related self-care, and personal and private activities. b	 Includes time spent eating or drinking (except when identified as part of work or volunteer activity); does not include time spent

purchasing meals, snacks, or beverages. c	 Includes housework, cooking, yard care, pet care, vehicle maintenance and repair, home maintenance, repair, decoration, and renovation. d	 Includes purchase of consumer goods, professional (e.g., banking, legal, medical, real estate) and personal care services (e.g., hair salons, 

barbershops, day spas, tanning salons), household services (e.g., housecleaning, lawn care and landscaping, pet care, dry cleaning, 

vehicle maintenance, construction), and government services (e.g., applying for food stamps, government required licenses or paying 

fines). e	 Includes time spent caring or helping to care for child or adult household member (e.g., physical care, playing with children, reading to

child or adult, attending to health care needs, dropping off, picking up or waiting for children). f	 Includes time spent caring or helping to care for child or adult who is not a household member (e.g., physical care, playing with children, 

reading to child or adult, attending to health care needs, dropping off, picking up or waiting for children). Does not include activities

done through a volunteer organization. g	 Includes time spent as part of the job, income-generating activities, or job search activities. Also includes travel time for work-related

activities. h	 Includes taking classes, doing research and homework, registering for classes, and before and after school extra-curricular activities, 

except sports. i	 Includes time spent volunteering for or through civic obligations (e.g., jury duty, voting, attending town hall meetings), or through

participating in religious or spiritual activities (e.g., church choir, youth groups, praying). j	 Includes sports, exercise, and recreation. This category is broken down into subcategories for the 15 to 19 years old age category. k	 Includes telephone use, mail and e-mail. Does not include communications related to purchase of goods and services or those related to

work or volunteering. l	 Includes residual activities that could not be coded or where information was missing. 

Source:	 DOL (2007). 

Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-183 
 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Page Exposure Factors Handbook 

16-184 November 2011 

Table 16-102. Mean Time Spent (minutes/day) in Moderate toVigorous Physical Activity 

(children only) 

Weekday Weekend 

Age (years) Number of Participants Mean (SD) Mean (SD) 

Boys Girls Boys Girls Both Boys Girls Both 

9 555 543 190.8(53.2) 173.3(46.6) 181.8(50.6) 184.3(68.6) 173.3(64.3) 178.6(66.6) 

11 544 540 133.0(42.9) 115.6(36.3) 124.1(40.6) 127.1(59.5) 112.6(53.2) 119.7(56.8) 

12 532 532 105.3(40.2) 86.0(32.5) 95.6(37.8) 93.4(55.3) 73.9(45.8) 83.6(51.7) 

15 503 506 58.2(31.8) 38.7(23.6) 49.2(29.9) 43.2(38.0) 25.5(23.3) 35.1(33.3) 

SD = Standard deviation.
 

Source: Nader et al. (2008).
 

Table 16-103. Occupational Tenure of Employed Individualsa by Age and Sex 

Age Group Median Tenure (years) 

(years) N All Workers N Men N Women 

16 to 24 19,090 1.9 9,520 2.0 9,270 1.9 

25 to 29 16,326 4.4 8,974 4.6 7,353 4.1 

30 to 34 15,833 6.9 8,971 7.6 6,863 6.0 

35 to 39 14,674 9.0 8,109 10.4 6,565 7.0 

40 to 44 11,871 10.7 6,463 13.8 5,408 8.0 

45 to 49 9,350 13.3 5,208 17.5 4,152 10.0 

50 to 54 7,684 15.2 4,341 20.0 3,343 10.8 

55 to 59 6,914 17.7 4,006 21.9 2,908 12.4 

60 to 64 4,500 19.4 2,673 23.9 1,827 14.5 

65 to 69 1,692 20.1 1,000 26.9 692 15.6 

70 and older 1,146 21.9 678 30.5 467 18.8 

Total 109,090 6.6 60,242 7.9 41,949 5.4 a Working population = 109.1 million persons. 

N = Number of individuals. 

Source: Carey (1988). 
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Exposure Factors Handbook Page
 

November 2011 16-185 

Table 16-104. Occupational Tenure for Employed Individualsa Grouped by Sex and Race 

Median Tenure (years) 

All Individuals 

Race N N Men N Women 

White 95,044 6.7 53,096 8.3 41,949 5.4 

Black 10,851 5.8 5,447 5.8 5,404 5.8 

Hispanic 7,198 4.5 4,408 5.1 2,790 3.7 a 

 Working population = 109.1 million persons. 

N = Number of individuals. 

Source: Carey (1988). 

 

Table 16-105. Occupational Tenure for Employed Individualsa Grouped by Sex and Employment Status 

Median Tenure (years) 

Employment 

Status N All Individuals N Men N Women 

Full-Time 93,665 7.2 55,464 8.4 38,201 5.9 

Part-Time 15,425 3.1 4,778 2.4 10,647 3.6 a Working population = 109.1 million persons. 

N = Number of individuals. 

Source: Carey (1988). 

 

 

 

Table 16-106. Occupational Tenure of Employed Individualsa Grouped by Major Occupational Groups and Age 

Median Tenure (years) 

Age Group (years) 

Occupational Group Totalb 16–24 25–34 35–44 45–54 55–64 65+ 

Executive, Administrative, and Managerial 8.4 2.4 5.6 10.1 15.1 17.9 26.3 

Professional Specialty 9.6 2.0 5.7 12.0 18.2 25.6 36.2 

Technicians and Related Support 6.9 2.2 5.7 10.9 17.7 20.8 22.2 

Sales Occupations 5.1 1.7 4.7 7.7 10.5 15.5 21.6 

Administrative Support, including Clerical 5.4 2.1 5.0 7.6 10.9 14.6 15.4 

Service Occupations 4.1 1.7 4.4 6.9 9.0 10.6 10.4 

Precision Production, Craft, and Repair 9.3 2.6 7.1 13.5 19.9 25.7 30.1 

Operators, Fabricators, and Laborers 5.5 1.7 4.6 9.1 13.7 18.1 14.7 

Farming, Forestry, and Fishing 10.4 2.9 7.9 13.5 20.7 30.5 39.8 a Working population = 109.1 million persons. b Includes all workers 16 years and older. 

Source: Carey (1988). 
 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-107. Voluntary Occupational Mobility Rates for Workersa Age 16 Years and Older 

Age Group (years) Occupational Mobility Rateb 

(percent) 

16 to 24 12.7 

25 to 34 6.6 

35 to 44 4.0 

45 to 54 1.9 

55 to 64 1.0 

64 and older 0.3 

Total, age 16 and older 5.3 a Working population = 100.1 million persons. b Occupational mobility rate = percentage of persons employed in an occupation who had voluntarily entered it from 

another occupation. 

Source: Carey (1990). 

Page Exposure Factors Handbook 

16-186 November 2011 
 

Chapter 16—Exposure Factors Handbook

Activity Factors

Exposure Factors Handbook PageNovember 2011 16-187

Table 16-108. Descriptive Statistics for Residential Occupancy Period (years) 

Percentiles 

N Mean 5th 10th 25th 50th 75th 90th 95th 98th 99th 99.5th 99.8th 99.9th 

2nd Largest 

Value Max. 

Both sexes 500,000 11.7 2 2 3 9 16 26 33 41 47 51 55 

Male only 244,274 11.1 2 2 4 8 15 24 31 39 44 48 53 

Female only 255,726 12.3 2 2 5 9 17 28 35 43 49 53 58 

59 

56 

61 

75 

73 

75 

87 

73 

87 

N = Number of simulated persons. 

Source: Johnson and Capel (1992).
Exposure Factors Handbook 

Chapter 16—Activity Factors 

Page Exposure Factors Handbook 

16-188 November 2011 

Table 16-109. Descriptive Statistics for Both Sexes by Current Age 

Current 

Age, Years 

Residential Ooccupancy Period (years) 

Mean 

Percentiles 

25 50 75 90 95 99 

3 

6 

9 

12 

15 

18 

21 

24 

27 

30 

33 

36 

39 

42 

45 

48 

51 

54 

57 

60 

63 

66 

69 

72 

75 

78 

81 

84 

87 

90 

All ages 

6.5 

8.0 

8.9 

9.3 

9.1 

8.2 

6.0 

5.2 

6.0 

7.3 

8.7 

10.4 

12.0 

13.5 

15.3 

16.6 

17.4 

18.3 

19.1 

19.7 

20.2 

20.7 

21.2 

21.6 

21.5 

21.4 

21.2 

20.3 

20.6 

18.9 

11.7 

3 

4 

5 

5 

5 

4 

2 

2 

3 

3 

4 

5 

5 

6 

7 

8 

9 

9 

10 

11 

11 

12 

12 

13 

13 

12 

11 

11 

10 

8 

4 

5 

7 

8 

9 

8 

7 

4 

4 

5 

6 

7 

8 

9 

11 

13 

14 

15 

16 

17 

18 

19 

20 

20 

20 

20 

19 

20 

19 

18 

15 

9 

8

10

12

13

12

11

8

6

8

9

11

13

15

18

20

22

24

25

26

27

27

28

29

29

29

29

29

28

29

27

16 

13

15

16

16

16

16

13

11

12

14

17

21

24

27 

31 

32 

33 

34 

35 

35 

36 

36 

37 

37 

38 

38 

39 

37 

39 

40 

26 

17

18

18

18

18

19

17

15

16

19

23

28

31

35 

38 

39 

39 

40 

41 

40 

41 

41 

42 

43 

43 

44 

45 

44 

46 

47 

33 

22 

22 

22 

23 

23 

23 

23 

25 

27 

32 

39 

47 

48 

49 

52 

52 

50 

50 

51 

51 

51 

50 

50 

53 

53 

53 

55 

56 

57 

56 

47 

Source: Johnson and Capel (1992). 
 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-110. Residence Time of Owner/Renter Occupied Units 

Year Household Moved Into Unit Total Occupied Units (number in thousands) 

2005–2009 33,543 

2000–2004 28,695 

1995–1999 15,120 

1990–1994 9,631 

1985–1989 6,459 

1980–1984 3,703 

1975–1979 4,412 

1970–1974 2,979 

1960–1969 3,661 

1950–1959 1,892 

1940–1949 460 

1939 or earlier 137 

Total 110,692 

Source: U.S. Census Bureau (2008a). 

Table 16-111. Percent of Householders Living in Houses for Specified Ranges of Time, and Statistics for Years 

Lived in Current Home 

Years Lived in Current Home Percent of Total Households 

0–4 

5–9 

10–14 

15–19 

20–24 

25–29 

30–34 

35–44 

45–54 

55–64 

65–74 

>75 

30.3 

25.9 

13.7 

8.7 

5.8 

3.3 

4.0 

2.7 

3.3 

1.7 

0.4 

0.1 

Totala

99.9 

Statistics for Years Lived in Current Home 

N Meanb 50th Percentileb 90th Percentileb 95th Percentileb 99th Percentileb 

110,692 13 8 32 46 62 

a Total does not equal 100 due to rounding errors. b The mean, 50th and 90th percentiles were calculated for the number of years lived in current house by apportioning 

the total sample size (110,692 households) to the indicated percentile associated with the applicable range of years 

lived in the current home, assuming an even distribution. 

Source: Adapted from U.S. Census Bureau (2008a). 

Exposure Factors Handbook Page
 

November 2011 16-189 
Exposure Factors Handbook 

Chapter 16—Activity Factors
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 16-112. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group in 

Surveya
 

Average Total Residence Average Current R Households (percent) esidence 

Households Time SD TCR (years) 

T (years) ST 1985 1987 

All households 4.55 ± 0.60 8.68 10.56 ± 0.10 100.0 100.0
 

Renters 2.35 ± 0.14 4.02 4.62 ± 0.08 36.5 36.0
 

Owners 11.36 ± 3.87 13.72 13.96 ± 0.12 63.5 64.0
 

Farms 17.31 ± 13.81 18.69 18.75 ± 0.38 2.1 1.9
 

Urban 4.19 ± 0.53 8.17 10.07 ± 0.10 74.9 74.5
 

Rural 7.80 ± 1.17 11.28 12.06 ± 0.23 25.1 25.5
 

Northeast region 7.37 ± 0.88 11.48 12.64 ± 0.12 21.2 20.9
 

Midwest region 5.11 ± 0.68 9.37 11.15 ± 0.10 25.0 24.5
 

South region 3.96 ± 0.47 8.03 10.12 ± 0.08 34.0 34.4
 

West region 3.49 ± 0.57 6.84 8.44 ± 0.11 19.8 20.2
 

a Values of the average current residence time, TCR, are given for comparison. 

Source: Israeli and Nelson (1992). 

 

 

 

Table 16-113. Total Residence Time, T (years), Corresponding to Selected Values of R(t)a by Housing 

Category 

R(t) = 0.05 0.1 0.25 0.5 0.75 

All households 23.1 12.9 3.7 1.4 0.5 

Renters 8.0 5.2 2.6 1.2 0.5 

Owners 41.4 32.0 17.1 5.2 1.4 

Farms 58.4 48.3 26.7 10.0 2.4 

Urban 21.7 10.9 3.4 1.4 0.5 

Rural 32.3 21.7 9.1 3.3 1.2 

Northeast region 34.4 22.3 7.5 2.8 1.0 

Midwest region 25.7 15.0 4.3 1.6 0.6 

South region 20.7 10.8 3.0 1.2 0.4 

West region 17.1 8.9 2.9 1.2 0.4 

a R(t) = fraction of households living in the same residence for T years or more. 

Source: Israeli and Nelson (1992). 

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16-190 November 2011 
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November 2011 16-191 

 

 

 

Exposure Factors Handbook 

Chapter 16—Activity Factors
 

Table 16-114. Summary of Residence Time of Recent Home Buyers (1993) 

Number of Years Lived in Previous House Percent of Respondents 

1 year or less 

2–3 

4–7 

8–9 

10 years or more 

2 

16 

40 

10 

32 

Source: NAR (1993). 

Table 16-115. Tenure in Previous Home (percentage distribution) 

1987 1989 1991 1993 

Percent 

1 year or less 

2–3 Years 

4–7 Years 

8–9 Years 

10 or More Years 

5 

25 

36 

10 

24 

8 

15 

22 

11 

34 

4 

21 

37 

9 

29 

2 

16 

40 

10 

32 

Total 100 100 100 100 

Years 

Median 6 6 6 6 

Source: NAR (1993). 

Table 16-116. Number of Miles Moved (percentage distribution) 

All Buyers 

First-Time Buyer Repeat Buyer New Home Buyer Existing Home 

Buyer 

Mile Percent 

Less than 5 miles 

5–9 miles 

10–19 miles 

20–34 miles 

35–50 miles 

51–100 miles 

Over 100 miles 

29 

20 

18 

9 

2 

5 

17 

33 

25 

20 

11 

2 

2 

6 

27 

16 

17 

8 

2 

6 

24 

23 

18 

20 

12 

2 

6 

19 

31 

20 

17 

9 

3 

4 

16 

Total 100 100 100 100 100 

Miles 

Median 9 8 11 11 8 

Mean 200 110 270 230 190 

Source: NAR (1993). 
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Table 16-117. General Mobility, by Race and Hispanic Origin, Region, Sex, Age, Educational Attainment, Marital Status, Nativity, Tenure, 

and Poverty Level: 2006−2007 (numbers in thousands) 

Different County, Different State, Different Division, Different 

Total Mover Same County Same State Same Division Same Region Region Abroad 

% % % % % % % 

Population N N (of total) N (of movers) N (of movers) N (of movers) N (of movers) N (of movers) N (of movers) 

Total 1+ years 292,749 38,681 13% 25,192 65% 7,436 19% 1,446 4% 968 3% 2,448 6% 1,191 3% 

Sex 

Male 143,589 19,457 14% 12,579 65% 3,693 19% 771 4% 505 3% 1,220 6% 689 4% 

Female 149,160 19,224 13% 12,613 66% 3,743 19% 675 4% 463 2% 1,228 6% 502 3% 

Age (years) 

1 to 4 years 16,455 3,217 20% 2,188 68% 577 18% 117 4% 81 3% 184 6% 72 2% 

5 to 9 years 19,830 3,161 16% 2,092 66% 614 19% 121 4% 73 2% 179 6% 81 3% 

10 to 14 years 20,444 2,517 12% 1,735 69% 441 18% 92 4% 62 2% 139 6% 47 2% 

15 to 17 years 13,297 1,465 11% 1,057 72% 224 15% 50 3% 22 2% 75 5% 37 3% 

18 to 19 years 7,873 1,330 17% 898 68% 252 19% 40 3% 25 2% 68 5% 47 4% 

20 to 24 years 20,532 5,516 27% 3,623 66% 1,069 19% 168 3% 157 3% 320 6% 179 3% 

25 to 29 years 20,666 5,316 26% 3,335 63% 1,061 20% 219 4% 136 3% 339 6% 226 4% 

30 to 34 years 19,202 3,767 20% 2,374 63% 789 21% 140 4% 106 3% 221 6% 137 4% 

35 to 39 years 20,907 2,962 14% 1,877 63% 587 20% 104 4% 84 3% 187 6% 121 4% 

40 to 44 years 21,856 2,456 11% 1,567 64% 480 20% 102 4% 60 2% 178 7% 68 3% 

45 to 49 years 22,643 1,963 9% 1,362 69% 304 15% 74 4% 42 2% 131 7% 49 2% 

50 to 54 years 20,819 1,612 8% 1,119 69% 292 18% 55 3% 42 3% 76 5% 27 2% 

55 to 59 years 18,221 1,171 6% 706 60% 258 22% 57 5% 37 3% 86 7% 27 2% 

60 to 61 years 6,093 381 6% 212 56% 82 22% 30 8% 9 2% 39 10% 10 3% 

62 to 64 years 7,877 386 5% 201 52% 98 25% 19 5% 1 0% 49 13% 18 5% 

65 to 69 years 10,629 496 5% 286 58% 110 22% 16 3% 5 1% 63 13% 16 3% 

70 to 74 years 8,369 357 4% 179 50% 79 22% 24 7% 17 5% 43 12% 15 4% 

75 to 79 years 7,567 233 3% 153 66% 41 18% 4 2% 6 3% 21 9% 7 3% 

80 to 84 years 5,513 219 4% 121 55% 53 24% 10 5% 4 2% 26 12% 5 2% 

85+ years 3,958 159 4% 108 68% 24 15% 2 1% - - 22 14% 3 2% 

Educational Attainment 

Not a high school graduate 27,742 3,458 12% 2,431 70% 575 17% 103 3% 33 1% 137 4% 178 5% 

High school graduate 61,490 6,435 10% 4,398 68% 1,207 19% 221 3% 145 2% 353 5% 112 2% 

Some college or AA degree 49,243 5,534 11% 3,475 63% 1,167 21% 206 4% 145 3% 411 7% 130 2% 

Bachelor's degree 36,658 4,062 11% 2,290 56% 910 22% 231 6% 124 3% 336 8% 172 4% 

Prof or graduate degree 19,184 1,985 10% 1,004 51% 399 20% 97 5% 102 5% 246 12% 137 7% 

Persons age 1 to 24 98,431 17,205 17% 11,593 67% 3,177 18% 589 3% 419 2% 965 6% 462 3% 
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Table 16-117. General Mobility, by Race and Hispanic Origin, Region, Sex, Age, Educational Attainment, Marital Status, Nativity, Tenure, and 

Poverty Level: 2006−2007 (numbers in thousands) (continued)
 Different County, Different State, Different Division, Different 

Total Mover Same County Same State Same Division Same Region Region Abroad 

% % % % % % % 

Population N N (of total) N (of movers) N (of movers) N (of movers) N (of movers) N (of movers) N (of movers) 

Marital Status 

Married, spouse present 121,390 10,671 9% 6,434 60% 2,220 21% 502 5% 338 3% 808 8% 369 3% 

Married, spouse absent 3,472 805 23% 501 62% 90 11% 31 4% 11 1% 73 9% 98 12% 

Widowed 13,920 802 6% 533 66% 136 17% 34 4% 8 1% 68 8% 22 3% 

Divorced 22,867 3,483 15% 2,369 68% 702 20% 93 3% 69 2% 200 6% 50 1% 

Separated 5,047 1,246 25% 911 73% 213 17% 29 2% 16 1% 57 5% 19 2% 

Never married 69,324 12,779 18% 8,429 66% 2,442 19% 427 3% 310 2% 739 6% 433 3% 

Persons age 1 to 14 56,730 8,895 16% 6,015 68% 1,632 18% 330 4% 216 2% 502 6% 200 2% 

Nativity 

Native 255,501 33,023 13% 21,603 65% 6,671 20% 1,279 4% 904 3% 2,180 7% 387 1% 

Foreign born 37,248 5,658 15% 3,589 63% 765 14% 167 3% 64 1% 268 5% 804 14% 

Naturalized US citizen 14,525 1,161 8% 768 66% 212 18% 41 4% 31 3% 76 7% 31 3% 

Not a US citizen 22,723 4,497 20% 2,821 63% 553 12% 126 3% 33 1% 192 4% 772 17% 

Tenure 

Owner-occupied housing 

unit 207,774 13,760 7% 8,467 62% 2,881 21% 595 4% 408 3% 1,027 7% 381 3% 

Renter-occupied housing 

unit 81,351 24,228 30% 16,353 67% 4,374 18% 806 3% 547 2% 1,371 6% 776 3% 

No cash renter-occupied 

housing unit 3,624 694 19% 372 54% 181 26% 45 6% 13 2% 49 7% 33 5% 

Poverty Status 

Below 100% of poverty 35,924 8,777 24% 6,041 69% 1,484 17% 270 3% 166 2% 392 4% 423 5% 

100% to 149% of poverty 26,183 4,705 18% 3,312 70% 832 18% 128 3% 84 2% 215 5% 136 3% 

150% of poverty and above 230,642 25,199 11% 15,839 63% 5,120 20% 1,048 4% 718 3% 1,841 7% 632 3% 

- Represents 0 or rounds to 0. 

N = Number of respondents. 

Source: U.S. Census Bureau (2008b). 
 

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Table 16-118. Distance of Intercounty Movea, by Sex, Age, Race and Hispanic Origin, Educational Attainment, Marital Status,
 

Nativity, Tenure, Poverty Status, Reason for Move, and State of Residence 1 Year Ago: 2006 to 2007
 

(numbers in thousands)
 

Total Less than 50 miles 50 to 199 miles 200 to 499 miles 500 miles or more 

Population N N % N % N % N % 

Intercounty Movers 1+ years 12,299 5,149 42% 2,582 21% 1,802 15% 2,765 22% 

Sex 

Male 6,190 2,554 41% 1,324 21% 894 14% 1,418 23% 

Female 6,109 2,595 42% 1,258 21% 909 15% 1,347 22% 

Age 

Under 16 years 2,809 1,230 44% 520 19% 455 16% 603 21% 

16 to 19 years 629 279 44% 148 24% 82 13% 120 19% 

20 to 24 years 1,714 720 42% 436 25% 185 11% 373 22% 

25 to 29 years 1,755 792 45% 347 20% 215 12% 400 23% 

30 to 44 years 3,040 1,295 43% 618 20% 458 15% 669 22% 

45 to 64 years 1,782 633 36% 408 23% 312 18% 429 24% 

65 to 74 years 357 128 36% 68 19% 66 18% 95 27% 

75+ years 213 71 33% 37 17% 30 14% 76 36% 

Race and Hispanic Origin 

White alone 9,730 4,049 42% 2,064 21% 1,382 14% 2,234 23% 

Black or African American alone 1,626 729 45% 285 18% 320 20% 293 18% 

Asian alone 515 205 40% 120 23% 51 10% 138 27% 

All remaining single races and all race combinationsb 427 166 39% 113 26% 49 11% 99 23% 

White alone, not Hispanic or Latino 8,290 3,527 43% 1,697 20% 1,156 14% 1,910 23% 

Hispanic or Latinoc 1,575 578 37% 401 25% 232 15% 364 23% 

White alone or in combination with 1 or more other 

races 9,986 4,161 42% 2,130 21% 1,405 14% 2,290 23% 

Black or African American alone or in combination 

with 1 or more other races 1,733 777 45% 312 18% 329 19% 315 18% 

Asian alone or in combination with 1 or more other 

races 573 223 39% 146 25% 59 10% 144 25% 
 

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Table 16-118. Distance of Intercounty Movea, by Sex, Age, Race and Hispanic Origin, Educational Attainment, Marital Status,
 

Nativity, Tenure, Poverty Status, Reason for Move, and State of Residence 1 Year Ago: 2006 to 2007 (numbers in thousands)
 

(continued) 

Total Less than 50 miles 50 to 199 miles 200 to 499 miles 500 miles or more 

Population N N % N % N % N % 

Educational Attainment 

Not a high school graduate 848 390 46% 197 23% 126 15% 135 16% 

High school graduate 1,926 776 40% 414 21% 351 18% 385 20% 

Some college or AA degree 1,929 836 43% 376 19% 254 13% 463 24% 

Bachelor's degree 1,601 651 41% 340 21% 210 13% 400 25% 

Prof. or graduate degree 844 268 32% 151 18% 140 17% 286 34% 

Persons age 1 to 24 5,151 2,229 43% 1,104 21% 721 14% 1,096 21% 

Marital Status 

Married, spouse present 3,868 1,500 39% 834 22% 560 14% 975 25% 

Married, spouse absent 206 57 28% 44 21% 31 15% 74 36% 

Widowed 246 78 32% 60 24% 45 18% 63 26% 

Divorced 1,065 493 46% 221 21% 158 15% 193 18% 

Separated 316 146 46% 57 18% 66 21% 47 15% 

Never married 3,917 1,691 43% 867 22% 517 13% 843 22% 

Persons age 1 to 14 2,680 1,184 44% 500 19% 426 16% 570 21% 

Nativity 

Native 11,034 4,627 42% 2,299 21% 1,646 15% 2,462 22% 

Foreign born 1,265 523 41% 283 22% 156 12% 303 24% 

Naturalized U.S. citizen 361 156 43% 63 17% 45 12% 96 27% 

Not a US citizen 904 367 41% 220 24% 111 12% 206 23% 

Tenure 

Owner-occupied housing unit 4,912 2,083 42% 950 19% 742 15% 1,137 23% 

Renter-occupied housing unit 7,099 2,962 42% 1,554 22% 1,019 14% 1,564 22% 

No cash renter-occupied housing unit 288 104 36% 78 27% 41 14% 64 22% 

Poverty Status 

Below 100% of poverty 2,313 967 42% 576 25% 353 15% 417 18% 

100% to 149% of poverty 1,258 625 50% 245 19% 176 14% 212 17% 

150% of poverty and above 8,728 3,558 41% 1,761 20% 1,274 15% 2,136 24% 
 

 

 

 

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Table 16-118. Distance of Intercounty Movea, by Sex, Age, Race and Hispanic Origin, Educational Attainment, Marital Status,
 

Nativity, Tenure, Poverty Status, Reason for Move, and State of Residence 1 Year Ago: 2006 to 2007 (continued)
 

(numbers in thousands)
 

Total Less than 50 miles 50 to 199 miles 200 to 499 miles 500 miles or more 

Population N N % N % N N % N 

State of Residence 1 Year Ago 

Same state 7,436 4,741 64% 2,059 28% 627 8% 9 0% 

Different state 4,862 408 8% 524 11% 1,175 24% 2,756 57% 

a The estimated distance in miles of an intercounty move is measured from the county of previous residence's geographic population centroid 

to the county of current residence's geographic population centroid. b Includes American Indian and Alaska Native alone, Native Hawaiian and Other Pacific Islander alone, and 2 or More Races. 

Hispanics or Latinos may be of any race. 

Source: U.S. Census Bureau (2008b). 

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Exposure Factors Handbook 

Chapter 17—Consumer Products 

17. CONSUMER PRODUCTS 

17.1. INTRODUCTION 

17.1.1. Background 

Consumer products may contain toxic or 

potentially toxic chemical constituents to which 

people may be exposed as a result of their use. For 

example, household cleaners can contain ammonia, 

alcohols, acids, and/or organic solvents that may pose 

health concerns. Potential routes of exposure to 

consumer products or chemicals released from 

consumer products during use include ingestion, 

inhalation, and dermal contact. These household 

consumer products include cleaners, solvents, and 

paints. Non-users, including children, can be 

passively exposed to chemicals in these products. 

Because people spend a large amount of time 

indoors, the use of household chemicals in the indoor 

environment can be a principal source of exposure 

(Franklin, 2008). 

Very little information is available about the exact 

way the different kinds of products are used by 

consumers, including the many ways in which these 

products are handled, the frequency and duration of 

contact, and the measures consumers may take to 

minimize exposure or risk (Steenbekkers, 2001). In 

addition, the factors that influence these behaviors 

are not well studied, but some studies have shown 

that a large variation exists in behavior between 

persons (Steenbekkers, 2001). 

This chapter presents information on the amount 

of product used, the frequency of use, and the 

duration of use for various consumer products 

typically found in consumer households. All tables 

that present information for these consumer products 

are located at the end of this chapter. 

Note that this chapter does not provide an 

exhaustive treatment of all consumer products, but 

rather, it provides some background and data that can 

be used in an exposure assessment. Also, the data 

presented may not capture the information needed to 

assess the highly exposed population (i.e., consumers 

who use commercial and industrial strength products 

at home). The studies presented in the following 

sections represent readily available surveys for which 

data were collected on the frequency and duration of 

use and the amount of use of cleaning products, 

painting products, household solvent products, 

cosmetic and other personal care products, household 

equipment, pesticides, and tobacco. Also note that 

some of the data in this chapter comes from 

corporate, consortia, or trade organizations. 

17.1.2. Additional Sources of Information 

There are several sources of information on data 

relevant to consumer products. Table 17-1 provides a 

list of household consumer products found in some 

U.S. households (U.S. EPA, 1987). It should be 

noted, however, that this list was compiled by the 

U.S. Environmental Protection Agency (EPA) in 

1987, and consumer use of some products listed may 

have changed (e.g., aerosol product use has declined). 

Therefore, refer to the Household Product Database 

of the National Library of Medicine database as a 

source of more current information on the types of 

products used. This database contains over 7,000 

consumer brands including auto products; products 

used inside the home; pesticides; landscape and yard; 

personal care; home maintenance, arts, and crafts; pet 

care; and home office. The information includes 

chemical ingredients, specific brands that contain 

those ingredients, and acute and chronic health 

effects associated with specific ingredients. The 

database does not contain any information on 

frequency or amount of product used. 

The Soaps and Detergent Association (SDA) 

developed a peer-reviewed document that presents 

methodologies and specific exposure information that 

can be used for screening-level risk assessments from 

exposures to high production volume chemicals. The 

document addresses the use of consumer products, 

including laundry, cleaning, and personal care 

products. It includes data for daily frequency of use 

and the amount of product used. The data used were 

compiled from a number of sources including 

cosmetic associations and data from the SDA. The 

document Exposure and Risk Screening Methods for 

Consumer Product Ingredients can be found on the 

SDA Web site at http://www.cleaning101.com/files/ 

Exposure_and_Risk_Screening_Methods_for_Consu 

mer_Product_Ingredients.pdf. 

Another document has been developed by the 

U.S. EPA Office of Toxic Substances (1986a, b): 

Standard Scenarios for Estimating Exposure to 

Chemical Substances During Use of Consumer 

Products – Volumes I and II. This document presents 

data and supporting information required to assess 

consumer exposure to constituents in household 

cleaners and components of adhesives. Its 

information includes a description of standard 

scenarios selected to represent upper bound 

exposures for each product. Values also are presented 

for parameters needed to estimate exposure for 

defined exposure routes and pathways assumed for 

each scenario. 

An additional reference is the Simmons Market 

Research Bureau’s (SMRB’s) Simmons Study of 

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Chapter 17—Consumer Products 

Media and Markets. This document provides an

example of available marketing data that may be

useful in assessing exposure to selected products. The 

report is published biannually. Data are collected on 

the buying habits of the U.S. population during the 

previous 12 months for more than 1,000 consumer 

products. Data are presented on frequency of use, 

total number of buyers in each use category, and

selected demographics. The consumer product data 

are presented according to the buyer and not

necessarily according to the user (i.e., actively

exposed person). Therefore, it may be necessary to 

adjust the data to reflect potential uses. The reports 

are available for purchase from the SMRB. Table 

17-2 presents a list of product categories in the 

Simmons Study of Media and Markets for which

information is available. 

17.2. RECOMMENDATIONS 

Because of the large range and variation among 

consumer products and their exposure pathways, it is 

not feasible to recommend specific exposure values 

as has been done in other chapters of this handbook. 

Refer to the information provided by the references 

of this chapter to derive appropriate exposure factors. 

The following sections of this chapter provide

summaries of data from surveys involving the use of 

consumer products. 

17.3. CONSUMER PRODUCTS USE STUDIES 

17.3.1. CTFA (1983)—Cosmetic, Toiletry, and 

Fragrance Association, Inc.—Summary 

of Results of Surveys of the Amount and 

Frequency of Use of Cosmetic Products 

by Women 

The Cosmetic, Toiletry, and Fragrance

Association, Inc. (CTFA, 1983), a major

manufacturer and a market research bureau,

published three surveys that collected data on the

frequency of use of various cosmetic products and 

selected baby products. In the first survey, CTFA

(1983) conducted a 1-week prospective survey of

47 female employees and relatives of employees

between ages 13 and 61 years. In the second survey, a 

cosmetic manufacturer conducted a retrospective

survey of 1,129 of its customers. In the third survey, a 

market research bureau sampled 19,035 female

consumers nationwide over a 91⁄2-month period. Of 

the 19,035 females interviewed, responses from only 

9,684 females were tabulated (CTFA, 1983). The 

respondents in all three surveys were asked to record 

the number of times they used the various products in 

a given time period (i.e., a week, a day, a month, or a 

year). The third survey also was designed to reflect 

the socio-demographic (e.g., age, income)

characteristics of the entire U.S. population. 

To obtain the average frequency of use for each 

cosmetic product, responses were averaged for each 

product in each survey. Averages were calculated by 

adding the reported number of uses per given time 

period for each product, dividing by the total number 

of respondents in the survey, and then dividing again 

by the number of days in the given time period 

(CTFA, 1983). The average frequency of use of 

cosmetic products was determined for both users and 

non-users. The frequency of use of baby products 

was determined among users only. The upper

90th percentile frequency of use values were 

determined by eliminating the top 10% most extreme 

frequencies of use. Therefore, the highest remaining 

frequency of use was recorded as the upper

90th percentile value. Table 17-3 presents the amount 

of product used per application (grams) and the 

average and 90th percentile frequency of use per day 

for various cosmetic products for all the surveys. 

Note that Table 17-3 reports values provided by 

cosmetic companies, associations, or market research 

firms. 

An advantage of the frequency data obtained from 

the third survey (by the market research bureau) is 

that the sample population was more likely to be 

representative of the U.S. population. Another 

advantage of the third data set is that the survey was 

conducted over a longer period of time when

compared with the other two frequency datasets. 

Also, the study provided empirical data that may be 

useful in generating more accurate estimates of 

consumer exposure to cosmetic products. In contrast 

to the large market research bureau survey, the CTFA 

employee survey is very small, and both that survey 

and the cosmetic company survey are likely to be 

biased toward high-end users. Therefore, data from 

these two surveys should be used with caution. The 

limitations of these surveys are that data were not 

tabulated by age, are more than 20 years old, and are 

only representative of products used by babies and 

female consumers. Another limitation is that these 

data may not be representative of long-term use 

patterns. 

17.3.2.	 Westat (1987a)—Household Solvent 

Products: A National Usage Survey 

Westat (1987a) conducted a nationwide survey to 

determine consumer exposure to common household 

products believed to contain methylene chloride or its 

substitutes (i.e., carbon tetrachloride, trichloroethane, 

trichloroethylene, perchloroethylene, and 1,1,1,2,2,2 ­

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trichlorotrifluoroethane). The survey methodology 

was comprised of two phases. In the first phase, the 

sample population was generated by using a random 

digit dialing (RDD) procedure, in which telephone 

numbers of households nationwide were randomly 

selected by using an unbiased, equal probability of 

selection method, known as the Waksberg Method 

(Westat, 1987a). After the respondents in the selected 

households (18 years and older) agreed to participate 

in the survey, questionnaires and product pictures 

were mailed to each respondent. Finally, telephone 

follow-up calls were made to those respondents who 

did not respond to the mailed questionnaire within a 

4-week period to administer the same questionnaire. 

Of the 6,700 individuals contacted for the survey, 

4,920 individuals either responded to the mailed 

questionnaire or to a telephone interview (a response 

rate of 73%). Survey questions included how often 

the products were used in the last 12 months, when 

they were last used, how much time was spent using 

a product (per occasion or year), how long the 

respondent remained in the room after use, how much 

of a product was used per occasion or year, and what 

protective measures were used (Westat, 1987a). 

Thirty-two categories of common household 

products were included in the survey and are 

presented in Table 17-4. Table 17-4, Table 17-5, 

Table 17-6, and Table 17-7 provide means, medians, 

and percentile rankings for the following variables: 

frequency of use, exposure time, amount of use, and 

time exposed after use. 

An advantage of this study is that the RDD 

procedure (i.e., Waksberg Method) to identify 

participants enabled a diverse selection of a 

representative, unbiased sample of the U.S. 

population (Westat, 1987a). Also, empirical data on 

consumer household product use are provided. 

However, a limitation associated with this study is 

that the data generated were based on recall behavior. 

Another limitation is that extrapolation of these data 

to long-term use patterns may be difficult; the data 

are more than 20 years old and cannot be broken out 

by age groups. 

17.3.3.	 Westat (1987c)—National Usage Survey 

of Household Cleaning Products 

Westat (1987c) collected usage data from a 

nationwide survey to assess the magnitude of 

exposure of consumers to various products used 

when performing certain household cleaning tasks. 

The survey was conducted from the middle of 

November 1985 to the middle of January 1986. 

Telephone interviews were conducted with 

193 households. According to Westat (1987c), the 

resulting response rate for this survey was 78%. The 

Waksberg Method discussed in the Westat (1987a) 

study also was used in randomly selecting telephone 

numbers employed in this survey. The survey was 

designed to obtain information on cleaning activities 

performed in the interior of the home during the 

previous year. The person who did the majority of the 

cleaning in the kitchen and bathroom areas of each 

household was interviewed. Of those respondents, the 

primary cleaner was female in 160 households (83%) 

and male in 30 households (16%); the sex of the 

respondents in the three remaining households was 

not ascertained (Westat, 1987c). Data obtained from 

the survey included the frequency of performing 

14 different cleaning tasks, the amount of time 

(duration) spent at each task, the cleaning product 

most frequently used, the type of product (i.e., liquid, 

powder, aerosol, or spray pump) used, and the 

protective measures taken during cleaning, such as 

wearing rubber gloves or having a window open or 

an exhaust fan on (Westat, 1987c). 

Table 17-8 through Table 7-12 present the survey 

data. Table 17-8 presents the mean and median total 

exposure time of use for each cleaning task and the 

product type preferred for each task. Table 17-9 

presents the percentile rankings for the total time 

exposed to the products used for 14 cleaning tasks. 

Table 17-10 presents the mean and percentile 

rankings of the frequency in performing each task. 

Table 17-11 shows the mean and percentile rankings 

for exposure time per event of performing household 

tasks. Table 17-12 presents the mean and percentile 

rankings for total number of hours spent per year 

using the top 10 product groups. 

Westat (1987c) randomly selected a subset of 

30 respondents from the original survey and reinterviewed them during the first 2 weeks of March 

1986 as a reliability check on the recall data from the 

original phone survey. Frequency and duration data 

for 3 of the original 14 cleaning tasks were obtained 

from the re-interviews. In a second effort to validate 

the phone survey, 50 respondents of the original 

phone survey participated in a 4-week diary study 

(between February and March 1986) of 8 of the 

14 cleaning tasks originally studied. The diary 

approach assessed the validity of using a 1-time 

telephone survey to determine usual cleaning 

behavior (Westat, 1987c). The data (i.e., frequency 

and duration) obtained from the re-interviews and the 

diary approach were lower than the data from the 

original telephone survey, but were more consistent 

with one other. Westat (1987c) attributed the 

significant differences in the data obtained from these 

surveys to seasonal changes rather than 

methodological problems. 

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A limitation of this survey is evident from the 

reliability and validity check of the data collected by 

Westat (1987c). The data obtained from the telephone 

survey may reflect heavier seasonal cleaning because 

the survey was conducted during the holidays 

(November through January). Therefore, usage data 

obtained in this study may be biased and may 

represent upper bound estimates. Other limitations of 

this study include the small size of the sample 

population, the age of the data set, and that the data 

cannot be broken out by age groups. An advantage of 

this survey is that the RDD procedure (Waksberg 

Method) used provides unbiased results of sample 

selection and reduces the number of unproductive 

calls. Another advantage of this study is that it 

provides empirical data on frequency and duration of 

consumer use. 

17.3.4.	 Westat (1987b)—National Household 

Survey of Interior Painters 

Westat (1987b) conducted a nationwide study 

between November 1985 and January 1986 to obtain 

usage information that estimates the magnitude of 

exposure of consumers to different types of painting 

and painting-related products used while painting the 

interior of the home. The study sampled 

777 households to determine whether any household 

member had painted the interior of the home during 

the 12 months prior to the survey date. Of the 

sampled households, 208 households (27%) had a 

household member who had painted during the past 

12 months. Based on the households with primary 

painters, the response rate was 90% (Westat, 1987b). 

The person in each household who did most of the 

interior painting during the past 12 months was 

interviewed over the telephone. The RDD procedure 

(Waksberg Method) previously described in Westat 

(1987a) was used to generate sample blocks of 

telephone numbers in this survey. Questions were 

asked about the frequency and time spent for interior 

painting activities, the amount of paint used, and the 

protective measures used (i.e., wearing gloves, hats, 

and masks or keeping a window open) (Westat, 

1987b). Fifty-three percent of the primary painters in 

the households interviewed were male, 46% were 

female, and the sex of the remaining 1% was not 

ascertained. Three types of painting products were 

used in this study: latex paint, oil-based paint, and 

wood stains and varnishes. Of the respondents, 

94.7% used latex paint, 16.8% used oil-based paint, 

and 20.2% used wood stains and varnishes. 

Table 17-13, Table 17-14, and Table 17-15 

summarize data generated from this survey. Table 

17-13 presents the mean, standard deviation, and 

percentile rankings for the total exposure time for 

painting activity by paint type. Table 17-14 presents 

the mean and median exposure times for each 

painting activity per occasion for each paint type. A 

painting occasion is defined as a time period from 

start to cleanup (Westat, 1987b). Table 17-14 also 

presents the frequency and percentile rankings of 

painting occasions per year. Table 17-15 presents the 

total amount of paint used by interior painters. 

In addition, 30 respondents from the original 

survey were re-interviewed in April 1986 as a 

reliability check on the recall data. There were no 

significant differences between the data obtained 

from the re-interviews and the original painting 

survey (Westat, 1987b). 

An advantage of this survey, based on the 

reliability check conducted by Westat (1987b), is the 

stability in the painting data obtained. Another 

advantage of this survey is that the response rate was 

high (90%), thus minimizing non-response bias. Also, 

the Waksberg Method employed provides an 

unbiased equal probability method of RDD. The 

limitations of the survey are that the data are based 

on 12-month recall and may not accurately reflect 

long-term use patterns and the age of the data set. 

17.3.5.	 Abt (1992)—Methylene Chloride 

Consumer Use Study Survey Findings 

As part of a plan to assess the effectiveness of 

labeling of consumer products containing methylene 

chloride, Abt (1992) conducted a nationwide 

telephone survey of nearly 5,000 households. The 

survey was conducted in April and May of 1991. 

Three classes of products were included: (1) paint 

strippers, (2) non-automotive spray paint, and (3) 

adhesive removers. The survey paralleled a 

1986 consumer use survey conducted by Abt for the 

U.S. EPA. 

The survey was conducted to estimate the 

percentage of the U.S. adult population using paint 

remover, adhesive remover, and non-automotive 

spray paint. In addition, an estimate of the population 

using these products containing methylene chloride 

was determined. A survey questionnaire was 

developed to collect product usage data and 

demographic data. The survey sample was generated 

using a RDD technique. 

A total of 4,997 product screener interviews were 

conducted for the product interview sections. The 

number of respondents was 381 for paint strippers, 

58 for adhesive removers, and 791 for 

non-automotive spray paint. Survey responses were 

weighted to allow estimation at the level of the total 

U.S. population (Abt, 1992). A follow-up mail survey 

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also was conducted by using a short questionnaire. 

Respondents who had used the product in the past 

year or had purchased the product in the past 2 years 

and still had the container were asked to respond to 

the questionnaire (Abt, 1992). Of the 527 mailed 

questionnaires, 259 were returned. The questionnaire 

responses included 67 on paint strippers, 6 on 

adhesive removers, and 186 on non-automotive spray 

paint. Table 17-16 through Table 17-21 (Ns are 

unweighted) present the results of the survey. Data 

are presented for recent users, who were defined as 

persons who have used the product within the last 

year of the survey or who have purchased the product 

in the past 2 years. 

Abt (1992) found the following results when 

comparing the new data to the 1986 findings: 

•	 A significantly smaller proportion of

current survey respondents used a paint 

stripper, spray paint, or adhesive remover. 

•	 The proportion of the population who used 

the three products recently (within the past 

year) decreased substantially. 

•	 Those who used the products reported a 

significantly longer time since their last 

use. For all three products, the reported 

amount used per year was significantly 

higher in the current survey. 

An advantage of this survey is that the survey 

population was large, and the survey responses were 

weighted to represent the U.S. population. In 

addition, the survey was designed to collect data for 

frequency of product use and amount of product used 

by sex. Limitations of the survey are that the 

information may be dated, and that the data were 

generated based on recall behavior. Extrapolation of 

these data to accurately reflect long-term use patterns 

may be difficult. 

17.3.6.	 U.S. EPA (1996)—National Human 

Activity Pattern Survey (NHAPS) 

U.S. EPA (1996) collected data on the duration 

and frequency of selected activities and the time 

spent in selected microenvironments via 24-hour 

diaries as part of the National Human Activity Pattern 

Survey (NHAPS). More than 9,000 individuals from 

various age groups in 48 contiguous states

participated in NHAPS, including 2,000 children. 

The survey was conducted between October 1992 

and September 1994. Individuals were interviewed to 

categorize their 24-hour routines (diaries) and/or to 

answer follow-up questions that were related to

exposure events. Demographic, including

socioeconomic (e.g., sex, age, race, education),

geographic (e.g., census region, state), and temporal 

(i.e., day of week, month, season) data were included 

in the study. Data were collected for a maximum of 

82 possible microenvironments and 91 different

activities. 

As part of the survey, data also were collected on 

duration and frequency of use of selected consumer 

products. Table 17-22 through Table 17-30 present 

data on the number of minutes that survey

respondents spent in activities working with or being 

near certain consumer products, including microwave 

ovens; freshly applied paints; household cleaning 

agents such as scouring powders or ammonia; floor 

wax, furniture wax, or shoe polish; glue; solvents, 

fumes, or strong-smelling chemicals; stain or spot 

removers; gasoline, diesel-powered equipment, or 

automobiles; and pesticides, bug sprays, or bug 

strips. Table 17-31 through Table 17-35 present data 

on the number of respondents in these age categories 

that used fragrances, aerosol sprays, humidifiers, and 

pesticides (professionally-applied and consumerapplied). Because the age categories used by the 

study authors did not coincide with the standardized 

age categories recommended in U.S. EPA (2005) and 

used elsewhere in this handbook, the source data 

from NHAPS on pesticide use (professionally applied 

and consumer-applied) were reanalyzed by U.S. EPA 

to generate data for the standardized age categories. 

Data for subsets of the 1st year of life (e.g., 1 to 

2 months, 3 to 5 months, etc.) were not available. 

As discussed in previous chapters that used

NHAPS as a data source, the primary advantage is 

that the data were collected for a large number of 

individuals, and the survey was designed to be

representative of the U.S. general population. 

However, due to the wording of questions in the 

survey, precise data were not available for consumers 

who spent more than 60 or 120 minutes (depending 

on the activity) using some consumer products. This 

prevents accurate characterization of the high end of 

the distribution and also may introduce error into the 

calculation of the mean. Another limitation is that the 

adult data were not broken down into finer age 

categories. These data are also based on 24-hour 

diaries and may not be representative of long-term 

use patterns. 

17.3.7.	 Bass et al. (2001)—What’s Being Used at 

Home: A Household Pesticide Survey 

Bass et al. (2001) conducted a survey to 

assess the use of pesticide products in homes with 

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children in March 1999. The study obtained 

information on what pesticides were used, where they 

were used, and how frequently they were used. A 

total of 107 households in Arizona that had a least 

one child less than 10 years old in the household and 

had used a pesticide within the last 6 months were 

surveyed (Bass et al., 2001). The survey population 

was composed predominantly of Hispanic females 

and represented a survey response rate of 

approximately 74%. Study participants were selected 

by systematic random sampling. Pesticide use was 

assessed by a one-on-one interview in the home. 

Survey questions pertained to household pesticides 

used inside the house for insect control and outside 

the house for controlling weeds in the garden and 

repelling animals from the garden. As part of the 

interview, information was gathered on the 

pesticides’ frequency of use. 

Table 17-36 presents information on the type, 

characteristics, and frequency of pesticide use, as 

well as information on the demographics of the 

survey population. A total of 148 pesticide products 

were used in the 107 households surveyed. 

Respondents had used pesticides in the kitchen, 

bathroom, floors, baseboards, and cabinets with 

dishes or cookware. The frequency of use data 

showed the following: about 32% of the households 

used pesticides once per week or more; about 44% 

used the products once per month or once in 

3 months; and about 19% used the products once in 

6 months or once per year (Bass et al., 2001). 

Although this study was limited to a selected area 

in Arizona, it provides useful information on the 

frequency of use of pesticides among households 

with children. This may be useful for populations in 

similar geographical locations where site-specific 

data are not available. However, these data are the 

result of a community-based survey and are not 

representative of the U.S. general population. 

17.3.8.	 Weegels and van Veen (2001)—Variation 

of Consumer Contact With Household 

Products: A Preliminary Investigation 

Weegels and van Veen (2001) conducted a survey 

to determine consumer exposure to common 

household products used once a day or every other 

day. Thirty households participated in the study, 

including 10 families with children, 10 couples, 

9 individuals, and 1 household of 6 adults from the 

city of Delft in The Netherlands. Households were 

recruited through the Usability Panel of the School of 

Industrial Design and through public notices and 

pamphlets. 

Three types of products were studied: 

dishwashing detergent, all-purpose cleaners, and hairstyling products. Three activities in which these 

products are commonly used were studied in more 

detail: dishwashing, toilet cleaning, and styling hair. 

In-home observations, diaries, and measurement of 

the amount of product utilized were used to collect 

data. Subjects were visited in their homes and 

videotaped performing the activities. After 3 weeks, 

subjects were again visited in their homes and 

videotaped performing activities, diaries were 

collected, and the amount of product used was 

measured. 

Table 17-37 presents the survey data. During 

toilet cleaning, 22 of 29 subjects observed used at 

least two different products (e.g., toilet cleaner, allpurpose cleaner, and/or abrasive cleaner). The large 

variation in duration of toilet cleaning was due to the 

diverse ways in which toilet cleaner was used: some 

subjects left the toilet cleaner to soak overnight, some 

left it in the bowl while cleaning the remainder of the 

toilet, others flushed the toilet immediately after 

cleaning. The authors noted that the findings of the 

study suggest that “...individuals have a consistent 

way of using a product for a particular activity, but 

there is a large variety in product usage among 

consumers, with relations among frequency, 

durations and amount. If this conclusion is confirmed 

by future research, it suggests that there will be 

people who exhibit high-end use of products and will, 

most likely follow their own routine, which may have 

consequences for the definition of worst-case use of 

consumer products.” 

An advantage of this study is that the empirical 

data generated provide more accurate calculations of 

exposure than studies relying on recall data. 

Limitations of the study are the small study 

population (30 households) and that The Netherlands 

may not be representative of U.S. population 

behaviors. Another limitation is that the short 

duration (3 weeks) may not accurately reflect longterm or seasonal usage patterns. 

17.3.9.	 Loretz et al. (2005)—Exposure Data for 

Cosmetic Products: Lipstick, Body 

Lotion, and Face Cream 

Loretz et al. (2005) conducted a nationwide 

survey to estimate the usage (i.e., frequency of 

application and amount used per application) of 

lipstick, body lotion, and face cream. The study was 

conducted in 2000 and included 360 study subjects 

recruited in 10 U.S. cities (i.e., Atlanta, GA; Boston, 

MA; Chicago, IL; Denver, CO; Houston, TX; 

Minneapolis, MN; St. Louis, MO; San Bernardino, 

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CA; Tampa Bay, FL; and Seattle, WA). The survey 

participants were women, ages 19 to 65 years, who 

regularly used the products of interest. Typical 

cosmetic formulations of the three product types were 

weighed and provided to the women for use over a 

2-week period. Subjects recorded information on 

product usage (e.g., whether the product was used, 

number of applications, time of applications) on a 

daily basis in a diary provided to them. At the end of 

the 2-week period, unused portions of product were 

returned and weighed. The amount of product used 

was estimated as the difference between the weight of 

product at the beginning and end of the survey 

period. Of the 360 subjects, 86.4%, 83.3%, and 

85.6% completed the study and returned the diaries 

for lipstick, body lotion, and face cream, respectively 

(Loretz et al., 2005). 

Table 17-38 and Table 17-39 present the survey 

data. Table 17-38 provides the mean, median, and 

standard deviations for the frequency of use. Table 

17-39 provides distribution data for the total amount 

applied, the average amount applied per use day, and 

the average amount applied per application. 

An advantage of this study is that the survey 

population covered a diverse geographical area of the 

United States and that it was not based on recall data. 

A limitation of the study is that the short duration 

(2 weeks) may not accurately reflect long-term usage 

patterns. Another limitation is that the study only 

included women who already used the products; 

therefore, the usage patterns are not representative of 

the entire female population. Also, the data are not 

presented by age group. 

17.3.10. Loretz et al. (2006)—Exposure Data for 

Personal Care Products: Hairspray, 

Spray Perfume, Liquid Foundation, 

Shampoo, Body Wash, and Solid 

Antiperspirant 

Loretz et al. (2006) conducted a nationwide 

survey to determine the usage (i.e., frequency of use 

and amount used) of hairspray, spray perfume, liquid 

foundation, shampoo, body wash, and solid 

antiperspirant. The survey was similar to that 

described by Loretz et al. (2005). This study was 

conducted in 2000 and 2001. A total of 360 women 

were recruited from 10 U.S. cities (Atlanta, GA; 

Boston, MA; Chicago, IL; Denver, CO; Houston, TX; 

Minneapolis, MN; St. Louis, MO; San Bernardino, 

CA; Tampa Bay, FL; and Seattle, WA). The survey 

participants were women, ages 19 to 65 years old, 

who regularly used the test products. Subjects kept 

daily records on product usage (e.g., whether the 

product was used, number of applications, time of 

applications) in a diary. For spray perfume, liquid 

foundation, and body wash, subjects recorded the 

body areas where these products were applied. For 

shampoo, subjects recorded information on their hair 

type (i.e., length, thickness, oiliness, straight or curly, 

and color treated or not). At the end of the 2-week 

period, unused portions of products were returned 

and weighed. Of the 360 subjects recruited per 

product, the study was completed by 91% of 

participants for hairspray, 91% for spray perfume, 

94% for liquid foundation, and 94% for shampoo, 

body wash, and solid antiperspirant. 

Table 17-40 through Table 17-42 present the 

survey data. Table 17-40 provides the minimum, 

maximum, mean, and standard deviations for the 

frequency of use. Table 17-41 provides percentile 

values for the amount of product applied per 

application. Table 17-42 provides distribution data 

for the amount applied per use day. 

An advantage of this study is that the survey 

population covered a diverse geographical range of 

the United States and that it did not rely on recall 

data. A limitation of the study is that the short 

duration (2 weeks) may not accurately reflect longterm usage patterns. Another limitation is that the 

study only included women who already used these 

products; therefore, the usage patterns are not entirely 

representative of the entire female population. Also, 

the data are not presented by age group. 

17.3.11. Hall et al. (2007)—European Consumer 

Exposure to Cosmetic Products, a 

Framework for Conducting Population 

Exposure Assessments 

European cosmetic manufacturers constructed a 

probabilistic European population model of exposure 

for six cosmetic products: body lotion, 

deodorant/antiperspirant, lipstick, facial moisturizer, 

shampoo, and toothpaste (Hall et al., 2007). Data 

were collected by using both market information 

databases and a controlled product use study from 

44,100 households and 18,057 individual consumers, 

creating a sample of the 249 million inhabitants of 

the 15 countries in the European Union. Tables Table 

17-43 through Table 17-50 show the amount used in 

g/day and mg/kg-day. The study found an inverse 

correlation between frequency of product use and 

quantity used per application for body lotion, facial 

moisturizer, toothpaste, and shampoo, and so the 

authors cautioned against calculating daily exposure 

to these products by multiplying the maximum 

frequency value by the maximum quantity per event 

value. 

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The advantage of this study is that it included a 

large sample size. However, behaviors and activities 

in the European population may not be representative 

of the U.S. population, and results were not broken 

out by age groups. 

17.3.12. Loretz et al. (2008)—Exposure Data for 

Cosmetic Products: Facial Cleanser, Hair 

Conditioner, and Eye Shadow 

Loretz et al. (2008) used the data from a study 

conducted in 2005 to estimate frequency of use and 

usage amount for facial cleanser, hair conditioner, 

and eye shadow. The study was conducted in a 

similar manner as Loretz et al. (2006; 2005). A total 

of 360 women, ages 18 to 69 years, were recruited by 

telephone to provide diary records of product use 

during a 2-week period. The study subjects were 

representative of four U.S. Census regions (i.e., 

Northeast, Midwest, South, and West). A total of 295, 

297, and 299 women completed the study for facial 

cleanser, hair conditioner, and eye shadow, 

respectively. 

The participants recorded daily in a diary whether 

the product was used that day, the number of 

applications, and the time of applications during a 

2-week period. Products were weighed at the start 

and completion of the study to determine the amount 

used. A statistical analysis of the data was conducted 

to provide summary distributions of use patterns, 

including number of applications, amount used per 

day, and amount of product used per application for 

each product. Table 17-51 provides data on the 

number of applications per use day. Table 17-52 

shows the average amounts of product applied per 

use day, while Table 17-53 shows the average 

amounts of product applied per application. 

The advantages of this study are that it is 

representative of the U.S. female population for users 

of the products studied, it provides data for frequency 

of use and amount used, and it provides distribution 

data. A limitation of the study is that the data were 

not provided by age group. In addition, the 

participants were regular users of the product, so the 

amount applied and the frequency of use may be 

higher than for other individuals who may use the 

products. According to Loretz et al. (2008), 

“...variability in amount used by the different 

subjects is high, but consistent with the data from 

other cosmetic and personal care studies.” The 

authors also noted that it was not clear if the high-end 

users of products represented true usage. Data were 

also collected over a 2-week period and may not be 

representative of long-term usage patterns. 

17.3.13. Sathyanarayana et al. (2008)—Baby Care 

Products; Possible Sources of Infant 

Phthalate Exposure 

Sathyanarayana et al. (2008) investigated dermal 

exposure to phthalates via the dermal application of 

personal care products. The study was conducted on 

163 infants born between 2000 and 2005. The 

products studied were baby lotion, baby powder, 

baby shampoo, diaper cream, and baby wipes. Infants 

were recruited through Future Families, a multicenter 

pregnancy cohort study, at prenatal clinics in Los 

Angeles, CA; Minneapolis, MN; and Columbia, MO. 

Although the study was designed to assess exposure 

to phthalates, the authors collected information on the 

percentage of the total participants who used the baby 

products. Data were collected from questionnaire 

responses of the mothers and at study visits. Table 

17-54 shows the characteristics and the percentage of 

the population using the studied baby products. Of 

the 163 infants studied, 94% of the participants used 

baby wipes, and 54% used infant shampoo. 

The advantages of this study are that it 

specifically targeted consumer products used by 

children, it captured the percentage of the study 

population using these products, and it collected the 

data from a diverse ethnic population. The limitation 

is that these data may not be entirely representative of 

the U.S. population because the study population was 

from only three states and the sample size was small. 

Also, this study did not contain any information on 

amount or frequency of product use. 

17.4. REFERENCES FOR CHAPTER 17 

Abt (Abt Associates Inc.). (1992). Methylene 

chloride consumer products use survey 

findings. Bethesda, MD: U.S. Consumer 

Product Safety Commission. 

Bass, JK; Ortega, L; Rosales, C; Petersen, NJ; Philen, 

RM. (2001). What's being used at home: A 

household pesticide survey. Rev Panam 

Salud Publica 9: 138-144. 

CTFA (Cosmetic, Toiletry, and Fragrance 

Association). (1983). Summary of the 

results of surveys of the amount and 

frequency of use of cosmetic products by 

women. Washington, DC: CTFA Inc. 

Franklin, P. (2008). Household chemicals: good 

housekeeping or occupational hazard? Eur 

Respir J 31: 489-491. 

http://dx.doi.org/10.1183/09031936.001702 

07. 

Hall, B; Tozer, S; Safford, B; Coroama, M; Steiling, 

W; Leneveu-Duchemin, MC; Mcnamara, C; 

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Gibney, M. (2007). European consumer 

exposure to cosmetic products, a framework 

for conducting population exposure 

assessments. Food Chem Toxicol 45: 2097­

2108. 

http://dx.doi.org/10.1016/j.fct.2007.06.017. 

Loretz, L; Api, AM; Barraj, L; Burdick, J; Davis, d; 

Dressler, W; Gilberti, E; Jarrett, G; Mann, S; 

Laurie Pan, YH; Re, T; Renskers, K; 

Scrafford, C; Vater, S. (2006). Exposure data 

for personal care products: hairspray, spray 

perfume, liquid foundation, shampoo, body 

wash, and solid antiperspirant. Food Chem 

Toxicol 44: 2008-2018. 

http://dx.doi.org/10.1016/j.fct.2006.06.029. 

Loretz, LJ; Api, AM; Babcock, L; Barraj, LM; 

Burdick, J; Cater, KC; Jarrett, G; Mann, S; 

Pan, YH; Re, TA; Renskers, KJ; Scrafford, 

CG. (2008). Exposure data for cosmetic 

products: facial cleanser, hair conditioner, 

and eye shadow. Food Chem Toxicol 46: 

1516-1524. 

http://dx.doi.org/10.1016/j.fct.2007.12.011. 

Loretz, LJ; Api, AM; Barraj, LM; Burdick, J; 

Dressler, WE; Gettings, SD; Han Hsu, H; 

Pan, YH; Re, TA; Renskers, KJ; 

Rothenstein, A; Scrafford, CG; Sewall, C. 

(2005). Exposure data for cosmetic 

products: lipstick, body lotion, and face 

cream. Food Chem Toxicol 43: 279-291. 

http://dx.doi.org/10.1016/j.fct.2004.09.016. 

Sathyanarayana, S; Karr, CJ; Lozano, P; Brown, E; 

Calafat, AM; Liu, F; Swan, SH. (2008). 

Baby care products: possible sources of 

infant phthalate exposure. Pediatrics 121: 

e260-268. 

http://dx.doi.org/10.1542/peds.2006-3766. 

Steenbekkers, LP. (2001). Methods to study everyday 

use of products in households: The 

Wageningen Mouthing Study as an example. 

Ann Occup Hyg 45 Suppl 1: S125-S129. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1986a). Standard scenarios for estimating 

exposure to chemical substances during use 

of consumer products: Volume I. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1986b). Standard scenarios for estimating 

exposure to chemical substances during use 

of consumer products: Volume II. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1987). Methods for assessing exposure to 

chemical substances: Volume 7: Methods for 

assessing consumer exposure to chemical 

substances [EPA Report]. (EPA/560/5­

85/007). Washington, DC.

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=P1007I8Y.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1996). Descriptive statistics from a detailed 

analysis of the National Human Activity 

Pattern Survey (NHAPS) responses. 

(EPA/600/R-96/148). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2005). Guidance on selecting age groups 

for monitoring and assessing childhood 

exposures to environmental contaminants 

(final). (EPA/630/P-03/003F). Washington, 

DC: U.S. Environmental Protection Agency, 

Risk Assessment Forum.

http://www.epa.gov/raf/publications/guidanc 

e-on-selecting-age-groups.htm. 

Weegels, ME; van Veen, MP. (2001). Variation of 

consumer contact with household products: 

a preliminary investigation. Risk Anal 21: 

499-511. 

Westat.	 (1987a). Household solvent products: A 

national usage survey. Washington, DC: 

U.S. Environmental Protection Agency. 

http://www.ntis.gov/search/product.aspx?A 

BBR=PB88132881. 

Westat.	 (1987b). National household survey of 

interior painters : Final report. (EPA 

560/1987 WI/003). Washington, DC: U.S. 

Environmental Protection Agency. 

Westat. (1987c). National usage survey of household 

cleaning products. Washington, DC: U.S. 

Environmental Protection Agency. 

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Table 17-1. Consumer Products Commonly Found in Some U.S. Householdsa 

Consumer Product Category Consumer Product 

Cosmetics Hygiene Products  Adhesive bandages  Lip products 

 Bath additives (liquid)  Mouthwash/breath freshener 

 Bath additives (powder)  Sanitary napkins and pads 

 Cologne/perfume/aftershave  Shampoo 

 Contact lens solutions  Shaving creams (aerosols) 

 Deodorant/antiperspirant (aerosol)  Skin creams (non-drug) 

 Deodorant/antiperspirant (wax and liquid)  Skin oils (non-drug) 

 Depilatories  Soap (toilet bar) 

 Facial makeup  Sunscreen/suntan products 

 Fingernail cosmetics  Talc/body powder (non-drug) 

 Hair coloring/tinting products  Toothpaste 

 Hair conditioning products  Waterless skin cleaners 

 Hairsprays (aerosol) 

Household Furnishings  Carpeting  Shower curtains 

 Draperies/curtains  Vinyl upholstery, furniture 

 Rugs (area) 

Garment Conditioning Products  Anti-static spray (aerosol)  Suede cleaner/polish (liquid and 

 Leather treatment (liquid and wax) aerosol) 

 Shoe polish  Textile water-proofing (aerosol) 

 Spray starch (aerosol) 

Household Maintenance Products  Adhesive (general) (liquid)  Insect repellent (liquid and aerosol) 

 Bleach (household) (liquid)  Laundry detergent/bleach (liquid) 

 Bleach (see laundry)  Laundry detergent (powder) 

 Candles  Laundry prewash/soak (powder) 

 Cat box litter  Laundry prewash/soak (liquid) 

 Charcoal briquettes  Laundry prewash/soak (aerosol 

 Charcoal lighter fluid and pump) 

 Drain cleaner (liquid and powder)  Lubricant oil (liquid) 

 Dishwasher detergent (powder)  Lubricant (aerosol) 

 Dishwashing liquid  Matches 

 Fabric dye (DIY)b  Metal polish 

 Fabric rinse/softener (liquid)  Oven cleaner (aerosol) 

 Fabric rinse/softener (powder)  Pesticide (home) (solid) 

 Fertilizer (garden) (liquid)  Pesticide (pet dip) (liquid) 

 Fertilizer (garden) (powder)  Pesticide (pet) (powder) 

 Fire extinguishers (aerosol)  Pesticide (pet) (aerosol) 

 Floor polish/wax (liquid)  Pesticide (pet) (collar) 

 Food packaging and packaged food  Petroleum fuels (home) (liquid and 

 Furniture polish (liquid) aerosol) 

 Furniture polish (aerosol)  Rug cleaner/shampoo (liquid and 

 General cleaner/disinfectant (liquid) aerosol) 

 General cleaner (powder)  Rug deodorizer/freshener (powder) 

 General cleaner/disinfectant (aerosol  Room deodorizer (solid) 

and pump)  Room deodorizer (aerosol) 

 General spot/stain remover (liquid)  Scouring pad 

 General spot/stain remover (aerosol and  Toilet bowl cleaner 

pump)  Toiler bowl deodorant (solid) 

 Herbicide (garden-patio) (liquid and aerosol)  Water-treating chemicals 

 Insecticide (home and garden) (powder) (swimming pools) 

 Insecticide (home and garden) 

(aerosol and pump) 

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Table 17-1. Consumer Products Commonly Found in Some U.S. Householdsa (continued) 

Consumer Product Category Consumer Product 

Home Building/Improvement 

Products (DIY)b 

 Adhesives, specialty (liquid)  Paint/varnish removers 

 Ceiling tile  Paint thinner/brush cleaners 

 Caulks/sealers/fillers  Patching/ceiling plaster 

 Dry wall/wall board  Roofing 

 Flooring (vinyl)  Refinishing products 

 House paint (interior) (liquid) (e.g., polyurethane, varnishes) 

 House paint and stain (exterior)  Spray paints (home) (aerosol) 

(liquid)  Wall paneling 

 Insulation (solid)  Wall paper 

 Insulation (foam)  Wall paper glue 

Automobile-Related Products  Antifreeze  Motor oil 

 Car polish/wax  Radiator flush/cleaner 

 Fuel/lubricant additives  Automotive touch-up paint 

 Gasoline/diesel fuel (aerosol) 

 Interior upholstery/components,  Windshield washer solvents 

synthetic 

Personal Materials  Clothes/shoes  Sheets/towels 

 Diapers/vinyl pants  Toys (intended to be placed in 

 Jewelry mouths) 

 Printed material (colorprint, newsprint, 

photographs) a A subjective listing based on consumer use profiles. b DIY = do it yourself. 

Source: U.S. EPA (1987). 

Exposure Factors Handbook Page
 

September 2011 17-11
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-2. List of Product Categories in the Simmons Study of Media and Markets 

The volumes included in the Media series are as follows: 

M1 

M2 

M3 

M4 

M5 

M6 

M7 

M8 

Publications: Total Audiences 

Publications: Qualitative Measurements and In-Home Audiences 

Publications: Duplication of Audiences 

Multi-Media Audiences: Adults 

Multi-Media Audiences: Males 

Multi-Media Audiences: Females and Mothers 

Business to Business 

Multi-Media Reach and Frequency and Television Attentiveness and Special Events 

The following volumes are included in the Product series: 

P1 

P2 

P3 

P4 

P5 

P6 

P7 

P8 

P9 

P10 

P11 

P12 

P13 

P14 

P15 

P16 

P17 

P18 

P19 

P20 

P21 

P22 

P23 

P24 

P25 

P26 

Automobiles, Cycles, Trucks and Vans 

Automotive Products and Services 

Travel 

Banking, Investments, Insurance, Credit Cards and Contributions, Memberships and Public 

Activities 

Games and Toys, Children's and Babies' Apparel and Specialty Products 

Computers, Books, Discs, Records, Tapes, Stereo, Telephones, TV and Video 

Appliances, Garden Care, Sewing and Photography 

Home Furnishings and Home Improvements 

Sports and Leisure 

Restaurants, Stores and Grocery Shopping 

Direct Mail and Other In-Home Shopping, Yellow Pages, Florist, Telegrams, Faxes and Greeting 

Cards 

Jewelry, Watches, Luggage, Writing Tools and Men's Apparel 

Women's Apparel 

Distilled Spirits, Mixed Drinks, Malt Beverages, Wine and Tobacco Products 

Coffee, Tea, Cocoa, Milk, Soft Drinks, Juices and Bottled Water 

Dairy Products, Desserts, Baking and Bread Products 

Cereals and Spreads, Rice, Pasta, Pizza, Mexican Foods, Fruits and Vegetables 

Soup, Meat, Fish, Poultry, Condiments and Dressings 

Chewing Gum, Candy, Cookies and Snacks 

Soap, Laundry, Paper Products and Kitchen Wraps 

Household Cleaners, Room Deodorizers, Pest Controls and Pet Foods 

Health Care Products and Remedies 

Oral Hygiene Products, Skin Care, Deodorants and Drug Stores 

Hair Care, Shaving Products and Fragrances 

Women's Beauty Aids, Cosmetics and Personal Products 

Relative Volume of Consumption 

Page Exposure Factors Handbook 

17-12 September 2011 
 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-3. Amount and Frequency of Use of Various Cosmetic and Baby Products 

Upper 90th Percentile Frequency of 

Product Type 

Amount of 

Product per 

Applicationa 

(grams) 

Average Frequency of Use 

(per day) 

Survey Type 

CTFA Cosmetic 

Co. 

Marketb 

Research 

Bureau 

CTFA 

Use 

(per day) 

Survey Type 

Cosmetic 

Co. 

Market 

Research 

Bureau 

Baby Lotion - baby usec 1.4 0.38 1.0 – 0.57 2.0 – 

Baby Lotion - adult use 1.0 0.22 0.19 0.24d 0.86 1.0 1.0d 

Baby Oil - baby usec 1.3 0.14 1.2 – 0.14 3.0 – 

Baby Oil - adult use 5.0 0.06 0.13 – 0.29 0.57 – 

Baby Powder - baby usec 0.8 5.36 1.5 0.35d 8.43 3.0 1.0d 

Baby Powder - adult use 0.8 0.13 0.22 – 0.57 1.0 – 

Baby Cream - baby usec – 0.43 1.3 – 0.43 3.0 – 

Baby Cream - adult use – 0.07 0.10 – 0.14 0.14e – 

Baby Shampoo - baby usec 0.5 0.14 – 0.11f 0.14 – 0.43f 

Baby Shampoo - adult use 5.0 0.02 – – 0.86e – – 

Bath Oils 14.7 0.08 0.19 0.22g 0.29 0.86 1.0g 

Bath Tablets – 0.003 0.008 – 0.14e 0.14e – 

Bath Salts 18.9 0.006 0.013 – 0.14e 0.14e – 

Bubble Baths 11.8 0.088 0.13 – 0.43 0.57 – 

Bath Capsules – 0.018 0.019 – 0.29e 0.14e – 

Bath Crystals – 0.006 – – 0.29e 0.14e – 

Eyebrow Pencil – 0.27 0.49 – 1.0 1.0 – 

Eyeliner – 0.42 0.68 0.27 1.43 1.0 1.0 

Eye Shadow – 0.69 0.78 0.40 1.43 1.0 1.0 

Eye Lotion – 0.094 0.34 – 0.43 1.0 – 

Eye Makeup Remover – 0.29 0.45 – 1.0 1.0 – 

Mascara – 0.79 0.87 0.46 1.29 1.0 1.5 

Under Eye Cover – 0.79 – – 0.29 – – 

Blusher and Rouge 0.011 1.18 1.24 0.55 2.0 1.43 1.5 

Face Powders 0.085 0.35 0.67 0.33 1.29 1.0 1.0 

Foundations 0.265 0.46 0.78 0.47 1.0 1.0 1.5 

Leg and Body Paints – 0.003 0.011 – 0.14e 0.14e – 

Lipstick and Lip Gloss – 1.73 1.23 2.62 4.0 2.86 6.0 

Makeup Bases 0.13 0.24 0.64 – 0.86 1.0 – 

Exposure Factors Handbook Page
 

September 2011 17-13 
Table 17-3. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued) 

Product Type 

Amount of 

Product per 

Applicationa 

(grams) 

Average Frequency of Use 

(per day) 

Upper 90 th Percentile Frequency of 

Use 

(per day) 

Survey Type Survey Type 

Marketb 

Cosmetic CTFA Research Co. Bureau 

Market Cosmetic CTFA Research Co. Bureau 

Makeup Fixatives 

Sunscreen 

Colognes and Toilet Water 

Perfumes 

Powders 

Sachets 

Fragrance Lotion 

Hair Conditioners 

Hair Sprays 

Hair Rinses 

Shampoos 

Tonics and Dressings 

Wave Sets 

Dentifrices 

Mouthwashes 

Breath Fresheners 

Nail Basecoats 

Cuticle Softeners 

Nail Creams and Lotions 

Nail Extenders 

Nail Polish and Enamel 

Nail Polish and Enamel 

Remover 

Nail Undercoats 

Bath Soaps 

Underarm Deodorants 

Douches 

Feminine Hygiene 

Deodorants 

Cleansing Products (cold 

 creams, cleansing lotions, 

 liquids, and pads) 

Depilatories 

– 

3.18 

0.65 

0.23 

2.01 

0.2 

– 

12.4 

– 

12.7 

16.4 

2.9 

2.6 

– 

– 

– 

0.2 

0.7 

0.6 

– 

0.3 

3.1 

– 

2.6 

0.5 

– 

– 

1.7 

– 

0.052 

0.003 

0.68 

0.29 

0.18 

0.0061 

0.0061 

0.4 

0.25 

0.064 

0.82 

0.073 

0.003h 

1.62 

0.42 

0.052 

0.052 

0.040 

0.070 

0.003 

0.16 

0.088 

0.049 

1.53 

1.01 

0.013 

0.021 

0.63 

0.0061 

0.12 

– 

0.85 

0.26 

0.39 

0.034 

– 

0.40 

0.55 

0.18 

0.59 

0.021 

0.040 

0.67 

0.62 

0.43 

0.13 

0.10 

0.14 

0.013 

0.20 

0.19 

0.12 

0.95 

0.80 

0.089 

0.084 

0.80 

0.051 

– 

0.002 

0.56 

0.38 

– 

– 

– 

0.27 

0.32 

– 

0.48 

– 

– 

2.12 

0.58 

0.46 

– 

– 

– 

– 

0.07 

– 

– 

– 

1.10 

0.085 

0.05 

0.54 

0.009 

0.14 

0.14e 

1.71 

0.86 

1.0 

0.14e 

0.29e 

1.0 

1.0 

0.29 

1.0 

0.29 h –

2.6 

1.86 

0.14 

0.29 

0.14 

0.29 

0.14e 

0.71 

0.29 

0.14 

3.0 

1.29 

0.14e 

1.0e 

1.71 

0.016 

1.0 

– 

1.43 

1.0 

1.0 

0.14e 

– 

1.0 

1.0 

1.0 

1.0 

0.14d 

0.14 

2.0 

1.14 

1.0 

0.29 

0.29 

0.43 

0.14e 

0.43 

0.43 

0.29 

1.43 

1.29 

0.29 

0.29 

2.0 

0.14 

– 

0.005 

1.5 

1.5 

– 

– 

– 

0.86 

1.0 

– 

1.0 

– 

– 

4.0 

1.5 

0.57 

– 

– 

– 

– 

1.0 

– 

– 

– 

2.0 

0.29 

0.14 

1.5 

0.033 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 

17-14 September 2011 
 

 

 

 

 

 

 

 

c 

Table 17-3. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued) 

Upper 90th Percentile Frequency of 

Average Frequency of Use Use 

Amount of (per day) (per day) 

Product Type Product per 

Applicationa Survey Type Survey Type 

(grams) 

CTFA Cosmetic 

Co. 

Marketb 

Research 

Bureau 

CTFA Cosmetic 

Co. 

Market 

Research 

Bureau 

Face, Body and Hand Preps 3.5 0.65 – 1.12 2.0 – 2.14 

(excluding shaving preps) 

Foot Powder and Sprays – 0.061 0.079 – 0.57e 0.29 – 

Hormones – 0.012 0.028 – 0.57e 0.14e – 

Moisturizers 0.5 0.98 0.88 0.63 2.0 1.71 1.5 

Night Skin Care Products 1.3 0.18 0.50 – 1.0 1.0 – 

Paste Masks (mud packs) 3.7 0.027 0.20 – 0.14 0.43 – 

Skin Lighteners – – 0.024 – –e 0.14e – 

Skin Fresheners and 2.0 0.33 0.56 – 1.0 1.43 – 

Astringents
 

Wrinkle Smoothers 0.4 0.021 0.15 – 1.0d 1.0 –
 

(removers)
 

Facial Cream 0.6 0.0061 – – 0.0061 – – 

Permanent Wave 101 0.003 – 0.001 0.0082 – 0.005 

Hair Straighteners 0.2 0.0007 – – 0.005e – – 

Hair Dye – 0.001 – 0.005 0.004e – 0.014 

Hair Lighteners – 0.0003 – – 0.005e – – 

Hair Bleaches – 0.0005 – – 0.02e – – 

Hair Tints – 0.0001 – – 0.005e – – 

Hair Rinse (coloring) – 0.0004 – – 0.02e – – 

Shampoo (coloring) – 0.0005 – – 0.02e – – 

–e Hair Color Spray – – – –	 – – 

Shave Cream 1.73 – – 0.082 – – 0.36 a Values reported are the averages of the responses reported by the 20 companies interviewed. b The averages shown for the Market Research Bureau are not true averages - this is due to the fact that in many cases the class of most 

frequent users is indicated by "1 or more"; also, ranges are used in many cases (i.e., "10-12"). The average, therefore, is 

underestimated slightly. The "1 or more" designation also skews the 90th percentile figures in many instances. The 90th percentile 

values may, in actuality, be somewhat higher for many products.
 

Average usage among users only for baby products.
 d	 Usage data reflects entire household use for both baby lotion and baby oil. e	 Fewer than 10% of individuals surveyed used these products. Value listed is lowest frequency among individuals reporting usage. In 

the case of wave sets, skin lighteners, and hair color spray, none of the individuals surveyed by the CTFA used this product during the 

period of the study. f Usage data reflects entire household use. g Usage data reflects total bath product usage. h None of the individuals surveyed reported using this product. 

(–) indicate no data available. 

Source:	 CTFA (1983). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Exposure Factors Handbook Page
 

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Table 17-4. Frequency of Use for Household Solvent Products (users only) 

Products Mean 

(use/year) SD Min 1 5 

Percentile Rankings for Frequency of Use/Year 

10 25 50 75 90 95 99 Max 

Spray Shoe Polish 10.28 20.10 1.00 1.00 1.00 1.00 2.00 4.00 8.00 24.30 52.00 111.26 156.00 

Water Repellents/Protectors 3.50 11.70 1.00 1.00 1.00 1.00 1.00 2.00 3.00 6.00 10.00 35.70 300.00 

Spot Removers 15.59 43.34 1.00 1.00 1.00 1.00 2.00 3.00 10.00 40.00 52.00 300.00 365.00 

Solvent-Type Cleaning Fluids or Degreasers 16.46 44.12 1.00 1.00 1.00 1.00 2.00 4.00 12.00 46.00 52.00 300.00 365.00 

Wood Floor and Paneling Cleaners 8.48 20.89 1.00 1.00 1.00 1.00 NA 2.00 6.00 24.00 50.00 56.00 350.00 

Typewriter Correction Fluid 40.00 74.78 1.00 1.00 1.00 2.00 4.00 12.00 40.00 100.00 200.00 365.00 520.00 

Adhesives 8.89 26.20 1.00 1.00 1.00 1.00 2.00 3.00 6.00 15.00 28.00 100.00 500.00 

Adhesive Removers 4.22 12.30 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 16.80 100.00 100.00 

Silicone Lubricants 10.32 25.44 1.00 1.00 1.00 1.00 2.00 3.00 10.00 20.00 46.35 150.00 300.00 

Other Lubricants (excluding automotive) 10.66 25.46 1.00 1.00 1.00 1.00 2.00 4.00 10.00 20.00 50.00 100.00 420.00 

Specialized Electronic Cleaners (e.g., for TVs) 13.41 38.16 1.00 1.00 1.00 1.00 2.00 3.00 10.00 24.00 52.00 224.50 400.00 

Latex Paint 3.93 20.81 1.00 1.00 1.00 1.00 1.00 2.00 4.00 6.00 10.00 30.00 800.00 

Oil Paint 5.66 23.10 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 12.00 139.20 300.00 

Wood Stains, Varnishes, and Finishes 4.21 12.19 1.00 1.00 1.00 1.00 1.00 2.00 4.00 7.00 12.00 50.80 250.00 

Paint Removers/Strippers 3.68 9.10 1.00 1.00 1.00 1.00 4.00 2.00 3.00 6.00 11.80 44.56 100.00 

Paint Thinners 6.78 22.10 0.03 0.03 0.10 0.23 1.00 2.00 4.00 12.00 23.00 100.00 352.00 

Aerosol Spray Paint 4.22 15.59 1.00 1.00 1.00 1.00 1.00 2.00 4.00 6.10 12.00 31.05 365.00 

Primers and Special Primers 3.43 8.76 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 10.00 50.06 104.00 

Aerosol Rust Removers 6.17 9.82 1.00 1.00 1.00 1.00 1.00 2.00 6.00 15.00 24.45 50.90 80.00 

Outdoor Water Repellents (for wood or cement) 2.07 3.71 1.00 1.00 1.00 1.00 1.00 2.00 2.00 3.00 5.90 12.00 52.00 

Glass Frostings, Window Tints, and Artificial 

Snow 2.78 21.96 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 27.20 365.00 

Engine Degreasers 4.18 13.72 1.00 1.00 1.00 1.00 1.00 2.00 3.25 6.70 12.00 41.70 300.00 

Carburetor Cleaners 3.77 7.10 1.00 1.00 1.00 1.00 1.00 2.00 3.00 6.00 12.00 47.28 100.00 

Aerosol Spray Paints for Cars 4.50 9.71 1.00 1.00 1.00 1.00 1.00 2.00 4.00 10.00 15.00 60.00 100.00 

Auto Spray Primers 6.42 33.89 1.00 1.00 1.00 1.00 1.00 2.00 3.75 10.00 15.00 139.00 500.00 

Spray Lubricant for Cars 10.31 30.71 1.00 1.00 1.00 1.00 2.00 3.00 6.00 20.00 40.00 105.60 365.00 

Transmission Cleaners 2.28 3.55 1.00 NA 1.00 1.00 1.00 1.00 2.00 3.00 9.00 NA 26.00 

Battery Terminal Protectors 3.95 24.33 1.00 1.00 1.00 1.00 1.00 2.00 2.00 4.00 6.55 41.30 365.00 

Brake Quieters Cleaners 3.00 6.06 1.00 NA 1.00 1.00 1.00 2.00 2.00 6.00 10.40 NA 52.00 

Gasket Remover 2.50 4.39 1.00 NA 1.00 1.00 1.00 1.00 2.00 5.00 6.50 NA 30.00 

Tire/Hubcap Cleaners 11.18 18.67 1.00 1.00 1.00 1.00 2.00 4.00 12.00 30.00 50.00 77.00 200.00 

Ignition and Wire Dryers 3.01 5.71 1.00 1.00 1.00 1.00 1.00 2.00 3.00 5.00 9.70 44.52 60.00 

NA = Not available. 

SD = Standard deviation. 

Min/Max= Minimum/Maximum. 

Source: Westat (1987a). 
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Table 17-5. Exposure Time of Use for Household Solvent Products (users only) 

Products Mean 

(minutes) SD Min 1 5 

Percentile Rankings for Duration of Use (minutes) 

10 25 50 75 90 95 99 Max 

Spray Shoe Polish 7.49 9.60 0.02 0.03 0.25 0.50 2.00 5.00 10.00 18.00 30.00 60.00 60.00 

Water Repellents/Protectors 14.46 24.10 0.02 0.08 0.50 1.40 3.00 10.00 15.00 30.00 60.00 120.00 480.00 

Spot Removers 10.68 22.36 0.02 0.03 0.08 0.25 2.00 5.00 10.00 30.00 30.00 120.00 360.00 

Solvent-Type Cleaning Fluids or Degreasers 29.48 97.49 0.02 0.03 1.00 2.00 5.00 15.00 30.00 60.00 120.00 300.00 1,800.00 

Wood Floor and Paneling Cleaners 74.04 128.43 0.02 1.00 5.00 10.00 20.00 30.00 90.00 147.00 240.00 480.00 2,700.00 

Typewriter Correction Fluid 7.62 29.66 0.02 0.02 0.03 0.03 0.17 1.00 2.00 10.00 32.00 120.00 480.00 

Adhesives 15.58 81.80 0.02 0.03 0.08 0.33 1.00 4.25 10.00 30.00 60.00 180.00 2,880.00 

Adhesive Removers 121.20 171.63 0.03 0.03 1.45 3.00 15.00 60.00 120.00 246.00 480.00 960.00 960.00 

Silicone Lubricants 10.42 29.47 0.02 0.03 0.08 0.17 0.50 2.00 10.00 20.00 45.00 180.00 360.00 

Other Lubricants (excluding automotive) 8.12 32.20 0.02 0.03 0.05 0.08 0.50 2.00 5.00 15.00 30.00 90.00 900.00 

Specialized Electronic Cleaners (e.g., for TVs) 9.47 45.35 0.02 0.03 0.08 0.17 0.50 2.00 5.00 20.00 30.00 93.60 900.00 

Latex Paint 295.08 476.11 0.02 1.00 22.50 30.00 90.00 180.00 360.00 480.00 810.00 2,880.00 5,760.00 

Oil Paint 194.12 345.68 0.02 0.51 15.00 30.00 60.00 12.00 240.00 480.00 579.00 1,702.80 5,760.00 

Wood Stains, Varnishes, and Finishes 117.17 193.05 0.02 0.74 5.00 10.00 30.00 60.00 120.00 140.00 360.00 720.00 280.00 

Paint Removers/Strippers 125.27 286.59 0.02 0.38 5.00 5.00 20.00 60.00 120.00 240.00 420.00 1,200.00 4,320.00 

Paint Thinners 39.43 114.85 0.02 0.08 1.00 2.00 5.00 10.00 30.00 60.00 180.00 480.00 2,400.00 

Aerosol Spray Paint 39.54 87.79 0.02 0.17 2.00 5.00 10.00 20.00 45.00 60.00 120.00 300.00 1,800.00 

Primers and Special Primers 91.29 175.05 0.05 0.24 3.00 5.00 15.00 30.00 120.00 240.00 360.00 981.60 1,920.00 

Aerosol Rust Removers 18.57 48.54 0.02 0.05 0.17 0.25 2.00 5.00 20.00 60.00 60.00 130.20 720.00 

Outdoor Water Repellents (for wood or cement) 104.94 115.36 0.02 0.05 5.00 15.00 30.00 60.00 120.00 240.00 300.00 480.00 960.00 

Glass Frostings, Window Tints, and Artificial Snow 29.45 48.16 0.03 0.14 2.00 3.00 5.00 15.00 30.00 60.00 96.00 268.80 360.00 

Engine Degreasers 29.29 48.14 0.02 0.95 2.00 5.00 10.00 15.00 30.00 60.00 120.00 180.00 900.00 

Carburetor Cleaners 13.57 23.00 0.02 0.08 0.33 1.00 3.00 7.00 15.00 30.00 45.00 120.00 300.00 

Aerosol Spray Paints for Cars 42.77 71.39 0.03 0.19 1.00 3.00 10.00 20.00 60.00 120.00 145.00 360.00 900.00 

Auto Spray Primers 51.45 86.11 0.05 0.22 2.00 5.00 10.00 27.50 60.00 120.00 180.00 529.20 600.00 

Spray Lubricant for Cars 9.90 35.62 0.02 0.03 0.08 0.17 1.00 5.00 10.00 15.00 30.00 120.00 720.00 

Transmission Cleaners 27.90 61.44 0.17 NA 0.35 1.80 5.00 15.00 30.00 60.00 60.00 NA 450.00 

Battery Terminal Protectors 9.61 18.15 0.03 0.04 0.08 0.23 1.00 5.00 10.00 20.00 30.00 120.00 180.00 

Brake Quieters/Cleaners 23.38 36.32 0.07 NA 0.50 1.00 5.00 15.00 30.00 49.50 120.00 NA 240.00 

Gasket Remover 23.57 27.18 0.33 NA 0.50 2.00 6.25 15.00 30.00 60.00 60.00 NA 180.00 

Tire/Hubcap Cleaners 22.66 23.94 0.08 0.71 3.00 5.00 10.00 15.00 30.00 60.00 60.00 120.00 240.00 

Ignition and Wire Dryers 7.24 8.48 0.02 0.02 0.08 0.47 1.50 5.00 10.00 15.00 25.50 48.60 60.00 

NA = Not available. 

SD = Standard deviation. 

Min/Max = Minimum/Maximum. 

Source: Westat (1987a). 
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Table 17-6. Amount of Products Used for Household Solvent Products (users only) 

Products Mean 

(ounces/year) SD 

Min. 1 

Percentile Rankings for Amount of Products Used (ounces/year) 

5 10 25 50 75 90 95 99 Max 

Spray Shoe Polish 9.90 17.90 0.04 0.20 0.63 1.00 2.00 4.50 10.00 24.00 36.00 99.36 180.00 

Water Repellents/Protectors 11.38 22.00 0.04 0.47 0.98 1.43 2.75 6.00 12.00 24.00 33.00 121.84 450.00 

Spot Removers 26.32 90.10 0.01 0.24 0.60 1.00 2.00 5.50 16.00 48.00 119.20 384.00 1,600.00 

Solvent-Type Cleaning Fluids or Degreasers 58.30 226.97 0.04 0.50 2.00 3.00 6.50 16.00 32.00 96.00 192.00 845.00 5,120.00 

Wood Floor and Paneling Cleaners 28.41 57.23 0.03 0.80 2.45 3.50 7.00 14.00 30.00 64.00 96.00 204.40 1,144.00 

Typewriter Correction Fluid 4.14 13.72 0.01 0.02 0.06 0.12 0.30 0.94 2.40 8.00 18.00 67.44 181.80 

Adhesives 7.49 55.90 0.01 0.02 0.05 0.12 0.35 1.00 3.00 8.00 20.00 128.00 1,280.00 

Adhesive Removers 34.46 96.60 0.25 0.29 1.22 2.80 6.00 10.88 32.00 64.00 138.70 665.60 1,024.00 

Silicone Lubricants 12.50 27.85 0.02 0.20 0.69 1.00 2.25 4.50 12.00 24.00 41.20 192.00 312.00 

Other Lubricants (excluding automotive) 9.93 44.18 0.01 0.18 0.30 0.52 1.00 2.25 8.00 18.00 32.00 128.00 1,280.00 

Specialized Electronic Cleaners (e.g., for TVs) 9.48 55.26 0.01 0.05 0.13 0.25 0.52 2.00 6.00 12.65 24.00 109.84 1,024.00 

Latex Paint 371.27 543.86 0.03 4.00 12.92 32.00 64.00 256.00 384.00 857.60 1,280.00 2,560.00 6,400.00 

Oil Paint 168.92 367.82 0.02 0.33 4.00 8.00 25.20 64.00 148.48 384.00 640.00 1,532.16 5,120.00 

Wood Stains, Varnishes, and Finishes 65.06 174.01 0.12 1.09 4.00 4.00 8.00 16.00 64.00 128.00 256.00 768.00 3,840.00 

Paint Removers/Strippers 63.73 144.33 0.64 1.50 4.00 8.00 16.00 32.00 64.00 128.00 256.00 512.00 2,560.00 

Paint Thinners 69.45 190.55 0.03 0.45 3.10 4.00 8.00 20.48 64.00 128.00 256.00 640.00 3,200.00 

Aerosol Spray Paint 30.75 52.84 0.02 0.75 2.01 3.25 7.00 13.00 32.00 65.00 104.00 240.00 1,053.00 

Primers and Special Primers 68.39 171.21 0.01 0.09 1.30 3.23 8.00 16.00 60.00 128.00 256.00 867.75 1,920.00 

Aerosol Rust Removers 18.21 81.37 0.09 0.25 1.00 1.43 2.75 8.00 13.00 32.00 42.60 199.80 1,280.00 

Outdoor Water Repellents (for wood or cement) 148.71 280.65 0.01 0.37 3.63 8.00 16.00 64.00 128.00 448.00 640.00 979.20 3,200.00 

Glass Frostings, Window Tints, and Artificial Snow 13.82 14.91 1.00 1.40 2.38 3.25 6.00 12.00 14.00 28.00 33.00 98.40 120.00 

Engine Degreasers 46.95 135.17 0.04 1.56 4.00 6.00 12.00 16.00 36.00 80.00 160.00 480.00 2,560.00 

Carburetor Cleaners 22.00 50.60 0.10 0.50 1.50 3.00 5.22 12.00 16.00 39.00 75.00 212.00 672.00 

Aerosol Spray Paints for Cars 44.95 89.78 0.04 0.14 1.50 3.00 6.12 16.00 48.00 100.80 156.00 557.76 900.00 

Auto Spray Primers 70.37 274.56 0.12 0.77 3.00 4.00 9.00 16.00 48.00 128.00 222.00 1,167.36 3840.00 

Spray Lubricant for Cars 18.63 54.74 0.08 0.40 0.96 1.00 2.75 6.00 15.50 36.00 64.00 240.00 864.00 

Transmission Cleaners 35.71 62.93 2.00 NA 3.75 4.00 8.00 15.00 32.00 77.00 140.00 NA 360.00 

Battery Terminal Protectors 16.49 87.84 0.12 0.13 0.58 1.00 2.00 4.00 8.00 15.00 24.60 627.00 1,050.00 

Brake Quieters/Cleaners 11.72 13.25 0.50 NA 1.00 2.00 3.02 8.00 14.25 32.00 38.60 NA 78.00 

Gasket Remover 13.25 22.35 0.50 NA 1.00 1.00 3.75 7.75 16.00 24.00 58.40 NA 160.00 

Tire/Hubcap Cleaners 31.58 80.39 0.12 0.50 1.82 3.00 6.00 12.00 28.00 64.00 96.00 443.52 960.00 

Ignition and Wire Dryers 9.02 14.59 0.13 0.32 1.09 1.50 3.00 6.00 10.75 16.00 20.55 113.04 120.00 

NA = Not available. 

SD = Standard deviation. 

Min/Max = Minimum/Maximum. 

Source: Westat (1987a). 
September 

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17-19 

Table 17-7. Time Exposed After Duration of Use for Household Solvent Products (users only) 

Products Mean 

(minutes) SD 

Min. 1 

Percentile Rankings for Time Exposed After Duration of Use (minutes) 

5 10 25 50 75 90 95 99 Max 

Spray Shoe Polish 31.40 80.50 0.00 0.00 0.00 0.00 0.00 5.00 20.00 120.00 120.00 480.00 720.00 

Water Repellents/Protectors 37.95 111.40 0.00 0.00 0.00 0.00 0.00 3.00 20.00 120.00 240.00 480.00 1,800.00 

Spot Removers 43.65 106.97 0.00 0.00 0.00 0.00 1.00 5.00 30.00 120.00 240.00 480.00 1,440.00 

Solvent-Type Cleaning Fluids or Degreasers 33.29 90.39 0.00 0.00 0.00 0.00 0.00 3.00 28.75 60.00 180.00 480.00 1,440.00 

Wood Floor and Paneling Cleaners 96.75 192.88 0.00 0.00 0.00 0.00 5.00 30.00 120.00 240.00 480.00 1,062.00 1,440.00 

Typewriter Correction Fluid 124.70 153.46 0.00 0.00 1.00 5.00 30.00 60.00 180.00 360.00 480.00 600.00 1,800.00 

Adhesives 68.88 163.72 0.00 0.00 0.00 0.00 1.00 10.00 60.00 180.00 360.00 720.00 2,100.00 

Adhesive Removers 94.12 157.69 0.00 0.00 0.00 0.00 1.75 20.00 120.00 360.00 480.00 720.00 720.00 

Silicone Lubricants 30.77 107.39 0.00 0.00 0.00 0.00 0.00 0.00 10.00 60.00 180.00 480.00 1,440.00 

Other Lubricants (excluding automotive) 47.45 127.11 0.00 0.00 0.00 0.00 0.00 2.00 30.00 120.00 240.00 485.40 1,440.00 

Specialized Electronic Cleaners (e.g., for TVs) 117.24 154.38 0.00 0.00 0.00 1.00 10.00 60.00 180.00 300.00 480.00 720.00 1,440.00 

Latex Paint 91.38 254.61 0.00 0.00 0.00 0.00 0.00 5.00 60.00 240.00 480.00 1,440.00 2,880.00 

Oil Paint 44.56 155.19 0.00 0.00 0.00 0.00 0.00 0.00 30.00 120.00 240.00 480.00 2,880.00 

Wood Stains, Varnishes, and Finishes 48.33 156.44 0.00 0.00 0.00 0.00 0.00 1.00 30.00 120.00 240.00 694.00 2,880.00 

Paint Removers/Strippers 31.38 103.07 0.00 0.00 0.00 0.00 0.00 0.00 20.00 60.00 180.00 541.20 1,440.00 

Paint Thinners 32.86 105.62 0.00 0.00 0.00 0.00 0.00 0.00 15.00 60.00 180.00 480.00 1,440.00 

Aerosol Spray Paint 12.70 62.80 0.00 0.00 0.00 0.00 0.00 0.00 1.00 30.00 60.00 260.50 1,440.00 

Primers and Special Primers 22.28 65.57 0.00 0.00 0.00 0.00 0.00 0.00 10.00 60.00 120.00 319.20 720.00 

Aerosol Rust Removers 15.06 47.58 0.00 0.00 0.00 0.00 0.00 0.00 5.00 60.00 60.00 190.20 600.00 

Outdoor Water Repellents (for wood or cement) 8.33 43.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.00 58.50 309.60 420.00 

Glass Frostings, Window Tints, and Artificial Snow 137.87 243.21 0.00 0.00 0.00 0.00 3.00 60.00 180.00 360.00 480.00 1,440.00 1,800.00 

Engine Degreasers 4.52 24.39 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15.50 120.00 360.00 

Carburetor Cleaners 7.51 68.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 30.00 120.60 1,800.00 

Aerosol Spray Paints for Cars 10.71 45.53 0.00 0.00 0.00 0.00 0.00 0.00 0.00 17.50 60.00 282.00 480.00 

Auto Spray Primers 11.37 45.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.00 77.25 360.00 360.00 

Spray Lubricant for Cars 4.54 30.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 15.00 70.20 420.00 

Transmission Cleaners 5.29 29.50 0.00 NA 0.00 0.00 0.00 0.00 0.00 5.00 22.50 NA 240.00 

Battery Terminal Protectors 3.25 17.27 0.00 NA 0.00 0.00 0.00 0.00 0.00 2.90 15.00 120.00 180.00 

Brake Quieters/Cleaners 10.27 30.02 0.00 NA 0.00 0.00 0.00 0.00 0.00 30.00 120.00 NA 120.00 

Gasket Remover 27.56 58.54 0.00 NA 0.00 0.00 0.00 0.00 12.50 120.00 180.00 NA 240.00 

Tire/Hubcap Cleaners 1.51 20.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 30.00 480.00 

Ignition and Wire Dryers 6.39 31.63 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 30.00 216.60 240.00 

NA = Not available. 

SD = Standard deviation. 

Min/Max = Minimum/Maximum. 

Source: Westat (1987a). 
 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-8. Total Exposure Time of Performing Task and Product Type Used by Task for Household 

Cleaning Products 

Tasks Mean 

(hours/year) 

Median 

(hours/year) 

Product Type 

Used 

Percent of 

Preference 

Clean Bathroom Sinks and Tubs 44 26 Liquid 29% 

Powder 44% 

Aerosol 16% 

Spray pump 10% 

Other 1% 

Clean Kitchen Sinks 41 18 Liquid 31% 

Powder 61% 

Aerosol 2% 

Spray pump 4% 

Other 2% 

Clean Inside of Cabinets 

(e.g., kitchen) 

12 5 Liquid 68% 

Powder 12% 

Aerosol 2% 

Spray pump 16% 

Other 2% 

Clean Outside of Cabinets 21 6 Liquid 61% 

Powder 8% 

Aerosol 16% 

Spray pump 13% 

Other 2% 

Wipe Off Kitchen Counters 92 55 Liquid 67% 

Powder 13% 

Aerosol 2% 

Spray pump 15% 

Other 3% 

Thoroughly Clean Counters 24 13 Liquid 56% 

Powder 21% 

Aerosol 5% 

Spray pump 17% 

Other 1% 

Clean Bathroom Floors 20 9 Liquid 70% 

Powder 21% 

Aerosol 2% 

Spray pump 4% 

Other 3% 

Clean Kitchen Floors 31 14 Liquid 70% 

Powder 27% 

Aerosol 2% 

Spray pump 1% 

Other -

Clean Bathroom or Other tilted or Ceramic Walls 16 9 Liquid 37% 

Powder 18% 

Aerosol 17% 

Spray pump 25% 

Other 3% 

Page Exposure Factors Handbook 

17-20 September 2011 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-8. Total Exposure Time of Performing Task and Product Type Used by Task for Household 

Cleaning Products (continued) 

Tasks Mean 

(hours/year) 

Median 

(hours/year) 

Product Type 

Used 

Percent of 

Preference 

Clean Outside of Windows 13 6 Liquid 27% 

Powder 2% 

Aerosol 6% 

Spray pump 65% 

Other -

Clean Inside of Windows 18 6 Liquid 24% 

Powder 1% 

Aerosol 8% 

Spray pump 66% 

Other 2% 

Clean Glass Surfaces Such as Mirrors and Tables 34 13 Liquid 13% 

Powder 1% 

Aerosol 8% 

Spray pump 76% 

Other 2% 

Clean Outside of Refrigerator and Other Appliances 27 13 Liquid 48% 

Powder 3% 

Aerosol 7% 

Spray pump 38% 

Other 4% 

Clean Spots or Dirt on Walls or Doors 

Finishes 

19 8 Liquid 46% 

Powder 15% 

Aerosol 4% 

Spray pump 30% 

Other 4% 

- Indicates value is less than 1%. 

Source: Westat (1987c). 

Exposure Factors Handbook Page
 

September 2011 17-21 
Table 17-9. Percentile Rankings for Total Exposure Time in Performing Household Tasks 

Tasks Min 

Percentile Rankings for Total Exposure Time Performing Task 

(hours/year) 

10th 25th 50th 75th 90th 95th Max 

Clean Bathroom Sinks and Tubs 

Clean Kitchen Sinks 

Clean Inside of Kitchen Cabinets 

Clean Outside of Cabinets 

Wipe Off Kitchen Counters 

Thoroughly Clean Counters 

Clean Bathroom Floors 

Clean Kitchen Floors 

Clean Bathroom or Other Tilted or Ceramic 

Walls 

Clean Outside of Windows 

Clean Inside of Windows 

Clean Glass Surfaces Such as Mirrors and 

Tables 

Clean Outside Refrigerator and Other 

Appliances 

Clean Spots or Dirt on Walls or Doors 

0.4 

0.3 

0.2 

0.1 

1.2 

0.2 

0.1 

0.5 

0.2 

0.1 

0.2 

0.2 

0.1 

0.1 

5.2 

3.5 

1 

1 

12 

1.8 

2 

4.3 

1 

1.5 

1.2 

1.7 

1.8 

0.6 

13 

8.7 

2 

2 

24.3 

6 

4.3 

8.7 

3 

2 

3 

6 

4.3 

2 

26 

18.3 

4.8 

6 

54.8 

13 

8.7 

14 

8.7 

6 

6 

13 

13 

8 

52 

60.8 

12 

17.3 

91.5 

26 

26 

26 

26 

11.5 

19.5 

26 

30.4 

24 

91.3 

97.6 

32.5 

36 

231.2 

52 

36.8 

52 

36 

24 

36 

60.8 

91.3 

52 

121.7 

121.7 

48 

78.7 

456.3 

94.4 

71.5 

97 

52 

32.6 

72 

104 

95.3 

78 

365 

547.5 

208 

780 

912.5 

547.5 

365 

730 

208 

468 

273 

1460 

365 

312 

Min 

Max 

Source: 

= Minimum. 

= Maximum. 

Westat (1987c). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 

17-22 September 2011 
 

 

Chapter 17—Exposure Factors Handbook 

Consumer Products 

Exposure Factors Handbook PageSeptember 2011 17-23

Table 17-10. Mean Percentile Rankings for Frequency of Performing Household Tasks 

Tasks Mean 

Min 10th 25th 

Percentile Rankings 

50th 75th 90th 95th Max 

Clean Bathroom Sinks and Tubs 3 ×/week 0.2 ×/week 1 ×/week 1 ×/week 2 ×/week 3.5 ×/week 7 ×/week 7 ×/week 42 ×/week 

Clean Kitchen Sinks 7 ×/week 0 ×/week 1 ×/week 2 ×/week 7 ×/week 7 ×/week 15 ×/week 21 ×/week 28 ×/week 

Clean Inside of Cabinets Such as Those 

in the Kitchen 

9 ×/year 1 ×/year 1 ×/year 1 ×/year 2 ×/year 12 ×/year 12 ×/year 52 ×/year 156 ×/year 

Clean Outside of Cabinets 3 ×/month 0.1 ×/month 0.1 ×/month 0.3 ×/month 1 ×/month 4 ×/month 4 ×/month 22 ×/month 30 ×/month 

Wipe Off Counters Such as Those in the 

Kitchen 2 ×/day 0 ×/day 0.4 ×/day 1 ×/day 1 ×/day 3 ×/day 4 ×/day 6 ×/day 16 ×/day 

Thoroughly Clean Counters 8 ×/month 0.1 ×/month 0.8 ×/month 1 ×/month 4 ×/month 4 ×/month 30 ×/month 30 ×/month 183 ×/month 

Clean Bathroom Floors 6 ×/month 0.2 ×/month 1 ×/month 2 ×/month 4 ×/month 4 ×/month 13 ×/month 30 ×/month 30 ×/month 

Clean Kitchen Floors 6 ×/month 0.1 ×/month 1 ×/month 2 ×/month 4 ×/month 4 ×/month 13 ×/month 30 ×/month 30 ×/month 

Clean Bathroom or Other Tiled or 

Ceramic Walls 4 ×/month 0.1 ×/month 0.2 ×/month 1 ×/month 2 ×/month 4 ×/month 9 ×/month 13 ×/month 30 ×/month 

Clean Outside of Windows 5 ×/year 1 ×/year 1 ×/year 1 ×/year 2 ×/year 4 ×/year 12 ×/year 12 ×/year 156 ×/year 

Clean Inside of Windows 10 ×/year 1 ×/year 1 ×/year 2 ×/year 4 ×/year 12 ×/year 24 ×/year 52 ×/year 156 ×/year 

Clean Other Glass Surfaces such as 

Mirrors and Tables 

7 ×/month 0.1 ×/month 1 ×/month 2 ×/month 4 ×/month 4 ×/month 17 ×/month 30 ×/month 61 ×/month 

Clean Outside of Refrigerator and Other 

Appliances 

10 ×/month 0.2 ×/month 1 ×/month 2 ×/month 4 ×/month 13 ×/month 30 ×/month 30 ×/month 61 ×/month 

Clean Spots or Dirt on Walls or Doors 

Min = Minimum. 

Max = Maximum. 

6 ×/month 0.1 ×/month 0.2 ×/month 0.3 ×/month 1 ×/month 4 ×/month 13 ×/month 30 ×/month 152 ×/month 

Source: Westat (1987c). 
Table 17-11. Mean and Percentile Rankings for Exposure Time per Event of Performing Household Tasks 

Tasks Mean 

(minutes/event) 

Percentile Rankings (minutes/event) 

Min 10th 25th 50th 75th 90th 95th Max 

Clean Bathroom Sinks and Tubs 

Clean Kitchen Sinks 

Clean Inside of Cabinets Such as Those in the 

Kitchen 

Clean Outside of Cabinets 

Wipe Off Counters Such as Those in the 

Kitchen 

Thoroughly Clean Counters 

Clean Bathroom Floors 

Clean Kitchen Floors 

Clean Bathroom or Other Tiled or Ceramic 

Walls 

Clean Outside of Windows 

Clean Inside of Windows 

Clean Other Glass Surfaces Such as Mirrors 

and Tables 

Clean Outside of Refrigerator and Other 

Appliances 

Clean Spots or Dirt on Walls or Doors 

20 

10 

137 

52 

9 

25 

16 

30 

34 

180 

127 

24 

19 

50 

1 

1 

5 

1 

1 

1 

1 

2 

1 

4 

4 

1 

1 

1 

5 

2 

24 

5 

2 

5 

5 

10 

5 

30 

20 

5 

4 

5 

10 

3 

44 

15 

3 

10 

10 

15 

15 

60 

45 

10 

5 

10 

15 

5 

120 

30 

5 

15 

15 

20 

30 

120 

90 

15 

10 

20 

30 

10 

180 

60 

10 

30 

20 

30 

45 

240 

158 

30 

20 

60 

45 

15 

240 

120 

15 

60 

30 

60 

60 

420 

300 

60 

30 

120 

60 

20 

360 

180 

30 

90 

38 

60 

120 

480 

381 

60 

45 

216 

90 

480 

2,880 

330 

120 

180 

60 

180 

240 

1,200 

1,200 

180 

240 

960 

Min 

Max 

Source: 

= Minimum. 

= Maximum. 

Westat (1987c). 

Table 17-12. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaning a 

Percentile Rankings of Total Exposure Time Mean Products (hours/year) Min 10th 25th 

(hours/year) 

50th 75th 90th 95th Max 

Dish Detergents 107 0.2 6 24 56 134 274 486 941 

Glass Cleaners 67 0.4 3 12 29 62 139 260 1,508 

Floor Cleaners 52 0.7 4 7 22 52 102 414 449 

Furniture Polish 32 0.1 0.3 1 12 36 101 215 243 

Bathroom Tile Cleaners 47 0.5 2 8 17 48 115 287 369 

Liquid Cleansers 68 0.2 2 9 22 52 122 215 2,381 

Scouring Powders 78 0.3 9 17 35 92 165 281 747 

Laundry Detergents 66 0.6 8 14 48 103 174 202 202 

Rug Cleaners/Shampoos 12 0.3 0.3 0.3 9 26 26 26 26 

All Purpose Cleaners 64 0.3 4 9 26 77 174 262 677 a	 The data in Table 17-12 reflect only the 14 tasks included in the survey. Therefore, many of the durations reported in 

the table underestimate the hours of the use of the product group. For example, use of dish detergents to wash dishes is 

not included. 

Min = Minimum. 

Max = Maximum. 

Source: Westat (1987c). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 

17-24 September 2011 
Table 17-13. Total Exposure Time of Painting Activity of Interior Painters (hours) 

Types of Paint Mean 

(hours) SD 

Percentile Rankings for Duration of Painting Activity 

(hours) 

Min 10 25 50 75 90 95 Max 

Latex 12.2 11.3 1 3 4 9 15 24 40 248 

Oil-Based 10.7 15.6 1 1.6 3 6 10 21.6 65.6 72 

Wood Stains and Varnishes 8.6 10.9 1 1 2 4 9.3 24 40 42 

SD = Standard deviation. 

Min = Minimum. 

Max = Maximum. 

Source: Westat (1987b). 

Table 17-14. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of Occasions 

Spent Painting per Year 

Types of Paint 

Duration of 

Painting/Occasion 

(hours) 

Frequency of 

Occasions Spent 

Painting/Year Percentile Rankings for Frequency of Occasions Spent Painting 

Mean Median Mean SD Min 10 25 50 75 90 95 Max 

Latex 3.0 3 4.2 5.5 1 1 2 3 4 9 10 62 

Oil-Based 2.1 3 5.1 12.0 1 1 1 2 4 8 26 72 

Wood Stains and 

Varnishes 

2.2 2 4.0 4.9 1 1 1 2 4 9 20 20 

SD = Standard deviation. 

Min = Minimum. 

Max = Maximum. 

Source: Westat (1987b). 

 

Table 17-15. Amount of Paint Used by Interior Painters 

Types of Paint Median 

(gallons) 

Mean 

(gallons) SD 

Percentile Rankings for Amount of Paint Used 

(gallons) 

Min 10 25 50 75 90 95 Max 

Latex 3.0 3.9 4.6 0.1 1 2 3 5 8 10 50 

Oil-Based 2.0 2.6 3.0 0.1 0.3 0.5 2 3 7 12 12 

Wood Stains and 

Varnishes 

0.8 0.9 0.8 0.1 0.1 0.3 0.8 1 2 2 4.3 

SD = Standard deviation. 

Min = Minimum. 

Max = Maximum. 

Source: Westat (1987b). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Exposure Factors Handbook Page
 

September 2011 17-25 
 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-16. Frequency of Use and Amount of Product Used for Adhesive Removers 

No. of Times 

Used Within the 

Last 12 Months 

N = 58 

Minutes 

Using 

N = 52 

Minutes in Room 

After Usinga 

N = 51 

Minutes in 

Room After 

Usingb 

N = 5 

Amount Used in 

Past Year (fluid oz.) 

N = 51 

Amount per 

Use (fluid oz.) 

N = 51 

Mean 1.66 172.87 13.79 143.37 96.95 81.84 

Standard Deviation 1.67 304.50 67.40 169.31 213.20 210.44 

Minimum Value 

1st Percentile 

5th Percentile 

10th Percentile 

25th Percentile 

1.00 

1.00 

1.00 

1.00 

1.00 

5.00 

5.00 

10.00 

15.00 

29.50 

0.00 

0.00 

0.00 

0.00 

0.00 

5.00 

5.00 

5.00 

5.00 

20.00 

13.00 

13.00 

13.00 

16.00 

16.00 

5.20 

5.20 

6.50 

10.67 

16.00 

Median Value 

75th Percentile 

90th Percentile 

95th Percentile 

99th Percentile 

1.00 

2.00 

3.00 

5.00 

12.00 

120.00 

240.00 

480.00 

1,440.00 

1,440.00 

0.00 

0.00 

0.00 

120.00 

420.00 

120.00 

420.00 

420.00 

420.00 

420.00 

32.00 

96.00 

128.00 

384.00 

1,280.00 

26.00 

64.00 

128.00 

192.00 

1,280.00 

Maximum Value 12.00 1,440.00 420.00 1,440.00 1,280.00 1,280.00 a Includes those who did not spend any time in the room after use. b Includes only those who spent time in the room. 

Source: Abt (1992). 

Table 17-17. Adhesive Remover Usage by Sex 

Sex 

Males Females 

N = 25 N = 33 

Mean number of months since last time adhesive remover was used – includes 35.33 43.89 

all respondents (unweighted N = 240). 

Mean number of uses of product in the past year. 1.94 1.30 

Mean number of minutes spent with the product during last use. 127.95 233.43 

Mean number of minutes spent in the room after last use of product. (Includes 19.76 0 

all recent users.) 

Mean number of minutes spent in the room after last use of product. (Includes 143.37 0 

only those who did not leave immediately.) 

Mean ounces of product used in the past year. 70.48 139.71 

Mean ounces of product used per use in the past year. 48.70 130.36 

Source: Abt (1992). 

Page Exposure Factors Handbook 

17-26 September 2011 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-18. Frequency of Use and Amount of Product Used for Spray Paint 

No. of Times 

Used Within the 

Last 12 Months 

N = 775 

Minutes 

Using 

N = 786 

Minutes in Room 

After Usinga 

N = 791 

Minutes in Room 

After Usingb 

N = 35 

Amount Used in 

Past Year 

(fluid oz.) 

N = 778 

Amount per 

Use (fluid oz.) 

N = 778 

Mean 8.23 40.87 3.55 65.06 83.92 

Standard Deviation 31.98 71.71 22.03 70.02 175.32 

Minimum Value 

1st Percentile 

5th Percentile 

10th Percentile 

25th Percentile 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

3.00 

5.00 

10.00 

0.00 

0.00 

0.00 

0.00 

0.00 

1.00 

1.00 

1.00 

10.00 

15.00 

13.00 

13.00 

13.00 

13.00 

13.00 

Median Value 

75th Percentile 

90th Percentile 

95th Percentile 

99th Percentile 

2.00 

4.00 

11.00 

20.00 

104.00 

20.00 

45.00 

90.00 

120.00 

360.00 

0.00 

0.00 

0.00 

0.00 

120.00 

30.00 

60.00 

120.00 

120.00 

300.00 

26.00 

65.00 

156.00 

260.00 

1,170.00 

Maximum Value 365.00 960.00 300.00 300.00 1,664.00 

19.04 

25.34 

0.36 

0.36 

3.47 

6.50 

9.75 

13.00 

21.67 

36.11 

52.00 

104.00 

312.00 a Includes those who did not spend any time in the room after use. b Includes only those who spent time in the room. 

Source: Abt (1992). 

Table 17-19. Spray Paint Usage by Sex 

Sex 

Males Females 

N = 405 N = 386 

Mean number of months since last time spray paint was used – includes all 

respondents (unweighted N = 1724). 17.39 26.46 

Mean number of uses of product in the past year. 10.45 4.63 

Mean number of minutes spent with the product during last use. 40.87 40.88 

Mean number of minutes spent in the room after last use of product. (Includes 

all recent users.) 5.49 0.40 

Mean number of minutes spent in the room after last use of product. (Includes 

only those who did not leave immediately.) 67.76 34.69 

Mean ounces of product used in the past year. 103.07 59.99 

Mean ounces of product used per use in the past year. 18.50 19.92 

Source: Abt (1992). 

Exposure Factors Handbook Page
 

September 2011 17-27 
 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-20. Frequency of Use and Amount of Product Used for Paint Removers/Strippers 

No. of Times 

Used Within the 

Last 12 Months 

N = 316 

Minutes 

Using 

N = 390 

Minutes in Room 

After Usinga 

N = 390 

Minutes in Room 

After Usingb 

N = 39 

Amount Used in 

Past Year 

(fluid oz.) 

N = 307 

Amount per 

Use (fluid oz.) 

N = 307 

Mean 3.54 144.59 12.96 93.88 142.05 64.84 

Standard Deviation 7.32 175.54 85.07 211.71 321.73 157.50 

Minimum Value 

1st Percentile 

5th Percentile 

10th Percentile 

25th Percentile 

1.00 

1.00 

1.00 

1.00 

1.00 

2.00 

5.00 

15.00 

20.00 

45.00 

0.00 

0.00 

0.00 

0.00 

0.00 

1.00 

1.00 

1.00 

3.00 

10.00 

15.00 

15.00 

16.00 

16.00 

32.00 

0.35 

2.67 

8.00 

10.67 

16.00 

Median Value 

75th Percentile 

90th Percentile 

95th Percentile 

99th Percentile 

2.00 

3.00 

6.00 

12.00 

50.00 

120.00 

180.00 

360.00 

480.00 

720.00 

0.00 

0.00 

10.00 

60.00 

180.00 

60.00 

120.00 

180.00 

420.00 

1,440.00 

64.00 

128.00 

256.00 

384.00 

1,920.00 

32.00 

64.00 

128.00 

192.00 

320.00 

Maximum Value 70.00 1,440.00 1,440.00 1,440.00 3,200.00 2,560.00 a Includes those who did not spend any time in the room after use. b Includes only those who spent time in the room. 

Source: Abt (1992). 

Table 17-21. Paint Stripper Usage by Sex 

Males 

N = 156 

Sex 

Females 

N = 162 

Mean number of months since last time paint stripper was used – includes all 

respondents (unweighted N = 1724). 32.07 47.63 

Mean number of uses of product in the past year. 3.88 3.01 

Mean number of minutes spent with the product during last use. 136.70 156.85 

Mean number of minutes spent in the room after last use of product. (Includes 

all recent users.) 15.07 9.80 

Mean number of minutes spent in the room after last use of product. (Includes 

only those who did not leave immediately.) 

Mean ounces of product used in the past year. 

101.42 

160.27 

80.15 

114.05 

Mean ounces of product used per use in the past year. 74.32 50.29 

Source: Abt (1992). 

Page Exposure Factors Handbook 

17-28 September 2011 
Table 17-22. Number of Minutes Spent Using Any Microwave Oven (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

5 to 11 years 62 0 0 0 1 1 2 5 10 15 20 30 30 

12 to 17 years 141 0 0 0 1 2 3 5 10 15 30 30 60 

18 to 64 years 1,686 0 0 1 2 3 5 10 15 25 45 60 121 

> 64 years 375 0 0 1 2 3 5 10 20 30 60 60 70 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N =doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

 

 

Table 17-23. Number of Minutes Spent in Activities Working With or Near Freshly 

Applied Paints (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 7 3 3 3 3 5 15 121 121 121 121 121 121 

5 to 11 years 12 5 5 5 15 20 45 120 120 121 121 121 121 

12 to 17 years 20 0 0 0.5 3 8 45 75 121 121 121 121 121 

18 to 64 years 212 0 0 1 2 11 60 121 121 121 121 121 121 

> 64 years 20 0 0 0 3 18 90 121 121 121 121 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N = doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

 

 

 

Table 17-24. Number of Minutes Spent in Activities Working With or Near Household 

Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 21 0 0 0 0 5 10 15 20 30 121 121 121 

5 to 11 years 26 1 1 2 2 3 5 15 30 30 30 30 30 

12 to 17 years 41 0 0 0 0 2 5 10 40 60 60 60 60 

18 to 64 years 672 0 0 1 2 5 10 20 60 121 121 121 121 

> 64 years 127 0 0 0 1 3 5 15 30 60 120 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N = doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Exposure Factors Handbook Page
 

September 2011 17-29 
Table 17-25. Number of Minutes Spent in Activities (at home or elsewhere) Working With 

or Near Floorwax, Furniture Wax, or Shoe Polish (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 13 0 0 0 5 10 15 20 60 121 121 121 121 

5 to 11 years 21 0 0 2 2 3 5 10 35 60 120 120 120 

12 to 17 years 15 0 0 0 1 2 10 25 45 121 121 121 121 

18 to 64 years 238 0 0 2 3 5 15 30 120 121 121 121 121 

> 64 years 34 0 0 0 2 5 10 20 35 121 121 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N =doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

 

 

Table 17-26. Number of Minutes Spent in Activities Working With or Near Glue 

(minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 6 0 0 0 0 30 30 30 50 50 50 50 50 

5 to 11 years 36 2 2 3 5 5 12.5 25 30 60 120 120 120 

12 to 17 years 34 0 0 1 2 5 10 30 30 60 120 120 120 

18 to 64 years 207 0 0 0 1 5 20 90 121 121 121 121 121 

> 64 years 10 0 0 0 0 0 4 60 121 121 121 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N = doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

 

 

Table 17-27. Number of Minutes Spent in Activities Working With or Near Solvents, 

Fumes, or Strong Smelling Chemicals (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 7 0 0 0 0 1 5 60 121 121 121 121 121 

5 to 11 years 16 0 0 0 2 5 5 17.5 45 70 70 70 70 

12 to 17 years 38 0 0 0 0 5 10 60 121 121 121 121 121 

18 to 64 years 407 0 0 1 2 5 30 121 121 121 121 121 121 

> 64 years 21 0 0 0 0 2 5 15 121 121 121 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N = doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 

17-30 September 2011 
Table 17-28. Number of Minutes Spent in Activities Working With or Near Stain or Spot 

Removers (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 3 0 0 0 0 0 0 3 3 3 3 3 3 

5 to 11 years 3 3 3 3 3 3 5 5 5 5 5 5 5 

12 to 17 years 7 0 0 0 0 5 15 35 60 60 60 60 60 

18 to 64 years 87 0 0 0 0 2 5 15 60 121 121 121 121 

> 64 years 9 0 0 0 0 2 3 15 121 121 121 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N =doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

 

 

Table 17-29. Number of Minutes Spent in Activities Working With or Near Gasoline or 

Diesel-Powered Equipment, Besides Automobiles (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 14 0 0 0 1 5 22.5 120 121 121 121 121 121 

5 to 11 years 12 1 1 1 3 7.5 25 50 60 60 60 60 60 

12 to 17 years 25 2 2 5 5 13 35 120 121 121 121 121 121 

18 to 64 years 312 0 0 1 3 15 60 121 121 121 121 121 121 

> 64 years 26 2 2 2 3 10 25 90 121 121 121 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N = doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

 

 

Table 17-30. Number of Minutes Spent in Activities Working With or Near Pesticides, 

Including Bug Sprays or Bug Strips (minutes/day) 

Age Group Percentiles 

N 1 2 5 10 25 50 75 90 95 98 99 Max 

1 to 4 years 6 1 1 1 1 3 10 15 20 20 20 20 20 

5 to 11 years 16 0 0 0 0 1.5 7.5 30 121 121 121 121 121 

12 to 17 years 10 0 0 0 0 2 2.5 40 121 121 121 121 121 

18 to 64 years 190 0 0 0 1 2 10 88 121 121 121 121 121 

> 64 years 764 31 0 0 0 02 5 15 60 121 121 121 121 

Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; 

N = doer sample size; percentiles are the percentage of doers below or equal to a given number 

of minutes. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Exposure Factors Handbook Page
 

September 2011 17-31 
Table 17-31. Number of Respondents Using Cologne, Perfume, Aftershave, or Other Fragrances at
 

Specified Daily Frequencies
 

Age Group Total N 

Number of Times Used in a Day 

1 to 2 3 to 5 6 to 9 10+ Do Not 

Know 

5 to 11 years 26 24 2 * * * 

12 to 17 years 144 133 9 * 1 1 

18 to 64 years 1,735 1,635 93 3 1 3 

> 64 years 285 277 8 0 0 0 

* = Missing data. 

N = Number of respondents. 

Source: U.S. EPA (1996). 

 

 

Table 17-32. Number of Respondents Using Any Aerosol Spray Product or Personal Care Item Such as 

Deodorant or Hair Spray at Specified Daily Frequencies 

Age Group Total N Number of Times Used in a Day 

1 2 3 4 5 6 7 10 10+ Don’t Know 

1 to 4 years 

5 to 11 years 

12 to 17 years 

18 to 64 years 

> 64 years 

40 

75 

103 

1,071 

175 

30 

57 

53 

724 

141 

9 

14 

31 

263 

27 

0 

1 

12 

39 

4 

0 

1 

4 

15 

0 

1 

1 

1 

13 

0 

0 

1 

0 

1 

0 

0 

0 

0 

1 

0 

0 

0 

1 

2 

0 

0 

0 

1 

8 

1 

0 

0 

0 

5 

2 

N = Number of respondents. 

Source: U.S. EPA (1996). 

Table 17-33. Number of Respondents Using a Humidifier at Home 

Frequency 

Age Group Total N Almost 

Every 3–5 Times a 1−2 Times a 1−2 Times a Don’t 

Day Week Week Month Know 

1 to 4 years 111 33 16 7 53 2 

5 to 11 years 88 18 10 12 46 2 

12 to 17 years 83 21 7 5 49 1 

18 to 64 years 629 183 77 70 287 12 

> 64 years 120 42 10 10 53 5 

N = Number of respondents. 

Source: U.S. EPA (1996). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 

17-32 September 2011 
Table 17-34. Number of Respondents Indicating Pesticides Were Applied by a Professional at Home to 

Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
 

Age Group Total N 

Frequency 

(number of times over a 6-month period that pesticides were applied by a 

professional) 

None 1 to 2 3 to 5 6 to 9 10+ Don’t Know 

<1 year 

1 to <2 years 

2 to <3 years 

3 to <6 years 

6 to <11 years 

11 to <16 years 

16 to <21 years 

18 to 64 years 

> 64 years 

15 

23 

32 

80 

106 

115 

87 

1,264 

243 

9 

13 

9 

51 

59 

68 

40 

660 

146 

4 

5 

15 

22 

22 

35 

36 

387 

55 

1 

3 

5 

5 

7 

4 

2 

89 

15 

1 

1 

3 

2 

17 

6 

5 

97 

19 

0 

1 

0 

0 

1 

0 

1 

15 

3 

0 

0 

0 

0 

0 

2 

3 

16 

5 

N 

Source: 

= Number of respondents. 

U.S. EPA reanalysis of NHAPS (U.S. EPA, 1996) data. 

Table 17-35. Number of Respondents Reporting Pesticides Applied by the Consumer at Home to
 

Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
 

Frequency 

Age Group Total N (number of times over a 6-month period that pesticides were applied by a resident) 

None 1 to 2 3 to 5 6 to 9 10+ Don’t Know 

<1 year 15 4 8 2 0 1 0 

1 to <2 years 23 11 10 1 0 1 0 

2 to <3 years 32 18 9 2 2 1 0 

3 to <6 years 80 26 35 18 1 0 0 

6 to <11 years 106 37 49 14 1 4 1 

11 to <16 years 115 37 50 18 4 6 0 

16 to <21 years 87 36 33 9 4 4 1 

18 to 64 years 1,264 473 477 192 48 55 19 

> 64 years 243 94 85 31 15 9 9 

N = Number of respondents. 

Source: U.S. EPA reanalysis of NHAPS (U.S. EPA, 1996) data. 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Exposure Factors Handbook Page
 

September 2011 17-33 
 

 

Table 17-36. Household Demographics and Pesticide Types, Characteristics, 

and Frequency of Pesticide Use 

Survey Population Demographics 

Numbera Percenta 

Sex 

Female 

Male 

Language of Interview

Spanish

English

Reading Skills

Able to read English

Able to read Spanish

Number in Household 

2 to 3 people

4 to 5 people

6 to 8 people

Children under 10 years

1 child 

2 children 

3 to 5 children 

Type of Home

Single family detached

Multi-family

Trailer/mobile home

Single-family attached

Apartment/other 

Pets 

Pets kept in household

Pesticides used on pets 

Type of Pesticide

Insecticide 

Rodenticide 

Herbicide 

Storage of Pesticide

Kitchen 

Garage/shed

Laundry/washroom

Other, inside home 

Other, outside home 

Bathroom 

Basement 

Closet 

Storage Precautions

Child-resistant container 

Pesticide locked away

Storage Risks

< 4 feet from ground

Kept near food

Kept near dishes/cookware 

Disposal 

Throw it away

Wrap in separate container, throw away

Other 

Frequency of Use

More than once/week

Once/week

Once/month

Once every 3 months

Once every 6 months

Once/year

Time Stored in Home 

< 6 months 

6 to 12 months 

12 to 24 months 

> 24 months 

90 

17 

72 

35 

71 

95 

25 

59 

23 

37 

45 

25 

75 

9 

9 

8 

4 

55 

22 

Pesticide Use 

135 91.2 

10 6.8 

3 2.0 

67 45.3 

30 20.3 

14 9.4 

11 7.4 

7 4.7 

7 4.7 

4 2.7 

4 2.7 

83 56.1 

55 37.2 

72 48.6 

5 3.4 

5 3.4 

132 89.2 

10 6.8 

5 3.4 

20 13.5 

27 18.2 

42 28.4 

23 15.5 

16 10.8 

13 8.8 

75 50.7 

24 15.2 

17 11.5 

16 10.8 

84.1 

15.9 

67.3 

32.7 

66.4 

88.8 

23.3 

55.1 

21.4 

34.6 

42.1 

23.3 

70.1 

8.4 

8.4 

7.5 

3.7 

51.4 

40.0 

a Totals may not add up to 107 participants or 148 products, and percentages may not add up to 100 because of some non-responses 

to survey questions. 

Source: Bass et al. (2001). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 

17-34 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 17-37. Amount and Frequency of Use of Household Products 

Overall Per Subject Product Type Mean SD Min Max Subjects Events Min Max 

Dishwashing Liquid 

Frequency of use per day 0.63 0.79 0 5 45 596 0.05 2.29 

Duration of contact (minutes) 11 5 1 60 45 596 2 35 

Amount used per contact 5 3 1 16 13 163 2 10 (grams) 

All-Purpose Cleaner 

Frequency of use per day 0.35 0.70 0 4 28 218 0.050 1.82 

Duration of contact (minutes) 20 22 1 135 28 204 5 60 

Amount used per contact 27 30 1 123 12 105 2 74 (grams) 

Toilet Cleaner 

Frequency of use per day 0.28 0.55 0 2 18 105 0.05 1.67 

2a Duration of contact (minutes) 74 204 1 1,209 28 101 24a 

Amount used per contact - - - - - - 9 153 (grams) 

Hair Spray 

Frequency of use per day 0.76 0.68 0 3 9 143 0.29 1.76 

Amount used per contact - - - - - - 1.0 11.6 (grams) 

Duration of release (seconds) 11 6 5 25 12 - - ­

Duration of contact with 23 11 5 41 12 - - - nebula (seconds) 

Duration of contact with 

nebula × gram released 48 48 5 150 10 - - -

(seconds × grams) a Excludes durations over 30 minutes. 

- Indicates insufficient sample size to estimate average use. 

Source: Weegels and van Veen (2001). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Exposure Factors Handbook Page
 

September 2011 17-35 
 

Table 17-38. Frequency of Use of Cosmetic Products 

Number of Applications per Day Product Type N Mean Median SD 

Lipstick 311 2.35 2 1.80 

Body lotion, hands 308 2.12 2 1.59 

Body lotion, arms 308 1.52 1 1.30 

Body lotion, feet 308 0.95 1 1.01 

Body lotion, legs 308 1.11 1 0.98 

Body lotion, neck and throat 308 0.43 0 0.82 

Body lotion, back 308 0.26 0 0.63 

Body lotion, other 308 0.40 0 0.76 

Face cream 300 1.77 2 1.16 

N = Number of subjects (women, ages 19 to 65 years). 

SD = Standard deviation. 

Source: Loretz et al. (2005). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 

17-36 September 2011 
Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-39. Amount of Test Product Used (grams) for Lipstick, Body Lotion, and Face Cream 

Summary Statistics Total Amount Applied Averagea Amount Applied per 

Use Day 

Averageb Amount 

Applied per Application 

Lipstick 

Minimum 0.001 0.000 0.000 

Maximum 2.666 0.214 0.214 

Mean 0.272 0.024 0.010 

SD 0.408 0.034 0.018 

Percentiles 

10th 0.026 0.003 0.001 

20th 0.063 0.005 0.003 

30th 0.082 0.008 0.004 

40th 0.110 0.010 0.004 

50th 0.147 0.013 0.005 

60th 0.186 0.016 0.006 

70th 0.242 0.021 0.009 

80th 0.326 0.029 0.011 

90th 0.655 0.055 0.024 

95th 0.986 0.087 0.037 

99th 2.427 0.191 0.089 

Best Fit Distributions and 

Parametersc 

Lognormal Distribution 

GM = 0.14 

GSD = 3.56 

p-value (Gof) = 0.01 

Lognormal Distribution 

GM = 0.01 

GSD = 3.45 

p-value (Gof) <0.01 

Lognormal Distribution 

GM = 0.01 

GSD = 3.29 

p-value (Gof) <0.01 

Body Lotion 

Minimum 0.67 0.05 0.05 

Maximum 217.66 36.31 36.31 

Mean 103.21 8.69 4.42 

SD 53.40 5.09 4.19 

Percentiles 

10th 36.74 3.33 1.30 

20th 51.99 4.68 1.73 

30th 68.43 5.71 2.32 

40th 82.75 6.74 2.76 

50th 96.41 7.63 3.45 

60th 110.85 9.25 4.22 

70th 134.20 10.90 4.93 

80th 160.26 12.36 6.14 

Exposure Factors Handbook Page
 

September 2011 17-37 
 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-39. Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream (continued) 

Summary Statistics Total Amount Applied Averagea Amount Applied per 

Use Day 

Averageb Amount 

Applied per Application 

90th 182.67 14.39 8.05 

95th 190.13 16.83 10.22 

99th 208.50 27.91 21.71 

Best Fit Distributions and 

Parametersc 

Beta Distributionc 

Alpha = 1.53 

Beta = 1.77 

Scale = 222.01 

p-value (GoF) = 0.06 

Gamma Distribution 

Location = -0.86 

Scale = 2.53 

Shape = 3.77 

p-value (GoF) = 0.37 

Lognormal Distribution 

GM = 3.26 

GSD = 2.25 

p-value (GoF) = 0.63 

Face Cream 

Minimum 0.04 0.00 0.00 

Maximum 55.85 42.01 21.01 

Mean 22.36 2.05 1.22 

SD 14.01 2.90 1.76 

Percentiles 

10th 5.75 0.47 0.28 

20th 9.35 0.70 0.40 

30th 12.83 1.03 0.53 

40th 16.15 1.26 0.67 

50th 19.86 1.53 0.84 

60th 23.79 1.88 1.04 

70th 29.31 2.23 1.22 

80th 36.12 2.90 1.55 

90th 44.58 3.50 2.11 

95th 48.89 3.99 2.97 

99th 51.29 12.54 10.44 

Best Fit Distributions and 

Parametersc 

Triangle Distribution 

Minimum = -1.09 

Maximum = 58.71 

Likeliest = 7.53 

p-value (GoF) = 0.27 

Lognormal Distributionc 

GM = 1.39 

GSD = 2.58 

p-value (GoF) <0.01 

Lognormal Distributionc 

GM = 0.80 

GSD = 2.55 

p-value (GoF) = 0.02 

a Derived as the ratio of the total amount used to the number of use days. b Derived as the ratio of the total amount used to the total number of applications during the survey. c None of the tested distributions provided a good fit. 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

GoF = Goodness of fit. 

Note: Data are for women, ages 19 to 65 years. 

Source: Loretz et al. (2005). 

Page Exposure Factors Handbook 

17-38 September 2011 
Table 17-40. Frequency of Use of Personal Care Products 

Average Number of Applications per Use Daya 

Product Type N 

Mean SD Min Max 

Hairspray (aerosol) 165b 1.49 0.63 1.00 5.36 

Hairspray (pump) 162 1.51 0.64 1.00 4.22 

Liquid Foundation 326 1.24 0.32 1.00 2.00 

Spray Perfume 326 1.67 1.10 1.00 11.64 

Body Wash 340 1.37 0.58 1.00 6.36 

Shampoo 340 1.11 0.24 1.00 2.14 

Solid Antiperspirant 340 1.30 0.40 1.00 4.00 a Derived as the ratio of the number of applications to the number of use days. b Subjects who completed the study but did not report their number of applications were excluded. 

N = Number of subjects (women, ages 18 to 65 years). 

SD = Standard deviation. 

Source: Loretz et al. (2006). 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Exposure Factors Handbook Page
 

September 2011 17-39 
 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Page Exposure Factors Handbook 17-40 September 2011 

Table 17-41. Average Amount of Product Applied per Applicationa (grams) 

Summary Statistics Hairspray 

(aerosol) 

Hairspray 

(pump) Spray Perfume Liquid Foundation Shampoo Body Wash Solid Antiperspirant 

N 163b 161b 310b 321b 340 340 340 

Mean 2.58 3.64 0.33 0.54 11.76 11.3 0.61 

SD 2.26 3.50 0.41 0.52 8.77 6.9 0.56 

Minimum 0.05 0.00 0.00 0.00 0.39 1.1 0.00 

Maximum 14.08 21.44 5.08 2.65 67.89 58.2 5.55 

Percentiles 

10th 0.66 0.70 0.06 0.08 3.90 4.6 0.14 

20th 0.94 1.01 0.10 0.14 5.50 5.8 0.22 

30th 1.26 1.59 0.13 0.19 6.78 7.1 0.30 

40th 1.56 2.14 0.18 0.26 8.27 8.5 0.37 

50th 1.83 2.66 0.23 0.36 9.56 9.5 0.45 

60th 2.38 3.43 0.28 0.48 11.32 11.4 0.55 

70th 2.87 3.84 0.36 0.63 13.29 13.4 0.69 

80th 3.55 5.16 0.49 0.86 16.07 16.0 0.89 

90th 5.33 7.81 0.68 1.23 22.59 21.1 1.25 

95th 7.42 10.95 0.94 1.70 27.95 24.3 1.67 

97.5th 8.77 14.68 1.25 2.07 35.65 28.4 2.15 

99th c 11.30 15.52 1.73 2.36 51.12 35.1 2.52 

Best Fit Distributions 

and Parameters 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal 

Distribution Lognormal Gamma Lognormal Distribution 

GM = 1.84 GM = 2.44 GM = 0.21 GM = 0.33 GM = 9.32 Location = 0.51 GM = 0.43 

GSD = 2.40 GSD = 2.67 GSD = 3.01 GSD = 2.99 GSD = 2.02 Scale = 3.92 GSD = 2.37 

Shape = 2.76 

p-value 

(Kolmogorov-Smirnov) 0.06 0.07 0.077 0.041 0.1328 0.486 0.339 

a Derived as the ratio of the total amount used to the total number of applications. b Subjects who completed the study, but did not report their number of applications, or who did not return the unused portion of the product, were excluded. c Estimate does not meet the minimum sample size criteria (N = 800) as set by the National Center for Health Statistics. For upper percentile (>75), the 

minimum sample size (N) satisfies the following rule: n[8/(1-p)]. http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf. 

N = Number of subjects (women, ages 19 to 65 years). 

SD = Standard deviation. 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

Source: Loretz et al. (2006). 
 

Chapter 17—Exposure Factors Handbook 

Consumer Products 

Exposure Factors Handbook PageSeptember 2011 17-41

Table 17-42. Average Amount of Product Applied per Use Daya (grams) 

Summary Statistics Hairspray 

(aerosol) 

Hairspray 

(pump) Spray Perfume Liquid Foundation Shampoo Body Wash Solid Antiperspirant 

N 163b 161b 310b 321b 340 340 340 

Mean 3.57 5.18 0.53 0.67 12.80 14.5 0.79 

SD 3.09 4.83 0.57 0.65 9.11 8.5 0.78 

Minimum 0.05 0.00 0.00 0.00 0.55 1.3 0.00 

Maximum 18.25 24.12 5.08 3.00 67.89 63.4 5.55 

Percentiles 

10th 0.84 0.91 0.08 0.10 4.12 5.7 0.17 

20th 1.35 1.48 0.12 0.16 5.80 7.6 0.29 

30th 1.65 2.33 0.19 0.23 7.32 9.3 0.38 

40th 2.23 2.66 0.26 0.30 9.09 10.9 0.46 

50th 2.71 3.74 0.34 0.45 10.75 12.9 0.59 

60th 3.30 4.71 0.45 0.58 12.82 14.8 0.70 

70th 3.89 5.67 0.61 0.76 14.73 17.4 0.86 

80th 4.86 7.38 0.81 1.04 17.61 20.7 1.08 

90th 7.73 12.22 1.45 1.76 23.63 25.5 1.70 

95th 9.89 15.62 1.77 2.18 29.08 29.1 2.32 

97.5th 13.34 19.41 1.86 2.40 36.46 35.6 3.33 

99th c 15.05 23.98 2.01 2.70 51.12 43.5 4.42 

Best fit distributions 

and parameters 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal Gamma Lognormal 

Distribution 

GM = 2.57 GM = 3.45 GM = 0.30 GM = 0.40 Location = 0.38 Location = 0.67 GM = 0.56 

GSD = 2.37 GSD = 2.70 GSD = 3.36 GSD = 3.10 Scale = 5.79 Scale = 4.89 GSD = 2.41 

Shape = 2.15 Shape = 2.84 

p-value 

(Kolmogorov-Smirnov) 0.05 0.05 0.075 0.047 0.8208 0.760 0.293 

a Derived as the ratio of the total amount used to the total number of applications. b Subjects who completed the study, but did not report their number of applications, or who did not return the unused portion of the product, were 

excluded. c Estimate does not meet the minimum sample size criteria (N = 800) as set by the National Center for Health Statistics. For upper percentile (>75), the 

minimum sample size (N) satisfies the following rule: n[8/(1-p)]. http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf. 

N = Number of subjects (women, ages 19 to 65 years). 

SD = Standard deviation. 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

Source: Loretz et al. (2006). 
 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-43. Body Lotion Exposure for Consumers Only (males and 

females) 

Distribution 

Parameter 

Amount 

(g/day) Parameter SD Amount (mg/kg-day) Parameter SD 

Mean 4.543 0.012 67.869 0.228 

Standard Deviation 2.707 0.013 43.866 0.307 

Median 4.556 0.023 64.265 0.369 

Minimum 0.005 0.000 0.043 0.003 

Maximum 21.081 1.264 401.371 46.215 

Percentile 

p01 0.005 0.000 0.079 0.003 

p02.5 0.017 0.000 0.250 0.011 

p05 0.556 0.008 8.066 0.191 

p10 1.129 0.006 15.055 0.293 

p20 1.948 0.018 27.535 0.330 

p30 2.907 0.024 40.763 0.359 

p40 3.737 0.027 53.072 0.357 

p50 4.556 0.023 64.265 0.369 

p60 5.246 0.023 75.114 0.374 

p70 5.898 0.021 86.751 0.404 

p80 6.645 0.024 101.024 0.495 

p90 7.822 0.033 123.227 0.715 

p92 8.183 0.038 130.177 0.868 

p94 8.651 0.042 139.085 0.968 

p95 8.951 0.047 144.797 1.072 

p96 9.326 0.054 151.892 1.211 

p97.5 10.191 0.081 167.036 1.559 

p98 10.655 0.096 174.414 1.768 

p99 12.261 0.155 198.018 2.888 

p99.5 13.893 0.221 222.667 4.420 

p99.9 16.991 0.413 282.959 10.304 

Source: Hall et al. (2007). 

Page Exposure Factors Handbook 

17-42 September 2011 
 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-44. Deodorant/Antiperspirant Spray Exposure for 

Consumers Only (males and females)―Under Arms Only 

Value Amount 

(g/day) Parameter SD Amount (mg/kg-day) Parameter SD 

Mean 3.478 0.007 49.07 0.13 

Standard Deviation 2.051 0.009 31.00 0.22 

Median 3.153 0.012 43.52 0.19 

Minimum 0.045 0.005 0.59 0.10 

Maximum 23.663 1.724 379.03 63.23 

Percentile 

p01 0.228 0.012 3.08 0.13 

p02.5 0.373 0.008 5.08 0.12 

p05 0.598 0.011 8.23 0.16 

p10 1.135 0.014 15.31 0.20 

p20 1.951 0.012 25.75 0.17 

p30 2.425 0.010 32.38 0.17 

p40 2.796 0.011 37.96 0.17 

p50 3.153 0.012 43.52 0.19 

p60 3.548 0.013 49.73 0.22 

p70 4.049 0.015 57.50 0.27 

p80 4.804 0.019 68.59 0.32 

p90 6.095 0.029 87.79 0.49 

p92 6.477 0.031 93.94 0.58 

p94 6.955 0.037 101.93 0.71 

p95 7.262 0.040 107.01 0.81 

p96 7.645 0.047 113.29 0.91 

p97.5 8.537 0.064 126.91 1.24 

p98 9.005 0.076 133.46 1.40 

p99 10.451 0.107 154.31 1.98 

p99.5 11.628 0.132 175.01 2.80 

p99.9 13.843 0.277 222.53 7.29 

Source: Hall et al. (2007). 

Exposure Factors Handbook Page
 

September 2011 17-43 
 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-45. Deodorant/Antiperspirant Spray Exposure for 

Consumers Only (male sand females) Using Product 

Over Torso and Under Arms 

Value Amount 

(g/day) Parameter SD Amount (mg/kg-day) Parameter SD 

Mean 3.732 0.008 52.47 0.14 

Standard 

Deviation 2.213 0.010 32.94 0.23 

Median 3.383 0.012 46.66 0.20 

Minimum 0.044 0.005 0.59 0.10 

Maximum 24.662 2.057 389.12 66.91 

Percentile 

p01 0.239 0.014 3.19 0.14 

p02.5 0.384 0.009 5.30 0.15 

p05 0.639 0.015 8.80 0.18 

p10 1.214 0.015 16.47 0.23 

p20 2.078 0.013 27.71 0.18 

p30 2.580 0.012 34.76 0.17 

p40 2.986 0.011 40.73 0.18 

p50 3.383 0.012 46.66 0.20 

p60 3.819 0.014 53.26 0.21 

p70 4.364 0.016 61.50 0.27 

p80 5.156 0.021 73.25 0.35 

p90 6.543 0.030 93.70 0.53 

p92 6.969 0.036 100.24 0.60 

p94 7.505 0.042 108.70 0.73 

p95 7.839 0.048 114.08 0.81 

p96 8.263 0.053 120.73 0.92 

p97.5 9.213 0.069 135.17 1.24 

p98 9.711 0.080 142.13 1.42 

p99 11.263 0.117 164.14 2.31 

p99.5 12.544 0.157 186.13 3.14 

p99.9 14.898 0.300 235.47 7.01 

Source: Hall et al. (2007). 

Page Exposure Factors Handbook 

17-44 September 2011 
 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-46. Deodorant/Antiperspirant Non-Spray for Consumers 

Only (males and females) 

Value Amount 

(g/day) Parameter SD Amount 

(mg/kg-day) Parameter SD 

Mean 0.898 0.002 12.95 0.04 

Standard Deviation 0.494 0.002 7.34 0.05 

Median 0.820 0.003 11.77 0.05 

Minimum 0.000 0.000 0.00 0.00 

Maximum 4.528 0.300 73.91 7.48 

Percentile 

p01 0.064 0.002 0.90 0.04 

p02.5 0.123 0.004 1.75 0.05 

p05 0.221 0.004 3.12 0.06 

p10 0.363 0.003 5.08 0.05 

p20 0.509 0.003 7.26 0.05 

p30 0.617 0.003 8.85 0.05 

p40 0.718 0.003 10.30 0.05 

p50 0.820 0.003 11.77 0.05 

p60 0.934 0.004 13.36 0.05 

p70 1.068 0.004 15.25 0.07 

p80 1.238 0.005 17.77 0.08 

p90 1.509 0.007 22.08 0.12 

p92 1.598 0.008 23.51 0.14 

p94 1.722 0.010 25.37 0.17 

p95 1.806 0.011 26.57 0.19 

p96 1.912 0.013 28.05 0.21 

p97.5 2.134 0.016 31.18 0.28 

p98 2.233 0.017 32.67 0.32 

p99 2.515 0.025 37.25 0.48 

p99.5 2.771 0.033 41.93 0.72 

p99.9 3.426 0.088 52.79 1.63 

Source: Hall et al. (2007). 

Exposure Factors Handbook Page
 

September 2011 17-45 
Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-47. Lipstick Exposure for Consumers Only (females) 

Value Amount 

(mg/day) Parameter SD Amount (mg/kg-day) Parameter SD 

Mean 24.61 0.17 0.39 0.00 

Standard Deviation 24.05 0.25 0.40 0.01 

Median 17.11 0.18 0.26 0.00 

Minimum 0.13 0.04 0.00 0.00 

Maximum 217.53 26.01 3.88 0.55 

Percentile 

p01 0.57 0.04 0.01 0.00 

p02.5 1.00 0.07 0.02 0.00 

p05 1.68 0.07 0.03 0.00 

p10 2.95 0.07 0.04 0.00 

p20 5.69 0.11 0.09 0.00 

p30 9.20 0.14 0.14 0.00 

p40 12.93 0.15 0.20 0.00 

p50 17.11 0.18 0.26 0.00 

p60 22.37 0.24 0.34 0.00 

p70 29.43 0.33 0.46 0.01 

p80 39.70 0.47 0.62 0.01 

p90 56.53 0.66 0.90 0.01 

p92 61.66 0.72 0.98 0.01 

p94 68.29 0.86 1.10 0.02 

p95 72.51 0.95 1.17 0.02 

p96 77.78 1.08 1.26 0.02 

p97.5 89.08 1.34 1.46 0.03 

p98 94.46 1.52 1.55 0.03 

p99 110.98 2.06 1.84 0.04 

p99.5 126.71 2.93 2.13 0.06 

p99.9 160.06 6.33 2.78 0.14 

Source: Hall et al. (2007). 

Page Exposure Factors Handbook 

17-46 September 2011 
Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-48. Facial Moisturizer Exposure for Consumers Only 

(males and females) 

Value Amount 

(g/day) 

Parameter 

SD 

Amount 

(mg/kg-day) Parameter SD 

Mean 0.906 0.003 13.62 0.05 

Standard Deviation 0.533 0.004 8.63 0.08 

Median 0.851 0.004 12.42 0.06 

Minimum 0.001 0.000 0.02 0.00 

Maximum 4.751 0.380 92.75 11.80 

Percentile 

p01 0.055 0.002 0.73 0.04 

p02.5 0.079 0.004 1.13 0.03 

p05 0.138 0.001 1.89 0.04 

p10 0.261 0.004 3.67 0.06 

p20 0.472 0.004 6.63 0.05 

p30 0.603 0.003 8.66 0.05 

p40 0.721 0.003 10.51 0.06 

p50 0.851 0.004 12.42 0.06 

p60 0.990 0.004 14.47 0.07 

p70 1.131 0.004 16.78 0.07 

p80 1.289 0.005 19.65 0.10 

p90 1.536 0.007 24.14 0.14 

p92 1.617 0.008 25.57 0.17 

p94 1.727 0.010 27.46 0.19 

p95 1.801 0.012 28.68 0.22 

p96 1.897 0.014 30.23 0.25 

p97.5 2.129 0.022 33.73 0.35 

p98 2.251 0.027 35.52 0.43 

p99 2.653 0.043 41.63 0.71 

p99.5 3.040 0.057 48.23 1.08 

p99.9 3.714 0.108 63.35 2.62 

Source: Hall et al. (2007). 

Exposure Factors Handbook Page
 

September 2011 17-47 
 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-49. Shampoo Exposure for Consumers Only 

(males and females) 

Value Amount 

(g/day) Parameter SD Amount (mg/kg-day) Parameter SD 

Mean 6.034 0.014 85.888 0.223 

Standard Deviation 3.296 0.015 48.992 0.278 

Median 5.503 0.020 77.895 0.294 

Minimum 0.344 0.036 3.826 0.461 

Maximum 29.607 0.669 528.361 65.887 

Percentile 

p01 1.071 0.000 12.781 0.148 

p02.5 1.268 0.023 16.367 0.181 

p05 1.482 0.024 21.059 0.182 

p10 2.178 0.019 29.737 0.269 

p20 3.236 0.016 44.415 0.242 

p30 3.843 0.019 55.58 0.253 

p40 4.777 0.023 66.502 0.27 

p50 5.503 0.020 77.895 0.294 

p60 6.416 0.022 90.255 0.332 

p70 7.390 0.026 104.537 0.373 

p80 8.597 0.028 122.6 0.461 

p90 10.456 0.039 150.488 0.642 

p92 11.013 0.054 159.046 0.73 

p94 11.721 0.041 169.939 0.846 

p95 12.181 0.063 176.768 0.922 

p96 12.705 0.064 185.092 1.08 

p97.5 13.765 0.073 202.349 1.396 

p98 14.194 0.091 210.49 1.551 

p99 15.637 0.110 235.613 2.142 

p99.5 16.992 0.149 260.624 3.009 

p99.9 20.397 0.443 320.47 6.689 

Source: Hall et al. (2007). 

Page Exposure Factors Handbook 

17-48 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-50. Toothpaste Exposure for Consumers Only 

(males and females) 

Value Amount 

(g/day) 

Parameter 

SD 

Amount 

(mg/kgday) 

Parameter 

SD 

Mean 2.092 0.001 29.85 0.04 

Standard Deviation 0.577 0.001 10.34 0.05 

Median 2.101 0.003 28.67 0.06 

Minimum 0.069 0.012 0.93 0.18 

Maximum 4.969 0.159 98.77 8.19 

Percentile 

p01 0.777 0.011 10.14 0.14 

p02.5 1.049 0.006 13.34 0.08 

p05 1.204 0.004 15.47 0.06 

p10 1.370 0.003 17.96 0.06 

p20 1.591 0.003 21.29 0.05 

p30 1.790 0.003 23.94 0.05 

p40 1.958 0.003 26.32 0.06 

p50 2.101 0.003 28.67 0.06 

p60 2.237 0.003 31.15 0.06 

p70 2.383 0.003 34.00 0.07 

p80 2.551 0.003 37.62 0.08 

p90 2.749 0.003 43.29 0.12 

p92 2.809 0.004 45.03 0.14 

p94 2.895 0.005 47.23 0.16 

p95 2.960 0.006 48.61 0.17 

p96 3.052 0.008 50.27 0.20 

p97.5 3.323 0.010 53.70 0.25 

p98 3.447 0.015 55.28 0.26 

p99 3.760 0.006 60.12 0.39 

p99.5 3.956 0.026 64.77 0.52 

p99.9 4.303 0.049 74.84 1.10 

Source: Hall et al. (2007). 

Exposure Factors Handbook Page
 

September 2011 17-49 
 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-51. Average Number of Applications per Use Daya 

Summary Statistics 

Facial Cleanser 

(lathering and nonlathering) 

Hair 

Conditioner Eye Shadow 

N 295 297 299 

Mean 1.6 1.1 1.2 

SD 0.52 0.19 0.33 

Minimum 1.0 1.0 1.0 

Maximum 3.2 2.4 2.7 

Percentiles 

10th 1.0 1.0 1.0 

20th 1.0 1.0 1.0 

30th 1.2 1.0 1.0 

40th 1.4 1.0 1.1 

50th 1.7 1.0 1.1 

60th 1.9 1.0 1.1 

70th 2.0 1.0 1.2 

80th 2.0 1.1 1.4 

90th 2.2 1.2 1.7 

95th 2.4 1.4 2.0 

97.5th 2.9b 1.8b 2.2b 

99th b 3.1b 2.1b 2.5b 

a Derived as the ratio of the number of applications to the number of use 

days. b Estimate does not meet the minimum sample size criteria (n = 800) as set 

by the National Center for Health Statistics. For upper percentile (>0.75), 

the minimum sample size (n) satisfies the following rule: n [8/(1-p.] 

See http://www/cdc/gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf. 

N = Number of subjects (women, ages 18 to 69 years). 

SD = Standard deviation. 

Source: Loretz et al. (2008). 

Page Exposure Factors Handbook 

17-50 September 2011 
 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-52. Average Amount of Product Applied per Use Day (grams)a 

Summary Statistics 

Facial Cleanser 

(lathering and 

non-lathering) 

Facial Cleanser 

(lathering) 

Facial Cleanser 

(non-lathering) Hair Conditioner Eye Shadow 

N 295 174 121 297 299 

Mean 4.06 4.07 4.05 13.77 0.04 

SD 2.78 2.87 2.67 11.50 0.11 

Minimum 0.33 0.33 0.83 0.84 0.001 

Maximum 16.70 15.32 16.70 87.86 0.74 

Percentiles 

10th 1.41 1.23 1.50 3.71 0.003 

20th 1.79 1.72 1.94 5.54 0.005 

30th 2.18 2.15 2.22 6.95 0.007 

40th 2.66 2.64 2.80 8.73 0.009 

50th 3.25 3.19 3.33 10.62 0.010 

60th 3.86 3.84 3.88 12.61 0.013 

70th 4.62 4.71 4.59 15.54 0.017 

80th 6.24 6.33 5.92 20.63 0.025 

90th 8.28 8.24 8.40 28.20 0.052 

95th 9.93 10.50 9.37b 33.19 0.096 

97.5th 10.71b 11.47b 10.26b 45.68b 0.525b 

99th b 12.44b 13.07b 15.29b 60.20b 0.673b 

Best Fit Distributions 

and Parameters 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal 

Distribution 

Lognormal 

Distribution 

GM = 3.26 GM = 3.21 GM = 3.35 GM = 10.28 GM = 0.01 

GSD = 1.12 GSD = 2.03 GSD = 1.86 GSD = 2.20 GSD = 3.61 

p-value 

(chi-square test) 0.1251 0.4429 0.4064 0.8595 <0.0001 a Derived as the ratio of the total amount used to the number of use days. b Estimate does not meet the minimum sample size criteria (n = 800) as set by the National Center for Health Statistics. 

For upper percentile (>0.75), the minimum sample size (n) satisfies the following rule: n [8/(1-p)]. See 

http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf. 

N = Number of subjects (women, ages 18 to 69 years). 

SD = Standard deviation. 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

Source: Loretz et al. (2008). 

Exposure Factors Handbook Page
 

September 2011 17-51 
 

 

Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-53. Average Amount of Product Applied per Application (grams)a 

Summary Statistics 

Facial Cleanser 

(lathering and 

non-lathering) 

Facial Cleanser 

(lathering) 

Facial Cleanser 

(non-lathering) Hair Conditioner Eye Shadow 

N 295 174 121 297 299 

Mean 2.57 2.56 2.58 13.13 0.03 

SD 1.78 1.78 1.77 11.22 0.10 

Minimum 0.33 0.33 0.57 0.84 0.0004 

Maximum 14.61 10.67 14.61 87.86 0.69 

Percentiles 

10th 0.92 0.83 1.10 3.48 0.003 

20th 1.32 1.26 1.35 5.34 0.004 

30th 1.57 1.55 1.59 6.71 0.006 

40th 1.85 1.84 1.89 8.26 0.007 

50th 2.11 2.11 2.15 10.21 0.009 

60th 2.50 2.50 2.51 12.24 0.011 

70th 2.94 2.96 2.96 14.54 0.015 

80th 3.47 3.56 3.40 18.88 0.022 

90th 4.81 5.10 4.52 27.32 0.041 

95th 5.89 6.37 5.11b 32.43 0.096 

97.5th 7.16b 7.77b 6.29b 45.68b 0.488b 

99thb 9.44b 9.61b 15.46b 60.20b 0.562b 

Best Fit 

Distributions and 

Parameters 

Extreme Value Gamma Extreme Value Lognormal 

Distribution 

Lognormal 

Distribution 

Mode = 1.86 Loc = 0.28 Mode = 1.92 GM = 9.78 GM = 0.01 

Scale = 1.12 Scale = 1.29 Scale = 1.03 GSD = 2.20 GSD = 3.59 

p-value (chi-square 

test) 0.0464 0.6123 0.5219 0.9501 <0.0001 a Derived as the ratio of the total amount used to the total number of applications. b Estimate does not meet the minimum sample size criteria (n = 800) as set by the National Center for Health 

Statistics. For upper percentile (>0.75), the minimum sample size (n) satisfies the following rule: n [8/(1-p)]. 

http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf. 

N = Number of subjects (women, ages 18 to 69 years). 

SD = Standard deviation. 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

Source: Loretz et al. (2008). 

Page Exposure Factors Handbook 

17-52 September 2011 
Exposure Factors Handbook 

Chapter 17—Consumer Products 

Table 17-54. Characteristics of the Study Population and the Percentage Using 

Selected Baby Care Products 

Characteristic Sample Number (%) 

Number of Participants 

Los Angeles, CA 43 (26) 

Minneapolis, MN 77 (47) 

Columbia, MO 43 (26) 

Sex 

Male 84 (52) 

Female 79 (48) 

Age (months) 

2 to 8 42 (26) 

9 to 16 82 (50) 

17 to 24 30 (18) 

24 to 28 9 (6) 

Infant Weight (kg) 

≤10 84 (52) 

>10 79 (48) 

Race 

White 131 (80) 

Hispanic/Latino 17 (10) 

Native American 3 (2) 

Asian 8 (5) 

Black 4 (3) 

Product Use % Using 

Baby Lotion 36 

Baby Shampoo 54 

Baby Powder 14 

Diaper Cream 33 

Baby Wipes 94 

Source: Sathyanarayana et al. (2008) 

Exposure Factors Handbook Page
 

September 2011 17-53 
Exposure Factors Handbook 

Chapter 18—Lifetime 

 

 

 

 

 

 

 

 

 

 

 

 

18. LIFETIME 

18.1. INTRODUCTION 

The length of an individual’s life is an important 

factor to consider when evaluating cancer risk 

because the dose estimate is averaged over an 

individual’s lifetime. The recommendations for life 

expectancy are provided in the next section, along 

with a summary of the confidence rating for this 

recommendation. Because the averaging time is 

found in the denominator of the dose equation, a 

shorter lifetime would result in a higher potential risk 

estimate, and, conversely, a longer life expectancy 

would produce a lower potential risk estimate. 

The recommended values are based on one key 

study identified by the U.S. Environmental Protection 

Agency (EPA) for this factor. Following the 

recommendations, the key study is summarized. 

18.2. RECOMMENDATIONS 

Current data suggest that 78 years would be an 

appropriate value to reflect the average life 

expectancy of the general population and is the 

recommended value. If sex is a factor considered in 

the assessment, note that the average life expectancy 

value for females is higher than that for males. It is 

recommended that the assessor use the appropriate 

value of 75 years for males and 80 years for females, 

based on life expectancy data from 2007 (Xu et al., 

2010). If race is a consideration in assessing exposure 

for individuals, note that the life expectancy is longer 

for Whites than for Blacks. Therefore, assessors are 

encouraged to use values that most reflect the 

exposed population. Table 18-1 and Table 18-2 

present the recommendations and confidence ratings 

for life expectancy, respectively. 

This recommended value is different than the 

70 years commonly assumed for the general 

population in U.S. EPA risk assessments. The 

Integrated Risk Information System does not use a 

70-year lifetime assumption in the derivation of 

reference concentration and reference dose, cancer 

slope factors, or unit risks. Therefore, using a value 

different than 70 years will not result in an 

inconsistency with the toxicity data. 

Table 18-1. Recommended Values for Expectation of Life at Birth: 2007 

Population Life Expectancy 

(years) 

Source 

Total 78 

Males 75 

Females 80 

Xu et al. (2010) 

Exposure Factors Handbook Page
 

September 2011 18-1
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 18—Lifetime 

Table 18-2. Confidence in Lifetime Expectancy Recommendations 

Considerations Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

Recommendations are based on data from death certificates 

filed in the 50 states in the United States and District of 

Columbia. 

There are no apparent biases. 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

Death certificate data were used to calculate life expectancy 

for various population groups born between 1940 and 2007. 

The data are representative of the U.S. population. 

The study was published in 2010 based on data collected in 

2007. 

Data were collected in 2007. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The key study is widely available to the public. 

Results can be reproduced by analyzing death certificate 

data. 

Information on ensuring data quality are available publicly. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Data were averaged by sex and race—but only for Blacks 

and Whites; no other nationalities were represented within 

the study. 

Data were based on death certificates filed in the 50 states in 

the United States and District of Columbia. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

Data are published and have been peer reviewed. 

Recommendations for expectation of life at birth were based 

on only one study. 

High 

Overall Rating High 

Page Exposure Factors Handbook 

18-2 September 2011 
Exposure Factors Handbook 

Chapter 18—Lifetime 

18.3. KEY LIFETIME STUDY 

18.3.1.	 Xu et al. (2010)—Deaths: Final Data for 

2007 

Xu et al. (2010) used information compiled from 

death certificates filed in the 50 states of the United 

States and District of Columbia and calculated life 

expectancy for various population groups born 

between 1940 and 2007. “Life expectancy at birth 

represents the average number of years that a group 

of infants would live if the group was to experience 

throughout life the age-specific death rates present in 

the year of birth” (Xu et al., 2010). 

Table 18-3 shows life expectancy data by sex, 

age, and race (i.e., Whites and Blacks). Although data 

for other ethnic groups were collected, they were not 

considered as reliable because of inconsistencies 

between the race reported in the death certificates and 

in the censuses and surveys. Data for 2007 show that 

the life expectancy for an average person born in the 

United States is 77.9 years (Xu et al., 2010). The 

average life expectancy for males in 2007 was 

75.4 years and 80.4 years for females. Whereas the 

gap between males and females was about 7 years in 

1970, it has now narrowed to about 5 years. 

Table 18-3 also indicates that life expectancy for 

White males and females is consistently longer than 

for Black males and females. Table 18-4 presents data 

for the expectation of life for persons at a specific age 

in year 2007 (Xu et al., 2010). The advantages of this 

study are that it is representative of the United States 

and provides life expectancy data based on death 

certificates and calculations of death rates. A 

disadvantage is that the data were averaged by sex 

and race—but only for Blacks and Whites. 

18.4. RELEVANT LIFETIME STUDY 

18.4.1.	 U.S. Census Bureau (2008)—U.S. 

Population Projections: Projected Life 

Expectancy at Birth by Sex, Race, and 

Hispanic Origin for the United States: 

2010 to 2050 

Statistical data on life expectancy are published 

annually by the U.S. Department of Commerce in the 

publication, Statistical Abstract of the United States. 

Data are collected for the 50 states and the District of 

Columbia. The Statistical Abstract of the United 

States has been published by the U.S. Census Bureau 

since 1878 (U.S. Census Bureau, 2010). The U.S. 

Census Bureau (2008) computed life expectancy 

projections for 2010 through 2050, by decade. This 

analysis uses historical mortality trend data collected 

by the National Center for Health Statistics and 

applies forecast models to estimate projected life 

expectancy at birth. These data are provided, by sex 

and race in Table 18-5. 

The advantage of this survey is that it is 

representative of the United States, and it provides 

projections by sex and race. A disadvantage is that 

life expectancy estimates are based on future 

projections. 

18.5. REFERENCES FOR CHAPTER 18 

U.S. Census Bureau. (2008). U.S. population 

projections: Table 10. Projected life 

expectancy at birth by sex, race, and 

Hispanic origin for the United States: 2010 

to 2050. (NP2008-T10). Washington, DC. 

http://www.census.gov/population/www/pro 

jections/summarytables.html. 

U.S. Census Bureau. (2010). The 2010 statistical 

abstract. 

http://www.census.gov/compendia/statab/20 

10. 

Xu, JQ; Kochanek, KD; Murphy, SL; Tejada-Vera, B. 

(2010). Deaths: Final Data for 2007. 

Hyattsville, MD: National Center for Health 

Statistics. 

http://www.cdc.gov/nchs/data/nvsr/nvsr58/n 

vsr58_19.pdf. 

Exposure Factors Handbook Page
 

September 2011 18-3
 
 

Table 18-3. Expectation of Life at Birth, 1970 to 2007 (years)a 

b Year Total White Black 

Total Males Females Total Males Females Total Males Females 

1970 

1975 

1980 

1982 

1983 

1984 

1985 

1986 

1987 

1988 

1989 

1990 

1991 

1992 

1993 

1994 

1995 

1996 

1997 

1998 

1999 

2000 

2001 

2002 

2003 

2004 

2005 

2006 

2007 

70.8 

72.6 

73.7 

74.5 

74.6 

74.7 

74.7 

74.7 

74.9 

74.9 

75.1 

75.4 

75.5 

75.8 

75.5 

75.7 

75.8 

76.1 

76.5 

76.7 

76.7 

76.8 

76.9 

76.9 

77.1 

77.5 

77.4 

77.7 

77.9 

67.1 

68.8 

70.0 

70.8 

71.0 

71.1 

71.1 

71.2 

71.4 

71.4 

71.7 

71.8 

72.0 

72.3 

72.2 

72.4 

72.5 

73.1 

73.6 

73.8 

73.9 

74.1 

74.2 

74.3 

74.5 

74.9 

74.9 

75.1 

75.4 

74.7 

76.6 

77.4 

78.1 

78.1 

78.2 

78.2 

78.2 

78.3 

78.3 

78.5 

78.8 

78.9 

79.1 

78.8 

79.0 

78.9 

79.1 

79.4 

79.5 

79.4 

79.3 

79.4 

79.5 

79.6 

79.9 

79.9 

80.2 

80.4 

71.7 

73.4 

74.4 

75.1 

75.2 

75.3 

75.3 

75.4 

75.6 

75.6 

75.9 

76.1 

76.3 

76.5 

76.3 

76.5 

76.5 

76.8 

77.2 

77.3 

77.3 

77.3 

77.4 

77.4 

77.6 

77.9 

77.9 

78.2 

78.4 

68.0 

69.5 

70.7 

71.5 

71.6 

71.8 

71.8 

71.9 

72.1 

72.2 

72.5 

72.7 

72.9 

73.2 

73.1 

73.3 

73.4 

73.9 

74.3 

74.5 

74.6 

74.7 

74.8 

74.9 

75.0 

75.4 

75.4 

75.7 

75.9 

75.6 

77.3 

78.1 

78.7 

78.7 

78.7 

78.7 

78.8 

78.9 

78.9 

79.2 

79.4 

79.6 

79.8 

79.5 

79.6 

79.6 

79.7 

79.9 

80.0 

79.9 

79.9 

79.9 

79.9 

80.0 

80.4 

80.4 

80.6 

80.8 

64.1 

66.8 

68.1 

69.4 

69.4 

69.5 

69.3 

69.1 

69.1 

68.9 

68.8 

69.1 

69.3 

69.6 

69.2 

69.5 

69.6 

70.2 

71.1 

71.3 

71.4 

71.8 

72.0 

72.1 

72.3 

72.8 

72.8 

73.2 

73.6 

60.0 

62.4 

63.8 

65.1 

65.2 

65.3 

65.0 

64.8 

64.7 

64.4 

64.3 

64.5 

64.6 

65.0 

64.6 

64.9 

65.2 

66.1 

67.2 

67.6 

67.8 

68.2 

68.4 

68.6 

68.8 

69.3 

69.3 

69.7 

70.0 

68.3 

71.3 

72.5 

73.6 

73.5 

73.6 

73.4 

73.4 

73.4 

73.2 

73.3 

73.6 

73.8 

73.9 

73.7 

73.9 

73.9 

74.2 

74.7 

74.8 

74.7 

75.1 

75.2 

75.4 

75.6 

76.0 

76.1 

76.5 

76.8 a Based on middle mortality assumptions; for details, source: U.S. Census Bureau (2008). b Life expectancies for 2000–2007 were calculated using a revised methodology and may differ from 

those previously published; see Xu et al. (2010). 

Source: Xu et al. (2010). 

Exposure Factors Handbook 

Chapter 18—Lifetime 

Page Exposure Factors Handbook 

18-4 September 2011 
Exposure Factors Handbook 

Chapter 18—Lifetime 

Table 18-4. Expectation of Life by Race, Sex, and Age: 2007 

Exact Age in 

Years 

Both 

Sexes 

All Racesa 

Males Females 

Both 

Sexes 

White 

Males Females 

Both 

Sexes 

Black 

Males Females 

0 77.9 75.4 80.4 78.4 75.9 80.8 73.6 70.0 76.8 

1 77.5 74.9 79.9 77.8 75.4 80.2 73.6 70.1 76.8 

5 73.6 71.0 76.0 73.9 71.4 76.3 69.7 66.2 72.9 

10 68.6 66.1 71.0 68.9 66.5 71.3 64.7 61.3 67.9 

15 63.7 61.1 66.1 64.0 61.6 66.3 59.8 56.3 63.0 

20 58.8 56.4 61.2 59.2 56.8 61.5 55.1 51.7 58.1 

25 54.1 51.8 56.3 54.4 52.2 56.6 50.4 47.2 53.3 

30 49.4 47.1 51.5 49.7 47.5 51.7 45.8 42.7 48.5 

35 44.6 42.5 46.7 44.9 42.8 46.9 41.2 38.2 43.8 

40 39.9 37.8 41.9 40.2 38.1 42.1 36.7 33.8 39.1 

45 35.4 33.3 37.2 35.6 33.6 37.4 32.3 29.5 34.7 

50 30.9 29.0 32.7 31.1 29.2 32.8 28.1 25.4 30.4 

55 26.7 24.9 28.2 26.8 25.1 28.4 24.2 21.7 26.3 

60 22.5 20.9 23.9 22.6 21.0 24.0 20.6 18.3 22.4 

65 18.6 17.2 19.9 18.7 17.3 19.9 17.2 15.2 18.7 

70 15.0 13.7 16.0 15.0 13.8 16.0 14.1 12.4 15.2 

75 11.7 10.6 12.5 11.7 10.6 12.4 11.2 9.9 12.1 

80 8.8 7.9 9.4 8.8 7.9 9.3 8.7 7.7 9.4 

85 6.5 5.8 6.8 6.4 5.7 6.8 6.7 6.0 7.1 

90 4.6 4.1 4.8 4.6 4.1 4.8 5.1 4.6 5.3 

95 3.2 2.9 3.3 3.2 2.9 3.3 3.8 3.5 3.9 

100 2.3 2.1 2.3 2.2 2.0 2.2 2.8 2.6 2.8 a Includes races other than White and Black. 

Source: Xu et al. (2010). 

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September 2011 18-5
 
 

Exposure Factors Handbook 

Chapter 18—Lifetime 

Table 18-5. Projected Life Expectancy at Birth by Sex, Race, and Hispanic Origin for 

the United States: 2010 to 2050 

Sex, Race, and Hispanic Origin 2010 2020 2030 2040 2050 

Males and Females Combined 

Total Population 78.3 79.5 80.7 81.9 83.1 

White 78.9 80.0 81.1 82.2 83.3 

Black 73.8 76.1 78.1 80.0 81.8 

American Indian and Alaskan 

Native 79.1 80.2 81.3 82.3 83.4 

Asian 78.8 80.0 81.1 82.2 83.3 

Native Hawaii or Pacific Islander 79.2 80.2 81.2 82.4 83.4 

Two or more races 79.4 80.5 81.5 82.4 83.4 

Non-Hispanic White alone 78.7 79.8 80.9 82.0 83.1 

Hispanica 81.1 81.8 82.6 83.3 84.1 

Males 

Total Population 75.7 77.1 78.4 79.6 80.9 

White 76.5 77.7 78.9 80.0 81.2 

Black 70.2 72.6 74.9 77.1 79.1 

American Indian and Alaskan 

Native 76.6 77.8 79.0 80.1 81.2 

Asian 76.3 77.5 78.7 79.8 81.0 

Native Hawaii or Pacific Islander 76.8 77.8 79.0 80.1 81.2 

Two or more races 77.0 78.1 79.1 80.2 81.2 

Non-Hispanic White alone 76.3 77.5 78.7 79.8 81.0 

Hispanica 78.4 79.3 80.2 81.0 81.8 

Females 

Total Population 80.8 81.9 83.1 84.2 85.3 

White 81.3 82.4 83.4 84.5 85.5 

Black 77.2 79.2 81.0 82.7 84.3 

American Indian and Alaskan 

Native 81.5 82.5 83.6 84.5 85.5 

Asian 81.1 82.2 83.2 84.2 85.3 

Native Hawaii or Pacific Islander 81.6 82.6 83.5 84.5 85.5 

Two or more races 81.7 82.7 83.6 84.6 85.5 

Non-Hispanic White alone 81.1 82.1 83.2 84.2 85.2 

Hispanica 83.7 84.4 85.0 85.6 86.3 a Hispanics may be of any race. 

Source: U.S. Census Bureau (2008). 

Page Exposure Factors Handbook 

18-6 September 2011 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

19. BUILDING CHARACTERISTICS 

19.1. INTRODUCTION 

Unlike previous chapters in this handbook, 

which focus on human behavior or characteristics 

that affect exposure, this chapter focuses on building 

characteristics. Assessment of exposure in indoor 

settings requires information on the availability of the 

chemical(s) of concern at the point of exposure, 

characteristics of the structure and microenvironment 

that affect exposure, and human presence within the 

building. The purpose of this chapter is to provide 

data that are available on building characteristics that 

affect exposure in an indoor environment. This 

chapter addresses residential and non-residential 

building characteristics (volumes, surface areas, 

mechanical systems, and types of foundations), 

transport phenomena that affect chemical transport 

within a building (airflow, chemical-specific 

deposition and filtration, and soil tracking), and 

information on various types of indoor 

building-related sources associated with airborne 

exposure and soil/house dust sources. 

Source-receptor relationships in indoor exposure 

scenarios can be complex due to interactions among 

sources, and transport/transformation processes that 

result from chemical-specific and building-specific 

factors. 

There are many factors that affect indoor air 

exposures. Indoor air models generally require data 

on several parameters. This chapter provides 

recommendations on two parameters, volume and air 

exchange rates. Other factors that affect indoor air 

quality are furnishings, siting, weather, ventilation 

and infiltration, environmental control systems, 

material durability, operation and maintenance, 

occupants and their activities, and building structure. 

Available relevant information on some of these other 

factors is provided in this chapter, but specific 

recommendations are not provided, as site-specific 

parameters are preferred. 

Figure 19-1 illustrates the complex factors that 

must be considered when conducting exposure 

assessments in an indoor setting. In addition to 

sources within the building, chemicals of concern 

may enter the indoor environment from outdoor air, 

soil, gas, water supply, tracked-in soil, and industrial 

work clothes worn by the residents. Indoor 

concentrations are affected by loss mechanisms, also 

illustrated in Figure 19-1, involving chemical 

reactions, deposition to and re-emission from 

surfaces, and transport out of the building. 

Particle-bound chemicals can enter indoor air through 

resuspension. Indoor air concentrations of gas-phase 

organic chemicals are affected by the presence of 

reversible sinks formed by a wide range of indoor 

materials. In addition, the activity of human receptors 

greatly affects their exposure as they move from 

room to room, entering and leaving the exposure 

scene. 

Inhalation exposure assessments in indoor 

settings are modeled by considering the building as 

an assemblage of one or more well-mixed zones. A 

zone is defined as one room, a group of 

interconnected rooms, or an entire building. At this 

macroscopic level, well-mixed assumptions form the 

basis for interpretation of measurement data as well 

as simulation of hypothetical scenarios. Exposure 

assessment models on a macroscopic level 

incorporate important physical factors and processes. 

These well-mixed, macroscopic models have been 

used to perform indoor air quality simulations (Axley, 

1989), as well as indoor air exposure assessments 

(Ryan, 1991; Mckone, 1989). Nazaroff and Cass 

(1986) and Wilkes et al. (1992) have used computer 

programs featuring finite difference or finite element 

numerical techniques to model mass balance. A 

simplified approach using desktop spreadsheet 

programs has been used by U.S. Environmental 

Protection Agency (EPA) (1990b). EPA has created 

two useful indoor air quality models: the (I-BEAM) 

(http://www.epa.gov/iaq/largebldgs/ 

i-beam/index.html), which estimates indoor air 

quality in commercial buildings and the 

Multi-Chamber Concentration and Exposure Model 

(MCCEM) (http://www.epa.gov/opptintr/exposure/ 

pubs/mccem.htm), which estimates average and peak 

indoor air concentrations of chemicals released from 

residences. 

Major air transport pathways for airborne 

substances in buildings include the following: 

•	 Air exchange—Air leakage through windows, 

doorways, intakes and exhausts, and 

“adventitious openings” (i.e., cracks and 

seams) that combine to form the leakage 

configuration of the building envelope plus 

natural and mechanical ventilation; 

•	 Interzonal airflows—Transport through 

doorways, ductwork, and service chaseways 

that interconnect rooms or zones within a 

building; and 

•	 Local circulation—Convective and advective 

air circulation and mixing within a room or 

within a zone. 

The air exchange rate is generally expressed in 

terms of air changes per hour (ACH), with units of 

Exposure Factors Handbook Page
 

September 2011 19-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

(hour-1). It is defined as the ratio of the airflow 

(m3 hour–1) to the volume (m3

). The distribution of 

airflows across the building envelope that contributes 

to air exchange and the interzonal airflows along 

interior flowpaths is determined by the interior 

pressure distribution. The forces causing the airflows 

are temperature differences, the actions of wind, and 

mechanical ventilation systems. Basic concepts on 

distributions and airflows have been reviewed by the 

American Society of Heating Refrigerating & Air 

Conditioning Engineers (ASHRAE, 2009). Indooroutdoor and room-to-room temperature differences 

create density differences that help determine basic 

patterns of air motion. During the heating season, 

warmer indoor air tends to rise to exit the building at 

upper levels by stack action. Exiting air is replaced at 

lower levels by an influx of colder outdoor air. 

During the cooling season, this pattern is reversed: 

stack forces during the cooling season are generally 

not as strong as in the heating season because the 

indoor-outdoor temperature differences are not as 

pronounced. 

The position of the neutral pressure level (i.e., 

the point where indoor-outdoor pressures are equal) 

depends on the leakage configuration of the building 

envelope. The stack effect arising from 

indoor-outdoor temperature differences is also 

influenced by the partitioning of the building interior. 

When there is free communication between floors or 

stories, the building behaves as a single volume 

affected by a generally rising current during the 

heating season and a generally falling current during 

the cooling season. When vertical communication is 

restricted, each level essentially becomes an 

independent zone. As the wind flows past a building, 

regions of positive and negative pressure (relative to 

indoors) are created within the building; positive 

pressures induce an influx of air, whereas negative 

pressures induce an outflow. Wind effects and stack 

effects combine to determine a net inflow or outflow. 

The final element of indoor transport involves 

the actions of mechanical ventilation systems that 

circulate indoor air through the use of fans. 

Mechanical ventilation systems may be connected to 

heating/cooling systems that, depending on the type 

of building, recirculate thermally treated indoor air or 

a mixture of fresh air and recirculated air. Mechanical 

systems also may be solely dedicated to exhausting 

air from a designated area, as with some kitchen 

range hoods and bath exhausts, or to recirculating air 

in designated areas as with a room fan. Local air 

circulation also is influenced by the movement of 

people and the operation of local heat sources. 

19.2. RECOMMENDATIONS 

Table 19-1 presents the recommendations for 

residential building volumes and air exchange rates. 

Table 19-2 presents the confidence ratings for the 

recommended residential building volumes. The 

U.S. EPA 2010 analysis of the 2005 Residential 

Energy Consumption Survey (RECS) data indicates a 

492 m3 average living space (DOE, 2008a). However, 

these values vary depending on the type of housing 

(see Section 19.3.1.1). The recommended lower end 

of housing volume is 154 m3

. Other percentiles are 

available in Section 19.3.1.1. Residential air 

exchange rates vary by region of the country. The 

recommended median air exchange rate for all 

regions combined is 0.45 ACH. The arithmetic mean 

is not preferred because it is influenced fairly heavily 

by extreme values at the upper tail of the distribution. 

This value was derived by Koontz and Rector (1995) 

using the perflourocarbon tracer (PFT) database. 

Section 19.5.1.1.1 presents distributions for the 

various regions of the country. For a conservative 

value, the 10th percentile for the PFT database 

(0.18 ACH) is recommended (see Section 19.5.1.1.1). 

Table 19-3 presents the recommended values for 

non-residential building volumes and air exchange 

rates. Volumes of non-residential buildings vary with 

type of building (e.g., office space, malls). They 

range from 1,889 m3 for food services to 287,978 m3 

for enclosed malls. The mean for all buildings 

combined is 5,575 m3

. These data come from the 

Commercial Buildings Energy Consumption Survey 

(CBECS) (DOE, 2008b). The last CBECS for which 

data are publicly available was conducted in 2003. 

Table 19-4 presents the confidence ratings for the 

non-residential building volume recommendations. 

The mean air exchange rate for all non-residential 

buildings combined is 1.5 ACH. The 10th percentile 

air exchange rate for all buildings combined is 

0.60 ACH. These data come from Turk et al. (1987). 

Table 19-5 presents the confidence ratings for the 

air exchange rate recommendations for both 

residential and non-residential buildings. Air 

exchange rate data presented in the studies are 

extremely limited. Therefore, the recommended 

values have been assigned a "low" overall confidence 

rating, and these values should be used with caution. 

Volume and air exchange rates can be used by 

exposure assessors in modeling indoor-air 

concentrations as one of the inputs to exposure 

estimation. Other inputs to the modeling effort 

include rates of indoor pollutant generation and 

losses to (and, in some cases, re-emissions from) 

indoor sinks. Other things being equal (i.e., holding 

constant the pollutant generation rate and effect of 

Page Exposure Factors Handbook 

19-2 September 2011 
 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

indoor sinks), lower values for either the indoor 

volume or the air exchange rate will result in higher 

indoor-air concentrations. Thus, values near the lower 

end of the distribution (e.g., 10th percentile) for either 

parameter are appropriate in developing conservative 

estimates of exposure. 

There are some uncertainties in, or limitations 

on, the distribution for volumes and air exchange 

rates that are presented in this chapter. For example, 

the RECS contains information on floor area rather 

than total volume. The PFT database did not base its 

measurements on a sample that was statistically 

representative of the national housing stock. PFT has 

been found to underpredict seasonal average air 

exchange by 20 to 30% Sherman (1989). Using PFT 

to determine air exchange can produce significant 

errors when conditions during the measurements 

greatly deviate from idealizations calling for 

constant, well-mixed conditions. Principal concerns 

focus on the effects of naturally varying air exchange 

and the effects of temperature in the permeation 

source. Some researchers have found that failing to 

use a time-weighted average temperature can greatly 

affect air exchange rate estimates (Leaderer et al., 

1985). A final difficulty in estimating air exchange 

rates for any particular zone results from 

interconnectedness of multi-zone models and the 

effect of neighboring zones as demonstrated by 

Sinden (1978) and Sandberg (1984). 

Table 19-1. Summary of Recommended Values for Residential Building Parameters 

Mean 10th Percentile Source 

Volume of Residencea 

Air Exchange Rate 

492 m3 (central estimate)b 

0.45 ACH (central estimate)d 

154 m3 (lower percentile)c 

0.18 ACH (lower percentile)e 

U.S. EPA 2010 analysis of U.S. DOE 

(2008a) 

Koontz and Rector (1995) a Volumes vary with type of housing. For specific housing type volumes, see Table 19-6. b Mean value presented in Table 19-6 recommended for use as a central estimate for all single family homes, including 

mobile homes and multifamily units. c 10th percentile value from Table 19-8 recommended to be used as a lower percentile estimate. d Median value recommended to be used as a central estimate based across all U.S. census regions (see Table 19-24). e 10th percentile value across all U.S. census regions recommended to be used as a lower percentile value (see 

Table 19-24). 

ACH = Air changes per hour. 

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September 2011 19-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-2. Confidence in Residential Volume Recommendations 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The study was based on primary data. Volumes were 

estimated assuming an 8-foot ceiling height. The effect of 

this assumption has been tested by Murray (1997) and 

found to be insignificant. 

Selection of residences was random. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The focus of the studies was on estimating house volume as 

well as other factors. 

Residences in the United States were the focus of the study. 

The sample size was fairly large and representative of the 

entire United States. Samples were selected at random. 

The most recent RECS survey was conducted in 2005. 

Data were collected in 2005. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The RECS database is publicly available. 

Direct measurements were made. 

Not applicable. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Distributions are presented by housing type and regions, but 

some subcategory sample sizes were small. 

Although residence volumes were estimated using the 

assumption of 8-foot ceiling height, Murray (1997) found 

this assumption to have minimal impact. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The RECS database is publicly available. Some data 

analysis was conducted by U.S. EPA. 

Only one study was used to derive recommendations. Other 

relevant studies provide supporting evidence. 

Medium 

Overall Rating . Medium 

Page Exposure Factors Handbook 

19-4 September 2011 
 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-3. Summary of Recommended Values for Non-Residential Building Parameters 

Meana 10th Percentileb Source 

Volume of Building (m3)

c 

U.S. EPA analysis of 

U.S. DOE (2008b) 

Vacant 4,789 408 

Office 5,036 510 

Laboratory 24,681 2,039 

Non-refrigerated 

warehouse 9,298 1,019 

Food sales 1,889 476 

Public order and safety 5,253 816 

Outpatient healthcare 3,537 680 

Refrigerated warehouse 19,716 1,133 

Religious worship 3,443 612 

Public assembly 4,839 595 

Education 8,694 527 

Food service 1,889 442 

Inpatient healthcare 82,034 17,330 

Nursing 15,522 1,546 

Lodging 11,559 527 

Strip shopping mall 7,891 1,359 

Enclosed mall 287,978 35,679 

Retail other than mall 3,310 510 

Service 2,213 459 

Other 5,236 425 

All Buildingsd 5,575 527 

Air Exchange Ratee Mean (SD)1.5 (0.87) ACH 

Range 0.3–4.1 ACH 0.60 ACH Turk et al. (1987) 

a Mean values are recommended as central estimates for non-residential buildings (see Table 19-20). b 10th percentile values are recommended as lower estimates for non-residential buildings (see 

Table 19-20). c Volumes were calculated assuming a ceiling height of 20 feet for warehouses and enclosed malls and 

12 feet for other structures (see Table 19-20). d Weighted average assuming a ceiling height of 20 feet for warehouses and enclosed malls and 12 feet 

for other structures (see Table 19-20). e Air exchange rates for commercial buildings (see Table 19-27). 

SD = Standard deviation. 

ACH = Air changes per hour. 

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Table 19-4. Confidence in Non-Residential Volume Recommendations 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

All non-residential data were based on one study: CBECS 

(DOE, 2008b). Volumes were estimated assuming a 20-foot 

ceiling height assumption for warehouses and a 12-foot 

height assumption for all other non-residential buildings 

based on scant anecdotal information. Although Murray 

(1997) found that the impact of an 8-foot ceiling assumption 

was insignificant for residential structures, the impact of 

these ceiling height assumptions for non-residential 

buildings is unknown. 

Selection of residences was random for CBECS. 

Medium 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency, Data Collection Period 

CBECS (DOE, 2008b) contained ample building size data, 

which were used as the basis provided for volume estimates. 

CBECS (DOE, 2008b) was a nationwide study that 

generated weighted nationwide data based upon a large 

random sample. 

The data were collected in 2003. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The data are available online in both summary tables and 

raw data. http://www.eia.doe.gov/emeu/cbecs/contents.html 

Direct measurements were made. 

Not applicable. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Distributions are presented by building type, heating and 

cooling system type, and employment, but a few 

subcategory sample sizes were small. 

Volumes were calculated using speculative assumptions for 

building height. The impact of such assumptions may or 

may not be significant. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

There are no studies from the peer-reviewed literature. 

All data are based upon one study: CBECS (DOE, 2008b). 

Low 

Overall Rating . Medium 

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Table 19-5. Confidence in Air Exchange Rate Recommendations for Residential and Non-Residential 

Buildings 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The studies were based on primary data; however, most 

approaches contained major limitations, such as assuming 

uniform mixing, and residences were typically not selected 

at random. 

Bias may result because the selection of residences and 

buildings was not random. The commercial building study 

(Turk et al., 1987) was conducted only on buildings in the 

northwest United States. 

Low 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The focus of the studies was on estimating air exchange 

rates as well as other factors. 

Study residences were typically in the United States, but 

only RECS (DOE, 2008a) selected residences randomly. 

PFT residences were not representative of the United States. 

Distributions are presented by housing type and regions; 

although some of the sample sizes for the subcategories 

were small. The commercial building study (Turk et al., 

1987) was conducted only on buildings in the northwest 

United States. 

Measurements in the PFT database were taken between 

1982–1987. The Turk et al. (1987) study was conducted in 

the mid-1980s. 

Only short-term data were collected; some residences were 

measured during different seasons; however, long-term air 

exchange rates are not well characterized. Individual 

commercial buildings were measured during one season. 

Low 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

Papers are widely available from government reports and 

peer-reviewed journals. 

Precision across repeat analyses has been documented to be 

acceptable. 

Not applicable. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

For the residential estimates, distributions are presented by 

U.S. regions, seasons, and climatic regions, but some of the 

sample sizes for the subcategories were small. The 

commercial estimate comes from buildings in the northwest 

U.S. representing two climate zones, and measurements 

were taken in three seasons (spring, summer, and winter). 

Some measurement error may exist. Additionally, PFT has 

been found to underpredict seasonal average air exchange 

by 20–30% (Sherman, 1989). Turk et al. (1987) estimates a 

10–20% measurement error for the technique used to 

measure ventilation in commercial buildings. 

Medium 

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Table 19-5. Confidence in Air Exchange Rate Recommendations for Residential and Non-Residential 

Buildings (continued) 

General Assessment Factors Rationale Rating 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The studies appear in peer-reviewed literature. 

Three residential studies are based on the same PFT 

database. The database contains results of 20 projects of 

varying scope. The commercial building rate is based on 

one study. 

Low 

Overall Rating Low 

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19.3.	 RESIDENTIAL BUILDING 

CHARACTERISTICS STUDIES 

19.3.1.	 Key Study of Volumes of Residences 

19.3.1.1.	 U.S. DOE (2008a)—Residential Energy 

Consumption Survey (RECS) 

Measurement surveys have not been conducted 

to directly characterize the range and distribution of 

volumes for a random sample of U.S. residences. 

Related data, however, are regularly collected 

through the U.S. Department of Energy’s (DOE) 

RECS. In addition to collecting information on 

energy use, this triennial survey collects data on 

housing characteristics including direct 

measurements of total and heated floor space for 

buildings visited by survey specialists. For the most 

recent survey done in 2005, a multistage probability 

sample of 4,381 residences was surveyed, 

representing 111 million housing units nationwide. 

The 2005 survey response rate was 77.1%. Volumes 

were estimated from the RECS measurements by 

multiplying the heated floor space area by an 

assumed ceiling height of 8 feet. The data and data 

tables were released to the public in 2008. 

In 2010, the U.S. EPA conducted an analysis of 

the RECS 2005 survey data. Table 19-6 and 

Table 19-7 present results for residential volume 

distributions by type of residence, ownership, and 

year of construction from the 2005 RECS. Table 19-6 

provides information on average estimated residential 

volumes according to housing type and ownership. 

The predominant housing type—single-family 

detached homes—also had the largest average 

volume. Multifamily units and mobile homes had 

volumes averaging about half that of single-family 

detached homes, with single-family attached homes 

about halfway between these extremes. Within each 

category of housing type, owner-occupied residences 

averaged about 50% greater volume than rental units. 

Data on the relationship of residential volume to year 

of construction are provided in Table 19-7 and 

indicate a slight decrease in residential volumes 

between 1950 and 1979, followed by an increasing 

trend. A ceiling height of 8 feet was assumed in 

estimating the average volumes, whereas there may 

have been some time-related trends in ceiling height. 

Table 19-8 presents distributions of residential 

volumes for all house types and all units. The average 

house volume for all types of units for all years was 

estimated to be 492 m3

. 

It is important to note that in 2005, the RECS 

changed the way it calculated total square footage. 

The total average square footage per housing unit for 

the 2001 RECS was reported as 1,975 ft2

. This figure 

excluded unheated garages, and for most housing 

units, living space in attics. The average total square 

footage for housing units in the 2005 RECS was 

2,171 ft2 (i.e., 492 m3 converted to ft3 and assuming 

an 8-foot ceiling; see Table 19-7), which includes 

attic living space for all housing units. The only 

available figures that permit comparison of total 

square footage for both survey years would exclude 

all garage floorspace and attic floorspace in all 

housing units—for 2001, the average total square 

footage was 2,005, and for 2005, the average total 

was 2,029 ft2

. 

The advantages of this study were that the 

sample size was large, and it was representative of 

houses in the United States. Also, it included various 

housing types. A limitation of this analysis is that 

volumes were estimated assuming a ceiling height of 

8 feet. Volumes of individual rooms in the house 

cannot be estimated. 

19.3.2.	 Relevant Studies of Volumes of 

Residences 

19.3.2.1.	 Versar (1990)—Database on 

Perfluorocarbon Tracer (PFT) 

Ventilation Measurements 

Versar (1990) compiled a database of 

time-averaged air exchange and interzonal airflow 

measurements in more than 4,000 residences. These 

data were collected between 1982 and 1987. The 

residences that appear in this database are not a 

random sample of U.S. homes. However, they 

represent a compilation of homes visited in about 

100 different field studies, some of which involved 

random sampling. In each study, the house volumes 

were directly measured or estimated. The collective 

homes visited in these field projects are not 

geographically balanced. A large fraction of these 

homes are located in southern California. Statistical 

weighting techniques were applied in developing 

estimates of nationwide distributions to compensate 

for the geographic imbalance. The Versar (1990) PFT 

database found a mean value of 369 m3 (see 

Table 19-9). 

The advantage of this study is that it provides a 

distribution of house volumes. However, more 

up-to-date data are available from RECS 2005 (DOE, 

2008a). 

19.3.2.2.	 Murray (1997)—Analysis of RECS and 

PFT Databases 

Using a database from the 1993 RECS and an 

assumed ceiling height of 8 feet, Murray (1997) 

estimated a mean residential volume of 382 m3 using 

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RECS estimates of heated floor space. This estimate 

is slightly different from the mean of 369 m3 given in 

Table 19-9. Murray’s (1997) sensitivity analysis 

indicated that when a fixed ceiling height of 8 feet 

was replaced with a randomly varying height with a 

mean of 8 feet, there was little effect on the standard 

deviation of the estimated distribution. From a 

separate analysis of the PFT database, based on 

1,751 individual household measurements, Murray 

(1997) estimated an average volume of 369 m3

, the 

same as previously given in Table 19-9. In 

performing this analysis, the author carefully 

reviewed the PFT database in an effort to use each 

residence only once, for those residences thought to 

have multiple PFT measurements. 

Murray (1997) analyzed the distribution of 

selected residential zones (i.e., a series of connected 

rooms) using the PFT database. The author analyzed 

the "kitchen zone" and the "bedroom zone" for 

houses in the Los Angeles area that were labeled in 

this manner by field researchers, and "basement," 

"first floor," and "second floor" zones for houses 

outside of Los Angeles for which the researchers 

labeled individual floors as zones. The kitchen zone 

contained the kitchen in addition to any of the 

following associated spaces: utility room, dining 

room, living room, and family room. The bedroom 

zone contained all the bedrooms plus any bathrooms 

and hallways associated with the bedrooms. The 

following summary statistics (mean ± standard 

deviation) were reported by Murray (1997) for the 

volumes of the zones described above: 199 ± 115 m3 

for the kitchen zone, 128 ± 67 m3 for the bedroom 

zone, 205 ± 64 m3 for the basement, 233 ± 72 m3 for 

the first floor, and 233 ± 111 m3 for the second floor. 

The advantage of this study is that the data are 

representative of homes in the United States. 

However, more up-to-date data are available from the 

RECS 2005 (DOE, 2008a). 

19.3.2.3.	 U.S. Census Bureau (2009)—American 

Housing Survey for the United States: 

2009 

The American Housing Survey (AHS) is 

conducted by the Census Bureau for the Department 

of Housing and Urban Development. It collects data 

on the Nation's housing, including apartments, 

single-family homes, mobile homes, vacant housing 

units, household characteristics, housing quality, 

foundation type, drinking water source, equipment 

and fuels, and housing unit size. National data are 

collected in odd-numbered years, and data for each of 

47 selected Metropolitan Areas are collected about 

every 6 years. The national sample includes about 

55,000 housing units. Each metropolitan area 

samples 4,100 or more housing units. The AHS 

returns to the same housing units year after year to 

gather data. The U.S. Census Bureau (2009) lists the 

number of residential single detached and 

manufactured/mobile homes in the United States 

within various categories including seasonal, yearround occupied, and new in the last 4 years, based on 

the AHS (see Table 19-10). Assuming an 8-foot 

ceiling, these units have a median size of 385 m3

; 

however, these values do not include multifamily 

units. It should be mentioned that 8 feet is the most 

common ceiling height, and Murray (1997) has 

shown that the effect of the 8-foot ceiling height 

assumption is not significant. 

The advantage of this study is that it was a large 

national sample and, therefore, representative of the 

United States. The limitations of these data are that 

distributions were not provided by the authors, and 

the analysis did not include multifamily units. 

19.3.3. Other Factors 

19.3.3.1.	 Surface Area and Room Volumes 

The surface areas of floors are commonly 

considered in relation to the room or house volume, 

and their relative loadings are expressed as a surface 

area-to-volume, or loading ratio. Table 19-11 

provides the basis for calculating loading ratios for 

typical-sized rooms. Constant features in the 

examples are a room width of 12 feet and a ceiling 

height of 8 feet (typical for residential buildings), or a 

ceiling height of 12 feet (typical for some types of 

commercial buildings). 

Volumes of individual rooms are dependent on 

the building size and configuration, but summary 

data are not readily available. The exposure assessor 

is advised to define specific rooms, or assemblies of 

rooms, that best fit the scenario of interest. Most 

models for predicting indoor air concentrations 

specify airflows in m3 per hour and, correspondingly, 

express volumes in m3

. A measurement in ft3 can be 

converted to m3 by multiplying the value in ft3 by 

0.0283 m3

/ft3. For example, a bedroom that is 9 feet 

wide by 12 feet long by 8 feet high has a volume of 

864 ft3 or 24.5 m3

. Similarly, a living room with 

dimensions of 12 feet wide by 20 feet long by 8 feet 

high has a volume of 1,920 ft3 or 54.3 m3

, and a 

bathroom with dimensions of 5 feet by 12 feet by 

8 feet has a volume of 480 ft3 or 13.6 m3

. 

19.3.3.2.	 Products and Materials 

Table 19-12 presents examples of assumed 

amounts of selected products and materials used in 

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constructing or finishing residential surfaces (Tucker, 

1991). Products used for floor surfaces include 

adhesive, varnish, and wood stain; and materials used 

for walls include paneling, painted gypsum board, 

and wallpaper. Particleboard and chipboard are 

commonly used for interior furnishings such as 

shelves or cabinets but could also be used for decking 

or underlayment. It should be noted that numbers 

presented in the table for surface area are based on 

typical values for residences, and they are presented 

as examples. In contrast to the concept of loading 

ratios presented above (as a surface area), the 

numbers in the table also are not scaled to any 

particular residential volume. In some cases, it may 

be preferable for the exposure assessor to use 

professional judgment in combination with the 

loading ratios given above. For example, if the 

exposure scenario involves residential carpeting, 

either as an indoor source or as an indoor sink, then 

the American Society for Testing and Materials 

(ASTM) loading ratio of 0.43 m2

m–3 for floor 

materials could be multiplied by an assumed 

residential volume and assumed fractional coverage 

of carpeting to derive an estimate of the surface area. 

More specifically, a residence with a volume of 

300 m3

, a loading ratio of 0.43 m2m–3, and coverage 

of 80%, would have 103 m2 of carpeting. The 

estimates discussed here relate to macroscopic 

surfaces; the true surface area for carpeting, for 

example, would be considerably larger because of the 

nature of its fibrous material. 

19.3.3.3. Loading Ratios 

The loading ratios for the 8-foot ceiling height 

range from 0.98 m2

m–3 to 2.18 m2m–3 for wall areas 

and from 0.36 m2

m–3 to 0.44 m2m–3 for floor area. In 

comparison, ASTM Standard E 1333 (ASTM, 1990), 

for large-chamber testing of formaldehyde levels 

from wood products, specifies the following loading 

ratios: (1) 0.95 m2

m–3 for testing plywood (assumes 

plywood or paneling on all four walls of a typical 

size room); and (2) 0.43 m2

m–3 for testing 

particleboard (assumes that particleboard decking or 

underlayment would be used as a substrate for the 

entire floor of a structure). 

19.3.3.4. Mechanical System Configurations 

Mechanical systems for air movement in 

residences can affect the migration and mixing of 

pollutants released indoors and the rate of pollutant 

removal. Three types of mechanical systems are 

(1) systems associated with heating, ventilating, and 

air conditioning (HVAC); (2) systems whose primary 

function is providing localized exhaust; and 

(3) systems intended to increase the overall air 

exchange rate of the residence. 

Portable space heaters intended to serve a single 

room, or a series of adjacent rooms, may or may not 

be equipped with blowers that promote air movement 

and mixing. Without a blower, these heaters still have 

the ability to induce mixing through convective heat 

transfer. If the heater is a source of combustion 

pollutants, as with unvented gas or kerosene space 

heaters, then the combination of convective heat 

transfer and thermal buoyancy of combustion 

products will result in fairly rapid dispersal of such 

pollutants. The pollutants will disperse throughout 

the floor where the heater is located and to floors 

above the heater, but will not disperse to floors 

below. 

Central forced-air HVAC systems are common in 

many residences. Such systems, through a network of 

supply/return ducts and registers, can achieve fairly 

complete mixing within 20 to 30 minutes (Koontz et 

al., 1988). The air handler for such systems is 

commonly equipped with a filter (see Figure 19-2) 

that can remove particle-phase contaminants. Further 

removal of particles, via deposition on various room 

surfaces (see Section 19.5.5), is accomplished 

through increased air movement when the air handler 

is operating. 

Figure 19-2 also distinguishes forced-air HVAC 

systems by the return layout in relation to supply 

registers. The return layout shown in the upper 

portion of the figure is the type most commonly 

found in residential settings. On any floor of the 

residence, it is typical to find one or more supply 

registers to individual rooms, with one or 

two centralized return registers. With this layout, 

supply/return imbalances can often occur in 

individual rooms, particularly if the interior doors to 

rooms are closed. In comparison, the supply/return 

layout shown in the lower portion of the figure by 

design tends to achieve a balance in individual rooms 

or zones. Airflow imbalances can also be caused by 

inadvertent duct leakage to unconditioned spaces 

such as attics, basements, and crawl spaces. Such 

imbalances usually depressurize the house, thereby 

increasing the likelihood of contaminant entry via 

soil-gas transport or through spillage of combustion 

products from vented fossil-fuel appliances such as 

fireplaces and gas/oil furnaces. 

Mechanical devices such as kitchen fans, 

bathroom fans, and clothes dryers are intended 

primarily to provide localized removal of unwanted 

heat, moisture, or odors. Operation of these devices 

tends to increase the air exchange rate between the 

indoors and outdoors. Because local exhaust devices 

are designed to be near certain indoor sources, their 

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effective removal rate for locally generated pollutants 

is greater than would be expected from the dilution 

effect of increased air exchange. Operation of these 

devices also tends to depressurize the house, because 

replacement air usually is not provided to balance the 

exhausted air. 

An alternative approach to pollutant removal is 

one which relies on an increase in air exchange to 

dilute pollutants generated indoors. This approach 

can be accomplished using heat recovery ventilators 

(HRVs) or energy recovery ventilators (ERVs). Both 

types of ventilators are designed to provide balanced 

supply and exhaust airflows and are intended to 

recover most of the energy that normally is lost when 

additional outdoor air is introduced. Although 

ventilators can provide for more rapid dilution of 

internally generated pollutants, they also increase the 

rate at which outdoor pollutants are brought into the 

house. A distinguishing feature of the two types is 

that ERVs provide for recovery of latent heat 

(moisture) in addition to sensible heat. Moreover, 

ERVs typically recover latent heat using a 

moisture-transfer device such as a desiccant wheel. It 

has been observed in some studies that the transfer of 

moisture between outbound and inbound air streams 

can result in some re-entrainment of indoor pollutants 

that otherwise would have been exhausted from the 

house (Andersson et al., 1993). Inadvertent air 

communication between the supply and exhaust air 

streams can have a similar effect. 

Studies quantifying the effect of mechanical 

devices on air exchange using tracer-gas 

measurements are uncommon and typically provide 

only anecdotal data. The common approach is for the 

expected increment in the air exchange rate to be 

estimated from the rated airflow capacity of the 

device(s). For example, if a device with a rated 

capacity of 100 ft3 per minute, or 170 m3 per hour, is 

operated continuously in a house with a volume of 

400 m3

, then the expected increment in the air 

exchange rate of the house would be 

170 m3 hour-1/400 m3

, or approximately 0.4 ACH. 

U.S. DOE RECS contains data on residential 

heating characteristics. The data show that most 

homes in the United States have some kind of heating 

and air conditioning system (DOE, 2008a). The types 

of system vary regionally within the United States. 

Table 19-13 shows the type of primary and secondary 

heating systems found in U.S. residences. The 

predominant primary heating system in the Midwest 

is natural gas (used by 72% of homes there) while 

most homes in the South (54%) primarily heat with 

electricity. Nationwide, 31% of residences have a 

secondary heating source, typically an electric 

source. 

Table 19-14 shows the type of heating systems 

found in the United States by urban/rural location. It 

is noteworthy that 56% of suburban residences use 

central heating compared to 16% in rural areas. 

Another difference is that only 25% of residences in 

cities used a secondary heating system, which used 

typically electric, compared to 48% in rural areas, 

typically electric or wood. 

Table 19-15 shows that 84% of U.S. residences 

have some type of cooling system: 59% have central 

air while 26% use window units. Like heating 

systems, cooling system type varies regionally as 

well. In the South, 97% of residences have either 

central or room air conditioning units whereas only 

57% of residences in the Western United States have 

air conditioning. Frequency of use varies regionally 

as well. About 61% of residences in the South use 

their air conditioner all summer long, but only 15% 

do so in the Northeast. 

19.3.3.5. Type of Foundation 

The type of foundation of a residence is of 

interest in residential exposure assessment. It 

provides some indication of the number of stories and 

house configuration, as well as an indication of the 

relative potential for soil−gas transport. For example, 

such transport can occur readily in homes with 

enclosed crawl spaces. Homes with basements 

provide some resistance, but still have numerous 

pathways for soil−gas entry. By comparison, homes 

with crawl spaces open to the outside have significant 

opportunities for dilution of soil gases prior to 

transport into the house. Using data from the 2009 

AHS, of total housing units in the United States, 33% 

have a basement under the entire building, 10% have 

a basement under part of the building, 23% have a 

crawl space, and 32% are on a concrete slab (U.S. 

Census Bureau, 2009). 

19.3.3.5.1.	 Lucas et al. (1992)—National 

Residential Radon Survey 

The estimated percentage of homes with a full or 

partial basement according to the National 

Residential Radon Survey of 5,700 households 

nationwide was 45% (see Table 19-16) (Lucas et al., 

1992). The National Residential Radon Survey 

provides data for more refined geographical areas, 

with a breakdown by the 10 U.S. EPA Regions. The 

New England region (i.e., U.S. EPA Region 1), which 

includes Connecticut, Maine, Massachusetts, New 

Hampshire, Rhode Island, and Vermont, had the 

highest prevalence of basements (93%). The lowest 

prevalence (4%) was for the South Central region 

(i.e., U.S. EPA Region 6), which includes Arkansas, 

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Louisiana, New Mexico, Oklahoma, and Texas. 

Section 19.3.3.5.2 presents the States associated with 

each census region and U.S. EPA region. 

19.3.3.5.2.	 U.S. DOE (2008a)—Residential 

Energy Consumption Survey 

(RECS) 

The most recent RECS (described in 

Section 19.3.1.1) was administered in 2005 to over 

4,381 households (DOE, 2008a). The type of 

information requested by the survey questionnaire 

included the type of foundation for the residence (i.e., 

basement, enclosed crawl space, crawl space open to 

outside, or concrete slab). This information was not 

obtained for multifamily structures with five or more 

dwelling units or for mobile homes. U.S. EPA 

analyzed the RECS 2005 data (DOE, 2008a) to 

estimate the percentage of residences with basements 

and different foundation types by census region and 

by U.S. EPA region. Table 19-17 presents these 

estimates. Table 19-18 shows the states associated 

with each U.S. EPA region and census region. 

Table 19-19 presents estimates of the percentage of 

residences with each foundation type, by census 

region, and for the entire United States. The 

percentages can add up to more than 100% because 

some residences have more than one type of 

foundation; for example, many split-level structures 

have a partial basement combined with some 

crawlspace that typically is enclosed. The data in 

Table 19-19 indicate that 40.6% of residences 

nationwide have a basement. It also shows that a 

large fraction of homes have concrete slabs (46%). 

There are also variations by census region. For 

example, around 73% and 68% of the residences in 

the Northeast and Midwest regions, respectively, 

have basements. In the South and West regions, the 

predominant foundation type is concrete slab. 

The advantage of this study is that it had a large 

sample size, and it was representative of houses in 

the United States. Also, it included various housing 

types. A limitation of this analysis is that homes have 

multiple foundation types, and the analysis does not 

provide estimates of square footage for each type of 

foundation. 

19.4.	 NON-RESIDENTIAL BUILDING 

CHARACTERISTICS STUDIES 

19.4.1.	 U.S. DOE (2008b)—Non-Residential 

Building Characteristics—Commercial 

Buildings Energy Consumption Survey 

(CBECS) 

The U.S. Department of Energy conducts the 

CBECS to collect data on the characteristics and 

energy use of commercial buildings. The survey is 

conducted every 4 years. The latest survey for which 

data are available (released in 2008) is the 2003 

CBECS. CBECS defines “Commercial” buildings as 

all buildings in which at least half of the floorspace is 

used for a purpose that is not residential, industrial, or 

agricultural, so they include building types that might 

not traditionally be considered commercial, such as 

schools, correctional institutions, and buildings used 

for religious worship. 

CBECS is a national survey of U.S. buildings 

that DOE first conducted in 1979. The 2003 CBECS 

provided nationwide estimates for the United States 

based upon a weighted statistical sample of 

5,215 buildings. DOE releases a data set about the 

sample buildings for public use. The 2003 CBECS 

Public Use Microdata set includes data for 

4,820 non-mall commercial buildings (DOE, 2008b). 

A second data set available that includes information 

on malls, lacks building characteristics data. Building 

characteristics data provided by CBECS includes 

floor area, number of floors, census division, heating 

and cooling design, principal building activity, 

number of employees, and weighting factors. The 

2003 CBECS data survey provides the best statistical 

characterization of the commercial sector available 

for the United States. A 2007 CBECS was conducted, 

but the data were not publicly available at the time 

this handbook was published. 

In 2010, U.S. EPA conducted an analysis of the 

U.S. DOE CBECS 2003 data, released in 2008. 

Table 19-20 shows that non-residential buildings vary 

greatly in volumes. The table shows average volume 

for a numbers of structures including offices 

(5,036 m3

), restaurants (food services) (1,889 m3), 

schools (education) (8,694 m3

), hotels (lodging) 

(11,559 m3

), and enclosed shopping malls (287,978 

m3

). Each of these structures varies considerably in 

size as well. The large shopping malls are over 

500,000 m3 (90th percentile). The most numerous of 

the non-residential buildings are office buildings 

(18%), non-food service buildings (13%), and 

warehouses (13%). 

Table 19-21 presents data on the number of 

hours various types of non-residential buildings are 

open for business and the number of employees that 

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work in such buildings. In general, places of worship 

have the most limited hours. The average place of 

worship is open 32 hours per week. On the other 

extreme are healthcare facilities, which are open 

168 hours a week (24 hours per day, 7 days per 

week). The average restaurant is open 86 hours per 

week. Hours vary considerably by building type. 

Some offices, labs, warehouses, restaurants, police 

stations, and hotels are also open 24 hours per day, 

7 days per week, as reflected by the 90th percentiles. 

Table 19-21 also presents the number of employees 

typically employed in such buildings during the main 

shift. Overall, the average building houses 

16 workers during its primary shift, but some 

facilities employ many more. The average hospital 

employs 471 workers during its main shift, although 

those in the 10th percentile employ only 175, and 

those in the 90th employ 2,250. 

CBECS data on heating and cooling sources 

were tabulated by the U.S. Energy Information 

Administration of the U.S. DOE and released to the 

public (along with the data) in 2008 (DOE, 2008b). 

Table 19-22 and Table 19-23 present these data. 

Table 19-22 indicates that electricity and natural gas 

are the heating sources used by a majority of 

non-residential buildings. Of those buildings heated 

by fuel oil, most are older buildings. 

Table 19-23 describes non-residential building 

cooling characteristics. About 78% (i.e., 3,625/4,645) 

of non-residential buildings have air conditioning, but 

this varies regionally from 14% in the Northeast to 

41% in the South. Nationwide, 77% (i.e., 

3,589/4,645) of non-residential buildings use 

electricity for air conditioning. The remaining 

fraction use natural gas or chilled water. 

It should be noted, however, that there are many 

critical exposure assessment elements not addressed 

by CBECS. These include a number of elements 

discussed in more detail in the Residential Building 

Characteristics Studies section (i.e., Section 19.3). 

Data to characterize the room volume, products and 

materials, loading ratios, and foundation type for 

non-residential buildings were not available in 

CBECS. 

Another characteristic of non-residential 

buildings needed in ventilation and air exchange 

calculations is ceiling height. In the residential 

section of this chapter, ceiling height was assumed to 

be 8 feet, a figure often assumed for residential 

buildings. For non-residential buildings, U.S. EPA 

has assumed a 20 foot ceiling height for warehouses 

and enclosed shopping malls and a 12-foot average 

ceiling height for other structures. These assumptions 

are based on professional judgment. Murray (1997) 

found that the impact of assuming an 8-foot ceiling 

height for residences was insignificant, but 

non-residential ceiling height varies more greatly and 

may or may not have a significant impact on 

calculations. 

19.5. TRANSPORT RATE STUDIES 

19.5.1. Air Exchange Rates 

Air exchange is the balanced flow into and out of 

a building and is composed of three processes: 

(1) infiltration—air leakage through random cracks, 

interstices, and other unintentional openings in the 

building envelope; (2) natural ventilation—airflows 

through open windows, doors, and other designed 

openings in the building envelope; and (3) forced or 

mechanical ventilation—controlled air movement 

driven by fans. For nearly all indoor exposure 

scenarios, air exchange is treated as the principal 

means of diluting indoor concentrations. The air 

exchange rate is generally expressed in terms of ACH 

(with units of hours–1). It is defined as the ratio of the 

airflow (m3 hours–1) to the volume (m3

). Thus, ACH 

and building size and volume are negatively 

correlated. 

No measurement surveys have been conducted to 

directly evaluate the range and distribution of 

building air exchange rates. Although a significant 

number of air exchange measurements have been 

carried out over the years, there has been a diversity 

of protocols and study objectives. Since the early 

1980s, however, an inexpensive PFT technique has 

been used to measure time-averaged air exchange and 

interzonal airflows in thousands of occupied 

residences using essentially similar protocols (Dietz 

et al., 1986). The PFT technique utilizes miniature 

permeation tubes as tracer emitters and passive 

samplers to collect the tracers. The passive samplers 

are returned to the laboratory for analysis by gas 

chromatography. These measurement results have 

been compiled to allow various researchers to access 

the data (Versar, 1990). 

With regard to residential air exchange, an 

attached garage can negatively impact indoor air 

quality. In addition to automobile exhaust, people 

often store gasoline, oil, paints, lacquers, and yard 

and garden supplies in garages. Appliances such as 

furnaces, heaters, hot water heaters, dryers, 

gasoline-powered appliances, and wood stoves may 

also impact indoor air quality. Garages can be a 

source of volatile organic compounds (VOCs) such 

as benzene, toluene, ethylbenzene, m,p-xylene, and 

o-xylene. Emmerich et al. (2003) conducted a 

literature review on indoor air quality and the 

transport of pollutants from attached garages to 

residential living spaces. The authors found the body 

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Chapter 19—Building Characteristics 

of literature on the subject was limited and contained 

little data with regard to airtightness and geometry of 

the house-garage interface, and the impact of heating 

and cooling equipment. They concluded, however, 

that there is substantial evidence that the transport of 

contaminants from garages has the potential to 

negatively impact residences. 

19.5.1.1.	 Key Study of Residential Air Exchange 

Rates 

19.5.1.1.1.	 Koontz and Rector (1995)— 

Estimation of Distributions for 

Residential Air Exchange Rates 

In analyzing the composite data from various 

projects (2,971 measurements), Koontz and Rector 

(1995) assigned weights to the results from each state 

to compensate for the geographic imbalance in 

locations where PFT measurements were taken. The 

results were weighted in such a way that the resultant 

number of cases would represent each state in 

proportion to its share of occupied housing units, as 

determined from the 1990 U.S. Census of Population 

and Housing. 

Table 19-24 shows summary statistics from the 

Koontz and Rector (1995) analysis, for the country as 

a whole and by census regions. Based on the statistics 

for all regions combined, the authors suggested that a 

10th percentile value of 0.18 ACH would be 

appropriate as a conservative estimator for air 

exchange in residential settings, and that the 

50th percentile value of 0.45 ACH would be 

appropriate as a typical air exchange rate. In applying 

conservative or typical values of air exchange rates, it 

is important to realize the limitations of the 

underlying database. Although the estimates are 

based on thousands of measurements, the residences 

represented in the database are not a random sample 

of the U.S. housing stock. Also, the sample 

population is not balanced in terms of geography or 

time of year, although statistical techniques were 

applied to compensate for some of these imbalances. 

In addition, PFT measurements of air exchange rates 

assume uniform mixing of the tracer within the 

building. This is not always so easily achieved. 

Furthermore, the degree of mixing can vary from day 

to day and house to house because of the nature of 

the factors controlling mixing (e.g., convective air 

monitoring driven by weather, and type and operation 

of the heating system). The relative placement of the 

PFT source and the sampler can also cause variability 

and uncertainty. It should be noted that sampling is 

typically done in a single location in a house that may 

not represent the average from that house. In 

addition, very high and very low values of air 

exchange rates based on PFT measurements have 

greater uncertainties than those in the middle of the 

distribution. Despite such limitations, the estimates in 

Table 19-24 are believed to represent the best 

available information on the distribution of air 

exchange rates across U.S. residences throughout the 

year. 

19.5.1.2.	 Relevant Studies of Residential Air 

Exchange Rates 

19.5.1.2.1.	 Nazaroff et al. (1988)—Radon Entry 

via Potable Water 

Nazaroff et al. (1988) aggregated the data from 

two studies conducted earlier using tracer-gas decay. 

At the time these studies were conducted, they were 

the largest U.S. studies to include air exchange 

measurements. The first (Grot and Clark, 1979) was 

conducted in 255 dwellings occupied by low-income 

families in 14 different cities. The geometric 

mean ± standard deviation for the air exchange 

measurements in these homes, with a median house 

age of 45 years, was 0.90 ± 2.13 ACH. The second 

study (Grimsrud et al., 1983) involved 312 newer 

residences, with a median age of less than 10 years. 

Based on measurements taken during the heating 

season, the geometric mean ± standard deviation for 

these homes was 0.53 ± 1.71 ACH. Based on an 

aggregation of the two distributions with proportional 

weighting by the respective number of houses 

studied, Nazaroff et al. (1988) developed an overall 

distribution with a geometric mean of 0.68 ACH and 

a geometric standard deviation of 2.01. 

19.5.1.2.2.	 Versar (1990)—Database of PFT 

Ventilation Measurements 

The residences included in the PFT database do 

not constitute a random sample across the United 

States. They represent a compilation of homes visited 

in the course of about 100 separate field-research 

projects by various organizations, some of which 

involved random sampling, and some of which 

involved judgmental or fortuitous sampling. 

Table 19-25 summarizes the larger projects in the 

PFT database, in terms of the number of 

measurements (samples), states where samples were 

taken, months when samples were taken, and 

summary statistics for their respective distributions of 

measured air exchange rates. For selected projects 

(Lawrence Berkeley Laboratory, Research Triangle 

Institute, Southern California—SOCAL), multiple 

measurements were taken for the same house, usually 

during different seasons. A large majority of the 

measurements are from the SOCAL project that was 

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conducted in Southern California. The means of the 

respective studies generally range from 0.2 to 

1.0 ACH, with the exception of two California 

projects—RTI2 and SOCAL2. Both projects involved 

measurements in Southern California during a time of 

year (July) when windows would likely be opened by 

many occupants. 

The limitation of this study is that the PFT 

database did not base its measurements on a sample 

that was statistically representative of the national 

housing stock. PFT has been found to underpredict 

seasonal average air exchange by 20 to 30% 

(Sherman, 1989). Using PFT to determine air 

exchange can produce significant errors when 

conditions in the measurement scene greatly deviate 

from idealizations calling for constant, well-mixed 

conditions. 

19.5.1.2.3. Murray and Burmaster (1995)— 

Residential Air Exchange Rates in 

the United States: Empirical and 

Estimated Parametric Distributions 

by Season and Climatic Region 

Murray and Burmaster (1995) analyzed the PFT 

database using 2,844 measurements (essentially the 

same cases as analyzed by Koontz and Rector (1995), 

but without the compensating weights). These 

authors summarized distributions for subsets of the 

data defined by climate region and season. The 

months of December, January, and February were 

defined as winter; March, April, and May were 

defined as spring; and so on. Table 19-26 summarizes 

the results of Murray and Burmaster (1995) 

Neglecting the summer results in the colder regions, 

which have only a few observations, the results 

indicate that the highest air exchange rates occur in 

the warmest climate region during the summer. As 

noted earlier, many of the measurements in the 

warmer climate region were from field studies 

conducted in Southern California during a time of 

year (July) when windows would tend to be open in 

that area. Data for this region in particular should be 

used with caution because other areas within this 

region tend to have very hot summers, and residences 

use air conditioners, resulting in lower air exchange 

rates. The lowest rates generally occur in the colder 

regions during the fall. 

19.5.1.2.4.	 Diamond et al. (1996)—Ventilation 

and Infiltration in High-Rise 

Apartment Buildings 

Diamond et al. (1996) studied air flow in a 

13-story apartment building and concluded that “the 

ventilation to the individual units varies 

considerably.” With the ventilation system disabled, 

units at the lower level of the building had adequate 

ventilation only on days with high temperature 

differences, while units on higher floors had no 

ventilation at all. At times, units facing the windward 

side were over-ventilated. With the mechanical 

ventilation system operating, they found wide 

variation in the air flows to individual apartments. 

Diamond et al. (1996) also conducted a literature 

review and concluded there were little published data 

on air exchange in multifamily buildings, and that 

there was a general problem measuring, modeling, 

and designing ventilation systems for high-rise 

multifamily buildings. Air flow was dependent upon 

building type, occupation behavior, unit location, and 

meteorological conditions. 

19.5.1.2.5.	 Graham et al. (2004)—Contribution 

of Vehicle Emissions From an 

Attached Garage to Residential 

Indoor Air Pollution Levels 

There have been several studies of vehicle 

emission seepage into homes from attached garages, 

which examined a single home. Graham et al. (2004) 

conducted a study of vehicle emission seepage of 

16 homes with attached garages. On average, 11% of 

total house leakage was attributed to the house/garage 

interface (equivalent to an opening of 124 cm2

), but 

this varied from 0.6 to 29.6%. The amount of 

in-house chemical concentrations attributed to 

vehicle emissions from the garage varied widely 

between homes from 9 to 85%. Greater leakage 

tended to occur in houses where the garage attached 

to the house on more than one side. The home’s age 

was not an important factor. Whether the engine was 

warm or cold when it was started was important 

because cold-start emissions are dominated by the 

by-products of incomplete combustion. Cold-start tail 

pipe emissions were 32 times greater for carbon 

monoxide (CO), 10 times greater for nitrogen oxide 

(NOx), and 18 times greater for total hydrocarbon 

emissions than hot-start tailpipe emissions. 

19.5.1.2.6.	 Price et al. (2006)—Indoor-Outdoor 

Air Leakage of Apartments and 

Commercial Buildings 

Price et al. (2006) compiled air exchange rate 

data from 14 different studies on apartment buildings 

in the United States and Canada. The authors found 

that indoor-outdoor air exchange rates seem to be 

twice as high for apartments as for single-family 

houses. The observed apartment air exchange rates 

ranged from 0.5 to 2 ACH. 

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Chapter 19—Building Characteristics 

19.5.1.2.7.	 Yamamoto et al. (2010)—Residential 

Air Exchange Rates in Three U.S. 

Metropolitan Areas: Results From 

the Relationship Among Indoor, 

Outdoor, and Personal Air Study 

1999–2001 

Between 1999 and 2001, Yamamoto et al. (2010) 

conducted approximately 500 indoor-outdoor air 

exchange rate (AER) calculations based on 

residences in metropolitan Elizabeth, NJ; Houston, 

TX; and Los Angeles, CA. The median AER across 

these urban areas was 0.71 ACH; 0.87 in CA, 0.88 in 

NJ, and 0.47 in TX. In Texas, the measured AERs 

were lower in the summer cooling season 

(median = 0.37 ACH) than in the winter heating 

season (median = 0.63 ACH), likely because of the 

reported use of room air conditioners. The measured 

AERs in California were higher in summer 

(median = 1.13 ACH) than in winter

(median = 0.61 ACH) because summers in Los 

Angeles County are less humid than NJ or TX, and 

residents are more likely to utilize natural ventilation 

through open windows and screened doors. In New 

Jersey, air exchange rates in the heating and cooling 

seasons were similar. 

19.5.1.3.	 Key Study of Non-Residential Air 

Exchange Rates 

19.5.1.3.1.	 Turk et al. (1987)—Commercial 

Building Ventilation Rates and 

Particle Concentrations 

Few air exchange rates for commercial buildings 

are provided in the literature. Turk et al. (1987) 

conducted indoor air quality measurements, including 

air exchange rates, in 38 commercial buildings. The 

buildings ranged in age from 0.5 to 90 years old. 

One test was conducted in 36 buildings, and two tests 

were conducted in 2 buildings. Each building was 

monitored for 10 working days over a 2-week period 

yielding a minimum sampling time of 75 hours per 

building. Researchers found an average ventilation 

measurement of 1.5 ACH, which ranged from 0.3 to 

4.1 ACH with a standard deviation of 0.87. 

Table 19-27 presents the results by building type. 

19.5.2. Indoor Air Models 

Achieving adequate indoor air quality in a nonresidential building can be challenging. There are 

many factors that affect indoor air quality in 

buildings (e.g., building materials, outdoor 

environment, ventilation systems, operation and 

maintenance, occupants and their activities). Indoor 

air models are typically used to study, identify, and 

solve problems involving indoor air quality in 

buildings, as well as to assess efficiency of energy 

use. Indoor air quality models generally are not 

software products that can be purchased as "off-theshelf" items. Most existing software models are 

research tools that have been developed for specific 

purposes and are being continuously refined by 

researchers. Leading examples of indoor air models 

implemented as software products are as follows: 

 CONTAM 3.0—CONTAM was developed at 

the National Institute of Standards and 

Technology (NIST) with support from 

U.S. EPA and the U.S. DOE. Version 3.0 was 

sponsored by the Naval Surface Warfare 

Center Dahlgren Division. (Walton and Dols, 

2010; Wang et al., 2010; Axley, 1988). 

 IAQX—The Indoor Air Quality and Inhalation 

Exposure model is a Windows-based 

simulation software package developed by 

U.S. EPA (Guo, 2000). 

 CPIEM—The California Population Indoor 

Exposure Model was developed for the 

California Air Resources Board (Rosenbaum 

et al., 2002). 

 TEM—The Total Exposure Model was 

developed with support from U.S. EPA and 

the U.S. Air Force (Wilkes and Nuckols, 

2000; Wilkes, 1998). 

 RISK—RISK was developed by the Indoor 

Environment Management Branch of the 

U.S. EPA National Risk Management 

Research Laboratory (Sparks, 1997). 

 TRIM—The Total Risk Integrated

Methodology is an ongoing modeling project 

of U.S. EPA’s Office of Air Quality Planning 

and Standards (Efroymson and Murphy, 2001; 

Palma et al., 1999). 

 TOXLT/TOXST—The Toxic Modeling

System Long-Term was developed along with 

the release of the new version of the 

U.S. EPA’s Industrial Source Complex 

Dispersion Models (U.S. EPA, 1995). 

 MIAQ—The Multi-Chamber Indoor Air 

Quality Model was developed for the 

California Institute of Technology and 

Lawrence Berkeley National Laboratory. 

Documentation last updated in 2002. 

(Nazaroff and Cass, 1989b, 1986). 

 MCCEM—the Multi-Chamber Consumer 

Exposure Model was developed for U.S. 

EPA Office of Pollution Prevention and 

Toxics (EPA/OPPT) (Koontz and Nagda, 

1991; GeoMet, 1989). 

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Price (2001) is an evaluation of the use of many 

of the above products (TOXLT/TOXST, MCCEM, 

IAQX, CONTAM, CPIEM, TEM, TRIM, and RISK) 

in a tiered approach to assessing exposures and risks 

to children. The information provided is also 

applicable to adults. 

19.5.3. Infiltration Models 

A variety of mathematical models exist for 

prediction of air infiltration rates in individual 

buildings. A number of these models have been 

reviewed, for example, by Liddament and Allen 

(1983), and by Persily and Linteris (1983). Basic 

principles are concisely summarized in the ASHRAE 

Handbook of Fundamentals (ASHRAE, 2009). These 

models have a similar theoretical basis; all address 

indoor-outdoor pressure differences that are 

maintained by the actions of wind and stack 

(temperature difference) effects. The models 

generally incorporate a network of airflows where 

nodes representing regions of different pressure are 

interconnected by leakage paths. Individual models 

differ in details such as the number of nodes they can 

treat or the specifics of leakage paths (e.g., individual 

components such as cracks around doors or windows 

versus a combination of components such as an entire 

section of a building). Such models are not easily 

applied by exposure assessors, however, because the 

required inputs (e.g., inferred leakage areas, crack 

lengths) for the model are not easy to gather. 

Another approach for estimating air infiltration 

rates is developing empirical models. Such models 

generally rely on the collection of infiltration 

measurements in a specific building under a variety 

of weather conditions. The relationship between the 

infiltration rate and weather conditions can then be 

estimated through regression analysis and is usually 

stated in the following form: 

A = a + b T n i −T 0 + cU	 (Eqn. 19-1) 

where: 

A = air infiltration rate (hours–1), 

Ti = indoor temperature (°C), 

To = outdoor temperature (°C), 

U = windspeed (m/second), 

n is an exponent with a value typically 

between 1 and 2, and 

a, b and c are parameters to be estimated. 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Relatively good predictive accuracy usually can 

be obtained for individual buildings through this 

approach. However, exposure assessors often do not 

have the information resources required to develop 

parameter estimates for making such predictions. 

A reasonable compromise between the

theoretical and empirical approaches has been

developed in the model specified by Dietz et al. 

(1986). The model, drawn from correlation analysis 

of environmental measurements and air infiltration 

data, is formulated as follows: 

 0.03  A = L0.006∆T U 1.5  (Eqn. 19-2)  C 

where: 

A = average ACH or infiltration rate, 

hours–1, 

L = generalized house leakiness factor 

(1 < L < 5), 

C = terrain sheltering factor (1 < C < 10), 

ΔT = indoor-outdoor temperature difference 

(°C), and 

U = windspeed (m/second). 

The value of L is greater as house leakiness 

increases, and the value of C is greater as terrain 

sheltering (reflects shielding of nearby wind barrier) 

increases. Although the above model has not been 

extensively validated, it has intuitive appeal, and it is 

possible for the user to develop reasonable estimates 

for L and C with limited guidance. Historical data 

from various U.S. airports are available for

estimation of the temperature and windspeed

parameters. As an example application, consider a 

house that has central values of 3 and 5 for L and C, 

respectively. Under conditions where the indoor 

temperature is 20°C (68°F), the outdoor temperature 

is 0°C (32°F), and the windspeed is 5 m/second, the 

predicted infiltration rate for that house would be 3 

(0.006 × 20 + 0.03/5 × 51.5), or 0.56 ACH. This 

prediction applies under the condition that exterior 

doors and windows are closed and does not include 

the contributions, if any, from mechanical systems 

(see Section 19.3.3.4). Occupant behavior, such as 

opening windows, can, of course, overwhelm the 

idealized effects of temperature and wind speed. 

Chan et al. (2005) analyzed the U.S. Residential 

Air Leakage database at Lawrence Berkley National 

Laboratory (LBNL) containing 73,000 air leakage 

measurements from 30 states (predominantly Ohio, 

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19-18 September 2011 
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Chapter 19—Building Characteristics 

Alaska, and Wisconsin). They present the following 

equation for estimating ACH: 

 2.5 0.3  NL ACH = 48  −1  [h ] (Eqn. 19-3)  H  HF 

where: 

ACH = air changes per hour, 

H = building height (meters),
 

NL = normalized leakage (unitless),
 

F = scaling factor (unitless), and
 

h = hours.
 

Chan et al. (2005) found that “older and smaller 

homes are more likely to have higher normalized 

leakage areas than newer and larger ones.” 

Table 19-28 summarizes the normalized leakage 

distributions in the United States. 

It should be noted that newer homes were 

generally built tighter until about 1997 when the 

construction trend leveled off. Sherman and Matson 

(2002) also examined LBNL’s U.S. Residential Air 

Leakage database and found that average normalized 

leakage for 22,000 houses already in the database 

was 1.18 NL (total leakage cm2 normalized for 

dwelling size m2

), but leakage among the 

8,700 newer homes averaged 0.30 NL. 

19.5.4. Vapor Intrusion 

In 1998, concerns about subsurface 

contamination of soil or ground water impacting 

indoor air quality led the U.S. EPA to develop a series 

of models for estimating health risks from subsurface 

vapor intrusion into buildings based on the analytical 

solutions of Johnson and Ettinger (1991). Since that 

time, the models have been revised, and new models 

have been added. The 3-phase soil contamination 

models theoretically partition the contamination into 

three discrete phases: (1) in solution with water, 

(2) sorbed to the soil organic carbon, and (3) in vapor 

phase within the air-filled pores of the soil. Two new 

models have been added, allowing the user to 

estimate vapor intrusion into buildings from 

measured soil gas data. When Non-Aqueous Phase 

Liquid (NAPL) is present in soils, the contamination 

includes a fourth or residual phase. In such cases, the 

new NAPL models can be used to estimate the rate of 

vapor intrusion into buildings and the associated 

health risks. The new NAPL models use a numerical 

approach for simultaneously solving the 

time-averaged soil and building vapor concentration 

for each of up to 10 soil contaminants. This involves 

a series of iterative calculations for each contaminant. 

These models are available online from U.S. EPA at 

http://www.epa.gov/oswer/riskassessment/airmodel/ 

johnson_ettinger.htm. 

19.5.5. Deposition and Filtration 

Deposition refers to the removal of airborne

substances to available surfaces that occurs as a result 

of gravitational settling and diffusion, as well as 

electrophoresis and thermophoresis. Filtration is

driven by similar processes but is confined to

material through which air passes. Filtration is

usually a matter of design, whereas deposition is a 

matter of fact. 

19.5.5.1. Deposition 

The deposition of particulate matter and reactive 

gas-phase pollutants to indoor surfaces is often stated 

in terms of a characteristic deposition velocity

(m hour–1) allied to the surface-to-volume ratio

(m2 m–3) of the building or room interior, forming a 

first order loss rate (hour–1) similar to that of air 

exchange. Theoretical considerations specific to

indoor environments have been summarized in

comprehensive reviews by Nazaroff and Cass

(1989a) and Nazaroff et al. (1993). 

For airborne particles, deposition rates depend on 

aerosol properties (size, shape, density) as well as 

room factors (thermal gradients, turbulence, surface 

geometry). The motions of larger particles are

dominated by gravitational settling; the motions of 

smaller particles are subject to convection and

diffusion. Consequently, larger particles tend to

accumulate more rapidly on floors and up-facing 

surfaces while smaller particles may accumulate on 

surfaces facing in any direction. Figure 19-3 

illustrates the general trend for particle deposition 

across the size range of general concern for

inhalation exposure (<10 μm). The current thought is 

that theoretical calculations of deposition rates are 

likely to provide unsatisfactory results due to

knowledge gaps relating to near-surface air motions 

and other sources of inhomogeneity (Nazaroff et al., 

1993). 

19.5.5.1.1.	 Thatcher and Layton (1995)— 

Deposition, Resuspension, and 

Penetration of Particles Within a 

Residence 

Thatcher and Layton (1995) evaluated removal 

rates for indoor particles in four size ranges (1–5, 

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5-10, 10–25, and >25 μm) in a study of one house 

occupied by a family of four. Table 19-29 lists these 

values. In a subsequent evaluation of data collected in 

100 Dutch residences, Layton and Thatcher (1995) 

estimated settling velocities of 2.7 m hour–1 for leadbearing particles captured in total suspended 

particulate matter samples. 

19.5.5.1.2.	 Wallace (1996)—Indoor Particles: A 

Review 

In a major review of indoor particles, Wallace 

(1996) cited overall particle deposition per hour 

(hour–1) for respirable (PM2.5), inhalable (PM10), and 

coarse (difference between PM10 and PM2.5) size 

fractions determined from U.S. EPA’s Particle Total 

Exposure Assessment Methodological Study 

(PTEAM) study. These values, listed in Table 19-30, 

were derived from measurements conducted in nearly 

200 residences. 

19.5.5.1.3.	 Thatcher et al. (2002)—Effects of 

Room Furnishings and Air Speed on 

Particle Deposition Rates Indoors 

Thatcher et al. (2002) measured deposition loss 

rate coefficients for particles of different median 

diameters (0.55 to 8.66 mm) with fans off and on at 

various airspeeds in three types of experimental 

rooms: (1) bare (unfurnished with metal floor), 

(2) carpeted and unfurnished, and (3) fully furnished. 

They concluded that large particles (over 25 μm) 

settle eight times faster than small particles (1–5 μm). 

Table 19-31 summarizes the results. 

19.5.5.1.4.	 He et al. (2005)—Particle Deposition 

Rates in Residential Houses 

He et al. (2005) investigated particle deposition 

rates for particles ranging in size from 0.015 to 6 μm. 

The lowest deposition rates were found for particles 

between 0.2 and 0.3 μm for both minimum (air

exchange rate: 0.61 ± 0.45 hour−1) and normal (air 

exchange rate: 3.00 ± 1.23 hour−1) conditions. Thus, 

air exchange rate was an important factor affecting 

deposition rates for particles between 0.08 and 

1.0 μm, but not for particles smaller than 0.08 μm or

larger than 1.0 μm.

19.5.5.2. Filtration 

A variety of air cleaning techniques have been 

applied to residential settings. Basic principles related 

to residential-scale air cleaning technologies have 

been summarized in conjunction with reporting early 

test results (Offermann et al., 1984). General 

engineering principles are summarized in ASHRAE 

(1988). In addition to fibrous filters integrated into 

central heating and air conditioning systems, 

extended surface filters and High Efficiency Particle 

Arrest filters, as well as electrostatic systems, are 

available to increase removal efficiency. 

Free-standing air cleaners (portable and/or console) 

are also being used. Product-by-product test results 

reported by Hanley et al. (1994); Shaughnessy et al. 

(1994); and Offerman et al. (1984) exhibit 

considerable variability across systems, ranging from 

ineffectual (<1% efficiency) to nearly complete 

removal. 

19.5.6. Interzonal Airflows 

Residential structures consist of a number of 

rooms that may be connected horizontally, vertically, 

or both horizontally and vertically. Before 

considering residential structures as a detailed 

network of rooms, it is convenient to divide them into 

one or more zones. At a minimum, each floor is 

typically defined as a separate zone. For indoor air 

exposure assessments, further divisions are 

sometimes made within a floor, depending on 

(1) locations of specific contaminant sources and 

(2) the presumed degree of air communication among 

areas with and without sources. 

Defining the airflow balance for a multiple-zone 

exposure scenario rapidly increases the information 

requirements as rooms or zones are added. As shown 

in Figure 19-4, a single-zone system (considering the 

entire building as a single well-mixed volume) 

requires only two airflows to define air exchange. 

Further, because air exchange is balanced flow (air 

does not "pile up" in the building, nor is a vacuum 

formed), only one number (the air exchange rate) is 

needed. With two zones, six airflows are needed to 

accommodate interzonal airflows plus air exchange; 

with three zones, 12 airflows are required. In some 

cases, the complexity can be reduced using judicious 

(if not convenient) assumptions. Interzonal airflows 

connecting non-adjacent rooms can be set to zero, for 

example, if flow pathways do not exist. Symmetry 

also can be applied to the system by assuming that 

each flow pair is balanced. 

Examples of interzonal airflow models include 

CONTAM (developed by NIST) and COMIS (Feustel 

and Raynor-Hoosen, 1990). 

19.5.7. House Dust and Soil Loadings 

House dust is a complex mixture of biologically 

derived material (animal dander, fungal spores, etc.), 

particulate matter deposited from the indoor aerosol, 

and soil particles brought in by foot traffic. House 

dust may contain VOCs (Hirvonen et al., 1994; 

Wolkoff and Wilkins, 1994), pesticides from 

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imported soil particles as well as from direct 

applications indoors (Roberts et al., 1991), and trace 

metals derived from outdoor sources (Layton and 

Thatcher, 1995). The indoor abundance of house dust 

depends on the interplay of deposition from the 

airborne state, resuspension due to various activities, 

direct accumulation, and infiltration. 

In the absence of indoor sources, indoor 

concentrations of particulate matter are significantly 

lower than outdoor levels. For some time, this 

observation supported the idea that a significant 

fraction of the outdoor aerosol is filtered out by the 

building envelope. More recent data, however, have 

shown that deposition (incompletely addressed in 

earlier studies) accounts for the indoor-outdoor 

contrast, and outdoor particles smaller than 10-μm 

aerodynamic diameter penetrate the building 

envelope as completely as non-reactive gases 

(Wallace, 1996). 

It should be noted that carpet dust loadings may 

be higher than previously believed. This is important 

because embedded dust is a reservoir for organic 

compounds. Fortune et al. (2000) compared the mass 

of dust in carpets removed using conventional 

vacuuming to that removed by vacuuming with a 

beater-bar to remove deeply embedded dust. The 

amount removed was 10 times that removed by 

conventional vacuuming. 

19.5.7.1.	 Roberts et al. (1991)—Development and 

Field Testing of a High-Volume Sampler 

for Pesticides and Toxics in Dust 

Dust loadings, reported by Roberts et al. (1991), 

were measured in conjunction with the 

Non-Occupational Pesticide Exposure Study 

(NOPES). In this study, house dust was sampled from 

a representative grid using a specially constructed 

high-volume surface sampler. The surface sampler 

collection efficiency was verified in conformance 

with ASTM F608 (ASTM, 1989). Table 19-32 

summarizes data collected from carpeted areas in 

volunteer households in Florida encountered during 

the course of NOPES. Seven of the nine sites were 

single-family detached homes, and two were mobile 

homes. The authors noted that the two houses 

exhibiting the highest dust loadings were only those 

homes where a vacuum cleaner was not used for 

housekeeping. 

19.5.7.2.	 Thatcher and Layton (1995)— 

Deposition, Resuspension, and 

Penetration of Particles Within a 

Residence 

Relatively few studies have been conducted at 

the level of detail needed to clarify the dynamics of 

indoor aerosols. One intensive study of a California 

residence (Thatcher and Layton, 1995), however, 

provides instructive results. Using a model-based 

analysis for data collected under controlled 

circumstances, the investigators verified penetration 

of the outdoor aerosol and estimated rates for particle 

deposition and resuspension (see Table 19-33). The 

investigators stressed that normal household activities 

are a significant source of airborne particles larger 

than 5 μm. During the study, they observed that just 

walking into and out of a room could momentarily 

double the concentration. The airborne abundance of 

submicrometer particles, on the other hand, was 

unaffected by either cleaning or walking. 

Mass loading of floor surfaces (see Table 19-34) 

was measured in the study of Thatcher and Layton 

(1995) by thoroughly cleaning the house and 

sampling accumulated dust, after 1 week of normal 

habitation and no vacuuming. The methodology, 

validated under ASTM F608 (ASTM, 1989), showed 

fine dust recovery efficiencies of 50% with new 

carpet and 72% for linoleum. Tracked areas showed 

consistently higher accumulations than untracked 

areas, confirming the importance of tracked-in 

material. Differences between tracked areas upstairs 

and downstairs show that tracked-in material is not 

readily transported upstairs. The consistency of 

untracked carpeted areas throughout the house, 

suggests that, in the absence of tracking, particle 

transport processes are similar on both floors. 

19.6.	 CHARACTERIZING INDOOR 

SOURCES 

Product- and chemical-specific mechanisms for 

indoor sources can be described using simple 

emission factors to represent instantaneous releases, 

as well as constant releases over defined time 

periods; more complex formulations may be required 

for time-varying sources. Guidance documents for 

characterizing indoor sources within the context of 

the exposure assessment process are limited [see, for 

example, U.S. EPA (1987); Wolkoff (1995)]. Fairly 

extensive guidance exists in the technical literature, 

however, provided that the exposure assessor has the 

means to define (or estimate) key mechanisms and 

chemical-specific parameters. Basic concepts are 

summarized below for the broad source categories 

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Chapter 19—Building Characteristics 

that relate to airborne contaminants, waterborne 

contaminants, and for soil/house dust indoor sources. 

19.6.1.	 Source Descriptions for Airborne 

Contaminants 

Table 19-35 summarizes simplified indoor 

source descriptions for airborne chemicals for direct 

emission sources (e.g., combustion, pressurized 

propellant products), as well as emanation sources 

(e.g., evaporation from “wet” films, diffusion from 

porous media), and transport-related sources (e.g., 

infiltration of outdoor air contaminants, soil gas 

entry). 

Direct-emission sources can be approximated 

using simple formulas that relate pollutant mass 

released to characteristic process rates. Combustion 

sources, for example, may be stated in terms of an 

emission factor, fuel content (or heating value), and 

fuel consumption (or carrier delivery) rate. Emission 

factors for combustion products of general concern 

(e.g., CO, NOx) have been measured for a number of 

combustion appliances using room-sized chambers 

[see, for example, Relwani et al. (1986)]. Other 

direct-emission sources would include volatiles 

released from water use and from pressurized 

consumer products. Resuspension of house dust (see 

Section 19.5.5.1) would take on a similar form by 

combining an activity-specific rate constant with an 

applicable dust mass. 

Diffusion-limited sources (e.g., carpet backing, 

furniture, flooring, dried paint) represent probably the 

greatest challenge in source characterization for 

indoor air quality. Vapor-phase organics dominate 

this group, offering great complexity because 

(1) there is a fairly long list of chemicals that could 

be of concern, (2) ubiquitous consumer products, 

building materials, coatings, and furnishings contain 

varying amounts of different chemicals, (3) source 

dynamics may include non-linear mechanisms, and 

(4) for many of the chemicals, emitting as well as 

non-emitting materials evident in realistic settings 

may promote reversible and irreversible sink effects. 

Very detailed descriptions for diffusion-limited 

sources can be constructed to link specific properties 

of the chemical, the source material, and the 

receiving environment to calculate expected behavior 

[see, for example, U.S. EPA (1990a); Cussler (1984)]. 

Validation to actual circumstances, however, suffers 

practical shortfalls because many parameters simply 

cannot be measured directly. 

The exponential formulation listed in

Table 19-35 was derived based on a series of papers 

generated during the development of chamber testing 

methodology by U.S. EPA (Dunn and Chen, 1993; 

Dunn and Tichenor, 1988; Dunn, 1987). This 

framework represents an empirical alternative that 

works best when the results of chamber tests are 

available. Estimates for the initial emission rate (Eo) 

and decay factor (ks) can be developed for 

hypothetical sources from information on pollutant 

mass available for release (M) and supporting 

assumptions. 

Assuming that a critical time period (tc) 

coincides with reduction of the emission rate to a 

critical level (Ec) or with the release of a critical 

fraction of the total mass (Mc), the decay factor can 

be estimated by solving either of these relationships: 

Ec	 = e	 

−kstc (Eqn. 19-4) E0 

where: 

Ec	 = emission rate to a critical level 

(μg hour

–1), 

E0	 = initial emission rate (μg hour

–1), 

ks	 = decay factor (μg hour

–1), and 

tc	 = critical time period (hours), 

or 

Mc = 1− e−kst 	 c (Eqn. 19-5) M 

where: 

Mc = critical mass (μg), and 

M = total mass (μg). 

The critical time period can be derived from 

product-specific considerations (e.g., equating drying 

time for paint to 90% emissions reduction). Given 

such an estimate for ks, the initial emission rate can 

be estimated by integrating the emission formula to 

infinite time under the assumption that all chemical 

mass is released: 

∞ E

M = ∫ E − 0

0 e kst dt = (Eqn. 19-6) 

0	 ks 

The basis for the exponential source algorithm 

has also been extended to the description of more 

complex diffusion-limited sources. With these 

sources, diffusive or evaporative transport at the 

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19-22 September 2011 
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Chapter 19—Building Characteristics 

interface may be much more rapid than diffusive 

transport from within the source material, so that the 

abundance at the source/air interface becomes 

depleted, limiting the transfer rate to the air. Such 

effects can prevail with skin formation in "wet" 

sources like stains and paints [see, for example, 

Chang and Guo (1992)]. Similar emission profiles 

have been observed with the emanation of 

formaldehyde from particleboard with "rapid" decline 

as formaldehyde evaporates from surface sites of the 

particleboard over the first few weeks. It is then 

followed by a much slower decline over ensuing 

years as formaldehyde diffuses from within the 

matrix to reach the surface [see, for example, Zinn 

et al. (1990)]. 

Transport-based sources bring contaminated air 

from other areas into the airspace of concern. 

Examples include infiltration of outdoor 

contaminants, and soil gas entry. Soil gas entry is a 

particularly complex phenomenon and is frequently 

treated as a separate modeling issue (Sextro, 1994; 

Little et al., 1992). Room-to-room migration of 

indoor contaminants would also fall under this 

category, but this concept is best considered using 

multi-zone models. 

19.6.2.	 Source Descriptions for Waterborne 

Contaminants 

Residential water supplies may be a route for 

exposure to chemicals through ingestion, dermal 

contact, or inhalation. These chemicals may appear in 

the form of contaminants (e.g., trichloroethylene) as 

well as naturally occurring by-products of water 

system history (e.g., chloroform, radon). Among 

indoor water uses, showering, bathing, and handwashing of dishes or clothes provide the primary 

opportunities for dermal exposure. The escape of 

volatile chemicals to the gas phase associates water 

use with inhalation exposure. The exposure potential 

for a given chemical will depend on the source of 

water, the types and extents of water uses, and the 

extent of volatilization of specific chemicals. Primary 

types of residential water use include 

showering/bathing, toilet use, clothes washing, 

dishwashing, and faucet use (e.g., for drinking, 

cooking, general cleaning, or washing hands). 

Upper-bounding estimates of chemical release 

rates from water use can be formulated as simple 

emission factors by combining the concentration in 

the feed water (g m–3) with the flow rate for the water 

use (m3 hour–1), and assuming that the chemical 

escapes to the gas phase. For some chemicals, 

however, not all of the chemical escapes in realistic 

situations due to diffusion-limited transport and 

solubility factors. For inhalation exposure estimates, 

this may not pose a problem because the bounding 

estimate would overestimate emissions by no more 

than approximately a factor of two. For multiple 

exposure pathways, the chemical mass remaining in 

the water may be of importance. Refined estimates of 

volatile emissions are usually considered under 

two-resistance theory to accommodate mass transport 

aspects of the water-air system ([see, for example, 

U.S. EPA (2000); Howard-Reed et al. (1999); Moya 

et al. (1999); Little (1992); Andelman (1990); 

McKone (1987)]. More detailed descriptions of 

models used to estimate emissions from indoor water 

sources including showers, bathtubs, dishwashers, 

and washing machines are included in U.S. EPA 

(2000). Release rates (S) are formulated as 

 C  S = Km Fw w − a

C  (Eqn. 19-7)  H 

 

where: 

S = chemical release rate (g hour–1), 

Km = dimensionless mass-transfer 

coefficient, 

Fw = water flow rate (m3 hour–1), 

Cw = concentration in feed water (g m–3), 

Ca = concentration in air (g m–3), and 

H = dimensionless Henry’s Law 

constant. 

Because the emission rate is dependent on the air 

concentration, recursive techniques are required. The 

mass-transfer coefficient is a function of water use 

characteristics (e.g., water droplet size spectrum, fall 

distance, water film) and chemical properties 

(diffusion in gas and liquid phases). Estimates of 

practical value are based on empirical tests to 

incorporate system characteristics into a single 

parameter [see, for example, Giardino et al. (1990)]. 

Once characteristics of one chemical-water use 

system are known (reference chemical, subscript r), 

the mass-transfer coefficient for another chemical 

(index chemical, subscript i) delivered by the same 

system can be estimated using formulations identified 

in the review by Little (1992): 

1  D

 Li 

1/2 

1  = K  D Lr  KLr 

2/3 1/2 

1 1  D   D  = −  Gr Li    KGr H  D Gi   DLr 

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September 2011 19-23 
 

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Chapter 19—Building Characteristics 

(Eqn. 19-8) 

where: 

DL = liquid diffusivity (m2 second–1), 

DG = gas diffusivity (m2 second–1), 

KL = liquid-phase mass-transfer 

coefficient, 

KG = gas-phase mass transfer coefficient, 

and 

H = dimensionless Henry’s Law 

constant. 

19.6.3. Soil and House Dust Sources 

The rate process descriptions compiled for soil 

and house dust provide inputs for estimating indoor 

emission rates: 

Sd = M d Rd Af (Eqn. 19-9) 

where: 

S = dust e ion (g hour

–1 d miss ), 

M = dust mass loading (g m–2 d ), 

Rd = resuspension rates (hour

–1), and 

Af = floor area (m2

). 

Because house dust is a complex mixture, 

transfer of particle-bound constituents to the gas 

phase may be of concern for some exposure 

assessments. For emission estimates, one would then 

need to consider particle mass residing in each 

reservoir (dust deposit, airborne). 

19.7. ADVANCED CONCEPTS 

19.7.1. Uniform Mixing Assumption 

Many exposure measurements are predicated on 

the assumption of uniform mixing within a room or 

zone of a house. Mage and Ott (1994) offer an 

extensive review of the history of use and misuse of 

the concept. Experimental work by Baughman et al. 

(1994) and Drescher et al. (1995) indicates that, for 

an instantaneous release from a point source in a 

room, fairly complete mixing is achieved within 

10 minutes when convective flow is induced by solar 

radiation. However, up to 100 minutes may be 

required for complete mixing under quiescent (nearly 

isothermal) conditions. While these experiments were 

conducted at extremely low air exchange rates 

(<0.1 ACH), based on the results, attention is focused 

on mixing within a room. 

The situation changes if a human invokes a point 

source for a longer period and remains in the 

immediate vicinity of that source. Personal exposure 

in the near vicinity of a source can be much higher 

than the well-mixed assumption would suggest. A 

series of experiments conducted by GeoMet (1989) 

for the U.S. EPA involved controlled point-source 

releases of carbon monoxide tracer (CO), each for 

30 minutes. Breathing-zone measurements located 

within 0.4 m of the release point were 10 times 

higher than for other locations in the room during 

early stages of mixing and transport. 

Similar investigations conducted by Furtaw et al. 

(1995) involved a series of experiments in a 

controlled-environment, room-sized chamber. Furtaw 

et al. (1995) studied spatial concentration gradients 

around a continuous point source simulated by sulfur 

hexafluoride (SF6) tracer with a human moving about 

the room. Average breathing-zone concentrations 

when the subject was near the source exceeded those 

several meters away by a factor that varied inversely 

with the ventilation intensity in the room. At typical 

room ventilation rates, the ratio of source-proximate 

to slightly-removed concentration was on the order of 

2:1. 

19.7.2. Reversible Sinks 

For some chemicals, the actions of reversible 

sinks are of concern. For an initially “clean” 

condition in the sink material, sorption effects can 

greatly deplete indoor concentrations. However, once 

enough of the chemical has been adsorbed, the 

diffusion gradient will reverse, allowing the chemical 

to escape. For persistent indoor sources, such effects 

can serve to reduce indoor levels initially, but once 

the system equilibrates, the net effect on the average 

concentration of the reversible sink is negligible. 

Over suitably short time frames, this can also affect 

integrated exposure. For indoor sources whose 

emission profile declines with time (or ends 

abruptly), reversible sinks can serve to extend the 

emissions period as the chemical desorbs long after 

direct emissions are finished. Reversible sink effects 

have been observed for a number of chemicals in the 

presence of carpeting, wall coverings, and other 

materials commonly found in residential 

environments. 

Interactive sinks (and models of the processes) 

are of special importance; while sink effects can 

greatly reduce indoor air concentrations, re-emission 

at lower rates over longer time periods could greatly 

extend the exposure period of concern. For 

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Chapter 19—Building Characteristics 

completely reversible sinks, the extended time could 

bring the cumulative exposure to levels approaching 

the sink-free case. Publications (Axley and 

Lorenzetti, 1993; Tichenor et al., 1991) show that 

first principles provide useful guidance in postulating 

models and setting assumptions for reversibleirreversible sink models. Sorption/desorption can be 

described in terms of Langmuir (monolayer) as well 

as Brunauer-Emmet-Teller (BET, multilayer) 

adsorption. 

19.8. REFERENCES FOR CHAPTER 19 

Andelman, JB. (1990). Total exposure to volatile 

organic compounds in potable water. In NM 

Ram; RF Christman; KP Cantor (Eds.), 

Significance and treatment of volatile 

organic compounds in water supplies (pp. 

485–504). Chelsea, MI: Lewis Publishers. 

Andersson, B; Andersson, K; Sundell, J; Zingmark, 

PA. (1993). Mass transfer of contaminants in 

rotary enthalpy exchangers. Indoor Air 3: 

143-148. 

ASHRAE (American Society of Heating, 

Refrigerating and Air-Conditioning 

Engineers Inc.). (1988). [Excerpts from the 

1988 Equipment Handbook]. In 1988 

ASHRAE Handbook: Equipment. Atlanta, 

GA: American Society of Heating, 

Refrigerating and Air-Conditioning 

Engineers Inc. 

ASHRAE (American Society of Heating, 

Refrigerating and Air-Conditioning 

Engineers Inc.). (2009). The 2009 ASHRAE 

Handbook-Fundamentals. Atlanta, GA: 

American Society of Heating, Refrigerating 

and Air-Conditioning Engineers Inc. 

http://www.ashrae.org/publications/page/228 

3. 

ASTM (American Society for Testing and Materials). 

(1989). Standard laboratory test method for 

evaluation of carpet-embedded dirt removal 

effectiveness of household vacuum cleaners 

[Standard]. (Standard F 608-89). 

Philadelphia, PA. 

ASTM (American Society for Testing and Materials). 

(1990). Standard test method for 

determining formaldehyde levels from wood 

products under defined conditions using a 

large chamber [Standard]. (Standard E 1333 

90). Philadelphia, PA. 

Axley, JW. (1988). Progress toward a general 

analytical method for predicting indoor air 

pollution in buildings: Indoor air quality 

modeling phase III report. (NBSIR 88­

3814). Gaitherberg, MD: National Bureau of 

Standards. 

Axley, JW. (1989). Multi-zone dispersal analysis by 

element assembly. Build Environ 24: 113­

130. http://dx.doi.org/10.1016/0360­

1323(89)90001-2. 

Axley, JW; Lorenzetti, D. (1993). Sorption transport 

models for indoor air quality analysis. In NL 

Nagda (Ed.), Modeling of indoor air quality 

and exposure (pp. 105-127). Philadelphia, 

PA: American Society for Testing and 

Materials. 

Baughman, AV; Gadgil, AJ; Nazaroff, WW. (1994). 

Mixing of a point source pollutant by natural 

convection flow within a room. Indoor Air 

4: 114-122. http://dx.doi.org/10.1111/j.1600­

0668.1994.t01-2-00006.x. 

Chan, WR; Nazaroff, WW; Price, PN; Sohn, MD; 

Gadgil, AJ. (2005). Analyzing a database of 

residential air leakage in the United States. 

Atmos Environ 39: 3445-3455. 

Chang, J; Guo, Z. (1992). Characterization of organic 

emissions from a wood finishing product– 

wood stain. Indoor Air 2: 146-153. 

Cussler, EL. (1984). Diffusion: Mass transfer in fluid 

systems. Cambridge, UK: Cambridge 

University Press. 

Diamond, RC; Feustel, HE; Dickerhoff, DJ. (1996). 

Ventilation and infiltration in high-rise 

apartment buildings. (LBL-38103). 

Berkeley, CA: University of California 

Berkeley, Lawrence Berkeley Laboratory. 

Dietz, RN; Goodrich, RW; Cote, EA; Wieser, RF. 

(1986). Detailed description and 

performance of a passive perfluorocarbon 

tracer system for building ventilation and air 

exchange measurements. In Measured air 

leakage of buildings: A symposium (pp. 

203–264). (ASTM STP 904). Philadelphia, 

PA: American Society for Testing and 

Materials. 

DOE (U.S. Department of Energy). (2008a). 

Residential Energy Consumption Survey 

(RECS). (DOE/EIA-0314(93)). Washington, 

DC: U.S. Department of Energy, Energy 

Information Administration. 

DOE (U.S. Department of Energy). (2008b). U.S. 

EPA analysis of survey data. Commercial 

buildings energy consumption survey 

(CBECS). Form EIA-871A. 

Drescher, A; Lobascio, C; Gadgil, A; Nazarofif, W. 

(1995). Mixing of a Point Source Indoor 

Pollutant by Forced Convection. Indoor Air 

5: 204-214. 

Exposure Factors Handbook Page
 

September 2011 19-25 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Dunn, JE. (1987). Models and statistical methods for 

gaseous emission testing of finite sources in 

well-mixed chambers. Atmos Environ 21: 

425-430. 

Dunn, JE; Chen, T. (1993). Critical evaluation of the 

diffusion hypothesis in the theory of porous 

media volatile organic compounds (VOC) 

sources and sinks. In Modeling of indoor air 

quality and exposure (pp. 64–80). (ASTM 

STP 1205). Philadelphia, PA: American 

Society for Testing and Materials. 

Dunn, JE; Tichenor, BA. (1988). Compensating for 

sink effects in emissions test chambers by 

mathematical modeling. 22: 885-894. 

http://dx.doi.org/10.1016/0004­

6981(88)90265-X. 

Efroymson, RA; Murphy, DL. (2001). Ecological risk 

assessment of multimedia hazardous air 

pollutants: Estimating exposure and effects. 

Sci Total Environ 274: 219-230. 

http://dx.doi.org/10.1016/S0048­

9697(01)00745-8. 

Emmerich, S; Gorfain, J; Howard-Reed, C. (2003). 

Air and Pollutant Transport from Attached 

Garages to Residential Living Spaces– 

Literature Review and Field Tests. Int J Vent 

2. 

Feustel, HE; Raynor-Hoosen, A. (1990). 

Fundamentals of the multizone airflow 

model COMIS. (Technical note AIVC 29). 

Coventry, UK: Air Infiltration and 

Ventilation Centre. 

Fortune, CR; Blanchard, FT; Elleson, WD; Lewis, 

RG. (2000). Analysis of aged in-home 

carpeting to determine the distribution of 

pesticide residues between dust, carpet, and 

pad compartments [EPA Report]. 

(EPA/600/R-00/030). Research Triangle 

Park, NC: U.S. Environmental Protection 

Agency. 

Furtaw, EJ; Pandian, MD; Nelson, DR; Behar, JV. 

(1995). Modeling indoor air concentrations 

near emission sources in perfectly mixed 

rooms: Engineering solutions to indoor air 

quality problems. Presentation presented at 

Sixth Conference of the International 

Society for Environmental Epidemiology 

and Fourth Conference of the International 

Society for Exposure Analysis (Joint 

Conference), September 1994, Research 

Triangle Park, NC. 

GeoMet (GeoMet Incorporated). (1989). Assessment 

of indoor air pollutant exposure within 

building zones. (IE-2149). Washinton, DC: 

U.S. Environmental Protection Agency. 

Giardino, NJ; Gumerman, E; Esmen, NA; Andelman, 

JB; Wilkes, CR; Small, MJ. (1990). Realtime air measurements of trichloroethylene 

in domestic bathrooms using contaminated 

water. 

Graham, LA; Noseworthy, L; Fugler, D; O'Leary, K; 

Karman, D; Grande, C. (2004). Contribution 

of vehicle emissions from an attached 

garage to residential indoor air pollution 

levels. J Air Waste Manag Assoc 54: 563­

584. 

Grimsrud, DT; Sherman, MH; Sonderegger, RC. 

(1983). Calculating infiltration: implications 

for a construction quality standard. 

Grot, RA; Clark, RE. (1979). Air leakage 

characteristics and weatherization 

techniques for low-income housing. 

Guo, Z, . (2000). Simulation tool kit for indoor air 

quality and inhalation exposure (IAQX) 

version 1.0 user's guide. (EPA-600/R00/094). RTP, NC: U.S. Environmental 

Protection Agency. 

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=P1000A0G.txt. 

Hanley,	 JT; Ensor, DS; Smith, DD; Sparks, LE. 

(1994). Fractional aerosol filtration 

efficiency of in-duct ventilation air cleaners. 

Indoor Air 4: 169-178. 

He, C; Morawska, L; Gilbert, D. (2005). Particle 

deposition rates in residential houses. Atmos 

Environ 39: 3891-3899. 

http://dx.doi.org/10.1016/j.atmosenv.2005.0 

3.016. 

Hirvonen, A; Pasanen, P; Tarhanen, J; Ruuskanen, J. 

(1994). Thermal desorption of organic 

compounds associated with settled 

household dust. Indoor Air 4: 255-264. 

Howard-Reed, C; Corsi, RL; Moya, J. (1999). Mass 

Transfer of Volatile Organic Compounds 

from Drinking Water to Indoor Air: The 

Role of Residential Dishwashers. Environ 

Sci Technol 33: 2266-2272. 

http://dx.doi.org/10.1021/es981354h. 

Johnson, PC; Ettinger, RA. (1991). Model for 

subsurface vapor intrusion into buildings. 

Washington, DC: U.S. Environmental 

Protection Agency. 

http://www.epa.gov/oswer/riskassessment/ai 

rmodel/johnson_ettinger.htm. 

Koontz, MD; Nagda, NL. (1991). A multichamber 

model for assessing consumer inhalation 

exposure. Indoor Air 1: 593-605. 

Koontz, MD; Rector, HE. (1995). Estimation of 

distributions for residential air exchange 

rates: Final report. Washington, DC: U.S. 

Page Exposure Factors Handbook 

19-26 September 2011 
Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Environmental Protection Agency, Office of 

Pollution Prevention and Toxics. 

Koontz, MD; Rector, HE; Fortmann, RC; Nagda, NL. 

(1988). Preliminary experiments in a 

research house to investigate contaminant 

migration in indoor air [EPA Report]. (EPA 

560/5-88/004). Washington, DC: U.S. 

Environmental Protection Agency. 

http://nepis.epa.gov/Adobe/PDF/P1003BBS. 

PDF. 

Layton, DW; Thatcher, TL. (1995). Movement of 

outdoor particles to the indoor environment: 

an analysis of the Arnhem lead study. 

Leaderer, BP; Schaap, L; Dietz, RN. (1985). 

Evaluation of the perfluorocarbon tracer 

technique for determining infiltration rates 

in residences. Environ Sci Technol 19: 1225­

1232. 

http://dx.doi.org/10.1021/es00142a015. 

Liddament, M; Allen, C. (1983). Validation and 

comparison of mathematical models of air 

infiltration. (Technical Note AIC 11). 

Coventry, UK: Air Infiltration and 

Ventilation Centre. 

Little, JC. (1992). Applying the two-resistance theory 

to contaminant volatilization in showers. 

Environ Sci Technol 26: 1341-1349. 

Little, JC; Daisey, JM; Nazaroff, WW. (1992). 

Transport of subsurface contaminants into 

buildings: An exposure pathway for volatile 

organics. Environ Sci Technol 26: 2058­

2066. 

http://dx.doi.org/10.1021/es00035a001. 

Lucas, RM; Grillo, RB; Perez-Michael, A; Kemp, S. 

(1992). National residential radon survey 

statistical analysis -- volume 2: Summary of 

the questionnaire data. (RTI/5158/49-2F). 

Research Triangle Park, NC: Research 

Triangle Institute. 

Mage, DT; Ott, WR. (1994). The correction for 

nonuniform mixing in indoor environments. 

In Papers from the ASTM Symposium on 

Characterizing Indoor Sources and Sink 

Effects. Washington, DC: American Society 

for Testing and Materials. 

McKone, TE. (1987). Human exposure to volatile 

organic compounds in household tap water: 

the indoor inhalation pathway. Environ Sci 

Technol 21: 1194-1201. 

Mckone, TE. (1989). Household exposure models. 

Toxicol Lett 49: 321-339. 

Moya, J; Howard-Reed, C; Corsi, RL. (1999). 

Volatilization of chemicals from tap water to 

indoor air from contaminated water used for 

showering. Environ Sci Technol 33: 2321­

2327. 

Murray, DM. (1997). Residential house and zone 

volumes in the United States: empirical and 

estimated parametric distributions. Risk 

Anal 17: 439-446. 

Murray, DM; Burmaster, DE. (1995). Residential air 

exchange rates in the United States: 

empirical and estimated parametric 

distributions by season and climatic region. 

Risk Anal 15: 459-465. 

Nazaroff, WW; Cass, GR. (1986). Mathematical 

modeling of chemically reactive pollutants 

in indoor air. Environ Sci Technol 20: 924­

934. 

Nazaroff, WW; Cass, GR. (1989a). Mass-transport 

aspects of pollutant removal at indoor 

surfaces. Environ Int 15: 567-584. 

http://dx.doi.org/10.1016/0160­

4120(89)90078-0. 

Nazaroff, WW; Cass, GR. (1989b). Mathematical 

modeling of indoor aerosol dynamics. 

Environ Sci Technol 23: 157-166. 

Nazaroff, WW; Doyle, SM; Nero, AV, Jr; Sextro, RG. 

(1988). Radon entry via potable water. In 

WW Nazaroff; AV Nero, Jr. (Eds.), Radon 

and its decay products in indoor air. New 

York, NY: John Wiley & Sons. 

Nazaroff, WW; Gadgil, AJ; Weschler, CJ. (1993). 

Critique of the use of deposition velocity in 

modeling indoor air quality. 

Offermann, FJ; Sextro, RG; Fisk, WJ; Nazaroff, 

WW; Nero, AV; Revzan, KL; Yater, J. 

(1984). Control of respirable particles and 

radon progeny with portable air cleaners. 

Offermann, FJ; Sextro, RG; Fisk, WJ; 

Nazaroff, WW; Nero, AV; Revzan, KL; 

Yater, J. 

Palma, T; Vasu, AB; Hetes, RG. (1999). The Total 

Risk Integrated Methodology (TRIM). 

EM30-34. 

Persily, A; Linteris, G. (1983). A comparison of 

measured and predicted infiltration rates. 

89. 

Price, PN; Shehabi, A; Chan, R. (2006). Indooroutdoor air leakage of apartments and 

commercial buildings. Berkeley, CA: 

California Energy Commission. 

http://www.energy.ca.gov/2006publications/ 

CEC-500-2006-111/CEC-500-2006­

111.PDF. 

Price, S. (2001). An evaluation of the potential for 

use of existing exposure software (or 

software currently under development) in a 

tiered approach to the assessment of 

Exposure Factors Handbook Page
 

September 2011 19-27 
 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

exposures and risks to children. Washington, 

DC: American Chemistry Council. 

http://www.epa.gov/opptintr/vccep/pubs/rev 

modlr.pdf. 

Relwani, SM; Moschandreas, DJ; Billick, IH. (1986). 

Effects of operational factors on pollutant 

emission rates from residential gas 

appliances. J Air Pollut Control Assoc 36: 

1233-1237. 

Roberts, JW; Budd, WT; Ruby, MG; Bond, AE; 

Lewis, RG; Wiener, RW; Camann, DE. 

(1991). Development and field testing of a 

high volume sampler for pesticides and 

toxics in dust. J Expo Sci Environ Epidemiol 

1: 143-155. 

Rosenbaum, AS; Cohen, JP; Kavoosi, F. (2002). 

Update and refinement of an indoor 

exposure assessment methodology. 

(Contract 98-327). Sacramento, CA: 

California Air Resources Board. 

Ryan, PB. (1991). An overview of human exposure 

modeling. J Expo Sci Environ Epidemiol 1: 

453-474. 

Sandberg, M. (1984). The multi-chamber theory 

reconsidered from the viewpoint of air 

quality studies. Build Environ 19: 221-233. 

http://dx.doi.org/10.1016/0360­

1323(84)90003-9. 

Sextro, RG. (1994). Radon and the natural 

environment. In NL Nagda (Ed.), Radon: 

Rrevalence, measurements, health risks, and 

control (pp. 9-32). Philadelphia, PA: ASTM. 

http://dx.doi.org/10.1520/MNL10140M. 

Shaughnessy, RJ; Levetin, E; Blocker, J; Sublette, 

KL. (1994). Effectiveness of portable indoor 

air cleaners: sensory testing results. Indoor 

Air 4: 179-188. 

Sherman, MH. (1989). Analysis of errors associated 

with passive ventilation measurement 

techniques. Build Environ 24: 131-139. 

http://dx.doi.org/10.1016/0360­

1323(89)90002-4. 

Sherman, MH; Matson, NE. (2002). Air tightness of 

new U.S. houses: A preliminary report. 

(LBNL-48671). Berkeley, CA: Lawrence 

Berkeley National Laboratory.

http://energy.lbl.gov/ie/pdf/LBNL48671.pdf. 

Sinden, FW. (1978). Multi-chamber theory of air 

infiltration. Build Environ 13: 21-28. 

http://dx.doi.org/10.1016/0360­

1323(78)90005-7. 

Sparks, LE. (1997). RISK version 1.7: Multiple 

pollutant IAQ model. Research Triangle 

Park, NC: U.S. Environmental Protection 

Agency. 

Thatcher, TL; Lai, ACK; Moreno-Jackson, R; Sextro, 

RG; Nazaroff, WW. (2002). Effects of room 

furnishings and air speed on particle 

deposition rates indoors. Atmos Environ 36: 

1811-1819. http://dx.doi.org/10.1016/S1352­

2310(02)00157-7. 

Thatcher, TL; Layton, DW. (1995). Deposition, 

resuspension, and penetration of particles 

within a residence. Atmos Environ 29: 1487­

1497. http://dx.doi.org/10.1016/1352­

2310(95)00016-R. 

Tichenor, BA; Guo, Z; Dunn, JE; Sparks, LE; Mason, 

MA. (1991). The interaction of vapour phase 

organic compounds with indoor sinks. 

Indoor Air 1: 23-35. 

Tucker, WG. (1991). Emission of organic substances 

from indoor surface materials. Environ Int 

17: 357-363. 

Turk, BH; Brown, JT; Geisling-Sobotka, K; 

Froehlich, DA; Grimsrud, DT; Harrison, J; 

Koonce, JF; Prill, RJ; Revzan, KL. (1987). 

Indoor air quality and ventilation 

measurements in 38 Pacific Northwest 

commercial buildings: Volume I: 

Measurement results and interpretation: 

Final report. (LBL22315 1/2). Berkeley, CA: 

Lawrence Berkeley National Laboratory. 

http://www.ntis.gov/search/product.aspx?A 

BBR=DE88014064. 

U.S. Census Bureau. (2009). American housing 

survey for the United States: 2009. 

Washington, DC: U.S. Government Printing 

Office. 

http://www.census.gov/prod/2011pubs/h150 

-09.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1987). Methods for assessing exposure to 

chemical substances: Volume 7: Methods for 

assessing consumer exposure to chemical 

substances [EPA Report]. (EPA/560/5­

85/007). Washington, DC.

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=P1007I8Y.txt. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1990a). Methods for assessing exposure to 

chemical substances: Volume 11: 

Methodology for estimating the migration of 

additives and impurities from polymeric 

materials [EPA Report]. (EPA 560/5-85­

015). Washington, DC.

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=P100BCMB.txt. 

Page Exposure Factors Handbook 

19-28 September 2011 
Exposure Factors Handbook 

Chapter 19—Building Characteristics 

U.S. EPA (U.S. Environmental Protection Agency). 

(1990b). Methods for assessing exposure to 

chemical substances: Volume 12: Methods 

for estimating the concentration of chemical 

substances in indoor air [EPA Report]. (EPA 

560/5-85-016). Washington, DC. 

U.S. EPA (U.S. Environmental Protection Agency). 

(1995). User's guide for the industrial source 

complex (ISC3) dispersion models. (EPA454/B-95-003a). Research Triangle Park, 

NC. 

http://www.epa.gov/scram001/userg/regmod 

/isc3v1.pdf. 

U.S. EPA (U.S. Environmental Protection Agency). 

(2000). Volatilization rates from water to 

indoor air--Phase II. (EPA/600/R-00/096). 

Washington, DC.

http://nepis.epa.gov/Exe/ZyPURL.cgi?Dock 

ey=30002F5O.txt. 

Versar (Versar Inc.). (1990). Database of 

perfluorocarbon tracer (PFT) ventilation 

measurements: Description and user's 

manual [Database]. Washington, DC: U.S. 

Environmental Protection Agency. 

Wallace, L. (1996). Indoor particles: a review 

[Review]. J Air Waste Manag Assoc 46: 98­

126. 

Walton, GN; Dols, WS. (2010). CONTAM user guide 

and program documentation. Gaithersburg, 

MD: National Institute of Standards and 

Technology. 

Wang, LL; Dols, WS; Chen, Q. (2010). Using CFD 

Capabilities of CONTAM 3.0 for Simulating 

Airflow and Contaminant Transport in and 

around Buildings. HVACandR Research 16: 

749-763. 

Wilkes, C; Nuckols, JR. (2000). Comparing exposure 

classification by three alternative methods: 

Measured blood levels, questionnaire 

results, and model predictions [abstract]. In 

10th annual conference of the International 

Society of Exposure Analysis : exposure 

analysis in the 21st century : integrating 

science, policy & quality of life : October 24 

to 27 2000 : abstracts. Boston, MA: 

International Society of Exposure Analysis. 

Wilkes, CR. (1998). Case studies. In SS Olin (Ed.), 

Exposure to contaminants in drinking water: 

Estimating uptake through the skin and by 

inhalation. Boca Raton, FL: CRC Press. 

http://www.crcpress.com/product/isbn/9780 

849328046;jsessionid=8QXzIDzide2ijbzWDzsbg**. 

Wilkes, CR; Small, MJ; Andelman, JB; Giardino, NJ; 

Marshall, J. (1992). Inhalation exposure 

model for volatile chemicals from indoor 

uses of	 water. Atmos Environ 26: 2227­

2236. http://dx.doi.org/10.1016/0960­

1686(92)90412-E. 

Wolkoff, P. (1995). Volatile Organic Compounds 

Sources, Measurements, Emissions, and the 

Impact on Indoor Air Quality. Indoor Air 5: 

5-73. http://dx.doi.org/10.1111/j.1600­

0668.1995.tb00017.x. 

Wolkoff, P; Wilkins, CK. (1994). Indoor VOCs from 

household floor dust: comparison of 

headspace with desorbed VOCs; method for 

VOC release determination. Indoor Air 4: 

248-254. 

Yamamoto, N; Shendell, D; Winer, A; Zhang, J. 

(2010). Residential air exchange rates in 

three major US metropolitan areas: results 

from the Relationship Among Indoor, 

Outdoor, and Personal Air Study 1999– 

2001. Indoor Air 20: 85-90. 

http://dx.doi.org/10.1111/j.1600­

0668.2009.00622.x. 

Zinn, TW; Cline, D; Lehmann, WF. (1990). Longterm study of formaldehyde emission decay 

from particleboard. For Prod J 40: 15-18. 

Exposure Factors Handbook Page
 

September 2011 19-29 
 

Table 19-6. Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership 

Ownership 

Owner-Occupied Rentala All Units 

Housing 

Type 

b Volume

(m3) 

% 

of Total 

b Volume

(m3) 

% 

of Total 

b Volume

(m3) 

% 

of Total 

Single-Family 

(Detached) 

Single-Family 

(Attached) 

Multifamily 

 (2–4 units) 

Multifamily 

 (5+ Units) 

Mobile Home 

All Types 

637 

544 

363 

253 

249 

586 

57.7 

3.8 

1.7 

2.1 

5.2 

70.5 

449 

313 

211 

189 

196 

269 

7.2 

3.1 

5.3 

13.0 

1.1 

29.7 

616 

440 

247 

197 

240 

492 

64.9 

6.8 

7.0 

15.1 

6.3 

100 

a The classification "Occupied without payment of rent" is included in the estimates for rentals. b Volumes calculated from floor areas assuming a ceiling height of 8 feet. Excludes floor space in unheated 

garages. 

Source: U.S. EPA Analysis of U.S. DOE (2008a). 

 

 

 

 

 

 

 

 

 

 

Table 19-7. Residential Volumes in Relation to Year of Construction 

Year of Construction Volumea (m3) % of Total 

Before 1940 527 13.2 

1940–1949 464 6.7 

1950–1959 465 11.3 

1960–1969 446 11.2 

1970–1979 422 17.0 

1980–1989 451 16.7 

1990–1999 567 15.6 

2000–2005 640 8.3 

All Years 492 100 

a Volumes calculated from floor areas assuming a ceiling height of 8 feet. Excludes floor space in unheated 

garages. 

Source: U.S. EPA Analysis of U.S. DOE (2008a). 

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Chapter 19—Building Characteristics 

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19-30 September 2011 
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Chapter 19—Building Characteristics 

Table 19-8. Summary of Residential Volume 

Distributions Based on U.S. DOE (2008a)

a 

(m3) 

Parameter Volume 

Arithmetic Mean 492 

Standard Deviation 349 

10th Percentile 154 

25th Percentile 231 

50th Percentile 395 

75th Percentile 648 

90th Percentile 971 

a All housing types, all units. 

Source: U.S. EPA’s Analysis of U.S. DOE (2008a). 

Table 19-9. Summary of Residential Volume 

Distributions Based on Versar (1990) (m3) 

Parameter Volume 

Arithmetic Mean 369 

Standard Deviation 209 

10th Percentile 167 

25th Percentile 225 

50th Percentile 321 

75th Percentile 473 

90th Percentile 575 

Source: Versar (1990); based on PFT database. 

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Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-10. Number of Residential Single Detached and Mobile Homes by Volumea (m3) 

and Median Volumes by Housing Type 

Housing Units 

Total 

Housing 

Units Seasonal 

Year-Round 

New units 

in last 4 

Total years 

Occupied Vacant 

Owner Renter 

Total 

Vacant 

Manuf./ 

mobile 

homes 

Total all housing units 130,112 4,618 125,494 76,428 35,378 13,688 5,955 8,769 

Single detached and 

manufactured/mobile homes 91,241 3,524 87,717 68,742 11,176 7,799 4,291 

Volume (m3) 

Less than 113.3 988 225 764 383 220 161 10 

113.3–169.7 2,765 462 2,303 1,085 686 532 19 

169.9–226.3 6,440 593 5,847 3,519 1,495 833 68 

226.5–339.6 21,224 814 20,410 14,978 3,441 1,991 557 

339.8–452.8 20,636 521 20,115 16,284 2,235 1,596 827 

453.1–566.1 14,361 284 14,077 12,057 1,134 886 813 

566.3–679.4 7,589 141 7,448 6,622 429 398 535 

679.6–905.9 7,252 137 7,115 6,391 301 424 751 

906 or more 4,456 113 4,343 3,787 243 313 469 

Not reported/Don't know 5,529 234 5,295 3,638 992 666 241 

8,769 

331 

1,020 

1,935 

2,779 

1,309 

334 

126 

54 

146 

735 

Median Volume (m3) 385.1 260.5 393.3 407.8 294.5 339.8 521.0 247.4 a Converted from ft2

. Assumes 8-foot ceiling. 

Source: U.S. Census Bureau (2009). 

Table 19-11. Dimensional Quantities for Residential Rooms 

Nominal Dimensions Length 

(meters) 

Width 

(meters) 

Height 

(meters) 

Volume 

(m3) 

Wall Area 

(m2) 

Floor Area 

(m2) 

Total Area 

(m2) 

8-Foot Ceiling 

12’ × 15’ 

12’ × 12’ 

10’ × 12’ 

9’ × 12’ 

6’ × 12’ 

4’ × 12’ 

12-Foot Ceiling 

12’ × 15’ 

12’ × 12’ 

10’ × 12’ 

9’ × 12’ 

6’ × 12’ 

4’ × 12’ 

4.6 3.7 2.4 41 40 

3.7 3.7 2.4 33 36 

3.0 3.7 2.4 27 33 

2.7 3.7 2.4 24 31 

1.8 3.7 2.4 16 27 

1.2 3.7 2.4 11 24 

4.6 3.7 3.7 61 60 

3.7 3.7 3.7 49 54 

3.0 3.7 3.7 41 49 

2.7 3.7 3.7 37 47 

1.8 3.7 3.7 24 40 

1.2 3.7 3.7 16 36 

17 

13 

11 

10 

7 

4 

17 

13 

11 

10 

7 

4 

74 

62 

55 

51 

40 

32 

94 

80 

71 

67 

54 

44 

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19-32 September 2011 
Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-12. Examples of Products and Materials Associated With Floor and Wall Surfaces in Residences 

Material Sources Assumed Amount of 

Surface Covereda (m2) 

Silicone caulk 0.2 

Floor adhesive 10.0 

Floor wax 50.0 

Wood stain 10.0 

Polyurethane wood finish 10.0 

Floor varnish or lacquer 50.0 

Plywood paneling 100.0 

Chipboard 100.0 

Gypsum board 100.0 

Wallpaper 100.0 a Based on typical values for a residence. 

Source: Adapted from Tucker (1991). 

Exposure Factors Handbook Page
 

September 2011 19-33 
 

 

 

 

Table 19-13. Residential Heating Characteristics by U.S. Census Region 

Housing U.S. Census Region Space Heating Characteristics Units (%) Northeast Midwest South West 

Total 100.0 100.0 100.0 100.0 100.0 

Do Not Have Space Heating Equipment 1.1 Q Q Q 2.9 

Have Main Space Heating Equipment 98.8 99.5 100.0 99.0 96.7 

Main Heating Fuel and Equipment 

Natural Gas 52.4 55.3 71.9 33.4 60.7 

Central Warm-Air Furnace 40.2 29.6 63.3 27.0 47.1 

Steam or Hot Water System 7.4 23.8 6.3 2.5 2.5 

Floor, Wall or Pipeless Furnace 2.1 Q 1.2 0.5 6.6 

Room Heater 1.8 Q Q 2.2 3.3 

Other Equipment 0.8 1.0 Q 1.0 1.2 

Electricity 30.3 7.8 13.7 54.3 26.9 

Built-in Electric Units 4.5 4.4 4.3 3.7 6.6 

Central Warm-Air Furnace 14.4 1.5 5.5 27.0 14.0 

Heat Pump 8.3 Q 3.1 17.7 4.1 

Portable Electric Heater 1.4 Q Q 2.2 2.1 

Other Equipment 1.7 1.0 Q 3.4 Q 

Fuel Oil 6.9 30.1 2.7 1.2 1.2 

Steam or Hot Water System 4.2 20.9 Q Q Q 

Central Warm-Air Furnace 2.5 8.7 2.0 0.7 Q 

Other Equipment 0.3 Q Q Q Q 

Wood 2.6 2.4 2.7 2.2 3.3 

Propane/LPGa 5.4 1.9 7.4 6.6 4.1 

Central Warm-Air Furnace 3.7 1.0 6.6 3.7 2.5 

Room Heater 0.8 Q Q 1.7 Q 

Other Equipment 0.9 Q Q 1.0 1.2 

Kerosene 0.6 1.0 Q 1.0 Q 

Other Fuel 0.5 Q Q Q Q 

Secondary Heating Fuel and Equipment 

No 68.6 78.6 63.3 71.0 61.6 

Yes (More than One May Apply) 31.4 21.4 36.7 29.0 38.4 

Natural Gas 4.5 1.9 5.9 3.2 7.4 

Fireplace 2.4 Q 3.1 1.5 4.5 

Room Heater 0.5 Q Q 0.7 Q 

Central Warm-Air Furnace 1.0 Q 1.6 Q 1.7 

Other Equipment 0.7 Q Q Q 1.2 

Electricity 17.7 12.1 20.7 17.0 21.1 

Portable Heater 14.4 9.7 16.8 13.8 16.9 

Built-in Electric Units 2.0 1.9 2.3 1.0 2.9 

Heat Pump 0.5 N/R Q 1.0 Q 

Other Equipment 1.2 Q 1.6 1.5 1.7 

Fuel Oil 0.4 1.0 Q Q N/R 

Wood 8.0 4.4 8.6 7.6 11.2 

Propane/LPG 2.1 1.5 2.7 2.7 N/R 

Kerosene 0.8 1.0 1.2 1.0 N/R 

Other Fuel 0.2 Q Q Q Q a Liquefied Petroleum Gas. 

Q = Data withheld either because the Relative Standard Error (RSE) was greater than 50% or fewer than 10 

households were sampled. 

N/R = No cases in reporting sample. 

Source: U.S. DOE (2008a). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Page Exposure Factors Handbook 

19-34 September 2011 
 

 

Table 19-14. Residential Heating Characteristics by Urban/Rural Location 

Housing Urban/Rural Location 

Space Heating Characteristics Units (%) City Town Suburbs Rural 

Total 100.0 100.0 100.0 100.0 100.0 

Do Not Have Space Heating Equipment 1.1 1.5 Q 0.9 Q 

Have Main Space Heating Equipment 98.8 98.3 99.5 99.1 99.1 

Main Heating Fuel and Equipment 

Natural Gas 52.4 57.3 62.6 65.6 19.3 

Central Warm-Air Furnace 40.2 42.0 45.3 56.4 16.1 

Steam or Hot Water System 7.4 9.3 11.1 6.2 1.3 

Floor, Wall or Pipeless Furnace 2.1 2.5 2.6 1.8 Q 

Room Heater 1.8 2.3 2.6 Q Q 

Other Equipment 0.8 0.8 1.6 Q Q 

Electricity 30.3 33.8 24.2 25.6 33.2 

Built-in Electric Units 4.5 5.3 4.2 4.0 4.0 

Central Warm-Air Furnace 14.4 16.8 14.2 10.1 14.3 

Heat Pump 8.3 7.2 4.2 9.7 12.1 

Portable Electric Heater 1.4 1.7 Q Q 2.2 

Other Equipment 1.7 2.5 Q Q Q 

Fuel Oil 6.9 5.1 8.9 5.3 10.8 

Steam or Hot Water System 4.2 3.8 4.7 3.5 5.4 

Central Warm-Air Furnace 2.5 1.3 3.7 2.2 4.5 

Other Equipment 0.3 Q Q N/R Q 

Wood 2.6 0.6 Q Q 10.3 

Heating Stove 1.8 Q Q Q 6.7 

Other Equipment 0.8 Q Q N/R 3.1 

Propane/LPGa 5.4 0.6 1.1 1.3 23.3 

Central Warm-Air Furnace 3.7 Q Q Q 16.6 

Room Heater 0.8 Q Q Q 3.1 

Other Equipment 0.9 Q Q Q 3.6 

Kerosene 0.6 Q Q Q 1.8 

Other Fuel 0.5 0.6 Q Q Q 

Secondary Heating Fuel and Equipment 

No 68.6 75.2 73.2 67.4 52.0 

Yes (More than One May Apply) 31.4 24.8 26.8 32.2 48.4 

Natural Gas 4.5 3.8 3.7 7.5 3.1 

Fireplace 2.4 1.9 1.6 4.8 1.8 

Room Heater 0.5 Q Q Q Q 

Central Warm-Air Furnace 1.0 0.8 Q 1.3 Q 

Other Equipment 0.7 0.8 Q Q Q 

Electricity 17.7 15.9 15.8 17.6 23.3 

Portable Heater 14.4 13.2 13.7 14.5 17.0 

Built-in Electric Units 2.0 1.7 Q 2.2 3.1 

Heat Pump 0.5 Q Q Q 1.3 

Other Equipment 1.2 0.8 1.1 Q 2.2 

Fuel Oil 0.4 N/R Q Q Q 

Wood 8.0 5.5 6.3 7.0 15.2 

Propane/LPG 2.1 Q Q 1.3 8.1 

Kerosene 0.8 Q Q Q 2.2 

Other Fuel 0.2 Q Q Q Q a Liquefied Petroleum Gas. 

Q = Data withheld either because Relative Standard Error (RSE) was >50% or <10 households were sampled. 

N/R = No cases in reporting sample. 

Source: U.S. DOE (2008a). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Exposure Factors Handbook Page
 

September 2011 19-35 
 

 

Table 19-15. Residential Air Conditioning Characteristics by U.S. Census Region 

Housing U.S. Census Region Air Conditioning Characteristics Units (%) Northeast Midwest South West 

Total 100.0 100.0 100.0 100.0 100.0 

Do Not Have Cooling Equipment 16.0 19.4 8.2 3.4 42.6 

Have Cooling Equipment 84.0 80.1 91.8 96.6 57.4 

Air-Conditioning Equipmenta, b 

Central System 59.3 29.1 67.6 78.9 43.4 

Window/Wall Units 26.0 51.9 25.8 19.7 14.9 

Frequency of Central Air-Conditioner Use 

Never 1.3 Q Q 1.0 3.3 

Only a Few Times When Needed 10.3 7.8 15.2 6.1 14.0 

Quite a Bit 11.3 5.8 17.6 11.1 9.9 

All Summer 36.5 14.6 34.4 60.9 16.1 

Frequency Most-Used Unit Used 

Never 0.5 Q Q Q Q 

Only a Few Times When Needed 10.9 23.8 12.1 5.2 8.3 

Quite a Bit 6.8 14.6 6.3 5.4 2.9 

All Summer 7.7 12.6 7.0 8.8 2.9 a In the 2005 RECS, 1.5 million housing units reported having both central and window/wall air conditioners. b	 The number of housing units using air-conditioning includes a small, undetermined number of housing units 

where the fuel for central air-conditioning was other than electricity; these housing units were treated 

as if the air-conditioning fuel was electricity. 

Q = Data withheld either because the Relative Standard Error (RSE) was greater than 50% or fewer than 

10 households were sampled. 

Source:	 U.S. DOE (2008a). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-16. Percent of Residences With Basement, by 

Census Region and U.S. EPA Region 

Census Region U.S. EPA Regions 

% of Residences 

With Basements 

Northeast 1 93.4 

Northeast 2 55.9 

Midwest 3 67.9 

Midwest 4 19.3 

South 5 73.5 

South 6 4.1 

South 7 75.3 

West 8 68.5 

West 9 10.3 

West 10 11.5 

All Regions 45.2 

Source: Lucas et al. (1992). 

Page Exposure Factors Handbook 

19-36 September 2011 
Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-17. Percent of Residences With Basement, by Census 

Region 

Census Region Census Divisions 

% of Residences With 

Basements 

Northeast 1 New England 83.2 

Northeast 2 Mid Atlantic 69.1 

Midwest 3 East North Central 68.7 

Midwest 4 West North Central 65.3 

South 5 South Atlantic 27.0 

South 6 East South Central 23.7 

South 7 West South Central 2.8 

West 8 Mountain 29.9 

West 9 Pacific 10.9 

All Divisions 40.6 

Source: U.S. EPA Analysis of U.S. DOE (2008a). 

Exposure Factors Handbook Page
 

September 2011 19-37 
 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-18. States Associated With U.S. EPA Regions and Census Regions 

U.S. EPA Regions 

Region 1 

Connecticut 

Maine 

Massachusetts 

New Hampshire 

Rhode Island 

Vermont 

Region 2 

New Jersey 

New York 

Region 3 

Delaware 

District of Columbia 

Maryland 

Pennsylvania 

Virginia 

West Virginia 

Region 4 

Alabama 

Florida 

Georgia 

Kentucky 

Mississippi 

North Carolina 

South Carolina 

Tennessee 

Region 5 

Illinois 

Indiana 

Michigan 

Minnesota 

Ohio 

Wisconsin 

Region 6 

Arkansas 

Louisiana 

New Mexico 

Oklahoma 

Texas 

Region 7 

Iowa 

Kansas 

Missouri 

Nebraska 

Region 8 

Colorado 

Montana 

North Dakota 

South Dakota 

Utah 

Wyoming 

Region 9 

Arizona 

California 

Hawaii 

Nevada 

Region 10 

Alaska 

Idaho 

Oregon 

Washington 

U.S. Census Bureau Regions 

Northeast Region 

Connecticut 

Maine 

Massachusetts 

New Hampshire 

New Jersey 

New York 

Pennsylvania 

Rhode island 

Vermont 

Midwest Region 

Illinois 

Indiana 

Iowa 

Kansas 

Michigan 

Minnesota 

Missouri 

Nebraska 

North Dakota 

Ohio 

South Dakota 

Wisconsin 

South Region 

Alabama 

Arkansas 

Delaware 

District of Columbia 

Florida 

Georgia 

Kentucky 

Louisiana 

Maryland 

Mississippi 

North Carolina 

Oklahoma 

South Carolina 

Tennessee 

Texas 

Virginia 

West Virginia 

West Region 

Alaska 

Arizona 

California 

Colorado 

Hawaii 

Idaho 

Montana 

Nevada 

New Mexico 

Oregon 

Utah 

Washington 

Wyoming 

Source: U.S. DOE (2008a). 

Page Exposure Factors Handbook 

19-38 September 2011 
Table 19-19. Percent of Residences With Certain Foundation Types by 

Census Region 

% of Residencesa 

With With With 

Census 

Region Basement Crawlspace Concrete Slab 

Northeast 72.9 18.9 24.5 

Midwest 67.7 27.4 30.2 

South 19.1 29.7 58.5 

West 17.0 36.9 61.8 

All Regions 40.6 28.7 46.0 a	 Percentage may add to more than 100 because more than one foundation 

type may apply to a given residence. 

Source:	 U.S. EPA Analysis of U.S. DOE (2008a). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Exposure Factors Handbook Page
 

September 2011 19-39 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-20. Average Estimated Volumesa of U.S. Commercial Buildings, by Primary 

Activity 

Primary 

Building 

Activity 

SE of 

Mean 

Percentiles 

% of 

Total N Mean 10th 25th 50th 75th 90th 

Vacant 134 4,789 581 408 612 1,257 3,823 11,213 3.7 

Office 976 5,036 397 510 714 1,359 3,398 8,155 17.0 

Laboratory 43 24,681 1,114 2,039 5,437 10,534 40,776 61,164 0.2 

Nonrefrigerated 

warehouse 

473 9,298 992 1,019 1,812 2,945 7,504 16,990 12.0 

Food sales 125 1,889 106 476 680 951 2,039 3,398 4.6 

Public order 

and safety 85 5,253 482 816 1,019 1,699 3,398 8,495 1.5 

Outpatient 

healthcare 144 3,537 251 680 1,019 2,039 3,398 6,966 2.5 

Refrigerated 

warehouse 20 19,716 3,377 1,133 1,699 3,398 8,212 38,511 0.3 

Religious 

worship 311 3,443 186 612 917 2,039 4,163 8,325 7.6 

Public 

assembly 279 4,839 394 595 1,019 2,277 4,417 7,136 5.7 

Education 649 8,694 513 527 867 2,379 10,194 23,786 7.9 

Food 

service 242 1,889 112 442 680 1,189 2,039 3,568 6.1 

Inpatient 

healthcare 217 82,034 5,541 17,330 25,485 36,019 95,145 203,881 0.2 

Nursing 73 15,522 559 1,546 5,097 10,534 17,330 38,737 0.4 

Lodging 260 11,559 1,257 527 1,376 4,078 10,194 27,184 2.5 

Strip 

shopping 

mall 

349 7,891 610 1,359 2,277 4,078 6,966 19,709 4.3 

Enclosed 

mall 46 287,978 14,780 35,679 35,679 113,268 453,070 849,505 0.1 

Retail other 

than mall 355 3,310 218 510 680 1,631 3,398 6,116 9.1 

Service 370 2,213 182 459 629 934 2,039 4,587 12.8 

Other 64 5,236 984 425 544 1,427 3,398 9,175 1.4 

All 

Buildingsb 5,215 5,575 256 527 816 1,699 4,248 10,194 100 

a Volumes calculated from floor areas assuming a ceiling height of 12 feet for other structures 

and 20 feet for warehouses. b Weighted average calculated from floor areas assuming a ceiling height of 12 feet for all 

buildings except warehouses and enclosed malls, which assumed 20-foot ceilings. 

N = Number of observations. 

SE = Standard error. 

Source: U.S. EPA Analysis of U.S. DOE (2008b). 

Page Exposure Factors Handbook 

19-40 September 2011 
Table 19-21. Non-Residential Buildings: Hours per Week Open and Number of Employees 

Number of Hours/Week Open Number of Employees During Main Shift 

Percentiles Percentiles Primary Building SE of SE of 

Activity N % Mean Mean 10th 25th 50th 75th 90th Mean Mean 10th 25th 50th 75th 90th 

Vacant 134 2.8% 6.7 1.2 0 0 0 0 40 0.35 0.08 0 0 0 0 0 

Office 976 20.2% 54.7 1.6 40 45 54 65 168 34.2 2.8 4 11 57 300 886 

Laboratory 43 0.9% 103.5 0.8 50 58 98 168 168 105.6 4.5 20 55 156 300 435 

Non-refrigerated warehouse 473 9.8% 66.2 4.8 20 40 55 80 168 7.0 0.9 0 1 8 25 64 

Food sales 125 2.6% 107.3 2.5 60 80 109 127 168 6.3 0.5 1 2 4 15 50 

Public order and safety 85 1.8% 103.0 7.6 10 40 168 168 168 19.1 2.2 1 4 15 60 200 

Outpatient healthcare 144 3.0% 52.0 2.8 40 45 54 70 168 21.5 1.9 5 8 40 125 200 

Refrigerated warehouse 20 0.4% 61.3 0.7 44 53 102 126 168 18.2 2.4 4 8 38 61 165 

Religious worship 311 6.5% 32.0 2.4 5 13 40 60 79 4.6 0.5 1 1 3 10 19 

Public assembly 279 5.8% 50.3 3.8 12 40 63 96 125 8.7 1.5 0 2 5 22 80 

Education 649 13.5% 49.6 1.0 38 42 54 70 85 32.4 8.8 3 14 38 75 133 

Food service 242 5.0% 85.8 2.6 40 66 84 105 130 10.5 0.9 2 4 8 15 33 

Inpatient healthcare 217 4.5% 168.0 * 168 168 168 168 168 471.0 40.4 175 315 785 1,300 2,250 

Nursing 73 1.5% 168.0 * 168 168 168 168 168 44.8 2.5 15 25 50 80 170 

Lodging 260 5.4% 166.6 0.8 168 168 168 168 168 12.3 2.0 1 3 10 25 80 

Retail other than mall 355 7.4% 59.1 1.5 42 50 62 80 105 7.8 0.7 2 3 6 22 72 

Service 370 7.7% 55.0 2.1 40 40 50 68 105 5.9 0.6 1 2 4 10 35 

Other 64 1.3% 57.8 7.1 12 40 51 90 168 12.3 1.7 1 2 10 44 150 

All Activities 4,820 100.0% 61.2 1.2 30 45 60 98 168 15.7 1.2 1 3 14 66 300 

* All sampled inpatient healthcare and nursing buildings reported being open 24 hours a day, 7 days a week.
 

N = Number of observations.
 

SE = Standard error.
 

Source: U.S. EPA Analysis of U.S. DOE (2008b). 

Chapter 19—Exposure Factors Handbook 

Building Characteristics 

Exposure Factors Handbook Page September 2011 19-41 
 

Table 19-22. Non-Residential Heating Energy Sources for Non-Mall Buildings 

All 

Buildingsa 

Buildings 

With 

Space 

Heating 

Space-Heating Energy Sources Usedb 

Electricity 

Natural Fuel District 

Gas Oil Heat Propane Otherc 

All Buildingsa 

Building Floorspace (ft2) 

1,001–5,000 

5,001–10,000 

10,001–25,000 

25,001–50,000 

50,001–100,000 

100,001–200,000 

200,001–500,000 

Over 500,000 

Principal Building Activity 

Education 

Food Sales 

Food Service 

Health Care 

Lodging 

Retail (Other Than Mall) 

Office 

Public Assembly 

Public Order and Safety 

Religious Worship 

Service 

Warehouse and Storage 

Other 

Vacant 

Year Constructed 

Before 1920 

1920–1945 

1946–1959 

1960–1969 

1970–1979 

1980–1989 

1990–1999 

2000–2003 

Census Region and 

Division 

Northeast 

Midwest 

South 

West 

Heating Equipmentb 

Heat Pumps 

Furnaces 

Individual Space Heaters 

District Heat 

Boilers 

Packaged Heating Units 

4,645 

54.9% 

19.1% 

15.9% 

5.2% 

2.8% 

1.4% 

0.5% 

0.2% 

8.3% 

4.9% 

6.4% 

2.8% 

3.1% 

9.5% 

17.7% 

6.0% 

1.5% 

8.0% 

13.4% 

12.9% 

1.7% 

3.9% 

7.1% 

11.3% 

12.1% 

12.5% 

15.7% 

15.2% 

18.9% 

7.2% 

15.6% 

27.3% 

38.2% 

18.9% 

10.2% 

40.1% 

17.6% 

1.4% 

12.5% 

20.5% 

3,982 

52.7% 

19.6% 

16.5% 

5.7% 

3.1% 

1.6% 

0.6% 

0.2% 

9.6% 

4.7% 

7.1% 

3.1% 

3.6% 

10.2% 

20.1% 

6.5% 

1.8% 

9.0% 

12.9% 

7.9% 

1.7% 

1.7% 

7.6% 

11.1% 

12.4% 

13.2% 

16.3% 

15.5% 

18.1% 

5.9% 

16.9% 

27.9% 

36.7% 

18.5% 

12.0% 

46.8% 

20.6% 

1.6% 

14.5% 

23.9% 

1,766 

50.3% 

19.8% 

17.6% 

6.5% 

3.4% 

1.6% 

0.6% 

0.2% 

10.2% 

5.5% 

7.1% 

3.5% 

5.8% 

9.6% 

21.5% 

4.7% 

1.4% 

8.6% 

10.2% 

8.5% 

1.8% 

1.5% 

3.7% 

8.0% 

11.0% 

12.0% 

16.6% 

19.9% 

21.5% 

7.1% 

10.1% 

20.2% 

50.0% 

19.7% 

26.4% 

31.4% 

34.2% 

0.3% 

9.1% 

32.4% 

2,165 

46.8% 

20.8% 

18.9% 

7.0% 

3.9% 

1.8% 

0.7% 

0.2% 

8.6% 

3.6% 

7.9% 

3.1% 

2.6% 

10.9% 

21.5% 

6.5% 

1.4% 

9.6% 

12.3% 

8.2% 

1.9% 

1.8% 

8.5% 

14.3% 

12.9% 

13.0% 

16.6% 

12.5% 

17.2% 

4.9% 

16.0% 

35.8% 

29.1% 

19.1% 

5.7% 

58.8% 

18.4% 

0.2% 

18.3% 

24.4% 

360 

54.4% 

23.9% 

12.8% 

3.1% 

2.2% 

2.5% 

1.1% 

0.3% 

5.8% 

Q 

Q 

Q 

4.4% 

9.7% 

12.8% 

10.3% 

Q 

10.0% 

22.8% 

7.8% 

Q 

Q 

20.0% 

13.3% 

18.1% 

13.6% 

12.8% 

10.0% 

9.4% 

Q 

63.6% 

16.4% 

14.2% 

6.1% 

1.7% 

52.2% 

21.9% 

Q 

40.0% 

4.7% 

65 

Q 

Q 

27.7% 

13.8% 

12.3% 

13.8% 

6.2% 

3.1% 

38.5% 

N/R 

Q 

3.1% 

Q 

Q 

24.6% 

9.2% 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

18.5% 

20.0% 

20.0% 

9.2% 

6.2% 

12.3% 

Q 

26.2% 

20.0% 

30.8% 

23.1% 

3.1% 

Q 

6.2% 

100.0% 

Q 

4.6% 

372 

65.3% 

19.4% 

10.2% 

3.0% 

Q 

Q 

Q 

Q 

9.7% 

Q 

8.3% 

Q 

Q 

10.8% 

9.7% 

Q 

Q 

11.8% 

20.2% 

6.5% 

Q 

Q 

Q 

Q 

11.0% 

11.6% 

12.9% 

19.9% 

19.4% 

12.6% 

6.5% 

38.7% 

36.6% 

18.0% 

7.5% 

57.0% 

32.8% 

Q 

8.1% 

21.2% 

113 

63.7% 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

N/R 

60.2% 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

39.8% 

Q 

Q 

Q 

Q 

31.9% 

Q 

Q 

Q 

57.5% 

35.4% 

N/R 

15.9% 

Q 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Page Exposure Factors Handbook 

19-42 September 2011 
Exposure Factors Handbook 

Chapter 19—Building Characteristics 

 

Table 19-22. Non-Residential Heating Energy Sources for Non-Mall Buildings (continued) 

All 

Buildingsa 

Buildings 

With 

Space 

Heating 

Space-Heating Energy Sources Usedb 

Electricity 

Natural 

Gas 

Fuel 

Oil 

District 

Heat Propane 

Other 4.4% 5.1% 6.6% 3.7% 10.0% Q 10.8% a Figures in this table do not include enclosed malls and strip malls. b More than one may apply. c “Other” includes wood, coal, solar, and all other energy sources. 

Q = Data withheld because the Relative Standard Error (RSE) was >50%, or <20 buildings were sampled. 

N/R = No responding cases in sample. 

Otherc 

41.6% 

Source: U.S. DOE (2008b). 

Exposure Factors Handbook Page
 

September 2011 19-43 
Page Exposure Factors Handbook 

19-44 September 2011 

Table 19-23. Non-Residential Air Conditioning Energy Sources for Non-Mall Buildings 

Buildings Cooling Energy Sources

b 

All With Natural District 

Buildings

a Cooling Electricity Gas Chilled Water 

All Buildings

a 4,645 3,625 3,589 17 33 

Building Floorspace (ft

2

) 

1,001–5,000 54.9% 50.8% 51.2% Q Q 

5,001–10,000 19.1% 20.2% 20.3% Q Q 

10,001–25,000 15.9% 17.4% 17.2% Q Q 

25,001–50,000 5.2% 6.0% 5.9% Q 18.2% 

50,001–100,000 2.8% 3.3% 3.2% Q 15.2% 

100,001–200,000 1.4% 1.7% 1.5% Q 18.2% 

200,001–500,000 0.5% 0.6% 0.6% Q 6.1% 

Over 500,000 0.2% 0.2% 0.1% Q 3.0% 

Principal Building Activity 

Education 8.3% 9.7% 9.4% Q 42.4% 

Food Sales 4.9% 5.8% 5.8% N/R N/R 

Food Service 6.4% 7.8% 7.9% Q Q 

Health Care 2.8% 3.6% 3.6% 0.0% 3.0% 

Lodging 3.1% 3.6% 3.6% Q Q 

Retail (Other Than Mall) 9.5% 11.2% 11.3% Q Q 

Office 17.7% 21.8% 21.8% Q 27.3% 

Public Assembly 6.0% 5.9% 5.9% Q 9.1% 

Public Order and Safety 1.5% 1.7% 1.7% Q Q 

Religious Worship 8.0% 8.5% 8.6% Q Q 

Service 13.4% 10.2% 10.3% Q N/R 

Warehouse and Storage 12.9% 7.3% 7.3% Q Q 

Other 1.7% 1.6% 1.6% Q Q 

Vacant 3.9% 1.4% 1.4% N/R Q 

Year Constructed 

Before 1920 7.1% 6.4% 6.4% Q Q 

1920–1945 11.3% 10.5% 10.6% Q Q 

1946–1959 12.1% 11.9% 11.9% Q 12.1% 

1960–1969 12.5% 12.9% 12.8% Q 12.1% 

1970–1979 15.7% 16.8% 16.9% Q 15.2% 

1980–1989 15.2% 15.9% 15.9% Q 15.2% 

1990–1999 18.9% 19.2% 19.1% Q 24.2% 

2000–2003 7.2% 6.5% 6.5% Q Q 

Census Region and Division 

Northeast 15.6% 14.3% 14.3% 41.2% 18.2% 

Midwest 27.3% 26.4% 26.5% Q 12.1% 

South 38.2% 40.8% 40.9% Q 42.4% 

West 18.9% 18.5% 18.4% Q 27.3% 

Cooling Equipmentb 

Central Air Conditioners 21.7% 27.8% 28.0% Q Q 

Heat Pumps 10.6% 13.6% 13.7% 47.1% 3.0% 

Individual Air Conditioners 16.0% 20.5% 20.7% Q 6.1% 

District Chilled Water 0.7% 0.9% 0.3% Q 100.0% 

Central Chillers 2.4% 3.1% 3.0% 29.4% Q 

Packaged A/C Units 34.7% 44.5% 44.9% 23.5% 12.1% 

Swamp Coolers 2.6% 3.4% 3.4% Q Q 

Other 0.9% 1.1% 0.8% Q Q a Figures in this table do not include enclosed malls and strip malls. b More than one may apply. 

Q = Data withheld because the Relative Standard Error (RSE) was >50%, or <20 buildings were 

sampled. 

N/R = No responding cases in sample. 

Source: U.S. DOE (2008b). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 
Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-24. Summary Statistics for Residential Air Exchange Rates (in ACH), 

a by Region 

West 

Region 

Midwest 

Region 

Northeast 

Region 

South 

Region 

All 

Regions 

Arithmetic Mean 0.66 0.57 0.71 0.61 0.63 

Arithmetic Standard Deviation 0.87 0.63 0.60 0.51 0.65 

Geometric Mean 0.47 0.39 0.54 0.46 0.46 

Geometric Standard Deviation 2.11 2.36 2.14 2.28 2.25 

10th Percentile 0.20 0.16 0.23 0.16 0.18 

50th Percentile 0.43 0.35 0.49 0.49 0.45 

90th Percentile 1.25 1.49 1.33 1.21 1.26 

Maximum 23.32 4.52 5.49 3.44 23.32 a

ACH = Air changes per hour. 

Source: Koontz and Rector (1995). 

Exposure Factors Handbook Page
 

September 2011 19-45 
 

Table 19-25. Summary of Major Projects Providing Air Exchange Measurements in the PFT Database 

Project Code State Month(s)a Number of 

Measurements 

Mean Air 

Exchange Rate 

(ACH) 

SDb 

Percentiles 

10th 25th 50th 75th 90th 

ADM 

BSG 

GSS 

FLEMING 

GEOMET1 

GEOMET2 

GEOMET3 

LAMBERT1 

LAMBERT2 

LAMBERT3 

LAMBERT4 

LBL1 

LBL2 

LBL3 

LBL4 

LBL5 

LBL6 

NAHB 

NYSDH 

PEI 

PIERCE 

RTI1 

RTI2 

RTI3 

SOCAL1 

SOCAL2 

SOCAL3 

UMINN 

UWISC 

CA 

CA 

AZ 

NY 

FL 

MD 

TX 

ID 

MT 

OR 

WA 

OR 

WA 

ID 

WA 

WA 

ID 

MN 

NY 

MD 

CT 

CA 

CA 

NY 

CA 

CA 

CA 

MN 

WI 

5–7 

1, 8–12 

1–3, 8–9 

1–6, 8–12 

1,6–8, 10–12 

1–6 

1–3 

2–3, 10–11 

1–3, 11 

1–3, 10–12 

1–3, 10–12 

1–4, 10–12 

1–4, 10–12 

1–5, 11–12 

1–4, 11–12 

2–4 

3–4 

1–5, 9–12 

1–2, 4, 12 

3–4 

1–3 

2 

7 

1–4 

3 

7 

1 

1–4 

2–5 

29 

40 

25 

56 

18 

23 

42 

36 

51 

83 

114 

126 

71 

23 

29 

21 

19 

28 

74 

140 

25 

45 

41 

397 

551 

408 

330 

35 

57 

0.70 

0.53 

0.39 

0.24 

0.31 

0.59 

0.87 

0.25 

0.23 

0.46 

0.30 

0.56 

0.36 

1.03 

0.39 

0.36 

0.28 

0.22 

0.59 

0.59 

0.80 

0.90 

2.77 

0.55 

0.81 

1.51 

0.76 

0.36 

0.82 

0.52 

0.30 

0.21 

0.28 

0.16 

0.34 

0.59 

0.13 

0.15 

0.40 

0.15 

0.37 

0.19 

0.47 

0.27 

0.21 

0.14 

0.11 

0.37 

0.45 

1.14 

0.73 

2.12 

0.37 

0.66 

1.48 

1.76 

0.32 

0.76 

0.29 

0.21 

0.16 

0.05 

0.15 

0.12 

0.33 

0.10 

0.10 

0.19 

0.14 

0.28 

0.18 

0.37 

0.14 

0.13 

0.11 

0.11 

0.28 

0.15 

0.20 

0.38 

0.79 

0.26 

0.29 

0.35 

0.26 

0.17 

0.22 

0.36 

0.30 

0.23 

0.12 

0.18 

0.29 

0.51 

0.17 

0.14 

0.26 

0.20 

0.35 

0.25 

0.73 

0.18 

0.19 

0.17 

0.16 

0.37 

0.26 

0.22 

0.48 

1.18 

0.33 

0.44 

0.59 

0.37 

0.20 

0.33 

0.48 

0.40 

0.33 

0.22 

0.25 

0.65 

0.71 

0.23 

0.19 

0.38 

0.30 

0.45 

0.32 

0.99 

0.36 

0.30 

0.26 

0.20 

0.50 

0.49 

0.38 

0.78 

2.31 

0.44 

0.66 

1.08 

0.48 

0.28 

0.55 

0.81 

0.70 

0.49 

0.29 

0.48 

0.83 

1.09 

0.33 

0.26 

0.56 

0.39 

0.60 

0.42 

1.34 

0.47 

0.47 

0.38 

0.24 

0.68 

0.83 

0.77 

1.08 

3.59 

0.63 

0.94 

1.90 

0.75 

0.40 

1.04 

1.75 

0.90 

0.77 

0.37 

0.60 

0.92 

1.58 

0.49 

0.38 

0.80 

0.50 

1.02 

0.52 

1.76 

0.63 

0.62 

0.55 

0.38 

1.07 

1.20 

2.35 

1.52 

5.89 

0.94 

1.43 

3.11 

1.11 

0.56 

1.87 a 

b 

Source: 

1 = January, 2 = February, etc. 

SD = Standard deviation. 

Adapted from Versar (1990). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Page Exposure Factors Handbook 

19-46 September 2011 
Table 19-26. Distributions of Residential Air Exchange Rates (in ACH)a by Climate Region and Season 

Climate b Region Season Sample Size Arithmetic 

Mean 

Standard 

Deviation 

Percentiles 

10th 25th 50th 75th 90th 

Coldest Winter 

Spring 

Summer 

Fall 

161 

254 

5 

47 

0.36 

0.44 

0.82 

0.25 

0.28 

0.31 

0.69 

0.12 

0.11 

0.18 

0.27 

0.10 

0.18 

0.24 

0.41 

0.15 

0.27 

0.36 

0.57 

0.22 

0.48 

0.53 

1.08 

0.34 

0.71 

0.80 

2.01 

0.42 

Colder Winter 

Spring 

Summer 

Fall 

428 

43 

2 

23 

0.57 

0.52 

1.31 

0.35 

0.43 

0.91 

-

0.18 

0.21 

0.13 

-

0.15 

0.30 

0.21 

-

0.22 

0.42 

0.24 

-

0.33 

0.69 

0.39 

-

0.41 

1.18 

0.83 

-

0.59 

Warmer Winter 

Spring 

Summer 

Fall 

96 

165 

34 

37 

0.47 

0.59 

0.68 

0.51 

0.40 

0.43 

0.50 

0.25 

0.19 

0.18 

0.27 

0.30 

0.26 

0.28 

0.36 

0.30 

0.39 

0.48 

0.51 

0.44 

0.58 

0.82 

0.83 

0.60 

0.78 

1.11 

1.30 

0.82 

Warmest Winter 

Spring 

Summer 

Fall 

454 

589 

488 

18 

0.63 

0.77 

1.57 

0.72 

0.52 

0.62 

1.56 

1.43 

0.24 

0.28 

0.33 

0.22 

0.34 

0.42 

0.58 

0.25 

0.48 

0.63 

1.10 

0.42 

0.78 

0.92 

1.98 

0.46 

1.13 

1.42 

3.28 

0.74 

a 

b 

-

Source: 

ACH = air changes per hour. 

The coldest region was defined as having 7,000 or more heating degree days, the colder region as 5,500–6,999 degree 

days, the warmer region as 2,500–5,499 degree days, and the warmest region as fewer than 2,500 degree days. 

Few observations for summer results in colder regions. Data not available. 

Murray and Burmaster (1995). 

Table 19-27. Air Exchange Rates in Commercial Buildings by Building Type 

Building Type 

N Mean 

(ACHa) SD 10th Percentile Range (ACH) 

Educational 7 1.9 0.8 to 3.0 

Office (<100,000 ft2) 8 1.5 0.3 to 4.1 

Office (>100,000 ft2) 14 1.8 0.7 to 3.6 

Libraries 3 0.6 0.3 to 1.0 

Multi-use 5 1.4 0.6 to 1.9 

Naturally ventilated 3 0.8 0.6 to 0.9 

Total (all commercial) 40 1.5 0.87 0.60b 0.3 to 4.1 

a ACH = air changes per hour. 

b Calculated from data presented in Turk et al. (1987), Table IV.C.1. 

N = Number of observations. 

SD = Standard deviation. 

Source: Turk et al. (1987). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Exposure Factors Handbook Page
 

September 2011 19-47 
 

Table 19-28. Statistics of Estimated Normalized Leakage Distribution Weighted for All Dwellings in the
 

United States
 

Estimated Normalized Leakage Percentiles Estimated House Code 10th 25th 50th 75th 90th 95th 5th GM GSD 

Low income 0.30 0.39 0.62 0.98 1.5 2.2 2.7 0.92 1.9
 

Conventional 0.17 0.21 0.31 0.48 0.75 1.1 1.4 0.49 1.9
 

Whole U.S. 0.17 0.22 0.33 0.52 0.84 1.3 1.7 0.54 2.0 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

Source: Chan et al. (2005). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-29. Particle Deposition During Normal Activities 

Particle Size Range Particle Removal Rate 

(hour–1) 

1–5 

5–10 

10–25 

>25 

0.5 

1.4 

2.4 

4.1 

Source: Adapted from Thatcher and Layton (1995). 

Table 19-30. Deposition Rates for Indoor Particles 

Size Fraction Deposition Rate (hour –1) 

PM2.5 

PM10 

Coarse 

0.39 

0.65 

1.0 

Source: Adapted from Wallace (1996). 

Page Exposure Factors Handbook 

19-48 September 2011 
–1 Table 19-31. Measured Deposition Loss Rate Coefficients (hour )

Room Core Airspeed Room Core Airspeed Room Core Airspeed Fans Off 5.4 cm/second 14.2 cm/s 19.1 cm/second 

Median Particle 

Diameter (μm) 

Bare roomsurfacesCarpetedroomFully furnishedBare roomsurfacesCarpetedroomFully furnishedBare roomsurfacesCarpetedroomFully furnishedBare roomsurfacesCarpetedroomFully furnished 

0.55 1.10 0.12 0.20 0.10 0.13 0.23 0.09 0.18 0.23 0.14 0.16 0.27 

0.65 0.10 0.12 0.20 0.10 0.13 0.23 0.10 0.19 0.24 0.14 0.17 0.28 

0.81 0.10 0.11 0.19 0.10 0.15 0.24 0.11 0.19 0.27 0.15 0.19 0.30 

1.00 0.13 0.12 0.21 0.12 0.20 0.28 0.15 0.23 0.33 0.20 0.25 0.38 

1.24 0.20 0.18 0.29 0.18 0.28 0.38 0.25 0.34 0.47 0.33 0.38 0.53 

1.54 0.32 0.28 0.42 0.27 0.39 0.54 0.39 0.51 0.67 0.51 0.59 0.77 

1.91 0.49 0.44 0.61 0.42 0.58 0.75 0.61 0.78 0.93 0.80 0.89 1.11 

2.37 0.78 0.70 0.93 0.64 0.84 1.07 0.92 1.17 1.32 1.27 1.45 1.60 

2.94 1.24 1.02 1.30 0.92 1.17 1.46 1.45 1.78 1.93 2.12 2.27 2.89 

3.65 1.81 1.37 1.93 1.28 1.58 1.93 2.54 2.64 3.39 3.28 3.13 3.88 

4.53 2.83 2.13 2.64 1.95 2.41 2.95 3.79 4.11 4.71 4.55 4.60 5.46 

5.62 4.41 2.92 3.43 3.01 3.17 3.51 4.88 5.19 5.73 6.65 5.79 6.59 

6.98 5.33 3.97 4.12 4.29 4.06 4.47 6.48 6.73 7.78 10.6 8.33 8.89 

8.66 6.79 4.92 5.45 6.72 5.55 5.77 8.84 8.83 10.5 12.6 11.6 11.6 

Source: Thatcher et al. (2002). 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-32. Total Dust Loading for Carpeted Areas 

Household Total Dust Load 

(g/m2) Fine Dust (<150 μm) Load (g/m2

) 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10.8 

4.2 

0.3 

2.2; 0.8 

1.4; 4.3 

0.8 

6.6 

33.7 

812.7 

6.6 

3.0 

0.1 

1.2; 0.3 

1.0; 1.1 

0.3 

4.7 

23.3 

168.9 

Source: Adapted from Roberts et al. (1991). 

Exposure Factors Handbook Page
 

September 2011 19-49 
 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-33. Particle Deposition and Resuspension During Normal Activities 

Particle Size Range (μm) Particle Deposition Rate (hour –1) Particle Resuspension Rate (hour –1) 

0.3–0.5 

0.6–1 

1–5 

5–10 

10–25 

>25 

(not measured) 

(not measured) 

0.5 

1.4 

2.4 

4.1 

9.9 × 10–7 

4.4 × 10–7 

1.8 × 10–5 

8.3 × 10–5 

3.8 × 10–4 

3.4 × 10–5 

Source: Adapted from Thatcher and Layton (1995). 

Table 19-34. Dust Mass Loading After 1 Week Without Vacuum Cleaning 

Location in Test House Dust Loading (g/m2) 

Tracked area of downstairs carpet 

Untracked area of downstairs carpet 

Tracked area of linoleum 

Untracked area of linoleum 

Tracked area of upstairs carpet 

Untracked area of upstairs carpet 

Front doormat 

2.20 

0.58 

0.08 

0.06 

1.08 

0.60 

43.34 

Source: Adapted from Thatcher and Layton (1995). 

Page Exposure Factors Handbook 

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Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Table 19-35. Simplified Source Descriptions for Airborne Contaminants 

Description Components Dimensions 

Direct emission rate 

Combustion emission rate 

Volume emission rate 

Mass emission rate 

Ef Hf Mf 

Ef = emission factor 

Hf = fuel content 

Mf = fuel consumption rate 

Qp Cp_ε

Qp = volume delivery rate 

Cp = concentration in carrier 

ε = transfer efficiency 

Mp we ε

Mp = mass delivery rate 

we = weight fraction 

ε = transfer efficiency 

Diffusion limited emission rate 

Exponential emission rate 

(Df δ–1 )(Cs – Ci )Ai 

Df = diffusivity 

δ –1 = boundary layer thickness 

Cs = vapor pressure of surface 

Ci = room concentration 

Ai = area 

Ai Eo e –k t 

Ai = area 

Eo = initial unit emission rate 

k = emission decay factor 

t = time 

Transport 

Infiltration 

Interzonal 

Soil gas 

Qji Cj 

Qji = air flow from zone j 

Cj = air concentration in zone j 

g hour

–1 

g J–1 

J mol–1 

mol hour

–1 

g hour

–1 

m3 hour –1 

g m–3 

g g –1 

g hour

–1 

g hour

–1 

g g –1 

g g –1 

g hour

–1 

m 2 hour –1 

meters 

g m–3 

g m–3 

m2 

g hour–1 

m 2 

g hour–1 m–2 

hour–1 

hours 

g hour

–1 

m3 hour –1 

g m–3 

Exposure Factors Handbook Page
 

September 2011 19-51 
 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Air In 

Water In 

Soil In 

Out 

Concentration, C Exposure, E for Occupant(s) 

Decay 

Removal 

Resuspension 

Source 

Reversible 

Sinks 

Figure 19-1. Elements of Residential Exposure. 

Figure 19-2. Configuration for Residential Forced-Air Systems. 

Page Exposure Factors Handbook 

19-52 September 2011 
 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Figure 19-3. Idealized Patterns of Particle Deposition Indoors. 

Source: Adapted from Nazaroff and Cass (1989b). 

Exposure Factors Handbook Page
 

September 2011 19-53 
 

 

Exposure Factors Handbook 

Chapter 19—Building Characteristics 

Figure 19-4. Air Flows for Multiple-Zone Systems. 

Page Exposure Factors Handbook 

19-54 September 2011 
GLOSSARY OF TERMS 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Glossary 

Absorbed dose—The amount of an agent that enters 

a target by crossing an exposure surface that acts as 

an absorption barrier. See also Absorption barrier, 

Dose, and Internal dose. 

Absorption barrier—Any exposure surface that 

may retard the rate of penetration of an agent into a 

target. Examples include the skin, respiratory tract 

lining, and gastrointestinal tract wall. 

Activity pattern data—Information on human 

activities used in exposure assessments. These may 

include a description of the activity, frequency of 

activity, duration spent performing the activity, and 

the microenvironment in which the activity occurs. 

Acute exposure—A single exposure to a toxic 

substance which may result in severe biological harm 

or death. Acute exposures are usually characterized 

as lasting no longer than a day, as compared to 

longer, continuing exposure over a period of time. 

Adherence factor—The amount of a material (e.g., 

soil) that adheres to the skin per unit of surface area. 

Activity pattern (time use) data—Information on 

activities in which various individuals engage, length 

of time spent performing various activities, locations 

in which individuals spend time and length of time 

spent by individuals within those various 

environments. 

Age dependent adjustment factor (ADAF)—In 

cases where age-related differences in toxicity occur, 

differences in both toxicity and exposure need to be 

integrated across all relevant age intervals, by the use 

of age dependent potency adjustment factors 

(ADAFs). This is a departure from the way cancer 

risks have historically been calculated based upon the 

premise that risk is proportional to the daily average 

of the long-term adult dose. 

Agent—Refers to a chemical, biological, or physical 

entity that contacts a target. 

Aggregate exposure—The combined exposure of an 

individual (or defined population) to a specific agent 

or stressor via relevant routes, pathways, and sources. 

Total exposure can include exposure through 

multiple routes (e.g., dermal, inhalation, and 

ingestion). 

Agricultural commodity—Used by U.S. EPA to 

mean plant (or animal) parts consumed by humans as 

food. When such items are raw or unprocessed, they 

are referred to as "raw agricultural commodities." 

Air exchange rate—Rate of air leakage through 

windows, doorways, intakes and exhausts, and 

“adventitious openings” (i.e., cracks and seams) that 

combine to form the leakage configuration of the 

building envelope plus natural and mechanical 

ventilation. 

All water sources—Includes water from all supply 

sources such as community water supply (i.e., tap 

water), bottled water, etc. 

Analytical uncertainty propagation—Examining 

how uncertainty in individual parameters affects the 

overall uncertainty of the exposure assessment. 

Anthropometric—The study of human body 

measurements for use in anthropological 

classification and comparison. 

As-consumed intake—Intake rate based on the 

weight of the food in the form that it is consumed 

(e.g., cooked or prepared). 

Assessment—A determination or appraisal of 

possible consequences resulting from an analysis of 

data. 

Average Daily Dose (ADD)—The mean amount of 

an agent to which a person is exposed on a daily 

basis, often averaged over a long period of time. U.S. 

EPA is transitioning from average daily dose 

methodologies to more refined aggregate and 

cumulative approaches for estimating exposure 

across each lifestage. See also Lifetime average daily 

dose (LADD) and Time-averaged exposure. 

Bayesian Analysis—Bayesian analysis is a method 

of statistical inference in which the knowledge of 

prior events is used to predict future events. Bayes’ 

Theorem is a means of quantifying uncertainty. 

Benchmark Dose or Concentration—An exposure 

due to a dose or concentration of a substance 

associated with a specified low incidence of risk, 

generally in the range of 1% to 10%, of a health 

effect; or the dose or concentration associated with a 

specified measure or change of a biological effect. 

Best Tracer Method (BTM)—Method for 

estimating soil ingestion that allows for the selection 

of the most recoverable tracer for a particular subject 

or group of subjects. Selection of the best tracer is 

made on the basis of the food/soil (F/S) ratio. 

Bioaccumulate—The increase in concentration in 

living organisms as they take in contaminated air, 

water, or food because the substances are very slowly 

metabolized or excreted. 

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Exposure Factors Handbook 

Glossary 

Bias—A systematic error inherent in a method or 

caused by some feature of the measurement system. 

Bioavailability—The rate and extent to which an 

agent can be absorbed by an organism and is 

available for metabolism or interaction with 

biologically significant receptors. Bioavailability 

involves both release from a medium (if present) and 

absorption by an organism. 

Bioconcentrate—The accumulation of a chemical in 

tissues of a fish or other organism to levels greater 

than in the surrounding medium. 

Biokinetic model comparison—A methodology that 

compares direct measurements of a biomarker such 

as blood or urine levels of a toxicant with predictions 

from a biokinetic model. 

Biological marker or biomarker—An indicator of 

changes or events in biological systems. Biological 

markers of exposure are cellular, biochemical, 

analytical, or molecular measures that are obtained 

from biological media such as tissues, cells, or fluids 

and are indicative of exposure to an agent. 

Biomarkers of effect are quantifiable changes, 

indicating exposure to a compound, while biomarkers 

of susceptibility are characteristics that make an 

individual susceptible to the effects of an exposure. 

Biomarker model comparison—A methodology 

that compares results from a biokinetic exposure 

model to biomarker measurements children blood. 

The method is used to confirm assumptions about 

ingested soil and dust quantities in this handbook. 

Basal Metabolic Rate (BMR)—Minimum level of 

energy required to maintain normal body functions. 

Body Mass Index (BMI)—The ratio of weight and 

height squared. 

Bootstrap—A statistical method of resampling data 

use to estimate variance and bias of an estimator and 

provide confidence intervals for parameters. 

Bounding estimate—An estimate of exposure, dose, 

or risk that is higher or lower than that incurred by 

the person with the highest or lowest exposure, dose, 

or risk in the population being assessed. Bounding 

estimates are useful in developing statements that 

exposures, doses, or risks are "not greater than" or 

“less than” the estimated value, because assumptions 

are used which define the likely bounding conditions. 

Central tendency exposure—A measure of the 

middle or the center of an exposure distribution. The 

mean is the most commonly used measure of central 

tendency. 

Chronic exposure—Repeated exposure by the oral, 

dermal, or inhalation route for more than 

approximately 10% of the life span in humans (more 

than approximately 90 days to 2 years in typically 

used laboratory animal species). 

Chronic intake—The long term period over which a 

substance crosses the outer boundary of an organism 

without passing an absorption barrier. 

Classical statistical methods—Estimating the 

population exposure distribution directly, based on 

measured values from a representative sample. 

Coating—Method used to measure skin surface area, 

in which either the whole body or specific body 

regions are coated with a substance of known density 

and thickness. 

Community water—Includes tap water ingested 

from community or municipal water supply. 

Comparability—The ability to describe likenesses 

and differences in the quality and relevance of two or 

more data sets. 

Concentration—Amount of a material or agent 

dissolved or contained in unit quantity in a given 

medium or system. 

Confidence intervals—An estimated range of values 

with a given probability of including the population 

parameter of interest. The range of values is usually 

based on the results of a sample that estimated the 

mean and the sampling error or standard error. 

Consumer-only intake rate—The average quantity 

of food consumed per person in a population 

composed only of individuals who ate the food item 

of interest during a specified period. 

Contact boundary—The surface on a target where 

an agent is present. Examples of outer exposure 

surfaces include the exterior of an eyeball, the skin 

surface, and a conceptual surface over the nose and 

open mouth. Examples of inner exposure surfaces 

include the gastrointestinal tract, the respiratory tract, 

and the urinary tract lining. As an exposure surface 

gets smaller, the limit is an exposure point. It is also 

referred to as an exposure surface. 

Contaminant concentration—Contaminant 

concentration is the concentration of the contaminant 

in the medium (air, food, soil, etc.) contacting the 

body and has units of mass/volume or mass/mass. 

Creel study—A study in which fishermen are 

interviewed while fishing. 

Exposure Factors Handbook Page 

September 2011 G-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure Factors Handbook 

Glossary 

Cumulative exposure—Exposure via mixtures of 

contaminants both indoors and outdoors. Exposure 

may also occur through more than one pathway. New 

directions in risk assessments in U.S. EPA put more 

emphasis on total exposures via multiple pathways. 

Deposition—The removal of airborne substances to 

available surfaces that occurs as a result of 

gravitational settling and diffusion, as well as 

electrophoresis and thermophoresis. 

Dermal absorption—A route of exposure by which 

substances can enter the body through the skin. 

Dermal adherence—The loading of a substance 

onto the outer surface of the skin. 

Diary study—Survey in which individuals are asked 

to record food intake, activities, or other factors in a 

diary which is later used to evaluate exposure factors 

associated with specific populations. 

Direct water ingestion—Consumption of plain 

water as a beverage. It does not include water used 

for preparing beverages such as coffee or tea. 

Distribution—A set of values derived from a 

specific population or set of measurements that 

represents the range and array of data for the factor 

being studied. 

Doers—Survey respondents who report participating 

in a specified activity. 

Dose—The amount of an agent that enters a target 

after crossing an exposure surface. If the exposure 

surface is an absorption barrier, the dose is an 

absorbed dose. If the exposure surface is not an 

absorption barrier, the dose is an intake dose. 

Dose rate—Dose per unit time. 

Dose-response assessment—Analysis of the 

relationship between the total amount of an agent 

administered to, taken up by, or absorbed by an 

organism, system, or target population and the 

changes developed in that organism, system, or target 

population in reaction to that agent, and inferences 

derived from such an analysis with respect to the 

entire population. Dose-response assessment is the 

second of four steps in risk assessment. 

Dose-response curve—Graphical presentation of a 

dose-response relationship. 

Dose-response relationship—The resulting 

biological responses in an organ or organism 

expressed as a function of a series of doses. 

Dressed weight—The portion of the harvest brought 

into kitchens for use, including bones for particular 

species. 

Drinking water— All fluids consumed by 

individuals to satisfy body needs for internal water. 

Dry-weight intake rates—Intake rates that are based 

on the weight of the food consumed after the 

moisture content has been removed. 

Dust Ingestion—Consumption of dust that results 

from various behaviors including, but not limited to, 

mouthing objects or hands, eating dropped food, 

consuming dust directly, or inhaling dust that passes 

from the respiratory system into the gastrointestinal 

tract. 

Effect—Change in the state or dynamics of an 

organism, system, or (sub) population caused by 

exposure to an agent. 

Employer tenure—The length of time a worker has 

been with the same employer. 

Energy expenditures—The amount of energy 

expended by an individual during activities. 

Exclusively breast fed—Infants whose sole source 

of milk comes from human milk with no other milk 

substitutes. 

Exposed foods—Foods grown above ground. 

Exposure—Contact between an agent and a target. 

Exposure assessment—The process of estimating or 

measuring the magnitude, frequency, and duration of 

exposure to an agent, along with the number and 

characteristics of the population exposed. 

Exposure concentration—The concentration of a 

chemical in its transport or carrier medium at the 

point of contact. 

Exposure duration—Length of time over which 

contact with the contaminant lasts. 

Exposure event—The occurrence of continuous 

contact between an agent and a target. 

Exposure factor—Factors related to human behavior 

and characteristics that help determine an individual's 

exposure to an agent. 

Exposure frequency—The number of exposure 

events in an exposure duration. 

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Exposure Factors Handbook 

Glossary 

Exposure loading—The exposure mass divided by 

the exposure surface area. For example, a dermal 

exposure measurement based on a skin wipe sample, 

expressed as a mass of residue per skin surface area, 

is an exposure loading. 

Exposure pathway—The physical course a chemical 

takes from the source to the organism exposed. 

Exposure route—The way a chemical pollutant 

enters an organism after contact, e.g., by ingestion, 

inhalation, or dermal absorption. 

Exposure scenario—A set of facts, assumptions, and 

interferences about how exposure takes place that 

aids the exposure assessor in evaluating estimating, 

or quantifying exposures. 

Exposure surface—See contact boundary. 

Fate—Pattern of distribution of an agent, its 

derivatives, or metabolites in an organism, system, 

compartment, or population of concern as a result of 

transport, partitioning, transformation, or 

degradation. 

Foremilk—Milk produced at the beginning of 

breastfeeding. 

General population—The total of individuals 

inhabiting an area or making up a whole group. 

Geographic information system (GIS)—GIS is a 

system of hardware and software that captures, 

stores, analyzes, manages, and presents geographic 

data. 

Geometric mean—The nth root of the product of n 

values. 

Geophagy—A form of soil ingestion involving the 

intentional ingestion of earths, usually associated 

with cultural practices. 

Hazard—Inherent property of an agent or situation 

having the potential to cause adverse effects when an 

organism, system, or population is exposed to that 

agent. 

Hazard assessment—A process designed to 

determine the possible adverse effects of an agent or 

situation to which an organism, system, or target 

population could be exposed. The process typically 

includes hazard identification, dose-response 

evaluation and hazard characterization. The process 

focuses on the hazard, in contrast to risk assessment, 

where exposure assessment is a distinct additional 

step. 

High-end exposure—An estimate of individual 

exposure or dose for those persons at the upper end 

of an exposure or dose distribution, conceptually 

above the 90th percentile, but not higher than the 

individual in the population who has the highest 

exposure or dose. See also Bounding estimate. 

Hindmilk—Milk produced at the end of the 

breastfeeding. 

Home-produced foods—Fruits and vegetables 

produced by home gardeners, meat and dairy 

products derived form consumer-raised livestock, 

game meat, and home caught fish. 

Human Equivalent Concentration or Dose—The 

human concentration (for inhalation exposure) or 

dose (for other routes of exposure) of an agent that is 

believed to induce the same magnitude of toxic effect 

as the experimental animal species concentration or 

dose. This adjustment may incorporate toxicokinetic 

information on the particular agent, if available, or 

use a default procedure, such as assuming that daily 

oral doses experienced for a lifetime are proportional 

to body weight raised to the 0.75 power. 

Indirect water ingestion—Includes water added 

during food preparation, but not water intrinsic to 

purchased foods. Indirect water includes for example, 

water used to prepare baby formulas, cake mix, and 

concentrated orange juice. 

Indoor settled dust—Particles in building interiors 

that have settled onto objects, surfaces, floors, and 

carpeting. These particles may include soil particles 

that have been tracked into the indoor environment 

from outdoors. 

Infiltration—Air leakage through random cracks, 

interstices, and other unintentional openings in the 

building envelope. 

Inhalation dosimetry—Process of measuring or 

estimating inhaled dose. 

Inhalation unit risk—The upper-bound excess 

lifetime cancer risk estimated to result from 

continuous exposure to an agent at a concentration of 

1 μg/m3 in air for a lifetime. 

Inhaled dose—The amount of an inhaled substance 

that is available for interaction with metabolic 

processes or biologically significant receptors after 

crossing the outer boundary of an organism. 

Insensible water loss—Evaporative water losses that 

occur during breastfeeding. Corrections are made to 

account for insensible water loss when estimating 

breast milk intake using the test weighing method. 

Exposure Factors Handbook Page 

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Exposure Factors Handbook 

Glossary 

Intake—The process by which a substance crosses 

the outer boundary of an organism without passing an 

absorption barrier (e.g., through ingestion or 

inhalation). 

Intake dose—The amount of an agent that enters a 

target by crossing an exposure surface that does not 

act as an absorption barrier. See also Absorption 

barrier and Dose. 

Intake rate—Rate of inhalation, ingestion, and 

dermal contact depending on the route of exposure. 

For ingestion, the intake rate is simply the amount of 

food containing the contaminant of interest that an 

individual ingests during some specific time period 

(units of mass/time). For inhalation, the intake rate is 

the rate at which contaminated air is inhaled. Factors 

that affect dermal exposure are the amount of 

material that comes into contact with the skin, and 

the rate at which the contaminant is absorbed. 

Inter-individual variability—Variations between 

individuals in terms of human characteristics such as 

age or body weight, or behaviors such as location, 

activity patterns, and ingestion rates. 

Internal dose—The amount of an agent that enters a 

target by crossing an exposure surface that acts as an 

absorption barrier. Synonymous with absorbed dose. 

See also Absorption barrier and Dose. 

Interzonal air flows—Transport of air through 

doorways, ductwork, and service chaseways that 

interconnect rooms or zones within a building. 

Intra-individual variability—Fluctuations in an 

individual’s physiologic (e.g., body weight), or 

behavioral characteristics (e.g., ingestion rates or 

activity patterns). 

Key study—A study that is the most up-to-date and 

scientifically sound for deriving recommendations for 

exposure factors. Alternatively, studies may be 

classified as “relevant” and not “key” for one or more 

of the following: (1) they provide supporting data 

(e.g., older studies on food intake that may be useful 

for trend analysis); (2) they provide information 

related to the factor of interest (e.g., data on 

prevalence of breast feeding); or (3) the study design 

or approach makes the data less applicable for 

exposure assessment purposes (e.g., studies with 

small sample size, studies not conducted in the 

United States). As new data or analyses are 

published, “key” studies may be moved to the 

“relevant” category because they are replaced by 

more up-to-date data or an analysis of improved 

quality. 

Lead isotope ratio methodology—A method that 

measures different lead isotopes in children’s blood 

and/or urine, food, water, and house dust and 

compares the ratio of these isotopes to infer sources 

of lead exposure that may include dust or other 

environmental exposures. 

Life expectancy—The length of an individual’s life. 

Lifestage—A distinguishable time frame in an 

individual’s life characterized by unique and 

relatively stable behavioral and/or physiological 

characteristics that are associated with development 

and growth. 

Lifetime Average Daily Dose (LADD)—Dose rate 

averaged over a lifetime. The LADD is used for 

compounds with carcinogenic or chronic effects. The 

LADD is usually expressed in terms of mg/kg-day or 

other mass/mass-time units. Often used in carcinogen 

risk assessments that employ linear low-dose 

extrapolation methods. See also Average daily dose 

and Time-averaged exposure. 

Limiting Tracer Method (LTM)—Method for 

evaluating soil ingestion that assumes that the 

maximum amount of soil ingested corresponds with 

the lowest estimate from various tracer elements. 

Local circulation—Convective and adjective air 

circulation and mixing within a room or within a 

zone. 

Long-term exposure—Repeated exposure for more 

than 30 days, up to approximately 10% of the life 

span in humans (more than 30 days). 

Lowest-Observed-Adverse-Effect Level 

(LOAEL)—The lowest exposure level at which there 

are biologically significant increases in frequency or 

severity of adverse effects between the exposed 

population and its appropriate control group. 

Margin of safety—For some experts, margin of 

safety has the same meaning as margin of exposure, 

while for others, margin of safety means the margin 

between the reference dose and the actual exposure. 

Mass-balance/tracer techniques—Method for 

evaluating soil intake that accounts for both inputs 

and outputs of tracer elements. Tracers in soil, food, 

medicine and other ingested items as well as in feces 

and urine are accounted for. 

Mean value—Simple or arithmetic average of a 

range of values, computed by dividing the total of all 

values by the number of values. 

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Glossary 

Measurement error—A systematic error arising 

from inaccurate measurement (or classification) of 

subjects on the study variables. 

Measurement end-point—Measurable (ecological) 

characteristic that is related to the valued 

characteristic chosen as an assessment point. 

Mechanical ventilation—Controlled air movement 

driven by fans. Also referred to as forced ventilation. 

Median value—The value in a measurement data set 

such that half the measured values are greater and 

half are less. 

Metabolic Equivalent of Work (MET)—A 

dimensionless energy expenditure metric used to 

represent an activity level. 

Microenvironment—Surroundings that can be 

treated as homogeneous or well characterized in the 

concentrations of an agent (e.g., home, office, 

automobile, kitchen, store). 

Mode of action—Defined as a sequence of key 

events and processes, starting with interaction of an 

agent with a cell, proceeding through operational and 

anatomical changes, and resulting in cancer 

formation. 

Model uncertainty—Uncertainty regarding gaps in 

scientific theory required to make predictions on the 

basis of causal inferences. 

Moisture content—The portion of foods made up by 

water. The percent water is needed for converting 

food intake rates and residue concentrations between 

whole-weight and dry-weight values. 

Monte Carlo technique—A repeated random 

sampling from the distribution of values for each of 

the parameters in a generic (exposure or dose) 

equation to derive an estimate of the distribution of 

(exposures or doses in) the population. 

Mouthing behavior—Activities in which objects, 

including fingers, are touched by the mouth or put 

into the mouth except for eating and drinking, and 

includes licking, sucking, chewing, and biting. 

Natural ventilation—Airflow through open 

windows, doors, and other designed openings in the 

building envelope. 

Non-dietary ingestion— Ingestion of non-food 

substances, typically resulting from the mouthing of 

hands and objects. 

No-Observed-Adverse-Effect-Level (NOAEL)— 

The highest exposure level at which there are no 

biologically significant increases in the frequency or 

severity of adverse effect between the exposed 

population and its appropriate control; some effects 

may be produced at this level, but they are not 

considered adverse or precursors of adverse effects. 

Occupational mobility—An indicator of the 

frequency at which workers change from one 

occupation to another. 

Occupational tenure—The cumulative number of 

years a person worked in his or her current 

occupation, regardless of number of employers, 

interruptions in employment, or time spent in other 

occupations. 

Outdoor settled dust—Particles that have settled 

onto outdoor objects and surfaces due to either wet or 

dry deposition. 

Oxygen consumption (VO2)—The rate at which 

oxygen is used by tissues. 

Parameter uncertainty—Uncertainty regarding 

some parameter. 

Partially breast fed—Infants whose source of milk 

comes from both human milk and other milk 

substitutes. 

Pathway—The physical course a chemical or 

pollutant takes from the source to the organism 

exposed. 

Physiologically-based pharmacokinetic (PBPK) 

modeling—PBPK modeling is an approach for 

predicting the absorption, distribution, metabolism 

and excretion of a compound in humans. 

Per capita intake rate—The average quantity of 

food consumed per person in a population composed 

of both individuals who ate the food during a 

specified time period and those that did not. 

Pica—Pica behavior is the repeated eating of 

non-nutritive substances, whereas soil-pica is a form 

of soil ingestion that is characterized by the recurrent 

ingestion of unusually high amounts of soil (i.e., on 

the order of 1,000–5,000 milligrams per day or 

more). 

Plain tap water—Excludes tap water consumed in 

the form of juices and other beverages containing tap 

water. 

Population mobility—An indicator of the frequency 

at which individuals move from one residential 

location to another. 

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Glossary 

Population risk descriptor—An assessment of the 

extent of harm to the population being addressed. It 

can be either an estimate of the number of cases of a 

particular effect that might occur in a population (or 

population segment), or a description of what fraction 

of the population receives exposures, doses, or risks 

greater than a specified value. 

Potential dose—The amount of a chemical contained 

in material ingested, air breathed, or bulk material 

applied to the skin. 

Poverty/income ratio—Ratio of reported family 

income to federal poverty level. 

Precision—A measure of the reproducibility of a 

measured value under a given set of circumstances. 

Preparation losses—Net cooking losses, which 

include dripping and volatile losses, post cooking 

losses, which involve losses from cutting, bones, 

excess fat, scraps and juices, and other preparation 

losses which include losses from paring or coring. 

Primary data/analysis— Information gathered from 

observations or measurements of a phenomena or the 

surveying of respondents. 

Probabilistic uncertainty analysis—Technique that 

assigns a probability density function to each input 

parameter, then randomly selects values from each of 

the distributions and inserts them into the exposure 

equation. Repeated calculations produce a 

distribution of predicted values, reflecting the 

combined impact of variability in each input to the 

calculation. Monte Carlo is a common type of 

probabilistic Uncertainty analysis. 

Protected products—Foods that have an outer 

protective coating that is typically removed before 

consumption. 

Questionnaire/survey response—A “question and 

answer” data collection methodology conducted via 

in-person interview, mailed questionnaire, or 

questions administered in a test format in a school 

setting. 

Random samples—Samples selected from a 

statistical population such that each sample has an 

equal probability of being selected. 

Range—The difference between the largest and 

smallest values in a measurement data set. 

Ready-to-feed—Infant and baby products (formula, 

juices, beverages, baby food), and table foods that do 

not need to have water added to them prior to 

feeding. 

Real-time hand recording—Method by which 

trained observers manually record information on 

children’s behavior. 

Reasonable maximum exposure—A 

semiquantitative term referring to the lower portion 

of the high end of the exposure, dose, or risk 

distribution. As a semiquantitative term, it should 

refer to a range that can conceptually be described as 

above the 90th percentile in the distribution, but 

below the 98th percentile. 

Recreational/sport fishermen—Individuals who 

catch fish as part of a sporting or recreational activity 

and not for the purpose of providing a primary source 

of food for themselves or for their families. 

Reference Concentration (RfC)—An estimate (with 

uncertainty spanning perhaps an order of magnitude) 

of a continuous inhalation exposure to the human 

population (including sensitive target groups) that is 

likely to be without an appreciable risk of deleterious 

effects during a lifetime. It can be derived from a 

NOAEL, LOAEL, or benchmark concentration, with 

uncertainty factors generally applied to reflect 

limitations of the data used. Generally used in 

U.S. EPA's noncancer health assessments. Durations 

include acute, short-term, subchronic, and chronic. 

Reference Dose (RfD)—An estimate (with 

uncertainty spanning perhaps an order of magnitude) 

of a daily oral exposure to the human population 

(including sensitive target groups) that is likely to be 

without an appreciable risk of deleterious noncancer 

effects during a lifetime. It can be derived from a 

NOAEL, LOAEL, or benchmark dose, with 

uncertainty factors generally applied to reflect 

limitations of the data used. Generally used in U.S. 

EPA's noncancer health assessments. Durations 

include acute, short-term, subchronic, and chronic. 

Relevant study—Studies that are applicable or 

pertinent, but not necessarily the most important to 

derive exposure factors. See also Key study. 

Representativeness—The degree to which a sample 

is, or samples are, characteristic of the whole 

medium, exposure, or dose for which the samples are 

being used to make inferences. 

Residential occupancy period—The time between a 

person moving into a residence and the time the 

person moves out or dies. 

Residential volume—The volume (m3

) of the 

structure in which an individual resides and may be 

exposed to airborne contaminants. 

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Glossary 

Risk—The probability of an adverse effect in an 

organism, system, or population caused under 

specified circumstances by exposure to an agent. 

Risk assessment—A process intended to calculate or 

estimate the risk to a given target organism, system, 

or population, including the identification of 

attendant uncertainties, following exposure to a 

particular agent, taking into account the inherent 

characteristics of the agent of concern as well as the 

characteristics of the specific target system. The risk 

assessment process includes four steps: hazard 

identification, hazard characterization (related term: 

Dose-response assessment), exposure assessment, 

and risk characterization. It is the first component in 

a risk analysis process. 

Risk characterization—The qualitative and, 

wherever possible, quantitative determination, 

including attendant uncertainties, of the probability of 

occurrence of known and potential adverse effects of 

an agent in a given organism, system, or population, 

under defined exposure conditions. Risk 

characterization is the fourth step in the risk 

assessment process. 

Risk communication—Interactive exchange of 

information about (health or environmental) risks 

among risk assessors, managers, news media, 

interested groups, and the general public. 

Route—The way a chemical or pollutant enters an 

organism after contact, e.g., by ingestion, inhalation, 

or dermal absorption. 

Sample—A small part of something designed to 

show the nature or quality of the whole. 

Exposure-related measurements are usually samples 

of environmental or ambient media, exposures of a 

small portion of a population for a short time, or 

biological samples, all for the purpose of inferring the 

nature and quality of parameters important to 

evaluating exposure. 

Scenario uncertainty—Uncertainty regarding 

missing or incomplete information needed to fully 

define exposure and dose. 

Screening-level assessment—An exposure 

assessment that examines exposures that would fall 

on or beyond the high end of the expected exposure 

distribution. 

Secondary data/analysis—The reanalysis of data 

collected by other individuals or group; an analysis of 

data for purposes other than those for which the data 

were originally collected. 

Sensitivity analysis—Process of changing one 

variable while leaving the others constant to 

determine its effect on the output. This procedure 

fixes each uncertain quantity at its credible lower and 

upper bounds (holding all others at their nominal 

values, such as medians) and computes the results of 

each combination of values. The results help to 

identify the variables that have the greatest effect on 

exposure estimates and help focus further 

information-gathering efforts. 

Serving sizes—The quantities of individual foods 

consumed per eating occasion. These estimates may 

be useful for assessing acute exposures. 

Short-term exposure—Repeated exposure for more 

than 24 hours, up to 30 days. 

Slope Factor—An upper bound, approximating a 

95% confidence limit, on the increased cancer risk 

from a lifetime exposure to an agent. This estimate, 

usually expressed in units of proportion (of a 

population) affected per mg/kg-day, is generally 

reserved for use in the low-dose region of the doseresponse relationship, that is, for exposures 

corresponding to risks less than 1 in 100. 

Soil—Particles of unconsolidated mineral and/or 

organic matter from the earth’s surface that are 

located outdoors, or are used indoors to support plant 

growth. 

Soil adherence—The quantity of soil that adheres to 

the skin and from which chemical contaminants are 

available for uptake at the skin surface. 

Soil ingestion—The intentional or unintentional 

consumption of soil, resulting from various behaviors 

including, but not limited to, mouthing, contacting 

dirty hands, eating dropped food, or consuming soil 

directly. Soil-pica is a form of soil ingestion that is 

characterized by the recurrent ingestion of unusually 

high amounts of soil (i.e., on the order of 1,000– 

5,000 milligrams per day or more). Geophagy is also 

a form of soil ingestion defined as the intentional 

ingestion of earths and is usually associated with 

cultural practices. 

Spatial variability—Variability across location, 

whether long- or short-term. 

Subchronic exposure—Repeated exposure by the 

oral, dermal, or inhalation route for more than 30 

days, up to approximately 10% of the life span in 

humans (more than 30 days up to approximately 90 

days in typically used laboratory animal species). 

Subsistence fishermen—Individuals who consume 

fresh caught fish as a major source of food. 

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Glossary 

Surface area—Coating, triangulation, and surface 

integration are direct measurement techniques that 

have been used to measure total body surface area 

and the surface area of specific body parts. 

Consideration has been given for differences due to 

age, gender, and race. Surface integration is 

performed by using a planimeter and adding the 

areas. 

Surface integration—Method used to measure skin 

surface area in which a planimeter is used to measure 

areas of the skin, and the areas of various surfaces are 

summed. 

Survey response methodology—Responses to 

survey questions are analyzed. This methodology 

includes questions asked of children directly, or their 

care givers, about behaviors affecting exposures. 

Target—refers to any physical, biological, or 

ecological object exposed to an agent. 

Tap water from food manufacturing—Water used 

in industrial production of foods. 

Temporal variability—Variability over time, 

whether long- or short-term. 

Threshold—Dose or exposure concentration of an 

agent below which a stated effect is not observed or 

expected to occur. 

Time-averaged exposure—The time-integrated 

exposure divided by the exposure duration. An 

example is the daily average exposure of an 

individual to carbon monoxide. (Also called 

timeweighted average exposure.) 

Total dietary intake—The sum of all foods in the 

following food categories: dairy, meats, fish, eggs, 

grains, vegetables, fruits, and fats. It does not include 

beverages, sugar, candy, sweets, nuts and nut 

products. 

Total tap water—Water consumed directly from the 

tap as a beverage or used in the preparation of foods 

and beverages (i.e., coffee, tea, frozen juices, soups, 

etc.). 

Total fluid intake—Consumption of all types of 

fluids including tapwater, milk, soft drinks, alcoholic 

beverages, and water intrinsic to purchased foods. 

Total water—Water from tap water and non tap 

water sources including water contained in food. 

Toxicodynamics—The physiological mechanisms by 

which toxins are absorbed, distributed, metabolized 

and excreted 

Toxicokinetics—The passage through the body of a 

toxic agent or its metabolites, usually in an action 

similar to that of pharmacokinetics. 

Tracer-element studies—Soil ingestion studies that 

use trace elements found in soil and poorly 

metabolized in the human gut as indicators of soil 

intake. 

Triangulation—Method used to measure skin 

surface area in which areas of the body are marked 

into geometric figures, then their linear dimensions 

are calculated. 

Uncertainty—Uncertainty represents a lack of 

knowledge about factors affecting exposure or risk 

and can lead to inaccurate or biased estimates of 

exposure. The types of uncertainty include: scenario, 

parameter, and model. 

Unit risk—The quantitative estimate in terms of 

either risk per μg/L drinking water (water unit risk) 

or risk per μg/m3 air breathed (air unit risk). 

Upper percentile—Values in the upper tail (i.e., 

between 90th and 99.9th percentile) of the distribution 

of values for a particular exposure factor. Values at 

the upper end of the distribution of values for a 

particular set of data. 

Uptake—The process by which a substance crosses 

an absorption barrier and is absorbed into the body. 

Usual dietary intakes— Refers to the long-term 

average daily intake by an individual. 

Vapor intrusion—The migration of volatile 

chemicals from contaminated groundwater or soil 

into an overlying building. 

Variability—Variability arises from true 

heterogeneity across people, places or time and can 

affect the precision of exposure estimates and the 

degree to which they can be generalized. The types of 

variability include: spatial, temporal, and 

inter-individual. 

Ventilation Rate (VR)—Alternative term for 

inhalation rate or breathing rate. Usually measured as 

minute volume, i.e., volume (liters) of air exhaled per 

minute. 

Video transcription—Method by which trained 

videographers tape a child’s activities and 

subsequently extract data manually with computer 

software. 

Wet-weight intake rates—Intake rates that are 

based on the wet (or whole) weight of the food 

consumed. This in contrast to dry-weight intake rates. 

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Exposure Factors Handbook 

Glossary 

Worst case scenario—The maximum possible 

exposure, when everything that can plausibly happen 

to maximize exposure happens. The worst case 

represents a hypothetical individual and an extreme 

set of conditions that usually will not be observed in 

an actual population. 

GLOSSARY ENTRIES ADAPTED FROM: 

International Programme on Chemical Safety. (2004) 

IPCS risk assessment terminology. 

Available online at:

http://www.who.int/ipcs/methods/harmoniza 

tion/areas/ipcsterminologyparts1and2.pdf 

U.S. EPA (Environmental Protection Agency). 

(1992) Guidelines for exposure assessment. 

Office of Research and Development, Office 

of Health and Environmental Assessment, 

Washington, DC; EPA/600/2-92/001. 

U.S. EPA. (Environmental Protection Agency) 

(1997) Exposure factors handbook revised. 

Office of Research and Development, 

Washington, DC; EPA/600/P-95/002F. 

U.S. EPA (Environmental Protection Agency) (2005) 

Guidelines for carcinogen risk assessment. 

Risk Assessment Forum, Washington, DC; 

EPA/630/P-03/001F. Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.c 

fm?deid=116283. 

Zartarian, VG, Ott, WR, Duan, N. (2007). Basic 

concepts and definitions of exposure and 

dose. In: Ott, W.R., Steinemann, A.C., and 

Wallace, L.A. (Eds.). Exp Anal 33–63. Boca 

Raton, FL: CRC Press, Taylor & Francis 

Group. 

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