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EPA/600/R-06/096F | September 2008 | www.epa.gov/ncea Child-Specific Exposure Factors Handbo

EPA/600/R-06/096F 
Child-Specific Exposure Factors Handbook 

CSEFH 

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. 

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TABLE OF CONTENTS 

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

1.1	 PURPOSE .............................................................. . 1-1
 

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

1.3	 BACKGROUND ......................................................... . 1-1
 

1.4	 SELECTION OF STUDIES FOR THE HANDBOOK ............................. . 1-3
 

1.4.1	 General Assessment Factors .......................................... . 1-4
 

1.4.2	 Selection Criteria .................................................. . 1-4
 

1.5	 APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE 

FACTORS .............................................................. . 1-6
 

1.6	 SUGGESTED REFERENCES FOR USE IN CONJUNCTION WITH THIS HANDBOOK . . 1-8
 

1.7	 THE USE OF AGE GROUPINGS WHEN ASSESSING EXPOSURE ................. . 1-9
 

1.8	 CONSIDERING LIFESTAGE WHEN CALCULATING EXPOSURE AND RISK ...... . 1-11
 

1.9	 FUNDAMENTAL PRINCIPLES OF EXPOSURE ASSESSMENT .................. . 1-11
 

1.9.1	 Dose Equations ................................................... . 1-12
 

1.9.2	 Use of Exposure Factors Data in Probabilistic Analyses .................... . 1-14
 

1.10	 CUMULATIVE EXPOSURES .............................................. . 1-15
 

1.11	 ORGANIZATION ....................................................... . 1-15
 

1.12	 REFERENCES FOR CHAPTER 1 ........................................... . 1-16
 

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

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

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

2.3	 ADDRESSING VARIABILITY .............................................. . 2-3
 

2.4	 TYPES OF UNCERTAINTY ................................................ . 2-4
 

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

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

2.7	 PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS ...... . 2-5
 

2.8	 REFERENCES FOR CHAPTER 2 ............................................ . 2-6
 

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	 Water Ingestion while Swimming ...................................... . 3-2
 

3.3	 DRINKING WATER INGESTION STUDIES ................................... . 3-6
 

3.3.1	 Key Drinking Water Ingestion Study ................................... . 3-6
 

3.3.1.1 Kahn and Stralka, 2008 ...................................... . 3-6
 

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3.3.2 Relevant Drinking Water Ingestion Studies .............................. . 3-7
 

3.3.2.1 Levy et al., 1995 ............................................ . 3-7
 

3.3.2.2 Heller et al., 2000 ........................................... . 3-8
 

3.3.2.3 Sichert-Hellert et al., 2001 .................................... . 3-8
 

3.3.2.4 Sohn et al., 2001 ............................................ . 3-9
 

3.3.2.5 Hilbig et al., 2002 .......................................... . 3-10
 

3.3.2.6 Marshall et al., 2003a ....................................... . 3-10
 

3.3.2.7 Marshall et al., 2003b ....................................... . 3-11
 

3.3.2.8 Skinner et al., 2004 ......................................... . 3-11
 

3.4 WATER INGESTION WHILE SWIMMING ................................... . 3-11
 

3.4.1 Dufour et al., 2006 ................................................ . 3-11
 

3.5 REFERENCES FOR CHAPTER 3 ........................................... . 3-12
 

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 ........................................... . 4-7
 

4.3.1.5 Black et al., 2005 ........................................... . 4-7
 

4.3.1.6 Xue et al., 2007 ............................................. . 4-8
 

4.3.2 Relevant Studies of Mouthing Frequency ................................ . 4-8
 

4.3.2.1 Davis et al., 1995 ........................................... . 4-8
 

4.3.2.2 Lew and Butterworth, 1997 .................................... . 4-9
 

4.3.2.3 Tudella et al., 2000 ......................................... . 4-10
 

4.3.2.4 AuYeung et al., 2004 ....................................... . 4-10
 

4.3.2.5 Ko et al., 2007 ............................................ . 4-11
 

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 ............................................. . 4-12
 

4.4.2 Relevant Mouthing Duration Studies .................................. . 4-13
 

4.4.2.1 Barr et al., 1994 ........................................... . 4-13
 

4.4.2.2 Zartarian et al., 1997a/Zartarian et al., 1997b/Zartarian et al., 1998 .... . 4-14
 

4.4.2.3 Groot et al., 1998 .......................................... . 4-14
 

4.4.2.4 Smith and Norris, 2003/Norris and Smith, 2002 ................... . 4-15
 

4.4.2.5 Au Yeung et al, 2004 ....................................... . 4-16
 

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4.5 MOUTHING PREVALENCE .............................................. . 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
 

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

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

5.2 RECOMMENDATIONS ................................................... . 5-2
 

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 Survey Response 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/Barnes, 1990/Calabrese et al., 1991 ............ . 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/Calabrese et al., 1997b ........................ . 5-11
 

5.3.2.7 Davis and Mirick, 2006 ..................................... . 5-12
 

5.3.3 Key Studies of Secondary Analysis .................................... . 5-12
 

5.3.3.1 Wong, 1988/Calabrese and Stanek, 1993 ........................ . 5-12
 

5.3.3.2 Hogan et al., 1998 .......................................... . 5-13
 

5.3.4 Relevant Studies of Primary Analysis .................................. . 5-13
 

5.3.4.1 Dickins and Ford, 1942 ...................................... . 5-14
 

5.3.4.2 Cooper, 1957 ............................................. . 5-14
 

5.3.4.3 Barltrop, 1966 ............................................. . 5-14
 

5.3.4.4 Bruhn and Pangborn, 1971 ................................... . 5-14
 

5.3.4.5 Robischon, 1971 ........................................... . 5-14
 

5.3.4.6 Binder et al., 1986 ......................................... . 5-15
 

5.3.4.7 Clausing, et al., 1987 ....................................... . 5-15
 

5.3.4.8 Smulian et al., 1995 ........................................ . 5-16
 

5.3.5 Relevant Studies of Secondary Analysis ................................ . 5-16
 

5.3.5.1 Stanek et al., 2001a ......................................... . 5-16
 

5.3.5.2 Calabrese and Stanek, 1995 .................................. . 5-17
 

5.3.5.3 Stanek and Calabrese, 1995a .................................. . 5-17
 

5.3.5.4 Calabrese and Stanek, 1992b ................................. . 5-18
 

5.3.5.5 Calabrese et al., 1996 ....................................... . 5-18
 

5.3.5.6 Stanek et al., 1999 ......................................... . 5-19
 

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5.3.5.7 Stanek and Calabrese, 1995b ................................. . 5-19
 

5.3.5.8 Stanek and Calabrese, 2000 .................................. . 5-19
 

5.3.5.9 Stanek et al., 2001b ......................................... . 5-19
 

5.3.5.10 von Lindern et al., 2003 ..................................... . 5-20
 

5.4 LIMITATIONS OF KEY STUDY METHODOLOGIES .......................... . 5-20
 

5.4.1 Tracer Element Methodology ........................................ . 5-20
 

5.4.2 Biokinetic Model Comparison Methodology ............................. . 5-23
 

5.4.3 Survey Response Methodology ....................................... . 5-23
 

5.4.4 Key Studies: Representativeness of U.S. Population ....................... . 5-24
 

5.5 SUMMARY OF SOIL AND DUST INGESTION ESTIMATES FROM KEY STUDIES . . . 5-25
 

5.6 REFERENCES FOR CHAPTER 5 ........................................... . 5-26
 

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

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

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

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

6.3.1 Brochu et al., 2006 ................................................. . 6-6
 

6.3.2 U.S. EPA, 2006 ................................................... . 6-6
 

6.3.3 Arcus-Arth and Blaisdell, 2007 ....................................... . 6-8
 

6.3.4 Stifelman, 2007 ................................................... . 6-9
 

6.3.5 Key Studies Combined .............................................. . 6-9
 

6.4 RELEVANT INHALATION RATE STUDIES .................................. . 6-9
 

6.4.1 International Commission on Radiological Protection (ICRP), 1981 ........... . 6-9
 

6.4.2 U.S. EPA, 1985 .................................................. . 6-10
 

6.4.3 Linn et al., 1992 .................................................. . 6-10
 

6.4.4 Spier et al., 1992 ................................................. . 6-11
 

6.4.5 Adams, 1993 .................................................... . 6-11
 

6.4.6 Layton, 1993 .................................................... . 6-12
 

6.4.7 Rusconi et al., 1994 ............................................... . 6-14
 

6.4.8 Price et al., 2003 .................................................. . 6-14
 

6.5 REFERENCES FOR CHAPTER 6 ........................................... . 6-15
 

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 .......................................... . 7-2
 

7.3 SURFACE AREA ....................................................... . 7-10
 

7.3.1 Key Body Surface Area Studies ...................................... . 7-10
 

7.3.1.1 U.S. EPA, 1985 ........................................... . 7-10
 

7.3.1.2 U.S. EPA Analysis of NHANES 1999-2006 Data .................. . 7-10
 

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7.3.2 Relevant Body Surface Area Studies ................................... . 7-10
 

7.3.2.1 Phillips et al., 1993 ......................................... . 7-10
 

7.3.2.2 Wong et al., 2000 .......................................... . 7-11
 

7.4 ADHERENCE OF SOLIDS TO SKIN ........................................ . 7-11
 

7.4.1 Key Adherence of Solids to Skin Studies ............................... . 7-11
 

7.4.1.1 Kissel et al., 1996a ......................................... . 7-11
 

7.4.1.2 Holmes et al., 1999 ......................................... . 7-12
 

7.4.1.3 Shoaf et al., 2005 .......................................... . 7-12
 

7.4.2 Relevant Adherence of Solids to Skin Studies ............................ . 7-13
 

7.4.2.1 Kissel et al., 1996b ......................................... . 7-13
 

7.4.2.2 Kissel et al., 1998 .......................................... . 7-13
 

7.5 REFERENCES FOR CHAPTER 7 ........................................... . 7-14
 

APPENDIX 7A ...................................................................... . 7A-1
 

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 BODY WEIGHT STUDIES ...................................... . 8-4
 

8.4.1 National Center for Health Statistics, 1987 .............................. . 8-4
 

8.4.2 Burmaster and Crouch, 1997 ......................................... . 8-5
 

8.4.3 U.S. EPA, 2000 ................................................... . 8-5
 

8.4.4 Kuczmarski et al., 2002 ............................................. . 8-5
 

8.4.5 Ogden et al., 2004 ................................................. . 8-6
 

8.4.6 Freedman et al., 2006 ............................................... . 8-6
 

8.4.7 Martin et al., 2007 ................................................. . 8-7
 

8.4.8 Portier et al., 2007 ................................................. . 8-7
 

8.4.9 Kahn and Stralka, 2008 ............................................. . 8-8
 

8.5 RELEVANT FETAL WEIGHT STUDIES ...................................... . 8-8
 

8.5.1 Brenner et al., 1976 ................................................ . 8-8
 

8.5.2 Doubilet et al., 1997 ................................................ . 8-8
 

8.6 REFERENCES FOR CHAPTER 8 ............................................ . 8-9
 

9 INTAKE OF FRUITS AND VEGETABLES ........................................... . 9-1
 

9.1 INTRODUCTION ........................................................ . 9-1
 

9.2 RECOMMENDATIONS ................................................... . 9-2
 

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9.3	 INTAKE STUDIES ....................................................... . 9-6
 

9.3.1	 Key Fruits and Vegetables Intake Study ................................. . 9-6
 

9.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 ....................... . 9-6
 

9.3.2	 Relevant Fruit and Vegetable Intake Studies .............................. . 9-8
 

9.3.2.1 USDA, 1999 .............................................. . 9-8
 

9.3.2.2 Smiciklas-Wright et al., 2003 ................................. . 9-8
 

9.3.2.3 Fox et al., 2004 ............................................ . 9-9
 

9.3.2.4 Ponza et al., 2004 ........................................... . 9-9
 

9.3.2.5 Menella et al., 2006 ........................................ . 9-10
 

9.3.2.6 Fox et al., 2006 ............................................ . 9-10
 

9.4	 CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES ............ . 9-10
 

9.5	 REFERENCES FOR CHAPTER 9 ........................................... . 9-11

PENDIX 9A ..................................................................... . 9A-1
 

INTAKE OF FISH AND SHELLFISH ............................................... . 10-1
 

10.1	 INTRODUCTION ....................................................... . 10-1
 

10.2	 RECOMMENDATIONS .................................................. . 10-2
 

10.3	 GENERAL POPULATION STUDIES ....................................... . 10-6
 

10.3.1	 Key General Population Study ....................................... . 10-6
 

10.3.1.1 U.S. EPA 2002 ........................................... . 10-6
 

10.3.2	 Relevant General Population Studies .................................. . 10-6
 

10.3.2.1 U.S. EPA, 1996 ........................................... . 10-6
 

10.3.2.2 Moya et al., 2008 .......................................... . 10-7
 

10.4	 MARINE RECREATIONAL STUDIES ....................................... . 10-8
 

10.4.1	 Relevant Marine Recreational Studies .................................. . 10-8
 

10.4.1.1 KCA Research Division, 1994 ................................ . 10-8
 

10.4.1.2 Alcoa, 1998 .............................................. . 10-8
 

10.5	 FRESHWATER RECREATIONAL STUDIES .................................. . 10-9
 

10.5.1	 Relevant Freshwater Recreational Studies ............................... . 10-9
 

10.5.1.1 West et al., 1989 .......................................... . 10-9
 

10.5.1.2 Benson et al., 2001 ....................................... . 10-10
 

10.6	 NATIVE AMERICAN STUDIES .......................................... . 10-10
 

10.6.1	 Relevant Native American Studies ................................... . 10-10
 

10.6.1.1 Columbia River Inter-Tribal Fish Commission (CRITFC), 1994 ..... . 10-10
 

10.6.1.2 Toy et al., 1996 .......................................... . 10-12
 

10.6.1.3 Duncan, 2000 ........................................... . 10-13
 

10.6.1.4 Polissar et al., 2006 ....................................... . 10-13
 

10.7	 SERVING SIZE STUDY ................................................. . 10-14
 

10.7.1	 Smiciklas-Wright et al., 2002 ...................................... . 10-14
 

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10.8	 OTHER FACTORS TO CONSIDER FOR FISH CONSUMPTION ................. . 10-14
 

10.8.1	 Conversion Between Wet and Dry Weight ............................. . 10-14
 

10.8.2	 Conversion Between Wet Weight and Lipid Weight Intake Rates ............ . 10-15
 

10.9	 REFERENCES FOR CHAPTER 10 ......................................... . 10-15
 

11	 INTAKE OF MEATS, DAIRY PRODUCTS AND FATS ................................ . 11-1
 

11.1	 INTRODUCTION ....................................................... . 11-1
 

11.2	 RECOMMENDATIONS .................................................. . 11-2
 

11.3	 INTAKE STUDIES ...................................................... . 11-6
 

11.3.1	 Key Meat and Diary Intake Study ..................................... . 11-6
 

11.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 ...................... . 11-6
 

11.3.2	 Relevant Meat and Dairy Intake Studies ................................ . 11-7
 

11.3.2.1 USDA, 1999a ............................................. . 11-7
 

11.3.2.2 Smiciklas-Wright et al., 2002 ................................. . 11-8
 

11.3.2.3 Fox et al., 2004 ............................................ . 11-8
 

11.3.2.4 Ponza et al., 2004 .......................................... . 11-9
 

11.3.2.5 Mennella et al., 2006 ....................................... . 11-9
 

11.3.2.6 Fox et al., 2006 ........................................... . 11-10
 

11.4	 FAT INTAKE ......................................................... . 11-10
 

11.4.1	 Key Fat Intake Study ............................................. . 11-10
 

11.4.1.1 U.S. EPA, 2007 .......................................... . 11-10
 

11.4.2	 Relevant Fat Intake Studies ........................................ . 11-11
 

11.4.2.1 Cresanta et al., 1988; Nicklas et al., 1993; and Frank et al., 1986 ..... . 11-11
 

11.4.2.2 CDC, 1994 .............................................. . 11-11
 

11.5	 CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES ........... . 11-12
 

11.6	 CONVERSION BETWEEN WET WEIGHT AND LIPID WEIGHT INTAKE RATES . . . 11-12
 

11.7	 REFERENCES FOR CHAPTER 11 ......................................... . 11-13
 

APPENDIX 11A .................................................................... . 11A-1
 

APPENDIX 11B .................................................................... . 11B-1
 

12	 INTAKE OF GRAIN PRODUCTS ................................................. . 12-1
 

12.1	 INTRODUCTION ....................................................... . 12-1
 

12.2	 RECOMMENDATIONS .................................................. . 12-2
 

12.3	 INTAKE STUDIES ...................................................... . 12-6
 

12.3.1	 Key Grain Intake Study ............................................ . 12-6
 

12.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 ............... . 12-6
 

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12.3.2 Relevant Grain Intake Studies ....................................... . 12-7
 

12.3.2.1 USDA, 1999 ....................................... . 12-7
 

12.3.2.2 Smiciklas-Wright et al., 2002 .......................... . 12-8
 

12.3.2.3 Fox et al., 2004 .................................... . 12-8
 

12.3.2.4 Ponza et al., 2004 ................................... . 12-9
 

12.3.2.5 Mennella et al., 2006 ................................ . 12-9
 

12.3.2.6 Fox et al., 2006 ................................... . 12-10
 

12.4 CONVERSION BETWEEN WET AND DRY WEIGHT INTAKE RATES ........... . 12-10
 

12.5 REFERENCES FOR CHAPTER 12 ......................................... . 12-10

 APPENDIX 12A ................................................................... . 12A-1
 

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 ..................... . 13-6
 

13.3.1 U.S. EPA Analysis of NFCS 1987-1988 ................................ . 13-6
 

13.4 REFERENCES FOR CHAPTER 13 .......................................... . 13-8
 

APPENDIX 13A ................................................................... . 13A-1
 

APPENDIX 13B ................................................................... . 13B-1
 

14 TOTAL DIETARY INTAKE ...................................................... . 14-1
 

14.1 INTRODUCTION ....................................................... . 14-1
 

14.2 RECOMMENDATIONS .................................................. . 14-1
 

14.3 KEY STUDY OF TOTAL FOOD INTAKE .................................... . 14-4
 

14.3.1 U.S. EPA, 2007 .................................................. . 14-4
 

14.4 REFERENCES FOR CHAPTER 14 .......................................... . 14-5
 

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 ................................. . 15-10
 

15.3.1 Pao et al., 1980 .................................................. . 15-10
 

15.3.2 Dewey and Lönnerdal, 1983 ........................................ . 15-10
 

15.3.3 Butte et al., 1984 ................................................ . 15-10
 

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15.3.4	 Neville et al., 1988 ............................................... . 15-11
 

15.3.5	 Dewey et al., 1991a, b ............................................. . 15-11
 

15.3.6	 Butte, et al., 2000 ............................................... . 15-12
 

15.3.7	 Arcus-Arth et al., 2005 ........................................... . 15-13
 

15.4	 KEY STUDIES ON LIPID CONTENT AND LIPID INTAKE FROM HUMAN MILK . . . 15-13
 

15.4.1	 Butte et al., 1984 ................................................ . 15-14
 

15.4.2	 Mitoulas et al., 2002 ............................................. . 15-14
 

15.4.3	 Mitoulas et al., 2003 ............................................. . 15-15
 

15.4.4	 Arcus-Arth et al., 2005 ........................................... . 15-15
 

15.4.5	 Kent et al., 2006 ................................................ . 15-15
 

15.5	 RELEVANT STUDY ON LIPID INTAKE FROM HUMAN MILK ................ . 15-16
 

15.5.1	 Maxwell and Burmaster, 1993 ...................................... . 15-16
 

15.6	 OTHER FACTORS ..................................................... . 15-16
 

15.6.1	 Population of Nursing Infants ....................................... . 15-16
 

15.6.2	 Intake Rates Based on Nutritional Status .............................. . 15-19
 

15.6.3	 Frequency and Duration of Feeding .................................. . 15-19
 

15.7	 REFERENCES FOR CHAPTER 15 ......................................... . 15-20
 

ACTIVITY FACTORS .......................................................... . 16-1
 

16.1	 INTRODUCTION ....................................................... . 16-1
 

16.2 RECOMMENDATIONS .................................................. . 16-1
 

16.3	 ACTIVITY PATTERNS .................................................. . 16-7
 

16.3.1	 KEY STUDIES .................................................. . 16-7
 

16.3.1.1 Wiley et al., 1991 .......................................... . 16-7
 

16.3.1.2 U.S. EPA, 1996 ........................................... . 16-8
 

16.3.2	 RELEVANT STUDIES ............................................ . 16-9
 

16.3.2.1 Timmer et al., 1985 ........................................ . 16-9
 

16.3.2.2 Robinson and Thomas, 1991 ................................ . 16-10
 

16.3.2.3 Funk et al., 1998 ......................................... . 16-11
 

16.3.2.4 U.S. EPA, 2000 .......................................... . 16-11
 

16.3.2.5 Hubal et al., 2000 ......................................... . 16-12
 

16.3.2.6 Wong et al., 2000 ......................................... . 16-12
 

16.3.2.7 Graham and McCurdy, 2004 ................................ . 16-13
 

16.3.2.8 Vandewater et al., 2004 .................................... . 16-14
 

16.3.2.9 Juster et al. (2004) ........................................ . 16-14
 

16.3.2.10 U.S. Department of Labor, 2007 ....................... . 16-15
 

16.3.2.11 Nader et al. 2008 ................................... . 16-15
 

16.4	 REFERENCES FOR CHAPTER 16 ......................................... . 16-15
 

Page Child-Specific Exposure Factors Handbook 

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 17 

Child-Specific Exposure Factors Handbook 

CSEFH 

TABLE OF CONTENTS (Continued)

CONSUMER PRODUCTS ....................................................... . 17-1
 

17.1 INTRODUCTION ....................................................... . 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 U.S. EPA, 1996 .................................................. . 17-2
 

17.3.3 Bass et al., 2001 ................................................. . 17-3
 

17.3.4 Loretz et al., 2005 ................................................ . 17-4
 

17.3.5 Loretz et al., 2006 ................................................ . 17-4
 

17.3.6 Loretz et al., 2008 ................................................ . 17-5
 

17.3.7 Sathyanarayana et al., 2008 ......................................... . 17-5
 

17.4 REFERENCES FOR CHAPTER 17 .......................................... . 17-5
 

GLOSSARY OF TERMS ......................................................... . G-1
 

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September 2008 xi 
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CSEFH 

LIST OF TABLES 

Table 1-1. Characterization of Variability in Exposure Factors .............................. . 1-21
 

Table 1-2. Considerations Used to Rate Confidence in Recommended Values ................... . 1-22
 

Table 1-3. Integrating U.S. EPA’s Guidance on Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental Contaminants with U.S. EPA’s Supplemental Guidance 

for Assessing Susceptibility from Early-Life Exposure to Carcinogens For Those 

Contaminants Which Act Via a Mutagenic Mode of Action ........................ . 1-24
 

Table 2-1. Four Strategies for Confronting Variability ..................................... . 2-9
 

Table 2-2. Three Types of Uncertainty and Associated Sources and Examples ................... . 2-9
 

Table 2-3. Approaches to Quantitative Analysis of Uncertainty .............................. . 2-10
 

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. Confidence in Recommendations for Water Ingestion while Swimming ................ . 3-5
 

Table 3-4. Per Capita Estimates of Combined Direct and Indirect Water Ingestion: 

Community Water (mL/day) ............................................... . 3-14
 

Table 3-5. Per Capita Estimates of Combined Direct and Indirect Water Ingestion: 

Bottled Water (mL/day) ................................................... . 3-14
 

Table 3-6. Per Capita Estimates of Combined Direct and Indirect Water Ingestion: 

Other Sources (mL/day) .................................................. . 3-15
 

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

All Sources (mL/day) ..................................................... . 3-15
 

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

All Sources (mL/day) ..................................................... . 3-16
 

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

Community Water (mL/kg-day) ............................................. . 3-17
 

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

Bottled Water (mL/kg-day) ................................................ . 3-17
 

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

Other Sources (mL/kg-day) ................................................ . 3-18
 

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

All Sources (mL/kg-day) .................................................. . 3-18
 

Table 3-13. Per Capita Estimates of Total Direct and Indirect Water Ingestion: 

All Sources (mL/kg-day) .................................................. . 3-19
 

Table 3-14. Consumers Only Estimates of Combined Direct and Indirect Water Ingestion: 

Community Water (mL/day) ............................................... . 3-20
 

Table 3-15. Consumers Only Estimates of Combined Direct and Indirect Water Ingestion: 

Bottled Water (mL/day) ................................................... . 3-20
 

Table 3-16. Consumers Only Estimates of Combined Direct and Indirect Water Ingestion: 

Other Sources (mL/day) ................................................... . 3-21
 

Table 3-17. Consumers Only Estimates of Combined Direct and Indirect Water Ingestion: 

All Sources (mL/day) ..................................................... . 3-21
 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

CSEFH 

LIST OF TABLES (Continued) 

Table 3-18. Consumers Only Estimates of Combined Direct and Indirect Water Ingestion: 

All Sources (mL/day) ..................................................... . 3-22
 

Table 3-19. Consumers Only Estimates of Direct and Indirect Water Ingestion: 

Community Water (mL/kg-day) ............................................. . 3-23
 

Table 3-20. Consumers Only Estimates of Direct and Indirect Water Ingestion: 

Bottled Water (mL/kg-day) ................................................ . 3-23
 

Table 3-21. Consumers Only Estimates of Direct and Indirect Water Ingestion: 

Other Sources (mL/kg-day) ................................................ . 3-24
 

Table 3-22. Consumers Only Estimates of Direct and Indirect Water Ingestion: 

All Sources (mL/kg-day) .................................................. . 3-24
 

Table 3-23. Consumer Only Estimates of Total Direct and Indirect Water Ingestion (mL/kg-day) ..... . 3-25
 

Table 3-24. Water Ingested (mL/day) from Water By Itself and Water Added to Other Beverages 

and Foods .............................................................. . 3-26
 

Table 3-25. Mean Water Consumption (mL/kg-day) by Race/Ethnicity ......................... . 3-27
 

Table 3-26 Plain Tap Water and Total Water Consumption by Age, Sex, Region, Urbanicity, and 

Poverty Category ........................................................ . 3-28
 

Table 3-27. Intake of Water from Various Sources in 2-13-y-old Participants of the 

DONALD Study 1985-1999 ................................................ . 3-29
 

Table 3-28. Mean (± Standard Error) Fluid Intake (mL/kg/day) by Children Aged 1-10 years, 

NHANES III, 1988-94 .................................................... . 3-30
 

Table 3-29. Estimated Mean (± Standard Error) Amount of Total Fluid and Plain Water Intake 

among Children Aged 1-10 Years: (NHANES III, 1988-94) ........................ . 3-31
 

Table 3-30. Tap Water Intake in Breastfed and Formula-fed Infants and Mixed-fed Young Children at
 

Different Age Points ...................................................... . 3-32
 

Table 3-31. Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes (mL/day) 

for Children With Returned Questionnaires .................................... . 3-33
 

Table 3-32. Mean (± Standard Deviation) Daily Beverage Intakes Reported on Beverage Frequency
 

Questionnaire and 3-day Food and Beverage Dairies ............................. . 3-34
 

Table 3-33. Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study) . . 3-35
 

Table 3-34. Pool Water Ingestion by Swimmers .......................................... . 3-36
 

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

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

Table 4-3. New Jersey Children’s Mouthing Frequency (contacts/hour) from Video-transcription .... . 4-20
 

Table 4-4. Survey-Reported Percent of 168 Minnesota Children Exhibiting Behavior, by Age ....... . 4-20
 

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

(contacts/hour) .......................................................... . 4-20
 

Table 4-6. Variability in Objects Mouthed by Washington State Children (contacts/hour) .......... . 4-21
 

Table 4-7. Videotaped Mouthing Activity of Texas Children, Median Frequency (Mean ± SD) ...... . 4-22
 

Table 4-8. Indoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various 

Studies ................................................................ . 4-22
 

Table 4-9. Outdoor Hand-to-Mouth Frequency (contacts/hour) Distributions from Various 

Studies ................................................................ . 4-22
 

Child-Specific Exposure Factors Handbook Page 

September 2008 xiii 
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CSEFH 

LIST OF TABLES (Continued) 

Table 4-10. Survey Reported Mouthing Behaviors for 92 Washington State Children .............. . 4-23
 

Table 4-11. Indoor Mouthing Frequency (Contacts per hour), Video-transcription of 9 Children 

with >15 minutes in View Indoors ........................................... . 4-23
 

Table 4-12. Outdoor Mouthing Frequency (Contacts per hour), Video-transcription of 38 Children ... . 4-24
 

Table 4-13. Estimated Daily Mean Mouthing Times of New York State Children, for Pacifiers and 

Other Objects ........................................................... . 4-25
 

Table 4-14. Percent of Houston-area and Chicago-area Children Observed Mouthing, by Category 

and Child’s Age ........................................................ . 4-25
 

Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour) .................... . 4-26
 

Table 4-16. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without 

Pacifier, in Minutes per Day ................................................ . 4-28
 

Table 4-17. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys, 

and Other Objects (hours:minutes:seconds) .................................... . 4-29
 

Table 4-18. Outdoor Median Mouthing Duration (Seconds per contact), Video-transcription 

of 38 Children .......................................................... . 4-30
 

Table 4-19. Indoor Mouthing Duration (Minutes per hour), Video-transcription of 9 Children 

with >15 minutes in View Indoors ........................................... . 4-30
 

Table 4-20. Outdoor Mouthing Duration (Minutes per hour), Video-transcription of 38 Children ..... . 4-31
 

Table 4-21. Reported Daily Prevalence of Massachusetts Children’s Non-Food Mouthing/Ingestion 

Behaviors .............................................................. . 4-32
 

Table 5-1. Recommended Values for Soil, Dust, and Soil + Dust Ingestion ..................... . 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 ............................................................... . 5-31
 

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

Week (mg/day) .......................................................... . 5-32
 

Table 5-5. Amherst, Massachusetts Soil-Pica Child’s Tracer Ratios .......................... . 5-33
 

Table 5-6. Van Wïjnen et al., 1990 Limiting Tracer Method (LTM) Soil Ingestion Estimates for 

Sample of Dutch Children ................................................. . 5-34
 

Table 5-7. Estimated Geometric Mean Limiting Tracer Method (LTM) Values of Children 

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

Period ................................................................ . 5-35
 

Table 5-8. Estimated Soil Ingestion for Sample of Washington State Children .................. . 5-35
 

Table 5-9. Soil Ingestion Estimates for 64 Anaconda Children .............................. . 5-36
 

Table 5-10. Soil Ingestion Estimates for Massachusetts Child Displaying Soil Pica Behavior 

(mg/day) .............................................................. . 5-36
 

Table 5-11. Soil Ingestion Estimates for Sample of 12 Washington State Children ................ . 5-37
 

Table 5-12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children .............. . 5-38
 

Table 5-13. Estimated Daily Soil Ingestion for East Helena, Montana Children .................. . 5-39
 

Table 5-14. Estimated Soil Ingestion for Sample of Dutch Nursery School Children ............... . 5-39
 

Table 5-15. Estimated Soil Ingestion for Sample of Dutch Hospitalized, Bedridden Children ........ . 5-40
 

Table 5-16. Positive/negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989)
 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

CSEFH 

Study: Effect on Mean Soil Ingestion Estimate (mg/day) .......................... . 5-40
 

Table 5-17. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 

Children (mg/day) ....................................................... . 5-41
 

Table 5-18. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64 Subjects
 

Projected over 365 Days ................................................... . 5-41
 

Table 5- 19. Summary of Estimates of Soil and Dust Ingestion by Children (0.5-14 years old) from 

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

Table 6-1. Recommended Long-Term Exposure (More Than 30 Days) Values for Inhalation 

(Males and Females Combined) .............................................. . 6-3
 

Table 6-2. Recommended Short-Term Exposure (Less Than 30 Days) Values for Inhalation 

(Males and Females Combined) .............................................. . 6-4
 

Table 6-3. Confidence in Recommendations for Inhalation Rates ............................. . 6-5
 

Table 6-4. Physiological Daily Inhalation Rates for Newborns Aged 1 Month or Less ............. . 6-17
 

Table 6-5. Distribution Percentiles of Physiological Daily Inhalation Rates (m3

/day) for Free-living 

Normal-weight Males and Females Aged 2.6 months to 23 years ................... . 6-18
 

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

/day) for Free-living Normal-weight 

Males, Females, and Males and Females Combined. ............................. . 6-19
 

Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (m3

/day) for Free-living 

Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years .......... . 6-20
 

Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates per Unit of Body Weight 

(m3

/kg-day) for Free-living Normal-weight Males and Females Aged 2.6 months 

to 23 years ............................................................. . 6-21
 

Table 6-9. Distribution Percentiles of Physiological Daily Inhalation Rates (m3

/kg-day) for Free-living 

Normal-weight and Overweight/obese Males and Females Aged 4 to 18 years .......... . 6-22
 

Table 6-10. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Category ...... . 6-23
 

Table 6-11. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Category .... . 6-24
 

Table 6-12. Mean and 95th Percentile Inhalation Rate Values (m3

/day) for Males, Females and 

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

Table 6-13. Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the 

Specified Activity Category, for Males by Age Category .......................... . 6-26
 

Table 6-14. Descriptive Statistics for Average Ventilation Rate While Performing Activities Within the 

Specified Activity Category, for Females by Age Category ........................ . 6-28
 

Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities 

Within the Specified Activity Category, by Age and Gender Categories ............... . 6-30
 

Table 6-16. Nonnormalized Daily Inhalation Rates (m3

/day) Derived Using Layton’s (1993) 

Method and CSFII Energy Intake Data ........................................ . 6-32
 

Table 6-17. Mean and 95th Percentile Inhalation Rate Values (m3

/day) for Males and Females 

Combined ............................................................. . 6-33
 

Table 6-18. Summary of Institute of Medicine Energy Expenditure Recommendations
 

for Active and Very Active People with Equivalent Inhalation Rates ................. . 6-34
 

Table 6-19. Mean Inhalation Rate Values (m3

/day) for Males, Females, and Males and Females 

Combined ............................................................. . 6-35
 

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September 2008 xv 
Child-Specific Exposure Factors Handbook 

CSEFH 

LIST OF TABLES (Continued) 

Table 6-20. Mean Inhalation Rate Values (m3

/day) from Key Studies for Males and Females 

Combined ............................................................. . 6-36
 

Table 6-21. 95th Percentile Inhalation Rate Values (m3

/day) from Key Studies for Males and Females 

Combined ............................................................. . 6-37
 

Table 6-22. Daily Inhalation Rates Estimated From Daily Activities ........................... . 6-38
 

Table 6-23. Selected Inhalation Rate Values During Different Activity Levels Obtained From Various 

Literature Sources ....................................................... . 6-39
 

Table 6-24. Summary of Human Inhalation Rates for Children by Activity Level (m3

/hour) ......... . 6-40
 

Table 6-25. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for 

All Age Groups ......................................................... . 6-40
 

Table 6-26. Summary of Daily Inhalation Rates Grouped by Age and Activity Level .............. . 6-41
 

Table 6-27. Calibration and Field Protocols for Self-monitoring of Activities Grouped by 

Subject Panels .......................................................... . 6-42
 

Table 6-28. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-estimated 

Breathing Rates ......................................................... . 6-42
 

Table 6-29. Distribution of Predicted Inhalation Rates by Location and Activity Levels for Elementary 

and High School Students ................................................. . 6-43
 

Table 6-30. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary and 

High School Students ..................................................... . 6-44
 

Table 6-31. Summary of Average Inhalation Rates (m3

/hour) by Age Group and Activity Levels for 

Laboratory Protocols ..................................................... . 6-45
 

Table 6-32. Summary of Average Inhalation Rates (m3

/hour) by Age Group And Activity Levels in Field
 

Protocols .............................................................. . 6-46
 

Table 6-33. Mean Minute Inhalation Rate (m3

/minute) by Group and Activity for Laboratory Protocols . 6-47
 

Table 6-34. Mean Minute Inhalation Rate (m3

/minute) by Group and Activity for Field Protocols ..... . 6-47
 

Table 6-35. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-energy 

Intakes (EFD) for Individuals Sampled in the 1977-78 NFCS ...................... . 6-48
 

Table 6-36. Daily Inhalation Rates Calculated from Food-energy Intakes ....................... . 6-49
 

Table 6-37. Statistics of the Age/gender Cohorts Used to Develop Regression Equations for Predicting 

Basal Metabolic Rates (BMR) .............................................. . 6-50
 

Table 6-38. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal 

Metabolic Rate (BMR) .................................................... . 6-51
 

Table 6-39. Inhalation Rates for Short-term Exposures ..................................... . 6-52
 

Table 6-40. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in 618 

Infants and Children Grouped in Classes of Age ................................ . 6-53
 

Table 7-1. Recommended Values for Total Body Surface Area, Males and 

Females Combined ........................................................ . 7-4
 

Table 7-2. Recommended Values for Surface Area of Body Parts ............................. . 7-5
 

Table 7-3. Confidence in Recommendations for Body Surface Area ........................... . 7-6
 

Table 7-4. Recommended Values for Mean Solids Adherence ................................ . 7-8
 

Table 7-5. Confidence in Recommendations for Solids Adherence to Skin ...................... . 7-9
 

Table 7-6. Percentage of Total Body Surface Area by Body Part For Children ................... . 7-16
 

Page Child-Specific Exposure Factors Handbook 

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LIST OF TABLES (Continued) 

Table 7-7. Mean and Percentile Skin Surface Area (m2

) Derived from U.S. EPA Analysis of NHANES 

1999-2006 Males and Females Combined ..................................... . 7-17
 

Table 7-8. Mean and Percentile Skin Surface Area (m2

) Derived from U.S. EPA Analysis of NHANES 

1999-2006 Males ........................................................ . 7-17
 

Table 7-9. Mean and Percentile Skin Surface Area (m2

) Derived from U.S. EPA Analysis of NHANES 

1999-2006 Females ...................................................... . 7-18
 

Table 7-10. Descriptive Statistics For Surface Area/Body Weight (SA/BW) Ratios (m2

/kg) .......... . 7-19
 

Table 7-11. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities ........... . 7-20
 

Table 7-12. Summary of Field Studies ................................................. . 7-21
 

Table 7-13. Geometric Mean and Geometric Standard Deviations of Solids Adherence by 

Activity and Body Region .................................................. . 7-22
 

Table 7-14. Summary of Controlled Greenhouse Trials - Children Playing ...................... . 7-23
 

Table 7A-1. Estimated Parameter Values for Different Age Intervals .......................... . 7A-5
 

Table 7A-2. Summary of Surface Area Parameter Values for the Dubois and Dubois Model ........ . 7A-5
 

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 (kilograms) Derived from NHANES 1999-2006, Males and
 

Females Combined ...................................................... . 8-10
 

Table 8-4. Mean and Percentile Body Weights (kilograms) for Males Derived from NHANES 

1999-2006 ............................................................. . 8-11
 

Table 8-5. Mean and Percentile Body Weights (kilograms) for Females Derived from 

NHANES 1999-2006 ..................................................... . 8-11
 

Table 8-6. Weight in Kilograms for Males 2 Months-19 Years of Age– Number Examined, Mean, and
 

Selected Percentiles, by Age Category: United States, 1976-1980 ................... . 8-12
 

Table 8-7. Weight in Kilograms for Females 6 Months-19 Years of Age– Number Examined, Mean, and
 

Selected Percentiles, by Age Category: United States, 1976-1980 ................... . 8-13
 

Table 8-8. Statistics for Probability Plot Regression Analyses: 

Females Body Weights 6 Months to 20 Years of Age ............................. . 8-14
 

Table 8-9. Statistics for Probability Plot Regression Analyses: 

Males Body Weights 6 Months to 20 Years of Age ............................... . 8-15
 

Table 8-10. Body Weight Estimates (kilograms) by Age and Gender, U.S. Population Derived From 

NHANES III (1988-94 .................................................... . 8-16
 

Table 8-11. Body Weight Estimates (in kilograms) by Age, U.S. Population Derived From

 NHANES III (1988-94 ................................................... . 8-17
 

Table 8-12. Observed Mean, Standard Deviation and Selected Percentiles for Weight (kilograms) by Gender
 

and Age: Birth to 36 Months ............................................... . 8-18
 

Table 8-13. Mean Body Weight (kilograms) by Age and Gender Across Multiple Surveys .......... . 8-25
 

Table 8-14. Mean Height (centimeters) by Age and Gender Across Multiple Surveys .............. . 8-26
 

Table 8-15. Mean Body Mass Index (BMI) by Age and Gender Across Multiple Surveys ........... . 8-27
 

Table 8-16. Sample Sizes by Age, Sex, Race, and Examination .............................. . 8-28
 

Table 8-17. Mean BMI (kg/m2

) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex .. . 8-29
 

Table 8-18. Prevalence of Overweight and Obesitya

 Among Children .......................... . 8-30
 

Child-Specific Exposure Factors Handbook Page 

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LIST OF TABLES (Continued) 

Table 8-19. 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 ............... . 8-31
 

Table 8-20. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
 

NHANES II Data ....................................................... . 8-32
 

Table 8-21. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
 

NHANES III Data ................................................. . 8-33
 

Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using
 

NHANES IV Data ....................................................... . 8-34
 

Table 8-23. Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessments . 8-35
 

Table 8-24. Estimated Percentile Distribution of Body Weight by Fine Age Categories ............ . 8-35
 

Table 8-25. Estimated Percentile Distribution of Body Weight By Fine Age Categories With Confidence 

Interval ............................................................... . 8-36
 

Table 8-26. Fetal Weight (grams) Percentiles Throughout Pregnancy ......................... . 8-37
 

Table 8-27. Neonatal Weight by Gestational Age for Males and Females Combined .............. . 8-38
 

Table 9-1. Recommended Values for Intake of Fruits and Vegetables, As Consumed .............. . 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 (g/kg-day as consumed) .................. . 9-12
 

Table 9-4. Consumer Only Intake of Fruits and Vegetables (g/kg-day as consumed) .............. . 9-13
 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) .......... . 9-14
 

Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) ...... . 9-17
 

Table 9-7. Mean Quantities of Vegetables Consumed Daily by Sex and Age, Per Capita (g/day) ..... . 9-20
 

Table 9-8. Percentage of Individuals Consuming Vegetables, by Sex and Age (%) ............... . 9-21
 

Table 9-9. Mean Quantities of Fruits Consumed Daily by Sex and Age, Per Capita (g/day) ......... . 9-22
 

Table 9-10. Percentage of Individuals Consuming, Fruits by Sex and Age (%) ................... . 9-23
 

Table 9-11. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and 

Percentage of Individuals Using These Foods in Two Days ........................ . 9-24
 

Table 9-12. Characteristics of the FITS Sample Population .................................. . 9-25
 

Table 9-13. Percentage of Infants and Toddlers Consuming Different Types of Vegetables .......... . 9-26
 

Table 9-14. Top Five Vegetables Consumed by Infants and Toddlers .......................... . 9-27
 

Table 9-15. Percentage of Infants and Toddlers Consuming Different Types of Fruits .............. . 9-28
 

Table 9-16. Top Five Fruits Consumed by Infants and Toddlers .............................. . 9-29
 

Table 9-17. Characteristics of WIC Participants and Non-participants (Percentages) .............. . 9-30
 

Table 9-18. Food Choices for Infants and Toddlers by WIC Participation Status .................. . 9-32
 

Table 9-19. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming 

Different Types of Fruits and Vegetables on A Given Day ......................... . 9-33
 

Table 9-20. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants 

and Toddlers Per Age Group ............................................... . 9-34
 

Table 9-21. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly 

Consumed by Infants from the 2002 Feeding Infants and Toddlers Study .............. . 9-35
 

Table 9-22. Average Portion Sizes per Eating Occasion of Fruits and Vegetables Commonly 

Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study ............ . 9-36
 

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LIST OF TABLES (Continued) 

Table 9-23. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible 

Portions ............................................................... . 9-37
 

Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data .. . 9A-2
 

Table 10-1. Recommended Values for General Population Fish Intake ......................... . 10-4
 

Table 10-2. Confidence in Recommendations for General Population Fish Intake ................. . 10-5
 

Table 10-3. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
 

General Population Children Ages 3 to 17 Years - g/day, As-Consumed ............. . 10-17
 

Table 10-4. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
 

General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed ......... . 10-17
 

Table 10-5. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
 

General Population Children Ages 3 to 17 Years - g/day, As-Consumed ............. . 10-18
 

Table 10-6. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
 

General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed ......... . 10-18
 

Table 10-7. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
 

General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight ....... . 10-19
 

Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake
 

General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight ... . 10-19
 

Table 10-9. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake
 

General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight ....... . 10-20
 

Table 10-10. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight ... . 10-20
 

Table 10-11. Number of General Population Respondents Reporting Consumption of a 

Specified Number of Servings of Seafood in 1 Month, and Source of Seafood Eaten ..... . 10-21
 

Table 10-12. Fish Consumption Among General Population Children in Four States, 

Consumers Only, g/kg-day As-Consumed .................................... . 10-22
 

Table 10-13. Fish Consumption Among General Population in Four States According to Caught or Bought 

Status, g/kg-day As-Consumed ............................................. . 10-23
 

Table 10-14. Fish Consumption Among General Population and Anglers in Three States, 

g/kg-day As-Consumed .................................................. . 10-24
 

Table 10-15. Recreational Fish Consumption in Delaware Consumers Only ..................... . 10-24
 

Table 10-16. Consumption of Self-Caught Fish by Recreational Anglers 

Lavaca Bay, Texas, g/day ................................................. . 10-25
 

Table 10-17. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational 

Anglers Lavaca Bay, Texas ............................................... . 10-25
 

Table 10-18. Mean Fish Intake Among Individuals Who Eat Fish and 

Reside in Households With Recreational Fish Consumption - Michigan .............. . 10-26
 

Table 10-19. Consumption of Sports-caught and Purchased Fish by Minnesota and North Dakota 

Children, Ages 0 to 14 Years (g/day) ........................................ . 10-26
 

Table 10-20. Fish Consumption Rates among Native American Children (age 5 years and under) .... . 10-27
 

Table 10-21. Number of Fish Meal Eaten per Month and Fish Intake Among Native American 

Children who Consume Particular Species .................................... . 10-28
 

Table 10-22. Consumption Rates for Native American Children, Age Birth to Five Years (g/kg-day) .. . 10-29
 

Child-Specific Exposure Factors Handbook Page 

September 2008 xix 
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LIST OF TABLES (Continued) 

Table 10-23. Consumption Rates for Native American Children (g/kg-day), All Children 

(including non-consumers): Individual Finfish and Shellfish and Fish Groups ......... . 10-30
 

Table 10-24. Consumption Rates for Native American Children (g/kg-day),
 

Consumers Only: Individual Finfish and Shellfish and Fish Groups ................. . 10-31
 

Table 10-25. Fish Consumption Rates for Tulalip and Squaxin Island Children
 

Consumers Only (g/kg-day) ............................................... . 10-32
 

Table 10-26. Fish Consumption Rates by Gender for Tulalip and Squaxin Island Children
 

Consumers Only (g/kg-day) ............................................... . 10-33
 

Table 10-27. Distribution of Quantity of Canned Tuna Consumed (grams) Per Eating Occasion,
 

by Age and Sex ........................................................ . 10-34
 

Table 10-28. Distribution of Quantity of Other Finfish Consumed (grams) Per Eating Occasion, 

by Age and Sex ........................................................ . 10-34
 

Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species ................. . 10-35
 

Table 11-1. Recommended Values for Intake of Meats, Dairy Products, and Fats, As Consumed ..... . 11-3
 

Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats ......... . 11-4
 

Table 11-3. Per Capita Intake of Total Meat and Dairy Products (g/kg-day as consumed) .......... . 11-14
 

Table 11-4. Consumer Only Intake of Total Meat and Dairy Products (g/(kg-day as consumed) ..... . 11-15
 

Table 11-5. Per Capita Intake of Individual Meats and Dairy Products (g/kg-day as consumed) ..... . 11-16
 

Table 11-6. Consumer Only Intake of Individual Meats and Dairy Products (g/kg-day as consumed) . . 11-16
 

Table 11-7. Mean Quantities of Meat and Eggs consumed Daily by Sex and Age, Per Capita (g/day) . . 11-17
 

Table 11-8. Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%) .......... . 11-18
 

Table 11-9. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day) . . 11-19
 

Table 11-10. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%) ........... . 11-20
 

Table 11-11. Quantity (as consumed) of Meat and Dairy Products Consumed Per Eating Occasion and
 

Percentage of Individuals Using These Foods in Two Days ....................... . 11-21
 

Table 11-12. Characteristics of FITS Sample Population .................................... . 11-22
 

Table 11-13. Percentage of Infants and Toddlers Consuming Meat or Other Protein Sources ........ . 11-23
 

Table 11-14. Characteristics of WIC Participants and Non-participants (Percentages) ............. . 11-24
 

Table 11-15. Food Choices for Infants and Toddlers by WIC Participation Status ................. . 11-25
 

Table 11-16. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different 

Types of Milk, Meats or Other Protein Sources on A Given Day ................... . 11-26
 

Table 11-17. Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly 

Consumed by Infants from the 2002 Feeding Infants and Toddlers Study ............. . 11-27
 

Table 11-18. Average Portion Sizes Per Eating Occasion of Meats and Dairy Products Commonly 

Consumed by Toddlers from the 2002 Feeding Infants and Toddlers Study ........... . 11-28
 

Table 11-19. Total Fat Intake (Per capita; g/day) ......................................... . 11-29
 

Table 11-20. Total Fat Intake (Per capita; g/kg-day) ....................................... . 11-30
 

Table 11-21. Total Fat Intake (Consumers Only; g/day) .................................... . 11-31
 

Table 11-22. Total Fat Intake (Consumers Only; g/kg-day) .................................. . 11-32
 

Table 11-23. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/day) ....... . 11-33
 

Table 11-24. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/kg-day) ..... . 11-34
 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

CSEFH 

LIST OF TABLES (Continued) 

Table 11-25. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 

1973-1982 (g/day) ...................................................... . 11-35
 

Table 11-26. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 

1973-1982 (g/kg-day) .................................................... . 11-37
 

Table 11-27. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender ............ . 11-39
 

Table 11-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Products .... . 11-40
 

Table 11A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data . . 11A-2
 

Table 12-1. Recommended Values for Intake of Grains, As Consumed ......................... . 12-3
 

Table 12-2. Confidence in Recommendations for Intake of Grain Products ...................... . 12-4
 

Table 12-3. Per Capita Intake of Total Grains (g/kg-day as consumed) ........................ . 12-12
 

Table 12-4. Consumer Only Intake of Total Grains (g/kg-day as consumed) .................... . 12-12
 

Table 12-5. Per Capita Intake of Individual Grain Products (g/kg-day as consumed) .............. . 12-13
 

Table 12-6. Consumer Only Intake of Individual Grain Products (g/kg-day as consumed) .......... . 12-13
 

Table 12-7. Mean Quantities of Grain Products Consumed Daily by Sex and Age, Per Capita (g/day) . . 12-14
 

Table 12-8. Percentage of Individuals Consuming Grain Products, by Sex and Age (%) ........... . 12-15
 

Table 12-9. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and 

Percentage of Individuals Using These Foods in Two Days ....................... . 12-16
 

Table 12-10. Characteristics of the FITS Sample Population ................................. . 12-17
 

Table 12-11. Percentage of Infants and Toddlers Consuming Different Types of Grain Products ...... . 12-18
 

Table 12-12. Characteristics of WIC Participants and Nonparticipants (Percentages) .............. . 12-19
 

Table 12-13. Food Choices for Infants and Toddlers by WIC Participation Status ................. . 12-20
 

Table 12-14. Percentage of Hispanic and Non-Hispanic Infants and Toddlers Consuming Different 

Types of Grain Products on A Given Day ..................................... . 12-21
 

Table 12-15. Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed 

by Infants from the 2002 Feeding Infants and Toddlers Study ..................... . 12-22
 

Table 12-16. Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed 

by Toddlers from the 2002 Feeding Infants and Toddlers Study .................... . 12-22
 

Table 12-17. Mean Moisture Content of Selected Grain Products Expressed as Percentages 

of Edible Portions ....................................................... . 12-23
 

Table 12A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data . . 12A-2
 

Table 13-1. Summary of Recommended Values for Intake of Home-produced Foods (Consumers Only) . 13-3
 

Table 13-2. Confidence in Recommendations for Intake of Home-produced Foods ................ . 13-4
 

Table 13-3. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in 

Child-specific Analysis of Food Intake ....................................... . 13-10
 

Table 13-4. Consumer Only Intake of Home-produced Foods (g/kg-day) ....................... . 13-11
 

Table 13-5. Percent Weight Losses from Food Preparation ................................. . 13-12
 

Table 13-6. Fraction of Food Intake that is Home-produced ................................ . 13-13
 

Table 13A-1. Food Codes and Definitions Used in Child-specific Analysis of the 1987-1988 USDA 

NFCS Data to Estimate Intake of Home-produced Foods .................... . 13A-2 

Table 13B-1. Food Codes and Definitions Used in Analysis of the 1987-1988 USDA NFCS Household 

Data to Estimate Fraction of Food Intake that is Home-produced .................. . 13B-2
 

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September 2008 xxi 
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CSEFH 

LIST OF TABLES (Continued) 

Table 14-1. Recommended Values for Per Capita Total Intake of Foods, As Consumed ............ . 14-2
 

Table 14-2. Confidence in Recommendations for Total Food Intake ........................... . 14-3
 

Table 14-3. Per Capita Total Food Intake ............................................... . 14-6
 

Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed) . . 14-7
 

Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed)14-11
 

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 ........... . 14-15
 

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 ........... . 14-19
 

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 ... . 14-23
 

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 ............ . 14-27
 

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 . 14-31
 

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 ........... . 14-35
 

Table 15-1. Recommended Values for Human Milk And Lipid Intake Rates for Exclusively Breastfed 

Infants ................................................................ . 15-3
 

Table 15-2. Confidence in Recommendations for Human Milk Intake .......................... . 15-4
 

Table 15-3. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants 

(mL/day) .............................................................. . 15-6
 

Table 15-4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants 

(mL/kg/day) ............................................................ . 15-7
 

Table 15-5. Lipid Intake Rates Derived from Key Studies for Exclusively Breastfed Infants (mL/day) .. . 15-8
 

Table 15-6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast-fed Infants 

(mL/kg/day) ............................................................ . 15-9
 

Table 15-7. Daily Intakes of Human Milk .............................................. . 15-23
 

Table 15-8. Human Milk Intakes for Infants Aged 1 to 6 Months ............................ . 15-23
 

Table 15-9. Human Milk Intake Among Exclusively Breast-fed Infants During the First 4 Months 

of Life ............................................................... . 15-24
 

Table 15-10. Human Milk Intake During a 24-hour Period .................................. . 15-25
 

Table 15-11. Human Milk Intake Estimated by the Darling Study ............................. . 15-26
 

Table 15-12. Mean Breastfed Infants Characteristics ...................................... . 15-26
 

Table 15-13. Mean Human Milk Intake of Breastfed Infants (mL/day) ......................... . 15-27
 

Table 15-14. Feeding Practices by Percent of Infants ...................................... . 15-27
 

Table 15-15. Body Weight of Breastfed Infants ........................................... . 15-28
 

Table 15-16. AAP Dataset Milk Intake Rates at Different Ages .............................. . 15-29
 

Table 15-17. Average Daily Human Milk Intake (mL/kg day) ................................ . 15-30
 

Table 15-18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-fed 

Infants ............................................................... . 15-30
 

Table 15-19. Human Milk Production and Composition Over the First 12 Months of Lactation ...... . 15-31
 

Page Child-Specific Exposure Factors Handbook 

xxii September 2008 
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CSEFH 

LIST OF TABLES (Continued) 

Table 15-20. Changes in Volume of Human Milk Produced and Milk Fat Content Over the First Year of 

Lactation ............................................................. . 15-32
 

Table 15-21. Changes in Fatty Acid Composition of Human Milk Over the First Year of Lactation 

(g/100 g total fatty acids) ................................................. . 15-33
 

Table 15-22. Comparison of Lipid Content Assumptions (mL/kg-day) ......................... . 15-33
 

Table 15-23. Distribution of Average Daily Lipid Intake (mL/kg day) assuming 4% Milk Lipid Content 15-34
 

Table 15-24. Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age .............. . 15-34
 

Table 15-25. Socio-economic Characteristics of Exclusively Breast-fed Infants Born in 2004 ........ . 15-34
 

Table15-26. Geographic-specific Breastfeeding Percent Rates Among Children Born in 2004 ....... . 15-36
 

Table 15-27. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0-6 

Months Old ........................................................... . 15-37
 

Table 15-28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6-12 

Months Old ........................................................... . 15-38
 

Table 15-29. Population Weighted Averages of Mothers Who Reported Selected Feeding Practices 

During the Previous 24-hours .............................................. . 15-39
 

Table 15-30. Racial and Ethnic Differences in Proportion of Children Ever Breastfed, NHANES III 

(1988-1994) ........................................................... . 15-40
 

Table 15-31. Racial and Ethnic Differences in Proportion of Children Who Received Any Human Milk 

at 6 Months (NHANES III, 1988-1994) ...................................... . 15-41
 

Table 15-32. Racial and Ethnic Differences in Proportion of Children Exclusively Breastfed at 4 

Months (NHANES III, 1991-1994) ......................................... . 15-42
 

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 .................................................. . 15-43
 

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 .................................................. . 15-44
 

Table 15-35. Number of Meals Per Day ................................................ . 15-45
 

Table 15-36. Comparison of Breastfeeding Patterns Between Age and Groups (Mean ±SD) ......... . 15-45
 

Table 16-1. Recommended Values for Activity Factors ..................................... . 16-3
 

Table 16-2. Confidence in Recommendations for Activity Factors ............................. . 16-6
 

Table 16-3. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
 

Categories, for All Respondents and Doers .................................... . 16-17
 

Table 16-4. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
 

Categories, by Age and Gender ............................................ . 16-18
 

Table 16-5. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Ten Major Activity
 

Categories, Grouped by Seasons and Regions ................................. . 16-19
 

Table 16-6. Time (minutes/day) Children Under 12 Years of Age Spent in Six Major Location 

Categories, for All Respondents and Doers .................................... . 16-20
 

Table 16-7. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location 

Categories, Grouped by Age and Gender ..................................... . 16-21
 

Child-Specific Exposure Factors Handbook Page
 

September 2008 xxiii
 
Child-Specific Exposure Factors Handbook 

CSEFH 

LIST OF TABLES (Continued) 

Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in Six Location 

Categories, Grouped by Season and Region ................................... . 16-22
 

Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 

Proximity to Two Potential Sources of Exposure, Grouped by All Respondents, 

Age, and Gender ....................................................... . 16-23
 

Table 16-10. Mean Time (minutes/day) Children Under 12 Years of Age Spent Indoors and Outdoors, 

Grouped by Age and Gender .............................................. . 16-24
 

Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined
 

Whole Population and Doers Only .......................................... . 16-25
 

Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations Whole Population 

and Doers Only ........................................................ . 16-29
 

Table 16-13. Time Spent (minutes/day) in Selected Outdoor Locations Whole Population 

and Doers Only ........................................................ . 16-31
 

Table 16-14. Mean Time Spent (minutes/day) Inside and Outside, by Age Category ............... . 16-33
 

Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined
 

Whole Population and Doers Only .......................................... . 16-34
 

Table 16-16. Time Spent (minutes/day) in Selected Activities Whole Population and Doers Only ..... . 16-36
 

Table 16-17. Number of Showers Taken per Day, by Number of Respondents .................... . 16-40
 

Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing 

and Showering ........................................................ . 16-41
 

Table 16-19. Range of Number of Times Washing the Hands at Specified Daily Frequencies by 

the Number of Respondents ............................................... . 16-43
 

Table 16-20. Number of Times Swimming in a Month in Freshwater Swimming Pool by the 

Number of Respondents ................................................. . 16-44
 

Table 16-21. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool ............. . 16-45
 

Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass Whole Population 

and Doers Only ........................................................ . 16-46
 

Table 16-23. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air ......... . 16-48
 

Table 16-24. Time Spent (minutes/day) with Smokers Present ............................... . 16-48
 

Table 16-25. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex 

and Type of Day ....................................................... . 16-49
 

Table 16-26. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for Five Different 

Age Groups ........................................................... . 16-50
 

Table 16-27. Mean Time Spent (hours/day) Indoors and Outdoors, by Age and Day of the Week ..... . 16-51
 

Table 16-28. Mean Time Spent (minutes/day) in Various Microenvironments, Children Ages 12 to 

17 Years National and California Surveys .................................... . 16-52
 

Table 16-29. Gender and Age Groups ................................................. . 16-53
 

Table 16-30. Assignment of At-Home Activities to Inhalation Rate Levels for Children ........... . 16-54
 

Table 16-31. Aggregate Time Spent (minutes/day) At-Home in Activity Groups, by Adolescents 

and Children .......................................................... . 16-55
 

Table 16-32. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender (Adolescents) .... . 16-55
 

Table 16-33. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender and Age 

for Children ........................................................... . 16-56
 

Page Child-Specific Exposure Factors Handbook 

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CSEFH 

LIST OF TABLES (Continued) 

Table 16-34. Number of Person-Days/Individuals for Children in CHAD Database ............... . 16-57
 

Table 16-35. Time Spent (hours/day) in Various Microenvironments, by Age ................... . 16-58
 

Table 16-36. Mean Time Children Spent (hours/day) Doing Various Macroactivities 

While Indoors at Home .................................................. . 16-59
 

Table 16-37. Time Children Spent (hours/day) in Various Microenvironments, by Age 

Recast into New Standard Age Categories .................................... . 16-60
 

Table 16-38. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
 

Recast Into New Standard Age Categories .................................... . 16-61
 

Table 16-39. Number and Percentage of Respondents with Children and Those Reporting 

Outdoor Play Activities in both Warm and Cold Weather ........................ . 16-62
 

Table 16-40. Play Frequency and Duration for all Child Players (from SCS-II data) .............. . 16-63
 

Table 16-41. Hand Washing and Bathing Frequency for all Child Players (from SCS-II data) ....... . 16-63
 

Table 16-42. NHAPS and SCS-II Play Duration Comparison ................................ . 16-64
 

Table 16-43. NHAPS and SCS-II Hand Wash Frequency Comparison ......................... . 16-64
 

Table 16-44. Time Spent (minutes/day) Outdoors Based on CHAD Data (Doers Only) ............. . 16-65
 

Table 16-45. Comparison of Daily Time Spent Outdoors (minutes/day), Considering Gender 

and Age Cohort (Doers Only) .............................................. . 16-66
 

Table 16-46. Time Spent (minutes/day) Indoors Based on CHAD Data (Doers Only) .............. . 16-67
 

Table 16-47. Time Spent (minutes/day) in Motor Vehicles Based on CHAD Data (Doers Only) ...... . 16-68
 

Table 16-48. Time Spent (minutes/two-day period) in Various Activities by Children Participating 

in the Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement 

(CDS) ............................................................... . 16-69
 

Table 16-49. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekday ..... . 16-70
 

Table 16-50. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day . . 16-71
 

Table 16-51. Mean Time Spent (minutes/week) in Various Activity Categories for Children, Ages 6 to 1716-72
 

Table 16-52. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years ..................... . 16-73
 

Table 16-53. Mean Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity .......... . 16-74
 

Table 17-1. Consumer Products Commonly Found in Some U.S. Households .................... . 17-7
 

Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products .............. . 17-10
 

Table 17-3. Number of Minutes Spent in Activities Working With or Near Freshly Applied 

Paints (minutes/day) ..................................................... . 17-13
 

Table 17-4. Number of Minutes Spent in Activities Working With or Near Household Cleaning
 

Agents Such as Scouring Powders or Ammonia (minutes/day) ..................... . 17-13
 

Table 17-5. Number of Minutes Spent in Activities (at home or elsewhere) Working With
 

or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) .................... . 17-13
 

Table 17-6. Number of Minutes Spent in Activities Working With or Near Glue (minutes/day) ..... . 17-14
 

Table 17-7. Number of Minutes Spent in Activities Working With or Near Solvents, Fumes or 

Strong Smelling Chemicals (minutes/day) .................................... . 17-14
 

Table 17-8. Number of Minutes Spent in Activities Working With or Near Stain or Spot Removers 

(minutes/day) .......................................................... . 17-14
 

Table 17-9. Number of Minutes Spent in Activities Working With or Near Gasoline or
 

Diesel-powered Equipment, Besides Automobiles (minutes/day .................... . 17-15
 

Child-Specific Exposure Factors Handbook Page 

September 2008 xxv 
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CSEFH 

LIST OF TABLES (Continued) 

Table 17-10. Number of Minutes Spent in Activities Working with or Near Pesticides, 

Including Bug Sprays or Bug Strips (minutes/day) .............................. . 17-15
 

Table 17-11. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at 

Specified Daily Frequencies ............................................... . 17-15
 

Table 17-12. Number of Respondents Using Any Aerosol Spray Product for Personal Care Item
 

Such as Deodorant or Hair Spray at Specified Daily Frequencies ................... . 17-16
 

Table 17-13. Number of Respondents Using a Humidifier at Home ........................... . 17-16
 

Table 17-14. Number of Respondents Indicating that Pesticides Were Applied by the Professional at 

Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies .......... . 17-16
 

Table 17-15. Number of Respondents Reporting Pesticides Applied by the Consumer at Home
 

To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies ............... . 17-17
 

Table 17-16. Number of Respondents Indicating that Pesticides Were Applied by a 

Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified 

Frequencies ........................................................... . 17-17
 

Table 17-17. Number of Respondents Reporting Pesticides Applied by the Consumer at Home to 

Eradicate Insects, Rodents, or Other Pests at Specified Frequencies ................. . 17-17
 

Table 17-18. Household Demographics, and Pesticide Types, Characteristics, and Frequency of 

Pesticide Use .......................................................... . 17-18
 

Table 17-19. Frequency of Use of Cosmetic Products ...................................... . 17-19
 

Table 17-20. Amount of Test Product used (grams) for Lipstick, Body Lotion and Face Cream ....... . 17-20
 

Table 17-21. Frequency of Use of Personal Care Products ................................... . 17-22
 

Table 17-22. Average Amount of Product Applied per Application (grams) ..................... . 17-23
 

Table 17-23. Average Amount of Product Applied per Use Day (grams) ........................ . 17-24
 

Table 17-24. Average Number of Applications Per Use Day ................................. . 17-25
 

Table 17-25. Average Amount of Product Applied Per Use Day (grams) ........................ . 17-26
 

Table 17-26. Average Amount of Product Applied Per Application (grams) ..................... . 17-27
 

Table 17-27. Characteristics of the Study Population and the Percent Using Selected Baby Care 

Products .............................................................. . 17-28
 

Page Child-Specific Exposure Factors Handbook 

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LIST OF FIGURES 

Figure 1-1. The Exposure-Dose Effect Continuum ........................................ . 1-25
 

Figure 6-1. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Awake Subjects . . 6-54
 

Figure 6-2. 5th, 10th, 25th, 50th, 75th, 90th, and 95th Smoothed Centiles by Age in Asleep Subjects . . 6-54
 

Figure 7-1. Skin Coverage as Determined by Fluorescence vs. Body Part for Children Playing 

in Wet Soils ............................................................ . 7-24
 

Figure 7-2. Gravimetric Loading vs. Body Part for Children Playing in Wet and Dry Soils .......... . 7-24
 

Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months ...................... . 8-19
 

Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months ...................... . 8-20
 

Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months .................... . 8-21
 

Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months .................... . 8-22
 

Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years ......................... . 8-23
 

Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years ........................ . 8-24
 

Child-Specific Exposure Factors Handbook Page
 

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ACRONYMS AND ABBREVIATIONS 

AAP = American Academy of Pediatrics 

ADD = Average Daily Dose 

AF = Adherence Factor 

AIR = Acid Insoluble Residue 

ANOVA = Analysis of Variance 

ARS = Agricultural Research Service 

ATSDR = Agency for Toxic Substances and Disease Registry 

ATUS = American Time Use Study 

BI = Bootstrap Interval 

BMD = Benchmark Dose 

BMI = Body Mass Index 

BMR = Basal Metabolic Rate 

BTM = Best Tracer Method 

C = Contaminant Concentration 

CARB = California Air Resources Board 

CATI = Computer Assisted Telephone Interviewing 

CDC = Centers for Disease Control and Prevention 

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 

CTFA = Cosmetic, Toiletry, and Fragrance Association 

CV = Coefficient of Variation 

DARLING = Davis Area Research on Lactation, Infant Nutrition and Growth 

DIY = Do-it-yourself 

DLW = Doubly Labeled Water 

DONALD = Dortmund Nutritional and Anthropometric Longitudinally Designed 

E or EE = Energy Expenditure 

EBF = Exclusively Breastfed 

ECG = Energy Cost of Growth 

ED = Exposure Duration 

EI = Energy Intake 

EPA = Environmental Protection Agency 

fB = Breathing Frequency 

FCID = Food Commodity Intake Database 

FITS = Feeding Infant and Toddler Study 

FQPA = Food Quality Protection Act 

F/S = Food/Soil 

g = Gram 

Page Child-Specific Exposure Factors Handbook 

xxviii September 2008 
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GAF = General Assessment Factor 

GLM = General Linear Model 

H = Oxygen Uptake Factor 

HEC = Human Equivalent Exposure Concentrations 

HPV = High Production Volume 

HR = Heart Rate 

I = Tabulated Intake Rate 

IA = Adjusted Intake Rate 

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 

IRp = Intake Rate Percentile 

IRIS = Integrated Risk Information System 

KJ = Kilo Joules 

KS = Kolmogorov-Smirnov 

kg = Kilogram 

L1 = Cooking or Preparation Loss 

L2 = Post-cooking Loss 

LADD = Lifetime Average Daily Dose 

LTM = Limiting Tracer Method 

m2 = Square Meter 

m3 = Cubic Meter 

mg = Milligram 

MJ = Mega Joules 

mL = Milliliter 

METS = Metabolic Equivalents of Work 

MSA = Metropolitan Statistical Area 

N = Number of Subjects or Respondents 

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 

NHEXAS = National Human Exposure Assessment Survey 

NIS = National Immunization Survey 

NOAEL = No-observed-adverse-effect-level 

NRC = National Research Council 

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OPP = Office of Pesticide Programs 

ORD = Office of Research and Development 

PBPK = Physiologically-Based Pharmacokinetic 

PDIR = Physiological Daily Inhalation Rate 

PSID = Panel Study of Income Dynamics 

RAGS = Risk Assessment Guidance for Superfund 

RDD = Random Digit Dial 

RfD = Reference Dose 

RfC = Reference Concentration 

RME = Reasonable Maximum Exposure 

RQ = Respiratory Quotient 

RTF = Ready to Feed 

SA = Surface Area 

SA/BW = Surface Area to Body Weight Ratio 

SCS = Soil Contact Survey 

SD = Standard Deviation 

SDA = Soaps and Detergent Association 

SE = Standard Error 

SEM = Standard Error of the Mean 

SES = Socioeconomic Status 

SPC = Science Policy Council 

SPS = Statistical Processing System 

SRD = Source Ranking Database 

TDEE = Total Daily Energy Expenditure 

TFEI = Total Food Energy Intake 

USDA = United States Department of Agriculture 

USDL = United States Department of Labor 

USDHHS = United States Department of Health and Human Services 

UV = Ultraviolet 

VO2 = Oxygen Consumption Rate 

VQ = Ventilatory Equivalent 

VR = Ventilation Rate 

W = Weight 

wi = Sample Weight Assigned to Observation xi. 

WHO = World Health Organization 

WIC = USDA’s Women, Infants, and Children Program 

xi = ith observation 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

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PREFACE 

The Exposure Factors Program of the U.S. Environmental Protection Agency’s (U.S. EPA’s) Office of 

Research and Development (ORD) has three main goals: (1) provide updates to the Exposure Factors Handbook and 

the Child-Specific Exposure Factors Handbook; (2) identify exposure factors data gaps and needs in consultation with 

clients; and (3) develop companion documents to assist clients in the use of exposure factors data. The activities under 

each goal are supported by and respond to the needs of the various program offices. 

The National Center for Environmental Assessment (NCEA) of the U.S. EPA’s ORD has prepared this 

handbook to provide information on various physiological and behavioral factors commonly used in assessing 

children’s exposure to environmental chemicals. Children have different exposure circumstances than do adults. 

Understanding these differences is key for evaluating potential for environmental hazards from pollutants. They 

consume more of certain foods and water and have higher inhalation rates per unit of body weight than adults. Young 

children play close to the ground and come into contact with contaminated soil outdoors and with contaminated dust 

on surfaces and carpets indoors. Ingestion of breast milk is another potential pathway of exposure for infants and 

young children. 

NCEA published the Exposure Factors Handbook in 1997. That document includes exposure factors and 

related data on children, as well as adults. However, the U.S. EPA Program Offices identified the need to prepare a 

document specifically for children’s exposure factors. The Child-Specific Exposure Factors Handbook is intended to 

fulfill this need. 

This handbook was first offered to the public in 2002. Since that time, the U.S. EPA has incorporated updated 

data and revised the recommendations for several exposure factors and developed a standardized set of age categories 

to be used for children’s exposure assessment. Where possible, the U.S. EPA has used this standard set of age 

categories to permit easier comparison of data among multiple sources and to allow consistency between different types 

of exposure factors. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 xxxi
 
 

 

 

 

•	 ingestion ofwater and other select liquids 

(Chapter 3); 

•	 non-dietary ingestion factors (Chapter 4); 

•	 ingestion of soil and dust (Chapter 5); 

•	 inhalation rates (Chapter 6); 

•	 dermal exposure factors such as surface area 

and adherence (Chapter 7); 

•	 body weight (Chapter 8); 

•	 intake of fruits and vegetables (Chapter 9); 

•	 intake of fish and shellfish (Chapter 10); 

•	 intake ofmeat, dairy products, and fats 

(Chapter 11); 

•	 intake of grain products (Chapter 12); 

•	 intake ofhome-produced foods(Chapter 13); 

•	 total food intake (Chapter 14); 

•	 human milk intake (Chapter 15); 

•	 activity factors (Chapter 16); and 

•	 consumer products (Chapter 17). 

•	 Less than 12 monthsold: birth to <1 month, 

1 to <3 months, 3 to <6 months, and 6 to <12 

months. 

•	 Greater than 12 months old: 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. 

Child-Specific Exposure Factors Handbook 

CSEFH 

EXECUTIVE SUMMARY 

This Child-Specific Exposure Factors 

Handbook has been prepared to focus on various 

factors used in assessing exposure, specifically for 

children ages 0 to <21 years old. This handbook 

provides nonchemical-specific data on exposure factors 

for the U.S. EPA recommended set of childhood age 

groups in the following areas: 

The Child-specific Exposure Factors 

Handbook was first published in 2002. Subsequently, 

recognizing that exposures among infants, toddlers, 

adolescents, and teenagers can vary significantly, the 

U.S. EPA published its Guidance on Selecting Age 

Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. EPA. 

2005). To the extent possible, source data for the 

independent studies cited in the earlier version of this 

handbook were obtained and re-analyzed to conform to 

the standard age categories. This update and revision 

of the 2002 interim final Child-specific Exposure 

Factors Handbook is designed specifically to 

complement the U.S. EPA’s recommended set of 

childhood age groups: 

The data presented in this handbook have 

been compiled from various sources, which include the 

U.S. EPA’s Exposure Factor Handbook (U.S. EPA, 

1997), 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 has conducted 

analysis of published primary data to present results 

for 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). Overall confidence 

ratings of high, medium, or low were derived for the 

various exposure factors based on the evaluation of the 

elements described above. 

Many scientific studies were reviewed for 

possible inclusion in this handbook. The handbook 

contains summaries of selected studies published 

through July 2008. Generally, studies were designated 

as “key” or “relevant” studies. Key studies were 

considered the most useful 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’s procedure 

for developing recommendations was as follows: 

Page Child-Specific Exposure Factors Handbook 

xxxii September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

CSEFH 

1.	 Key studies were evaluated in terms of both 

quality and relevance to specific populations 

(general U. S. population, age groups, gender, 

etc.). The criteria for assessing the quality of 

studies are described in Section 1.4. 

2.	 If only one study was classified as key for a 

particular factor, the mean value from that 

study was selected as the recommended 

central tendency 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 mean value. If 

the key studies were judged to be unequal in 

quality, relevance, or study design, the range 

of means is presented and the user of this 

handbook should employ judgment in 

selecting the most appropriate value for the 

lifestage or local population of interest. 

Recommendations for upper percentiles, 

when multiple studies were available, were 

calculated as the midpoint of the range of 

upper percentile values of the studies for each 

age group where data were available. 

3.	 Aspects of exposure factors variability have 

been discussed. This document attempts to 

characterize the variability of each of the 

factors. Variability refers to true 

heterogeneity or diversity in a population. 

Differences among individuals in a 

population are referred to as inter-individual 

variability, differences for one individual over 

time is referred to as intra-individual 

variability. Since most of the studies used to 

derive exposure factors data are short term in 

nature, they present the variability in short 

term exposures across a population sample 

and often do not allow analysis of either 

inter-temporal variability within individuals 

nor inter-individual variability of long term 

average exposures. Inter-individual 

variability in this handbook is characterized 

in one or more of the following 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. 

4.	 Uncertainties were 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. 

5.	 The U.S. EPA assigned a confidence rating of 

low, medium or high to each recommended 

value. This 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. 

6.	 Finally, the U.S. EPA developed a table for 

each exposure factor to summarize the 

recommended values for that factor. Table 

ES-1 summarizes key recommended values 

for the exposure factors included in this 

handbook. Additional recommendations and 

detailed supporting information can be found 

in the individuals chapters that address these 

factors. 

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, 1992) (i.e., mean, 

50th, 90th, 95th, 98th, and 99.9th 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. 

It is important to note, however, that these percentiles 

Child-Specific Exposure Factors Handbook Page
 

September 2008 xxxiii
 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

CSEFH 

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 percentile) 

of the distribution of values for a particular exposure 

factor. 

Most of the data presented in this handbook 

are derived from studies that target (1) the general 

population (e.g., USDA food consumption surveys) or 

(2) a sample population from a specific area or group 

(e.g., soil ingestion study using children from the 

three-city area in southeastern Washington State). 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. 

It is important to note that 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 (e.g., more 

up-to-date data of better quality and more 

representative of the population of concern). 

U.S. EPA. (1992) Guidelines for exposure assessment. 

Washington, DC: Office of Research and 

Development, Office of Health and Environmental 

Assessment. EPA/600/Z-92/001. 

U.S. EPA. (1997) Exposure factors handbook. 

Washington, DC: National Center for Environmental 

Assessment, Office of Research and Development. 

EPA/600/P-95/002Fa,b,c. 

U.S. EPA. (2005) Guidance on selecting age groups 

for monitoring and assessing childhood exposures to 

environmental contaminants (2005). U.S. 

Environmental Protection Agency, Washington, D.C., 

EPA/630/P-03/003F. 

Page Child-Specific Exposure Factors Handbook 

xxxiv September 2008 
Child-Specific Exposure Factors Handbook 

CSEFH 

Table ES-1. Summary of Recommended Exposure Factors for Children

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Ingestion of Drinking Water (mL/day) - See Chapter 3

Mean per capita95 th percentlile per capita

Mean consumer only95 th percentile consumer only 

184839470858 

227896552

1,053 

362

1,056

556

1,171 

360

1,055

467

1,147 

271837308893 

317877356912 

380

1,078

417

1,099 

447

1,235

480

1,251 

606

1,727

652

1,744 

731

1,983

792

2,002 

826

2,540

895

2,565 

Ingestion of Drinking Water (mL/kg-day) - See Chapter 3

Mean per capita95 th percentile per capita

Mean consumer only95 th percentile consumer only 

52

232137238 

48

205119285 

52

159

80

173 

41

126

53

129 

23712775 

23602662 

22612465 

16431745 

12341334 

11311232 

12351335 

Ingestion of Water while Swimming (mL/hour) - See Chapter 3

MeanUpper percentile 

--

50

100 

--

2070 

Hand-to-mouth Frequency (contacts/hour) - See Chapter 4

Indoor Mean

95 th percentile 

Outdoor Mean

95 th percentile 

----

2865

--

19521547 

20631442 

1337

5

20 

1554

9

36 

7

21

3

12 

----

Object-to-mouth Frequency (contacts/hour) - See Chapter 4

Mean95 th percentile 

--

20

-

10

-

1

-

--

Object-to-mouth Duration (minutes/hour) - See Chapter 4

Mean95 th percentile 

--

1126 

8

22 

1316 

--

Child-Specific Exposure Factors Handbook Page
 

September 2008 xxxv
 
Child-Specific Exposure Factors Handbook 

CSEFH Table ES-1. Summary of Recommended Exposure Factors for Children (Continued)

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Soil/dust Ingestion (mg/day) - See Chapter 5

Soil Central Dust CentralSoil + Dust CentralSoil pica Upper percentileGeophagy Upper percentile 

-----

303060

--

5060

100

1,000

50,000 

Inhalation Rate - Long-term (m3 /day)- See Chapter 6

Mean95 th percentile 

3.67.1 

--

4.16.1 

5.48.1 

8.0

12.8 

9.5

15.9 

10.916.2 

12.418.7 

15.123.5 

16.527.6 

Inhalation Rate - Short-term (m3 /minute) - See Chapter 6

Sleep/nap Mean

95 th percentile 

Sedentary Mean

95 th percentile 

Light Mean

95 th percentile 

Moderate Mean

95 th percentile 

Heavy Mean

95 th percentile 

3.0E-034.6E-033.1E-034.7E-037.6E-031.1E-021.4E-022.3E-022.6E-024.1E-02 

4.5E-036.4E-034.7E-036.5E-031.2E-021.6E-022.1E-022.9E-023.8E-025.2E-02 

4.6E-036.4E-034.8E-036.5E-031.2E-021.6E-022.1E-022.9E-023.9E-025.3E-02 

4.3E-035.8E-034.5E-035.8E-031.1E-021.4E-022.1E-022.7E-023.7E-024.8E-02 

4.5E-036.3E-034.8E-036.4E-031.1E-021.5E-022.2E-022.9E-024.2E-025.9E-02 

5.0E-037.4E-035.4E-037.5E-031.3E-021.7E-022.5E-023.4E-024.9E-027.0E-02 

4.9E-037.1E-035.3E-037.2E-031.2E-021.6E-022.6E-023.7E-024.9E-027.3E-02 

Skin Surface Area - Total (m2 ) - See Chapter 7 

Total Body Mean

95 th 

0.290.34 

0.330.38 

0.380.44 

0.450.51 

0.530.61 

0.610.70 

0.760.95 

1.081.48 

1.592.06 

1.842.33 

Page Child-Specific Exposure Factors Handbook 

xxxvi September 2008 
Table ES-1. Summary of Recommended Exposure Factors for Children (Continued)

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Skin Surface Area - Body Parts (m 2 ) - See Chapter 7 

Head Mean

95 th percentile 

Trunk Mean

95 th percentile 

Arms Mean

95 th percentile 

Hands Mean

95 th percentile 

Legs Mean

95 th percentile 

Feet Mean

95 th percentile 

0.0530.0620.1040.1210.0400.0470.0150.0180.0600.0700.0190.022 

0.0600.0690.1180.1360.0450.0520.0170.0200.0680.0780.0210.025 

0.0690.0800.1360.1570.0520.0600.0200.0230.0780.0910.0250.029 

0.0820.0930.1610.1820.0620.0700.0240.0270.0930.1050.0290.033 

0.0870.1010.1880.2170.0690.0790.0300.0350.1220.1410.0330.038 

0.0870.0990.2350.2700.0720.0830.0320.0370.1420.1620.0430.050 

0.1040.1300.2410.3010.1080.1350.0450.0560.2070.2590.0550.069 

0.1360.1860.3750.5140.1370.1880.0540.0740.3010.4130.0780.107 

0.1490.1940.5360.6940.2050.2660.0840.1090.4980.6450.1190.155 

0.1440.1820.5920.7500.2820.3560.0990.1260.5920.7500.1310.165 

Adherence of Solids to Skin (means; mg/cm 2 ) - See Chapter 7 for specific activities and age groups represented by these values

Residential indoorDaycare (in & outdoors)Outdoor sportsIndoor sportsActivities with soilPlaying in mudPlaying in sediment 

0.0041 (arms); 0.011 (hands); 0.0035 (legs); 0.010 (feet) 

0.024 (arms); 0.099 (hands); 0.020 (legs); 0.071 (feet) 

0.012 (face); 0.011 (arms); 0.11 (hands); 0.031 (legs) 

0.0019 (arms); 0.0063 (hands); 0.0020 (legs); 0.0022 (feet)

0.054 (face); 0.046 (arms); 0.17 (hands); 0.051 (legs); 0.20 (feet) 

11 (arms); 47 (hands); 23 (legs); 15 (feet) 

0.040 (face); 0.17 (arms); 0.49 (hands); 0.70 (legs); 21 (feet) 

Body Weight (kg) - See Chapter 8

Mean 4.8 5.6 7.4 9.2 11.4 13.8 18.6 31.8 56.8 71.6 

Total Fruit Intake (g/kg-day) a - See Chapter 9 

Mean per capita95 th percentile per capita

Mean consumer only95 th percentile consumer 

5.7

211026 

6.2

19

6.9

19 

4.6

14

5.1

15 

2.48.82.79.3 

0.83.51.13.8 

Child-Specific Exposure Factors Handbook 

CSEFH 

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September 2008 xxxvii
 
Table ES-1. Summary of Recommended Exposure Factors for Children (Continued)

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Total Vegetable Intake (g/kg-day) a - See Chapter 9 

Mean per capita95 th percentile per capita

Mean consumer only95 th percentile consumer 

4.5

15

6.2

16 

6.9

17

6.9

17 

5.9

15

5.9

15 

4.19.94.19.9 

2.96.92.96.9 

Fish and Shellfish Intake (g/kg-day) a - See Chapter 10 

General Population 

Total Fish

Mean per capita95th percentile per capita

Mean consumer only95th consumer 

----

0.43

3.04.2

10 

0.28

1.93.28.7 

0.23

1.52.26.2 

0.16

1.32.16.6 

----

Marine

Mean per capita95th percentile per capita

Mean consumer only95th percentile consumer 

----

0.31

2.33.79.3 

0.20

1.52.88.0 

0.15

1.32.05.2 

0.100.46

2.06.5 

----

Freshwater

Mean per capita95th percentile per capita

Mean consumer only95th percentile consumer 

----

0.120.71

2.37.2 

0.080.35

1.86.2 

0.080.48

1.34.4 

0.070.29

1.43.3 

----

Recreational Marine - No age-specific recommendations; see Chapter 10.

Recreational Freshwater - No age-specific recommendations; see Chapter 10.

Native American - No age-specific recommendations; see Chapter 10. 

Child-Specific Exposure Factors Handbook 

CSEFH 

Page Child-Specific Exposure Factors Handbook 

xxxviii September 2008 
Table ES-1. Summary of Recommended Exposure Factors for Children (Continued)

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Total Meat Intake (g/kg-day) a - See Chapter 11 

Mean per capita95 th percentile per capita

Mean consumer only95 th percentile consumer 

1.26.73.09.2 

4.19.84.29.8 

4.19.44.29.4 

2.96.52.96.5 

2.14.82.14.8 

Total Dairy Intake (g/kg-day) a - See Chapter 11 

Mean per capita95 th percentile per capita

Mean consumer only95 th percentile consumer 

13491658 

37883788 

23492349 

14321432 

5.6

16

5.6

16 

Total Fat Intake (g/kg-day) a - See Chapter 11 

Mean per capita95 th percentile per capita

Mean consumer only95 th percentile consumer 

5.2

16

7.8

16 

4.5

11

6.0

12 

4.18.24.48.3 

3.77.03.77.0 

4.07.14.07.1 

3.66.43.66.4 

3.45.83.45.8 

2.64.22.64.2 

1.63.01.63.0 

1.32.71.32.7 

Total Grain Intake (g/kg-day)a - See Chapter 12 

Mean per capita95 th percentile per capita

Mean consumer only95 th percentile consumer 

2.58.63.69.2 

6.4

12

6.4

12 

6.3

12

6.3

12 

4.38.24.38.2 

2.55.12.55.1 

Child-Specific Exposure Factors Handbook 

CSEFH 

Child-Specific Exposure Factors Handbook Page
 

September 2008 xxxix
 
Table ES-1. Summary of Recommended Exposure Factors for Children (Continued)

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Home-produced Food Intake (g/kg-day) b - See Chapter 13 

Fruits Mean

95 th percentile 

--

8.7

60.6 

4.18.9 

3.6

15.8 

1.98.3 

Vegetables Mean

95 th percentile 

--

5.2

19.6 

2.57.7 

2.06.2 

1.56.0 

Meats Mean

95 th percentile 

--

3.7

10.0 

3.69.1 

3.7

14.0 

1.74.3 

Fish Mean

95 th percentile 

--

2.87.1 

1.54.7 

Total Food Intake (g/kg-day) - See Chapter 14

Mean per capita95 th percentile per capita 

2061 

1640 

2865 

56

134 

90

161 

74

126 

61

102 

4070 

2445 

1835 

Human Milk Intake (mL/day) - See Chapter 15

MeanUpper percentile 

510950 

690980 

770

1,000 

620

1,000 

NANA 

Human Milk Intake (mL/kg-day) - See Chapter 15

MeanUpper percentile 

150220 

140190 

110150 

83

130 

NANA 

Lipid Intake from Human Milk (mL/day) - See Chapter 15

MeanUpper percentile 

2038 

2740 

3042 

2542 

NANA 

Child-Specific Exposure Factors Handbook 

CSEFH 

Page Child-Specific Exposure Factors Handbook 

xl September 2008 
Table ES-1. Summary of Recommended Exposure Factors for Children (Continued)

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Lipid Intake from Human Milk (mL/kg-day) - See Chapter 15

MeanUpper percentile 

6.08.7 

5.58.0 

4.26.0 

3.35.2 

NANA 

Activity Factors - See Chapter 16

Mean (minutes/day) 

Indoors, total Mean Outdoors, total Mean 

1,440

0 

1,432

8 

1,414

26 

1,301

139 

1,353

36 

1,316

76 

1,278

107 

1,244

132 

1,260

100 

1,248

102 

Indoors, at residence Mean

95th 

Showering Mean

95 th 

Bathing Mean

95 th 

Playing on sand/gravel Mean

95th 

Playing on grass Mean

95th 

Playing on dirt Mean

95th 

1,1081,440

15

-

193018

-

52

-

33

-

1,0651,440

20

-

233243

121

68

121

56

121 

979

1,296

2244234553

121

62

121

47

121 

957

1,355

1734246060

121

79

121

63

121 

893

1,275

1841244667

121

73

121

63

121 

889

1,315

1840254367

121

75

121

49

120 

833

1,288

2045336083

-

60

-

30

-

Mean (minutes/month) 

Swimming Mean

95th 

96

-

105

-

116181 

137181 

151181 

139181 

145181 

Child-Specific Exposure Factors Handbook 

CSEFH 

Child-Specific Exposure Factors Handbook Page 

September 2008 xli 
Table ES-1. Summary of Recommended Exposure Factors for Children (Continued)

Age Group 0 to <1

mo. 

1 to <3

mos. 

3 to <6

mos. 

6 to <12

mos. 

1 to <2

yrs. 

2 to <3

yrs. 

3 to <6

yrs. 

6 to <11

yrs. 

11 to

<16 yrs. 

16 to<18

yrs. 

18 to <21

yrs. 

Consumer Products - See Chapter 17

No age-specific recommendations; see Chapter 17.

a Analysis was conducted using slightly different 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 recommended age categories closest to those used in the analysis.

b 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). Thus, age groups in the original study are slightly different than those presented here. See chapter for details.

- = No data available and/or no recommendation made.NA = Not applicable. 

Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

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AUTHORS, CONTRIBUTORS, AND 

REVIEWERS 

The National Center for Environmental 

Assessment (NCEA), Office of Research and 

Development (ORD) was responsible for the 

preparation of this handbook. Adraft of this document 

was prepared by the Exposure Assessment Division of 

Versar Inc. in Springfield, Virginia, under U.S. EPA 

Contract No. EP-W-04-035. Earlier versions (i.e., 

2002 and 2005) were prepared under Contract Nos. 

68-W-99-0041 and EP-W-04-035. The U.S. 

EPA/NCEA’s Jacqueline Moya served as Work 

Assignment Manager for both the original and the 

revision, providing overall direction, technical 

assistance, and serving as contributing author. The 

draft was reviewed by U.S. EPA staff who have an 

interest in exposure factors as well as by an 

independent panel of outside experts. 

AUTHORS WORD 

PROCESSING 

Versar, Inc. Versar, Inc. 

Adria Diaz Susan Perry 

Marit Espevik Malikah Moore 

Christopher Greene Valerie Schwartz 

Ron Lee 

Clarkson Meredith 

Nica Mostaghim 

Chuck Peck 

Todd Perryman 

Linda Phillips 

Kathleen Saunders-Coon 

Diane Sinkowski 

Patricia Wood 

U.S. EPA
 

Becky Cuthbertson
 

Jacqueline Moya
 

Linda Phillips
 

John Schaum
 

Laurie Schuda
 

The following U.S. EPA individuals reviewed 

an earlier draft of this document and provided valuable 

comments: 

Marcia Bailey, U.S. EPA, Region X 

Gary Bangs, U.S. EPA, Risk Assessment Forum, 

Office of Research and Development 

Denis R. Borum, U.S. EPA, Office of Water, Health 

and Ecological Criteria Division 

Dave Crawford, U.S. EPA, Office of Solid Waste 

Becky Cuthbertson, U.S. EPA, Office of Solid Waste 

Michael Dellarco, U.S. EPA, National Center for 

Environmental Assessment 

Lynn Delpire, U.S. EPA, Office of Prevention, 

Pesticides, and Toxic Substances 

Jeff Evans, U.S. EPA, Office of Pesticide Programs 

Cathy Fehrenbacher, U.S. EPA, Office of Prevention, 

Pesticides, and Toxic Substances 

Michael Firestone, U.S. EPA, Office of Children’s 

Health Protection 

Brenda Foos, U.S. EPA, Office of Children’s Health 

Protection 

Henry Kahn, U.S. EPA, National Center for 

Environmental Assessment 

Child-Specific Exposure Factors Handbook Page 

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Youngmoo Kim, U.S. EPA, Region VI 

Steve Kroner, U.S. EPA, Office of Solid Waste 

Tom McCurdy, U.S. EPA, National Exposure 

Research Laboratory 

David Miller, U.S. EPA Office of Pesticide Programs 

Deirdre Murphy, U.S. EPA, Office of Air Quality 

Planning and Standards 

Steve Nako, U.S. EPA, Office of Pesticide Programs 

Marian Olsen, U.S. EPA, Region II 

Glenn Rice, U.S. EPA, National Center for 

Environmental Assessment 

Harvey Richmond, U.S. EPA, Office of Air Quality 

Planning and Standards 

David Riley, U.S. EPA Region VI 

Marybeth Smuts, U.S. EPA, Region I 

Marc Stifelman, U.S. EPA, Region X 

Valerie Zartarian, U.S. EPA, National Exposure 

Research Laboratory 

Acknowledgment 

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 

Bernard Scheneider, Office of Pesticide Programs 

Nicole Tulve, National Exposure Research Laboratory 

Philip Villanueva, Office of Pesticide Programs 

Jianping Xue, National Exposure Research Laboratory 

Valerie Zartarian, National Exposure Research 

Laboratory 

This document was reviewed by an external panel of 

experts. The panel was composed of the following 

individuals: 

Ed Avol, Keck School of Medicine, University of 

Southern California 

James Bruckner, College of Pharmacy, University of 

Georgia 

Anna Fan, California Environmental Protection 

Agency 

Panos Georgopoulos, UMDNJ Robert Wood Johnson 

Medical School 

Lynn Goldman, Johns Hopkins Bloomberg School of 

Public Health 

Annette Guiseppi-Elie, Dupont Engineering 

Dale Hattis, Clark University 

Diane Rohiman, Oregon Health and Science 

University 

P. Barry Ryan, Emory University 

Edward Stanek, University of Massachusetts at 

Amherst 

Alan Stern, University of Medicine and Dentistry of 

New Jersey 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

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Nga Tran, Exponent 

Bernard Weiss, University of Rochester School of 

Medicine and Dentistry 

Robin Wyatt, Columbia University 

Rosemary Zaleski, ExxonMobil Biomedical Sciences, 

Inc. 

Finally, the following U.S. EPA/NCEA individuals 

reviewed this document for final clearance: 

David Bussard 

Jeffrey Frithsen 

Nicole Hagan 

Charles Ris 

John Vandenberg 

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Chapter 1 - Introduction 

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1 INTRODUCTION 

1.1 PURPOSE 

The purpose of the Child-Specific Exposure 

Factors Handbook is to provide exposure factors for 

children. The handbook highlights the changes in 

risk assessment practices that were first presented in 

the U.S. Environmental Protection Agency’s (EPA) 

Cancer Guidelines, regarding the need to consider 

children as lifestages rather than as subpopulations 

(U.S. EPA, 2005b). It also emphasizes a major 

recommendation in U.S. EPA’s Supplemental 

Guidance for Assessing Susceptibility from Early-Life 

Exposure to Carcinogens (U.S. EPA, 2005c) to sum 

exposures and risks across lifestages 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 the 

early 2000's, and is consistent with the U.S. EPA's 

new set of recommended childhood age groups (U.S. 

EPA 2005a), including a standardized way to define 

specific age groups. 

As with the earlier version of the handbook, 

this new version summarizes key data on human 

behaviors and characteristics that affect children’s 

exposure to environmental contaminants, and 

provides recommended values to use for these factors. 

These recommendations 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. The decision as to whether to use sitespecific 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 discussions of 

the issues that assessors may consider in assessing 

exposure among children of different ages, and may 

be used in conjunction with the U.S. EPA document 

entitled Socio-demographic Data Used for Identifying 

Potentially Highly Exposed Populations (U.S. EPA, 

1999). 

1.2 INTENDED AUDIENCE 

The Child-Specific Exposure Factors 

Handbook may be used by exposure and risk 

assessors, economists, and other interested parties as 

a source for data and/or U.S. EPA recommendations 

on numeric estimates for behavioral and physiological 

characteristics needed to estimate childhood exposure 

to toxic contaminants. 

1.3 BACKGROUND 

Because of physiological and behavioral 

differences, exposures among children are expected to 

be different from exposures among adults. Children 

may be more exposed to some environmental 

contaminants, because they consume more of certain 

foods and water per unit of body weight and have a 

higher ratio of body surface area to volume than adults. 

Equally important, rapid changes in behavior and 

physiology may lead to differences in exposure as a 

child grows up. Recognizing that exposures among 

infants, toddlers, adolescents, and teenagers can vary 

significantly, the U.S. EPA published its “Guidance 

on Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental Contaminants 

(U.S. EPA. 2005a).” This update and revision of the 

2002 interim final Child-Specific Exposure Factors 

Handbook (U.S. EPA, 2002a) is designed specifically 

to complement U.S. EPA’s recommended set of 

childhood age groups: 

? Less than 12 months old: birth to <1 month, 

1 to <3 months, 3 to <6 months, and 6 to <12 

months. 

? Greater than 12 months old: 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. 

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 

(Eskenazi et al., 1999; Gurunathan et al., 1998; Lewis 

et al., 1999; Nishioka et al., 1999; Garry, 2004). 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). Pesticides may be 

tracked into their homes by family members. In 

addition, children living in agricultural areas may also 

play in nearby fields or be exposed via consumption of 

Child-Specific Exposure Factors Handbook Page 

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Chapter 1 - Introduction 

CSEFH 

contaminated human milk from their farmworker 

mother (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, 2000a). The immaturity of metabolic 

enzyme systems and clearance mechanisms in young 

children can result in longer half-lives of 

environmental contaminants (Ginsberg et al., 2002, 

Clewell et al., 2004). The cellular immaturity of 

children and the ongoing growth processes account 

for elevated risk (AAP, 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 among children 

(Myers et al., 2000). Other authors have described 

the importance of exposure timing (i.e., 

preconceptional, prenatal, and postnatal) and how it 

affects the outcomes observed (Selevan et al., 2000). 

Breysee et al. (2005) suggests that higher levels of 

exposure to indoor air pollution and allergens among 

inner-city children compared to non-inner-city 

children may explain the difference in asthma levels 

between these two groups. With respect to 

contaminants that are carcinogenic via a mutagenic 

mode of action, 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, 2005c). 

Executive Order 13045: Protection of 

Children from Environmental Health Risks and 

Safety Risks, signed in 1997, requires all federal 

agencies to address health and safety risks to 

children, to coordinate research priorities on 

children’s health, and to ensure that their standards 

take into account special risks to children (EO, 1997). 

To implement the Order, the U.S. EPA established 

the Office of Children’s Health Protection (OCHP) 

(renamed the Office of Children’s Health Protection 

and Environmental Education (OCHPEE) in 2005), 

whose job it is to work with Program and regional 

offices within the U.S. EPA to promote a safe and 

healthy environment for children by ensuring that all 

regulations, standards, policies, and risk assessments 

take into account risks to children. Legislation, such as 

the Food Quality Protection Act and the Safe Drinking 

Water Act amendments, has made coverage of 

children’s health issues more explicit, and research on 

children’s health issues is continually expanding. As 

a result of the emphasis on children’s risk, the U.S. 

EPA Office of Research and Development (ORD) 

developed a Strategy for Research on Environmental 

Risks to Children (U.S. EPA, 2000a). The goal of the 

Strategy is to improve the quality of risk assessments 

for children. This Child-Specific Exposure Factors 

Handbook is also intended to support the U.S. 

EPA/ORD/NCEA’s efforts to improve exposure and 

risk assessments for children. 

In 1997, the U.S. EPA/ORD/NCEA published 

the Exposure Factors Handbook (U.S. EPA, 1997a). 

The handbook includes exposure factors and related 

data on both adults and children. Subsequently, the 

U.S. EPA Program Offices identified the need to 

consolidate all children’s exposure data into a single 

document and the Child-Specific Exposure Factors 

Handbook was published in 2002 to fulfill this need. 

This handbook updates the 2002 edition of the ChildSpecific Exposure Factors Handbook (U.S. EPA 

2002a). It provides non-chemical-specific data on 

exposure factors that can be used to assess 

contributions from dietary and non-dietary ingestion 

exposure, dermal exposure, and inhalation exposure 

among children. Although the preconceptional and 

prenatal (fetal) life stages are important to consider 

they are not covered in this handbook. 

Preconceptional exposures are included in the 

Exposure Factors Handbook since they relate to 

maternal and paternal exposures, and exposure factors 

for pregnant and lactating women are being developed 

as part of a separate effort. 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. The U.S. EPA 

Page Child-Specific Exposure Factors Handbook 

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Chapter 1 - Introduction 

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has developed guidance on how to use PBPK 

information in risk assessment. More information on 

the application of PBPK models and supporting data 

is found in U.S. EPA (2006a, 2006b). 

This handbook provides updated exposure 

factor information for children in the following areas: 

•	 ingestion of water and other select 

liquids; 

•	 non-dietary ingestion; 

•	 soil and dust ingestion; 

•	 inhalation rates; 

•	 dermal exposure factors such as surface 

area and adherence; 

•	 body weight; 

•	 intake of fruits and vegetables; 

•	 intake of fish and shellfish; 

•	 intake of meat, dairy products, and fats; 

•	 intake of grain products; 

•	 intake of home-produced foods; 

•	 total food intake; 

•	 human milk intake; 

•	 activity factors; and 

•	 consumer products. 

This handbook is a compilation of available 

data from a variety of sources. Most of these data 

have been described in detail in the U.S. EPA’s 

Exposure Factors Handbook (1997a), but data 

published after the release of the Exposure Factors 

Handbook are also included here. This latest 

handbook updates the 2002 interim final ChildSpecific Exposure Factors Handbook (U.S. EPA 

2002). With very few exceptions, the data presented 

here derive from the analyses of the individual study 

authors. Because the studies included in this 

handbook vary 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 age ranges to 

describe data for children. In most cases, the original 

data are unavailable, and the study results cannot be 

reallocated into the standard age groups used in this 

handbook. Every effort has been made to reallocate 

source data into the standard age groups 

recommended by the U.S. EPA in the report entitled 

Guidance on Selecting Age Groups for Monitoring and 

Assessing Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005a; see Section 1.7), 

when sufficiently detailed data are available. 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. 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. 

Most of the data presented in this handbook 

are derived from studies that target (1) the general 

population (e.g., USDA food consumption surveys) or 

(2) a sample population from a specific area or group 

(e.g., fish consumption among Native American 

children). 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, the 

reader is referred to Socio-demographic Data Used for 

Identifying Potentially Highly Exposed Populations 

(U.S. EPA, 1999). 

Because of the large number of tables in this 

handbook, tables are presented at the end of each 

chapter, before the appendices, if any. In conjunction 

with the Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005a), this 

handbook is adopting 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). 

1.4	 SELECTION OF STUDIES FOR THE 

HANDBOOK 

Information in this handbook has been 

summarized from studies documented in the scientific 

literature and other available sources. Studies were 

chosen that were seen as useful and appropriate for 

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Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH 

estimating exposure factors for children. The 

handbook contains summaries of selected studies 

published through July 2008. 

Certain studies described in this handbook 

are designated as “key,” that is, the most useful for 

deriving exposure factors. The recommended values 

for most exposure factors are based on the results of 

the key studies (See Section 1.5). Other studies are 

designated "relevant," meaning applicable or 

pertinent, but not necessarily the most important. 

This distinction was made on the strength of the 

attributes listed in the "General Assessment Factors" 

listed below. 

1.4.1 General Assessment Factors 

Many scientific studies were reviewed for 

possible inclusion in this handbook. Generally, 

studies identified in the Exposure Factors Handbook 

(U.S. EPA, 1997a) as key studies are also included in 

this handbook as key studies. Also included are new 

studies that became available after publication of the 

Exposure Factors Handbook and the 2002 ChildSpecific Exposure Factors Handbook (U.S. EPA, 

2002a). Key studies from the Exposure Factors 

Handbook were generally defined as the most useful 

for deriving recommendations for exposure factors. 

The recommended values for most exposure factors 

are based on the results of these studies. 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 2002b, 

2003a, 2006c). When evaluating scientific and 

technical information, the U.S. EPA’s Science Policy 

Council (SPC) 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 2003a). 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. 

1.4.2 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 were evaluated 

according to the following: 

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 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 

exposures 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. 

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 

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bias (i.e., an over 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.

 The 

applicability and utility of the available studies were 

evaluated based on the following criteria: 

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. 

Representativeness of the Population: 

More confidence was placed in studies that 

addressed the U.S. population. Data from 

populations outside the U.S. were sometimes 

included if behavioral patterns or other 

characteristics of exposure were similar. 

Studies seeking to characterize a particular 

region or sub-population 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. 

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-ofthe-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. 

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 are 

documented. Clarity and completeness was evaluated 

based on the following criteria. 

Accessibility: Studies that the user could 

access in their entirety, if needed, were 

preferred. 

Reproducibility: Studies that contained 

sufficient information so that methods could 

be reproduced, or could be evaluated, based 

on the details of the author’s work, were 

preferred. 

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. 

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(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. The types of uncertainty include: 

scenario, parameter, and model. The uncertainty and 

variability associated with the studies was evaluated 

based on the following criteria. 

Variability in the population: Studies 

were sought that characterized any 

variability within populations. The 

variability associated with the studies 

presented in this handbook is characterized 

as described in Section 1.5. Higher 

confidence ratings were given to exposure 

factors that were based on studies where 

variability was well characterized. 

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 

inherent variability in environmental and 

exposure-related parameters or 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: 

Peer review: Studies selected were those 

from the peer-reviewed literature and final 

government reports. Unpublished and 

internal or interim reports were avoided. 

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. 

1.5	 APPROACH USED TO DEVELOP 

RECOMMENDATIONS FO R 

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, gender, etc.). The criteria for assessing the 

quality of studies are described in Section 1.4. 

(2) Single 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 mean value. If the 

key studies were judged to be unequal in quality, 

relevance, or study design, the range of means is 

presented and the user of this handbook must employ 

judgment in selecting the most appropriate value for 

the population of interest. Recommendations for upper 

percentiles, when multiple studies were available, were 

calculated as the midpoint of the range of upper 

percentile values of the studies for each age group 

where data were available. 

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(3) 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 base, variability is 

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 

are made where appropriate based on the adequacy of 

the supporting data. The list of exposure factors and 

the way in which variability has been characterized 

throughout this handbook (i.e., average, median, 

upper percentiles, multiple percentiles, fitted 

distribution) are presented in Table 1-1. 

In the 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, 1992a) (i.e., mean, 

50th, 90th, 95th, 98th, and 99.9th 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. 

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 percentile) of the distribution of values for 

a particular exposure factor. 

(4) 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 discussion of variability and 

uncertainty for exposure factors is presented in 

Chapter 2 of this handbook. 

(5) Confidence Ratings: Finally, the U.S. EPA 

assigned a confidence rating of low, medium or high 

to each recommended value. This 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 

General Assessment Factors (GAFs) described in 

Section 1.4. 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 that was 

used to determine these ratings. Recommendations 

given in this handbook are accompanied by a 

discussion of the rationale for their rating. 

It is important to note that 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 were subjective and 

based on the professional judgement of the authors of 

this handbook. 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 

tapwater intake. In the case of tapwater 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 U.S." because the U.S. EPA 

specifically sought studies for the handbook that met 

these criteria. 

The elements in Table 1-2 were important 

considerations for inclusion of a study in this 

handbook. However, a high score for these elements 

did not necessarily translate into a high overall score. 

Other considerations went into determining the overall 

score. One such consideration was the ease at which 

the exposure factor of interest could be measured. For 

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example, soil ingestion by children can be estimated 

by measuring, in the feces of children, the levels of 

certain elements found in soil. Body weight, 

however, can be measured directly, and it is therefore 

a more reliable measurement. 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. 

(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. 

1.6	 SUGGESTED REFERENCES FOR USE 

IN CONJUNCTION WITH THIS 

HANDBOOK 

Some of the steps for performing an 

exposure assessment are: (1) identifying 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 time, 

frequency, and duration; and (5) identifying the 

exposed population. 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, 1986a); 

•	 Selection Criteria for Mathematical Models 

Used in Exposure Assessments: Surface 

Water Models (U.S. EPA, 1987); 

•	 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, 1989); 

•	 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, 1992a); 

•	 Dermal Exposure Assessment: Principles 

and Applications (U.S. EPA, 1992b); 

•	 Estimating Exposures to Dioxin-Like 

Compounds (U.S. EPA, 1994a); 

•	 Soil Screening Guidance (U.S. EPA 1996a); 

•	 Series 875 Occupational and Residential 

Exposure Test Guidelines - Final 

Guidelines - Group A - Application Exposure 

Monitoring Test Guidelines (U.S. EPA 

1996b); 

•	 Series 875 Occupational and Residential 

Exposure Test Guidelines - Group B - Post 

Application Exposure Monitoring Test 

Guidelines (U.S. EPA 1996c); 

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•	 Policy for Use of Probabilistic Analysis in 

Risk Assessment at the U.S. Environmental 

Protection Agency, (U.S. EPA, 1997b); 

•	 Guiding Principles for Monte Carlo 

Analysis (U.S. EPA, 1997c); 

•	 Sociodemographic Data for Identifying 

Potentially Highly Exposed Populations 

(U.S. EPA, 1999); 

•	 Options for Developing Parametric 

Probability Distributions for Exposure 

Factors (U.S. EPA 2000b); 

•	 Risk Assessment Guidance for Superfund, 

Volume I, Part D, Standardized Planning, 

Reporting, and Review of Superfund Risk 

Assessments (U.S. EPA, 2001a); 

•	 Risk Assessment Guidance for Superfund 

Volume III, Part A, Process for Conducting 

Probabilistic Risk Assessments (U.S. EPA, 

2001b); 

•	 Framework for Cumulative Risk Assessment 

(U.S. EPA, 2003b); 

•	 Example Exposure Scenarios (U.S. EPA, 

2003c); 

•	 Risk Assessment Guidance for Superfund, 

Volume I, Part E, Supplemental Guidance 

for Dermal Risk Assessment (U.S. EPA, 

2004); 

•	 Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants 

(U.S. EPA, 2005a); 

•	 Cancer Guidelines for Carcinogen Risk 

Assessment Supplemental Guidance for 

Assessing Susceptibility from Early-Life 

Exposure to Carcinogens (U.S. EPA, 

2005b); 

•	 Supplemental Guidance for Assessing 

Susceptibility from Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005c); 

•	 Protocol for Human Health Risk Assessment 

Protocol for Hazardous Waste Combustion 

Facilities (U.S. EPA, 2005d); 

•	 A Framework for Assessing Health Risk of 

Environmental Exposures to Children 

(Final). (U.S. EPA 2006d); and 

•	 Concepts, methods, and data sources for 

cumulative health risk assessment of multiple 

chemicals, exposures and effects: a resource 

document (Final) (U.S. EPA, 2008). 

These documents may serve as valuable information 

resources to assist in the assessment of exposure. The 

reader is encouraged to refer to them for more detailed 

discussion. 

1.7	 THE USE OF AGE GROUPINGS WHEN 

ASSESSING EXPOSURE 

When this handbook was first published in 

2002, 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 judgement. More recently, 

the U.S. EPA has endeavored to establish a consistent 

set of age groupings and publish guidance on this topic 

(U.S. EPA 2005a). This revision of the handbook 

attempts to present data in a manner consistent with 

the U.S. EPA’s recommended set of age groupings. 

The development of standardized age bins 

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, 2001c). The purpose of this workshop was 

to gain insight and input into factors that need to be 

considered when developing standardized age bins and 

identify future research necessary to accomplish these 

goals. Panelists were divided into two groups. One 

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group focused their discussions on defining and 

characterizing the important facets of behavioral 

development during childhood, while the other group 

focused on defining and characterizing physiological 

development during childhood. During the 

workshop, it was recognized that the ultimate goal of 

exposure assessment is to develop a day-to-day model 

of human life that can predict the chemical exposures 

an individual is likely to face at any point in life. 

However, this is not likely to be accomplished in the 

near future, and assessors often need to classify 

individuals into age bins in order to simplify the 

exposure model. The recommendations listed below 

are those of the panel members and were considered 

by the U.S. EPA in the development of age 

groupings: 

•	 Panelists agreed that child development is a 

series of discrete events, but these events 

occur along a continuum. 

•	 Age grouping/bins are a useful guide to 

fulfill the Agency’s immediate need, but are 

only a crude approximation of an underlying 

distribution. Ultimately, sufficient data 

should be gathered to develop a continuous 

multivariate model that can replace bins. 

•	 Adequacy of existing exposure data is highly 

variable. 

•	 A considerable amount of additional 

information already exists, but it is dispersed 

in the literature. It was recommended that 

the U.S. EPA consults with experts in 

developmental biology, physiology, 

pharmacology, and toxicology and conducts 

an in-depth review of the literature. 

•	 Long term research should include the 

development of integrated data sets that 

combines information about the exposure 

factors with biomarkers of exposure and 

effects. 

•	 The definition of age groups/bins for 

childhood exposure assessment are 

inextricably linked to toxicokinetic and 

toxicodynamic issues. 

•	 The two break out groups (i.e., behavioral 

and physiological) offered the following 

preliminary ideas for age groupings: 

Age grouping based on behavioral 

characteristics 

0-2 months 

2 - 6 months 

6-12 months 

1-2 years 

2-6 years 

6-11 years 

11-16 years 

16-21 years 

Age grouping based on physiological 

characteristics 

0-1 month 

1-6 months 

6-12 months 

1- 3 years 

3-9 years 

9-21 years 

One can observe that there was fairly good 

agreement among the two groups with regard to the 

age groupings that are important for infants and 

toddlers. However, there was some disagreement with 

regard to the older children. Appropriate age 

groupings depend not only on behavioral and 

physiological characteristics, but also on the specific 

scenario being studied and chemical of concern. 

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, 2005a). This revision of 

the handbook was developed specifically to present 

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, 2005a) are 

as follows: 

Birth to <1 month 

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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
 

1.8	 CONSIDERING LIFESTAGE WHEN 

CALCULATING EXPOSURE AND 

RISK 

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 2005a) involves the need to 

sum age-specific differences in exposure 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, 2005c). When assessing 

chronic risks (i.e., exposures greater than 10 percent 

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 lifestage; this handbook provides data 

arrayed by childhood age in order to follow this new 

guidance (U.S. EPA 2005a). This approach is 

expected to increase the accuracy of risk assessments, 

because it will take into account lifestage differences 

in exposure. Depending on whethe r 

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 for Assessing 

Susceptibility from Early-Life Exposure to 

Carcinogens 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. This guidance describes such a 

case for carcinogens that act via a mutagenic mode of 

action, where age dependent potency adjustments 

factors (ADAFs) of 10x and 3x are recommended for 

children ages birth < 2 years, and 2 < 16 years, 

respectively when there is exposure during those years 

and available data are insufficient to derive chemicalspecific adjustment factors. 

Table 1-3, along with Chapter 6 of the 

“Supplemental Guidance”have been developed to help 

the reader understand how to use the new sets of 

exposure and potency age groupings when calculating 

risk through the integration of lifestage specific 

changes in exposure and potency. 

Thus, Lifetime Cancer Risk (for a population 

with average life expectancy of 70 years) = ? 

(Exposure x Duration/70 yrs x Potency x ADAF) 

summed across all the age groups presented in Table 

1-3. 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. 

1.9	 FUNDAMENTAL PRINCIPLES OF 

EXPOSURE ASSESSMENT 

The definition of exposure as used by the 

International Programme on Chemical Safety (IPCS, 

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.” This means contact 

with the visible exterior of a person such as the skin, 

and openings such as the mouth, nostrils, and lesions. 

The process of a chemical 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 1-1 (U.S. EPA, 2003d; IPCS, 2006). The 

process begins with a chemical or agent released from 

a source into the environment. Once in the 

environment, the chemical or agent can be transformed 

and transported through the environment via air, 

water, soil, dust, and diet. Individuals become in 

contact with the chemical through inhalation, 

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ingestion, or skin/eye contact. The individual’s 

activity patterns as well as the concentration of the 

chemical will determine the magnitude, frequency, 

and duration of the exposure. The exposure becomes 

an absorbed dose when the chemical crosses an 

absorption barrier. When the chemical 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 

1-1 indicates the specific information that may be 

needed to characterize each box. 

1.9.1 Dose Equations 

Starting with a general integral equation for 

exposure (U.S. EPA, 1992a), 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 noncancer effects, averages exposures 

or doses over the period of time exposure occurred. 

The ADD can be calculated by averaging the 

potential dose over body weight and an averaging 

time. 

The exposure can be expressed as follows: 

External Dose = C × IR × E (Eqn 1­2) 

Where: 

C = Contaminant Concentration 

IR = Intake Rate 

ED = Exposure Duration 

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. 

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 food containing the 

contaminant of interest that an individual ingests 

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 the rate 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 soil that adheres to the skin. 

The exposure duration is the length of time of 

contaminant contact. The length time a person lives in 

an area, frequency of bathing, time spent indoors 

versus outdoors, etc., all affect the exposure duration. 

Chapter 16, Activity Factors, gives some examples of 

population behavior/activity patterns 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 exposure equation. When they change with 

time, a summation approach is needed to calculate 

exposure. 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 ADD’s should be 

calculated for each age group considered. Chronic 

exposures can then be calculated by summing across 

each lifestage-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 the 

Equation 1-1, with lifetime replacing averaging time. 

While the use of LADD may be appropriate when 

developing screening level estimates of cancer risk, as 

discussed in Section 1.8 above, the U.S. EPA is now 

recommending that risks should be calculated by 

integrating exposures or risks throughout all lifestages 

(U.S. EPA, 1992a). 

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 

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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 potential 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 

exposure 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 noncancer 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 exposure in a way which can be 

combined with the dose-response relationship to 

calculate risk. 

The body weight to be used in the exposure 

Equation 1-1 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 surveys, and 

they were explicitly factored into the food intake data 

in order to calculate the intake as g/kg body weightday. In this case, the body weight has already been 

included in the “intake rate” term in Equation 1-2, 

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 1-1) 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 lifestage can be 

 made using a scaling factor of BW3⁄4 (U.S. EPA 

2006d, 2006e). 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 and inhalation rates. 

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 longterm 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 contaminant 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, and reference concentrations, are 

based (U.S. EPA, 1994b). 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 lifestage-particular 

physiological characteristics in the dosimetry analysis 

may result in a refinement to the human equivalent 

concentration to insure relevance in risk assessment 

across lifestages, or might conceivably conclude with 

multiple human equivalent concentrations, and 

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corresponding inhalation unit risk values (e.g., 

separate for childhood and adulthood) (U.S. EPA, 

2005b). The RfC methodology, which is described in 

Methods for Derivation of Inhalation Reference 

Concentrations and Applications of Inhalation 

Dosimetry (U.S. EPA, 1994b), allows the user to 

incorporate population-specific assumptions into the 

models. The reader is referred to U.S. EPA guidance 

(U.S. EPA, 1994b) on how to make these 

adjustments. 

There are no specific exposure factor 

assumptions in the derivation of Reference Doses 

(RfDs). The assessment of the potential for adverse 

health effects in infants and children is part of the 

overall hazard and dose-response assessment for a 

chemical. Available data pertinent to children’s 

health risks are evaluated along with data on adults 

and the no-observed-adverse-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 children separately 

from the assessment for the general population or 

other population subgroups. 

1.9.2	 Use of Exposure Factors Data in 

Probabilistic Analyses 

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. 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 

1.9.1. 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. Probabilistic analysis is also 

not necessary when conducting assessments 

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. 

•	 It is important to note that the selection of 

distributions can be highly site-specific and 

dependent on the purpose of the assessment. 

In some cases the selection of distributions 

are driven by specific legislation. It will 

always involve some degree of judgment. 

Distributions derived from national data may 

not represent local conditions. The assessor 

needs to evaluate the site-specific data, when 

available, to assess 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 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 to be used in 

probabilistic analysis may be derived by 

fitting an appropriate function to empirical 

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Chapter 1 - Introduction 

CSEFH 

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 

itself 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. 

- 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. 

- assume a distribution. (The rationale for the 

selection of a distribution should be 

discussed at length.) There are, however, 

cases where assuming a distribution is not 

recommended. These include: 

-- data are missing or very limited for a 

key parameter; 

-- data were collected over a short time 

period and may not represent long term 

trends (the respondent usual behavior) ­

examples include: food consumption 

surveys; activity pattern data; 

-- 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 

-- 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. 

1.10 CUMULATIVE EXPOSURES 

The U.S. EPA recognizes that children 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, 2003d, U.S. EPA, 2008). Over 

the last several years, the U.S. EPA has developed a 

methodology for assessing risk from multiple 

chemicals (U.S. EPA, 1986b, 2000c). For more 

information, the reader is referred to the U.S. EPA’s 

Framework for Cumulative Risk Assessment (U.S. 

EPA, 2003b). 

1.11 ORGANIZATION 

The handbook is organized as follows: 

Chapter 1	 Introduction 

Chapter 2	 Variability and uncertainty 

Chapter 3	 Ingestion of water and other 

select liquids 

Chapter 4	 Non-dietary ingestion 

Chapter 5	 Soil and dust ingestion 

Chapter 6	 Inhalation rates 

Chapter 7	 Dermal exposure factors 

Chapter 8	 Body weight 

Chapter 9	 Intake of fruits and vegetables 

Chapter 10	 Intake of fish and shellfish 

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Chapter 1 - Introduction 

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Chapter 11	 Intake of meats, dairy products, 

and fats 

. Chapter 12 Intake of grain products 

Chapter 13	 Intake of home-produced foods 

Chapter 14	 Total food intake 

Chapter 15 Human milk intake 

Chapter 16	 Activity factors 

Chapter 17	 Consumer products 

Recommended values for exposure factors 

are presented at the beginning of each chapter, 

followed by detailed discussions of the data on 

which these recommendations are based. Because 

of the large number of tables in this handbook, 

tables are presented at the end of each chapter, 

before the appendices, if any. 

1.12 REFERENCES FOR CHAPTER 1 

AAP (1997) Child Health Issues for the Second 

Session of the 106th Congress. 

Environmental Health. American Academy 

of Pediatrics Department of Federal Affairs 

601 13th Street, NW Suite 400 North 

Washington, DC 20005. AAP Washington 

Office Child Health Issues for the Second 

Session of the 106th Congress: 

Environmental Health. Available online at 

http://www.aap.org/advocacy/washing/chieh/ 

htm. 

Breysee, P.N.; Buckley, T.J.; Williams, D.; Beck, 

C.M.; Jo, S.; Merriman, B.; Kanchanaraksa, 

S.; Swartz, L.J.; Callahan, K.A.; Butz, A.M.; 

Rand, C.S.; Diette, G.B.; Krishman, J.A.; 

Moseley, A.M.; Curlin-Brosnan, J.; Durkin, 

N.B.; Eggleston, P.A. (2005) Indoor 

exposures to air pollutants and allergens in 

the homes of asthmatic children in inner-city 

Baltimore. Environ Res. 98:167-176. 

Clewell, H.J.; Gentry, P.R.; Covington, T.R.; 

Sarangapani, R.; Teeguarden, J.G. (2004) 

Evaluation of the potential impact of ageand gender-specific pharmacokinetic 

differences on tissue dosimetry. Toxicol Sci. 

79:381-393. 

Curwin, B.D.; Hein, M.J.; Sanderson, W.T.; Striley, 

C.; Heederik, D.; Kromhout, H.; Reynolds, 

J.j.; Alavanja, M.C. (2007) Pesticide dose 

estimates for children of Iowa farmers and 

non-farmers. Environ Res. 105: 307-315. 

EO (1997) Executive Order 13045. Protection of 

Children for Environmental Health Risks and 

Safety Risks. Available on line at 

http://yosemite.epa.gov/ochp/ochpweb.nsf/con 

tent/whatwe_executiv.htm. 

Eskenazi, B.; Bradman, A.; Castriona, R. (1999) 

Exposure of children to organophosphate 

pesticides and their potential adverse health 

effects. Environ Health Perspect. 107(3):409­

419. 

Foos, B.; Marty, M.; Schwartz, J.; Bennet, W.; 

Moya, J.; Jarabek, A.M.; Salmon, A.G. 

(2008) Focusing on children's inhalation 

dosimetry and health effects for risk 

assessment: an introduction. J Toxicol 

Environ Health, Part A, 71(3):149-165. 

Garry, V.F. (2004) Pesticides and children. 

Toxicol Appl Pharmaol. 198(2004):152-163. 

Gilbert, R.O. (1987) Statistical methods for 

environmental pollution monitoring. New 

York: Van Nostrand Reinhold. 

Ginsberg, G.; Hattis, D.; Sonawame, B.; Russ, A.; 

Banati, P.; Kozlak, M.; Smolenski, S.; Goble, 

R. (2002) Evaluation of child/adult 

pharmacokinetic differences from a database 

derived from the therapeutic drug literature. 

Toxicol Sci. 66:185-200. 

Gurunathan, S.; Robson, M.; Freeman N.; Buckley, 

B.; Roy, A.; Meyer, R.; Bukowski, J.; Lioy, 

P.J. (1998) Accumulation of chloropyrifos on 

residential surfaces and toys accessible to 

children. Environ Health Perspect. 106(1):9­

16. 

IPCS (2001) Glossary of exposure assessment-related 

terms: a compilation. IPCS Exposure 

Terminology Subcommittee, International 

Programme on Chemical Safety, World 

Health Organization. Available on line at 

http://www.who.int/ipcs/publications/methods 

/harmonization/en/compilation_nov2001.pdf 

Page Child-Specific Exposure Factors Handbook 

1-16 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH 

IPCS (2006) Principles for Evaluating Health 

Risks in Children Associated with Exposure 

to Chemicals. Environmental Health 

Criteria 237. International Programme on 

Chemical Safety, World Health 

Organization. 

Landrigan, P.J.; Sonawane, B.; Butler, R.N.; 

Transande, L.; Callan, R. (2005) Early 

environmental origins of neurodegenerative 

disease in later life. Environ Health 

Perspect. 113(9):1230-1233. 

Lewis, R. G.; Fortune C.; Willis, R. D.; Camann, 

D. E.; Antley, J. T. (1999) Distribution of 

pesticides and polycyclic aromatic 

hydrocarbons in house dust as a function of 

particle size. Environ Health Perspect. 

107(9):721-726. 

Myers, G.J.; Davidson, P.W. (2000) Does 

methylmercury have a role in causing 

developmental disabilities in children? 

Environ Health Perspect. 108(3):413-419. 

Nishioka, M.G.; Burkholder, H.M.; and Brinkman, 

M.C.; Lewis, R.G. (1999) Distribution of 

2,4-dihlorophenoxyacetic acid in floor dust 

throughout homes following homeowner and 

commercial lawn application: quantitative 

effects of children, pets, and shoes. Environ 

Sci Technol. 33:1359-1365. 

Selevan, S.G.; Kimmel, C.A.; Mendola, P. (2000) 

Identifying critical windows of exposure for 

children's health- monograph based on 

papers developed from the Workshop: 

Identifying Critical Windows of Exposure 

for Children's Health held September 14-15, 

1999 in Richmond, VA. Environ Health 

Perspect. 108(3):451-455. 

U.S. EPA. (1983-1989) Methods for assessing 

exposure to chemical substances. Volumes 1 

- 13. Office of Toxic Substances, Exposure 

Evaluation Division, Washington, DC. 

U.S. EPA. (1986a) Standard scenarios for 

estimating exposure to chemical substances 

during use of consumer products. Volumes I 

and II. Office of Toxic Substance, Exposure 

Evaluation Division, Washington, DC. 

U.S. EPA. (1986b) Guidance for the health risk 

assessment of chemical mixtures. Risk 

Assessment Forum, Washington, DC. 

EPA/630/R-98/002. Available on line at 

http://cfpub.epa.gov/si/si_public_record_Repo 

rt.cfm?dirEntryID=20533 

U.S. EPA. (1987) Selection criteria for 

mathematical models used in exposure 

assessments: surface water models. Exposure 

Assessment Group, Office of Health and 

Environmental Assessment, Washington, DC. 

WPA/600/8 87/042. Available from NTIS, 

Springfield, VA; PB-88-139928/AS. 

U.S. EPA. (1988) Selection criteria for 

mathematical models used in exposure 

assessments: groundwater models. Exposure 

Assessment Group, Office of Health and 

Environmental Assessment, Washington, DC. 

EPA/600/8 88/075. Available from NTIS, 

Springfield, VA; PB-88-248752/AS. 

U.S. EPA. (1989) Risk assessment guidance for 

Superfund. Volume I Human health 

evaluation manual: Part A. Interim Final. 

Office of Solid Waste and Emergency 

Response, Washington, DC. EPA/540-1­

89/002. Available online at 

http://www.epa.gov/oswer/riskassessment/rags 

a/index.htm. 

U.S. EPA. (1990) Methodology for assessing health 

risks associated with indirect exposure to 

combustor emissions. EPA 600/6-90/003. 

Available from NTIS, Springfield, VA; 

PB-90-187055/AS. 

U.S. EPA. (1991a) Risk assessment guidance for 

Superfund. Volume I Human health 

evaluation manual: Part B, Development of 

preliminary remediation goals. Office of 

Solid Waste and Emergency Response, 

Washington, DC. EPA/540/R-92-003. 

Available online at 

http://www.epa.gov/oswer/riskassessment/rags 

b/index.htm. 

U.S. EPA. (1991b) Risk assessment guidance for 

Superfund. Volume I Human health 

evaluation manual: Part C, Risk evaluation of 

remedial alternatives. Office of Solid Waste 

and Emergency Response, Washington, DC. 

Publication 9285.7-01C. Available online at 

http://www.epa.gov/oswer/riskassessment/rags 

c/index.htm. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 1-17
 
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Chapter 1 - Introduction 

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U.S. EPA. (1992a) Guidelines for exposure 

assessment. Washington, DC: Office of 

Research and Development, Office of Health 

and Environmental Assessment. 

EPA/600/Z-92/001. Available at 

http://www.epa.gov/NCEA/raf/pdfs/exposure 

.pdf. 

U.S. EPA. (1992b) Dermal exposure assessment: 

principles and applications. Washington, 

DC: Office of Health and Environmental 

Assessments. EPA/600/8-9/011F. Available 

online at 

http://www.epa.gov/ncea/pdfs/efh/references/ 

DEREXP.PDF. 

U.S. EPA. (1994a) Estimating exposures to 

dioxin-like compounds. Draft Report. 

Office of Research and Development, 

Washington, DC. EPA/600/6-88/005Cb. 

U.S. EPA. (1994b) Methods for derivation of 

inhalation reference concentrations and 

applications of inhalation dosimetry 

Washington, DC. EPA/600/8-90/066F. 

U.S.EPA (1996a) Soil screening guidance. Office 

of Solid Waste and Emergency Response, 

Washington, DC. EPA/540/F-95/041. 

Available online at 

http://www.epa.gov/superfund/health/conme 

dia/soil/index.htm 

U.S.EPA. (1996b) Series 875 Occupational and 

Residential Exposure Test Guidelines - Final 

Guidelines - Group A - Application 

Exposure Monitoring Test Guidelines. 

EPA712-C96-261. Available online at 

http://www.epa.gov/opptsfrs/publications/OP 

PTS_Harmonized/875_Occupational_and_R 

esidential_Exposure_Test_Guidelines/Series/ 

875_000.pdf 

U.S. EPA. (1996c) Series 875 Occupational and 

Residential Exposure Test Guidelines ­

Group 

B - Post Application Exposure Monitoring 

Test Guidelines. EPA712-C96-266. 

Available online at 

http://www.epa.gov/opptsfrs/publications/OP 

PTS_Harmonized/875_Occupational_and_R 

esidential_Exposure_Test_Guidelines/Series/ 

875-2000.pdf 

U.S. EPA. (1997a) Exposure factors handbook. 

National Center for Environmental 

Assessment, Office of Research and 

Development, Washington, DC. 

EPA/600/P-95/002Fa,b,c. Available online at 

http://www.epa.gov/ncea/efh/. 

U.S. EPA. (1997b) Policy for use of probabilistic 

analysis in risk assessment at the U.S. 

Environmental Protection Agency. Science 

Policy Council. Available online at 

http://www.epa.gov/OSA/spc/pdfs/probpol.pdf 

U.S. EPA. (1997c) Guiding principles for Monte 

Carlo analysis. Office of Research and 

Development, Risk Assessment Forum, 

Washington, DC. EPA/600/R-97/001. 

Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=29596. 

U.S. EPA. (1999) Sociodemographic data used for 

identifying potentially highly exposed 

populations. U.S. Environmental Protection 

Agency, Washington, DC. EPA/600/R99/060. Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=22562. 

U.S. EPA. (2000a) Strategy for research on risks to 

children. Office of Research and 

Development, Washington, DC. EPA/600/R00/068. 

U.S. EPA. (2000b) Options for developing 

parametric probability distributions for 

exposure factors. National Center for 

Environmental Assessment, Office of 

Research and Development, Washington, DC. 

EPA/600/R-00/058. Available on line at 

 http://www.epa.gov/ncea/paramprob4ef.htm. 

U.S. EPA. (2000c) Supplementary guidance for 

conducting health risk assessment of chemical 

mixutres. Risk Assessment Forum, 

Washington, DC. EPA/630/00/002F. 

Available on line at 

http://www.epa.gov/NCEA/raf/pdfs/chem_mi 

x/chem_mix_08_2001.pdf 

U.S. EPA. (2001a) Risk assessment guidance for 

Superfund. Volume I Human health 

evaluation manual: Part D, Standardized 

planning, reporting and review of Superfund 

risk assessments. Office of Solid Waste and 

Page Child-Specific Exposure Factors Handbook 

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Chapter 1 - Introduction 

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Emergency Response, Washington, DC. 

Publication 9285.7-47. Available online at 

 

http://www.epa.gov/oswer/riskassessment/ra 

gsd/tara.htm. 

U.S. EPA. (2001b) Risk assessment guidance for 

Superfund. Volume III, Part A, Process for 

conducting probabilistic risk assessment. 

Office of Solid Waste and Emergency 

Response, Washington, DC. EPA/540/R02/002. Available online at 

http://www.epa.gov/oswer/riskassessment/ra 

gs3adt/ 

U.S. EPA (2001c) Summary report of the technical 

workshop on issues associated with 

considering developmental changes in 

behavior and anatomy when assessing 

exposure to children. Office of Research and 

Development, Risk Assessment Forum, 

Washington, DC. EPA/630/R-00/005. 

Available online at 

http://cfpub.epa.gov/ncea/raf/recordisplay.cf 

m?deid=20680 

U.S. EPA. (2002a) Child-Specific exposure factors 

handbook. Interim Final. National Center 

for Environmental Assessment, Office of 

Research and Development, Washington, 

DC. EPA/600/P-00/002B. 

U.S. EPA (2002b). Overview of the EPA quality 

system for environmental data and 

technology. Office of Environmental 

Information, Washington DC. EPA/240­

R/02/003. Accessed online at 

http://www.epa.gov/quality/qs-docs/overview 

-final.pdf 

U.S. EPA (2003a). A summary of general 

assessment factors for evaluating the quality 

of scientific and technical information. 

Science Policy Council, Washington DC. 

EPA/100/B-03/001. Accessed online at 

 

http://www.epa.gov/osa/spc/pdfs/assess2.pdf 

U. S. EPA. (2003b) Framework for cumulative 

risk assessment. Risk Assessment Forum, 

Washington, DC. EPA/630/P-02/001F. 

Available online at 

http://cfpub.epa.gov/ncea/raf/recordisplay.cf 

m?deid=54944. 

U.S. EPA. (2003c) Example exposure scenarios. 

Office of Research and Development, 

Washington, DC; EPA/600/R03/036. 

Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=85843. 

U.S. EPA. (2003d) Human health research strategy. 

Office of Research and Development, 

Washington DC 20460. EPA/600/R-02/050. 

Available online at 

http://www.epa.gov/ORD/htm/researchstrategi 

es.htm#rs01 

U.S. EPA. (2004) Risk assessment guidance for 

Superfund. Volume I Human health 

evaluation manual: Part E, Supplemental 

guidance for dermal risk assessment. Interim. 

Office of Solid Waste and Emergency 

Response, Washington, DC. 

EPA/540/R/99/005. Available online at 

http://www.epa.gov/oswer/riskassessment/rags 

e/index.htm. 

U.S. EPA. (2005a) Guidance on selecting age 

groups for monitoring and assessing 

childhood exposures to environmental 

contaminants. Office of Research and 

Development, Washington, DC. EPA/630/P03/003F. Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=146583 

U.S. EPA. (2005b) Guidelines for carcinogen risk 

assessment. EPA/630/P-03/001F. Available 

online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=116283. 

U.S. EPA. (2005c) Supplemental Guidance for 

Assessing Susceptibility from Early-Life 

Exposure to Carcinogens. Risk Assessment 

Forum, Washington, DC. EPA/630/R03/003F. Available online at: 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=116283. 

U.S. EPA. (2005d) Protocol for human health risk 

assessment protocol for hazardous waste 

combustion facilities. EPA530-R-05-006. 

Available online at 

http://www.epa.gov/combustion/risk.htm 

U.S. EPA. (2006a) Approaches for the application 

of physiologically based pharmacokinetic 

Child-Specific Exposure Factors Handbook Page
 

September 2008 1-19
 
Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH 

(PBPK) models and supporting data in risk 

assessment. Office of Research and 

Development, Washington DC. EPA/600/R05/043F. Available online at 

http://cfpub.epa.gov/ncea/CFM/recordisplay. 

cfm?deid=157668 

U.S. EPA. (2006b) Use of physiologically based 

pharmacokinetic (PBPK) models to quantify 

the impact of human age and interindividual 

differences in physiology and biochemistry 

pertinent to risk (Final Report). Office of 

Research and Development, Washington, 

DC. EPA/600/R-06/014A. Available online 

at 

http://cfpub.epa.gov/ncea/CFM/recordisplay. 

cfm?deid=151384

 U.S. EPA (2006c) Guidance on systematic 

planning using the data quality objectives 

process. Office of Environmental 

Information, Washington DC. 

EPA/240B/06/001. Availabel online at 

http://www.epa.gov/QUALITY/qs-docs/g4-fi 

nal.pdf 

U.S. EPA. (2006d) A framework for assessing 

health risk of environmental exposures to 

children (Final). Office of Research and 

Development, Washington, DC. 

EPA/600/R-05/093F. Available online at 

 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=158363 

U.S. EPA (2006e) Harmonization in interspecies 3/4 

extrapolation: use of BW as default 

method in derivation of the oral RfD 

(External Review Draft). Risk Assessment 

Forum, Washington, DC. EPA/630/R06/001. Available online at 

http://cfpub.epa.gov/ncea/raf/recordisplay.cf 

m?deid=148525 

U.S. EPA (2008) Concepts, methods, and data 

sources for cumulative health risk 

assessment of multiple chemicals, exposures 

and effects: a resource document (final). 

Office of Research and Development, 

Washington, DC. EPA/600/R-06/013F. 

Available online at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cf 

m?deid=190187 

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Table 1-1. Characterization of Variability in Exposure Factors 

Exposure Factors

 Average Median Upper 

percentile

 Multiple 

Percentiles 

Ingestion of water and other 

select liquids 

T T T T

Non-dietary ingestion T T T

Soil and dust ingestion T T Ta 

Inhalation rate T T T T

Surface area 

Soil adherence 

T

T

T T

Body weight T T T T

Intake of fruits and vegetables T T T T

Intake of fish and shellfish T T T T

Intake of meats, dairy products, 

and fats 

T T T T

Intake of grain products T T T T

Intake of home produced foods T T T T

Total food intake T T T T

Human milk intake T T

Time indoors 

Time outdoors 

Time showering 

Time bathing 

Time swimming 

Time playing on sand/gravel 

Time playing on grass 

Time playing on dirt 

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

T

a Soil pica and geophagy. 

T = Data available 

Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH

Child-Specific Exposure Factors Handbook Page
 

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

General Assessment Factors Increasing Confidence 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 percent 

for in-person interviews and telephone 

surveys, or greater than 70 percent 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 percent. 

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 could be accessed. 

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. 

Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH 

Page Child-Specific Exposure Factors Handbook 

1-22 September 2008 
Table 1-2. Considerations 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 high level of peer review 

(e.g., they are published in peer review 

journals). 

The number of studies is greater than 3. The 

results of studies from different researchers are 

in agreement. 

The studies received limited peer review. 

The number of studies is 1. The results of studies 

from different researchers are in disagreement. 

Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH 

Child-Specific Exposure Factors Handbook Page
 

September 2008 1-23
 
Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH 

Table 1-3. Integrating U.S. EPA’s Guidance on Selecting Age Groups for Monitoring and Assessing 

Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005a) with U.S. EPA’s Supplemental 

Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens (U.S. EPA, 2005c) For Those 

Contaminants Which Act Via a Mutagenic Mode of Action 

Exposure Age Groupa Exposure Duration (yr) ADAF (Age-Dependent Potency 

Adjustment Factor) 

Birth to < 1 month 0.083 10x 

1 < 3 months 0.167 10x 

3 < 6 months 0.25 10x 

6 < 12 months 0.5 10x 

1 to < 2 years 1 10x 

2 to < 3 years 1 3x 

3 to < 6 years 3 3x 

6 to < 11 years 5 3x 

11 to < 16 years 5 3x 

16 to < 21 years 5 1x 

> 21 years (21 to < 70 yr) 49 1x 

a

 EPA’s recommended childhood age groups (excluding ages >21 years). 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 1 - Introduction 

CSEFH
 

Source: U.S. EPA, 2003d; IPCS, 2006. 

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2 

Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

VARIABILITY AND UNCERTAINTY 

Variability and uncertainty are inherent in the 

exposure assessment process. Addressing variability and 

uncertainty will increase the likelihood that results of an 

assessment or analysis will be used in an appropriate 

manner. Thus, careful consideration of the variabilities 

and uncertainties associated with the exposure factors 

information used in an exposure assessment is of utmost 

importance. The characterization of variability and 

uncertainty will also assist in communicating risks to the 

risk manager and the public. 

Exposure assessment can involve a broad array of 

information sources and analysis techniques (U.S. EPA, 

1992). Even in situations where actual exposure-related 

measurements exist, assumptions or inferences will still be 

required because data are not likely to be available for all 

aspects of the exposure assessment. Moreover, the data 

that are available may be of questionable or unknown 

quality. Thus, exposure assessors have a responsibility to 

present not just numbers, but also a clear and explicit 

explanation of the implications and limitations of their 

analyses. 

Morgan and Henrion (1990) provide an argument 

for the need for variability and uncertainty analysis in 

exposure assessment. They state that when scientists 

report quantities that they have measured, they are 

expected to routinely report an estimate of the probable 

error associated with such measurements. They conclude 

that because variabilities and uncertainties inherent in 

policy analysis (of which exposure assessment is a part) 

tend to be even greater than those in the natural sciences, 

exposure assessors also should be expected to report or 

comment on the variabilities and uncertainties associated 

with their estimates. 

Some additional reasons for addressing variability 

and uncertainty in exposure or risk assessments (U.S. 

EPA, 1992, Morgan and Henrion, 1990) include the 

following: 

•	 Decisions may need to be made about whether or 

how to expend resources to acquire additional 

information; 

•	 Biases may occur in providing a so-called "best 

estimate" that in actuality is not very accurate; and 

•	 Important factors and potential sources of 

disagreement in a problem may be able to be 

identified. 

This chapter is intended to acquaint the exposure 

assessor with some of the fundamental concepts and 

precepts of variability and uncertainty as they relate to 

exposure assessment and the exposure factors presented 

in this handbook. It also provides methods and 

considerations for evaluating and presenting the 

uncertainty associated with exposure estimates. 

Subsequent sections in this chapter are devoted to the 

following topics: 

•	 Variability versus uncertainty; 

• Types of variability; 

C Addressing variability; 

•	 Types of uncertainty; 

•	 Reducing uncertainty; 

•	 Analysis of variability and uncertainty; and 

•	 Presenting results of variability/uncertainty 

analysis. 

Fairly extensive treatises on the topic of uncertainty 

have been provided, for example, by Morgan and Henrion 

(1990), the National Research Council (NRC, 1994) and, 

to a lesser extent, the U.S. EPA (1992; 1995). The topic 

commonly has been treated as it relates to the overall 

process of conducting risk assessments; because exposure 

assessment is a component of risk-assessment process, the 

general concepts apply equally to the exposure-assessment 

component. Since the publication of the National 

Research Council’s report entitled Science and Judgement 

in Risk Assessment (NRC, 1994), the field of variability 

and uncertainty analysis has continued to evolve. The use 

of probabilistic techniques to address variability and 

uncertainty have continued to increase. There are 

numerous on going efforts in the Agency and elsewhere to 

further improve the characterization of variability and 

uncertainty. For example, an Agency task force is 

developing white papers on the use of expert elicitation 

for characterizing uncertainty in risk assessments. The 

U.S. EPA’s Risk Assessment Forum has established a 

workgroup to promote the use of probabilistic techniques 

to better assess and communicate risk. The International 

Programme on Chemical Safety (IPCS) is developing 

guidance on characterizing and communicating 

uncertainty in exposure assessment (WHO, 2006). 

2.1	 VARIABILITY VERSUS UNCERTAINTY 

While some authors have treated variability as a 

specific type or component of uncertainty, the U.S. EPA 

(1995) has advised the risk assessor (and, by analogy, the 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

exposure assessor) to distinguish between variability and 

uncertainty. Uncertainty represents a lack of knowledge 

about factors affecting exposure or risk, whereas 

variability arises from true heterogeneity across people, 

places or time. In other words, uncertainty can lead to 

inaccurate or biased estimates, whereas variability can 

affect the precision of the estimates and the degree to 

which they can be generalized. Most of the data presented 

in this handbook concerns variability. 

Variability and uncertainty can complement or 

confound one another, and it may not always be 

appropriate to 

give special 

Uncertainty - a lack of knowledge significance to 

about factors affecting exposure or distinguishing 

risk. between the 

Variability - arises from true two in every 

heterogeneity across people, places case.	 Consider 

or time. a situation that 

r e l a t e s t o 

exposure, such 

as estimating the average daily dose by one exposure 

route -- ingestion of contaminated drinking water. 

Suppose that it is possible to measure an individual's daily 

water consumption (and concentration of the contaminant) 

exactly, thereby eliminating uncertainty in the measured 

daily dose. The daily dose still has an inherent day-to-day 

variability, however, due to changes in the individual's 

daily water intake or the contaminant concentration in 

water. 

It is impractical to measure the individual's dose 

every day. For this reason, the exposure assessor may 

estimate the average daily dose (ADD) based on a finite 

number of measurements, in an attempt to "average out" 

the day-to-day variability. The individual has a true (but 

unknown) ADD, which has now been estimated based on 

a sample of measurements. Because the individual's true 

average is unknown, it is uncertain how close the estimate 

is to the true value. Thus, the variability across daily 

doses has been translated into uncertainty in the ADD. 

Although the individual's true ADD has no variability, the 

estimate of the ADD has some uncertainty. It should be 

noted, however, that a rigid delineation of variability and 

uncertainty may not be as useful as assessing the available 

information and attendant variation and properly 

accounting for it (e.g., sensitivity analysis). 

The above discussion pertains to the ADD for one 

person. Now consider a distribution of ADDs across 

individuals in a defined population (e.g., the general U.S. 

population). In this case, variability refers to the range 

and distribution of ADDs across individuals in the 

population. By comparison, uncertainty refers to the 

exposure assessor's state of knowledge about that 

distribution, or about parameters describing the 

distribution (e.g., mean, standard deviation, general shape, 

various percentiles). 

As noted by the National Research Council (NRC, 

1994), the realms of variability and uncertainty have 

fundamentally different ramifications for science and 

judgment. For example, uncertainty may force decisionmakers to judge how probable it is that exposures have 

been overestimated or underestimated for every member 

of the exposed population, whereas variability forces them 

to cope with the certainty that different individuals are 

subject to exposures both above and below any of the 

exposure levels chosen as a reference point. 

2.2	 TYPES OF VARIABILITY 

Variability in exposure is a function of the 

variability in human exposure factors (i.e., those related 

to an individual's location, activity, behavior or 

preferences at a particular point in time, or physiological 

characteristics such as body weight), as well as variations 

in contaminants concentrations (i.e., those related to 

pollutant emission rates and physical/chemical processes 

that affect concentrations in various media; e.g., air, soil, 

food and water). The variations in human exposure factors 

and chemical concentrations are not necessarily 

independent of one another. For example, both personal 

activities and pollutant concentrations at a specific 

location might vary in response to weather conditions, or 

between weekdays and weekends. 

At a more fundamental level, four types of 

variability can be distinguished: 

•	 Variability across locations (Spatial Variability); 

•	 Variability over time (Temporal Variability); 

•	 Variability within an individual (Intra-individual 

Variability; and 

•	 Variability among individuals (Inter-individual 

Variability). 

Spatial variability can occur both at regional 

(macroscale) and local (microscale) levels. For example, 

fish intake rates can vary depending on the region of the 

country. Higher consumption may occur among 

populations located near large bodies of water such as the 

Great Lakes or coastal areas. As another example, 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

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 the pollutant 

source, whether it be an industrial plant or related to a 

personal activity such as showering or gardening. In the 

context of exposure to airborne pollutants, the concept of 

a "microenvironment" has been introduced (Duan, 1982) 

to denote a specific locality (e.g., a residential lot or a 

room in a specific building) where the airborne 

concentration can be treated as homogeneous (i.e., 

invariant) at a particular point in time. 

Temporal variability refers to variations over 

time, whether long- or short-term. Seasonal fluctuations 

in weather, pesticide applications, use of woodburning 

appliances and fraction of time spent outdoors are 

examples of longer-term variability. Examples of shorterterm 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 change 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, lifestage, or other factors 

associated with temporal variability. 

Inter-individual variability can be either of two 

types: (1) human characteristics such as age or body 

weight, and (2) human behaviors such as location, activity 

patterns, and ingestion rates. Each of these variabilities, 

in turn, may be related to several underlying phenomena 

that vary. For example, the natural variability in human 

weight is due to a combination of genetic, nutritional, and 

other lifestyle or environmental factors. Variability arising 

from independent factors that combine multiplicatively 

generally will lead to an approximately lognormal 

distribution across the population, or across 

spatial/temporal dimensions. Inter-individual variability 

may also be related to spatial and temporal factors. 

2.3 ADDRESSING VARIABILITY 

As noted in Section 1.6 of this handbook, this 

document attempts to characterize variability of each of 

the exposure factors presented. 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, (2) as analytical distributions with 

specified parameters, or (3) as a qualitative discussion. 

According to the National Research Council (NRC 

1994), variability in exposure estimates can be addressed, 

especially with regard to point estimates such as central 

tendency (CT) or high end exposures (e.g., reasonable 

maximum exposure (RME) used in the Superfund 

program) in four basic ways (Table 2-1) when dealing 

with science-policy questions surrounding issues such as 

exposure or risk assessment. The first is to ignore the 

variability. This strategy is likely to be used in 

combination with one of the other strategies described 

below (e.g., use the average value), and tends to work best 

when the variability is relatively small, as in the case with 

adult body weights. For example, the U.S.EPA practice 

of assuming that all adults weigh 70 kg is likely to be 

correct within ±25% for most adults and within a factor of 

3 for virtually all adults (NRC,1994). However, it is 

cautioned that this approach may not be appropriate for 

children, where variability may be large. 

The second strategy involves disaggregating the 

variability in some explicit way, in order to better 

understand it or reduce it. Mathematical models are 

appropriate in some cases, as in fitting a sine wave to the 

annual outdoor concentration cycle for a particular 

pollutant and location. In other cases, particularly those 

involving human characteristics or behaviors, it is easier 

to disaggregate the data by considering all the relevant 

subgroups or subpopulations. For example, distributions 

of body weight could be developed separately for adults, 

adolescents and children, and even for males and females 

within each of these subgroups. Temporal and spatial 

analogies for this concept involve measurements on 

appropriate time scales and choosing appropriate 

subregions or microenvironments. 

The third strategy is to use the average value of a 

quantity that varies. Although this strategy might appear 

as tantamount to ignoring variability, it needs to be based 

on a decision that the average value can be estimated 

reliably in light of the variability (e.g., when the 

variability is known to be relatively small, as in the case 

of adult body weight). 

The fourth strategy involves using the maximum 

or minimum value for an exposure factor. In this case, 

the variability is characterized by the range between the 

extreme values and a measure of central tendency. This 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

is perhaps the most common method of dealing with 

variability in exposure or risk assessment -- to focus on 

one time period (e.g., the period of peak exposure), one 

spatial region (e.g., in close proximity to the pollutant 

source of concern), or one subpopulation (e.g., exercising 

asthmatics). As noted by the U.S. EPA (1992), when an 

exposure assessor develops estimates of high-end 

individual exposure and dose, care must be taken not to 

set all factors to values that maximize exposure or dose -­

such an approach will almost always lead to an 

overestimate. 

Probabilistic techniques (e.g., Monte Carlo or Latin 

Hypercube Simulation) are frequently used for 

characterizing the variability in risk estimates by 

repeatedly sampling the probability distributions of the 

risk equation inputs and using these inputs to calculate a 

distribution of risk. This approach is used less frequently 

in uncertainty analysis. Techniques for characterizing 

both uncertainty and variability are available, and 

generally require two-dimensional Monte Carlo analysis 

(U.S. EPA, 2001). In situations in which an analyst 

wishes to apply probabilistic techniques, and data lend 

themselves to such analysis, more robust techniques to 

describe data goodness-of-fit, identification and 

deposition of data outliers, and sensitivity analysis of the 

respective model should be used to address parameter 

variability. These techniques are described in Section 

1.9.2 of this document. 

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.	 Uncertainty regarding missing or incomplete 

information needed to fully define exposure and 

dose (Scenario Uncertainty). 

2.	 Uncertainty regarding some parameter (Parameter 

Uncertainty). 

3.	 Uncertainty regarding gaps in scientific theory 

required to make predictions on the basis of causal 

inferences (Model Uncertainty). 

Sources and examples for each type of uncertainty are 

summarized in Table 2-2. As described in Section 1.6 of 

this handbook, U.S. EPA has attempted to address the 

uncertainty associated with the various exposure factors 

presented in the handbook by applying confidence ratings 

to the recommended data. In general, these confidence 

rating are based on detailed discussions of any limitations 

of the data presented. This information may be useful in 

analyzing the uncertainty associated with an overall 

exposure/risk assessment. 

2.5	 REDUCING UNCERTAINTY 

Identification of the sources of uncertainty in an 

exposure assessment is the first step in determining how 

to reduce that uncertainty. The types of uncertainty listed 

in Table 2-2 can be further defined by examining their 

principal causes. 

Because uncertainty in exposure assessments is 

fundamentally tied to a lack of knowledge concerning 

important exposure factors, strategies for reducing 

uncertainty necessarily involve reduction or elimination of 

knowledge gaps. Example strategies to reduce uncertainty 

include (1) collection of new data using a larger sample 

size, an unbiased sample design, a more direct 

measurement method or a more appropriate target 

population, and (2) use of more sophisticated modeling 

and analysis tools if data quality allows. 

2.6	 ANALYZING VARIABILITY AND 

UNCERTAINTY 

Exposure assessments often are 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. Screening-level assessments 

typically examine exposures that would fall on or beyond 

the high end of the expected exposure distribution. 

Because screening-level analyses usually are included in 

the final exposure assessment, the final document may 

contain scenarios that differ quite markedly in 

sophistication, data quality, and amenability to 

quantitative expressions of variability or uncertainty. 

According to the U.S. EPA (1992), uncertainty 

characterization and uncertainty assessment are two ways 

of describing uncertainty at different degrees of 

sophistication. Uncertainty characterization usually 

involves a qualitative discussion of the thought processes 

used to select or reject specific data, estimates, scenarios, 

etc. Uncertainty assessment is a more quantitative process 

that may range from simpler measures (e.g., ranges) and 

simpler analytical techniques (e.g., sensitivity analysis) to 

more complex measures and techniques. Its goal is to 

provide decision makers with information concerning the 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

quality of an assessment, including the potential 

variability in the estimated exposures, major data gaps, 

and the effect that these data gaps have on the exposure 

estimates developed. 

A distinction between variability and uncertainty 

was made in Section 2.1. Although the quantitative 

process mentioned above applies more directly to 

variability and the qualitative approach more so to 

uncertainty, there is some degree of overlap. In general, 

either method provides the assessor or decision-maker 

with insights to better evaluate the assessment in the 

context of available data and assumptions. The following 

paragraphs describe some of the more common 

procedures for analyzing variability and uncertainty in 

exposure assessments. Principles that pertain to 

presenting the results of variability/uncertainty analysis 

are discussed in the next section. 

Several approaches can be used to characterize 

uncertainty in parameter values. When uncertainty is 

high, the assessor may use order-of-magnitude bounding 

estimates of parameter ranges (e.g., from 0.1 to 10 liters 

for daily water intake). Another method describes the 

range for each parameter including the lower and upper 

bounds as well as a "best estimate" (e.g., 1.4 liters per 

day) determined by available data or professional 

judgement. 

When sensitivity analysis indicates that a parameter 

profoundly influences exposure estimates, the assessor 

should develop a probabilistic description of its range. If 

there are enough data to support their use, standard 

statistical methods are preferred. If the data are 

inadequate, expert judgment can be used to generate a 

subjective probabilistic representation. Such judgments 

should be developed in a consistent, well-documented 

manner. Morgan and Henrion (1990) and Rish (1988) 

describe techniques to solicit expert judgment. 

Most approaches to quantitative analysis examine 

how variability and uncertainty in values of specific 

parameters translate into the overall uncertainty of the 

assessment. Details may be found in various papers and 

reviews such as Bogen and Spear (1987), Cox and 

Baybutt (1981), Whitmore (1985), Inman and Helton 

(1988), Seller (1987), and Rish and Marnicio (1988). 

These approaches can generally be described (in order of 

increasing complexity and data needs) as: (1) sensitivity 

analysis; (2) analytical uncertainty propagation; 

(3) probabilistic uncertainty analysis; or (4) classical 

statistical methods (U.S. EPA 1992). The four approaches 

are summarized in Table 2-3. 

Additional discussions describing approaches to 

address variability and uncertainty in human exposure 

assessments can be found in the following references: 

Burin and Saunders (1999), Burmaster (1998a, b, and c), 

Burmaster and Crouch (1997), Calaberse and Baldwin 

(1998), Cox (1999), Cullen and Frey (1999), 

Fayerweather et al. (1999), Finkel (1997), Frey (2002), 

Frey and Patil (2002), Greenland, (2001), Hattis (1997), 

Hattis and Anderson (1999), Hattis and Silver (1994), 

Illing (1999), Jayjock (1997), Kalberlah et al. (2003), 

Kelley and Campbell (2000), Meek (2001), Nayak and 

Kundu (2001), Nicas and Jayjock (2002), Peretz et al. 

(1997), Price et al. (1997, 1999), Rai and Krewski (1998), 

Renwick (1999), Renwick et al. (2001), Robinson and 

Hurst (1997), Saltelli (2002), Semple et al. (2003), Simon 

(1997), Shlyakhter (1994), Slob and Pieters (1998), 

Wallace et al. (1994), Wallace and Williams (2005), 

Weiss (2001), and Zheng and Frey (2005). 

2.7	 PRESENTING RESULTS OF VARIABILITY 

AND UNCERTAINTY ANALYSIS 

Comprehensive qualitative analysis and rigorous 

quantitative analysis are of little value for use in the 

decision-making process, if their results are not clearly 

presented. In this chapter, variability (the receipt of 

different levels of exposure by different individuals) has 

been distinguished from uncertainty (the lack of 

knowledge about the correct value for a specific exposure 

measure or estimate). Most of the data that are presented 

in this handbook deal with variability directly, through 

inclusion of statistics that pertain to the distributions for 

various exposure factors. 

Not all approaches historically used to construct 

measures or estimates of exposure have attempted to 

distinguish between variability and uncertainty. The 

assessor is advised to use a variety of exposure 

descriptors, and where possible, the full population 

distribution, when presenting the results. This 

information will provide risk managers with a better 

understanding of how exposures are distributed over the 

population and how variability in population activities 

influences this distribution. 

Although incomplete analysis is essentially 

unquantifiable as a source of uncertainty, it should not be 

ignored. At a minimum, the assessor should describe the 

rationale for excluding particular exposure scenarios; 

characterize the uncertainty in these decisions as high, 

medium, or low; and state whether they were based on 

data, analogy, or professional judgment. Where 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

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 always used descriptors to 

communicate the kind of scenario being addressed, the 

1992 Exposure Guidelines establish clear quantitative 

definitions for these risk descriptors. These definitions 

were established to ensure that consistent terminology is 

used throughout the Agency. The risk descriptors defined 

in the Guidelines include descriptors of individual risk 

and population risk. Individual risk descriptors are 

intended to address questions dealing with risks borne by 

individuals within a population, including not only 

measures of central tendency (e.g., average or median), 

but also those risks at the high end of the distribution. 

Population risk descriptors refer to 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. The data presented in this handbook is 

one of the tools available to exposure assessors to 

construct the various risk descriptors. 

However, it is not sufficient to merely present the 

results using different exposure descriptors. Risk 

managers should also be presented with an analysis of the 

uncertainties surrounding these descriptors. Uncertainty 

may be presented using simple or very sophisticated 

techniques, depending on the requirements of the 

assessment and the amount of data available. It is beyond 

the scope of this handbook to discuss the mechanics of 

uncertainty analysis in detail. The assessor can address 

uncertainty qualitatively by answering questions such as: 

•	 What is the basis or rationale for selecting these 

assumptions/parameters, such as data, modeling, 

scientific judgment, Agency policy, "what if" 

considerations, etc.? 

•	 What is the range or variability of the key 

parameters? How were the parameter values 

selected for use in the assessment? Were average, 

median, or upper-percentile values chosen? If 

other choices had been made, how would the 

results have differed? 

•	 What is the assessor's confidence (including 

qualitative confidence aspects) in the key 

parameters and the overall assessment? What are 

the quality and the extent of the data base(s) 

supporting the selection of the chosen values? 

Any exposure estimate developed by an assessor 

will have associated assumptions about the setting, 

chemical, population characteristics, and howcontact with 

the chemical occurs through various exposure routes and 

pathways. The exposure assessor will need to examine 

many sources of information that bear either directly or 

indirectly on these components of the exposure 

assessment. In addition, the 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 also should qualitatively 

describe the rationale for selection of any conceptual or 

mathematical models that may have been used. 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. 

Table 2-2 summarizes the three types of 

uncertainty, associated sources, and examples. Table 2-3 

summarizes four approaches to analyze uncertainty 

quantitatively. These are described further in the 1992 

Exposure Guidelines (U.S. EPA, 1992). 

To the extent possible, this handbook provides 

information that can be used to characterize the variability 

and uncertainty of data for the various exposure factors. 

In general, variability is addressed by providing 

distribution of data, where available, or qualitative 

discussions of the data sets used. Uncertainty is addressed 

by applying confidence rating to the recommendations 

provided for the various factors, along with detailed 

discussions of any limitations of the data presented. 

2.8	 REFERENCES FOR CHAPTER 2 

Bogen, K.T. (1990) Uncertainty in environmental health 

risk assessment. Garland Publishing, NewYork, NY. 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

Bogen, K.T.; Spear, R.C. (1987). Integrating uncertainty 

and interindividual variability in environmental risk 

assessment. Risk Analysis. 7(4):427-436. 

Burin, G.J.; Saunders, D.R. (1999). Addressing human 

variability in risk assessment–the robustness of the 

intraspecies uncertainty factor. Reg. Tox. Pharm. 

30: 209-216. 

Burmaster, D.E.; Crouch, E.A.C. (1997). Lognormal 

distributions for body weight as a function of age for 

males and females in the United States, 1976-1980. 

Risk Analysis. 17: 499-505. 

Burmaster, D.E. (1998a). A lognormal distribution for 

time spent showering. Risk Analysis. 18: 33-35. 

Burmaster, D.E. (1998b). Lognormal distributions for 

total water intake and tap water intake by pregnant 

and lactating women in the United States. Risk 

Analysis 18: 215-219. 

Burmaster, D.E. (1998c). Lognormal distributions for 

skin area as a function of body weight. Risk 

Analysis 18: 27-32. 

Calabrese, E.J.; Baldwin, L.A. (1998). Hormesis as a 

biological hypothesis. Environ. Health Persp. 

106(Supp. 1): 357-362. 

Cox, D.C.; Baybutt, P.C. (1981) Methods for uncertainty 

analysis. A comparative survey. Risk Analysis 

1(4):251-258. 

Cox Jr., L.A. (1999). Internal dose, uncertainty analysis, 

and complexity of risk models. Environ. Inter. 25: 

841-852. 

Cullen, A.C.; Frey, H.C. (1999). Probabilistic 

Techniques in Exposure Assessment. New York: 

Plenum Press. 

Duan, N. (1982) Microenvironment types: A model for 

human exposure to air pollution. Environ. Intl. 

8:305-309. 

Fayerweather, W.E.; Collins, J.J.; Schnatter, A.R.; 

Hearne, F.T.; Menning, R.A.; Reyner, D.P. (1999). 

Quantifying uncertainty in a risk assessment using 

human data. Risk Analysis 19: 1077-1090. 

Finkel, A.M. (1997). Not to decide is to decide: ignoring 

susceptibility in not 'good science'. Environ. Tox. 

Pharm. 4: 219-228. 

Frey, H.C. (2002). Guest Editorial: Introduction to special 

section on sensitivity analysis and summary of 

NCSU/USDA workshop on sensitivity analysis. Risk 

Analysis 22: 539-545. 

Frey, H.C.; Patil, S.R. (2002).	 Identification and review 

of sensitivity analysis methods. Risk Analysis 22: 

553-578. 

Greenland, S. (2001). Sensitivity analysis, Monte Carlo 

risk analysis, and Bayesian uncertainty assessment. 

Risk Analysis 21: 579-583. 

Hattis, D. (1997). Human variability in susceptibility: 

how big, how often, for what responses to what 

agents? Environ. Tox. Pharm. 4: 195-208. 

Hattis, D. and Anderson, E.L. (1999). What should be the 

implications of uncertainty, variability, and inherent 

‘biases’/’conservatism’ for risk management 

decision-making. Risk Analysis 19: 95-107. 

Hattis, D. and Silver, K. (1994). Human interindividual 

variability - A major source of uncertainty in 

assessing risks for noncancer health effects. Risk 

Analysis. 14(4):421-431. 

Illing, H.P.A. (1999). Are societal judgements being 

incorporated into the uncertainty factor used in 

toxicological risk assessment? Reg. Toxicol. Pharm. 

29: 300-308. 

Inman, R.L.; Helton, J.C. (1988) An investigation of 

uncertainty and sensitivity analysis techniques for 

computer models. Risk Analysis. 8(1):71-91. 

Jayjock,	 M.A. (1997). Uncertainty analysis in the 

estimation of exposure. Amer. Ind. Hyg. Assoc. J. 

58: 380-382. 

Kalberlah, F.; Schneider, K.; et al. (2003). Uncertainty 

in toxicological risk assessment for non-carcinogenic 

health effects. Reg. Tox. Pharm. 37: 92-104. 

Kelly, E.J.; Campbell, K. (2000). Separating variability 

and uncertainty in environmental risk 

assessment–making choices. Human Ecol. Risk 

Assess. 6: 1-13. 

Meek, M.E. (2001) Categorical default uncertainty 

factors–interspecies variation and adequacy of 

database. Human Ecol. Risk Assess. 7: 157-163. 

Morgan, M.G.; Henrion, M. (1990) Uncertainty: A Guide 

to Dealing with Uncertainty in Quantitative Risk and 

Policy Analysis. Cambridge University Press, New 

York, NY. 

National Research Council (NRC). (1994) Science and 

Judgment in Risk Assessment. National Academy 

Press, Washington, DC. 

Nayak, T.K.; Kundu, S. (2001). Calculating and 

describing uncertainty in risk assessment: The 

Bayesian approach. Human Ecol. Risk Assess. 7: 

307-328. 

Nicas, M.; Jayjock, M. (2002).	 Uncertainty in exposure 

estimates made by modeling versus monitoring. 

AIHA J. 63: 275-283. 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

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. 

Price, P.S.; Keenan, R.E.; Schwab, B. (1999). Defining 

the interindividual (intraspecies) uncertainty factor. 

Human Ecol. Risk Assess. 5: 1023-1033. 

Price, P.S.; Keenan, R.E.; Swartout, J.C., Gillis, C.A., 

Carlson-Lynch, H., and Dourson, M.L. (1997). An 

approach for modeling noncancer dose responses 

with an emphasis on uncertainty. Risk Analysis 17: 

427-437. 

Rai, S.N.; Krewski, D. (1998). Uncertainty and 

variability analysis in multiplicative risk models. 

Risk Analysis. 18: 37-45. 

Renwick, A.G. (1999). Subdivision of uncertainty factors 

to allow for toxicokinetics and toxicodynamics. 

Human Ecol. Risk Assess. 5: 1035-1050. 

Renwick, A.G.; Dorne, J.-L.C.M.; Walton, K. (2001). 

Pathway-related factors: The potential for human data 

to improve the scientific basis of risk assessment. 

Human Ecol. Risk Assess. 7: 165-180. 

Rish, W.R. (1988) Approach to uncertainty in risk 

analysis. Oak Ridge National Laboratory. 

ORNL/TM-10746. 

Rish, W.R.; Marnicio, R.J. (1988) Review of studies 

related to uncertainty in risk analysis. Oak Ridge 

National Laboratory. ORNL/TM-10776. 

Robinson, R.B.; Hurst, B.T. (1997). Statistical 

quantification of the sources of variance in 

uncertainty analyses. Risk Analysis. 17: 447-453. 

Saltelli, A. (2002). Sensitivity Analysis for Importance 

Assessment. Risk Analysis. 22: 579-590. 

Seller, F.A. (1987) Error propagation for large errors. 

Risk Analysis 7(4):509-518. 

Semple, S.E.; Proud, L.A.; Cherrie, J.W. (2003).	 Use of 

Monte Carlo simulation to investigate uncertainty in 

exposure modeling. Scand. J. Work Environ. Health. 

29: 347-353. 

Shlyakhter, A.I. (1994). An improved framework for 

uncertainty analysis: Accounting for unsupected 

errors. Risk Analysis. 14(4): 441-447. 

Simon, T.W. (1997). Combining physiologically based 

pharmacokinetic modeling with Monte Carlo 

simulation to derive an acute inhalation guidance 

value for trichlorethylene. Reg. Tox. Pharm. 26: 

257-270. 

Slob, W.; Pieters, M.N. (1998). A probabilistic approach 

for deriving acceptable human intake limits and 

human health risks from toxicological studies: 

General framework. Risk Analysis. 18: 787-798. 

U.S. EPA (1992)	 Guidelines for exposure assessment. 

Washington, DC: Office of Research and 

Development, Office of Health and Environmental 

Assessment. EPA/600/2-92/001. 

U.S.	 EPA (1995) Guidance for risk characterization. 

Science Policy Council, Washington, DC. 

U.S.	 EPA (2001) Risk Assessment Guidance for 

Superfund: Volume III - Part A, Process for 

Conducting Probabilistic Risk Assessment. 

Washington, DC: Office of Solid Waste and 

Emergency Response. EPA/540-R-02-002. 

Wallace, L.A. et al. (1994). Can long-term exposure 

distributions be predicted from short-term 

measurements? Risk Analysis . 14(1):75-85. 

Wallace, L;. Williams, R. (2005). Validation of a method 

for estimating long-term exposures based on shortterm measurements. Risk Analysis. 25(3): 687-694. 

Weiss, B. (2001). A Web-based survey method for 

evaluating different components of uncertainty in 

relative health risk judgments. Neurotoxicology 22: 

707-721. 

WHO (2006) Draft guidance on characterizing and 

communicating uncertainty in exposure assessment. 

Accessed on line at: 

http://www.who.int/ipcs/methods/harmonization/ar 

eas/exposure_assessment/en/index.html 

Whitmore, R.W. (1985) Methodology for 

characterization of uncertainty in exposure 

assessments. EPA/600/8-86/009. 

Zheng, J.; Frey, H.C. (2005).	 Quantitative analysis of 

variability and uncertainty with known measurement 

error: Methodology and case study. Risk Analysis. 

25: 663-675. 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

Table 2-1. Four Strategies for Confronting Variability 

Strategy Example Comment 

Ignore variability Assume that all adults weigh 70 

kg 

Works best when variability is small 

Disaggregate the 

variability 

Develop distributions of body 

weight for age/gender groups 

Variability will be smaller in each group; it depends on 

availability of data 

Use the average value Use average body weight for 

adults 

Can the average be estimated reliably given what is known 

about the variability of a specific population or group with 

potential exposures? 

Use a maximum or 

minimum value 

Use a lower-end value from the 

weight distribution 

Conservative approach -- can lead to unrealistically high 

exposure estimate if taken for all factors. It may be useful 

as a screening method for eliminating pathways of exposure 

that are not significant. 

Source: NRC, 1994. 

Table 2-2. Three Types of Uncertainty and Associated Sources and Examples 

Type of Uncertainty Sources Examples 

Scenario Uncertainty 

Parameter Uncertainty 

Model Uncertainty 

Descriptive errors Incorrect or insufficient information 

Aggregation errors Spatial or temporal approximations 

Judgment errors Selection of an incorrect model 

Incomplete analysis Overlooking an important pathway 

Measurement errors Imprecise or biased measurements 

Sampling errors Small or unrepresentative samples 

Variability In time, space or activities 

Surrogate data Structurally-related chemicals 

Relationship errors Incorrect inference on the basis for correlations 

Modeling errors Excluding relevant variables 

Source: U.S. EPA, 1992. 

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Child-Specific Exposure Factors Handbook 

Chapter 2 - Variability and Uncertainty 

Table 2-3. Approaches to Quantitative Analysis of Uncertainty 

Approach Description Example 

Sensitivity Analysis 

Analytical Uncertainty Propagation 

Probabilistic Uncertainty Analysis 

Classical Statistical Methods 

Changing one input variable at a time while 

leaving others constant, to examine effect on 

output 

Fix each input at lower (then upper) bound 

while holding others at nominal values (e.g., 

medians) 

Examining how uncertainty in individual 

parameters affects the overall uncertainty of the 

exposure assessment 

Analytically or numerically obtain a partial 

derivative of the exposure equation with 

respect to each input parameter 

Varying each of the input variables over various 

values of their respective probability 

distributions 

Assign probability density function to each 

parameter; randomly sample values from each 

distribution and insert them in the exposure 

equation (Monte Carlo) 

Estimating the population exposure distribution 

directly, based on measured values from a 

representative sample 

Compute confidence interval estimates for 

various percentiles of the exposure 

distribution 

Source: U.S. EPA, 1992. 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

3	 INGESTION OF WATER AND OTHER 

SELECT LIQUIDS 

3.1	 INTRODUCTION 

Water ingestion can be a pathway of 

exposure to environmental chemicals among children. 

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). Children 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 quantityof water 

consumed. The purpose of this section is to describe 

key and relevant published studies that provide 

information on water ingestion among children 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. 

Currently, the U.S. EPA uses the quantity 1 L 

per day for infants (individuals of 10 kg body mass or 

less) and children as a default drinking water ingestion 

rate (U.S. EPA, 2000). This rate includes water 

consumed in the form of juices and other beverages 

containing tapwater. The National Academy of 

Sciences (NAS, 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 children 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. 

Various studies cited in this section have 

generated data on water ingestion rates; in general, 

these sources support U.S. EPA's use of 1 L/day as an 

upper-percentile tapwater ingestion rate for children 

under 10 years of age. Based on the applicability of 

the survey design to exposure assessments of the entire 

US population, the study by Khan and Stralka (2008) 

was selected as a keystudyof drinking water ingestion. 

In this study, ingestion rates for direct and indirect 

ingestion of water are reported. 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, 2008). Data for consumption of 

water from various sources (i.e., the community water 

supply, bottled water, and other sources) are also 

presented. 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, tapwater ingestion of community water, 

rather than total water ingestion, is emphasized in this 

section. 

The studies on water ingestion that are 

currentlyavailable are based on short-term surveydata 

(two 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 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 handbook, where 

sufficient data are available. Data were not available to 

estimate drinking water ingestion rates for children 

during high activity levels or in extreme climates (i.e., 

hot weather). Also, data are not provided for the 

location of water consumption (i.e., home, school, day 

care center, etc.). 

Limited information was available regarding 

children’s incidental ingestion of water while 

swimming. This exposure pathway may be important 

since children are likely to ingest larger volumes of 

water while swimming compared to adults; and 

therefore, may have a greater exposure to pathogenic 

microorganisms and chemicals present in the water 

than adults. A recent pilot study (Dufour et al., 2006) 

has provided some quantitative experimental data on 

water ingestion for child and adult swimmers. These 

data are provided in this chapter. 

The recommendations for water 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. EPA for this factor. 

Following the recommendations, the key study on 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

water ingestion is summarized. Relevant data on 

ingestion of water and other select liquids are also 

provided. These studies are presented to provide the 

reader with added perspective on the current state-ofknowledge 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 rates for 

children are based on Kahn and Stralka (2008 and 

supplementary data). This study presents estimates of 

water ingestion by age range categories for the 

population of the United States using data collected in 

the U.S. Department of Agriculture’s (USDA’s) 1994­

96 and 1998 Continuing Survey of Food Intakes by 

Individuals (CSFII) (USDA, 1998). A summary of the 

recommended values for water ingestion rates is 

presented in Table 3-1. A characterization of the 

overall confidence in the accuracyand appropriateness 

of the recommendations for drinking water intake is 

presented in Table 3-2. 

3.2.2	 Water Ingestion while Swimming 

Based on the results of the Dufour et al. 

(2006) study, a mean water ingestion rate of 50 

mL/hour for children ages 6 to 15 years is 

recommended for exposure scenarios involving 

swimming activities. The recommended upper 

percentile value is 100 mL/hour. The recommended 

values for children between 18 and 21 years of age are 

based on the results for adults from Dufour et al. 

(2006). The mean value is 20 mL/hour and the upper 

percentile value is 70 mL/hour. Although this estimate 

was derived from swimming pool experiments, Dufour 

et al. (2006) noted that swimming behavior of pool 

swimmers may be similar to freshwater swimmers. 

Estimates may be different for salt water swimmers. 

The confidence ratings for these recommendations are 

presented in Table 3-3. Data on the amount of time 

spent swimming can be found in chapter 16, Table 16­

21. 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

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

Age Group Mean 95th Percentile Multiple 

Percentiles Source mL/day mL/kg-day mL/day mL/kg-day 

Per Capita 

Birth to <1 month 184 52 839b 232b 

See Tables 

3-4 and 3-9 Kahn and Stralka (2008) 

1 to <3 months 227 48 896b 205b 

3 to <6 months 362 52 1,056 159 

6 to <12 months 360 41 1,055 126 

1 to <2 years 271 23 837 71 

2 to <3 years 317 23 877 60 

3 to <6 years 380 22 1,078 61 

6 to <11 years 447 16 1,235 43 

11 to <16 years 606 12 1,727 34 

16 to <18 years 731 11 1,983b 31b 

18 to <21 years 826 12 2,540b 35b 

Consumers Only 

Birth to <1 month 470b 137b 858b 238b 

See Tables 

3-14 and 3­

19 

Kahn and Stralka (2008) 

1 to <3 months 552 119 1,053b 285b 

3 to <6 months 556 80 1,171b 173b 

6 to <12 months 467 53 1,147 129 

1 to <2 years 308 27 893 75 

2 to <3 years 356 26 912 62 

3 to <6 years 417 24 1,099 65 

6 to <11 years 480 17 1,251 45 

11 to <16 years 652 13 1,744 34 

16 to <18 years 792 12 2,002b 32b 

18 to <21 years 895 13 2,565b 35b 

a Ingestion rates for combined direct and indirect water from community water supply. b The sample size does not meet minimum requirements as described in the “Third Report on Nutrition Monitoring 

in the United States” (LSRO, 1995). 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

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 was 

adequate. The survey sampled approximately 10,000 

individuals under the age of 21 years; 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 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 two non-consecutive days. 

However, long term variability may be small. Use of a 

short-term average as a chronic ingestion measure can 

be assumed. 

Medium to High 

Clarity and Completeness 

Accessibility

 Reproducibility

 Quality Assurance 

The CSFII data are publicly available. The Kahn and 

Stralka (2008) analysis of the CSFII 1994-96, 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. 

High 

Variability and Uncertainty 

Variability in Population

 Uncertainty 

Full distributions were given in a separate document 

(Khan and Stralka, 2008b). 

Except for data collection based on recall, sources of 

uncertainty were minimal. 

High 

Evaluation and Review 

Peer Review

 Number and Agreement of Studies 

The USDA CSFII survey received high level of peer 

review. The Kahn and Stralka (2008) study was 

published in a peer-reviewed journal. 

There was 1 key study for drinking water ingestion. 

Medium 

Overall Rating Medium to High 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Table 3-3. 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). 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 broken out 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 

Only mean values for water ingestion were provided. 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 1 study for ingestion of water when swimming. 

Medium 

Overall Rating Low 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

3.3	 DRINKING WATER INGESTION 

STUDIES 

3.3.1	 Key Drinking Water Ingestion Study 

3.3.1.1	 Kahn and Stralka, 2008 - 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 

Kahn and Stralka (2008) analyzed the 

combined 1994-96 and 1998 Continuing Survey of 

Food Intakes by Individuals (CSFII) data sets to 

examine water ingestion rates of adults and children. 

USDA surveyed households in the United States and 

District of Columbia and collected food and beverage 

recall data as part of the CSFII (USDA,1998). In the 

initial 1994-96 survey, over 15,000 respondents 

provided data on what they ate and drank over two 

non-consecutive days. A 1998 supplement, using the 

same methodology, added responses for approximately 

5,000 children aged 9 years and younger to the 

database. Of the more than 20,000 individuals 

surveyed, approximately10,000 were under 21 years of 

age, and approximately 9,000 were under the age of 

11. For both survey days, data were collected by an inhome interviewer. The day two interview was 

conducted 3 to 10 days later and on a different day of 

the week. The 1994-96 survey and 1998 supplement 

are referred to collectively as CSFII 1994-96, 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 water ingestion rates from various 

sources. 

Khan and Stralka (2008) derived mean and 

percentile estimates of daily average water ingestion 

for children in eleven different 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, 

and 18 to <21 years of age. The increased sample size 

for children younger than 11 years of age (from 4,339 

in the initial 1994-96 survey to 9,643 children in the 

combined 1994-96, 1998 survey) enabled water 

ingestion estimates to be categorized into the finer age 

categories recommended by U.S. EPA (2005). Per 

capita and consumers only water ingestion estimates 

were reported in the Kahn and Stralka (2008) studyfor 

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 bya 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 

(2008) only reported the mean, 90th and 95th percentile 

estimates of per capita and consumers only ingestion. 

The full distribution of ingestion estimates for various 

water source categories (all sources, communitywater, 

bottled water, and other sources) were provided by the 

author. Tables 3-4 to 3-7 provide mean and percentile 

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). The 90 percent confidence 

intervals around the estimated means and the 90 

percent bootstrap intervals around the 90th and 95th 

percentiles of total water ingestion from all water 

sources are presented in Table 3-8. Tables 3-9 to 3-13 

present the same information as Tables 3-4 to 3-8 but 

in units of mL/kg-day. Consumers only combined 

direct and indirect water ingestion estimates in mL/day 

for the various source categories are provided in Tables 

3-14 to 3-17. Table 3-18 presents confidence and 

bootstrap intervals for total water ingestion estimates 

by consumers only from all sources. Tables 3-19 to 3­

23 present the same information as Tables 3-14 to 3-18 

but in units of mL/kg-day. 

The data show that the total quantity of water 

ingested per unit mass of body weight is at a maximum 

in the first month of life and decreases with increasing 

age. The per capita ingestion rate of water from all 

sources combined for children under 1 month of age is 

approximately four times higher than that adults, and 

consumers younger than 1 month of age ingest 

approximately 8 times the amount of water (all sources 

combined) as adults (Kahn and Stralka, 2008). The 

pattern of decreasing water ingestion per unit of body 

weight is also observed in per capita and consumers 

only estimates of community water (Tables 3-9 and 3­

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

19), bottled water (Table 3-10 and 3-20) and other 

sources (Tables 3-11 and 3-21). 

The CSFII 1994-96, 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 (2008). The 

principal advantages of this survey are (1) that the 

survey was designed to obtain a statistically valid 

sample of the entire United States population that 

included children and low income groups; (2) sample 

weights were provided that facilitated proper analysis 

of the data and accounted for non-response; and (3) 

that the sample size (approximately 10,000 children) 

is sufficient to allow categorization within narrowly 

defined age categories. Over sampling of children 

enhanced the precision and accuracy of the estimates 

for the child population subsets. One limitation of this 

survey is that data were collected for only 2 days and 

does not necessarily represent “usual intake.” “Usual 

dietary intake” refers to the long-term average of daily 

intakes by an individual. Thus, upper percentile water 

ingestion estimates based on short-term data maydiffer 

from long-term rates because short-term consumption 

data tend to be inherently more variable. However, 

Kahn and Stralka (2008) noted that variability due to 

short term duration of the survey does not result in bias 

of estimates of overall mean. In addition, the survey 

was conducted on non-consecutive days, which 

improves the variance over consecutive days of 

consumption. However, the two non-consecutive days 

of data collection, although an advantage over two 

consecutive days, provide limited information on 

individual respondents. The two-day mean for an 

individual can easily be skewed for numerous reasons. 

Estimation at the individual respondent level was not, 

however, an objective of the survey. The large sample 

provides useful information on the overall distribution 

of ingestion by the population, and should adequately 

reflect the range among respondent variability. 

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 subpopulations 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 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 three-day beverage and food diaries for their 

infants at ages 6 weeks, and 3, 6, and 9 months of age 

(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 cow’s milk, breast-milk, ready-tofeed 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 nosignificant differences in the reported number 

of adults or children in the family, water sources, or 

family income at 3, 6, or 9 months. Table 3-24 

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 percent at 6 weeks to 66 

percent 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 percent at 9 months to 48 percent at 

6 months) came from the addition of water to formula. 

Levy et al. (1995) noted that 32 percent of the infants 

at age 6 weeks and 23 percent 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, 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

that the three-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. 

3.3.2.2	 Heller et al., 2000 - Water Consumption and 

Nursing Characteristics of Infants by Race 

and Ethnicity 

Heller et al. (2000) analyzed data from the 

1994-96 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 nonHispanic, 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-tofeed and other infant formula, (5) baby food, (6) 

carbonated beverages, (7) fruit and vegetable juices 

and other noncarbonated 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. Region was categorized 

as Northeast, Midwest, South, and West. The states 

represented by each of these regions was 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 3.3.2.4 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 ofan 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 income by the federal poverty 

threshold for that size household. The poverty 

categories used were 0-1.30, 1.31-3.50, and greater 

than 3.50 times the federal poverty level (Heller et al., 

2000). 

Table 3-25 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 (21.3 mL/kg-day), and white 

non-Hispanic children had the lowest mean plain tap 

water intake (12.7 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 3-26 presents tap 

water and total water ingestion by age, sex, region, 

urbanicity, and povertycategory. On average, children 

younger than 12 months of age consumed less plain 

tap water (11.0 mL/kg-day) than children aged 12-24 

months (17.7 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 (2008) and U.S. EPA (2004) and include 

surveying participants for only two days. 

3.3.2.3	 Sichert-Hellert et al., 2001 - Fifteen Year 

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 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

recruited in hospital maternity wards. Older children 

and parents of younger children were asked to keep 

dietary records for three 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 

3-27 presents the mean water ingestion rates for these 

different sources, as well as mean total water ingestion 

rates for three age ranges of children (age 2 to 3 years, 

age 4 to 8 years, and age 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. 

3.3.2.4	 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 l to 10 years and local climate using data 

from the third National Health and Nutrition 

Examination Survey (NHANES III, 1988-94). 

Children aged 1 to 10 years who completed the 24­

hour dietary interview (or proxy interview for the 

younger children) during the NHANES III surveywere 

selected for the analysis. Breast-fed children were 

excluded from the analysis. Among 8,613 children 

who were surveyed, 688 (18 percent) 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 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 percent) 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 

noncarbonated drinks), carbonated drinks, and plain 

water. Fluid intake from sources other than these 

major sources were all 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. 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 

are presented in Table 3-28. 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 3-29 according to age 

(years), sex, race/ethnicity, poverty/income ratio, 

region, and urban or rural. 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) = 

0.000-1.300 times the poverty/income ratio; medium 

SES = 1.3.01-3.500 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 3-29). Sohn et al. (2001) did not 

find 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 over 

represented since temperature data was only available 

for counties with populations in excess of a half 

Child-Specific Exposure Factors Handbook Page 

September 2008 3-9 
Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

million. In addition, whites were under-represented 

compared to other racial or ethnic groups. Other 

limitations include lack of data for children from 

extremely cold or hot weather conditions. 

3.3.2.5	 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 

previouslyunder the Sichert-Hellert et al. (2001)study 

in Section 3.3.2.3 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) formulafed 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 3-30 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 breastfed, formula fed and mixedfed children. Mean total tap water intake was higher 

in formula-fed infants (53 mL/kg-day) than in breastfed infants (17 g/kg-day) and mixed-fed young 

children (19 g/kg-day). Tap water from household 

sources constituted 66 to 97 percent 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. 

3.3.2.6	 Marshall et al., 2003a - Patterns of 

Beverage Consumption During the 

Transition Stage of Infant Nutrition 

Marshall et al. (2003a) investigated beverage 

ingestion during the transition stage of infant 

nutrition. Mean ingestion of infant formula, cow’s 

milk, combined juice and juice drinks, water, and other 

beverages were estimated using a frequency 

questionnaire. A total of 701 children, ages six 

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., 2003a). 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 

three-day food diary for reference (Marshall et al., 

2003a). The percentage of subjects consuming 

beverages and mean daily beverage ingestion for 

children with returned questionnaires are presented in 

Table 3-31. Human milk ingestion was not quantified, 

but the percent of children consuming human milk was 

provided at each age category (Table 3-31). Juice (100 

percent) 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 3-31, 97 percent of the children consumed 

human milk, formula, or cow’s 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., 2003a). 

Marshall et al. (2003a) observed that in general, lower 

familyincomeswere associated with less breastfeeding 

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 the 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 

percent juice and juice drinks; the data are parentreported and could reflect perceptions of appropriate 

ingestion instead of actual ingestion, and a substantial 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

number of the infants from well educated, 

economically secure households dropped out during 

the initial phase. 

3.3.2.7	 Marshall et al., 2003b - Relative Validation 

of a Beverage Frequency Questionnaire in 

Children Ages 6 Months through 5 Years 

Using 3-day Food and Beverage Diaries 

This study was 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 dairies 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, ages 6 

and 12 months, and 2 and 5 years of age. Beverages 

were categorized as human milk, infant formula, cow’s 

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 week days and 

included detailed information about beverages 

consumed. Table 3-32 presents the mean ingestion 

rates of all beverages for children aged 6 and 12 

months and 3 and 5 years. Marshall et al. (2003b) 

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 three 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 U.S. since participants were 

primarily white, and from affluent and well-educated 

families in one geographic region of the country. 

3.3.2.8	 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 Infant 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., 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 

are 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, goat milk), 100 percent 

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 

categoryand the mean amounts consumed. Table 3-33 

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 at 19 to 24 months old. The percentages of 

children consuming water increased from 34 percent 

at 4 to 6 months of age to 77 percent 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 

one 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	 WATER INGESTION WHILE 

SWIMMING 

3.4.1	 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 

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Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

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 x 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) 

CApool = concentration of cyanuric acid 

in pool water (mg/L) 

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 studypopulation included 

12 adults (4 males and 8 females) and 41 children 

between 6 and 15 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. 

The results of this pilot study are presented in 

Table 3-34. The mean volume of water ingested by 

children over a 45-minute period was 37 mL. The 

maximum volume of water ingested by children was 

154 mL/45 minutes and the 97th percentile was 90 mL. 

Individuals older than 18 years of age ingested an 

average of 16 mL over a 45-minute period; the 

maximum amount ingested by these individuals was 

53mL over a 45-minute period. The mean ingestion 

rates for males tended to be higher than that of 

females, but these differences were not statistically 

significant. The advantages 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 the 

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 

rate for exposure scenarios involving swimming 

activities is 50 mL/hour for children under 16 years of 

age (37 mL/0.75 hour, rounded to one significant 

figure) and the upper percentile value is 100 mL/hour 

(90 mL/0.75 hour, rounded to one significant figure). 

For children, ages 18 to <21 years, the recommended 

mean water ingestion rate for scenarios involving 

swimming activities is 20 mL/hour (16 mL/0.75 hour, 

rounded to one significant figure). Because the data 

set is limited, the upper percentile water ingestion rate 

for 18 to <21 year olds is based on the maximum value 

observed in adults in the Dufour et al. (2006) study: 70 

mL/hour (53 mL/0.75 hour, rounded to one significant 

figure). 

3.5 REFERENCES FOR CHAPTER 3 

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 (supplement 

1): S8-S13. 

Dufour, A.P.; Evans, O.; Behymer, T.D., Cantu, R. 

(2006) Water ingestion during swimming 

activities in a pool: a pilot study. J Water 

Health 4(4):425-430. 

Heller, K.; Sohn, W.; Burt, B.; Feigal, R. (2000) 

Water consumption and nursing 

characteristics of infants by race and 

ethnicity. J Public Health Dent 60 (3) 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 

assessment: Data of the DONALD study. 

Food Addit Contam 19 (9): 829-836. 

Kahn, H.; Stralka, K. (2008) 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. J Expo Anal Environ Epidemiol 

(accepted for publication May 2008). 

Page Child-Specific Exposure Factors Handbook 

3-12 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Levy, S.; Kohout, F.; Guha-Chowdhury, N.; Kiristy, 

J., Heilman, et al. (1995) Infants’ fluoride 

intake from drinking water alone, and from 

water added to formula, beverages, and food. 

J Dent Res (74):1399-1407. 

LSRO	 (1995) Life Sciences Research Office, 

Federation of American Societies for 

Experimental Biology Prepared for the 

Interagency Board for Nutrition Monitoring 

and Related Research. Third Report on 

Nutrition Monitoring in the United States: 

Volume 1. U.S. Government Printing Office, 

Washington, D.C. 

Marshall, T.; Levy, S.; Broffitt, B.; EichenbergerGilmore, J.; Stumbo, P. (2003a) Patterns of 

beverage consumption during the transition 

stage of infant nutrition. J Amer Diet Assoc 

103 (10):1350-1353. 

Marshall, T.; Eichenberger Gilmore, J; Broffitt, B.; 

Levy, S.; Stumbo, P. (2003b) Relative 

Validation of a beverage frequency 

questionnaire in children Ages 6 months 

through 5 years using 3-day food and 

beverage diaries. J Amer Diet Assoc 103 

(6):714-720. 

National Academy of Sciences (NAS). (1977) 

Drinking water and health. Vol. 1. 

Washington, DC: National Academy of 

Sciences-National Research Council. 

Sichert-Hellert, W.; Kersting, M.; Manz, F. (2001) 

Fifteen year trends in water intake in German 

children and adolescents: results of the 

DONALD study. Acta Paediatr 90: 732-7. 

Skinner, J.; Ziegler, P.; Ponza, M. (2004) - Transition 

in Infants’ and Toddles’ Beverage Patterns. 

J Amer Diet Assoc Supplement 1 104 (1): 

S45-S50. 

Sohn, W.; Heller, K. E.; Burt, B. A. (2001) Fluid 

consumption related to climate among 

children in the United States. J Public Health 

Dent. 61(2): 99-106. 

USDA.	 (1998) Continuing survey of food intakes by 

individuals: 1994-96, 1998. U.S. Department 

ofAgriculture, Agricultural Research Service. 

U.S. EPA.	 (2000) Methodology for deriving ambient 

water quality criteria for the protection of 

human health (2000). U.S. Environmental 

Protection Agency, Office of Water, 

Washington, D.C., EPA-822-00-004. October 

2000. 

U.S.	 EPA. (2004) Estimated Per Capita Water 

Ingestion and Body Weight in the United 

States— an Update: Based on Data Collected 

by the United States Department of 

Agriculture’s 1994-96 and 1998 Continuing 

Survey of Food Intakes by Individuals. U.S. 

Environmental Protection Agency, Office of 

Water, Washington, D.C., EPA-822-R-00­

001. October 2004. 

U.S. EPA. (2005) Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants. 

U.S. Environmental Protection Agency, 

Washington, D.C., EPA/630/P-03/003F. 

November 2005. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-13
 
 

 

Table 3-4. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: Community Water (mL/day) 

Age	 Sample 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

91 

253 

428 

714 

1,040 

1,056 

4,391 

1,670 

1,005 

363 

389 

184 

227 

362 

360 

271 

317 

380 

447 

606 

731 

826 

-

-

-

-

-

-

4 

22 

30 

16 

24 

-

-

-

17 

60 

78 

98 

133 

182 

194 

236 

-

-

148 

218 

188 

246 

291 

350 

459 

490 

628 

322 

456 

695 

628 

402 

479 

547 

648 

831 

961 

1,119 

687* 

804 

928 

885 

624 

683 

834 

980 

1,387 

1,562 

1,770 

839* 

896* 

1,056 

1,055 

837 

877 

1,078 

1,235 

1,727 

1,983* 

2,540* 

860* 

1,165* 

1,424* 

1,511* 

1,215* 

1,364* 

1,654 

1,870* 

2,568* 

3,720* 

3,889* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Table 3-5. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: Bottled Water (mL/day) 

Age	 Sample 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

91 

253 

428 

714 

1,040 

1,056 

4,391 

1,670 

1,005 

363 

389 

104 - -

106 - -

120 - -

120 - -

59 - -

76 - -

84 - -

84 - -

111 - -

109 - -

185 - -

- 18 

- -

- -

- 53 

- -

- -

- -

- -

- -

- -

- -

437* 

541 

572 

506 

212 

280 

325 

330 

382 

426 

514 

556* 

771* 

774 

761 

350 

494 

531 

532 

709 

680* 

1,141* 

1,007* 

1,056* 

1,443* 

1,284* 

801* 

1,001* 

1,031* 

1,079* 

1,431* 

1,605* 

2,364* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-14 September 2008 
Table 3-6. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: Other Sources (mL/day) 

Age	 Sample 

size Mean 

Percentiles 

10 25 50 75 90 95 99 

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 

91 

253 

428 

714 

1,040 

1,056 

4,391 

1,670 

1,005 

363 

389 

13 - -

35 - -

45 - -

45 - -

22 - -

39 - -

43 - -

61 - -

102 - -

97 - -

47 - -

- - -

- - -

- - -

- - 31 

- - -

- - 52 

- - 58 

- - 181 

- - 344 

- - 295 

- - -

-

367* 

365 

406 

118 

344 

343 

468 

786 

740* 

246* 

393* 

687* 

938* 

963* 

482* 

718* 

830 

1,047* 

1,698* 

1,760* 

1,047* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Table 3-7. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: All Sources (mL/day) 

Age	 Sample 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

91 

253 

428 

714 

1,040 

1,056 

4,391 

1,670 

1,005 

363 

389 

301 

368 

528 

530 

358 

437 

514 

600 

834 

964 

1,075 

-

-

-

37 

68 

104 

126 

169 

224 

236 

189 

-

-

89 

181 

147 

211 

251 

304 

401 

387 

406 

135 

267 

549 

505 

287 

372 

438 

503 

663 

742 

803 

542 

694 

812 

771 

477 

588 

681 

803 

1,099 

1,273 

1,394 

846* 

889 

1,025 

1,029 

735 

825 

980 

1,130 

1,649 

1,842 

2,117 

877* 

1,020* 

1,303 

1,278 

961 

999 

1,200 

1,409 

1,960 

2,344* 

2,985* 

1,088* 

1,265* 

1,509* 

1,690* 

1,281* 

1,662* 

1,794 

2,167* 

3,179* 

3,854* 

4,955* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-15
 
Table 3-8. Per Capitaa Estimates of Combined Direct and Indirectb Water Ingestion: All Sources (mL/day)

Mean 90th percentile 95th percentile 

Sample 90% C.I. 90% B.I. 90% B.I. Age size Lower Upper Lower Upper Lower Upper Estimate Estimate Estimate Bound Bound Bound Bound Bound Bound 

Birth to <1 month 91 301 215 387 846* 638* 859* 877* 798* 993* 1 to <3 months 253 368 304 432 889 862 896 1,020* 918* 1,070* 3 to <6 months 428 528 485 571 1,025 955 1,083 1,303 1,170 1,351 6 to <12 months 714 530 495 564 1,029 973 1,100 1,278 1,142 1,385 1 to <2 years 1,040 358 338 377 735 686 778 961 879 1,001 2 to <3 years 1,056 437 418 455 825 784 857 999 952 1,051 3 to <6 years 4,391 514 494 533 980 953 1,004 1,200 1,167 1,240 6 to <11 years 1,670 600 571 629 1,130 1,065 1,162 1,409 1,314 1,468 11 to <16 years 1,005 834 770 898 1,649 1,567 1,775 1,960 1,873 2,218 16 to <18 years 363 964 870 1,057 1,842 1,743 1,988 2,344* 2,071* 2,599* 18 to <21 years 389 1,075 980 1,171 2,117 1,952 2,299 2,985* 2,504* 3,785* 

a Includes all participants whether or not they ingested any water from the source during survey period.b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the preparation of food or

beverages. 

* The sample size does not meet minimum requirements as described in the “Third Report on Nutrition Monitoring in the United

States” (LSRO, 1995).

CI = Confidence Interval.BI = Bootstrap Interval. Source: Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-16 September 2008 
Table 3-9. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: Community Water (mL/kg-day) 

Age	 Sample 

size Mean 

Percentiles 

10 25 50 75 90 95 99 

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 

88 

245 

411 

678 

1,002 

994 

4,112 

1,553 

975 

360 

383 

52 

48 

52 

41 

23 

23 

22 

16 

12 

11 

12 

-

-

-

-

-

-

-

1 

1 

-

1 

-

-

-

2 

5 

6 

6 

5 

4 

3 

4 

-

-

20 

24 

17 

17 

17 

12 

9 

8 

10 

101 

91 

98 

71 

34 

33 

31 

22 

16 

15 

16 

196* 

151 

135 

102 

53 

50 

48 

34 

25 

23 

17 

232* 

205* 

159 

126 

71 

60 

61 

43 

34 

31* 

35* 

253* 

310* 

216* 

185* 

106* 

113* 

93 

71* 

54* 

55* 

63* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Table 3-10. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: Bottled Water (mL/kg-day) 

Age	 Sample 

size Mean 

Percentiles 

10 25 50 75 90 95 99 

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 

88 

245 

411 

678 

1,002 

994 

4,112 

1,553 

975 

360 

383 

33 - -

22 - -

16 - -

13 - -

5 - -

5 - -

5 - -

3 - -

2 - -

2 - -

3 - -

- 6 

- -

- -

- 4 

- -

- -

- -

- -

- -

- -

- -

131* 

97 

74 

52 

18 

19 

18 

10 

8 

6 

8 

243* 

161* 

117 

87 

28 

35 

30 

18 

14 

10* 

19* 

324* 

242* 

193* 

139* 

67* 

84* 

59 

41* 

26* 

27* 

34* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-17
 
 

 

Table 3-11. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: Other Sources (mL/kg-day) 

Age	 Sample 

size Mean 

Percentiles 

10 25 50 75 90 95 99 

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 

88 

245 

411 

678 

1,002 

994

4,112 

1,553 

975 

360 

383 

4 - -

7 - -

7 - -

5 - -

2 - -

3 - -

2 - -

2 - -

2 - -

2 - -

1 - -

- - -

- - -

- - -

- - 3 

- - -

- - 4 

- - 3 

- - 7 

- - 7 

- - 5 

- - -

-

52* 

55 

35 

11 

23

19 

16 

14 

11* 

4* 

122* 

148* 

155* 

95* 

45* 

61* 

48 

36* 

34* 

27* 

14* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Table 3-12. Per Capita a Estimates of Combined Direct and Indirectb Water Ingestion: All Sources (mL/kg-day) 

Age	 Sample 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

88 

245 

411 

678 

1,002 

994 

4,112 

1,553 

975 

360 

383 

89 

77 

75 

59 

31 

31 

29 

21 

16 

15 

16 

-

-

-

4 

6 

7 

7 

6 

4 

4 

3 

-

-

9 

20 

13 

15 

14 

10 

8 

6 

6 

21 

46 

73 

53 

24 

26 

25 

18 

13 

12 

12 

168 

134 

118 

86 

39 

41 

38 

27 

20 

18 

21 

235* 

173 

156 

118 

63 

59 

56 

39 

31 

28 

32 

269* 

246* 

186 

148 

85 

73 

69 

50 

39 

37* 

41* 

338* 

336* 

225* 

194* 

122* 

130* 

102 

76* 

60* 

59* 

73* 

a 

b 

-

* 	

Source:	 

Includes all participants whether or not they ingested any water from the source during survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

= Zero. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-18 September 2008 
Table 3-13. Per Capitaa Estimates of Total Direct and Indirectb Water Ingestion: All Sources (mL/kg-day)

Mean 90th percentile 95th percentile 

Sample 90% C.I. 90% B.I. 90% B.I. Age size Lower Upper Lower Upper Lower Upper Estimate Estimate Estimate Bound Bound Bound Bound Bound Bound 

Birth to <1 month 88 89 64 114 235* 198* 269* 269* 236* 332* 1 to <3 months 245 77 62 91 173 164 217 246* 187* 295* 3 to <6 months 411 75 68 82 156 145 162 186 176 199 6 to <12 months 678 59 54 63 118 112 128 148 134 166 1 to <2 years 1,002 31 29 32 63 59 68 85 73 95 2 to <3 years 994 31 30 33 59 57 62 73 69 81 

3 to <6 years 4,112 29 28 30 56 54 56 69 66 72 6 to <11 years 1,553 21 20 22 39 36 41 50 47 52 11 to <16 years 975 16 15 17 31 29 34 39 36 41 16 to <18 years 360 15 13 16 28 27 32 37* 33* 44* 18 to <21 years 383 16 14 17 32 29 35 41* 36* 44* 

a Includes all participants whether or not they ingested any water from the source during survey period.b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the preparation of food or

beverages. 

* The sample size does not meet minimum requirements as described in the “Third Report on Nutrition Monitoring in the United

States” (LSRO, 1995).

CI = Confidence Interval.BI = Bootstrap Interval. Source: Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-19
 
 

 

Table 3-14. Co 

Age	 

Birth to <1 month 

nsumers Onlya 

Sample	 

size 

40 

Estimates 

Mean 

470* 

 ofCombi

10

32* 

ned Direct 

(mL/day) 

25

215* 

and Indire

50

482* 

ct 

b Water Ing

Percentiles 

75

692* 

estion: C 

90

849* 

ommunity 

95

858* 

Water 

99 

919* 

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 

a Excludes i b Direct wat

preparatio

* 	 The sampl

Monitorin

114 

281 

562 

916 

934 

3,960 

1,555 

937 

341 

364 

ndividuals wh

er defined as 

n of food or beverages. 

e size does no 

g in the Unite 

552 

556 

467 

308 

356 

417 

480 

652 

792 

895 

o did not i 

water inges

t meet min 

d States” (

67* 

44 

44 

43 

49 

57 

74 

106 

106 

114 

ngest wate

ted direct

imum req

339 

180 

105 

107 

126 

146 

177 

236 

266 

295 

r from the 

ly as a beve 

uirements a

LSRO, 1995). 

533 

561 

426 

229 

281 

336 

373 

487 

591 

674 

source dur

rage; indi

s describe

801 

837 

710 

428 

510 

581 

682 

873 

987 

1,174 

ing the surve 

rect water de 

d in the “Thi

943* 

1,021 

971 

674 

700 

867 

994 

1,432 

1,647 

1,860 

y period.
 

fined as w

rd Report 

1,053* 

1,171* 

1,147 

893 

912 

1,099 

1,251 

1,744 

2,002* 

2,565* 

ater added 

1,264* 

1,440* 

1,586* 

1,248* 

1,388* 

1,684 

2,024* 

2,589* 

3,804* 

3,917* 

in the
 

on Nutrition 

Source:	 Kahn and Stralka, 2008 and supplementary data. 

Table 3-15. Consumers Only a Estimates of Combined Direct and Indirectb Water Ingestion: Bottled Water (mL/day) 

Age	 Sample 

size Mean 

Percentiles 

10 25 50 75 90 95 99 

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 

25

64 

103 

200 

229 

232 

1,021 

332 

192 

63 

97 

-

450* 

507 

425 

262 

352 

380 

430 

570 

615* 

769 

-

31* 

48* 

47 

45 

57 

72 

88 

116* 

85* 

118* 

-

62* 

88 

114 

88 

116 

149 

168 

229 

198* 

236 

-

329* 

493 

353 

188 

241 

291 

350 

414 

446* 

439 

-

743* 

747 

630 

324 

471 

502 

557 

719 

779* 

943 

-

886* 

1,041* 

945* 

600 

736 

796 

850 

1,162* 

1,365* 

1,788* 

-

1,045* 

1,436* 

1,103* 

709* 

977* 

958 

1,081* 

1,447* 

1,613* 

2,343* 

­

1,562* 

1,506* 

1,413* 

1,083* 

1,665* 

1,635* 

1,823* 

2,705* 

2,639* 

3,957* 

a Excludes individuals who did not ingest water from the source during the survey period.
 b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the
 

preparation of food or beverages. 

- 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” (LSRO, 1995). 

 

Source: Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-20 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Table 3-16. Consumers Only a Estimates of Combined Direct and Indirectb Water Ingestion: Other Sources (mL/day) 

Age	 Sample 

size Mean 

Percentiles 

10 25 50 75 90 95 99 

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 

3

19

38 

73 

98 

129 

533 

219 

151 

53 

33 

-

-

562* 

407* 

262 

354 

396 

448 

687 

657* 

569* 

-

-

59* 

31* 

18* 

56* 

59 

89 

171* 

152* 

103* 

-

-

179* 

121* 

65 

134 

148 

177 

296 

231* 

142* 

-

-

412* 

300* 

143 

318 

314 

347 

482 

398* 

371* 

-

-

739* 

563* 

371 

472 

546 

682 

947 

823* 

806* 

-

-

983* 

961* 

602* 

704* 

796 

931 

1,356* 

1,628* 

1,160* 

-

-

1,205* 

1,032* 

899* 

851* 

1,019 

1,090* 

1,839* 

1,887* 

1,959* 

­

­

2,264* 

1,144* 

1,204* 

1,334* 

1,543* 

1,596* 

2,891* 

2,635* 

1,962* 

a Excludes individuals who did not ingest water from the source during the survey period. b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

- 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” (LSRO, 1995). 

Source: Kahn and Stralka, 2008 and supplementary data. 

Table 3-17. Consumers Only a Estimates of Combined Direct and Indirectb Water Ingestion: All Sources (mL/day) 

Age	 Sample 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

58 

178 

363 

667 

1,017 

1,051 

4,350 

1,659 

1,000 

357 

383 

511* 

555 

629 

567 

366 

439 

518 

603 

837 

983 

1,094 

51* 

68* 

69 

90 

84 

105 

134 

177 

229 

252 

219 

266* 

275 

384 

250 

159 

213 

255 

310 

404 

395 

424 

520* 

545 

612 

551 

294 

375 

442 

506 

665 

754 

823 

713* 

801 

851 

784 

481 

589 

682 

805 

1,105 

1,276 

1,397 

858* 

946* 

1,064 

1,050 

735 

825 

980 

1,131 

1,649 

1,865 

2,144 

986* 

1,072* 

1,330* 

1,303 

978 

1,001 

1,206 

1,409 

1,961 

2,346* 

3,002* 

1,274* 

1,470* 

1,522* 

1,692* 

1,281* 

1,663* 

1,796 

2,168* 

3,184* 

3,866* 

4,967* 

a Excludes individuals who did not ingest water from the source during the survey period.
 b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the
 

preparation of food or beverages. 

* 	 The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Source: Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-21
 
 

 

Table 3-18. Consumers Onlya Estimates of Combined Direct and Indirectb Water Ingestion: All Sources (mL/day)

Mean 90th percentile 95th percentile 

Sample 90% C.I. 90% B.I. 90% B.I. Age size Estimate Lower Upper Estimate Lower Upper Estimate Lower Upper 

Birth to <1 month 58 511* 417* 606* 858* 856* 993* 986* 974* 1,076* 1 to <3 months 178 555 487 622 946* 891* 1,042* 1,072* 1,022* 1,183* 3 to <6 months 363 629 587 672 1,064 1,011 1,177 1,330* 1,183* 1,431* 6 to <12 months 667 567 534 600 1,050 1,001 1,141 1,303 1,181 1,372 1 to <2 years 1,017 366 346 385 735 715 765 978 915 1,001 2 to <3 years 1,051 439 420 457 825 784 857 1,001 944 1,075 3 to <6 years 4,350 518 499 537 980 961 1,000 1,206 1,171 1,253 6 to <11 years 1,659 603 574 632 1,131 1,075 1,162 1,409 1,336 1,468 11 to <16 years 1,000 837 773 901 1,649 1,568 1,749 1,961 1,873 2,104 16 to <18 years 357 983 896 1,071 1,865 1,774 1,982 2,346* 2,129* 2,599* 18 to <21 years 383 1,094 999 1,189 2,144 1,951 2,299 3,002* 2,576* 3,785* 

a Excludes individuals who did not ingest water from the source during the survey period.b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the preparation of food or

beverages. 

* The sample size does not meet minimum requirements as described in the “Third Report on Nutrition Monitoring in the United

States” (LSRO, 1995).

CI = Confidence Interval.BI = Bootstrap Interval. Source: Kahn and Stralka, 2008 . 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-22 September 2008 
Table 3-19. Consumers Only a Estimates of Direct and Indirectb Water Ingestion: Community Water (mL/kg-day) 

Age	 Sample 

size Mean 

Percentiles 

10 25 50 75 90 95 99 

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 

37 

108 

269 

534 

880 

879 

3,703 

1,439 

911 

339 

361 

137* 

119 

80 

53 

27 

26 

24 

17 

13 

12 

13 

11* 

12* 

7 

5 

4 

4 

3 

3 

2 

1 

2 

65* 

71 

27 

12 

9 

9 

8 

6 

5 

4 

5 

138* 

107 

77 

47 

20 

21 

19 

13 

10 

9 

10 

197* 

151 

118 

81 

36 

36 

33 

23 

17 

16 

17 

235* 

228* 

148 

112 

56 

52 

49 

35 

26 

24 

29 

238* 

285* 

173* 

129 

75 

62 

65 

45 

34 

32* 

35* 

263* 

345* 

222* 

186* 

109* 

121* 

97 

72* 

54* 

58* 

63* 

a 

b 

* 	

Source	 

Excludes individuals who did not ingest water from the source during the survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Table 3-20. Consumers Only a Estimates of Direct and Indirectb Water Ingestion: Bottled Water (mL/kg-day) 

Age	 Sample	 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

25

64 

95 

185 

216 

211 

946 

295 

180 

63 

93 

-

92* 

72 

47 

22 

25 

21 

15 

11 

10* 

11 

-

7* 

6* 

5* 

5 

4 

4 

3 

2* 

1* 

2* 

-

12* 

15 

11 

8 

8 

8 

5 

4 

3* 

3 

-

76* 

69 

34 

16 

17 

16 

11 

8 

7* 

6 

-

151* 

100 

73 

27 

35 

29 

19 

14 

11* 

14 

-

164* 

149* 

104* 

49 

54 

45 

30 

24* 

23* 

27* 

-

220* 

184* 

120* 

66* 

81* 

57 

42* 

27* 

27* 

30* 

­

411* 

213* 

166* 

103* 

91* 

90* 

69* 

44* 

37* 

54* 

a 

b 

-

* 	

Source:	 

Excludes individuals who did not ingest water from the source during the survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

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” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-23
 
 

 

Table 3-21. Consumers Only a Estimates of Direct and Indirectb Water Ingestion: Other Sources (mL/kg-day) 

Age	 Sample 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

3

19

38 

68 

95 

124 

505 

208 

148 

52 

33 

-

-

80* 

44* 

23 

26 

22 

16 

13 

10* 

8* 

-

-

10* 

4* 

1* 

4* 

3 

3 

3* 

2* 

1* 

-

-

23* 

10* 

5 

10 

8 

6 

6 

4* 

2* 

-

-

59* 

33* 

13 

21 

17 

12 

9 

7* 

6* 

-

-

106* 

65* 

28 

34 

30 

23 

18 

12* 

10* 

-

-

170* 

95* 

46* 

55* 

46 

32 

27* 

24* 

16* 

-

-

200* 

106* 

84* 

66* 

56 

39* 

36* 

29* 

27* 

­

­

246* 

147* 

125* 

114* 

79* 

62* 

56* 

43* 

31* 

a 

b 

-

* 	

Source	 

Excludes individuals who did not ingest water from the source during the survey period. 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the 

preparation of food or beverages. 

Means 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” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Table 3-22. Consumers Only a Estimates of Direct and Indirectb Water Ingestion: All Sources (mL/kg-day) 

Age	 Sample	 

size Mean Percentiles 

10 25 50 75 90 95 99 

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 

55 

172 

346 

631 

980 

989 

4,072 

1,542 

970 

354 

378 

153* 

116 

90 

63 

31 

31 

29 

21 

16 

15 

16 

13* 

12* 

9 

10 

7 

7 

7 

6 

4 

4 

3 

83* 

50 

52 

27 

14 

15 

15 

10 

8 

7 

6 

142* 

107 

86 

58 

25 

27 

25 

18 

13 

12 

12 

208* 

161 

125 

88 

40 

41 

38 

27 

20 

18 

21 

269* 

216* 

161 

120 

64 

59 

56 

39 

31 

29 

32 

273* 

291* 

195* 

152 

86 

73 

70 

50 

39 

37* 

41* 

400* 

361* 

233* 

198* 

122* 

130* 

102* 

76* 

60* 

60* 

73* 

a 

b 

* 	

Source	 

Excludes individuals who did not ingest water from the source during the survey period.
 

Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the
 

preparation of food or beverages. 

The sample size does not meet minimum requirements as described in the “Third Report on Nutrition 

Monitoring in the United States” (LSRO, 1995). 

Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-24 September 2008 
Table 3-23. Consumer Onlya Estimates of Total Direct and Indirectb Water Ingestion (mL/kg-day) 

Mean 90th percentile 95th percentile 

Sample 90% C.I. 90% B.I. 90% B.I. Age size Lower Upper Lower Upper Lower Upper Estimate Estimate Estimate Bound Bound Bound Bound Bound Bound 

Birth to <1 month 55 153* 125* 181* 269* 234* 273* 273* 263* 332* 1 to <3 months 172 116 100 132 216* 176* 259* 291* 214* 316* 3 to <6 months 346 90 83 97 161 145 178 195* 174* 212* 6 to <12 months 631 63 59 67 120 117 127 152 137 166 1 to <2 years 980 31 30 33 64 57 67 86 70 89 

2 to <3 years 989 31 30 33 59 56 61 73 67 81 3 to <6 years 4,072 29 28 30 56 54 57 70 67 73 6 to <11 years 1,542 21 20 22 39 37 41 50 46 52 11 to <16 years 970 16 15 17 31 29 33 39 38 42 16 to <18 years 354 15 14 16 29 27 32 37* 33v 44* 18 to <21 years 378 16 15 18 32 29 35 41* 36* 56* 

a Excludes individuals who did not ingest water from the source during the survey period.b Direct water defined as water ingested directly as a beverage; indirect water defined as water added in the preparation of food or

beverages. 

* The sample size does not meet minimum requirements as described in the “Third Report on Nutrition Monitoring in the United

States” (LSRO, 1995). 

CI = Confidence Interval.BI = Bootstrap Interval. Source: Kahn and Stralka, 2008 and supplementary data. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-25
 
 

 

 

 

Table 3-24. Water Ingested (mL/day)a from Water By Itself and Water Added to Other Beverages and Foods

Category 6 Weeks 3 Months 6 Months 9 Months

(N = 124) (N = 120) (N = 99) (N = 77) 

Water by Itself Range 0-355 0-355 0-266 0-473

Per capita meanb ± SD 30 ± 89 30 ± 59 30 ± 59 89 ± 89

c Consumer only mean 89 89 118 118 d Percent consuming 28 24 42 66 

Water Added to Formula Range 0-1,242 0-1,242 0-1,124 0-1,064

Powdered Concentrate Per capita mean ± SD 177 ± 296 266 ± 384 266 ± 355 207 ± 325

Consumer only mean 473 621 562 562

Percent consuming 39 42 48 36 

Liquid Concentrate Range 0-621 0-680 0-710 0-532

Per capita mean ± SD 89 ±148 237 ± 207 148 ± 207 59 ± 148

Consumer only mean 355 384 414 325

Percent consuming 23 30 35 21 

All Concentrated Formula Range 0-1,242 0-1,242 0-1,123 0-1,064

Per capita mean ± SD 266 ± 296 384 ± 355 414 ± 325 266 ± 296

Consumer only mean 444 562 532 503Percent consuming 60 68 81 56 

Water Added to Juices Range 0-118 0-710 0-473 0-887and Other Beverages Per capita mean ± SD <30 ± 30 30 ± 89 30 ± 89 59 ± 148

Consumer only mean 89 207 148 207

Percent consuming 3 9 18 32 

Water Added to Powdered Range 0-30 0-177 0-266 0-177

Baby Foods and Cereals Per capita mean ± SD <30 ± 30 <30 ± 30 59 ± 59 30 ± 59

Consumer only mean 30 59 89 89

Percent consuming 2 17 64 43 

Water Added to Other Foods Range - 0-118 0-118 0-355

(Soups, Jell-o, Puddings) Per capita mean ± SD - 30 ± 30 <30 ± 30 30 ± 59

Consumer only mean - 89 59 118

Percent consuming 0 2 8 29 

ALL SOURCES OF WATER Range 0-1,242 0-1,419 0-1,123 0-1,745

Per capita mean ± SD 296 ± 325 414 ± 414 473 ± 325 444 ± 355Consumer only mean 414 562 503 473

Percent consuming 68 77 94 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. Source: Levy et al., 1995. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-26 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion Table 3-25. Mean Water Consumption (mL/kg-day) by Race/Ethnicity Race/Ethnic

Group N Plain Tap Water Milk and Milk Drinks Reconstitute d Formula RTF Formula Baby Food Juices and Carbonated Drinks Non­ carbonated 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) 129 (5.7) 

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) 113 (2.6) 

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) 

123

(5.2) 

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) 

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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-27
 
 

 

Table 3-26. 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 

12-24 months 

Sex 

Male 

Female 

Region 

Northeast 

Midwest 

South 

West 

Urbanicity 

Urban 

Suburban 

Rural 

Poverty categorya 

0-1.30 

1.31-3.50 

>3.50 

Total 

296 

650 

475 

471 

175 

197 

352 

222 

305 

446 

195 

289 

424 

233 

946 

11 

18 

15 

15 

13 

14 

15 

17 

16 

13 

15 

19 

14 

12 

15 

1.0 

0.8 

1.0 

0.8 

1.4 

1.0 

1.3 

1.1 

1.5 

0.9 

1.2 

1.5 

1.0 

1.3 

0.6 

130 

108 

116 

119 

121 

120 

113 

119 

123 

117 

109 

128 

117 

109 

118 

4.6 

1.7 

4.1 

3.2 

6.3 

3.1 

3.7 

4.6 

3.5 

3.1 

3.9 

2.6 

4.2 

3.5 

2.3 

a 

N 

SE 

Source: 

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. 

= Number of observations. 

= Standard Error. 

Heller et al., 2000. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-28 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Table 3-27. Intake of Water from Various Sources in 2-13-y-old Participants of the 

DONALD Study 1985-1999 

Water Intake from: 

Boys and girls 

2-3 years 

N = 858b 

Boys and girls 

4-8 years 

N = 1,795b 

Boys 

9-13 years 

N = 541b 

Girls 

9-13 years 

N = 542b 

Mean 

Water in Food (mL/day)a 365 (33)c 487 (36) 673 (36) 

Beverages (mL/day)a 614 (55) 693 (51) 969 (51) 

Milk (mL/day)a 191 (17) 177 (13) 203 (11) 

Mineral water (mL/day)a 130 (12) 179 (13) 282 (15) 

Tap water (mL/day)a 45 (4) 36 (3) 62 (3) 

Juice (mL/day)a 114 (10) 122 (0) 133 (7) 

Soft drinks (mL/day)a 57 (5) 111 (8) 203 (11) 

Coffee/tea (mL/day)a 77 (7) 69 (5) 87 (4) 

634 (38) 

823 (49) 

144 (9) 

242 (15) 

56 (3) 

138 (8) 

155 (9) 

87 (5) 

Mean ± SD 

Total water intakea,d (mL/day) 1,114 ± 289 1,363 ± 333 1,891 ± 428 

Total water intakea,d (mL/kg-day) 78 ± 22 61 ± 13 49 ± 11 

Total water intakea,d (mL/kcalday) 

1.1 ± 0.3 0.9 ± 0.2 1.0 ± 0.2 

1,676 ± 386 

43 ± 10 

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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-29
 
 

 

Table 3-28. Mean (± Standard Error) Fluid Intake (mL/kg/day) by Children Aged 1-10 years, 

NHANES III, 1988-94 

Sample with Sample without 

Total Sample Temperature Information Temperature Information 

(N = 7,925) (N = 3,869) (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. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-30 September 2008 
 

Table 3-29. Estimated Mean (± Standard Error) Amount of Total Fluid and Plain Water Intake 

among Children a Aged 1-10 Years: (NHANES III, 1988-94) 

N 

Total Fluid Plain Water 

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

Age (years) 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

Sex 

Male 

Female 

Race/ethnicity 

White 

African American 

Mexican American 

Other b Poverty income ratio 

Low 

Medium 

High 

Regionc,d 

Northeast 

Midwest 

South 

West 

Urban/rurald 

Urban 

Rural 

Total 

578 

579 

502 

511 

465 

255 

235 

247 

254 

243 

1,974 

1,895 

736 

1,122 

1,728 

283 

1,868 

1,204 

379 

679 

699 

869 

1,622 

3,358 

511 

3,869 

1,393 ± 31 

1,446 ± 31 

1,548 ± 75 

1,601 ± 41 

1,670 ± 54 

1,855 ± 125 

1,808 ± 66 

1,792 ± 37 

2,113 ± 78 

2,051 ± 97 

1,802 ± 30 

1,664 ± 24 

1,653 ± 26 

1,859 ± 42 

1,817 ± 25 

1,813 ± 47 

1,828 ± 32 

1,690 ± 31 

1,668 ± 54 

1,735 ± 31 

1,734 ± 45 

1,739 ± 31 

737 ± 25 

1,736 ± 18 

1,737 ± 19 

1,737 ± 15 

124 ± 2.9 

107 ± 2.3 

100 ± 4.6 

91 ± 2.8 

84 ± 2.3 

81 ± 4.9 

71 ± 2.3 

61 ± 1.8 

65 ± 2.1 

58 ± 2.4 

86 ± 1.8 

81 ± 1.5 

79 ± 1.8 

88 ± 1.8 

89 ± 1.7 

90 ± 4.2 

93 ± 2.6 

80 ± 1.6 

76 ± 2.5 

87 ± 2.3 

84 ± 1.5 

83 ± 2.2 

81 ± 1.7 

84 ± 1.0 

84 ± 4.3 

84 ± 1.1 

298 ± 19 

430 ± 26 

482.± 27 

517 ± 23 

525 ± 36 

718 ± 118 

674 ± 46 

626 ± 37 

878 ± 59 

867 ± 74 

636 ± 32 

579 ± 26 

552 ± 34 

795 ± 36 

633 ± 23 

565 ± 39 

662 ± 27 

604 ± 35 

533 ± 41 

568 ± 52 

640 ± 54 

613 ± 24 

624 ± 44 

609 ± 29 

608 ± 20 

609 ± 24 

26 ± 1.8 

32 ± 1.9 

31 ± 1.8 

29 ± 1.3 

26 ± 1.7 

31 ± 4.7 

26 ± 1.9 

21 ± 1.2 

26 ± 1.4 

24 ± 2.0 

29 ± 1.3 

26 ± 1.0 

24 ± 1.3 

36 ± 1.5 

29 ± 1.1 

26 ± 1.7 

32 ± 1.3 

26 ± 1.4 

22 ± 1.7 

26 ± 2.1 

29 ± 1.8 

28 ± 1.3 

27 ± 1.9 

27 ± 1.1 

28 ± 1.2 

27 ± 1.0 a 

b 

c 

d 

N 

Source: 

Children for whom temperature data were obtained. 

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. 

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. 

= Number of observations. 

Sohn et al., 2001. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-31
 
 

 

 

 

Table 3-30. Tap Water Intake in Breastfed and Formula-fed Infants and Mixed-fed Young Children at Different Age Points

Tap water intakeb (mL/day) Tap water intakeb (mL/kg-day) 

Age N a Total 

Mean SD Median P95 Max 

d Total From Householdc From Manufacturing

Mean SD Median P95 Max % e Mean SD % f Mean SD % f 

Breastfed#1 year, total 30 130 180 50 525 1,172 

3 months 11 67 167 0 493 746 

6 months 12 136 150 68 479 634 

9 months 47 254 218 207 656 1,172 12 months 18 144 170 85 649 649 

17 24** 6 65 150 17 15 23** 85 2.4 4.7** 15 

10 25** 0 74 125 10 10 25** 97 0.3 1.9** 3 

18 20** 8 5`8 85 18 14 19** 79 3.8 6.3* 21 

30 27** 23 77 150 28 26 27** 87 3.7 3.4 13 

15 18** 9 66 66 19 13 18** 86 2.2 2.1 14 

Formula fed

#1 year, total 75 441 244 440 828 1,603 

3 months 78 662 154 673 874 994 

6 months 14 500 178 519 757 888 

9 months 24 434 236 406 839 1,579 12 months 29 360 256 335 789 1,603 

53 33 49 115 200 51 49 33 92 4.0 8.0 8 

107 23 107 147 159 93 103 28 97 3.4 17.9 3 

63 23 65 99 109 64 59 25 92 4.8 8.0 8 

49 27 45 94 200 50 44 27 91 4.5 6.3 9 37 26 32 83 175 39 33 25 91 3.3 3.7 9 

Mixed - Breast and Formula1-3 years, total 90 241 243 175 676 2,441 18 months 27 280 264 205 828 1,881 24 months 29 232 263 158 630 2,441 36 months 33 217 199 164 578 1,544 

19 20 14 56 203 24 15 20 78 3.9 5.5 22 

25 23 18 70 183 28 22 23 88 3.0 4.1 12 18 21 12 49 203 23 15 21 80 3.7 5.0 20 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. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-32 September 2008 
 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion Table 3-31. Percentage of Subjects Consuming Beverages and Mean Daily Beverage Intakes (mL/day) for Children With Returned Questionnaires Age at Questionnaire Actual Age (Months) N b 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 6-24 Monthsa 

-

585 c 

Human Milkd 30 19 11 5 3 0 -

Infant Formulae 

% dmL/dayf 

68

798 ± 234 

69

615 ± 328 

29

160 ± 275 

4

12 ± 77 

2

9 ± 83 

0

-

67 g

207 ± 112 

Cows’ Milke 

% dmL/dayf 

5

30 ± 145 

25

136 ± 278 

79

470 ± 310 

91

467 ± 251 

93

402 ± 237 

97

358 ± 225 

67 g

355 ± 163 

Formula and Cows’ Milke 

% dmL/dayf 

70

828 ± 186 

81

751 ± 213 

88

630 ± 245 

92

479 ± 248 

94

411 ± 237 

98

358 ± 228 

67 g

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 

99 h

183 ± 103 

Water% d

mL/dayf 

36

27 ± 47 

59

53 ± 71 

75

92 ± 109 

87

124 ± 118 

90

142 ± 127 

94

145 ± 148 

99 h

109 ± 74 

Other Beveragesi 

% dmL/dayf 

1

3 ± 18 

9

6 ± 27 

23

27 ± 71 

42

53 ± 109 

62

83 ±121 

86

89 ± 133 

80 h

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 six-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 six-through 24 month period. Children who consumed human milk are not included.h Percentage of children consuming beverage during six-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.

Source: Marshall et al., 2003a. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 3-33
 
 

 

Table 3-32. Mean (± Standard Deviation) Daily Beverage Intakes Reported on Beverage Frequency Questionnaire and 3-day Food and Beverage Dairies

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 %b a %b a %b a %b mL/day mL/day mL/day mL/day

Human Milk 204 ± 373 195 ± 358 28.0 9 ± 21 56 ± 225 12.6 NA c NA - NA NA ­

Infant formula 609 ± 387 603 ± 364 85.8 180 ± 290 139 ± 251 37.0 NA NA - NA NA ­

Cow’s 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 

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.
Source: Marshall et al., 2003b. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Page Child-Specific Exposure Factors Handbook 

3-34 September 2008 
 Table 3-33. Consumption of Beverages by Infants and Toddlers (Feeding Infants and Toddlers Study) Age (months) 4-6 (N = 862) 7-8 (N = 483) 9-11 (N = 679) 12-14 (N = 374) 15-18 (N = 308) 19-24 (N = 316) Beverage category Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD Consumers Mean ± SD %a b %a b %a b %a b %a b %a b mL/day mL/day mL/day mL/day mL/day mL/day c Total milks 100 778 ± 257 100 692 ± 257 99.7 659 ± 284 98.2 618 ± 293 94.2 580 ± 305 93.4 532 ± 281 d 100% juice 21.3 121 ± 89 45.6 145 ± 109 55.3 160 ± 127 56.2 186 ± 145 57.8 275 ± 189 61.6 281 ± 189 e Fruit drinks 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 f Other 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, nonresponse, 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.
 c Includes human milk, infant formula, cow’s milk, soy milk, and goat’s 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. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

Child-Specific Exposure Factors Handbook Page
 September 2008 3-35
 
 

 

Table 3-34. Pool Water Ingestion by Swimmers 

Study Group Number of Average Water Ingestion Rate Average Water Ingestion Rate 

Participants (mL/45-minute interval) (mL/hour)a 

Children <16 years old 41 37 49 

 Males<16 years old 20 45 60 

 Females <16 years old 21 30 43 

Adults (>18 Years) 12 16 21 

 Men 4 22 29 

 Women 8 12 16 

a Converted from mL/45 minute interval. 

Source: Dufour et al., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 3 - Water Ingestion 

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Child-Specific Exposure Factors Handbook 

Chapter 4 - Non-dietary Ingestion Factors 

4 NON-DIETARY INGESTION FACTORS 

4.1 INTRODUCTION 

Young 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). Young children mouth objects 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). 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 (e.g., Ko 

et al., 2007). 

In a large non-random sample of children born 

in Iowa, non-nutritive sucking behaviors were reported 

by parents to be very common in infancy, and to 

continue for a substantial proportion of children up to 

the third and fourth birthdays (Warren et al., 2000). 

Hand to mouth behavior has been observed in both preterm and full term infants (Rochat et al., 1988, Blass et 

al., 1989, Takaya et al., 2003). 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). 

Children’s mouthing behavior can potentially result in 

ingestion of toxic substances (Lepow et al., 1975). 

There are three general approaches to gather 

data on children’s mouthing behavior: real-time hand 

recording, in which trained observers manually record 

information (e.g., 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 (e.g., Black et 

al., 2005); and questionnaire, or survey response, 

techniques (e.g., Stanek et al., 1998). With real-time 

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 care giving 

relationship to the child. On the other hand, young 

children’s behavior may be influenced by the presence 

of unfamiliar people (e.g., 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 the children’s behavior. With videotranscription 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 crewcaused “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. 

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 handbook does not address issues 

related to contaminant transfer from thumbs, fingers, or 

objects or surfaces, into the mouth, and subsequent 

ingestion. The recommendations for mouthing 

Child-Specific Exposure Factors Handbook Page 

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Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

frequency and duration are provided in Section 4.2, 

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 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 in a 

meta analysis, which is the primary source of the 

recommendations provided in this chapter for hand-tomouth frequency. Following the recommendations, key 

and relevant studies on mouthing frequency (section 

4.3) and duration (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. In several cases, key studies pre-dated 

the recommendations on 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 were performed 

on groups of children of varying ages. 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. The recommended hand-tomouth 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 of interest to U.S. EPA and categorized the data 

according to indoor and outdoor contacts. The 

recommendations for frequency of object-to-mouth 

contact are based on data from Reed et al., (1999), 

Freeman et al., (2001), Tulve et al., (2002), AuYeung 

et al., (2004), and Black et al., 2005. 

Recommendations for duration of object-to-mouth are 

based on data from Juberg et al., (2001) and Greene, 

(2002). Recommendations for hand-to-mouth duration 

are not provided since those estimates may not be 

relevant to environmental exposures. 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-tomouth. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific 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 Percentiile 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 

Mean Frequency (contacts/hour) 95th Percentile Frequency (contacts/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 

-

-

-

24a 

20b 

10c 

10c 

1d 

-

-

-

-

-

-

-

-

-

-

-

-

Reed et al., 1999; Freeman 

et al., 2001; Tulve et al., 

2002; AuYeung et al., 2004; 

and Black et al., 2005. 

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 

-

-

11e 

11e 

8 

13g 

-

-

-

-

-

-

26f 

26f 

22 

16h 

-

-

-

-

Juberg et al., 2001 and 

Greene, 2002. 

a Mean calculated from Black et al., 2005 (7 to 12 months). 

b Mean calculated from Tulve et al., 2002 (#24 months), AuYeung et al., 2004 (#24 months), and Black et al., 2005 (1 and 2 

years). 

c Mean calculated from Reed et al., 1999 (2 to 6 years), Freeman et al., 2001 (3 to 4 years and 5 to 6 years), Tulve et al., 2002 (>24 

months), AuYeung et al., 2004 (2 to 6 years), and Black et al., 2005 (37 to 53 months). d Mean calculated from Freeman et al., 2001 (7 to 8 years and 10 to 12 years). e Mean calculated from Juberg et al., 2001 (0 to 18 months) and Greene, 2002 (3 to 12 months). f Calculated 95th percentile from Greene, 2002 (3 to 12 months). g Mean calculated from Juberg, et al., 2001 (19 to 36 months) and Greene, 2002 ( 24 to 36 months). h Calculated 95th percentile from Greene, 2002 ( 24 to 36 months). 

S = No data. 

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Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

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

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or defined) Bias 

The approaches for data collection and analysis used were adequate to 

provide estimates of children’s mouthing frequencies and durations. 

Sample sizes were very small relative to the population of interest. Almost 

all key studies published primary data; in cases where secondary data were 

used, U.S. EPA judged the secondary data 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 are 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, when compared with results obtained 

using alternate data collection techniques (e.g., Smith and Norris, 2003). 

Several of the key studies applied and documented quality assurance/quality 

control measures. 

Low 

Variability and Uncertinty 

Variability in Population 

Description of Uncertainty 

The key studies characterized inter-individual variability to a limited extent, 

and 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 

methodoloogies (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 

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Child-Specific 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.,1997a - Quantifying 

Videotaped Activity Patterns: Video 

Translation Software and Training 

Technologies/Zartarian et al., 1997b ­

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. (1997a, 1997b, 1998) 

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, resulting in 

poor inter-observer reliability and observer fatigue 

when attempted for long periods of time, prompting the 

investigation into using videotaping with transcription 

of the children’s activities at a point in time after the 

observations (videotaping) 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 one 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-activitypatterns 

of children to be used to evaluate software for 

videotaped activities and translation training methods. 

The researchers reported measures taken to assess interobserver 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. Average object 

to mouth contacts for the four children were reported to 

be 9 contacts per hour, with the average per child 

ranging from 1 to 19 contacts per hour (Zartarian et al., 

1997a). Objects mouthed included bedding/towels, 

clothes, dirt, grass/vegetation, hard surfaces, hard toys, 

paper/card, plush toy, and skin (Zartarian et al., 1997a). 

Average hand to mouth contacts for the four children 

were reported to be 13 contacts per hour (averaging the 

sum of left hand and right hand to mouth contacts and 

averaging across children, from Zartarian et al., 1997b), 

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 day care center in New 

Brunswick, New Jersey, and ten children ages 2 to 5 

years old at residences in Newark and Jersey City, New 

Jersey who were not selected randomly, were studied 

(gender 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. 

The video-transcription mouthing contact 

frequency results are presented in Table 4-3. 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” 

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Child-Specific Exposure Factors Handbook
 

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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 described 

quality assurance steps taken to assure reliability of 

transcribed videotape data. However, only a small 

number of children were studied, some 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. Due to the 

children’s ages, the presence of unfamiliar persons 

following the children with a video camera may 

influence the video-transcription results. The parents’ 

survey responses may also 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 Microactivity 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 nonfood items, and mouthing of thumbs/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 four 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 

percent 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. Gender 

differences were observed for some of the activities, 

with boys spending significantly more time outdoors 

than girls. Hand to mouth 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) was also 

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, 

in contact with soil or grass, and 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 

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Child-Specific Exposure Factors Handbook 

Chapter 4 - Non-dietary Ingestion Factors 

transcribed videotape data. However, the children in 

this study may not be representative of all children in 

the U.S. 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 186 15-minute 

observation periods were included in the study, with the 

number of observation periods per child ranging from 

1 to 6. 

Results of the data analyses indicated that 

there was no association between mouthing frequency 

and gender, 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 

children >24 months had the lowest (42 events/hour) 

(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 videotranscription 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, California peninsula, along with one 

child selected by convenience due to 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 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. (1997a). Both frequency 

and duration (see Section 4.4.2.5 of this Chapter) were 

analyzed. Between 5 and 10 percent 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 gender 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. Mouthing 

frequencies for indoor locations are shown in Table 4-7. 

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 (Table 4-8) were very similar for 

children #24 months of age (13.9 contacts/hour) and 

>24 months (14.6 contacts/hour). 

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Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

Nonparametric tests, such as the Wilcoxon 

rank sum test were used for the data analyses. Both age 

and gender 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 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. Due to the children’s ages, the 

presence of unfamiliar persons following the children 

with a video camera may have influenced the videotranscription 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, in the spring and 

summer of 2000, using a survey response and a videotranscription methodology. A companion study 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 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 foodhandling 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, genders, reported hand-washing, mouthing and 

food-handling 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 four 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 

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 

to mouth 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 gender 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). Results of this study 

are shown in Table 4-9. 

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 (mid-Rio 

Grande Valley) and is not likely to be representative of 

the national population. Due to the children’s ages, the 

presence of unfamiliar persons following the children 

with a video camera may have influenced the videotranscription methodology results. 

4.3.1.7	 Xue et al., 2007 - A Meta-analysis of 

Children’s Hand-to-Mouth Frequency Data 

for Estimating Nondietary Ingestion 

Exposure 

Xue et al. (2007) gathered hand-to-mouth 

frequency data from 9 available studies representing 

429 subjects and more than 2,000 hours of behavior 

observation. The studies used in this analysis included 

several of the studies summarized in this chapter 

(Zartarian et al. ,1998; Reed et al., 1999; Freeman et al., 

2001; Greene, 2002; Tulve et al., 2002; and Black et 

al., 2005), as well as several other sets of unpublished 

data. These data were used to conduct a meta-analysis 

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Child-Specific Exposure Factors Handbook 

Chapter 4 - Non-dietary Ingestion Factors 

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)), gender, and 

indoor/outdoor location; 

2) fit variability distributions to the available 

hand-to-mouth frequency data for use in one 

dimensional Monte Carlo exposure 

assessments; 

3) fit uncertainty distributions to the available 

hand-to-mouth frequency data for use in two 

dimensional 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 

(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. There were 894 hours of behavior 

observation data for the 429 children, ages 0.3 to 12 

years, across all available studies. It was found that age 

and location (indoor vs. outdoor) were important 

factors contributing to hand to mouth frequency, but 

study and gender were not (Xue et al., 2007). 

Distributions of hand to mouth frequencies were 

developed for both indoor and outdoor activities. 

Distributions are presented in Table 4-10 for indoor 

settings and Table 4-11 for outdoor settings. Hand to 

mouth frequencies decreased for both indoor and 

outdoor activity as age increased, and 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 using U.S. 

EPA’s recommended age groups using available data 

on mouthing behavior from studies using different 

methodologies, of children in different locations. 

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, Washington. 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 during a seven day period in 

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 

percent), their race as Caucasian (89 percent), their 

household income in the >$30,000 range (56 percent) 

or their housing status as single-family home occupants 

(69 percent). 

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 4-12 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 16 15-minute observation periods with 

60 15-second intervals per 15-minute observation 

period, or 960 15-second intervals in all. The number 

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Child-Specific Exposure Factors Handbook
 

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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 percent 

of the cases.” 

One advantage of this study is the 

simultaneous observations by both parents and trained 

observers that allows comparisons to be made 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. 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 care givers may also 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.” 

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 

Lewand Butterworth (1997) studied 14 mostly 

first-born infants (10 males, 4 females) in Stirling, 

United Kingdom, in 1990 using a video-transcription 

methodology. Attempts were made to study each 

infant within a week of the infant’s 2-month, 3-month, 

4-month 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 

percent) of the movements documented during the 

object handling period, and reported inter-observer 

agreement of 0.90 using Cohen’s kappa (a measure of 

the agreement between two raters) for the location of 

contacts. The frequency of contacts ranged between 0 

and 1 contacts per minute. 

The advantages of this study were that use of 

video cameras could be expected to have minimal 

impact 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 four 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 

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Child-Specific Exposure Factors Handbook 

Chapter 4 - Non-dietary Ingestion Factors 

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 four minute period. The researchers 

performed inter-observer reliability tests on the 

videotape data and reported an inter-coder Index of 

Concordance of 93 percent. 

The advantages of this study were that use of 

video cameras could be expected to have virtually no 

impact 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 

percent males, 49 percent females) 14 to 69 months old 

was recruited via an urban health center and direct 

contacts in the surrounding area, apparently in Chicago, 

Illinois. Participating children were primarily Hispanic 

(89 percent). 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 object in mouth. Mouthing behaviors included 

hand-to-mouth area both with and not with food, handin-mouth with or without food, and object-in-mouth 

including food, drinks, toys or other objects. 

Survey responses for the 37 children who were 

also 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 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 object-in-mouth touches per hour for the 2 

children reported to “never” perform this behavior. 

Videotaping was attempted for two 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 nonrandomly 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 

due to 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 due to the presence of strangers who 

videotaped them. 

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 children’s own home environments. 

The study consisted of an initial pilot study conducted 

in February 1998, a second phase conducted in April 

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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 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 five 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 day(s) 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. 

The results of the combined pilot and second 

phase II data are shown in Table 4-13. 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 nonconsecutive 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 (such as stopwatches, analog or digital 

clocks, or guesses) parents used to record mouthing 

event durations. 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 (CPSC) conducted a survey response and 

real-time hand recording studybetween 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 sucking, 

chewing, or otherwise putting an object on his/her lips 

or into his/her mouth. Participants were recruited via a 

random digit dialing telephone survey in urban and 

nearby rural areas of Houston, Texas and Chicago, 

Illinois. 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, 491children ages 3 to 81 months participated. 

Parents were instructed to use watches with second 

hands, or 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, non-consecutive 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 percent) 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 two hours of 

each of two days. The observations were done at 

different times of the day at the child’s home and/or 

child care facility. Table 4-14 shows the prevalence of 

observed mouthing among the 169 children in the 

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Child-Specific Exposure Factors Handbook 

Chapter 4 - Non-dietary Ingestion Factors 

second phase. All children were observed to mouth 

during the four hours of observation time; 99 percent 

mouthed the category defined as “anatomy.” Pacifiers 

were mouthed by 27 percent in an age-declining pattern 

ranging from 47 percent of children less than 12 months 

old to 10 percent of the 2 to <3 year olds. 

Table 4-15 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 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, there 

were usable data 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, from the 

2 hours of observation per day for two days, for the 109 

children, the researchers developed a statistical model 

that accounted for the children’s demographic 

characteristics, in order to estimate exposure times for 

the 60 children for whom exposure time data were 

missing, 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 percent 

males, 45 percent females. The study’s sample was 

drawn in an attempt to duplicate the overall U.S. 

demographic characteristics with respect to race, 

e t h n i c i t y , s o c i o e c o n o m i c s t a t u s a n d 

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 U.S. However, the observers’ presence and 

use of a stopwatch to time mouthing durations may 

have affected 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 Week 

Old Infants 

Barr et al. (1994) studied hand to mouth 

contact, as well as other behaviors, in 15 newborn (8 

males, 7 females) and 15 five to seven week old (8 

males, 7 females) full-term Canadian infants using a 

video-transcription methodology. The newborns were 

2 to 3 days old, in a quiet, temperature-controlled room 

at the hospital, 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 one 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 one minute baseline period were 

in the range of 0 to 2 percent. The five to seven 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 percent 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 interobserver reliability tests on the videotape data and 

reported a mean inter-observer reliability of 0.78 by 

Cohen’s kappa (a measure of the agreement between 

two raters). 

The advantages of this study were that use of 

video cameras could be expected to have virtually no 

impact on newborns’ or five to seven week old infants’ 

behavior, and inter-observer reliability tests were 

performed. The study data did not represent newborn 

or five to seven week old infant hand to mouth contact 

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Child-Specific Exposure Factors Handbook
 

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during periods in which infants of these ages were in a 

sleeping or other non-alert state, and 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., 1997a - Quantifying 

Videotaped Activity Patterns: Video 

Translation Software and Training 

Technologies/Zartarian et al., 1997b ­

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. 

(1997a, 1997b, 1998) 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, resulting in poor inter-observer 

reliability and observer fatigue when attempted for long 

periods of time, prompting the investigation into using 

videotaping with transcription of the children’s 

activities at a point in time after the observations 

(videotaping) occurred. 

Four Mexican-American farmworker 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 one 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-dietaryobjects 

an average of 4.35 percent (range 1.41 to 7.67 percent) 

of the total observation time, excluding the time during 

which the children were out of the camera’s view 

(Zartarian et al., 1997a). Objects mouthed included 

bedding/towels, clothes, dirt, grass/vegetation, hard 

surfaces, hard toys, paper/card, plush toy, and skin 

(Zartarian et al., 1997a). 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., 1997a, and 

is described in Zartarian et al., 1997b. The four 

children mouthed their hands an average of 2.35 

percent (range 1.0 to 4.4 percent) of observation time. 

The researchers reported measures taken to assess interobserver 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 video-transcription 

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 ten 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-observer 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 

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Chapter 4 - Non-dietary Ingestion Factors 

was to select 12 times per hour randomly during the 

entire waking period of four children during one day, in 

which the researchers recorded activities and total 

mouthing times. 

Although the sample size was relatively small, 

the results provided estimates of mouthing times, other 

than pacifier use, during a 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 two days of observations was interpreted 

as the estimate for that child. Summary statistics are 

shown in Table 4-16. 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 nonpacifier mouthing durations of 36.9 minutes per day, 

with toys as the most frequently mouthed product 

category, and the 6 to 12 month children (N=14) 44 

minutes per day (fingers most frequently mouthed). 

The 12 to 18 month olds’ (N=12) estimated mean nonpacifier 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’s 

behavior might affect the 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 observation interfered with care giving 

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 Behaviour 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 two 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, biting or 

chewing, with a description of each category, together 

with pictures, given to parents as guidance for what to 

record. 

The results of the study are shown in Table 4­

17. 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 percent 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 selected 25of the 236 children 

randomly for a single 15 minute observation of each 

child (total observation time across all children: 375 

minutes), in order 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 

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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 was 

also lower (6 minutes and 7 seconds by video versus 9 

minutes and 43 seconds for both parents and trained 

observers). 

The strengths of this study were its comparison 

of three types of observation (parents, trained 

professional 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 the study 

population, and may not be representative of U.S. 

children. 

4.4.2.5	 Au Yeung 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, California peninsula, 

along with one child selected by convenience due to 

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 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. (1997a). Both frequency 

(see Section 4.3.1.5 of this Chapter) and duration were 

analyzed. Between 5 and 10 percent 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 durations were 

analyzed by age and gender 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. Mouthing 

durations are shown in Table 4-18 (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 (Table 4-19). For 

outdoor environments, median contact durations for 

these age groups decreased to 0.8 and 0.6 minutes/hour, 

respectively (Table 4-20). 

Nonparametric tests, such as the Wilcoxon 

rank sum test were used for the data analyses. Both age 

and gender 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 a variety of 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. Due to the children’s ages, the 

presence of unfamiliar persons following the children 

with a video camera may have influenced the videotranscription methodology results. 

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Child-Specific Exposure Factors Handbook 

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4.5	 MOUTHING PREVALENCE 

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 4-21 presents the prevalence of reported 

non-food ingestion/mouthing behaviors by child’s age 

as the percent 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 

two year olds, but rose slightly for three and four 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 one year olds and declined 

with age for daily and more than weekly use; for more 

than monthly use of a pacifier several six year olds were 

reported to use pacifiers, which altered the agedeclining 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 one 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 of age 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 semi-urban 

residents within various socioeconomic categories and 

with varying racial/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 over 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, 3, 6, 9, 12, 16 and 24 months old, and 

yearly after age 24 months. Questions were posed 

regarding the child’s sucking behavior over the 

previous 3 to 12 months. 

The authors reported that nearly all children 

sucked non-nutritive items, including pacifiers, thumbs 

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Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

or other fingers, and/or other objects, at some point in 

their early years. The parent-reported sucking behavior 

prevalence peaked at 91 percent for 3 month old 

children. At 2 years of age, a majority (53 percent) 

retained a sucking habit, while 29 percent retained the 

habit at age 3 years and 21 percent 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 due to 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, 

A.C.; Leckie, J.O. (2004) Young children’s 

mouthing behavior: An observational study 

via videotaping in a primarily outdoor 

residential setting. J Children’s Health 2(3­

4):271-295. 

Barr, R.G.; Quek, V.S.H.; Cousineau, D.; Oberlander, 

T.F.; Brian, J.A.; Young, S.N. (1994) Effects 

of Intra-oral sucrose on crying, mouthing and 

hand-mouth contact in newborn and six-weekold infants. Dev Med Child Neurol 36:608­

618. 

Black, K.; Shalat, S.L.; Freeman, N.C.G.; Jimenez, M.; 

Donnelly, K.C.; Calvin, J.A. (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. 

Blass, E.M.; Fillion, T.J.; Rochat, P.; Hoffmeyer, L.B.; 

Metzger, M.A. (1989) Sensorimotor and 

Motivational Determinants of Hand-Mouth 

Coordination in 1-3-Day-Old Human Infants. 

Dev Psych 25(6):963-975. 

Davis, S.; Myers, P.A.; Kohler, E.; Wiggins, C. (1995). 

Soil Ingestion in Children with Pica: Final 

Report. U.S. EPA Cooperative Agreement 

CR 816334-01. Seattle, Washington: Fred 

Hutchinson Cancer Research Center. 

Ferguson, A.C.; Canales, R.A.; Beamer, P.; AuYeung, 

W.; Key, M.; Munninghoff, A.; Lee, K. T.-W.; 

Robertson, A., Leckie, J.O. (2006) Video 

methods in the quantification of children’s 

exposures. J Expo Sci Environ Epidemiol 

16:287-298. 

Freeman, C.G.; Jimenez, M.; Reed, K.J.; Gurunathan, 

S.; Edwards, R.D.; Roy, A.; Adgate, J.L.; 

Pellizzari, E.D.; Quackenboss, J.; Sexton, K.; 

Lioy, P.J. (2001) Quantitative analysis of 

children’s microactivity patterns: The 

Minnesota children’s pesticide exposure 

study. J Expo Anal Environ Epidemiol 

11:501-509. 

Greene, M.A. (2002) Mouthing times for children from 

the observational study. U.S. Consumer 

Product Safety Commission, Bethesda, MD. 

Groot, M. E.; Lekkerkerk, M. C.; Steenbekkers, L. P. 

A. (1998) Mouthing Behavior of Young 

Children: An observational Study. 

Wageningen Agricultural University, 

Wageningen, the Netherlands. 

Juberg, D.R.; Alfano, K.; Coughlin, R.J.; Thompson, 

K.M. (2001) An Observational Study of 

Object Mouthing Behavior by Young 

Children. Pediatrics 107(1)135-142. 

Ko, S.; Schaefer, P.; Vicario, C.; Binns, H.J. (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 17:47-47. 

Lepow, M.L.; Bruckman, L.; Gillette, M.; Markowitz, 

S.; Robino, R.; Kapish, J. (1975) 

Investigations into Sources of Lead in the 

Environment of Urban Children. Environ Res 

10:415-26. 

Lew, A.R.; 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(1):59-69. 

Norris,	 B.; Smith, S. (2002) Research into the 

mouthing behaviour of children up to 5 years 

old. London: Consumer and Competition 

Policy Directorate, Department of Trade and 

Industry. 

Page Child-Specific Exposure Factors Handbook 

4-18 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 4 - Non-dietary Ingestion Factors 

Reed, K.; Jimenez, M.; Freeman, N.; Lioy, P. (1999) 

Quantification of children’s hand and 

mouthing activities through a videotaping 

methodology. J Expo Anal Environ 

Epidemiol 9:513-520. 

Rochat,	 P.; Blass, E.M.; Hoffmeyer, L.B. (1988) 

Oropharyngeal Control of Hand-Mouth 

Coordination in Newborn Infants. Dev Psych 

24(4):459-63. 

Shalat, S.L.; Donnelly, K.C.; Freeman, N.C.G.; Calvin, 

J.A.; Ramesh, S.; Jimenez, M.; Black, K.; 

Coutinho, C.; Needham, L.L.; Barr, D.B.; 

Ramirez, J. (2003) Nondietary ingestion of 

pesticides by children in an agricultural 

community on the U.S./Mexico border: 

Preliminary Results. J Expos Anal Environ 

Epidemiol 13:42-50. 

Smith, S.A.; Norris, B. (2003). Reducing the risk of 

choking hazards: mouthing behavior of 

children aged 1 month to 5 years. Injury 

Control and Safety Promotion 10(3):145-154. 

Stanek, E.J.; Calabrese, E.J.; Mundt, K.; Pekow, P.; 

Yeatts, K.B. (1998) Prevalence of soil 

mouthing/ingestion among healthy children 

aged 1 to 6. J Soil Contam 7(2):227-242. 

Takaya,	 R.; Yukuo, K.; Bos, A.F.; 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 Bermasco, N.H. (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. 

Tulve, N.S.; Suggs, J.C.; McCurdy, T.; Cohen Hubal, 

E.A.; Moya, J. (2002) Frequency of mouthing 

behavior in young children. J Expo Anal 

Environ Epidemiol 12:259-264. 

U.S. EPA. (2005) Guidance on selecting age groups for 

monitoring and assessing childhood exposures 

to environmental contaminants. Washington, 

DC.: U.S. Environmental Protection Agency, 

Office of Research and Development. 

EPA/630/P-03/003F. 

Warren, J.J.; Levy, S.M.; Nowak, A.J.; Tang. S.	 Nonnutritive sucking behaviors in preschool 

children: a longitudinal study. (2000) Pediatr 

Dent 22(3):187-91. 

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 Analysis 27(2):411­

420. 

Zartarian, V.G.; Streicker, J.; Rivera, A.; Cornejo, C.S.; 

Molina, S.; Valadez, O.F.; Leckie, J.O. 

(1995) A Pilot Study to Collect MicroActivity Data of Two- to Four-Year-Old Farm 

Labor Children in Salinas Valley, California. 

J Expo Anal Environ Epidemiol 5(1):21-34. 

Zartarian V.G.; Ferguson A.C.; Ong, C.G.; Leckie J. 

(1997a) Quantifying Videotaped Activity 

Patterns: Video Translation Software and 

Training Methodologies. J Expo Anal 

Environ Epidemiol 7(4):535-542. 

Zartarian V.G.; Ferguson A.; Leckie J. (1997b) 

Quantified dermal activity data from a fourchild pilot field study. J Expo Anal Environ 

Epidemiol 7(4):543-553. 

Zartarian, V.G.; Ferguson, A.C.; Leckie, J.O. (1998) 

Quantified mouthing activity data from a fourchild pilot field study. J Expo Anal Environ 

Epidemiol 8(4):543-553. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 4-19
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific 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 

Object to mouth 

0.4 9.5 8.5 20.1 

0 16.3 3.6 77.1 

25.7 

86.2 

Source: Reed et al., 1999. 

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

Age Group Thumbs/fingers in Mouth Toes in Mouth Non-food Items in Mouth 

3 years 

4 years 

5 years 

6 years 

7 years 

8 years 

9 years 

10 years 

11 years 

12 years 

71 

63 

33 

30 

28 

33 

43 

38 

33 

33 

29 

0 

-

-

-

-

-

-

-

-

71 

31 

20 

29 

28 

40 

38 

38 

48 

17 

-

Source: 

= No data. 

Freeman et al., 2001. 

Table 4-5. Video-transcription Median (Mean) Observed Mouthing in 19 Minnesota Children (contacts/hour) 

Age Group N Object-to-moutha Hand-to-mouth 

3 to 4 years 

5 to 6 years 

7 to 8 years 

10 to 12 years 

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. 

Page Child-Specific Exposure Factors Handbook 

4-20 September 2008 
 

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 

Mouth-body 186 8 2 2-3 69 10 4 3-6 117 7 1 Mouth-hand 186 16 11 9-14 69 18 12 9-16 117 16 9 Mouth-surface 186 4 1 0.8-1.2 69 7 5 3-8 117 2 1 Mouth-toy 186 27 18 14-23 69 45 39 31-48 117 17 9 Total events 186 56 44 36-52 69 81 73 60-88 117 42 31 a Number of observations.
 b Arithmetic mean.
 c The 95% confidence intervals (CI) apply to median. Values were calculated in logs and converted to original units.
 

Source: Tulve et al., 2002. 

Child-Specific Exposure Factors Handbook Page 

September 2008 4-21 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Chapter 4 - Non-dietary Ingestion Factors
 

Table 4-7. Indoor Mouthing Frequency (Contacts per hour), Video-transcription of 9 Children with >15 minutes in View Indoors 

Age Group N Statistic Hands 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 hour), Video-transcription of 38 Children 

Age Group N Statistic Hands 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. 

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Chapter 4 - Non-dietary Ingestion Factors
 

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

Hand to mouth Object to Mouth 

Age N Frequency Frequency 

(contacts/hour) (contacts/hour) 

Infant 13 14 (19.8 ± 14.5) 18.1 (24.4 ± 11.6) 

1 year 12 13.3 (15.8 ± 8.7) 8.4 (9.8 ± 6.3) 

2 years 18 9.9 (11.9 ± 9.3) 5.5 (7.8 ± 5.8) 

Preschool 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. 

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

Age Group N Mean SD 

Percentiles 

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 

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) Distributions from Various Studies 

Age Group N Mean SD 

Percentiles 

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 

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. 

Child-Specific Exposure Factors Handbook Page 

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Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

Table 4-12. Survey Reported Mouthing Behaviors for 92 Washington State Children 

Behavior 

Never 

N % 

Seldom 

N % 

Occasionally 

N % 

Frequently 

N % 

Always 

N % 

Unknown 

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 4-13. 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 Object a 

All Children Only Children Who 

Mouthed Object a 

Minutes Minutes Minutes Minutes 

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 4-14. 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 

Pacifiers 

Non-pacifiers 

Soft Plastic Food Content Items 

Anatomy 

Non-soft Plastic Toys, Teethers, and Rattles 

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. 

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Chapter 4 - Non-dietary Ingestion Factors
 

Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour) 

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 Pacifiersb 

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 Items 

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 Items 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 Toys, Teethers, and Rattles 

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 Toys 

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 Teethers and Rattles 

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 Items 

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 

Child-Specific Exposure Factors Handbook Page
 

September 2008 4-25
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

Table 4-15. Estimates of Mouthing Time for Various Objects (minutes/hour) (continued) 

Age Group Mean (SD) Median 95th Percentile 99th Percentile 

Soft Plastic Food Contact Items 

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 

Non Soft Plastic Toys, Teethers, and Rattles 

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 Items 

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 

Pacifiers 

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, nonfood contact items (toys, teethers and rattles) 

and other soft plastic. 

SD = Standard deviation. 

Source: Greeene, 2002. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

Table 4-16. Mouthing Times of Dutch Children Extrapolated to Total Time While Awake, Without Pacifier, in Minutes per Day 

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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 4-27
 
 

Table 4-17. Estimated Mean Daily Mouthing Duration by Age Group for Pacifiers, Fingers, Toys, and Other Objects (hours:minutes:second

Age Group 

Item 1 to 3 3 to 6 6 to 9 9 to 12 12 to 15 15 to 18 18 to 21 21 to 24 2 3 4 

Mouthed months months months months months months months months years years years 

N = 9 14 15 17 16 14 16 12 39 31 29 

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 

Fingers 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 

Toys 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 

Other Objects 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 

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 

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 

N = Number of children in sample. Source: Smith and Norris, 2003. 

Page Child-Specific Exposure Factors Handbook 

4-28 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

Table 4-18. Outdoor Median Mouthing Duration (seconds per contact), Video-transcription of 38 Children 

Age Group N Statistic Hands 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 

2 

1 

0 to 40 

>24 months 30 

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 

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 4-19. Indoor Mouthing Duration (minutes per hour), Video-transcription of 9 Children with >15 minutes in View Indoors 

Age Group N Statistic Hands 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. 

Child-Specific Exposure Factors Handbook Page
 

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Child-Specific Exposure Factors Handbook
 

Chapter 4 - Non-dietary Ingestion Factors
 

Table 4-20. Outdoor Mouthing Duration (minutes per hour), Video-transcription of 38 Children 

Age Group N Statistic Hands 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 Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 4 - Non-dietary Ingestion Factors 

Table 4-21. Reported Daily Prevalence of Massachusetts Children’s Non-Food Mouthing/Ingestion Behaviors 

Percent of children reported to mouth/ingest daily Object or substance 

mouthed or ingested 1 year 2 years 3 to <6 yearsa 6 years All years 

N=171 N=70 N=265 N=22 N=528 

Grass, leaves, flowers 16 0 1 0 6 

Twigs, sticks, woodchips 12 0 0 0 4 

Teething toys 44 6 2 9 17 

Other toys 63 27 12 5 30 

Blankets, cloth 29 11 10 5 16 

Shoes, Footwear 20 1 0 0 7 

Clothing 25 7 9 14 14 

Crib, chairs, furniture 13 3 1 0 5 

Paper, cardboard, tissues 28 9 5 5 13 

Crayons, pencils, erasers 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 butts, tobacco 4 0 1 0 2 

Suck fingers/thumb 44 21 24 14 30 

Suck feet or toes 8 1 0 0 3 

Bite nails 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). 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

5 SOIL AND DUST INGESTION

5.1 INTRODUCTION

The ingestion of soil and dust is a potential 

route of exposure to environmental chemicals. Children 

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 also ingest soil and dust through 

deliberate hand to mouth movements, or unintentionally 

by eating food that has dropped on the floor. Thus, 

understanding soil and dust ingestion patterns is an 

important part of estimating children's 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. 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, soil­pica, 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.

Soil­pica 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 non­food substances, or 

ingesting large quantities of certain particular foods. 

Definitions of pica often include references to recurring 

or repeated ingestion of these substances. Soil­pica is 

pica that is specific to ingesting materials that are 

defined as soil, such as clays, yard soil, and flower­pot 

soil. Researchers in many different disciplines have 

hypothesized motivations for human soil­pica or 

geophagy behavior, including alleviating nutritional 

deficiencies, a desire to remove toxins or self­medicate, 

and other physiological or cultural influences (e.g., 

Danford, 1982). Bruhn and Pangborn (1971) and 

Harris and Harper (1997) suggest a religious context for 

certain geophagy or soil ingestion practices. Some 

researchers have investigated subpopulations of 

children who may be more likely than other children to 

exhibit soil­pica behavior on a recurring basis. These 

subpopulations might include 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 soil­pica and geophagy 

subpopulations remains difficult due to limited research 

on this topic. 

In this handbook, soil, indoor settled and 

outdoor settled dust, and dust ingestion are defined 

generally as: 

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 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 is 

not 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 by 

children. Three methodologies combine biomarker 

measurements with measurements of the biomarker 

substance’s presence in environmental media. A fourth 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

methodology offers indirect evidence of soil/dust 

ingestion behaviors from the responses of caregivers 

and/or children to survey questions. 

The first of the biomarker methodologies 

measures quantities of specific elements present in 

children’s 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 (e.g., 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 children’s 

blood lead levels, with biomarker measurements of lead 

in children’s blood (e.g., 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. The third biomarker 

methodology, the “lead isotope ratio” methodology, 

involves measurements of different lead isotopes in 

children’s 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 (e.g., Manton et al., 

2000). In the fourth, “survey response” methodology, 

responses to survey questions regarding soil and dust 

ingestion are analyzed. This methodology includes 

questions asked of children directly, or their caregivers, 

about soil and dust ingestion behaviors, frequency, and 

sometimes quantity (e.g., Barltrop, 1966). 

Although not directly evaluated in this chapter, 

a fifth methodology uses assumptions regarding 

ingested quantities of soil and dust that are based on 

general knowledge of children’s behavior, and 

potentially supplemented or informed by data from 

other methodologies (e.g., Hawley, 1985; Kissel et al., 

1998; Wong et al., 2000). 

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 U.S. EPA for this 

factor. Following the recommendations, key studies on 

soil and dust ingestion are summarized. Summaries of 

the relevant studies, methodology descriptions and 

methodological strengths and limitations are also 

provided. 

5.2 RECOMMENDATIONS

The key studies described in Section 5.3 were 

used to recommend values for soil and dust ingestion 

among children. The key studies pre­dated the age 

groups recommended 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. Due to the current state of research on soil 

and dust ingestion, the upper percentile 

recommendations are called “soil­pica” or “geophagy” 

recommendations that are likely to represent high soil 

ingestion episodes or behaviors at an unknown point on 

the high end of the distribution of soil ingestion. 

The soil ingestion recommendations in Table 

5­1 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. These recommendations are 

called “soil.” The dust ingestion recommendations in 

Table 5­1 include soil tracked into the indoor setting, 

indoor settled dust and air­suspended 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 air­suspended particulate matter that is 

inhaled, subsequently trapped in mucous and moved 

from the respiratory system to the gastrointestinal tract, 

and a soil­origin material located on indoor floor 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

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. 

Table 5­1 shows the central tendency 

recommendations for daily ingestion of soil, dust, or 

soil + dust, in mg/day. It also shows the soil­pica or 

geophagy recommendations for daily ingestion of soil, 

in mg/day. No data are available on which to base 

comparable upper percentile recommendations for 

“dust” or “soil + dust.” Published estimates from the 

key studies have been rounded to one significant figure. 

The recommended central tendency soil + dust 

ingestion estimate for infants from 6 months up to their 

first birthday is 60 mg/day. If an estimate is needed for 

soil only, from outdoor or indoor sources, or both 

outdoor and indoor sources, the recommendation is 30 

mg/day. If an estimate for indoor dust only is needed, 

that would include a certain quantity of tracked­in soil 

from outside, the recommendation is 30 mg/day. The 

confidence rating for this recommendation is low due to 

the small numbers of study subjects in the study on 

which the recommendation is 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 to 12 month 

old children is the same as the central tendency 

assumption for older children (45 percent soil, 55 

percent dust, based on U.S. EPA (1994a)), and the 

assumption that pre­natal or non­soil, non­dust sources 

of lead exposure do not dominate these children’s blood 

lead levels. 

When assessing risks for children who are not 

expected to exhibit soil­pica or geophagy behavior, the 

recommended central tendency soil + dust ingestion 

estimate is 100 mg/day for children ages 1 to <6 years. 

If an estimate for soil only is needed, for exposure to 

soil such as manufactured topsoil or potted­plant 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. If an 

estimate for indoor dust only is needed, the 

recommendation is 60 mg/day. 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. 

When assessing risks for children who may 

exhibit soil­pica behavior, or a group of children that 

includes individual children who may exhibit soil­pica 

behavior, the soil­pica ingestion estimate for children 

up to age 14 ranges from 400 to 41,000 mg/day. Due 

to the definition of soil­pica used in this chapter, that 

sets a lower bound on the quantity referred to as “soilpica” at 1,000 mg/day, and due to the significant 

number of observations in the U.S. tracer element 

studies that are at or exceed that quantity, the 

recommended soil­pica ingestion rate is 1,000 mg/day. 

Currently, no data are available for upper percentile, 

soil­pica behavior for children ages 16 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, soil­pica 

behavior may occur at any age up to <21 years. 

The recommended geophagy soil estimate is 

50,000 mg/day (50 grams). Risk assessors should use 

this value for soil ingestion in areas where residents are 

known to exhibit geophagy behaviors. 

These recommendations are not robust enough 

for use in probabilistic risk assessments. 

Table 5­2 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 

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­3
 
Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

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 bulk densities of surface 

soils are often in the range of 1.3 to 1.7 g/cm3

. U.S. 

EPA (1996) recommends using 1.5 g/cm3 as a default 

value for dry soil bulk density. The central tendency 

recommendation of 50 mg/day, or 0.050 g/day, dry 

weight basis, with a 1.5 g/cm3 bulk density would be 

equivalent to approximately 0.03 cm3

. A teaspoon is 

approximately 5 cm 3 in volume, so the 50 mg/day 

quantity would be roughly equivalent to seven 

thousandths of a teaspoon per day. The 50 g/day 

ingestion rate recommended to represent geophagy 

behavior would be roughly equivalent to 5 to 7 

teaspoons per day in volume. 

Indoor settled dust could be expected to have 

a lower dry bulk density than the surface soil bulk 

density cited above (for example, bulk densities of five 

grain dusts are reported by Parnell et al. (1986) to be 

0.15­0.31 g/cm3

, “specific density” of Danish office 

building dust is reported by Mølhave et al. (2000) to be 

1.0 gm/cm3

). Thus, volumes of indoor settled dust 

could be expected to weigh less than comparable 

volumes of surface soil. The central tendency “dust” 

recommendation for children of 60 mg/day, or 0.060 

g/day, dry weight basis, with a 1.0 g/cm3 bulk density 

would be equivalent to approximately 0.06 cm 3

, or 

roughly equivalent to twelve thousandths of a teaspoon 

per day. 

Page Child­Specific Exposure Factors Handbook
 

5­4 September 2008
 
Table 5­1. Recommended Values for Daily Soil, Dust, and Soil + Dust Ingestion 

Age Group 

Soila b Dust Soil + Dust 

Central Tendency 

(mg/day) 

Upper Percentile 

Central Tendency 

(mg/day) 

Central Tendency 

Soil­Pica Geophagy (mg/day) 

(mg/day) (mg/day) 

6 to <12months 30 ­ ­ 30 60 

1 to <6years 50 1,000 50,000 60 100c 

6 to <21 years 50 1,000 50,000 60 100c 

­

a 

b 

c 

No recommendation. 

Includes soil and outdoor settled dust. 

Includes indoor settled dust only. 

Total soil and dust ingestion rate is 110 mg/day; rounded to one significant figure it is 100 mg/day. 

Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­5
 
Table 5­2. Confidence in Recommendations for Ingestion of Soil and Dust 

General Assessment Factors Rationale Rating 

Soundness

      Adequacy of Approach 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). Four of the 9 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). Thetotal number of 

children in key studies was 1,203 (859 U.S. children, 292 Dutch, and 52 Jamaican 

children), while the target population currently numbers more than 74 million (U.S. 

DOC, 2008). The response rates for in­person 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. 

Low 

      Minimal (or defined) Bias Numerous sources of measurement error exist in the tracer element studies. Biokinetic 

model comparison study may contain less measurement error than tracer element studies. 

Survey response study may contain measurement error. 

Applicability and Utility

      Exposure Factor of Interest 8 of the 9 key studies focused on the soil exposure factor, with no or less focus on the 

dust exposure factor. Biokinetic model comparison study did not focus exclusively on 

soil and dust exposure factors. 

Low 

   Representativeness The study samples may not be representative of the U.S. in terms of race, ethnicity, 

socio­economics, and geographical location; studies focused on specific areas. 

   Currency Studies results are likely to represent current conditions. 

      Data Collection Period Tracer element studies’ data collection periods may not represent long­term behaviors. 

Biokinetic model comparison and survey response studies do represent longer term 

behaviors. 

Clarity and Completeness

   Accessibility Observations for individual children are available for only 3 of the 9 key studies. 

Low 

   Reproducibility For the methodologies used by more than one research group, reproducible results were 

obtained in some instances. Somemethodologies have been used by only one research 

group and have not been reproduced by others. 

      Quality Assurance For some studies, information on quality assurance/quality control was limited or absent. 

Variability and Uncertainty

      Variability in Population Tracer element studies characterized variability among study sample members; 

biokinetic model comparison and survey response studies did not. Day­to­day and 

seasonal variability was not very well characterized. Numerous factors that may 

influence variability have not been explored in detail. 

Low 

      Minimal Uncertainty Estimates are highly uncertain. Tracer element studies’ design appears to introduces 

biases in the results. 

Evaluation and Review

      Peer Review All key studies appeared in peer review journals. 

Medium 

      Number and Agreement

    Studies

of 9 key studies. Researchers using similar methodologies obtained generally similar 

results; somewhat general agreement between researchers using different 

methodologies. 

Overall Rating Low

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Chapter 5 ­ Ingestion of Soil and Dust

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

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. children’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 other studies’ design or 

implementation. 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, non­randomized, 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 

non­randomized 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 re­analyses of data 

previously published. 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 children’s residences 

and/or play areas, and the children’s feces, and 

sometimes also 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 fromnon­soil substances 

(food, medications, and non­food sources such as 

toothpaste) that children might swallow. 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 non­soil 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 by each child is as follows: the quantity of a 

given tracer element, in milligrams, present in the 

child’s feces and urine, minus the quantity of that tracer 

element, in milligrams, present in the child’s food and 

medicine, the result of which is divided by the tracer 

element’s soil concentration, in milligrams of tracer per 

gram of soil, 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 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

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 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 non­food, 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 vs. dust. 

Each child’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 

one of the U.S. research teams (Lásztity et al., 1989) 

has published estimates calculated for pairs of tracer 

elements using simultaneous equations. 

The U.S. tracer element studies have been 

performed for only short­duration study periods, and 

only for 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/Barnes 1990; 64 in 

Calabrese et al., 1997a; and 12 in Calabrese et al., 

1997b). They provide information on quantities of soil 

and dust ingested for the studied groups of children for 

short time periods, but provide limited information on 

overall prevalence of soil ingestion by U.S. 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 children’s soil or dust ingestion 

estimates to be negative, which is not physically 

possible. In some studies, for some of the tracers, so 

many individual children’s “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 children’s measured blood lead levels with 

predictions from the Integrated Exposure and Uptake 

Biokinetic (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 the 

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 Survey Response Methodology

The survey response methodology includes 

studies that survey children’s caretakers, or children 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

themselves, via in­person or mailed surveys that ask 

about mouthing behavior and ingestion of various nonfood items. Sometimes, questions about amounts 

ingested are included in the survey instrument. There 

could be either false positive or false negative responses 

to these questions, for various reasons. 

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; 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 percent) 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. There was no reported geophagy among 25 

adolescent study subjects questioned. The average 

daily amount of clay consumed was reported to be 

about 50 grams, for the 32 adult and 18 under­age­13 

years 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

Soil­Pica Behaviour 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 nonrandom sample of 30 male and 34 female 1, 2 and 3 

year­olds from the greater Amherst, Massachusetts area 

were studied, presumably in 1987. The children were 

predominantly from two­parent households where the 

parents were highly educated. The study was 

conducted over a period of eight days spread over two 

weeks. During each week, duplicate samples of food, 

beverages, medicines, and vitamins were collected on 

Monday through Wednesday, while excreta were 

collected for four 24­hour 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. 

Fecal and urine samples, excluding wipes and toilet 

paper, were also collected and analyzed for tracer 

elements. 

Table 5­3 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. 

Data for the uppermost 23 subject­weeks (the 

highest soil ingestion estimates, averaged over the four 

days of excreta collection during each of the two 

weeks) were published in Calabrese et al. (1991). One 

child’s soil­pica 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 aluminum­based soil ingestion 

estimates were 19 g/day (18,700 mg/day) and 36 g/day 

(35,600 mg/day), silicon­based soil ingestion estimates 

were 20 g/day (20,000 mg/day) and 24 g/day (24,000), 

and simultaneous­equation 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 

5­4), and averaged 6 g/day across the entire study 

period. Additional information about this child’s 

apparent ingestion of soil vs. dust during the study 

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Chapter 5 ­ Ingestion of Soil and Dust

period, shown in Table 5­5, was published in Calabrese 

and Stanek (1992a). 

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 g 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 (Table 5­6). 

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 percent 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 percent 

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 (Table 5­7). 

5.3.2.4	 Davis et al., 1990 ­ Quantitative Estimates of

Soil Ingestion in Normal Children between

the Ages of 2 and 7 Years: Population­based

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 three­city 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 seven 

day period, with four 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 ingested on a daily basis 

was estimated using equation 5­1: 

Si.e=(((DWf+ DWP) x Ef

) + 2Eu) ­ (DWfd x Efd)  (Eq. 5­1) 

Esoil

where: 

Si,e = soil ingested for child i based on 

tracer e (g); 

DWf = feces dry weight (g); 

DWp = feces dry weight on toilet paper (g); 

Ef = tracer concentration in feces (�g/g); 

Eu = tracer amount in urine (�g); 

DWfd = food dry weight (g); 

Efd = tracer concentration in food (�g/g); 

and 

Esoil = tracer concentration in soil (�g/g). 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

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 4­day 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 

(Table 5­8). 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 

silicon­based estimates; residing in one of the three 

cities to be a significant predictor with aluminum­based 

estimates, and washing the face before eating significant 

for titanium­based estimates. 

5.3.2.5	 Calabrese et al. 1997a ­ Soil Ingestion

Estimates for Children Residing on a

Superfund Site

Calabrese et al. (1997a) 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 1­3 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 

over­the­counter medicines and vitamins were collected 

over the seven day period, along with fecal samples. In 

addition, soil and dust samples were collected from the 

children’s home and play areas. Toothpaste containing 

nondetectable 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. 

Calabrese et al. (1997a) estimated soil 

ingestion by each tracer element, as shown in Table 5­9. 

5.3.2.6	 Stanek et al. 1998 ­ Prevalence of Soil

Mouthing/Ingestion among Healthy

Children Aged 1 to 6/Calabrese et al. 1997b ­

SoilIngestionRatesinChildren Identified by

Parental Observation as Likely High Soil

Ingesters

Stanek et al. (1998) conducted a survey 

response study using in­person 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 percent, daily 

mouthing or ingestion of soil and dirt in 4 percent, and 

daily mouthing or ingestion of dust, lint and dustballs in 

1 percent. Parents reported more than weekly mouthing 

or ingestion of sand and stones in 16 percent, more than 

weekly mouthing or ingestion of soil and dirt in 10 

percent, and more than weekly mouthing or ingestion of 

dust, lint and dustballs in 3 percent. Parents reported 

more than monthly mouthing or ingestion of sand and 

stones in 27 percent, more than monthly mouthing or 

ingestion of soil and dirt in 18 percent, and more than 

monthly mouthing or ingestion of dust, lint and 

dustballs in 6 percent. 

Calabrese and colleagues performed a followup tracer element study (Calabrese et al. 1997b) 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 follow­up tracer study 

relative to the original survey response study was not 

stated; the study duration was 7 days. Of the 12 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

children in Calabrese et al. 1997b, one exhibited 

behavior that the authors believed was clearly soil pica; 

Table 5­10 shows estimated soil ingestion rates for this 

child during the study period. Estimated average daily 

soil ingestion estimates (calculated based on soil tracer 

element concentrations only) ranged from ­0.015 to 

+1.783 g/day based on aluminum, ­0.046 to +0.931 

g/day based on silicon, and ­0.047 to +3.581 g/day 

based on titanium. Estimated average daily dust 

ingestion estimates (calculated based on dust tracer 

element concentrations only) ranged from ­0.039 to 

+2.652 g/day based on aluminum, ­0.028 to +3.145 

g/day based on silicon, and ­0.098 to +3.632 g/day 

based on titanium. Calabrese et al. (1997b) 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 12 year period 

prior to tracer element quantification with laboratory 

analysis. 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), and 

were chosen based on high compliance with the 

previous study protocol and expressed willingness to 

participate in a future study. 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 24­hour 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. 

Children’s estimated soil ingestion rates are 

shown in Table 5­11. 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, 

calculated by setting negative estimates to zero. These 

estimates fall within the range of those reported by 

Davis et al., 1990. Similar to the previous Davis et al. 

study, the soil ingestion estimates were the highest for 

titanium. 

Only two of a number of children’s behaviors 

examined for their relationship to soil ingestion were 

found to be associated with increased soil ingestion in 

this study: 

• reported eating of dirt; and 

• hand washing before meals (based on 2 of 12 

children who were reported not to wash hands 

before eating). 

Several typical childhood behaviors, however, 

including thumb­sucking, furniture licking, and carrying 

around a blanket or toy were not associated with 

increased soil ingestion for the participating children. 

When investigating correlations within the same family, 

a child’s soil ingestion rate was not found to be 

associated with either parent’s soil ingestion rate. 

5.3.3	 Key Studies of Secondary Analysis

5.3.3.1	 Wong, 1988 ­ The Role of Environmental

and Host Behavioural 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 fourmonth 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 

percent silicon, or 14.5 mg Si per gram of dry feces. 

This quantity was used to correct measured fecal silicon 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

from dietary sources. Fecal silicon quantities greater 

than 1.45 percent 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 4­month study period, 9 of 84 samples (or 10.5 

percent) yielded soil ingestion estimates in excess of 1 

g/day. 

Of the 52 children studied, 6 had one­day 

estimates of more than 1,000 mg/day. The estimated 

soil ingestion for these six children is shown in Table 5­

12. The article describes 5 of 24 (or 20.8 percent) 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 soilpica behavior on 2, 3, and 4 days, respectively, with the 

most consistent (4 out of 4 days) soil­pica child having 

the highest estimated soil ingestion, 3.8 to 60.7 g/day. 

5.3.3.2	 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, whose 

environmental lead exposures (soil and dust lead levels) 

had been collected as part of public health evaluations 

in these communities. 

The Integrated Exposure and Uptake 

Biokinetic (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 child­specific 

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. 

For Palmerton, Pennsylvania (n=34), the 

community­wide geometric mean measured blood lead 

levels (6.8 ug/dl) were slightly over­predicted by the 

m o d e l ( 7 . 5 u g / d l ) ; f o r s o u t h e a s t e r n 

Kansas/southwestern Missouri (n=111), the blood lead 

levels (5.2 ug/dl) were slightly under­predicted (4.6 

ug/dl), and for Madison County, Illinois (n=333), the 

geometric mean measured blood lead levels matched 

the model predictions (5.9 ug/dl measured and 

predicted), with very slight differences in the 95 percent 

confidence interval. These results suggest that the 

default soil and dust ingestion rates used in this version 

of the IEUBK model (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 residencedwelling children in the three locations studied. 

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 non­soil tracer exposures 

was not as well­developed as the methodology in the 

five U.S. tracer element studies. However, Clausing et 

al. (1987) was used in developing the 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 non­randomized 

design, insufficient information was provided to 

determine important details regarding study design, or 

no data were provided to allow quantitative estimates of 

soil and/or dust ingestion rates. 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

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 test­taking 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	 Cooper, 1957 ­ Present Study

Cooper (1957) conducted a non­randomized 

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. 

5.3.4.3	 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 were contacted for 

in­person caregiver interviews, in which a total of 186 

families (37 percent) participated. A separate stratified 

subsample of 1,000 children was selected for a mailed 

survey, in which 277 (28 percent) of the families 

participated. Interview­obtained data regarding caregiver reports of pica (in this study is defined as placing 

nonfood items in the mouth and swallowing them) 

behavior in all children ages 1 to 6 in the 186 families 

(n=439) indicated 19 had ingested dirt (defined as yard 

dirt, house dust, plant­pot 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 

non­response bias. Interviews were conducted in the 

March/April time frame, presumably in 1964. Mailsurvey 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. 

5.3.4.4	 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 (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 percent (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 percent (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. 

5.3.4.5	 Robischon, 1971 ­ Pica Practice and Other

Hand­Mouth Behavior and Children’s

Developmental Level

A survey response sample of 19­ to 24­month 

old children examined at an urban well­child clinic in 

the late 1960s or 1970 in an unspecified location 

indicated that 48 of the 130 children whose caregivers 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

were interviewed, exhibited pica behavior (defined as 

“ate nonedibles 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 nonedible substance. The soil and dustlike 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 nonedibles less than once a week.” 

5.3.4.6	 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 3­day 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. 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 (5­2): 

Ti,e = fi,e x Fi (Eq. 5­2) 

Si,e

where: 

estimated soil ingestion for child i

based on element e (g/day); 

Ti,e	­ = 

concentration of element e in fecal 

sample of child i (mg/g); 

Fi = fecal dry weight (g/day); and 

fi,e	­ = 

concentration of element e in child i's 

yard soil (mg/g). 

Si,e	­ = 

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 (Table 5­13). 

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. 

5.3.4.7	 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 acid­insoluble 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 5­day 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 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

group, representing children who had very limited 

access to soil; 8 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 

aluminum­based soil ingestion estimates for the school 

children in this study ranged from 23 to 979 mg/day, 

the AIR­based estimates ranged from 48 to 362 mg/day, 

and the titanium­based 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 (Table 5­14). Based on the Limiting Tracer 

Method (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 

aluminum­based soil ingestion estimate was 56 

mg/day; titanium­based 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 (Table 5­15). AIR measurements were not 

reported for the hospitalized children. Using the LTM 

method, the mean soil 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 nonsoil 

source of titanium for some children and a background 

nonsoil 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 nonsoil sources. 

5.3.4.8	 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. Of the 18 women 

who acknowledged practicing pica, 4 acknowledged 

eating “white dirt” (common name for white clay) or 

“red dirt.” Of the 18 women, 9 stated the amount of 

substances that they ingested (which included several 

substances besides white or red dirt). Thus, of the 4 

respondents who acknowledged ingesting white or red 

dirt, an unknown number of them acknowledged 

ingesting 0.5 to 1.0 pounds of dirt or clay per week 

(roughly 200­500 g/week). Of the 9 women who stated 

amounts of substances ingested, 6 stated that their 

ingestion occurred daily and 3 stated that it occurred 

three times per week. The authors found a prevalence 

for the overall pica, by race/ethnicity, of 17.8 percent of 

the black women, 10.6 percent of the white women, and 

0 percent of the Asian and Hispanic women in the 

sample, with no significant differences between pica 

and nonpica groups with respect to age distribution or 

race. 

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 short­term studies’ estimates for long 

term soil and dust ingestion behavior estimates is also 

discussed. 

5.3.5.1	 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 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

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. 

(1997a) (the Anaconda study) and Calabrese et al. 

(1997b) (soil­pica in Massachusetts), and relied only on 

the 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 percent for percentile 95th 

estimates in a 4­day 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 percent 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). 

5.3.5.2	 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 subject­week and 

trace element basis. Calabrese and Stanek (1995) 

identified possible sources of positive errors to be: 

• 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 non­food 

or non­soil source during the study period. 

Possible sources of negative bias were identified as: 

• 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 subject­day estimates); (2) a 

daily soil ingestion rate was estimated for each tracer 

for each 24­hour day a fecal sample was obtained; (3) 

the median tracer­based soil ingestion rate for each 

subject­day was determined; and (4) negative errors due 

to missing fecal samples at the end of the study period 

were also determined. Also, upper­ and lower­bound 

estimates were determined based on criteria formed 

using an assumption of the magnitude of the relative 

standard deviation (RSD) 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 5­16 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 non­negative mean soil ingestion 

rates (Table 5­3) 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. 

5.3.5.3	 Stanek and Calabrese, 1995a ­ Daily

Estimates of Soil Ingestion in Children

Stanek and Calabrese (1995a) presented a 

methodology which links the physical passage of food 

and fecal samples to construct daily soil ingestion 

estimates from daily food and fecal trace­element 

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 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

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 5­17 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 (Table 5­18). 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 

365­day 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 2­week 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. 

5.3.5.4	 Calabrese and Stanek, 1992b ­ What

Proportion of Household Dust is Derived

from Outdoor Soil?

Calabrese and Stanek (1992b) 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 

percent 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). Using 

an assumption that 50 percent of excess fecal tracers 

were from indoor origin and 50 percent were from 

outdoor origin, and multiplying the 50 percent indoororigin excess fecal tracer by the model prediction that 

31.3 percent of indoor dust came from outdoor soil, 

results in an estimate that 15 percent of excess fecal 

tracers were from soil materials that were present in 

indoor dust. Adding this 15 percent to the 50 percent 

assumed outdoor (soil) origin excess fecal tracer 

quantity results in an estimate that approximately 65 

percent of the total residual excess fecal tracer was of 

soil origin (Calabrese and Stanek, 1992b). 

5.3.5.5	 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. (1997a) 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 �m in 

diameter (it was sieved to <2 mm soil particle size in 

Calabrese et al. (1997a)). 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 two­ to fourfold at the 

smaller soil particle size. Soil ingestion estimates for 

these three tracers were decreased by approximately 60 

percent at the 95th percentile compared to the 

Calabrese et al. (1997a) results. 

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5.3.5.6	 Stanek et al., 1999 ­ SoilIngestion Estimates

for Children in Anaconda Using Trace

ElementConcentrationsinDifferentParticle

Size Fractions

Stanek et al. (1999) extends the findings from 

Calabrese et al. (1996) by quantifying trace element 

concentrations in soil based on sieving to particle sizes 

of 100 to 250 �m and to particle sizes of 53 to < 100 

�m. This study used the data from soil concentrations 

from the Anaconda, Montana site reported by Calabrese 

et al. (1997a). Results of the study indicated that soil 

concentrations of aluminum, silicon and titanium do 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 

100­250 �m particle size range when compared with 

the 0 to 2 �m particle size range. There was not a 

significant increase in concentration in the 53 to 100 

�m particle size range. 

5.3.5.7	 Stanek andCalabrese, 1995b ­ SoilIngestion

Estimates for Use in Site Evaluations Based

on the Best Tracer Method

Stanek and Calabrese (1995b) recalculated 

children’s soil ingestion rates from two previous 

studies, using data for 8 tracers from Calabrese et al., 

1989 and 3 tracers from Davis et al., 1990. 

Recalculations were performed using the Best Tracer 

Method (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. 

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 

child, calculated on a per­week (“subject­week”) 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 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 subjectweeks 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. 

5.3.5.8	 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 percent lower 

(Stanek and Calabrese, 2000). 

5.3.5.9	 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 

short­term soil ingestion estimates. This study 

estimated the long­term average soil ingestion 

distribution using daily soil ingestion estimates from 

children who participated in the Anaconda, Montana 

study. In this long­term (annual) distribution, the soil 

ingestion estimates were: mean 31, median 24, 75th 

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Chapter 5 ­ Ingestion of Soil and Dust

percentile 42, 90th percentile 75, and 95th percentile 91 

mg/day. 

5.3.5.10 von Lindern et al., 2003 ­ Assessing remedial

effectivenessthrough 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 non­random sample of several hundred 

children ages 0­9 years in an area of northern Idaho 

from 1989­1998 during community­wide 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 

overpredicted blood lead levels, with the overprediction 

decreasing as the community soil remediation 

progressed. The authors stated that the overprediction 

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 underpredictions 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 percent) than 

neighborhood soils (28 percent) or yard soils (22 

percent) to soil found in house dust of the studied 

children. 

5.4	 LIMITATIONS OF KEY 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 and 

biokinetic model comparison 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. 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 

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. 

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Chapter 5 ­ Ingestion of Soil and Dust

The subsequent U.S. tracer element studies (Calabrese 

et al. (1989)/Barnes (1990), Davis et al. (1990), 

Calabrese et al. (1997a), and Davis and Mirick (2006)) 

made some progress in addressing some of the Binder 

et al. (1986) study’s stated limitations. 

Regarding the issue of non­yard (communitywide) soil as a source of ingested soil, one study 

(Calabrese et al. 1989/Barnes 1990) addressed this 

issue to some extent, by including samples of children’s 

day care center soil in the analysis. Calabrese et al. 

(1997a) attempted to address the issue by excluding 

children in day care 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 threecity area. Stanek et al. (2001a) conclude that there is 

“minimal impact” on estimates of soil ingestion due to 

mis­specifying a child’s play area. 

Regarding the issue of soil and dust both 

contributing to measured tracer element quantities in 

excreta samples, the five key U.S. tracer element 

studies all attempt 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 (e.g., Calabrese and Stanek 

(1992b)). An issue similar to the community­wide soil 

exposures in the previous paragraph could also exist 

with community­wide 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 community­wide indoor dust 

exposures (that due to occupying day care facilities) 

was addressed in the Calabrese et al. (1989)/Barnes 

(1990) study, but not in the other three key tracer 

element studies. In addition, if the key studies’ vacuum 

cleaner collection method for household and day care 

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 four 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. (1997a) 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. 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 five 

key U.S. tracer element studies have all addressed 

dietary (and non­dietary, non­soil) intake by subtracting 

quantitated 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 

non­dietary, non­soil corrections required subtracting 

the tracer element contributions from these non­soil 

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, nonChild­Specific Exposure Factors Handbook Page
 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

dietary non­soil, and soil) and outputs (fecal and urine). 

The gastrointestinal transit time assumption introduced 

a new potential source of bias that some authors (e.g., 

Stanek and Calabrese, 1995a) called input/output 

misalignment or transit time error. This 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. (1997a). 

ICRP (2002) 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 et al., 1990; Calabrese et al., 1989/Barnes 

(1990); Davis and Mirick, 2006). 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) offer another other possible explanation for the 

negative soil and dust ingestion rates estimated for 

some study participants. Because the weights of dried 

food and liquid (input) samples were sufficiently great, 

relative to the urine and fecal (output) samples, 

overestimates in laboratory analytical values for the 

input samples would not be compensated for by a 

similar overestimate in the output 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., 1989 and 1997a studies). Estimates 

based on a particular tracer element with a lower or 

higher recovery than the expected 100 percent 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 percent (e.g., Calabrese et al., 

1989). 

Davis et al. (1990) offered an assessment of 

the impact of swallowed toothpaste on the tracer­based 

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 pre­analyzed for 

its tracer element content, but it is not known to what 

extent the children actually used the supplied 

toothpaste. Similarly, Calabrese et al., 1989 and 1997a 

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 (2002); Shepherd et al. 

(1987); Powell et al. (1996)). Second, gastrointestinal 

uptake of silicon may have occurred, which could bias 

those estimates downward. Evidence of silicon’s role 

in bone formation (e.g., Carlisle (1980)) supported by 

newer research on dietary silicon uptake (Jugdaohsingh 

et al. (2002); Van Dyck et al. (2000)) suggests a 

possible negative bias in the silicon­based 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 (e.g., Dominy et al., 2003; Hooda et 

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Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

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 BiokineticModelComparisonMethodology

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 the 

biokinetic model comparison studies is that there may 

be three 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 under­predict, 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. The 

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 for those children, which could result in either 

upward or downward biases in those children’s 

predicted blood lead levels. Comparing upward­biased 

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. Comparing 

downward­biased 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 were accurate, when in fact the 

children’s soil and dust ingestion rates, or some other 

lead source, were actually lower than the default 

assumption. The 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. 

5.4.3 Survey Response Methodology

Each data collection methodology (in­person 

interview, mailed questionnaire, or questions 

administered in “test” format in a school setting) may 

have had specific limitations. In­person 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 in­person interviews, 

but may allow respondents to respond when they are not 

distracted by childcare duties. An in­school test format 

is more problematic than either interviews or mailed 

surveys, because respondent bias related to teacher 

expectations could influence responses. 

Unweighted survey responses from the 

National Health and Nutrition Examination Survey 

(NHANES) I and II regarding children’s clay and dirt 

ingestion are available (U.S. DHHS 1981a, U.S. DHHS 

1981b, U.S. DHHS 1985a, U.S. DHHS 1985b) and 

appear generally to corroborate the results of the survey 

response studies summarized in this chapter, in that a 

small proportion of respondents acknowledge eating 

dirt or clay. U.S. EPA has undertaken an effort to 

weight the survey responses among adult caregiver 

respondents who acknowledged clay and dirt ingestion 

by children under age 12 years and among child 

respondents ages 12 up to 21 years who acknowledged 

clay and dirt ingestion, to develop an estimate of 

prevalence of the behavior among children. 

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); 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

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 U.S.

Population

The two key studies of Dutch and Jamaican 

children may represent different conditions and 

different study populations than those in the U.S.; thus, 

it is unclear to what extent those children’s soil 

ingestion behaviors may differ from U.S. children’s soil 

ingestion behaviors. 

Limitations regarding the key studies 

performed in the U.S. 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, gender, 

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. (1997a) 

tracer element studies were in locations with soils that 

had sand content ranging from 21­80 percent, silt 

content ranging from 16­71 percent, and clay content 

ranging from 3­20 percent by weight, based on data 

from USDA (2008). The location of children in the 

Calabrese et al. (1997b) study was not specified, but 

due to the original survey response study’s occurrence 

in western Massachusetts, the soil types in the vicinity 

of the Calabrese et al. (1997b) study are likely to be 

similar to those in the Calabrese et al. (1989)/Barnes 

(1990) study. 

The Hogan et al. (1998) study included 

locations in the central part of the U.S. (an area along 

the Kansas/Missouri border, and an area in western 

Illinois) and one in the eastern U.S. (Palmerton, 

Pennsylvania). The only key study conducted in the 

southern part of the U.S. 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 U.S. that experience 

moderate temperatures year­round, 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, 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 five key tracer element studies all took 

place in northern latitudes. The temperature and 

precipitation patterns that occurred during these four 

studies’ data collection periods was difficult to discern 

due to no mention of specific data collection dates in 

the published articles. The Calabrese et al. 

(1989)/Barnes (1990) study apparently took place in 

mid­ to late September 1987 in and near Amherst, 

Massachusetts; Calabrese et al. (1997a) 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 22­60 o

F and 25­48 oF, and daily highs from 53­81 o

F o and 55­88 in Calabrese et al. (1989) and F

Calabrese et al. (1997a), respectively, and daily lows 

from 51­72 o

F and 51 ­ 67 oF, and daily highs from 69­

103 o

F and 80­102 oF in Davis et al. (1990) and Davis 

and Mirick (2006), respectively) (National Climatic 

Data Center, 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. (1997a); precipitation in Kennewick 

and Richland during the data collection periods of 

Davis et al. (1990) was almost nonexistent; there was 

no recorded precipitation in Kennewick or Richland 

during the data collection period for Davis and Mirick 

(2006) (National Climatic Data Center, 2008). 

The key biokinetic model comparison study 

(Hogan et al., 1998) targeted three locations in more 

southerly latitudes (Pennsylvania, southern Illinois, and 

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Chapter 5 ­ Ingestion of Soil and Dust

southern Kansas/Missouri) than the five 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 gender and age 

suggested that males and females were represented 

roughly equally in those studies for which study 

subjects’ gender 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 

et al. (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 (Calabrese 

et al. 1989/Barnes 1990) 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. Self­reported 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 percent), Asian (6.7 percent), 

Hispanic (4.8 percent), Native American (1.0 percent), 

and Other (1.0 percent), and the 91 married or livingas­married respondents identified their spouses as 

White (86.8 percent), Hispanic (7.7 percent), Asian (4.4 

percent), and Other (1.1 percent). Davis and Mirick 

(2006) did not state the race and ethnicity of the followup study participants, who were a subset of the original 

study participants from Davis et al. (1990). For the 

Calabrese et al. (1997a) study in Anaconda, Montana, 

population demographics were not presented in the 

published article. The study sample appeared to have 

been drawn from a door­to­door 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 

percent were identified as white and the remaining 2.6 

percent were identified as native American, black, 

Asian and Hispanic (Hwang et al., 1997). The 64 

children in the Calabrese et al. (1997a) study apparently 

were a stratified random sample drawn from the 642 

children identified in the door­to­door census. 

Presumably these children identified as similar races 

and ethnicities to the Hwang et al. (1997) study 

children. The Calabrese et al. (1997b) study indicated 

that 11 of the 12 children studied were white. 

5.5	 SUMMARY OF SOIL AND DUST

INGESTION ESTIMATES FROM KEY

STUDIES

Table 5­19 summarizes the soil and dust 

ingestion estimates from the 9 key studies. 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 suggested different variations on these 

algorithms, or suggest adjustments that should be made 

for various reasons. However, because individual 

observations were not available from the studies with 

reanalyzed data, those reanalyzed estimates were not 

included in the summary table. Other reanalyses 

suggested 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 child’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 

soil­pica ingestion estimates from the tracer element 

studies were consistent with the estimated mean soil 

ingestion from the survey response study of geophagy 

behavior. Also note that 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. 

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Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

5.6	 REFERENCES FOR CHAPTER 5

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Chapter 5 ­ Ingestion of Soil and Dust

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Table 5­3. 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 

Barium 

 soil 

 dust 

 soil/dust 

combined 

Manganese 

 soil 

 dust 

 soil/dust 

combined 

Silicon 

 soil 

 dust 

 soil/dust 

combined 

Vanadium 

 soil 

 dust 

 soil//dust 

combined 

Yttrium 

 soil 

 dust 

 soil/dust 

combined 

Zirconium 

 soil 

 dust 

 soil/dust 

combined 

Titanium 

 soil 

 dust 

 soil/dust 

combined

64 

64 

64 

64 

64 

64 

64 

64 

64 

64 

64 

64 

62 

64 

62 

62 

64 

62 

62 

64 

62 

64 

64 

64 

153 

317 

154 

32 

31 

29 

­294 

­1,289 

­496 

154 

964 

483 

459 

453 

456 

85 

62 

65 

21 

27 

23 

218 

163 

170 

29 

31 

30 

­37 

­18 

­19 

­261 

­340 

­340 

40 

49 

49 

96 

127 

123 

9 

15 

11 

16 

12 

11 

55 

28 

30 

852 

1,272 

629 

1,002 

860 

868 

1,266 

9,087 

1,974 

693 

6,848 

3,105 

1,037 

1,005 

1,013 

890 

687 

717 

209 

133 

138 

1,150 

659 

691 

223 

506 

478 

283 

337 

331 

788 

2,916 

3,174 

276 

692 

653 

1,903 

1,918 

1,783 

106 

169 

159 

110 

160 

159 

1,432 

1,266 

1,059 

6,837 

8,462 

4,929 

6,773 

5,480 

5,626 

7,281 

20,575 

4,189 

5,549 

54,870 

24,900 

5,676 

6,782 

6,736 

6,736 

5,096 

5,269 

1,391 

789 

838 

6,707 

3,354 

3,597 

SD 

Source: 

= Standard deviation. 

Calabrese et al., 1989. 

Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­31
 
Table 5­4. Amherst, Massachusetts Soil­Pica 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. 

Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

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Chapter 5 ­ Ingestion of Soil and Dust

Table 5­5. Amherst, Massachusetts Soil­Pica Child’s Tracer Ratios 

Tracer Pairs 

Ratio 

Soil Fecal Dust 

Estimated Residual Fecal 

Tracers of Soil Origin as 

Predicted by Specific 

Tracer Ratios (%) 

1. Mn/Ti 

2. Ba/Ti 

3. Si/Ti 

4. V/Ti 

5. Ai/Ti 

6. Y/Ti 

7. Mn/Y 

8. Ba/Y 

9. Si/Y 

10. V/Y 

11. Al/Y 

12. Mn/Al 

13. Ba/Al 

14. Si/Al 

15. V/Al 

16. Si/V 

17. Mn/Si 

18. Ba/Si 

19. Mn/Ba 

208.368 

187.448 

148.117 

14.603 

18.410 

8.577 

24.293 

21.854 

17.268 

1.702 

2.146 

11.318 

10.182 

8.045 

0.793 

10.143 

1.407 

1.266 

1.112 

215.241 

206.191 

136.662 

10.261 

21.087 

9.621 

22.373 

21.432 

14.205 

1.067 

2.192 

10.207 

9.778 

6.481 

0.487 

13.318 

1.575 

1.509 

1.044 

260.126 

115.837 

7.490 

17.887 

13.326 

5.669 

45.882 

20.432 

1.321 

3.155 

2.351 

19.520 

8.692 

0.562 

1.342 

0.419 

34.732 

15.466 

2.246 

87 

100 

92 

100 

100 

100 

100 

71 

81 

100 

88 

100 

73 

81 

100 

100 

99 

83 

100 

Source: Calabrese and Stanek, 1992. 

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­33
 
Table 5­6. Van Wïjnen et al., 1990 Limiting Tracer Method (LTM) Soil Ingestion Estimates for Sample of Dutch Children 

Age (years) Sex 

Daycare Centers Campgrounds 

N GM LTM 

(mg/day) 

GSD LTM 

(mg/day) N GM LTM (mg/day) 

GSD LTM 

(mg/day) 

Birth to <1 

1 to <2 

2 to <3 

3 to <4 

4 to <5 

All girls 

All boys 

Total 

Girls 

Boys 

Girls 

Boys 

Girls 

Boys 

Girls 

Boys 

Girls 

Boys 

3 

1 

20 

17 

34 

17 

26 

29 

1 

4 

86 

72 

162a 

81 

75 

124 

114 

118 

96 

111 

110 

180 

99 

117 

104 

111 

1.09 

­

1.87 

1.47 

1.74 

1.53 

1.57 

1.32 

­

1.62 

1.70 

1.46 

1.60 

NA 

NA 

3 

5 

4 

8 

6 

8 

19 

18 

36 

42 

78b 

NA 

NA 

207 

312 

367 

232 

164 

148 

164 

136 

179 

169 

174 

NA 

NA 

1.99 

2.58 

2.44 

2.15 

1.27 

1.42 

1.48 

1.30 

1.67 

1.79 

1.73 

a 

b 

N 

GM 

LTM 

GSD 

NA 

Source: 

Age and/or sex not registered for 8 children; one untransformed value = 0. 

Age not registered for 7 children; geometric mean LTM value = 140. 

= Number of subjects. 

= Geometric mean. 

= Limiting tracer method. 

= Geometric standard deviation. 

= Not available. 

Adapted from Van Wïjnen et al., 1990. 

Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

Page Child­Specific Exposure Factors Handbook
 

5­34 September 2008
 
Table 5­7. Estimated Geometric Mean Limiting Tracer Method (LTM) Values of Children Attending Daycare Centers 

According to Age, Weather Category, and Sampling Period 

Weather Category Age (years) 

First Sampling Period Second Sampling Period 

N

Estimated 

Geometric Mean 

LTM Value 

(mg/day) 

Estimated 

Geometric Mean 

N LTM Value 

(mg/day) 

Bad 

(>4 days/week 

precipitation) 

Reasonable 

(2­3 days/week 

precipitation) 

Good 

(<2 days/week 

precipitation) 

<1 

1 to <2 

2 to <3 

4 to <5 

<1 

1 to <2 

2 to <3 

3 to <4 

4 to <5 

<1 

1 to <2 

2 to <3 

3 to <4 

4 to <5 

3

18 

33 

5 

4 

42 

65 

67 

10 

94 

103 

109 

124 

102 

229 

166 

138 

132 

3

33 

48 

6 

1 

10 

13 

19 

1 

67 

80 

91 

109 

61 

96 

99 

94 

61 

N 

LTM 

Source: 

= Number of subjects. 

= Limiting tracer method. 

Van Wïjnen et al., 1990. 

 

 

 

 

 

 

 

 

 

Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

Table 5­8. Estimated Soil Ingestion for Sample of Washington State Children a 

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 non­soil 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. 

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­35
 
Table 5­9. Soil Ingestion Estimates for 64 Anaconda Children 

Estimated Soil Ingestion (mg/day) 

Tracer 

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 

P = Percentile. 

SD = Standard deviation. 

Note: Negative values are a result of limitations in the methodology.

Source: Calabrese et al., 1997a. 

 

 

Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

Table 5­10. Soil Ingestion Estimates for Massachusetts Child Displaying Soil Pica Behavior (mg/day) 

Study day Al­based estimate Si­based estimate Ti­based estimate 

1 53 9 153 

2 7,253 2,704 5,437 

3 2,755 1,841 2,007 

4 725 573 801 

5 5 12 21 

6 1,452 1,393 794 

7 238 92 84 

Source: Calabrese et al., 1997b. 

Page Child­Specific Exposure Factors Handbook
 

5­36 September 2008
 
Table 5­11. Soil Ingestion Estimates for Sample of 12 Washington State Children a 

 TracerElement 

Estimated Soil Ingestion 

(mg/day) 

b 

Mean Median SD Maximum 

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 

a 

b 

SD 

For some study participants, estimated soil ingestion resulted in a negative value. 

for tabulation and analysis. 

Results based on 12 children with complete food, excreta and soil data. 

= Standard deviation. 

 These estimates have been set to zero mg/day 

Source: Davis and Mirick, 2006. 

Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­37
 
Table 5­12. Estimated Soil Ingestion for Six High Soil Ingesting Jamaican Children 

Child Month Estimated soil ingestion (mg/day) 

11 

12 

14 

18 

22 

27 

1 

2 

3 

4 

1 

2 

3 

4 

1 

2 

3 

4 

1 

2 

3 

4 

1 

2 

3 

4 

1 

2 

3 

4 

55 

1,447 

22 

40 

0 

0 

7,924 

192 

1,016 

464 

2,690 

898 

30 

10,343 

4,222 

1,404 

0 

­

5,341 

0 

48,314 

60,692 

51,422 

3,782 

­

Source: 

= No data. 

Calabrese and Stanek, 1993. 

Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

Page Child­Specific Exposure Factors Handbook
 

5­38 September 2008
 
 

 

 

 

 

 

Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

Table 5­13. 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 181 121 203 25­1,324 584 

Silicon 184 136 175 31­799 578 

Titanium 1,834 618 3,091 4­17,076 9,590 

Minimum 108 88 121 4­708 386 

128 

130 

401 

65 

Source: Binder et al., 1986. 

Table 5­14. 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 

­

2 L5 

L13 

L27 

131 

184 

142 

­

103 

81 

71 

82 

84 

3 L2 

L17 

124 

670 

42 

566 

84 

174 

4 L4 

L11 

246 

2,990 

62 

65 

145 

139 

5 L8 

L21 

293 

313 

­

­

108 

152 

6 L12 

L16 

1,110 

176 

693 

­

362 

145 

7 L18 

L22 

11,620 

11,320 

­

77 

120 

­

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 

­

­

Arithmetic Mean 1,431 232 129 

103 

154 

23 

71 

82 

81 

42 

174 

62 

65 

108 

152 

362 

145 

120 

77 

82 

111 

124 

95 

106 

48 

71 

212 

51 

64 

56 

105 

­ = No data. 

Source: Adapted from Clausing et al., 1987. 

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­39
 
Table 5­15. 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 

2 

3 

4 

5 

6 

Arithmetic Mean 

G5 

G6 

G1 

G2 

G8 

G3 

G4 

G7 

3,290 

4,790 

28 

6,570 

2,480 

28 

1,100 

58 

2,293 

57 

71 

26 

94 

57 

77 

30 

38 

56 

57 

71 

26 

84 

57 

28 

30 

38 

49 

Source: Adapted from Clausing et al., 1987. 

Table 5­16. Positive/negative Error (Bias) in Soil Ingestion Estimates in Calabrese et al. (1989) Study: 
­

Effect on Mean Soil Ingestion Estimate (mg/day) a
­

Tracer 

Negative Error 

Lack of Fecal 

Sample on 

Final Study 

Day 

b Other Causes

Total 

Negative 

Error 

Total Positive 

Error Net Error Original Mean 

Adjusted 

Mean 

Aluminum 

Silicon 

Titanium 

Vanadium 

Yttrium 

Zirconium 

14 

15 

82 

66 

8 

6 

11 

6 

187 

55 

26 

91 

25 

21 

269 

121 

34 

97 

43 

41 

282 

432 

22 

5 

+18 

+20 

+13 

+311 

­12 

­92 

153 

154 

218 

459 

85 

21 

136 

133 

208 

148 

97 

113 

a

b

How to read table: forexample, 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. 

Values indicate impact on mean of 128­subject­weeks in milligrams of soil ingested per day. 

Source: Calabrese and Stanek, 1995. 

Child­Specific Exposure Factors Handbook 

Chapter 5 ­ Ingestion of Soil and Dust

Page Child­Specific Exposure Factors Handbook
 

5­40 September 2008
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

Table 5­17. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64 Childrena (mg/day) 

Type of Estimate Overall A1 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 4­8 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. 

Table 5­18. Estimated Distribution of Individual Mean Daily Soil Ingestion 

Based on Data for 64 Subjects Projected over 365 Daysa 

Range 1 ­ 2,268 mg/db 

50th Percentile (median) 75 mg/d 

90th Percentile 1,190 mg/d 

95th Percentile 1,751 mg/d 

a Based on fitting a log­normal distribution to model daily soil ingestion values. b Subject with pica excluded. 

Source: Stanek and Calabrese, 1995a. 

Child­Specific Exposure Factors Handbook Page
 

September 2008 5­41
 
      

               

     

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child­Specific Exposure Factors Handbook

Chapter 5 ­ Ingestion of Soil and Dust

Table 5­ 19. Summary of Estimates of Soil and Dust Ingestion by Children (0.5­14 years old) from Key Studies (mg/day) 

Sample 

Size 

Age 

(years) 

Ingestion 

medium 

Mean P25 P50 P75 P90 P95 Reference 

292 

101 

64 

12 

64 

478 

140 

52 

0.1 ­ <1 Soil 0 to 30 a NR NR NR NR NR Van Wijnen et 

al., 1990 

1 ­ <5 Soil 0 to 200 a NR NR NR #300 NR 

2­<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 

1­<4 Soil ­294 to +459 NR ­261 to +96 NR 67 to 1,366 106 to 1,903 Calabrese et al., 

1989 

Dust ­1,289 to +964 NR ­340 to +127 NR 91 to 1,700 160 to 2,916 

Soil and Dust ­496 to +483 NR ­340 to +456 NR 89 to 1,701 159 to 3,174 

3­<8 Soil 37 to 207 NR 26 to 47 NR NR NR Davis and 

Mirick, 2006 

1­<4 Soil ­544 to +270 ­582 ­ +65 ­31 to +220 1 to 411 37 to 1,238 69 to 1,378 Calabrese et al., 

1997a 

<1 ­ <7 Soil and Dust 113 NR NR NR NR NR Hogan et al., 

1998 

1 ­ 13+ Soil 50,000 b NR NR NR NR NR Vermeer and 

Frate, 1979 

0.3 ­ 14 Soil NR NR NR NR ~1,267 ~4,000 Wong 

(1988)/Calabres 

e and Stanek 

(1993) 

a 

b 

NR 

Geometric mean. 

Average includes adults and children. 

= Not reported. 

Page Child­Specific Exposure Factors Handbook
 

5­42 September 2008
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

6 INHALATION RATES 

6.1 INTRODUCTION 

Ambient and indoor air are potential sources 

of children’s exposure to toxic substances. Children 

can be exposed to contaminated air during a variety of 

activities in different environments. Children may be 

exposed due to sources that contribute pollution to 

ambient air. Children may also inhale chemicals from 

the indoor use of various consumer products. Due to 

their size, physiology, 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 per unit of body 

weight that requires cooling. For example, the oxygen 

consumption rate for a resting infant between one week 

and one 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 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. 

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 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). 

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. 

Children’s inhalation dosimetry and health 

effects were topics of discussion at a U.S. EPA 

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 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. Thus, the deposition of particles in the lower 

respiratory tract may be greater (Foos et al., 2008). 

Inclusion of this chapter in the Child-Specific 

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. 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 reference concentrations can be 

found in two methods manuals produced by the Agency 

(U.S. EPA, 1992; 1994). 

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, 2008). The current 

methodology recommends that risk assessors use the 

concentration of the chemical in air as the exposure 

Child-Specific Exposure Factors Handbook Page 

September 2008 6-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

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). 

Recommended inhalation rates (both long- and 

short-term) are provided in the next section, along with 

the confidence ratings for these recommendations. 

These recommendations are based on four key studies 

identified by U.S. EPA for this factor. Long-term 

exposure 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 

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 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 children 

are based on four recent studies: Brochu et al., 2006; 

U.S. EPA, 2006; Arcus-Arth and Blaisdell, 2007; and 

Stifelman, 2007. These studies represent an 

improvement upon those previously used for 

recommended inhalation rates in 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. The 

recommended long-term values for children (including 

infants) for use in various exposure scenarios are 

presented in Table 6-1 for the standard U.S. EPA 

childhood age groups used in this handbook. As 

shown in Table 6-1, the daily average inhalation rates 

for long-term exposures for male and female children 

combined (unadjusted for body weight) range from 3.6 

m3

/day for children from birth to <1 month to 16.5 

m3

/day for children aged 16 to <21 years. These values 

represent averages of the inhalation rate data from the 

four key studies. The 95th percentile values range from 

7.1 m3

/day to 27.6 m3/day for the same age categories. 

The 95th percentile values represent averages of the 

inhalation rate data from the three key studies for which 

95th percentile values were available for selected age 

groups (Brochu et al., 2006; U.S. EPA, 2006; ArcusArth and Blaisdell, 2007). It should be noted that there 

may be a high degree of uncertainty associated with the 

upper percentiles. These values equate to unusually 

high estimates of caloric intake per day, and are 

unlikely to be representative of the average child. For 

example, using Layton’s equation (Layton, 1993) for 

estimating metabolically consistent inhalation rates to 

calculate caloric equivalence (see Section 6.4.6), the 

95th percentile value for 16 to <21 year old children is 

4,840 kcal/day. All of the 95th percentile values listed 

in Table 6-1 may 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 children. These values should be 

used with caution when estimating long-term exposures. 

For short-term exposures for children aged 21 

years and under, for which activity patterns are known, 

mean and 95th percentile data are provided in Table 6-2 

for males and females combined, in m3

/minute. 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, 2006). 

The confidence ratings for the inhalation rate 

recommendations are shown in Table 6-3. Multiple 

percentiles for long- and short-term inhalation rates for 

both males and females are provided in Tables 6-5 

through 6-11 and Table 6-16. 

Page Child-Specific Exposure Factors Handbook 

6-2 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-1. Recommended Long-Term Exposure (More Than 30 Days) Values for Inhalation 

(Males and Females Combined). 

Age Group Mean 

m3

/day 

Sources Used 

for Means 

95th Percentile 

m3

/day 

Sources Used 

for 95th Percentiles Multiple Percentiles 

Birth to <1 month 3.6 a 7.1 a 

See Tables 6-5 

through 6-11 and 6-16 

1 to <3 months - b - - -

3 to <6 months 4.1 a,c 6.1 a,c 

6 to <12 months 5.4 a,c 8.1 a,c 

1 to <2 years 8.0 a,c,d,e 12.8 a,c,d 

2 to <3 years 9.5 a,d,e 15.9 a,d 

3 to <6 years 10.9 a,d,e 16.2 a,d 

6 to <11 years 12.4 a,d,e 18.7 a,d 

11 to <16 years 15.1 a,d,e 23.5 a,d 

16 to <21 years 16.5 a,d,e 27.6 a,d 

a Arcus-Arth and Blaisdell, 2007. b No data for this age group. c Brochu et al., 2006. d U.S. EPA, 2006. e Stifelman, 2007. 

Note: Some 95th percentile values may be unusually high, and may not be representative of the average child. 

Child-Specific Exposure Factors Handbook Page 

September 2008 6-3 
Table 6-2. Recommended Short-Term Exposure (Less Than 30 Days) Values for Inhalation 

(Males and Females Combined) 

Activity Level Age Group 

years 

Mean 

m3

/minute 

95th Percentile 

m3

/minute Multiple Percentiles 

Sleep or Nap 

Sedentary/ 

Passive 

Light Intensity 

Moderate Intensity 

High Intensity 

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 

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 

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 

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 

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 

3.0E-03 

4.5E-03 

4.6E-03 

4.3E-03 

4.5E-03 

5.0E-03 

4.9E-03 

3.1E-03 

4.7E-03 

4.8E-03 

4.5E-03 

4.8E-03 

5.4E-03 

5.3E-03 

7.6E-03 

1.2E-02 

1.2E-02 

1.1E-02 

1.1E-02 

1.3E-02 

1.2E-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 

3.8E-02 

3.9E-02 

3.7E-02 

4.2E-02 

4.9E-02 

4.9E-02 

4.6E-03 

6.4E-03 

6.4E-03 

5.8E-03 

6.3E-03 

7.4E-03 

7.1E-03 

4.7E-03 

6.5E-03 

6.5E-03 

5.8E-03 

6.4E-03 

7.5E-03 

7.2E-03 

1.1E-02 

1.6E-02 

1.6E-02 

1.4E-02 

1.5E-02 

1.7E-02 

1.6E-02 

2.2E-02 

2.9E-02 

2.9E-02 

2.7E-02 

2.9E-02 

3.4E-02 

3.7E-02 

4.1E-02 

5.2E-02 

5.3E-02 

4.8E-02 

5.9E-02 

7.0E-02 

7.3E-02 

See Tables 6-11 and 6-12 

Source: U.S. EPA, 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Page Child-Specific Exposure Factors Handbook 

6-4 September 2008 
Table 6-3. Confidence in Recommendations for Inhalation Rates 

General Assessment Factors Rationale Rating 

Soundness Medium 

 Adequacy of Approach The survey methodology and data analysis was adequate. 

 Measurements were made by indirect methods. The 

 studies analyzed existing primary data. 

 

 Minimal (or defined) Bias Potential bias within thestudies was fairly well 

 documented. 

Applicability and Utility 

 Exposure Factor of Interest The studies focused on inhalation rates and factors 

High 

influencing them. 

 

 Representativeness The studies focused on the U.S. population. Awide 

range of age groups were included. 

 

 Currency The studies were published during 2006 and 2007 and 

represent current exposure conditions. 

 

 DataCollection Period The data collection period for the studies may not be 

representative of long-term exposures. 

Clarity and Completeness 

 Accessibility All key studies are available from the peer reviewed 

Medium 

literature. 

 

 Reproducibility The methodologies were clearly presented; enough 

information was included to reproduce most results. 

 

 Quality Assurance Information on ensuring data quality in the key studies 

was limited. 

Variability and Uncertainty 

 Variability in Population In general, the key studies addressed variability in 

Medium 

inhalation rates based on age and activity level. 

However, other factors that may affect inhalation rates 

(e.g., weight, body mass index [BMI], ethnicity) are not 

discussed. 

 Uncertainty 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. 

Evaluation and Review High 

 Peer Review Three of the key studies appeared in peer reviewed 

journals, and one key study is a U.S. EPA peer reviewed 

 report. 

 Number and Agreement of Studies There are four key studies. Theresults of studies from 

different researchers are in general agreement. 

Overall Rating Medium 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Child-Specific Exposure Factors Handbook Page 

September 2008 6-5 
 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

6.3	 KEY INHALATION RATE STUDIES 

6.3.1	 Brochu et al., 2006 - 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. (2006) calculated physiological 

daily inhalation rates (PDIR) 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-isotoperatio 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 that 

of 18O represents water output plus carbon dioxide 

(CO2) production rates. The CO2 production rate is 

then calculated by 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) x H x 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. (2006) calculated daily inhalation 

rates (expressed in m3

/day and m3/kg-day) for a variety 

of age groups and physiological conditions. 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. Only the data for 

children are presented in this handbook. 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. 

Mean inhalation rates for newborns are 

presented in Table 6-4. Due to the insufficient number 

of subjects, no distributions were derived for this group. 

The distribution of daily inhalation rates for normalweight and overweight/obese individuals by gender and 

age groups are presented in Tables 6-5 to 6-9. 

An advantage of this study is that data are 

provided for age groups of less than one year. A 

limitation of this study is that data for individuals with 

pre-existing medical conditions was lacking. 

6.3.2	 U.S. EPA, 2006 - Metabolically-derived 

Human Ventilation Rates: A Revised 

Approach Based Upon Oxygen 

Consumption Rates 

U.S. EPA (2006) 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 ventilatory equivalent (VQ) and a 

linear relationship between oxygen consumption and 

fitness rate. A revised approach, developed by U.S. 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

fitness rate. A revised approach, developed by U.S. 

EPA’s National Exposure Research Laboratory 

(NERL), 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 (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 basal metabolic 

rate (BMR). 

NHANES provided age, gender, and body 

weight data for 19,022 individuals from throughout the 

United States. From these data, basal metabolic rate 

(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 

United States 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 are 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 into 

age categories using the standardized age categories 

presented elsewhere in this handbook, with the 

exception that children under the age of one year were 

placed into a single 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 gender 

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 energy expenditure (EE) by multiplying the METS 

by the basal metabolic rate (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 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 gender. 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 gender and age categories. 

Data from this study are presented in Tables 6­

10 through 6-15. Tables 6-10 and 6-11 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 6-12 presents the 

mean and 95th percentile values for males, females, and 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

males and females combined. Tables 6-13 and 6-14 

present, for male and female subjects, respectively, 

mean ventilation rates by age category on a volumetric 

(m3

/min) and body-weight adjusted (m3/min-kg) basis 

for the five different activity level ranges described 

above. Table 6-15 presents 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 datasets used, NHAPS and 

NHANES, are representative of the U.S. general 

population. Limitations are that the NHAPS data are 10 

years old, there is variability in the 24-hour activity, and 

there is uncertainty in the METs randomization, all of 

which were noted by the authors. 

6.3.3	 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 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 equation developed by Layton (1993) to 

calculate energy-dependent inhalation rates (see 

Equation 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 noninfant 

children, respectively, using the 1977-1978 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 

ears. 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. Twoday-averaged daily energy intake (EI) values reported 

in the CSFII data set were used 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 underreporting 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 

nonnormalized (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-month age groups for infants, oneyear age groups for children 1-18 years of age, and the 

age groups recommended by U.S. EPA cancer 

guidelines supplement (U.S. EPA, 2005) 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 9-18 

years (Table 6-16). For each age and age-gender 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 

nonnormalized 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 6-16 in units of m3

/day. 

There were statistical differences between boys and 

girls 9-18 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 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

increasing age. Table 6-17 presents the mean and 95th 

percentile values for males and females combined, 

averaged to fit within the standard 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 doubly labeled water (DLW) 

technique EE data that had been coupled with the 

Layton (1993) method. The infants’ CSFII-derived 

breathing rates were 15 to 27 percent greater than the 

comparison DLW EE breathing rates while the 

children’s CSFII rates ranged from 23 percent less to 14 

percent greater than comparison rates. Thus, the CSFII 

and comparison rates were quite 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 underreport food intakes. In addition, 

adolescents who misreport food intake may have also 

misreported body weights. 

6.3.4	 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 

(FAO). Stifelman (2007) used the equation of Layton 

(1993) to convert the recommended energy levels of 

IOM for the active-very active people to their 

equivalent inhalation rates. The IOM reports 

recommend energy expenditure levels organized by 

gender, age and body size (Stifelman, 2007). 

The equivalent inhalation rates are shown in 

Table 6-18. Shown in Table 6-19 are the mean and 95th 

percentile values for the IOM “active” energy level 

category, averaged to fit within the standard 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), 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. 

6.3.5	 Key Studies Combined 

In order to provide the recommended longterm inhalation rates shown in Table 6-1, data from the 

four key studies were combined. The data from each 

study were averaged by gender and grouped according 

to the standard U.S. EPA childhood age groups used in 

this handbook, when possible. Mean and 95th percentile 

inhalation rate values for the four key studies are shown 

in Tables 6-20 and 6-21, respectively. 

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 children (10 years old), infants (1 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

year old), and newborn babies by using a time-activityventilation 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 (Table 6-22). ICRP (1981) compiled 

reference values (Table 6-23) of minute 

volume/inhalation rates from various literature sources. 

ICRP (1981) assumed that the daily activities of a 

reference child (10 yrs) consisted of 8 hours of rest and 

16 hours of light 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 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 (Table 6-22). 

A limitation associated with this study is that 

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/gender 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 Assessments 

The U.S. EPA (1985) compiled measured 

values of minute ventilation for various age/gender 

cohorts from early studies. The data compiled by the 

U.S. EPA (1985) for each age/gender cohorts were 

obtained at various activity levels (Table 6-24). 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 6-24 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 6-24. Table 6-24 indicates that at 

rest, the mean inhalation rate for children, ages 6 and 10 

years, is 0.4 m3

/hr. Table 6-25 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 Tables 6-24 and 6-25, a daily inhalation 

rate was calculated for adults and children by using a 

time-activity-ventilation approach. These data are 

presented for children in Table 6-26. The average daily 

inhalation rate for 6 and 10 years 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 children. 

6.4.3	 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" 

subpopulation groups exposed to ozone in their daily 

activities in the Los Angeles area. The population 

surveyed consisted of several panels of children. The 

panels included Panel 2: 17 healthy elementary school 

students (5 males and 12 females, ages 10-12 years); 

Panel 3: 19 healthy high school students (7 males and 

12 females, ages 13-17 years); Panel 6: 13 young 

asthmatics (7 males and 6 females, ages 11-16 years). 

An initial calibration test was conducted, 

followed by a training session. Finally, a field study 

that involved the subjects collecting their own heart 

rates and diary data was conducted. During the 

calibration tests, ventilation rate (VR), breathing rate, 

and heart rate (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 recorded in 

diaries their daily activities, change in locations 

(indoors, outdoors, or in a vehicle), self-estimated 

breathing rates during each activity/location, and time 

spent at each activity/location. Healthy subjects 

recorded their HR once every 60 seconds using a Heart 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

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 6-27 presents the calibration 

and field protocols for self-monitoring of activities for 

each subject panel. 

Table 6-28 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 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 (Table 6-28). 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 subpopulation 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 both healthy and asthmatic children. 

6.4.4	 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 selfestimated 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 presented in Table 6-29 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 (Table 6-30). 

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. These data 

are useful in estimating exposure for the younger 

population. 

6.4.5	 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/gender 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 

and oxygen consumption. A total of 160 subjects 

participated in the primary study. For children, there 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

were two age-dependent groups: children 6 to 12.9 

years old and adolescents 13 to18.9 years old. 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 (breathing frequency), 

and VO2 (oxygen consumption). 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; most protocols were 

conducted for 30 minutes. All the active field protocols 

were conducted twice. Results are shown in Tables 6­

31 and 6-32. 

During all activities in either the laboratory or 

field protocols, VR for the children’s group revealed no 

significant gender differences. Therefore, VR data 

presented in Tables 6-33 and 6-34 were categorized by 

activity type (lying, sitting, standing, walking, and 

running) for young children and children without regard 

to gender. These categorized data from Tables 6-33 

and 6-32 are summarized as inhalation rates in Tables 

6-31 and 6-32. The laboratory protocols are shown in 

Table 6-31. Table 6-32 presents the mean inhalation 

rates by group and for moderate activity levels in field 

protocols. Data were not provided for the light and 

sedentary activities because the group did not perform 

for this protocol or the number of subjects was too 

small for appropriate comparisons. Accurate 

predictions of inhalation rates across all population 

groups and activity types were obtained by including 

body surface area (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) x Weight (0.425) x 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/gender cohorts. The estimated rates were based on 

short-term data and may not reflect long-term patterns. 

6.4.6	 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: 

where: 

VE =	 ventilation rate (m3

/min or 

m3

/day); 

E =	 energy expenditure rate; 

[kilojoules/minute (KJ/min) or 

megajoules/hour (MJ/hr)]; 

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

/min) to oxygen uptake 

(m3

/min)) unitless. 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Layton (1993) used two alternative approaches 

to estimate daily chronic (long term) inhalation rates for 

different age/gender cohorts of the U.S. population 

using this methodology. 

First Approach 

Inhalation rates were estimated by multiplying 

average daily food energy intakes for different 

age/gender cohorts, H, and VQ, as shown in the 

equation above. The average food energy intake data 

(Table 6-35) are based on approximately 30,000 

individuals and were obtained from the 1977-78 

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 1977-78 

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 footnote (a) of Table 6-36. Table 6-37 

presents the daily inhalation rate for each age/gender 

cohort. 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. Inhalation 

rates were also calculated for active and inactive 

periods for the various age/gender 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 is presented as F in Table 6­

36. These data for active and inactive inhalation rates 

are also presented in Table 6-36. 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. 

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/gender cohorts. The statistical data used to 

develop the regression equations are presented in Table 

6-37. The data obtained from the second approach are 

presented in Table 6-38. Inhalation rates for children 

(6 months - 10 years) ranged from 7.3 to 9.3 m3

/day for 

male and 5.6 to 8.6 m3

/day for female children; for 

older children (10 to 18 years), inhalation rates were 15 

m3

/day for males and 12 m3/day for females. 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. 

Inhalation rates were also obtained for shortterm exposures for various age/gender cohorts and five 

energy-expenditure categories (rest, sedentary, light, 

moderate, and heavy). BMRs were multiplied by the 

product of the metabolic equivalent, H, and VQ. The 

data obtained for short-term exposures are presented in 

Table 6-39. 

This study obtained similar results using two 

different approaches. The major strengths of this study 

are that it estimates inhalation rates in different age 

groups and that the populations are large. 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 populations were used in 

each approach, which may have introduced error. 

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Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

6.4.7	 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 disease were 

included in the study. Of the 618, a total of 309 were in 

good health and were observed in day care 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) (Table 6­

40). The children were assessed for one year in order to 

determine the repeatability of the recordings, to 

compare respiratoryrate 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. Figures 6-1 

and 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. 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. 

6.4.8	 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 models (PBPK). 

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 were the parameter values for an individual 

are correlated with one another and capture 

interindividual variation in populations of a specific 

gender, race, and age range. A computer program, 

Physiological Parameters for PBPK Modeling (PPPM 

or P3

M), which is publicly available (The Lifeline 

Group, 2007), was also developed to randomly retrieve 

records from the database for groups of individuals of 

specified age ranges, gender, and ethnicities. Price et 

al. (2003) recommends that output sets be used as 

inputs to Monte Carlo-based PBPK models of 

interindividual variation in dose. 

Page Child-Specific Exposure Factors Handbook 

6-14 September 2008 
Child-Specific Exposure Factors Handbook

Chapter 6 - Inhalation Rates

Child-Specific Exposure Factors Handbook Page

September 2008 6-15

6.5 REFERENCES FOR CHAPTER 6

Adams, W.C. (1993) Measurement of breathing rate

and volume in routinely performed daily

activities, Final Report. California Air

Resources Board (CARB) Contract No.

A033-205.June 1993. 185 pgs. 

Arcus-Arth, A. and Blaisdell, R. J. (2007) Statistical

distributions of daily breathing rates for

narrow age groups of infants and children.

Risk Anal 27(1):97-110

Brochu, P.; Ducré-Robitaille, J.; Brodeur, J. (2006)

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.

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

Monitoringin the United States. Prepared for

the Interagency Board for Nutrition

Monitoring and Related Research.

Washington, DC: U.S. Government Printing

Office.

Foos, B., Sonwane, B. (2008) Overview: workshop on

children’s inhalation dosimetry and health

effects for risk assessment. J Toxicol Environ

Health Part A 71(3):147-148. 

Foos, B.; Marty, M.; Schwartz, J.; Bennett, W.;

Moya, J.; Jarabek, A; Salmon, A. (2008)

Focusing on children’s inhalation dosimetry

and health effects for risk assessment: an

introduction. J Toxicol Environ Health Part A

71(3):149-165.

International Commission on Radiological Protection.

(1981) Report of the task group on reference

man. New York: Pergammon Press. 

Layton, D.W. (1993) Metabolically consistent

breathing rates for use in dose assessments.

Health Phys 64(1):23-36.

Linn, W.S.; Shamoo, D.A.; Hackney, J.D. (1992)

Documentation of activity patterns in "highrisk" groups exposed to ozone in the Los

Angeles area. In: Proceedings of the

Second EPA/AWMA Conference on

Tropospheric Ozone, Atlanta, Nov. 1991. 

pp. 701-712. Air and Waste Management

Assoc., Pittsburgh, PA. 

Price, P.; Conolly, R.; Chaisson, C.; Gross, E.;

Young, J.; Mathis, E.; Tedder, D. (2003)

Modeling interindividual variation in

physiological factors used in PBPK models

of humans. Crit Rev Toxicol 33 (5):469-

503.

Rusconi, F.; Castagneto, M.; Garliardi, 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(3):350-

355.

Scrimshaw, N. S.; Waterlow, J. C.; Schurch, B. (Eds.).

(1996) Energy and Protein Requirements.

Proceedings of an International Dietary and

Energy Consultancy Group Workshop; 1994

Oct 31–Nov 4; London, UK: Stockton Press.

Spier, C.E.; Little, D.E.; Trim, S.C.; Johnson, T.R.;

Linn, W.S.; Hackney, J.D. (1992) Activity

patterns in elementary and high school

students exposed to oxidant pollution. J Exp

Anal Environ Epidemiol 2(3):277-293.

 Stifelman, M. (2007) Using doubly-labeled water

measurements of human energy expenditure to

estimate inhalation rates. Sci Total Environ

373:585-590.

 The Lifeline Group. (2007) Physiological parameters

for PBPK modelingTM version 1.3 (P3MTM).

Accessed May 2007. Available at:

http://www.thelifelinegroup.org/p3m/

 U.S. EPA. (1985) Development of statistical

distributions or ranges of standard factors used

in exposure assessments. Washington, DC:

Office of Health and Environmental

Assessment; EPA Report No.

EPA 600/8-85-010. Available from: NTIS,

Springfield, VA; PB85-242667.

 U.S. EPA. (1992) Guidelines for exposure

assessment. Washington, DC: Office of
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Research and Development, Office of Health 

and Environmental Assessments. 

U.S. EPA. (1994) Methods for derivation of inhalation 

reference concentrations and application of 

inhalation dosimetry. Washington, DC: 

Office of Health and Environmental 

Assessment. EPA/600/8-90/066F. 

U.S.	 EPA. (1997) Exposure Factors Handbook. 

Washington, DC: Office of Research and 

Development, Office of Health and 

Environmental Assessment. 

U.S. EPA. (2005). Supplemental guidance for 

assessing susceptibility from early-life 

exposure to carcinogens. Washington, DC: 

Risk Assessment Forum. EPA/630/R03/003F. 

U.S.	 EPA. (2006) Metabolically-derived human 

ventilation rates: A revised approach based 

upon oxygen consumption rates. Washington, 

DC: National Center for Environmental 

Assessment. External Review Draft. Prepared 

for USEPA/ORD, Contract No. EP-C-04-027. 

U.S.	 EPA. (2008) Risk Assessment Guidance for 

Superfund: Volume I: Human Health 

Evaluation Manual (Part F, Supplemental 

Guidance for Inhalation Risk Assessment). 

Washington, DC: Office of Superfund 

Remediation and Technology Innovation. 

Peer Review Draft. Prepared for USEPA, 

Contract No. 68-W-01-05. 

WHO.	 (1986) Principles for evaluating health risks 

from chemicals during infancy and early 

childhood: the need for a special approach. 

Environmental Health Criteria 59, World 

Health Organization, International Programme 

on Chemical Safety. 

Page Child-Specific Exposure Factors Handbook 

6-16 September 2008 
Table 6-4. Physiological Daily Inhalation Rates for Newborns Aged 1 Month or Less 

Age Group N Body Weight (kg) 

Mean ± SD 

Physiological Daily Inhalation Rates e 

Mean ± SD 

(m3

/day) (m3/kg-day) 

21 days (3 weeks) 

32 days (~ 1 month) 

33 days (~ 1 month) 

13a,c 

10b,d 

10a,d 

1.2 ± 0.2 

4.7 ± 0.7 

4.8 ± 0.3 

0.85 ± 0.17 f 

2.45 ± 0.59 g 

2.99 ± 0.47 g 

0.74 ± 0.09 f 

0.53 ± 0.10 g 

0.62 ±0.09g 

a 

b 

c 

d 

e 

f 

g 

N 

SD 

Source: 

Formula-fed infants. 

Breast-fed infants. 

Healthy infants with very low birth weight. 

Infants evaluated as being clinically healthy and neither underweight or overweight. 

Physiological daily inhalation rates were calculated using the following equation: (TDEE + 

ECG)*H*(VE/VO2)*10-3, where H = 0.21 L of O 2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily 

energy expenditure (kcal/day) and ECG = stored daily energy cost for growth (kcal/day). 

TDEEs based on nutritional balance measurements during 3-day periods. 

TDEEs based on 

2

H2O and H2 18O disappearance rates from urine 

= Number of individuals. 

= Standard deviation. 

Brochu et al., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-17
 
Table 6-5. Distribution Percentiles of Physiological Daily Inhalation Rates (m 3

/day) for Free-living Normal-weight
 

Males and Females Aged 2.6 months to 23 years
 

 AgeGroup 

(years) N 

Body 

Weighta (kg)
 

Mean 

± SD
 

b Physiological Daily Inhalation Rates (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 

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 a Measured body weight. Normal-weight individuals defined according to the body mass index (BMI) cut-offs. b Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(V E/VO2)*10-3, where H = 

0.21 L of O 2/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., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Page Child-Specific Exposure Factors Handbook 

6-18 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-6. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Free-living Normal-weight 

Males, Females, and Males and Females Combined. 

Age Groupa N Mean 95th 

Males 

3 to <6 monthsb 32 3.38 4.57 

6 to <12 months 40 4.42 5.51 

1 to <2 years 35 5.12 6.56 

Females 

3 to <6 monthsb 53 3.26 4.36 

6 to <12 months 63 3.96 5.14 

1 to <2 years 66 4.78 6.36 

Males and Females Combined 

3 to <6 monthsb 85 3.32 4.47 

6 to <12 months 103 4.09 5.53 

1 to <2 years 101 4.95 6.46 

a No other age groups from Table 6-5 (Brochu et al., 2006) fit into the U.S. EPA age groupings. b Age group from Brochu et al. (2006) was 2.6 to <6 months. 

N = Number of individuals. 

Source: Brochu et al., 2006. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-19
 
Table 6-7. Distribution Percentiles of Physiological Daily Inhalation Rates (m 3

/day) for Free-living Normal-weight and Overweight/obese 

Males and Females Aged 4 to 18 years 

Age Group 

(years) N Body Weight a (kg)

Mean ± SD 

b Physiological Daily Inhalation Rates (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 

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 

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 

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 a 

b 

c 

N 

Measured body weight. Normal-weight and overweight/obese males defined according to the body mass index (BMI) cut-offs. 

Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(V E/VO2)*10-3, where H = 

0.21 L of O 2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily energy expenditure (kcal/day) and ECG = stored daily energy 

cost for growth (kcal/day). 

Percentiles based on a normal distribution assumption for age groups. 

= Number of individuals. 

SD = Standard deviation. 

Source: Brochu et al., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Page Child-Specific Exposure Factors Handbook 

6-20 September 2008 
Table 6-8. Distribution Percentiles of Physiological Daily Inhalation Rates per Unit of Body Weight (m 3

/kg-day) for Free-living
 

Normal-weight Males and Females Aged 2.6 months to 23 years
 

Age Group 

(years) 

Physiological Daily Inhalation Rates a (m3

/kg-day) 

Mean ± SD 

b Percentile

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 

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 a 

b 

SD 

Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(V E/VO2)*10-3, where 

H = 0.21 L of O 2/Kcal, VE/VO2 = 27 (Layton, 1993), TDEE = total daily energy expenditure (kcal/day) and ECG = stored 

daily energy cost for growth (kcal/day). 

Percentiles based on a normal distribution assumption for age groups. 

= Standard deviation. 

Source: Brochu et al., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-21
 
Table 6-9. Distribution Percentiles of Physiological Daily Inhalation Rates (m 3

/kg-day) for Free-living Normal-weight and
 

Overweight/obese Males and Females Aged 4 to 18 years
 

Age Group (years) 

Physiological Daily Inhalation Rates a (m3

/kg-day) 

Mean ± SD 

b Percentile

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 

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 

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 

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 a Physiological daily inhalation rates were calculated using the following equation: (TDEE + ECG)*H*(V E/VO2)*10-3 , 

where H = 0.21 L of O 2/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., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Page Child-Specific Exposure Factors Handbook 

6-22 September 2008 
 

 

 

Table 6-10. Descriptive Statistics for Daily Average Inhalation Rate in Males, by Age Categorya 

Age Group N 

Daily Average Inhalation Rate, Unadjusted for Body Weight
 

(m3

/day)
 

Mean 

Percentiles
 

Maximum 

5th 10th 25th 50th 75th 90th 95th 

Birth to <1 year 419 8.76 4.77 5.70 7.16 8.70 10.43 11.93 12.69 17.05 

1 to < 2 years 308 13.49 9.73 10.41 11.65 13.11 15.02 17.03 17.89 24.24 

2 to < 3 years 261 13.23 9.45 10.20 11.43 13.19 14.49 16.27 17.71 28.17 

3 to <6 years 540 12.65 10.42 10.87 11.40 12.58 13.64 14.63 15.41 19.52 

6 to <11 years 940 13.42 10.08 10.69 11.73 13.09 14.73 16.56 17.72 24.97 

11 to <16 years 1337 15.32 11.41 12.11 13.27 14.79 16.81 19.54 21.21 28.54 

16 to <21 years 1241 17.22 12.60 13.41 14.48 16.63 19.16 21.94 23.38 39.21 

Age Group N 

Daily Average Inhalation Rate, Adjusted for Body Weight 

(m3

/day-kg) 

Mean 

Percentiles 

Maximum 

5th 10th 25th 50th 75th 90th 95th 

Birth to <1 year 419 1.09 0.91 0.94 1.00 1.09 1.16 1.26 1.29 1.48 

1 to < 2 years 308 1.19 0.96 1.02 1.09 1.17 1.26 1.37 1.48 1.73 

2 to < 3 years 261 0.95 0.78 0.82 0.87 0.94 1.01 1.09 1.13 1.36 

3 to <6 years 540 0.70 0.52 0.56 0.61 0.69 0.78 0.87 0.92 1.08 

6 to <11 years 940 0.44 0.32 0.34 0.38 0.43 0.50 0.55 0.58 0.81 

11 to <16 years 1337 0.29 0.21 0.22 0.25 0.28 0.32 0.36 0.38 0.51 

16 to <21 years 1241 0.23 0.17 0.18 0.20 0.23 0.25 0.28 0.30 0.40 

a 

N 

BW 

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. 

= Number of individuals. 

= Body weight. 

Source: U.S. EPA, 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-23
 
 

 

 

Table 6-11. Descriptive Statistics for Daily Average Inhalation Rate in Females, by Age Categorya 

Age Group N 

Daily Average Inhalation Rate, Unadjusted for Body Weight
 

(m3

/day)
 

Mean 

Percentiles
 

Maximum 

5th 10th 25th 50th 75th 90th 95th 

Birth to <1 year 415 8.53 4.84 5.48 6.83 8.41 9.78 11.65 12.66 26.26 

1 year 245 13.31 9.08 10.12 11.24 13.03 14.64 17.45 18.62 24.77 

2 years 255 12.74 8.91 10.07 11.38 12.60 13.96 15.58 16.37 23.01 

3 to <6 years 543 12.16 9.87 10.38 11.20 12.02 13.01 14.03 14.93 19.74 

6 to <11 years 894 12.41 9.99 10.35 11.01 11.95 13.42 15.13 16.34 20.82 

11 to <16 years 1,451 13.44 10.47 11.11 12.04 13.08 14.54 16.25 17.41 26.58 

16 to <21 years 1,182 13.59 9.86 10.61 11.78 13.20 15.02 17.12 18.29 30.11 

Age Group N 

Daily Average Inhalation Rate, Adjusted for Body Weight
 

(m3

/day-kg)
 

Mean 

Percentiles
 

Maximum 

5th 10th 25th 50th 75th 90th 95th 

Birth to <1 year 415 1.14 0.91 0.97 1.04 1.13 1.24 1.33 1.38 1.60 

1 year 245 1.20 0.98 1.01 1.10 1.18 1.30 1.41 1.47 1.73 

2 years 255 0.96 0.82 0.84 0.89 0.96 1.01 1.07 1.11 1.23 

3 to <6 years 543 0.69 0.48 0.54 0.60 0.68 0.77 0.88 0.92 1.12 

6 to <11 years 894 0.43 0.28 0.31 0.36 0.43 0.49 0.55 0.58 0.75 

11 to <16 years 1,451 0.25 0.19 0.20 0.22 0.25 0.28 0.31 0.34 0.47 

16 to <21 years 1,182 0.21 0.16 0.17 0.19 0.21 0.24 0.27 0.28 0.36 

a 

N 

 

Source: 

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. 

= Number of individuals. 

U.S. EPA, 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Page Child-Specific Exposure Factors Handbook 

6-24 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-12. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males, Females and 

Males and Females Combined 

Age Groupa N Mean 95th 

Males 

Birth to <1 year 419 8.76 12.69 

1 to <2 years 308 13.49 17.89 

2 to <3 years 261 13.23 17.71 

3 to <6 years 540 12.65 15.41 

6 to <11 years 940 16.42 17.72 

11 to <16 years 1,337 15.32 21.21 

16 to <21 years 1,241 17.22 23.38 

Females 

Birth to <1 year 415 8.53 12.66 

1 to <2 years 245 13.31 18.62 

2 to <3 years 255 12.74 16.37 

3 to <6 years 543 12.16 14.93 

6 to <11 years 894 12.41 16.34 

11 to <16 years 1,451 13.44 17.41 

16 to <21 years 1,182 13.59 18.29 

Males and Females Combined 

Birth to <1 year 834 8.65 12.68 

1 to <2 years 553 13.40 18.26 

2 to <3 years 516 12.99 17.04 

3 to <6 years 1,083 12.41 15.17 

6 to <11 years 1,834 12.92 17.03 

11 to <16 years 2,788 14.38 19.31 

16 to <21 years 2423 15.41 20.84 

a No other age groups from Tables 6-9 and 6-10 (U.S. EPA, 2006) fit into the EPA age groupings. 

N = Number of individuals. 

Source: U.S. EPA, 2006. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-25
 
 

Table 6-13. Descriptive Statistics for Average Ventilation Ratea While Performing Activities Within the Specified Activity Category, fo

Males by Age Category
 

Age Group N
 

Average Ventilation Rate (m3/min), 

Unadjusted for Body Weight 

Average Ventilation Rate (m3/min-kg), 

Adjusted for Body Weight
 

Mean 

Percentiles 

Maximum Mean 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 5th 10th 25th 50th 75th 90th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 year 419 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 3.85E-04 2.81E-04 3.01E-04 3.37E-04 3.80E-04 4.27E-04 4.65E-04 5

1 year 308 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 3.95E-04 2.95E-04 3.13E-04 3.45E-04 3.84E-04 4.41E-04 4.91E-04 5

2 years 261 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 3.30E-04 2.48E-04 2.60E-04 2.89E-04 3.26E-04 3.62E-04 4.05E-04 4

3 to <6 years 540 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 2.43E-04 1.60E-04 1.74E-04 1.98E-04 2.37E-04 2.79E-04 3.14E-04 3

6 to <11 years 940 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 1.51E-04 1.02E-04 1.09E-04 1.25E-04 1.48E-04 1.74E-04 2.00E-04 2

11 to <16 years 1,337 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 9.80E-05 6.70E-05 7.20E-05 8.10E-05 9.40E-05 1.10E-04 1.29E-04 1

16 to <21 years 1,241 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 7.10E-05 4.70E-05 5.20E-05 6.10E-05 6.90E-05 8.00E-05 9.00E-05 9

Sedentary & Passive Activities (METS # 1.5 -- Includes Sleep or Nap) 

Birth to <1 year 419 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 3.97E-04 3.03E-04 3.17E-04 3.51E-04 3.91E-04 4.37E-04 4.70E-04 4

1 year 308 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 4.06E-04 3.21E-04 3.31E-04 3.63E-04 3.97E-04 4.48E-04 4.88E-04 5

2 years 261 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 3.43E-04 2.74E-04 2.86E-04 3.09E-04 3.40E-04 3.69E-04 4.05E-04 43 to <6 years 540 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 2.55E-04 1.78E-04 1.93E-04 2.15E-04 2.50E-04 2.88E-04 3.27E-04 3

6 to <11 years 940 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 1.60E-04 1.13E-04 1.18E-04 1.35E-04 1.57E-04 1.80E-04 2.09E-04 2

11 to <16 years 1,337 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 1.05E-04 7.70E-05 8.00E-05 8.80E-05 1.01E-04 1.18E-04 1.35E-04 1

16 to <21 years 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 7.70E-05 5.50E-05 6.00E-05 6.80E-05 7.60E-05 8.50E-05 9.50E-05 1

Light Intensity Activities (1.5 < METS # 3.0) 

Birth to <1 year 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 9.88E-04 7.86E-04 8.30E-04 8.97E-04 9.72E-04 1.07E-03 1.17E-03 1

1 year 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 1.02E-03 8.36E-04 8.59E-04 9.18E-04 1.01E-03 1.10E-03 1.22E-03 1

2 years 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 8.37E-04 6.83E-04 7.16E-04 7.61E-04 8.26E-04 8.87E-04 9.95E-04 1

3 to <6 years 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 6.33E-04 4.41E-04 4.80E-04 5.44E-04 6.26E-04 7.11E-04 7.94E-04 8

6 to <11 years 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 3.84E-04 2.67E-04 2.86E-04 3.24E-04 3.77E-04 4.37E-04 4.93E-04 5

11 to <16 years 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 2.46E-04 1.76E-04 1.87E-04 2.09E-04 2.38E-04 2.82E-04 3.11E-04 3

16 to <21 years 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 1.79E-04 1.37E-04 1.44E-04 1.56E-04 1.78E-04 1.99E-04 2.18E-04 2

Page Child-Specific Exposure Factors Handbook 

6-26 September 2008 
 Table 6-13. Descriptive Statistics for Average Ventilation Ratea While Performing Activities Within the Specified Activity Category, fo

Males by Age Category (continued)
 Age Group N
 Average Ventilation Rate (m3/min), Unadjusted for Body Weight Average Ventilation Rate (m3/min-kg), Adjusted for Body Weight
 Mean Percentiles Maximum Mean Percentiles 

5th 10th 25th 50th 75th 90th 95th 5th 10th 25th 50th 75th 90th 

Moderate Intensity Activities (3.0 < METS # 6.0) Birth to <1 year 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 1.80E-03 1.40E-03 1.49E-03 1.62E-03 1.78E-03 1.94E-03 2.18E-03 2.

1 year 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 1.88E-03 1.41E-03 1.50E-03 1.65E-03 1.82E-03 2.02E-03 2.34E-03 2.

2 years 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 1.55E-03 1.21E-03 1.28E-03 1.40E-03 1.54E-03 1.66E-03 1.84E-03 2.

3 to <6 years 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 1.17E-03 8.05E-04 8.83E-04 9.99E-04 1.12E-03 1.31E-03 1.56E-03 1.

6 to <11 years 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 7.36E-04 5.03E-04 5.45E-04 6.18E-04 7.14E-04 8.34E-04 9.58E-04 1.11 to <16 years 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 4.91E-04 3.59E-04 3.75E-04 4.18E-04 4.73E-04 5.52E-04 6.35E-04 6.

16 to <21 years 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 3.87E-04 2.81E-04 2.96E-04 3.34E-04 3.80E-04 4.31E-04 4.86E-04 5.

High Intensity (METS > 6.0) 

Birth to <1 year 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 3.48E-03 2.70E-03 2.93E-03 3.10E-03 3.46E-03 3.81E-03 4.14E-03 4.

1 year 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 3.52E-03 2.52E-03 2.89E-03 3.22E-03 3.57E-03 3.91E-03 4.11E-03 4.

2 years 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 2.89E-03 2.17E-03 2.34E-03 2.58E-03 2.87E-03 3.20E-03 3.43E-03 3.

3 to <6 years 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 2.17E-03 1.55E-03 1.66E-03 1.81E-03 2.11E-03 2.50E-03 2.73E-03 2.6 to <11 years 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 1.41E-03 9.36E-04 1.03E-03 1.19E-03 1.38E-03 1.59E-03 1.83E-03 1.

11 to <16 years 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 9.50E-04 6.35E-04 6.96E-04 7.90E-04 9.09E-04 1.09E-03 1.27E-03 1.

16 to <21 years 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 7.11E-04 4.75E-04 5.27E-04 5.99E-04 6.91E-04 8.02E-04 9.17E-04 9.

a	 

N MET 

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, estmultiple linear regression model, with weights corresponding to the number of minutes spent performing the activity. Numbers in these two columns represent averages, calculated across 

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. 

= Number of individuals.
 = Metabolic equivalent.
 

Source:	 U.S. EPA, 2006. 

Child-Specific Exposure Factors Handbook Page 

September 2008 6-27 
 

Table 6-14. Descriptive Statistics for Average Ventilation Ratea While Performing Activities Within the Specified Activity Category, for Females by 

Age Group 

N 

Average Ventilation Rate (m3/min), 

Unadjusted for Body Weight 

Average Ventilation Rate (m3/min-kg), 

Adjusted for Body Weight 

Mean Percentiles 

Maximum Mean 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 5th 10th 25th 50th 75th 90th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 year 415 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 3.91E-04 2.80E-04 3.01E-04 3.35E-04 3.86E-04 4.34E-04 4.79E-04 1 year 245 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 4.14E-04 3.15E-04 3.29E-04 3.61E-04 4.05E-04 4.64E-04 5.21E-04 

2 years 255 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 3.42E-04 2.58E-04 2.71E-04 2.93E-04 3.33E-04 3.91E-04 4.25E-04 3 to <6 years 543 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 2.38E-04 1.45E-04 1.63E-04 1.95E-04 2.33E-04 2.75E-04 3.20E-04 6 to <11 years 894 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 1.51E-04 8.90E-05 9.70E-05 1.20E-04 1.46E-04 1.76E-04 2.11E-04 

11 to <16 years 1,451 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 9.00E-05 5.90E-05 6.50E-05 7.50E-05 8.70E-05 1.02E-04 1.18E-04 

16 to <21 years 1,182 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 6.90E-05 4.40E-05 4.70E-05 5.70E-05 6.70E-05 8.00E-05 9.30E-05 

Sedentary & Passive Activities (METS # 1.5 -­ Includes Sleep or Nap) 

Birth to <1 year 415 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 4.02E-04 2.97E-04 3.16E-04 3.52E-04 3.96E-04 4.46E-04 4.82E-04 1 year 245 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 4.25E-04 3.35E-04 3.48E-04 3.76E-04 4.18E-04 4.69E-04 5.12E-04 

2 years 255 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 3.55E-04 2.85E-04 2.96E-04 3.20E-04 3.48E-04 3.91E-04 4.20E-04 3 to <6 years 543 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 2.51E-04 1.64E-04 1.79E-04 2.11E-04 2.48E-04 2.84E-04 3.28E-04 6 to <11 years 894 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 1.60E-04 9.90E-05 1.10E-04 1.31E-04 1.57E-04 1.85E-04 2.12E-04 

11 to <16 years 1,451 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 9.70E-05 7.10E-05 7.50E-05 8.30E-05 9.50E-05 1.09E-04 1.23E-04 

16 to <21 years 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 7.50E-05 5.30E-05 5.70E-05 6.30E-05 7.40E-05 8.50E-05 9.60E-05 

Light Intensity Activities (1.5 < METS # 3.0) 

Birth to <1 year 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 9.78E-04 7.91E-04 8.17E-04 8.80E-04 9.62E-04 1.05E-03 1.18E-03 1 year 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 1.05E-03 8.45E-04 8.68E-04 9.49E-04 1.04E-03 1.14E-03 1.25E-03 

2 years 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 8.97E-04 7.30E-04 7.63E-04 8.19E-04 8.93E-04 9.64E-04 1.04E-03 3 to <6 years 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 6.19E-04 4.48E-04 4.84E-04 5.37E-04 5.99E-04 6.98E-04 7.83E-04 6 to <11 years 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 3.82E-04 2.52E-04 2.70E-04 3.15E-04 3.76E-04 4.42E-04 5.03E-04 

11 to <16 years 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 2.25E-04 1.63E-04 1.74E-04 1.96E-04 2.17E-04 2.49E-04 2.84E-04 

16 to <21 years 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 1.74E-04 1.29E-04 1.38E-04 1.54E-04 1.73E-04 1.93E-04 2.13E-04 

Page Child-Specific Exposure Factors Handbook 

6-28 September 2008 
 Table 6-14. Descriptive Statistics for Average Ventilation Ratea While Performing Activities Within the Specified Activity Category, f

Females by Age Category (continued)
 AgeGroup N Average Ventilation Rate (m3/min), Unadjusted for Body Weight Average Ventilation Rate (m3/min-kg), Adjusted for Body Weight Mean Percentiles Maximum Mean Percentiles 

5th 10th 25th 50th 75th 90th 95th 5th 10th 25th 50th 75th 90th 95th Moderate Intensity Activities (3.0 < METS # 6.0) Birth to <1 year 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 1.87E-03 1.47E-03 1.52E-03 1.67E-03 1.85E-03 2.01E-03 2.25E-03 2.40E-

1 year 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 1.90E-03 1.52E-03 1.62E-03 1.73E-03 1.87E-03 2.02E-03 2.24E-03 2.37E-

2 years 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 1.60E-03 1.27E-03 1.31E-03 1.44E-03 1.58E-03 1.75E-03 1.92E-03 2.02E-

3 to <6 years 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 1.14E-03 7.92E-04 8.53E-04 9.64E-04 1.11E-03 1.31E-03 1.45E-03 1.56E-

6 to <11 years 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 7.23E-04 4.62E-04 5.12E-04 5.98E-04 7.15E-04 8.38E-04 9.42E-04 1.01E-

11 to <16 years 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 4.41E-04 3.17E-04 3.38E-04 3.80E-04 4.31E-04 4.92E-04 5.51E-04 6.11E-

16 to <21 years 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 3.65E-04 2.67E-04 2.82E-04 3.10E-04 3.51E-04 4.07E-04 4.63E-04 4.94E-

High Intensity (METS > 6.0) 

Birth to <1 year 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 3.26E-03 2.53E-03 2.62E-03 2.89E-03 3.23E-03 3.63E-03 3.96E-03 4.08E-

1 year 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 3.38E-03 2.57E-03 2.75E-03 2.97E-03 3.24E-03 3.71E-03 4.16E-03 4.87E-

2 years 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 2.80E-03 2.20E-03 2.31E-03 2.48E-03 2.81E-03 3.13E-03 3.36E-03 3.48E-

3 to <6 years 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 1.98E-03 1.36E-03 1.51E-03 1.69E-03 1.90E-03 2.19E-03 2.50E-03 2.99E-

6 to <11 years 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 1.33E-03 8.85E-04 9.67E-04 1.12E-03 1.33E-03 1.52E-03 1.72E-03 1.81E-

11 to <16 years 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 8.79E-04 5.89E-04 6.25E-04 7.12E-04 8.53E-04 1.01E-03 1.18E-03 1.31E-

16 to <21 years 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 6.96E-04 4.52E-04 4.96E-04 5.67E-04 6.86E-04 7.93E-04 9.16E-04 1.00E-

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 fa

the category, estimated using a multiple linear regression model, with weights corresponding to the number of minutes spent performing the activity. Numbers 

columns represent averages, calculated across individuals in the specified age category, of these weighted averages. These are weighted averages, with the we

corresponding to the 4-year sampling weights assigned within NHANES 1999-2002. 

N = Number of individuals.
 MET = Metabolic equivalent.
 Source: U.S. EPA, 2006. 

Child-Specific Exposure Factors Handbook Page 

September 2008 6-29 
 

Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the Specified Activity Category

by Age and Gender Categoriesa 

AgeGroup N 

Duration (hours/day) Spent at Activity – Males 

N 

Duration (hours/day) Spent at Activity – Fem

Mean 

Percentiles 

Maximum Mean 

Percentiles 

5th 10th 25th 50th 75th 90th 95th 5th 10th 25th 50th 75th 90th 

Sleep or nap (Activity ID = 14500) 

Birth to <1 year 419 13.51 12.63 12.78 13.19 13.53 13.88 14.24 14.46 15.03 415 12.99 12.00 12.16 12.53 12.96 13.44 13.82 1 year 308 12.61 11.89 12.15 12.34 12.61 12.89 13.13 13.29 13.79 245 12.58 11.59 11.88 12.29 12.63 12.96 13.16 2 years 261 12.06 11.19 11.45 11.80 12.07 12.39 12.65 12.75 13.40 255 12.09 11.45 11.68 11.86 12.08 12.34 12.57 3 to <6 years 540 11.18 10.57 10.70 10.94 11.18 11.45 11.63 11.82 12.39 543 11.13 10.45 10.70 10.92 11.12 11.38 11.58 6 to <11 years 940 10.18 9.65 9.75 9.93 10.19 10.39 10.59 10.72 11.24 894 10.26 9.55 9.73 10.01 10.27 10.54 10.74 11 to <16 years 1337 9.38 8.84 8.94 9.15 9.38 9.61 9.83 9.95 10.33 1451 9.57 8.82 8.97 9.27 9.55 9.87 10.17 16 to <21 years 1241 8.69 7.91 8.08 8.36 8.67 9.03 9.34 9.50 10.44 1182 9.08 8.26 8.44 8.74 9.08 9.39 9.79 

Sedentary & Passive Activities (METS # 1.5 -­ Includes Sleep or Nap) 

Birth to <1 year 419 14.95 13.82 14.03 14.49 14.88 15.44 15.90 16.12 17.48 415 14.07 12.86 13.05 13.53 14.08 14.54 15.08 1 year 308 14.27 13.22 13.33 13.76 14.25 14.74 15.08 15.38 16.45 245 14.32 13.02 13.25 13.73 14.31 14.88 15.36 2 years 261 14.62 13.52 13.67 14.11 14.54 15.11 15.60 15.77 17.28 255 14.86 13.81 13.95 14.44 14.81 15.32 15.78 3 to <6 years 540 14.12 13.01 13.18 13.54 14.03 14.53 15.26 15.62 17.29 543 14.27 12.88 13.15 13.56 14.23 14.82 15.43 6 to <11 years 940 13.51 12.19 12.45 12.86 13.30 13.85 14.82 15.94 19.21 894 13.97 12.49 12.74 13.22 13.82 14.50 15.34 11 to <16 years 1337 13.85 12.39 12.65 13.06 13.61 14.30 15.41 16.76 18.79 1451 14.19 12.38 12.76 13.34 14.05 14.82 15.87 16 to <21 years 1241 13.21 11.39 11.72 12.32 13.08 13.97 14.83 15.44 18.70 1182 13.58 11.80 12.17 12.79 13.52 14.29 15.08 

Light Intensity Activities (1.5 < METS # 3.0) 

Birth to <1 year 419 5.30 2.97 3.25 3.71 4.52 7.29 8.08 8.50 9.91 415 6.00 3.49 3.70 4.26 5.01 8.43 9.31 1 year 308 5.52 2.68 2.89 3.37 4.31 8.23 9.04 9.73 10.90 245 5.61 2.83 2.94 3.46 4.39 8.28 9.03 2 years 261 5.48 3.06 3.26 3.85 4.58 7.58 8.83 9.04 9.92 255 5.78 3.20 3.54 4.29 5.33 7.48 8.46 

3 to <6 years 540 6.60 3.86 4.25 5.16 6.20 8.26 9.31 9.70 10.74 543 6.25 3.78 4.10 4.79 5.84 7.86 8.84 6 to <11 years 940 7.62 5.07 5.57 6.63 7.63 8.72 9.78 10.12 11.59 894 7.27 4.63 5.46 6.33 7.17 8.34 9.42 11 to <16 years 1337 7.50 4.48 5.59 6.75 7.67 8.51 9.19 9.63 10.91 1451 7.55 4.89 5.62 6.75 7.67 8.55 9.27 16 to <21 years 1241 7.13 4.37 4.97 6.00 7.02 8.29 9.43 10.03 11.50 1182 6.98 4.60 5.08 5.91 6.85 7.96 9.16 

Page Child-Specific Exposure Factors Handbook 

6-30 September 2008 
 

Table 6-15. Descriptive Statistics for Duration of Time (hours/day) Spent Performing Activities Within the Specified Activity Category, by Age and Gender Categoriesa (continued) Age Group N Duration (hours/day) Spent at Activity – Males N Duration (hours/day) Spent at Activity – Fema

Mean Percentiles Maximum Mean Percentiles 

5th 10th 25th 50th 75th 90th 95th 5th 10th 25th 50th 75th 90th 

Moderate Intensity Activities (3.0 < METS # 6.0) Birth to <1 year 419 3.67 0.63 0.97 1.74 4.20 5.20 5.80 6.21 7.52 415 3.91 0.53 0.74 1.10 4.87 5.77 6.27 6

1 year 308 4.04 0.45 0.59 1.14 5.29 6.06 6.61 6.94 7.68 245 4.02 0.52 0.73 1.08 5.14 6.10 7.00 7

2 years 261 3.83 0.59 0.76 1.23 4.74 5.37 5.82 6.15 7.40 255 3.27 0.50 0.78 1.22 4.01 4.88 5.35 5

3 to <6 years 540 3.15 0.55 0.75 1.30 3.80 4.52 5.11 5.32 6.30 543 3.35 0.70 0.89 1.61 3.88 4.71 5.29 56 to <11 years 940 2.66 0.65 0.92 1.65 2.68 3.57 4.36 4.79 5.95 894 2.57 0.65 0.95 1.82 2.66 3.41 3.95 411 to <16 years 1337 2.35 0.88 1.09 1.66 2.30 3.02 3.62 3.89 5.90 1451 2.01 0.89 1.08 1.45 1.96 2.51 3.03 316 to <21 years 1241 3.35 1.13 1.42 2.19 3.45 4.37 5.24 5.59 6.83 1182 3.26 1.27 1.48 2.21 3.39 4.24 4.74 5

High Intensity (METS > 6.0) 

Birth to <1 year 183 0.20 0.00 0.00 0.01 0.14 0.28 0.50 0.59 0.96 79 0.17 0.03 0.05 0.09 0.14 0.21 0.33 01 year 164 0.31 0.01 0.01 0.03 0.22 0.56 0.78 0.93 1.52 55 0.22 0.03 0.05 0.09 0.18 0.35 0.40 02 years 162 0.10 0.00 0.01 0.03 0.05 0.14 0.25 0.33 0.48 130 0.15 0.00 0.01 0.03 0.08 0.16 0.48 03 to <6 years 263 0.27 0.02 0.03 0.04 0.13 0.33 0.75 1.16 1.48 347 0.19 0.01 0.02 0.05 0.10 0.22 0.46 06 to <11 years 637 0.32 0.01 0.01 0.03 0.13 0.38 1.10 1.50 3.20 707 0.24 0.02 0.03 0.06 0.12 0.26 0.67 011 to <16 years 1111 0.38 0.03 0.04 0.10 0.21 0.47 1.03 1.34 2.35 1170 0.30 0.03 0.04 0.08 0.19 0.40 0.66 016 to <21 years 968 0.40 0.03 0.04 0.14 0.27 0.53 0.99 1.29 2.59 887 0.24 0.01 0.03 0.08 0.18 0.34 0.51 0

a Individual measures are weighted by their 4-year sampling weights as assigned within NHANES 1999-2002 when calculating the statistics in this table. Ventilation 

estimated using a multiple linear regression model. 

N = Number of individuals. MET =Metabolic equivalent. Source: U.S. EPA, 2006. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-31
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-16. Nonnormalized Daily Inhalation Rates (m3/day) Derived Using Layton’s (1993) 

Method and CSFII Energy Intake Data 

Age Sample Size 

(Nonweighted) Mean SEM 

Percentiles 

SE of 95th 

percentile 50th 90th 95th 

Infancy 

0-2 months 182 3.63 0.14 3.30 5.44 7.10 0.64 

3-5 months 294 4.92 0.14 4.56 6.86 7.72 0.48 

6-8 months 261 6.09 0.15 5.67 8.38 9.76 0.86 

9-11 months 283 7.41 0.20 6.96 10.21 11.77 -

0-11 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 

9-18 years 983 19.27 0.28 17.96 28.78 32.82 1.39 

Adolescent Girls 

9-18 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. 

Page Child-Specific Exposure Factors Handbook 

6-32 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-17. Mean and 95th Percentile Inhalation Rate Values (m3/day) for Males and Females Combined 

Age Groupa Sample Size Mean 95th 

Birth to <1 monthb 

3 to <6 months 

6 to <12 monthsc 

182 

294 

544 

3.63 

4.92 

6.75 

7.10 

7.72 

10.77 

1 to <2 years 934 8.77 13.79 

2 to <3 years 989 9.76 14.81 

3 to <6 yearsd 4,107 11.37 17.29 

6 to <11 yearse 1,553 13.69 20.28 

11 to <16 yearsf 975 17.07 27.74 

16 to <21 yearsg 495 18.31 34.32 

a No other age groups from Table 6-14 (Arcus-Arth and Blaisdell, 2007) fit into the U.S. EPA age groupings. b Age group from Arcus-Arth and Blaisdell (2007) was 0-2 months. c Age groups of 6-8 months and 9-11 months from Arcus-Arth and Blaisdell (2007) were averaged. d Age groups of 3, 4 and 5 years from Arcus-Arth and Blaisdell (2007) were averaged. e Age groups of 6, 7, 8, 9 and 10 years from Arcus-Arth and Blaisdell (2007) were averaged. f Age groups of 11, 12, 13, 14 and 15 years from Arcus-Arth and Blaisdell (2007) were averaged. g Age groups of 16, 17 and 18 years from Arcus-Arth and Blaisdell (2007) were averaged. 

Source: Arcus-Arth and Blaisdell, 2007. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-33
 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-18. Summary of Institute of Medicine Energy Expenditure Recommendations 

for Active and Very Active People with Equivalent Inhalation Rates 

Males Females Age Energy 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 1050 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––30 3,015––3,490 17.0––19.7 2,373––2,683 13.4––15.2 

31––50 2,862––3,338 16.2––18.9 2,263––2,573 12.8––14.5 

51––70 2,671––3,147 15.1––17.8 2,124––2,435 12.0––13.8 

Source: Stifelman, 2007. 

Page Child-Specific Exposure Factors Handbook 

6-34 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-19. Mean Inhalation Rate Values (m3/day) for Males, Females, and Males and Females Combined.a 

Age Groupb Males Females Combined 

Birth to <1 year 3.4 3.4 3.4 

1 to <2 years 4.9 4.9 4.9 

2 to <3 years 5.9 5.5 5.7 

3 to <6 yearsc 9.2 8.3 8.8 

6 to <11 yearsd 10.9 10.2 10.6 

11 to <16 yearse 14.9 12.7 13.8 

16 to <21 yearsf 18.2 13.3 15.8 

a Inhalation rates are for IOM Physical Activity Level (PAL) category "active"; the total number of subjects for 

all PAL categories was 3007. b No other age groups from Table 6-15 (Stifelman, 2007) fit into the EPA age groupings. c Age groups of 3, 4, and 5 years from Stifelman, 2007 were averaged. d Age groups of 6, 7, 8, 9 and 10 years from Stifelman, 2007 were averaged. e Age groups of 11, 12, 13, 14 and 15 years from Stifelman, 2007 were averaged. f Age groups of 16, 17 and 18 years from Stifelman, 2007 were averaged. 

Source: Stifelman, 2007. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-35
 
 

 

 

Table 6-20. Mean Inhalation Rate Values (m 3/day) from Key Studies for Males and Females Combined 

Age Group 

U.S. EPA (2006) Brochu et al. 

(2006) 

Arcus-Arth and 

Blaisdell (2007) Stifelman (2007) Combined Key 

Studies 

Na Mean N Mean N Mean N Mean N Mean 

Birth to <1 month 

1 to <3 months 

3 to <6 months 

6 to <12 months 

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 

b 

-

-

-

-

834 

553 

516 

1,083 

1,834 

2,788 

2,423 

-

-

-

-

8.65 

13.40 

12.99 

12.41 

12.92 

14.38 

15.41 

-

-

85 

103 

-

101 

-

-

-

-

-

-

-

3.32 

4.09 

-

4.95 

-

-

-

-

-

182 

-

294 

544 

--

934 

989 

4,107 

1,553 

975 

495 

3.63 

-

4.92 

6.75 

--

8.77 

9.76 

11.37 

13.69 

17.07 

18.31 

- -

- -

- -

- -

- 3.40 

- 4.90 

- 5.70 

- 8.77 

- 10.57 

- 13.78 

- 15.75 

182 

-

379 

647 

834 

1,588 

1,505 

5,190 

3,387 

3,763 

2,918 

3.63 

­

4.12 

5.42 

6.03 

8.01 

9.48 

10.85 

12.39 

15.08 

16.48 

a 

b 

Number of individuals; the total number of subjects for Stifelman (2007) was 3,007. 

No data from this study for this age group. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Page Child-Specific Exposure Factors Handbook 

6-36 September 2008 
 

 

 

Table 6-21. 95th Percentile Inhalation Rate Values (m 3/day) from Key Studies for Males and Females Combined 

Age Group 

U.S. EPA (2006) Brochu et al. 

(2006) 

Arcus-Arth and 

Blaisdell (2007) Stifelman (2007) Combined Key 

Studies 

Na 95th 95th N 95th N 95th N 95th N 

Birth to <1 month b - - - - 182 7.10 - - 182 7.10 

1 to <3 months - - - - - - - - - ­

3 to <6 months - - 85 4.47 294 7.72 - - 379 6.09 

6 to <12 months - - 103 5.33 544 10.77 - - 647 8.05 

Birth to <1 year 834 12.68 - - - - - - 834 12.68 

1 to <2 years 553 18.26 101 6.46 934 13.79 - - 1,588 12.84 

2 to <3 years 516 17.04 - - 989 14.81 - - 1,505 15.93 

3 to <6 years 1,083 15.17 - - 4,107 17.29 - - 5,190 16.23 

6 to <11 years 1,834 17.03 - - 1,553 20.28 - - 3,387 18.66 

11 to <16 years 2,788 19.31 - - 975 27.74 - - 3,763 23.53 

16 to <21 years 2,423 20.84 - - 495 34.32 - - 2,918 27.58 

a 

b 

Number of individuals; the total number of subjects for Stifelman (2007) was 3,007. 

No data from this study for this age group. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-37
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-22. Daily Inhalation Rates Estimated From Daily Activitiesa 

Subject Inhalation Rate (m3

/hour) Daily Inhalation Rate (DIR)b 

(m3 Resting Light Activity /day) 

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 hours resting and 16 hours light activity for adults and children (10 yrs); 14 

hours resting and 10 hours light activity for infants (1 yr); 23 hours resting and 1 hour light activity for newborns. b 

DIR = Daily Inhalation Rate 

IRi = Corresponding inhalation rate at ith activity 

ti = Hours spent during the ith activity 

k = Number of activity periods 

T = Total time of the exposure period (i.e., a day) 

Source: ICRP, 1981. 

DIR 

T 

IR ti i 

i 

K 

= = 

∑1 

1 

Page Child-Specific Exposure Factors Handbook 

6-38 September 2008 
 Table 6-23. Selected Inhalation Rate Values During Different Activity Levels Obtained From Various Literature Sources Subject W (kg) Resting Light Activity Heavy Work Maximal 

Ex

f VT V* f VT V* f VT V* f V

Adolescent male, 14-16 y male, 14-15 y female, 14-16 y female, 14-15 y; 164.9 cm L 

Children 10 y; 140 cm L males, 10-11 y 

males, 10-11 y; 140.6 cm L females, 4-6 y 

females, 4-6 y; 111.6 cm L Infant, 1 y 

Newborn 20 hrs-13 wk 9.6 hrs 

6.6 days 

59.4 

56 

36.5 

32.5 

20.8 

18.4 

2.5 

2.5-5.3 

3.6 

3.7 

16 15 16 

30 

34 

25 

29 

330 300 300 

48 

15 

21 

21 

5.2 4.5 

4.8 

1.4a 

0.5 

0.5 

0.6 

24 600 14 

53 52 

58 61 

70 66 

68b 

21

11

65

5

W 

a b 

Source: 

= Body weights; f = frequency (breaths/min); VT = tidal volume (ml); V* = minute volume (l/min); cm L = length/height; y = years of ag

Calculated from V* = f x VT.
 Crying.
 

ICRP, 1981. 

Child-Specific Exposure Factors Handbook Page 

September 2008 6-39 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-24. Summary of Human Inhalation Rates for Children 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 5 2.3 

Child, 10 years 10 0.4 40 1 29 3.2 43 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 6-25. 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. 

Page Child-Specific Exposure Factors Handbook 

6-40 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-26. Summary of Daily Inhalation Rates 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 

a Daily inhalation rate was calculated using the following equation: 

IRi = Inhalation rate at ith activity (Table 6-13 and 6-14) 

ti = Hours spent per day during ith activity (Table 6-15) 

k = Number of activity periods 

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 Tables 6-24 and 6-25. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-41
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 6-28. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-estimated Breathing Rates 

Panel Number 

and Description 

Na 

Inhalation Rates (m 3

/hour) 

Mean VR 

b Mean VR at Activity Levels 99th Percentile 

VR Slow Medium Fast 

Healthy 

 2- Elementary School Students 

 3- High School Students 

17 

19 

0.90 

0.84 

1.98 

2.22 

0.84 

0.78 

0.96 

1.14 

1.14 

1.62 

Asthmatics 

 6- Elementary and High School 

 Students 

13 1.20 2.40 1.20 1.20 1.50 

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). 

VR	 = Ventilation rate. 

Source:	 Linn et al., 1992. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-27. Calibration and Field Protocols for Self-monitoring of Activities Grouped by Subject Panels 

Panel Calibration Protocol Field Protocol 

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 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. 

Source: Linn et al., 1992. 

Page Child-Specific Exposure Factors Handbook 

6-42 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-29. Distribution of Predicted Inhalation Rates by Location and Activity Levels 

for Elementary and High School Students 

Inhalation Rates (m3

/hour) 

Age (years) Student Location Activity % Recorded Percentile Rankingsb 

Level Timea 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 hr 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. c Elementary school student or high school student. d Number of students that participated in survey. e Highest single value. 

SD = Standard deviation. 

Source: Spier et al., 1992. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-43
 
 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-30. 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 

(hours/day) Slow Medium Fast 

Elementary school, ages 

10-12 years 

(N=17) 

Indoors 16.3 2.9 0.4 19.6 

Outdoors 2.2 1.7 0.5 4.4 

High school, 

ages 13-17 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. 

Page Child-Specific Exposure Factors Handbook 

6-44 September 2008 
 

 

 

Table 6-31. Summary of Average Inhalation Rates (m 3/hour) by
 

Age Group and Activity Levels for Laboratory Protocols
 

Age Group 

Activity Level 

Restinga b Sedentary Lightc Moderated Heavye 

Young Children 

(3-5.9 years) 

Average inhalation rate (m 3

/hour) 

(N=12, gender not specified) 

Children 

(6-12.9 years)
 

Average inhalation rate (m 3

/hour)
 

(N=40, 20 male and 20 female) 

0.37 

0.45 

0.40 

0.47 

0.65 

0.95 

DNPf 

1.74 

DNPf 

2.23
 

a 

b 

c 

d 

e 

f 

Source: 

Resting defined as lying (see Table 6-33 for original data). 

Sedentary defined as sitting and standing (see Table 6-33 for original data). 

Light defined as walking at speed level 1.5 - 3.0 mph (see Table 6-33 for original data). 

Moderate defined as fast walking (3.3 - 4.0 mph) and slow running (3.5 - 4.0 mph) (see Table 6-33 for original 

data). 

Heavy defined as fast running (4.5 - 6.0 mph) (see Table 6-33 for original data). 

Group did not perform (DNP) this protocol or N was too small for appropriate mean comparisons. Allyoung 

children did not run. 

Adapted from Adams, 1993. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-45
 
 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-32. Summary of Average Inhalation Rates (m3/hour) by Age Group And Activity Levels in Field Protocols 

Age Group Moderate Activitya 

Young Children (3-5.9 years) 

Average inhalation rate (m3

/hour) 

(N=12, gender not specified) 

0.68 

Children (6-12.9 years) 

Average inhalation rate (m3

/hour) 

(N=40, 20 male and 20 female) 

1.07 

a Moderate activity was defined as play. 

N = Number of individuals. 

Source: Adams, 1993. 

Page Child-Specific Exposure Factors Handbook 

6-46 September 2008 
 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-33. Mean Minute Inhalation Rate (m3/minute) by Group and Activity for Laboratory Protocols 

Activity Young Childrena Childrena 

Lying 

Sitting 

Standing 

6.19E-03 

6.48E-03 

6.76E-03 

7.51E-03 

7.28E-03 

8.49E-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 

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 

a Young Children, male and female 3-5.9 years old; Children, male and female 6-12.9 years old. b Group did not perform (DNP) this protocol or N was too small for appropriate mean comparisons. 

Source: Adams , 1993. 

Table 6-34. Mean Minute Inhalation Rate (m3

/minute) by Group and Activity for Field Protocols 

Activity Young Childrena Childrena 

Play 1.13E-02 1.89E-02 

a 

Source: 

Young children, male and female 3-5.9 years old; children, male and female 6-12.9 years old. 

Adams, 1993. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-47
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-35. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-energy Intakes (EFD) for 

Individuals Sampled in the 1977-78 NFCS 

Cohort/Age 

(years) 

Body Weight 

(kg) 

BMRa Energy Intake (EFD) Ratio 

EFDd

MJ/dayb /BMR 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 1209 1.65 

3 to 5 18 3.69 881 6.14 1466 1.66 

6 to 8 26 4.41 1053 7.43 1774 1.68 

Males 

9 to 11 36 5.42 1293 8.55 2040 1.58 

12 to 14 50 6.45 1540 9.54 2276 1.48 

15 to 18 66 7.64 1823 10.80 2568 1.41 

Females 

9 to 11 36 4.91 1173 7.75 1849 1.58 

12 to 14 49 5.64 1347 7.72 1842 1.37 

15 to 18 56 6.03 1440 7.32 1748 1.21 

a Calculated from the appropriate age and gender-based BMR equations given in Table 6-37. b MJ/day - mega joules/day. c Kcal/d - kilo calories/day. d Food energy intake (Kcal/day) or (MJ/day). 

Source: Layton, 1993. 

Page Child-Specific Exposure Factors Handbook 

6-48 September 2008 
 

 

 

Table 6-36. Daily Inhalation Rates Calculated from Food-energy Intakes 

Cohort/Age 

(years) 

Lb Daily Inhalation Rate c 

(m3/day) 

Sleep 

(hours) 

METa Value Inhalation Rates 

Ad Fe f f Inactive Active

(m3

/day) (m3/day) 

Males and Females 

<1 

1 to 2 

3 to 5 

6 to 8 

1 

2 

3 

3 

4.5 

6.8 

8.3 

10 

11 

11 

10 

10 

1.9 

1.6 

1.7 

1.7 

2.7 

2.2 

2.2 

2.2 

2.35 

4.16 

4.98 

5.95 

6.35 

9.15 

10.96 

13.09 

Males 

9 to 11 

12 to 14 

15 to 18 

3 

3 

4 

14 

15 

17 

9 

9 

8 

1.9 

1.8 

1.7 

2.5 

2.2 

2.1 

7.32 

8.71 

10.31 

18.3 

19.16 

21.65 

Females 

9 to 11 

12 to 14 

15 to 18 

3 

3 

4 

13 

12 

12 

9 

9 

8 

1.9 

1.6 

1.5 

2.5 

2.0 

1.7 

6.63 

7.61 

8.14 

16.58
 

15.22
 

13.84
 

a MET = Metabolic equivalent.
 b L = Number of years for each age cohort.
 a Daily inhalation rate was calculated by multiplying the EFD values (see Table 6-35) by H × VQ for subjects under 9
 

years of age and by 1.2 × H × VQ (for subjects 9 years of age and older (see text for explanation), where EFD = 

Food energy intake (Kcal/day) or (MJ/day), H = Oxygen uptake = 0.05 LO 2/KJ or 0.21 LO2/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) (Table 

6-35) by the factor 1.2 (see text for explanation). e F = (24 × A - 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. f	 Inhalation rate for inactive periods was calculated as BMR × H × VQ, and for active periods by multiplying the 

inactive inhalation rate by F (see footnote c); BMR values are from Table 6-35, where BMR = basal metabolic rate 

(MJ/day) or (kg/hr). 

Source:	 Layton, 1993. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-49
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-37. Statistics of the Age/gender Cohorts Used to Develop Regression Equations for Predicting 

Basal Metabolic Rates (BMR) 

Gender, 

Age (years) 

BMR 

CV 

Body 

Weight 

(kg) N BMR Equationa 

MJ d-1 SD r 

Males 

Under 3 

3 to < 10 

10 to < 18 

1.51 

4.14 

5.86 

0.92 

0.50 

1.17 

0.61 

0.12 

0.20 

6.6 

21 

42 

162 

338 

734 

0.249 bw - 0.127 

0.095 bw + 2.110 

0.074 bw + 2.754 

Females 

Under 3 

3 to < 10 

10 to < 18 

1.54 

3.85 

5.04 

0.92 

0.49 

0.78 

0.59 

0.13 

0.15 

6.9 

21 

38 

137 

413 

575 

0.244 bw - 0.130 

0.085 bw + 2.033 

0.056 bw + 2.898 

0.95 

0.83 

0.93 

0.96 

0.81 

0.8 

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. 

Page Child-Specific Exposure Factors Handbook 

6-50 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-38. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal Metabolic Rate (BMR) 

Gender/Age 

(years) 

Body Weighta 

(kg) 

BMRb 

(MJ/day) VQ Ac H 

(m3

O2/MJ) 

Inhalation Rate, VE 

(m3/day)d 

Males 

0.5 to <3 

3 to <10 

10 to <18 

14 

23 

53 

3.4 

4.3 

6.7 

27 

27 

27 

1.6 

1.6 

1.7 

0.05 

0.05 

0.05 

7.3 

9.3 

15 

Females 

0.5 to <3 

3 to <10 

10 to <18 

11 

23 

50 

2.6 

4.0 

5.7 

27 

27 

27 

1.6 

1.6 

1.5 

0.05 

0.05 

0.05 

5.6 

8.6 

12 

a Body weight was based on the average weights for age/gender cohorts in the U.S. population. b The BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations (see Table 6­

36). 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 6-36 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 x A x H x VQ; VQ = ventilation equivalent and H = oxygen uptake. 

Source: Layton, 1993. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-51
 
 

 

 

Table 6-39. Inhalation Rates for Short-term Exposures 

Gender/Age	 

(years)	 

Body 

Weight	 

(kg)a	 

BMRb 

(MJ/day) 

Activity Type 

Rest Sedentary Light Moderate Heavy 

MET (BMR Multiplier) 

1 2c 1.2	 4d 10e 

3

/minute)f,g Inhalation Rate (m 

Males 

 0.5to<3 

 3to<10 

 10to<18 

Females 

 0.5to<3 

 3to<10 

 10to<18 

14 

23 

53 

11 

23 

50 

3.40 

4.30 

6.70 

2.60 

4.00 

5.70 

3.2E-03 

4.0E-03 

6.3E-03 

2.4E-03 

3.8E-03 

5.3E-03 

3.8E-03 

4.8E-03 

7.5E-03 

2.9E-03 

4.5E-03 

6.4E-03 

6.4E-03 

8.1E-03 

1.3E-02 

4.9E-03 

7.5E-03 

1.1E-02 

1.3E-02 

1.6E-02 

2.5E-02 

1.0E-02 

1.5E-02 

2.1E-02 

h –

h –

6.3E-02 

h –

h –

5.3E-02 

a	 

b	 

c 

d 

e 

f 

g 

h 

Source:	 

Body weights were based on average weights for age/gender cohorts of the U.S. population 

The BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR 

equations (Table 6-37). 

Range = 1.5 - 2.5. 

Range = 3 - 5.
 

Range = >5 - 20.
 

The inhalation rate was calculated as IR = BMR (MJ/day) × H (0.05 L/KJ) × MET × VQ (27) × (day/1440 min)
 3 m L
 Original data were presented in L/min. Conversion to m 3

/min was obtained as follows: × 1000L min 

The maximum possible MET sustainable for more than 5 minutes does not reach 10 for females and males until age 

13 and 12, respectively. Therefore, a METs of 10 is not possible for this age category. 

Layton, 1993. 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Page Child-Specific Exposure Factors Handbook 

6-52 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 6 - Inhalation Rates 

Table 6-40. Mean, Median, and SD of Inhalation Rate According to Waking or Sleeping in 

618 Infants and Children Grouped in Classes of Age 

Inhalation Rate (breaths/min) 

Age (months) N Waking Sleeping 

Mean ± SD Median Mean ± SD Median 

<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 

N 

= Standard deviation. 

= Number of individuals. 

Source: Rusconi et al., 1994. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 6-53
 
 

 

 

 

 

 

 

Child-Specific 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. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific 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. EPA, 1992a; 1992b; 2004). 

These include: 

C Water (e.g., bathing, washing, 

swimming); 

C Soil (e.g., outdoor recreation, gardening, 

construction); 

C Sediment (e.g., wading, fishing); 

C Liquids (e.g., use of commercial 

products); 

C Vapors/fumes (e.g., use of commercial 

products); and 

C Indoor dust (e.g., carpets, floors, counter 

tops). 

Children may be more highly exposed to 

environmental toxicants through dermal routes than 

adults. For instance, children may crawl, roll or sit on 

surfaces treated with chemicals (i.e., carpets and floors) 

and play with objects such as toys where residues may 

settle. Children also are more likely to wear less 

clothing than adults. As a result, children may have 

higher dermal contact with contaminated media. In 

addition, young children who wear diapers may be 

exposed for long periods of time to chemical 

components of lotions and other products used for 

diapering. Children also have a higher surface area 

relative to body weight compared to adults. The 

surface-area-to-body weight ratio for newborn infants 

is more than two times greater than that for adults 

(Cohen-Hubal et al., 1999). Therefore, the dose 

relative to body weight would be greater for a child 

than for an adult with an equal amount of skin exposure 

to a chemical. 

This chapter focuses on measurements of body 

surface area and dermal adherence of solids to the skin. 

These are only two of a several parameters that 

influence dermal absorption. Other factors include the 

concentration of chemical in contact with the skin, 

characteristics of the chemical (i.e., lipophilicity, 

polarity, volatility, solubility), the site of application 

(i.e., the thickness of the stratum corneum varies over 

parts of the body), absorption of chemical through the 

skin and factors that affect absorption (i.e, thickness, 

age, condition), and the amount of chemical delivered 

to the target organ. For guidance on how to use skin 

surface area and dermal adherence factors, as well as 

these other factors to assess dermal exposure, readers 

are referred to Dermal Exposure Assessment: 

Principles and Applications (U.S. EPA, 1992b) and 

Risk Assessment Guidelines for Superfund (RAGs) Part 

E (U.S. EPA, 2004). Frequency and duration of contact 

also affect dermal exposure. Information on activity 

factors is presented in Chapter 17 of this handbook. 

Surface area of the skin can be determined 

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 (DuBois and DuBois, 1916; 

Boyd, 1935; Gehan and George, 1970). 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. A discussion and 

comparison of formulas are presented in Appendix 7A. 

The key studies on body surface area that are presented 

in Section 7.3 of this chapter are based on these 

formulas, and weight and height data from the National 

Health and Nutrition Examination Survey (NHANES). 

Several field studies have been conducted to 

estimate the adherence of solids to skin. These field 

studies consider factors such as activity, gender, age, 

field conditions, and clothing worn. These studies are 

presented in Section 7.4 of this chapter. 

The 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 

Child-Specific Exposure Factors Handbook Page 

September 2008 7-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

recommended values are based on key studies identified 

by U.S. EPA for these factors. Following the 

recommendations, the two key studies on skin surface 

area and the three key studies on dermal adherence of 

solids to skin are summarized. Relevant data on these 

factors are also presented to provide added perspective 

on the state-of-knowledge pertaining to dermal 

exposure factors. 

7.2 RECOMMENDATIONS 

7.2.1 Body Surface Area 

The recommended mean and 95th percentile 

total body surface area values for children are 

summarized in Table 7-1. If gender-specific data or 

data for percentiles other than the mean or 95th 

percentile are needed, the reader is referred to Tables 7­

7 through 7-9 of this chapter. The recommendations for 

total body surface area are based on the U.S. EPA 

analysis of NHANES 1999-2006 data and are presented 

for the standard age groupings recommended by U.S. 

EPA (2005) for male and female children combined. 

The U.S. EPA analysis of NHANES 1999-2006 data 

uses correlations with body weight and height for 

deriving skin surface area (see Section 7.3.1.2 and 

Appendix 7A). NHANES 1999-2006 used a 

statistically-based survey design which should ensure 

that the data are reasonably representative of the 

general population. The recommendations for the 

percentage of total body surface area represented by 

individual body parts are based on data from U.S. EPA 

(1985), and are presented in Table 7-2 (See Section 

7.3.1). Table 7-2 also provides age-specific body part 

surface areas (m2

) that were obtained by multiplying the 

mean body part percentages by the total body surface 

areas presented in Table 7-1. If gender-specific data or 

data for percentiles other than the mean and 95th 

percentile are needed, the body part percentages in 

Table 7-2 may be applied to the total skin surface area 

data in Tables 7-7 through 7-9. 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 

percent of the skin surface is exposed (U.S. EPA, 

1992b). More recent guidance recommends assuming 

100 percent 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 occurs to only 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 

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. 

7.2.2 Adherence of Solids to Skin 

The adherence factor (AF) describes the 

amount of 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. Assessors should refer to the 

activities described in Table 7-12 to select those that 

best represent the exposure scenarios of concern and 

use the corresponding adherence values from Table 7­

13. Table 7-12 lists the age ranges covered by each 

study. This may be used as a general guide to the ages 

covered by these data. Recommended mean AF values 

are summarized in Table 7-4 according to common 

activities involving children. Insufficient data were 

available to develop distributions or probability 

functions for these values. Also, the small number of 

subjects in these studies prevented the development of 

recommendations for the specific age groups 

recommended by U.S. EPA (2005). 

RAGS Part E (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) 

Page Child-Specific Exposure Factors Handbook 

7-2 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

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 percent of the 

arms and lower legs may be assumed to represent 40 

percent 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 (1992b) 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, 1992b). The rate of solids accumulation on skin 

over time has not been well studied, but probably 

occurs fairly quickly. Therefore, pro-rating the 

adherence values for exposure time periods of less than 

one day is not recommended. 

The confidence ratings for these AF 

recommendations are shown in Table 7-5. It should be 

noted that while the recommendations are based on the 

best available estimates of activity-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 

should also be noted that the skin adherence studies 

have 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 dermal adherence 

studies. 

Child-Specific Exposure Factors Handbook Page 

September 2008 7-3 
Table 7-1. Recommended Values for Total Body Surface Area, 

Males and Females Combined 

Age Group 

Mean 95 th Percentile Multiple 

Percentiles Source 

m2 

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 0.53 0.61 See Tables 7-7, U.S. EPA Analysis of 

2 to <3 years 0.61 0.70 7-8, and 7-9 NHANES 1999-2006 data 

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 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Page Child-Specific Exposure Factors Handbook 

7-4 September 2008 
Table 7-2. Recommended Values for Surface Area of Body Parts 

Age Group 

Head Trunk Arms Hands Legs Feet 

Source 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 16.5 35.5 13.0 5.7 23.1 6.3 U.S. EPA, 1985 

2 to <3 years 14.2 38.5 11.8 5.3 23.2 7.1 

3 to <6 years 13.7 31.7 14.2 5.9 27.3 7.3 

6 to <11 years 12.6 34.7 12.7 5.0 27.9 7.2 

11 to <16 years 9.4 33.7 12.9 5.3 31.3 7.5 

16 to <21 years 7.8 32.2 15.3 5.4 32.2 7.1 

Mean Surface Area by Body Part a 

m2 

Birth to <1 month 0.053 0.104 0.040 0.015 0.060 0.019 

1 to <3 months 0.060 0.118 0.045 0.017 0.068 0.021 

3 to <6 months 0.069 0.136 0.052 0.020 0.078 0.025 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

0.082 

0.087 

0.087 

0.104 

0.161 

0.188 

0.235 

0.241 

0.062 

0.069 

0.072 

0.108 

0.024 

0.030 

0.032 

0.045 

0.093 

0.122 

0.142 

0.207 

0.029 

0.033 

0.043 

0.055 

U.S. EPA Analysis 

of NHANES 1999­ 

2006 data and U.S. 

EPA, 1985 

6 to <11 years 0.136 0.375 0.137 0.054 0.301 0.078 

11 to <16 years 0.149 0.536 0.205 0.084 0.498 0.119 

16 to <21 years 0.144 0.592 0.282 0.099 0.592 0.131 

95 th Percentile Surface Area by Body Partb 

m2 

Birth to <1 month 0.062 0.121 0.047 0.018 0.070 0.022 

1 to <3 months 0.069 0.136 0.052 0.020 0.078 0.025 

3 to <6 months 0.080 0.157 0.060 0.023 0.091 0.029 

6 to <12 months 

1 to <2 years 

2 to <3 years 

3 to <6 years 

0.093 

0.101 

0.099 

0.130 

0.182 

0.217 

0.270 

0.301 

0.070 

0.079 

0.083 

0.135 

0.027 

0.035 

0.037 

0.056 

0.105 

0.141 

0.162 

0.259 

0.033 

0.038 

0.050 

0.069 

U.S. EPA Analysis 

of NHANES 1999­ 

2006 data and U.S. 

EPA, 1985 

6 to <11 years 0.186 0.514 0.188 0.074 0.413 0.107 

11 to <16 years 0.194 0.694 0.266 0.109 0.645 0.155 

16 to <21 years 0.182 0.750 0.356 0.126 0.750 0.165 a 

b 

Note: 

Calculated as mean percentage of body part times mean total body surface area. 

Calculated as mean percentage of body part times 95 th percentile total body surface area. 2 2 Surface area values reported in m canbe converted to cm 

2 by multiplying by 10,000 cm2

/m . 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Child-Specific Exposure Factors Handbook Page 

September 2008 7-5 
Table 7-3. Confidence in Recommendations for Body Surface Area 

General Assessment Factors Rationale Rating 

Soundness Medium 

 Adequacy of Approach 

 

Total surface area estimates were based on algorithms developed using 

direct measurements and data from NHANES surveys. Themethods 

used for developing these algorithms were adequate. TheNHANES 

data and the secondary data analyses to estimate total surface areas 

were appropriate. NHANES included a large sample sizes; sample size 

varied with age. Body part percentages were based on direct 

measurements from a limited number of subjects. 

 Minimal (or Defined) Bias The data used to develop the algorithms for estimating surface area 

from height and weight data were limited. NHANEScollected 

physical measurements of weight and height. Bodypart data were 

based on direct measurements from a limited number of subjects. 

Applicability and Utility 

 Exposure Factor of Interest The key studies were directly relevant to surface area estimates. 

Medium 

 Representativeness 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. The sample used to derive body part percentages of 

total surface was not representative of U.S. population. 

 

 Currency The U.S. EPA analysis used the most current data at the time both 

studies were conducted. The data on body part percentages were 

dated; however, the age of the data is not expected to affect its utility. 

 

 DataCollection Period The U.S. EPA analysis was based on four NHANES data sets covering 

1999-2006. 

Clarity and Completeness 

 Accessibility The U.S. EPA analysis of the NHANES data is unpublished, but 

available upon request. U.S. EPA (1985) is a U.S. EPA-published 

report. 

Medium 

 Reproducibility The methodology was clearly presented; enough information was 

included to reproduce the results. 

 Quality Assurance Quality assurance of NHANES data was good; quality control of 

secondary data analysis was not well described. 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Page Child-Specific Exposure Factors Handbook 

7-6 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Table 7-3. Confidence in Recommendations for Body Surface Area (continued) 

General Assessment Factors Rationale Rating 

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, there is uncertainty in the body part 

percentage estimates. 

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. 

There is one key study for total surface area and one key 

study for the surface area of body parts. 

Medium 

Overall Rating Medium for Total 

Surface Area and 

Low for Surface 

Area of Individual 

Body Parts 

Child-Specific Exposure Factors Handbook Page 

September 2008 7-7 
Table 7-4. Recommended Values for Mean Solids Adherence to Skin 

Face Arms Hands Legs Feet 

Source 

mg/cm2 

Residential (indoors)a 

Daycare (indoors & outdoors) b 

Outdoor sportsc 

d Indoor sports

Activities with soil e 

Playing in mud f 

Playing in sediment g 

-

-

0.012 

-

0.054 

-

0.040 

0.0041 

0.024 

0.011 

0.0019 

0.046 

11 

0.17 

0.011 

0.099 

0.11 

0.0063 

0.17 

47 

0.49 

0.0035 

0.020 

0.031 

0.0020 

0.051 

23 

0.70 

0.010 

0.071 

-

0.0022 

0.20 

15 

21 

Holmes et al., 1999 

Holmes et al., 1999 

Kissel et al., 1996a 

Kissel et al., 1996a 

Holmes et al., 1999 

Kissel et al., 1996a 

Shoaf et al., 2005 a 

b 

c 

d 

e 

e 

f 

-

Based on weighted average of geometric mean soil loadings for 2 groups of children (ages 3 to13 years; N = 10) 

playing indoors. 

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. 

Based on geometric mean soil loadings of 6 children (ages >8 years) and 1 adult engaging in Tae Kwon Do. 

Based on geometric mean soil loadings of 8 children (ages 13 to 15 years) playing soccer. 

Based on weighted average of geometric mean soil loadings for gardeners and archeologists (ages 16 to 35 years). 

Based on weighted average of geometric mean solids loading of 2 groups of children (age 9 to 14 years; N= 12) 

playing in mud. 

Based on geometric mean solids loading of 9 children (ages 7 to 12 years) playing in tidal flats. 

= No data. 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

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Child-Specific Exposure Factors Handbook 

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 (4 to 9 children) 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. 

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 

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. 

Medium 

Overall Rating Low 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

7.3	 SURFACE AREA 

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 

The U.S. EPA (1985) summarized the direct 

measurements of the surface area of children's body 

parts provided by Boyd (1935) and Van Graan (1969) 

as a percentage of total surface area. A total of 21 

children less than 18 years of age were included. These 

percentages are presented in Table 7-6. Because of the 

small sample size, it is unclear how accurately these 

estimates represent averages for the age groups. 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. 

7.3.1.2	 U.S. EPA Analysis of NHANES 1999-2006 

Data 

The U.S. EPA estimated total body surface 

areas for children in U.S. EPA’s standard age 

categories, using the empirical relationship shown in 

Appendix 7A and U.S. EPA (1985), and body weight 

and height data from the 1999-2006 NHANES. 

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, noninstitutionalized U.S. population. The 

NHANES 1999-2006 survey was conducted on a 

nationwide probabilitysample 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 anthropometrical measurements were taken 

for each participant in the study, including body weight 

and height. Unit nonresponse to the household 

interview was 19 percent, and an additional 4 percent 

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’ 

web site (http://www.cdc.gov/nchs/about/major/ 

nhanes/nhanes2005-2006/faqs05_06.htm#question%2 

012). 

Table 7-7 presents the mean and percentile 

estimates of body surface area by age category for male 

and female children, combined. Tables 7-8 and 7-9 

present mean and percentiles of body surface area by 

age category for male and female children, respectively. 

An advantage of using the NHANES datasets to derive 

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 under 2 years of age were 

based on recumbent length while standing height 

information was collected 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	 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 to body 

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 two age groups of children (infants aged 0 to 

2 years and children aged 2.1 to 17.9 years). These 

ratios were calculated by dividing body surface areas by 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

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 two age groups and the combined data set. 

Summary statistics for the two children’s age 

groups are presented in Table 7-10. 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 are lognormally 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 gender and age on SA/BW 

distribution was also analyzed by classifying the 

401 observations by gender 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. 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. 

7.3.2.2	 Wong et al., 2000 - Adult Proxy Responses to 

a Survey of Children’s Dermal Soil Contact 

Activities 

Wong et al. (2000) reported on two surveys 

that gathered information on activity patterns related to 

dermal contact with soil. The first of these national 

phone surveys (also reported on by Garlock et al., 

1999) was conducted in 1996 using random digit 

dialing. Information about children was gathered from 

adults over the age of 18, and obtained information on 

211 children. 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 old, 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 

though October) was obtained. The results of this 

survey indicate 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. These estimates are 

provided in Table 7-11. 

7.4	 ADHERENCE OF SOLIDS TO SKIN 

7.4.1	 Key Adherence of Solids to Skin Studies 

7.4.1.1	 Kissel et al., 1996a - Field Measurements of 

Dermal Soil Loading Attributable to Various 

Activities: Implications for Exposure 

Assessment 

Kissel et al. (1996a) 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 karate, 

soccer, rugby, reed gathering, irrigation installation, 

truck farming, and playing in mud. Skin surface areas 

monitored included hands, forearms, lower legs, faces 

and/or feet (Kissel et al., 1996a). 

Several of the activities studied by Kissel et al. 

(1996a) involved children, as shown in Table 7-12. A 

group of young male soccer players (Soccer) was 

monitored before and after 40 minutes of practice on a 

field consisting of half grass and half bare earth. Six 

children were monitored after 10 and 20 minutes of 

playing in the mud at a lake with an exposed shoreline 

(Kids-in-mud No. 1 and No. 2). For indoor activities, 

soil loadings were estimated from six children and one 

adult practicing tae kwon do (Tae Kwon Do); the 

activity lasted 90 minutes including a 30-min warm up. 

Information on activity duration, sample size and 

clothing worn by participants is provided in Table 7-12. 

The subjects’ body surfaces (forearms, hands, lower 

legs for all sample groups; faces and/or feet pairs 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 using allometric models of surface area. 

Geometric means for post-activity soil 

adherence by activity and body region for the four 

groups of volunteers evaluated are presented in Table 

7-13. Children playing in the mud had the highest soil 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

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 in the study. 

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 postactivity 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 (aged 16 to 35) removing historical 

artifacts from a site (Archeologists), and individuals 

(aged 16 to 35) performing gardening work 

(Gardeners). This study was conducted as a follow up 

to previous field sampling of soil adherence on 

individuals participating in various activities (Kissel et 

al., 1996a). For this round of sampling, soil loading 

data were collected utilizing the same methods used and 

described in Kissel et al. (1996a). Information 

regarding the groups studied and their observed 

activities is presented in Table 7-12. 

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. The 

backyard was described as having a grass lawn, shed, 

sand box, and wood chip box. In this setting, the 

children engaged in typical activities including: playing 

with toys and each other, wrestling, sleeping, and 

eating. The number of children within each day’s group 

and the clothing worn is described in Table 7-12. The 

five children measured on the first day were washed 

first thing in the morning to establish a preactivity level. 

They were next washed at noon to determine the 

postactivity soil loading for the morning (Daycare Kids 

No. 1a). The same children were washed once again at 

the close of the day for measurement of soil adherence 

from the afternoon play activities (Daycare Kids No. 

1b). For the second observation day (Daycare Kids No. 

2), postactivity 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 second 

group (Indoor Kids No. 2) had six children. The play 

area was described by the authors as being primarily 

carpeted. The clothing worn by the children within 

each day’s group is described in Table 7-12. 

Seven individuals (Archeologists), ages 16 to 

35 years, were monitored while excavating, screening, 

sorting, and cataloging historical artifacts from an 

ancient Native American site during a single event. 

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). The clothing worn by these 

groups is described in Table 7-12. 

The geometric means and standard deviations 

of the postactivity soil adherence for each group of 

individuals and for each body part are summarized in 

Table 7-13. 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., 1996a). 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., 2005 - Child Dermal Sediment 

Loads Following Play in a Tide Flat 

The purpose of this study was to obtain 

sediment adherence data for children playing in a tidal 

flat (Shoreline Play). The study was conducted on one 

day in late September 2003 at a tidal flat in Jamestown, 

Rhode Island. Nine subjects (three females and six 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

males) ages 7 to 12 years old participated in the study. 

Information on activity duration, sample size and 

clothing worn by participants is provided in Table 7-12. 

Participants’ parents completed questionnaires 

regarding 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 7-13, were 0.04 (2.9), 0.17 

(3.1), 0.49 (8.2), 0.70 (3.6) and 21 (1.9), respectively. 

The primary advantage of this study is that it 

provides adherence data specific to children and 

sediments which had previously 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 (9) and sampling during just one 

day and at one location, make extrapolation to other 

situations uncertain. 

7.4.2	 Relevant Adherence of Solids to Skin 

Studies 

7.4.2.1	 Kissel et al., 1996b - Factors Affecting Soil 

Adherence to Skin in Hand-press Trials: 

Investigation of Soil Contact and Skin 

Coverage 

Kissel et al. (1996b) conducted soil adherence 

experiments using five soil types obtained locally in the 

Seattle, WA, area: sand, 2 types of loamy sand, sandy 

loam, and silt loam. All soils were analyzed by 

hydrometer (settling velocity) to determine 

composition. Clay content ranged from 0.5 to 7.0 

percent. Organic carbon content, determined by 

combustion, ranged from 0.7 to 4.6 percent. 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, 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 

total hand area, 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. 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. 

7.4.2.2	 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, which included a group of 

children, 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 preactivity and postactivity were obtained from the 

different body parts examined. 

The studied group of children played for 20 

minutes in a soil bed of varying moisture content 

representing wet and dry soils. Three trials with 

children were conducted, each representing a different 

clothing/soil moisture scenario. For wet soils, both 

combinations of long sleeves and long pants, and short 

sleeves and short pants were tested. For dry soil, only 

short sleeves and short pants were worn during play. 

Clothing was laundered after each trial. The parameters 

describing each of these trials are summarized in Table 

7-14. Before each trial, each child was washed in order 

to obtain a preactivity or background gravimetric 

measurement. 

For wet soil, postactivity fluorescence results 

indicated that the hand had a much higher fractional 

coverage than other body surfaces (see Figure 7-1). No 

fluorescence was detected on the forearms or lower legs 

of children dressed in long sleeves and pants. As 

shown in Figure 7-2, postactivity gravimetric 

measurements showed higher soil loading on hands and 

much lower amounts on other body surfaces, as was 

observed with fluorescence data. According to Kissel 

et al. (1998), the relatively low loadings observed on 

non-hand body parts may be a result of a more limited 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

area of contact for the body part rather than lower 

localized loadings. The highest soil loading observed 

was a geometric mean dermal loading of 0.7 mg/cm2

, 

found on the children’s hands following play in wet 

soil. 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 a short activity 

duration. 

7.5	 REFERENCES FOR CHAPTER 7 

Boyd, E. (1935) The growth of the surface area of the 

human body. Minneapolis, MN: University 

of Minnesota Press. 

Buyken, A.E.; 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 29:24-28. 

Cohen-Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; 

McLundy, T.R.; Berry, M.R.; Rigas, M.L.; 

Zartarian, V.G.; Freeman, N.C.G. (1999) 

Children’s exposure assessment: A review of 

factors influencing children’s exposure, and 

the data available to characterize and assess 

that exposure. Research Triangle Park, NC: 

U.S. EPA, National Exposure Research 

Laboratory. 

D'Agostino, R.B.; Belanger, A.; D'Agostino, R.B. Jr. A 

suggestion for using powerful and informative 

tests of normality. The American Statistician 

44(4):316-321. 

Dubois, D.; Dubois, E.F. (1916) A formula to estimate 

the approximate surface area if height and 

weight be known. Arch Intern Med 17:863­

871. 

Garlock, T.J.; Shirai, J.H.; Kissel, J.C.	 (1999) Adult 

responses to a survey of soil contact related 

behaviors. J Expo Anal Environ Epidemiol 

9:134-142. 

Gehan, E.; George, G.L. (1970) Estimation of human 

body surface area from height and weight. 

Cancer Chemother Rep 54(4):225-235. 

George, S.L.; Gehan, E.A.; Haycock, G.B.; Schwartz, 

G.J. (1979) Letters to the editor. J Pediatr 

94(2):342. 

Holmes, Jr., K.K.; Shirai, J.H.; Richter, K.Y.; Kissel, 

J.C. (1999) Field measurement of dermal 

loadings in occupational and recreational 

activities. Environ Res Section A 80:148-157. 

Kissel, J.C.; Richter, K.; Fenske, R. (1996a) Field 

measurements of dermal soil loading 

attributable to various activities: Implications 

for exposure assessment. Risk Anal 

16(1):116-125. 

Kissel, J.C.; Richter, K.; Duff, R.; Fenske, R. (1996b) 

Factors affecting soil adherence to skin in 

hand-press trials. Bull Environ Contam 

Toxicol 56:722-728. 

Kissel, J.C.; Shirai, J.H.; Richter, K.Y.; Fenske, R.A. 

(1998) Investigation of dermal contact with 

soil in controlled trials. J Soil Contam 7(6): 

737-752. 

Phillips, L.J.; Fares, R.J.; Schweer, L.G. (1993) 

Distributions of total skin surface area to body 

weight ratios for use in dermal exposure 

assessments. J Expo Anal Environ Epidemiol 

3(3):331-338. 

Shoaf, M.B.;	 Shirai, J.H.; Kedan, G.; Schaum, J.; 

Kissel, J.C. (2005) Child dermal sediment 

loads following play in a tide flat. J Expo 

Anal Environ Epidemiol 15:407-412. 

U.S.	 EPA (1985) Development of statistical 

distributions or ranges of standard factors used 

in exposure assessments. Washington, DC: 

Office of Research and Development, Office 

of Health and Environmental Assessment. 

EPA 600/8-85-010. Available from: NTIS, 

Springfield, VA. PB85-242667. 

U.S. EPA (1992a) Guidelines for exposure assessment. 

Federal Register. FR 57:104:22888-22938. 

May 29, 1992. 

U.S.	 EPA (1992b) Dermal exposure assessment: 

principles and applications. Washington, DC: 

Office of Research and Development, Office 

o f H e a l t h a n d E n v i r o n m e n t a l 

Assessment/OHEA. U.S. EPA/600/8-9-91. 

U.S.	 EPA (2004) Risk assessment guidance for 

Superfund (RAGS): Volume I, Human Health 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Evaluation Manual, Part E. Washington, DC. 

EPA/540/R/99/005. 

U.S. EPA (2005) Guidance on selecting age groups for 

monitoring and assessing childhood exposures 

to environmental contaminants. U.S. 

Environmental Protection Agency, 

Washington, DC. EPA/630/P-03/003F. 

November 2005. 

Van Graan, C.H. (1969) The determination of body 

surface area. S Afr Med J 43(31):952-959. 

Wong, E.Y.; Shirai, J.H.; Garlock, T.J.; Kissel, J.C. 

(2000) Adult proxy responses to a survey of 

children’s dermal soil contact activities. J 

Expo Anal Environ Epidemiol 10:509-517. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 7-15
 
 

Table 7-6. Percentage of Total Body Surface Area by Body Part For Children 

Males and Females Combined 

Percent of Total 

Age 

(years) N M:F Head Trunk Arms Hands Legs F

Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max Mean 

< 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 

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 

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 

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 

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 

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 

N = Number of subjects, (M:F = males:females). Min. = Minimum percent. Max. = Maximum percent. Source: U.S. EPA, 1985. 

Page Child-Specific Exposure Factors Handbook 

7-16 September 2008 
Table 7-7. Mean and Percentile Skin Surface Area (m 2

) Derived from U.S. EPA Analysis of 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 

154 

281 

488 

923 

1159 

1122 

2303 

3590 

5294 

4843 

0.29 

0.33 

0.38 

0.45 

0.53 

0.61 

0.76 

1.08 

1.59 

1.84 

0.24 

0.27 

0.33 

0.38 

0.45 

0.52 

0.61 

0.81 

1.19 

1.47 

0.25 

0.29 

0.34 

0.39 

0.46 

0.54 

0.64 

0.85 

1.25 

1.53 

0.26 

0.29 

0.35 

0.40 

0.47 

0.55 

0.66 

0.88 

1.31 

1.58 

0.27 

0.31 

0.36 

0.42 

0.49 

0.57 

0.68 

0.93 

1.4 

1.65 

0.29 

0.33 

0.38 

0.45 

0.53 

0.61 

0.74 

1.05 

1.57 

1.80 

0.31 

0.35 

0.40 

0.48 

0.56 

0.64 

0.81 

1.21 

1.75 

1.99 

0.31 

0.37 

0.42 

0.49 

0.58 

0.67 

0.85 

1.31 

1.86 

2.10 

0.33 

0.37 

0.43 

0.50 

0.59 

0.68 

0.89 

1.36 

1.94 

2.21 

0.34 

0.38 

0.44 

0.51 

0.61 

0.70 

0.95 

1.48 

2.06 

2.33 

N 

Source: 

= Number of observations. 

U.S. EPA Analysis of NHANES 1999-2006 data. 

Table 7-8. Mean and Percentile Skin Surface Area (m 2) Derived from U.S. EPA Analysis of NHANES 1999-2006
 

Males
 

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 

85 

151 

255 

471 

620 

548 

1150 

1794 

2593 

2457 

0.29 

0.33 

0.39 

0.45 

0.53 

0.62 

0.76 

1.09 

1.61 

1.94 

0.24 

0.28 

0.34 

0.39 

0.46 

0.54 

0.61 

0.82 

1.17 

1.61 

0.25 

0.29 

0.35 

0.41 

0.47 

0.56 

0.64 

0.86 

1.23 

1.66 

0.26 

0.30 

0.36 

0.42 

0.48 

0.56 

0.66 

0.89 

1.28 

1.7 

0.27 

0.31 

0.37 

0.43 

0.50 

0.58 

0.69 

0.94 

1.39 

1.76 

0.29 

0.34 

0.39 

0.46 

0.53 

0.62 

0.75 

1.06 

1.60 

1.91 

0.31 

0.36 

0.41 

0.48 

0.57 

0.65 

0.82 

1.21 

1.79 

2.08 

0.33 

0.37 

0.42 

0.49 

0.58 

0.67 

0.86 

1.29 

1.90 

2.22 

0.34 

0.37 

0.43 

0.50 

0.59 

0.68 

0.89 

1.34 

1.99 

2.30 

0.36 

0.38 

0.44 

0.51 

0.62 

0.70 

0.95 

1.46 

2.12 

2.42 

N 

Source: 

= Number of observations. 

U.S. EPA Analysis of NHANES 1999-2006 data. 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Child-Specific Exposure Factors Handbook Page
 

September 2008 7-17
 
Table 7-9. Mean and Percentile Skin Surface Area (m 2

) Derived from U.S. EPA Analysis of NHANES 1999-2006
 

Females
 

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 

69 

130 

233 

452 

539 

574 

1153 

1796 

2701 

2386 

0.28 

0.32 

0.38 

0.44 

0.52 

0.60 

0.75 

1.08 

1.57 

1.73 

0.24 

0.27 

0.32 

0.38 

0.44 

0.51 

0.61 

0.80 

1.20 

1.42 

0.25 

0.28 

0.33 

0.39 

0.46 

0.53 

0.64 

0.85 

1.28 

1.47 

0.26 

0.29 

0.34 

0.40 

0.47 

0.54 

0.66 

0.87 

1.34 

1.51 

0.27 

0.30 

0.35 

0.41 

0.48 

0.56 

0.68 

0.92 

1.42 

1.57 

0.28 

0.31 

0.38 

0.44 

0.52 

0.59 

0.74 

1.04 

1.55 

1.69 

0.30 

0.35 

0.40 

0.47 

0.56 

0.63 

0.80 

1.21 

1.69 

1.85 

0.30 

0.36 

0.40 

0.48 

0.57 

0.66 

0.84 

1.33 

1.8 

1.98 

0.31 

0.37 

0.41 

0.49 

0.58 

0.67 

0.88 

1.39 

1.88 

2.06 

0.33 

0.37 

0.43 

0.51 

0.59 

0.70 

0.94 

1.51 

2.00 

2.17 

N 

Source: 

= Number of observations. 

U.S. EPA Analysis of NHANES 1999-2006 data. 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Page Child-Specific Exposure Factors Handbook 

7-18 September 2008 
 

Table 7-10. Descriptive Statistics For Surface Area/Body Weight (SA/BW) Ratios (m2/kg) Age (years) Mean Range Min-Max SD SE 

5th 10th 25th 

Percentiles 

50th 75th 90th 

0 to 2 0.064 0.042-0.114 0.011 0.001 0.047 0.051 0.056 0.062 0.072 0.0784 0.

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 0.0501 0.

SD SE 

= Standard deviation. = Standard error of the mean. 

Source: Phillips et al., 1993. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 7-19
 
Table 7-11. Estimated Skin Surface Exposed During Warm Weather Outdoor Activities 

Age (years) 

N 

Skin Area Exposed (% of total body surface area) 

Play Gardening/yardwork Organized Team Sport 

<5 

41 

5-17 5-17 

437 65 

Mean 38.0 33.8 29.0 

Median 36.5 33.0 30.0 

SD 6.0 8.3 10.5 

N 

SD 

= Number of observations. 

= Standard deviation. 

Source: Wong et al., 2000. 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Page Child-Specific Exposure Factors Handbook 

7-20 September 2008 
 

Table 7-12. Summary of Field Studies Activity Month Eventa (hrs) N M F Age (years) Conditions Clothing 

Indoor Tae Kwon Do Feb. 1.5 7 6 1 8-42 Carpeted floor All in long sleeve-long pants martial arts uniform, sleeves rolled back, barefoot K

19

Indoor Kids No. 1 Jan. 2 Indoor Kids No. 2 Feb. 2 Daycare Kids No. 1a Aug. 3.5 Daycare Kids No. 1b Aug. 4 Daycare Kids No. 2b Sept. 8 Daycare Kids No. 3 Nov. 8 4 6 6 6 5 4 3 4 5 5 4 3 1 6-13 Playing on carpeted floor 2 3-13 Playing on carpeted floor 1 1-6.5 Indoors: linoleum surface; Outdoors: grass, bare earth, barked area 1 1-6.5 Indoors: linoleum surface; Outdoors: grass, bare earth, barked area 1 1-4 Indoors: low napped carpeting, linoleum surfaces 1 1-4.5 Indoors: linoleum surface, 

Outside: grass, bare earth, barked area 

3 of 4 short pants, 2 of 4 short sleeves, socks, no shoes 

H19

5 of 6 long pants, 5 of 6 long sleeves, socks, no shoes 4 of 6 in long pants, 5 of 6 short sleeves, socks, shoes 4 of 6 long pants, 5 of 6 short sleeves, 3 of 6 barefoot all afternoon, others barefoot half the afternoon 4 of 5 long pants, 3 of 5 long sleeves, all barefoot for part of the day All long pants, 3 of 4 long sleeves, socks and shoes 

Outdoor 

Soccer Nov. 0.67 Kids-in-mud No. 1 Sept. 0.17 Kids-in-mud No. 2 Sept. 0.33 

8 6 6 

8 5 5 

0 13-15 Half grass-half bare earth 1 9-14 Lake shoreline 1 9-14 Lake shoreline 

6 of 8 long sleeves, 4 of 8 long pants, 3 of 4 short pants and shin guards 

K19

All in short sleeve T-shirts, shorts, barefoot All in short sleeve T-shirts, shorts, barefoot 

Gardeners Aug. 4 Archeologists July 11.5 

8 7 

1 3 

7 16-35 Weeding, pruning, digging a 

trench 

4 16-35 Digging with trowel, 

screening dirt, sorting 

6 of 8 long pants, 7 of 8 short sleeves, 1 sleeveless, socks, shoes, intermittent use of gloves 

H19

6 of 7 short pants, all short sleeves, 3 no shoes or socks, 2 sandals 

Shoreline Play Sept. 0.33-1.0 9 6 3 7-12 Tidal flat No shirt or short sleeve T-shirts, 

shorts, barefoot 

Sh20

a Event duration. b Activities were confined to the house. 

N = Number of subjects. M = Male. F = Female. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 7-21
 
Table 7-13. Geometric Mean and Geometric Standard Deviations of Solids Adherence by 

Activity and Body Region a 

Activity N Post-activity Dermal Solids Loadings (mg/cm 2

)

Hands Arms Legs Faces Feet 

Indoor 

Tae Kwon Do 7 0.0063 0.0019 0.0020	 0.0022 

1.9 4.1 2.0	 2.1 

Indoor Kids No. 1 4 0.0073 0.0042 0.0041	 0.012 

1.9 1.9 2.3	 1.4 

Indoor Kids No. 2 6 0.014 0.0041 0.0031	 0.0091 

1.5 2.0 1.5	 1.7 

Daycare Kids No. 1a 6 0.11 

1.9 

0.026 

1.9 

0.030	 

1.7	 

0.079 

2.4 

Daycare Kids No. 1b 6 0.15 

2.1 

0.031 

1.8 

0.023	 

1.2	 

0.13 

1.4 

Daycare Kids No. 2 5 0.073 

1.6 

0.023 

1.4 

0.011	 

1.4	 

0.044 

1.3 

Daycare Kids No. 3 4 0.036 

1.3 

0.012 

1.2 

0.014	 

3.0	 

0.0053 

5.1 

Outdoor 

Soccer	 8 0.11 0.011 0.031 0.012 

1.8 2.0 3.8 1.5 

Kids-in-mud No. 1 6 35 11 36	 24 

2.3 6.1 2.0	 3.6 

Kids-in-mud No. 2 6 58 11 9.5	 6.7 

2.3 3.8 2.3	 12.4 

Gardeners 8 0.20 0.050 0.072 0.058 0.17 

1.9 2.1 -- 1.6 -­

Archeologists 7 0.14 

1.3 

0.041 

1.9 

0.028 

4.1 

0.050 

1.8 

0.24 

1.4 

Shoreline Play 9 0.49 

8.2 

0.17 

3.1 

0.70 

3.6 

0.04 

2.9 

21 

1.9 

a	 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., 1996a; Holmes et al., 1999; Shoaf et al., 2005. 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Page Child-Specific Exposure Factors Handbook 

7-22 September 2008 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Table 7-14. Summary of Controlled Greenhouse Trials - Children Playing 

Activity Ages 

(years) 

Duration (min) Soil Moisture 

(%) 

Clothinga N Male Female 

Playing 8 to 12 20 17-18 

16-18 

3-4 

L 

S 

S 

4 

9 

5 

3 

5 

3 

1 

4 

2 

a L, long sleeves and long pants; S, short sleeves and short pants. 

N = Number of subjects. 

Source: Kissel et al., 1998. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 7-23
 
 

 

 

Figure 7-1.	 Skin Coverage as Determined by Fluorescence vs. Body Part for Children Playing in Wet 

Soils (bars are arithmetic means and corresponding 95% confidence intervals) 

Source: Kissel et al., 1998. 

 

 

 

Figure 7-2. Gravimetric Loading vs. Body Part for Children Playing in Wet and Dry Soils (symbols are 

geomettric means and 95% confidence intervals) 

Source: Kissel et al., 1998. 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Page Child-Specific Exposure Factors Handbook 

7-24 September 2008 
 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

APPENDIX 7A
 

FORMULAS FOR TOTAL BODY SURFACE AREA
 

Child-Specific Exposure Factors Handbook Page
 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

APPENDIX 7A - FORMULAS FOR TOTAL 

BODY SURFACE AREA 

Most formulas for estimating surface area (SA) 

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 the above 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 DuBois and DuBois 

(1916). Their model can be written: 

SA = a 1 2 (Eqn. 7A-2) 0Ha Wa 

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 Dubois 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 (1981) are based on the 

DuBois and DuBois formula. In addition, a 

computerized literature search conducted for this report 

identified several articles written in the last 10 years in 

which the DuBois and DuBois formula was used to 

estimate body surface area. 

Boyd (1935) developed new constants for the 

DuBois and DuBois 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 DuBois and DuBois 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 DuBois and DuBois formula 

based on height and weight. 

Gehan and George (1970) proposed another 

set of constants for the DuBois and DuBois 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 SA is: 

SA = 0.02350 H0.42246W0.51456 (Eqn. 7A-3) 

or in logarithmic form: 

lnSA = -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 percent 

of the variations in surface area among the 401 

individuals measured (Gehan and George, 1970). 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

The equation proposed by Gehan and George 

(1970) was determined by the U.S. EPA (1985) as 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 Dubois and Dubois (1916) and the Statistical 

Processing System (SPS) software package to obtain 

the standard error. 

The Dubois and Dubois (1916) formula uses 

weight and height as independent variables to predict 

total body surface area (SA), and can be written as: 

a SA 1 a 2

i = a 0Hi Wi ei (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 H0.417W0.517 (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 percent of the total 

variation in surface area among the observations, and 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 

percent 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 percent. Of these, 12 

weighed less than 15 pounds each, 1 was overweight (5 

feet 7 inches, 172 pounds), 1 was very thin (4 feet 11 

inches, 78 pounds), and 4 were of average build. Since 

the same observer measured surface area for these 4 

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. The different values for the constants 

are presented in Table 7A-1. 

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 square meter, 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 DuBois and DuBois 

model. Their interest in making the DuBois and 

DuBois model more accurate resulted from their work 

in pediatrics and the fact that DuBois and DuBois 

(1916) 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 2 hospitals (19 

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Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

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 white 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 coefficients: a0 = 

0.024265, a1 = 0.3964, and a2 = 0.5378. The result was 

the following equation for estimating surface area: 

SA = 0.024265H0.3964W0.5378 (Eqn. 7A-9) 

expressed logarithmically as: 

ln SA = ln 0.024265 + 0.3964 ln H + 0.5378 ln W 

(Eqn. 7A-10) 

The coefficients 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 DuBois and DuBois 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 DuBois and DuBois model 

that are different than those originally postulated in 

1916. The DuBois and DuBois model can be written 

logarithmically as: 

lnSA = lna0 + a1 lnH + a2 lnW (Eqn. 7A-11) 

The values for a0, a1, and a2 obtained by the 

various authors discussed in this section are presented 

in Table 7A-2. 

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 since 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 DuBois and DuBois (1916). Because 

the Sendroy and Cecchini method is graphical, it is 

inherently less precise and less accurate than the 

formulas of other authors discussed above. 

REFERENCES FOR APPENDIX 7A 

Boyd, E. (1935) The growth of the surface area of 

the human body. Minneapolis, MN: University of 

Minnesota Press. 

Dubois, D.; Dubois, E.F. (1916) A formula to 

estimate the approximate surface area if height and 

weight be known. Arch Intern Med 17:863-871. 

Gehan, E.; George, G.L. (1970) Estimation of human 

body surface area from height and weight. Cancer 

Chemother Rep 54(4):225-235. 

Geigy Scientific Tables (1981) Nomograms for 

determination of body surface area from height and 

mass. Lentner, C. (ed.). CIBA-Geigy Corporation, 

West Caldwell, NJ. pp. 226-227. 

Haycock, G.B.; Schwartz, G.J.; Wisotsky, D.H. 

(1978) Geometric method for measuring body surface 

area: A height-weight formula validated in infants, 

children, and adults. J Pediatr 93(1):62-66. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 7A-4
 
 

 

 

 

 

 

 

Table 7A-2. Summary of Surface Area Parameter Values for the Dubois and Dubois Model 

Author Number 

(year) of persons a0 a1 a2 

DuBois and DuBois (1916) 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 

Child-Specific Exposure Factors Handbook 

Chapter 7 - Dermal Exposure Factors 

Sendroy, J.; Cecchini, L.P. (1954) Determination of 

human body surface area from height and 

weight. J Appl Physiol 7(1):3-12. 

Table 7A-1. Estimated Parameter Values for Different Age Intervals 

Age 

Group 

Number 

of persons a0 a1 a2 

All ages 

<5 years old 

$5 to <20 years old 

$20 years old 

401 0.02350 0.42246 

229 0.02667 0.38217 

42 0.03050 0.35129 

30 0.01545 0.54468 

0.51456 

0.53937 

0.54375 

0.46336 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

8 BODY WEIGHT STUDIES 

8.1 INTRODUCTION 

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). 

The purpose of this section is to describe a key 

published study on body weight for children in the 

general U.S. population, as described in Section 1.5 of 

this handbook. 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. EPA for this factor. Following the 

recommendations, the key study on body weight is 

summarized. Relevant data on body weight are also 

provided. Since childhood obesity is a growing 

concern and may increase the risk of chronic diseases 

during adulthood, information on body mass index 

(BMI) and height are also provided. 

8.2 RECOMMENDATIONS 

The recommended values for body weight are 

summarized in Table 8-1. Table 8-2 presents the 

confidence ratings for body weight recommendations. 

The recommended values represent mean body weights 

in kilograms for the age groups recommended by U.S. 

EPA in Guidance for Monitoring and Assessing 

Childhood Exposures to Environmental Contaminants 

(U.S. EPA, 2005). 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 nonconservative approach. However, distributions of body 

weight data are provided in section 8.3 of this chapter. 

These distributions may be useful if probabilistic 

methods are used to assess exposure. Also, if genderspecific data are needed, or if data for finer age bins are 

needed, the reader should refer to the tables in Section 

8.3. 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-1. Recommended Values for Body Weight 

Age Group 

Mean Multiple 

Percentiles Source 

kg 

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 

4.8 

Tables 8-3 

through 8-5 

U.S. EPA analysis of 

NHANES, 1999-2006 

data 

5.6 

7.4 

9.2 

11.4 

13.8 

18.6 

31.8 

56.8 

71.6 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

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 secondary data analysis 

analysis was 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 4 data sets of 

NHANES data covering 1999-2006. 

High 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

NHANES data are available from NCHS; the U.S. EPA 

analysis of the NHANES data is available upon request. 

The methods used were well-described; enough information 

was provided to allow for reproduction of results. 

Quality assurance of NHANES data was good; quality 

control of secondary data analysis was not well described. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

The full distributions were given in the key study. 

No significant uncertainties 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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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

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 National Health and Nutrition Examination 

Survey (NHANES) to generate distributions of body 

weight for various age ranges of children. 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, noninstitutionalized 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 percent, and an additional 

4 percent 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' 

we b s i t e 

(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 

body weight statistics for the standard age categories. 

The mean value for a given group was calculated using 

the following formula: 

where: 

x = sample mean; 

xi = the i

th observation; 

wi = sample weight assigned to observation 

xi

. 

Percentile values were generated by first 

calculating the sum of the 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 weight, equal to its own weight plus all 

weights listed before the observation. The first 

observation listed with a cumulative 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 male and female 

children, combined. Tables 8-4 and 8-5 present the body 

weight means and percentiles for male and female 

children, respectively. 

The advantage of this study is that it provides 

body weight distributions for children at ages ranging 

from infancy to young adults. A limitation of the study 

is that the data in Tables 8-3 to 8-5 may underestimate 

current body weights due to an observed upward trend in 

body weights (Ogden et al., 2004). However, 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 BODY WEIGHT STUDIES 

8.4.1	 National Center for Health Statistics, 1987 ­

Anthropometric reference data and 

prevalence of overweight, United States, 

1976-80 

This study used anthropometric measurement 

data for body weight for the U.S. population that were 

collected by NCHS as part of the second 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 6 

months to 74 years from the civilian, noninstitutionalized 

population of the United States. A total of 20,322 

individuals in the sample were interviewed and 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

examined, resulting in a response rate of 73.1 percent. 

The sample was selected so that certain subgroups 

thought to be at high risk of malnutrition (persons with 

lowincomes, preschool 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, 

adjusted 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 

(NCHS, 1987). NCHS (1987) provided descriptive 

statistics of the body weight data. Means and 

percentiles, by age category, are presented in Table 8­

6 for males, and in Table 8-7 for females. 

The advantages of the study are that it is 

nationally representative and provides data for various 

age groups of children, beginning at 2 months of age. 

The limitation of the study is the age of the data. 

8.4.2	 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 

the second survey of the National Center for Health 

Statistics, NHANES II, which was based on a national 

probability sample of 27,801 persons 6 months to 74 

years of age in the U.S. (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 of children and teens, 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 gender across all age groups. The statistics 

for the lognormal probability plots for female and male 

children aged 9 months to 20 years are presented in 

Tables 8-8 and 8-9, respectively. 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 6 months to 20 years old. However, the 

analysis is based on an older set of NHANES data. 

8.4.3	 U.S. EPA, 2000 - Body weight estimates on 

NHANES III Data 

U.S. EPA’s Office of Water has estimated body 

weights for children by age and gender using data from 

NHANES III, which was conducted from 1988 to 1994. 

NHANES III collected body weight data for 

approximately 15,000 children between the ages of 2 

months and 17 years. Table 8-10 presents the body 

weight estimates in kilograms by age and gender. Table 

8-11 shows the body weight estimates for infants under 

the age of 3 months. 

The limitations of this analysis are that data 

were not available for infants under 2 months old, and 

that the data are roughly 14 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 Tables 8-10 and 8-11 may underestimate current body 

weights. However, the data are national in scope and 

represent the general children’s population. 

8.4.4	 Kuczmarski et al., 2002 - 2000 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 (1963-65) for ages 6-11 years, NHES 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

III (1966-70) for ages 12-17 years, National Health 

and Nutrition Examination Survey (NHANES) I 

(1971-74) for ages 1-17 years, NHANES II (1976-80) 

beginning at 6 months of age, and NHANES III (1988­

94) 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 gender and age. Figures 8-1 and 8-2 present weight 

by age percentiles for boys and girls, aged birth to 36 

months, respectively. Figures 8-3 and 8-4 present 

weight by length percentiles for boys and girls, 

respectively. Figures 8-5 and 8-6 provide the Body 

Mass Index (BMI) for boys and girls aged 2 to 20 

years old. 

A limitation of this analysis is that trends in 

the weight data cannot be assessed because data from 

various years were combined. 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 month-by-month basis up 

to 36 months of age, as well as BMI data for children 

through age 20 years. 

8.4.5	 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 National Health Examination 

Surveys II and III (NHES II and III), the National 

Health and Nutrition Examination Surveys I, II, and III 

(NHANES I, II, and III), and NHANES 1999-2002. 

The surveys covered the period from 1960 to 2002. 

Table 8-13 presents the measured body weights for 

various age groups as measured in NHES and NHANES. 

Tables 8-14 and 8-15 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. Because this study is based on an analysis of 

NHANES data, its limitations are the same as those for 

that study. However, it serves to illustrate the 

importance of the use of timely data when analyzing 

body weight. 

8.4.6	 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 to 1974), NHANES 

II (1976- 1980), NHANES III (1988 to 1994) and 

NHANES 1999-2002. The analyses included children 2 

to 17 years olds. 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 nonHispanic 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 BMIfor-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 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

response, and non-coverage. The sample sizes used in 

the analyses by age, race and survey are presented in 

Table 8-16. Mean BMI levels are provided in Table 

8-17 and the prevalence of overweight and obesity is 

shown in Table 8-18. Table 8-17 shows that in 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 8-18 

shows 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 2 

to 5 years old children. 

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. 

8.4.7	 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 U.S. Low birth weight 

was defined as <2,500 grams (<5 pounds 8 ounces) 

and very low birth weight was defined as <1,500 

grams (<3 pounds 4 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

19. 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 percent) 

and very low birth weights (3.3 percent). Martin et al. 

(2007) also provided statistics on the numbers and 

percentages of pre-term live births in the U.S. Of the 

4,138,349 live births in the U.S. in 2005, 522,913 were 

defined as pre-term (i.e., less than 37 weeks gestation). 

A total of 43.3 percent of these pre-term infants had low 

birth weights an 11.3 percent had very low birth weights. 

The advantage of this data set is that it is nationally 

representative and provides data for infants. 

8.4.8	 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 was 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 gender and various age 

brackets (Portier et al., 2007). The estimated mean body 

weights are shown in Tables 8-20, 8-21, and 8-22 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). The authors noted that the age groups are defined 

as starting at the birth month and include the next eleven 

months (i.e., age group 2 includes children 24-35 months 

at the time of the health assessment). Table 8-23 

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 genders and for 

single-year age groups. The study results are also based 

on a large sample size. 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

8.4.9	 Kahn and Stralka, 2008 - 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 

As part of an analysis of water ingestion, 

Kahn and Stralka (2008) provided body weight 

distributions for children. The analysis was based on 

self reported body weights from the 1994 - 1996, 1998 

Continuing Survey of Food Intake Among Individuals 

(CSFII). The average body weight across all 

individuals was 65 kilograms. According to Kahn and 

Stralka (2008), 10 kilograms, 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 

kilograms for the 6 to 12 month age category and 11 

kilograms for the 1 to 2 year old category (Kahn and 

Stralka, 2008). The body weight distributions are 

presented in Table 8-24 and the intervals around the 

mean and 90th and 95th percentiles are presented in 

Table 8-25. 

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. 

8.5	 RELEVANT FETAL WEIGHT STUDIES 

8.5.1	 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 2 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 pre-eclampsia, 

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, Ohio from 1962 to 1969. 

Percentiles for fetal weight were calculated 

from the data at each week of gestation and are shown in 

Table 8-26. The resulting percentile curves were 

smoothed with two-point weighted means. Variables 

associated with significant differences in fetal weight in 

the latter part of pregnancy (after 34-38 weeks of 

gestation) included maternal parity and race, and fetal 

gender. 

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 which may affect fetal 

weight (i.e., maternal smoking, disease, nutrition, and 

addictions) were not evaluated in this study. 

8.5.2	 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 5 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 first trimester sonogram. The database was 

screened for possible outliers, defined as infants with 

birth weights that exceeded 5000 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 5000 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 8-27 provides the distribution 

of neonatal weights by gestational age from 25 weeks of 

gestation onward. 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

8.6	 REFERENCES FOR CHAPTER 8 

Brenner, W.E.; Edelman, D.A.; Hendricks, C.H. 

(1976) A standard of fetal growth for the 

United States of America. Am J Obstet 

Gynecol 1:126(5):555-64. 

Burmaster, D.E.; Crouch, E.A.C. (1997) Lognormal 

distributions for body weight as a function of 

age for males and females in the United 

States, 1976-1980. Risk Anal 17(4):499­

505. 

Doubilet, P.M.; Benson, C.B.; Nadel, A.S.; Ringer, 

S.A. (1997) Improved birth weight table for 

neonates developed from gestations dated by 

early ultrasonography. J Ultrasound Med 

16:241-249. 

Freedman, D.; Kettel, K.; Serdula, M.; Ogden, C.; 

Dietz, W. (2006) Racial and ethnic 

differences in secular trends for childhood 

BMI, weight, and height. Obesity 

14(2):301:307. 

Kahn, H.; Stralka, K. (2008) 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 

(CSFII). J Expo Sci Environ Epidemiol 

(2008) 1-9. 

Kuczmarski, R.J.; Ogden, C.L.; Guo, S.S.; GrummerStrawn, L.; Flegal, K., et al. (2000) CDC 

growth charts for the United States: methods 

and development. National Center for Health 

Statistics. Vital Health Stat. 11(246)2002. 

LSRO (1995) Third report on nutrition monitoring in 

the United States: Volume 1. Prepared by: 

Federation of American Societies for 

Experimental Biology, Life Sciences 

Research Office for the Interagency Board 

for Nutrition Monitoring and Related 

Research. Washington, D.C.: U.S. 

Government Printing Office. 

Martin, J.; Hamilton, B.; Sutton, P.; Ventura, S.; Fay, 

M.; et al. (2007) Births: final data for 2005. 

CDC National Vital Statistics Report, 

Volume 56. No. 6. 

National Center for Health Statistics (NCHS). (1987) 

Anthropometric reference data and 

prevalence of overweight, United States, 

1976-80. Data from the National Health and 

Nutrition Examination Survey, Series 11, 

No. 238. Hyattsville, MD: U.S. Department of 

Health and Human Services, Public Health 

Service, National Center for Health Statistics. 

DHHS Publication No. (PHS) 87-1688. 

Ogden, C.L.; Fryar, C.D.; Carroll, M.D.; Flegal, K. M. 

(2004) Mean Body Weight, Height, and Body 

Mass Index, United States 1960-2002. Advance 

Data from Vital and Health Statistics, No. 347, 

October 27, 2004. U.S. Department of Health 

and Human Services, Centers for Disease 

Control and Prevention, National Center for 

Health Statistics. 

Portier K.; Tolson, J.; Roberts, S. (2007) Body weight 

distributions for risk assessment. Risk Anal 

27(1)11-26. 

U.S.	 EPA (1989) Risk assessment guidance for 

Superfund, Volume I: Human health evaluation 

manual. Washington, DC: U.S. Environmental 

Protection Agency, Office of Emergency and 

Remedial Response. EPA/540/1-89/002. 

U.S. EPA (2000) Memorandum entitled:	 Body weight 

estimates on NHANES III data, revised, 

Contract 68-C-99-242, Work Assignment 0-1 

from Bob Clickner, Westat Inc. to Helen 

Jacobs, U.S. EPA dated March 3, 2000. 

U.S. EPA (2005) Guidance on selecting age groups for 

monitoring and assessing childhood exposures 

to environmental contaminants (2005). 

Washington, D.C.: U.S. Environmental 

Protection Agency, EPA/630/P-03/003F. 

Child-Specific Exposure Factors Handbook Page 

September 2008 8-9 
 

 

 

 

Table 8-3. Mean and Percentile Body Weights (kilograms) 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 

158 

284 

489 

927 

1176 

1144 

2318 

3593 

5297 

4851 

4.8 

5.9 

7.4 

9.2 

11.4 

13.8 

18.6 

31.8 

56.8 

71.6 

3.6 

4.5 

5.7 

7.1 

8.9 

10.9 

13.5 

19.7 

34.0 

48.2 

3.9 

4.7 

6.1 

7.5 

9.3 

11.5 

14.4 

21.3 

37.2 

52.0 

4.1 

4.9 

6.3 

7.9 

9.7 

11.9 

14.9 

22.3 

40.6 

54.5 

4.2 

5.2 

6.7 

8.3 

10.3 

12.4 

15.8 

24.4 

45.0 

58.4 

4.8 

5.9 

7.3 

9.1 

11.3 

13.6 

17.8 

29.3 

54.2 

67.6 

5.1 

6.6 

8.0 

10.1 

12.4 

14.9 

20.3 

36.8 

65.0 

80.6 

5.5 

6.9 

8.4 

10.5 

13.0 

15.8 

22.0 

42.1 

73.0 

90.8 

5.8 

7.1 

8.7 

10.8 

13.4 

16.3 

23.6 

45.6 

79.3 

97.7 

6.2 

7.3 

9.1 

11.3 

14.0 

17.1 

26.2 

52.5 

88.8 

108.0 

Source: U.S. EPA Analysis of NHANES 1999-2006 data. 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Page Child-Specific Exposure Factors Handbook 

8-10 September 2008 
 

 

 

Table 8-4. Mean and Percentile Body Weights (kilograms) for Males Derived from NHANES 1999-2006 

Percentiles 

Age Group N Mean 

5th 10th 15th 25th 50th 75th 85th 90th 95th 

Birth to <1 month 88 4.9 3.6 3.6 4.0 4.4 4.8 5.5 5.8 6.2 6.8 

1 to <3 months 153 6.0 4.6 5.0 5.1 5.4 6.1 6.8 7.0 7.2 7.3 

3 to <6 months 255 7.6 5.9 6.4 6.6 6.9 7.5 8.2 8.6 8.8 9.1 

6 to <12 months 472 9.4 7.3 7.9 8.2 8.5 9.4 10.3 10.6 10.8 11.5 

1 to <2 years 632 11.6 9.0 9.7 10.0 10.5 11.5 12.6 13.2 13.5 14.3 

2 to <3 years 558 14.1 11.4 12.0 12.2 12.8 14.0 15.2 15.9 16.4 17.0 

3 to <6 years 1158 18.8 13.5 14.4 14.9 15.9 18.1 20.8 22.6 23.8 26.2 

6 to <11 years 1795 31.9 20.0 21.8 22.9 24.8 29.6 36.4 41.2 45.2 51.4 

11 to <16 years 2593 57.6 33.6 36.3 38.9 44.2 55.5 66.5 75.5 81.2 91.8 

16 to <21 years 2462 77.3 54.5 57.6 60.0 63.9 73.1 86.0 96.8 104.0 113.0 

Source: U.S. EPA Analysis of NHANES 1999-2006 data. 

Table 8-5. Mean and Percentile Body Weights (kilograms) for Females Derived from NHANES 1999-2006 

Percentiles 

Age Group N Mean 

5th 10th 15th 25th 50th 75th 85th 90th 95th 

Birth to <1 month 70 4.6 3.6 4.0 4.1 4.2 4.6 4.9 5.0 5.2 5.9 

1 to <3 months 131 5.7 4.3 4.6 4.74 5.1 5.5 6.4 6.6 6.9 7.3 

3 to <6 months 234 7.2 5.5 5.9 6.2 6.4 7.2 7.9 8.2 8.4 9.0 

6 to <12 months 455 9.0 7.1 7.3 7.6 8.0 8.9 9.8 10.3 10.6 11.2 

1 to <2 years 544 11.1 8.7 9.1 9.4 10.0 11.1 12.2 12.9 13.2 13.7 

2 to <3 years 586 13.5 10.5 11.0 11.5 12.1 13.2 14.6 15.5 16.2 17.1 

3 to <6 years 1160 18.3 13.5 14.3 14.7 15.6 17.5 19.7 21.3 23.2 26.2 

6 to <11 years 1798 31.7 19.3 20.9 22.0 23.9 29.0 37.3 43.1 46.7 53.4 

11 to <16 years 2704 55.9 34.9 38.6 41.6 45.7 53.3 62.8 70.7 76.5 86.3 

16 to <21 years 2389 65.9 46.2 48.6 51.1 54.5 61.5 73.3 83.4 89.9 99.7 

Source: U.S. EPA Analysis of NHANES 1999-2006 data. 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-11
 
 

 

Table 8-6. Weight in Kilograms for Males 2 Months-19 Years of Age– Number Examined, Mean, and Selected Percentiles, 

by Age Category: United States, 1976-1980a 

Number of Percentiles 

Persons Mean Age Group 5th 10th 15th 25th 50th 75th 85th 90th 

Examined (kg) 

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 3 to <6 months 287 7.7 6.3 6.6 6.7 7.0 7.7 8.4 8.9 9.2 6 to <12 months 589 9.4 7.5 7.9 8.1 8.6 9.4 10.2 10.6 10.9 1 to <2 years 613 11.7 9.4 9.8 10.1 10.8 11.7 12.6 13.1 13.7 2 to <3 years 627 13.7 11.4 11.8 12.2 12.6 13.6 14.6 15.2 15.8 3 to <6 years 1556 18.0 13.7 14.6 14.9 15.7 17.5 19.7 21.0 22.0 6 to <11 years 1373 30.7 19.5 21.1 22.1 24.0 28.5 35.2 40.5 43.5 11 to <16 years 1037 55.2 34.0 36.5 38.7 42.8 53.0 63.0 69.4 74.8 16 to <21 years 890 71.8 54.1 56.6 58.3 61.8 68.7 77.9 84.3 89.7 

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. 

- No data available for infants less than two months old. Source: National Center for Health Statistics, 1987. 

Page Child-Specific Exposure Factors Handbook 

8-12 September 2008 
 

Table 8-7. Weight in Kilograms for Females 6 Months-19 Years of Age– Number Examined, Mean, and Selected Percentiles, by Age Category: United States, 1976-1980a Number of Percentiles Age Group Mean Persons (kg) 5th 10th 15th 25th 50th 75th 85th 90

Examined 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 3 to <6 months 269 7.1 5.8 5.9 6.1 6.4 7.1 7.7 7.9 8.4 6 to <12 months 574 8.8 7.2 7.5 7.7 8.0 8.7 9.4 10.1 101 to <2 years 617 11.0 9.1 9.4 9.6 9.9 10.9 11.9 12.6 12.2 to <3 years 597 13.4 10.8 11.2 11.6 12.1 13.2 14.6 15.4 15.3 to <6 years 1658 18.0 13.3 14.0 14.5 15.4 17.2 19.7 21.1 22.6 to <11 years 1321 30.6 19.0 20.5 21.3 23.4 28.9 35.0 39.6 44.11 to <16 years 1144 53.2 34.1 37.2 40.4 45.2 51.6 60.0 67.2 70.16 to <21 years 1001 62.2 46.7 48.2 49.7 52.2 58.9 68.3 74.7 80.

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. 

- No data available for infants less than two months old. Source: National Center for Health Statistics, 1987. 

Child-Specific Exposure Factors Handbook Page 

September 2008 8-13 
 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-8. Statistics for Probability Plot Regression Analyses:
 

Females Body Weights 6 Months to 20 Years of Age
 

Lognormal Probability Plots 

Age Midpoint (years) Linear Curve 

μ2 

a F2 a 

0.75 2.16 0.145 

1.5 2.38 0.129 

2.5 2.56 0.112 

3.5 2.69 0.136 

4.5 2.83 0.134 

5.5 2.98 0.164 

6.5 3.10 0.174 

7.5 3.19 0.174 

8.5 3.31 0.156 

9.5 3.46 0.214 

10.5 3.57 0.199 

11.5 3.71 0.226 

12.5 3.82 0.213 

13.5 3.92 0.215 

14.5 3.99 0.187 

15.5 4.00 0.156 

16.5 4.05 0.167 

17.5 4.08 0.165 

18.5 4.07 0.147 

19.5 4.10 0.149 

a μ2, F2 - correspond to the mean and standard deviation, respectively, of the lognormal distribution of body weight (kg). 

Source: Burmaster and Crouch, 1997. 

Page Child-Specific Exposure Factors Handbook 

8-14 September 2008 
 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-9. Statistics for Probability Plot Regression Analyses:
 

Males Body Weights 6 Months to 20 Years of Age
 

Lognormal Probability Plots 

Age Midpoint (years) Linear Curve 

μ2 

a F2 a 

0.75 2.23 0.132 

1.5 2.46 0.119 

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 

a μ2, F2 - correspond to the mean and standard deviation, respectively, of the lognormal distribution of body weight (kg). 

Source: Burmaster and Crouch, 1997. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-15
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-10. Body Weight Estimates (kilograms) by Age and Gender, U.S. Population Derived From 

NHANES III (1988-94) 

Male and Female Male Female 

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 and older 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. 

Page Child-Specific Exposure Factors Handbook 

8-16 September 2008 
 

 

 

 

 

 

 

 

 

 

CI 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-11. Body Weight Estimates (in kilograms) by Age, U.S. Population Derived From
 

NHANES III (1988-94)
 

Male and Female 

Age Group Sample Size Population 

Median Mean 95% CI 

2 Months 243 408,837 6.3 6.3 6.1-6.4 

3 Months 190 332,823 7.0 6.9 6.7-7.1 

3 Months and Younger 433 741,660 6.6 6.6 6.4-6.7 

= Confidence Interval. 

Source: U.S. EPA, 2000. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-17
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-12. Observed Mean, Standard Deviation and Selected Percentiles for Weight (kilograms) by Gender and Age: Birth to 36 Months 

Percentile
 

Age Group Mean SD
 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 < 1 months ! ! ! ! ! ! ! !

1< 2 months ! ! ! ! ! ! ! !

2 < 3 months 6.5 0.8 5.6 5.8 6.7 6.9 7.4 7.5 

3 < 4 months 7.0 0.9 5.9 6.5 7.0 7.5 8.2 8.5 

4 < 5 months 7.2 0.8 6.3 6.7 7.2 7.7 8.0 8.4 

5 < 6 months 7.9 0.9 6.7 7.5 7.8 8.6 9.4 9.6 

6 < 7 months 8.4 1.1 7.3 7.6 8.4 9.0 10.2 10.7 

7 < 8 months 8.6 1.1 7.1 7.8 8.6 9.5 10.1 10.4 

8 < 9 months 9.3 1.1 7.9 8.6 9.2 10.1 10.5 11.0 

9 < 10 months 9.3 0.9 8.2 8.6 9.3 10.0 10.8 10.9 

10 < 11 months 9.5 1.1 8.3 8.7 9.3 10.1 11.3 11.5 

11 < 12 months 10.0 1.0 8.7 9.5 10.0 10.6 11.1 11.6 

12 < 15 months 10.6 1.2 9.2 9.8 10.6 11.3 12.1 12.4 

15 < 18 months 11.4 1.9 9.9 10.5 11.3 12.0 12.8 13.5 

18 < 21 months 12.1 1.5 10.4 11.0 11.9 12.7 13.9 15.5 

21 < 24 months 12.4 1.3 10.9 11.6 12.4 13.1 14.4 14.7 

24 < 30 months 13.1 1.7 11.3 12.1 12.9 14.1 15.1 15.9 

30 < 36 months 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 < 1 months ! ! ! ! ! ! ! !

1< 2 months ! ! ! ! ! ! ! !

2 < 3 months 5.4 0.5 4.8 5.0 5.6 5.9 6.0 !

3 < 4 months 6.3 0.7 5.6 5.8 6.3 6.8 7.4 7.8 

4 < 5 months 6.7 0.9 5.8 6.1 6.6 7.4 8.0 8.3 

5 < 6 months 7.3 0.9 6.3 6.7 7.1 7.7 8.5 8.8 

6 < 7 months 7.7 0.8 6.6 7.1 7.6 8.1 8.9 9.0 

7 < 8 months 8.0 1.4 6.7 7.4 7.8 8.6 9.4 9.8 

8 < 9 months 8.3 0.9 7.3 7.8 8.3 8.9 9.4 9.8 

9 < 10 months 8.9 0.9 7.8 8.1 8.7 9.4 10.1 10.5 

10 < 11 months 9.0 1.1 7.8 8.4 9.0 9.5 10.4 10.9 

11 < 12 months 9.3 1.0 7.9 8.6 9.2 10.1 10.6 10.9 

12 < 15 months 9.8 1.1 8.5 9.1 9.8 10.4 11.3 11.6 

15 < 18 months 10.4 1.1 9.1 9.7 10.3 11.2 11.8 12.0 

18 < 21 months 11.1 1.4 9.6 10.2 11.0 11.9 12.8 13.5 

21 < 24 months 11.8 1.3 10.1 10.9 11.8 12.8 13.5 13.9 

24 < 30 months 12.5 1.5 10.8 11.5 12.4 13.3 14.5 15.1 

30 < 36 months 13.6 1.7 11.8 12.5 13.4 14.52 15.7 16.4 

- No data available. 

Source: Kuczmarski et al. 2002. 

Page Child-Specific Exposure Factors Handbook 

8-18 September 2008 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Figure 8-1. Weight by Age Percentiles for Boys Aged Birth to 36 Months 

Source: Kuczmarski et al., 2002. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-19
 
 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Figure 8-2. Weight by Age Percentiles for Girls Aged Birth to 36 Months 

Source: Kuczmarski et al., 2002. 

Page Child-Specific Exposure Factors Handbook 

8-20 September 2008 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Figure 8-3. Weight by Length Percentiles for Boys Aged Birth to 36 Months 

Source: Kuczmarski et al., 2002. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-21
 
 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Figure 8-4. Weight by Length Percentiles for Girls Aged Birth to 36 Months 

Source: Kuczmarski et al., 2002. 

Page Child-Specific Exposure Factors Handbook 

8-22 September 2008 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Figure 8-5. Body Mass Index-for-Age Percentiles: Boys, 2 to 20 Years 

Source: Kuczmarski et al., 2002. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-23
 
 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Figure 8-6. Body Mass Index-for-Age Percentiles: Girls, 2 to 20 Years 

Source: Kuczmarski et al., 2002. 

Page Child-Specific Exposure Factors Handbook 

8-24 September 2008 
 

Table 8-13. Mean Body Weight (kilograms) by Age and Gender Across Multiple Surveys Gender NHES II, 1963-65 NHES III, 1966-70 NHANES I, 1971-74 NHANES II, 1976-80 NHANES III, 1988-94 NHANES 1999-

and Age (years) N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE N Mean 

Male 2 - - - - - - 298 13.6 0.2 370 13.4 0.1 644 13.6 0.1 262 13.7 

3 - - - - - - 308 15.6 0.1 421 15.5 0.1 516 15.8 0.2 216 15.9 

4 - - - - - - 304 17.7 0.1 405 17.6 0.1 549 17.6 0.2 179 18.5 

5 - - - - - - 273 20.2 0.2 393 19.7 0.1 497 20.1 0.2 147 21.3 

6 575 22.0 0.1 - - - 179 22.0 0.3 146 22.8 0.4 283 23.2 0.6 182 23.5 

7 632 24.7 0.2 - - - 164 24.9 0.4 150 24.9 0.4 269 26.3 0.4 185 27.2 

8 618 27.8 0.2 - - - 152 26.4 0.3 145 28.0 0.6 266 30.2 0.8 214 32.7 

9 603 31.2 0.4 - - - 169 31.6 0.8 141 30.7 0.6 281 34.4 1.0 174 36.0 

10 576 33.7 0.3 - - - 184 34.2 0.6 165 36.2 0.7 297 37.3 0.9 187 38.6 

11 595 38.2 0.3 - - - 178 38.8 0.8 153 39.7 0.9 281 42.5 0.9 182 43.7 

12 - - - 643 42.9 0.4 200 44.0 0.8 147 44.1 1.0 203 49.1 1.1 299 50.4 

13 - - - 626 50.0 0.5 174 49.9 1.0 165 49.5 1.2 187 54.0 1.0 298 53.9 

14 - - - 618 56.7 0.6 174 56.3 0.9 188 56.4 0.9 188 64.1 3.6 266 63.9 

15 - - - 613 61.6 0.4 171 60.3 1.2 180 61.2 1.0 187 66.9 1.9 283 68.3 

16 - - - 556 64.8 0.6 169 66.9 1.3 180 66.5 1.2 194 68.7 1.6 306 74.4 

17 - - - 458 68.1 0.4 176 68.6 1.1 183 66.7 0.8 196 72.9 1.3 313 75.6 

18 - - - - - - 124 74.3 1.3 156 71.1 1.2 176 71.3 1.7 284 75.6 

19 - - - - - - 136 72.6 1.3 150 71.8 0.8 168 73.0 2.2 270 78.2 

Female 

2 - - - - - - 272 13.0 0.1 330 12.8 0.1 624 13.2 0.1 248 13.3 

3 - - - - - - 292 15.0 0.2 367 14.8 0.1 587 15.4 0.1 178 15.2 

4 - - - - - - 281 16.8 0.2 388 16.8 0.2 537 17.9 0.3 191 17.9 

5 - - - - - - 314 19.7 0.3 369 19.4 0.3 554 20.2 0.2 186 20.6 

6 536 21.5 0.2 - - - 176 21.6 0.3 150 21.9 0.4 272 22.6 0.6 171 22.4 

7 609 24.2 0.2 - - - 169 24.3 0.4 154 24.6 0.5 274 26.4 0.8 196 25.9 

8 613 27.5 0.2 - - - 152 27.5 0.5 125 27.5 0.4 248 29.9 0.6 184 31.9 

9 581 31.4 0.4 - - - 171 32.0 0.6 154 31.7 0.7 280 34.4 1.2 183 35.4 

10 584 35.2 0.4 - - - 197 33.8 0.6 128 35.7 0.6 258 37.9 1.2 164 40.0 

11 525 39.8 0.4 - - - 166 41.2 0.8 143 41.4 0.9 275 44.1 1.1 194 47.9 

12 - - - 547 46.6 0.4 177 46.7 1.0 146 46.1 0.9 236 49.0 1.2 316 52.0 

13 - - - 582 50.5 0.5 198 51.8 1.0 155 50.9 1.2 220 55.8 1.6 321 57.7 

14 - - - 586 54.2 0.4 184 54.6 1.0 181 54.3 1.0 218 58.5 1.4 324 59.9 

15 - - - 503 56.5 0.5 167 56.6 0.9 144 55.0 0.8 191 58.1 1.1 266 61.1 

16 - - - 536 58.1 0.7 171 56.8 1.1 167 57.7 0.9 208 61.3 1.4 273 63.0 

17 - - - 442 57.6 0.6 150 59.5 1.6 134 59.6 1.0 201 62.4 1.2 256 61.7 

18 - - - - - - 141 58.2 1.1 156 59.0 1.0 175 61.2 1.9 243 65.2 

19 - - - - - - 130 59.5 1.4 158 59.8 1.0 177 63.2 1.9 225 67.9 

- Data not available. 

N = Number of individuals. SE = Standard error. Source: Ogden et al., 2004. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-25
 
 

 

Table 8-14. Mean Height (centimeters) by Age and Gender Across Multiple Surveys 

Gender 

and Age 

(years) 

NHES II, 1963-65 

N Mean SE 

NHES III, 1966-70 NHANES I, 1971-74 NHANES II, 1976-80 NHANES III, 1988-94 

N Mean SE N Mean SE N Mean SE N Mean SE 

NHA

N 

Male 

2 3 4 5 6 7 8 9 

10 11 12 13 14 15 16 17 18 19 

----

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 

--

298 308 304 273 179 164 152 169 184 178 200 174 174 171 169 176 124 136 

91.1 98.5 

106.0 112.8 118.1 125.0 129.0 135.1 140.0 146.3 152.8 159.3 166.7 170.8 175.0 176.9 176.6 176.5 

0.4 0.3 0.3 0.3 0.6 0.5 0.5 0.6 0.5 0.7 0.7 0.8 0.6 0.9 0.8 0.5 0.7 0.9 

350 421 405 393 146 150 145 141 165 153 147 165 188 180 180 183 156 150 

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 

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 

589 513 551 497 283 270 269 280 297 285 207 190 191 188 197 196 176 169 

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 

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 

254 222 183 156 188 187 217 177 188 187 301 298 267 287 310 317 289 275 

Female 

2 3 4 5 6 7 8 9 

10 11 12 13 14 15 16 17 18 19 

----

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 

--

272 292 281 314 176 169 152 171 197 166 177 198 184 167 171 150 141 130 

90.1 97.7 

104.2 112.2 118.2 124.6 129.2 135.9 140.1 148.2 154.6 158.9 160.8 163.6 161.7 162.1 164.7 163.1 

0.3 0.3 0.4 0.4 0.5 0.7 0.6 0.5 0.8 0.8 0.6 0.5 0.6 0.6 0.5 0.9 0.5 0.5 

314 367 388 369 150 154 125 154 128 143 146 155 181 144 167 134 156 158 

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 

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 

564 590 535 557 274 275 247 282 262 275 239 225 224 195 214 201 175 178 

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 

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 

233 187 195 190 172 200 184 189 164 194 318 324 326 271 275 258 249 231 

-N SE 

Data not available. = Number of individuals. = Standard error. 

Source: Ogden et al., 2004. 

Page Child-Specific Exposure Factors Handbook 

8-26 September 2008 
 

Table 8-15. Mean Body Mass Index (BMI) by Age and Gender Across Multiple Surveys Gender NHES II, 1963-65 NHES III, 1966-70 NHANES I, 1971-74 NHANES II, 1976-80 NHANES III, 1988-94 NHANES 19

and Age (years) N Mean SE N Mean SE N Mean SE N Mean SE N Mean SE N Mean 

Male 2 - - - - - - 298 16.3 0.1 350 16.2 0.1 588 16.5 0.1 225 16.6 

3 - - - - - - 308 16.0 0.1 421 15.9 0.1 512 16.1 0.2 209 16.2 

4 - - - - - - 304 15.7 0.1 405 15.8 0.1 547 15.9 0.1 178 16.3 

5 - - - - - - 273 15.6 0.1 393 15.6 0.1 495 15.9 0.1 147 16.5 

6 575 15.6 0.1 - - - 179 15.7 0.2 146 16.0 0.2 282 16.3 0.3 182 16.4 

7 632 15.9 0.1 - - - 164 15.8 0.2 150 16.0 0.2 269 16.5 0.2 185 17.0 

8 618 16.3 0.1 - - - 152 15.8 0.2 145 16.5 0.2 266 17.3 0.4 214 18.4 

9 603 16.9 0.2 - - - 169 17.1 0.3 141 16.8 0.2 279 18.0 0.7 174 18.7 

10 576 17.1 0.1 - - - 184 17.3 0.2 165 18.0 0.3 297 18.4 0.3 187 19.1 

11 595 17.9 0.1 - - - 178 18.0 0.3 153 18.6 0.3 280 19.4 0.3 182 19.6 

12 - - - 643 18.4 0.1 200 18.7 0.2 147 18.8 0.3 203 20.1 0.3 299 20.7 

13 - - - 626 19.4 0.1 174 19.6 0.3 165 19.5 0.4 187 20.5 0.3 298 20.7 

14 - - - 618 20.2 0.2 174 20.2 0.3 188 20.2 0.2 188 22.3 1.1 266 22.3 

15 - - - 613 20.9 0.1 171 20.5 0.3 180 20.8 0.3 187 22.3 0.5 283 22.5 

16 - - - 556 21.3 0.1 169 21.8 0.3 180 22.0 0.3 194 22.3 0.5 306 24.1 

17 - - - 458 22.1 0.1 176 21.9 0.3 183 21.8 0.2 196 23.4 0.4 313 24.5 

18 - - - - - - 124 23.7 0.3 156 22.6 0.4 176 22.6 0.5 284 24.2 

19 - - - - - - 136 23.3 0.5 150 23.1 0.3 168 23.7 0.6 269 24.9 

Female 

2 - - - - - - 272 15.9 0.1 314 16.1 0.1 562 16.5 0.1 214 16.4 

3 - - - - - - 292 15.7 0.1 367 15.6 0.1 582 15.9 0.1 173 16.0 

4 - - - - - - 281 15.5 0.1 388 15.5 0.1 533 16.0 0.2 190 15.9 

5 - - - - - - 314 15.5 0.1 369 15.6 0.1 554 15.9 0.1 186 16.1 

6 536 115.4 0.1 - - - 176 15.4 0.1 150 15.6 0.2 272 16.1 0.3 170 16.2 

7 609 15.8 0.1 - - - 169 15.6 0.2 154 16.1 0.2 274 16.9 0.3 196 16.6 

8 613 16.4 0.1 - - - 152 16.4 0.2 125 16.3 0.2 247 17.3 0.3 184 18.3 

9 581 17.0 0.1 - - - 171 17.2 0.2 154 17.5 0.3 280 18.2 0.5 183 18.7 

10 584 17.6 0.2 - - - 197 17.1 0.2 128 17.7 0.3 258 18.4 0.4 163 19.3 

11 525 18.2 0.2 - - - 166 18.6 0.3 143 18.9 0.3 275 19.4 0.4 194 20.7 

12 - - - 547 19.2 0.1 177 19.5 0.4 146 19.3 0.3 236 20.2 0.5 315 21.2 

13 - - - 582 19.9 0.1 198 20.4 0.3 155 20.1 0.4 220 21.8 0.6 321 22.6 

14 - - - 586 20.8 0.1 184 21.1 0.3 181 21.0 0.3 218 22.4 0.5 324 22.9 

15 - - - 503 21.4 0.2 167 21.1 0.3 144 20.6 0.3 191 21.9 0.4 266 23.2 

16 - - - 536 21.9 0.2 171 21.7 0.3 167 21.8 0.3 208 23.0 0.5 273 24.0 

17 - - - 442 21.7 0.2 150 22.6 0.5 134 22.3 0.4 201 23.3 0.5 255 23.1 

18 - - - - - - 141 21.5 0.3 156 22.3 0.4 175 22.9 0.6 243 24.4 

19 - - - - - - 130 22.5 0.6 158 22.4 0.3 177 23.7 0.8 225 25.5 

- Data not available. N = Number of individuals. SE = Standard error. Source: Ogden et al., 2004. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-27
 
 

 

Table 8-16. Sample Sizes by Age, Sex, Race, and Examination 

NHANES Examination 

Age Group Sex Racea I (1971-1974) II (1976-1980) III (1988-1994) 

Overall 6431 (10.3)b 6395 (10.6) 9610 (9.9) 6

2 to 5 years Boys White 829 (3.9) 1082 (4.1) 605 (4.0) 

Black 286 (3.9) 273 (4.1) 693 (3.9) Mexican American 51 (3.8) 105 (4.2) 732 (4.0) 

Girls White 772 (4.0) 1028 (4.0) 639 (4.0) 

Black 297 (4.0) 234 (4.0) 684 (3.9) Mexican American 56 (4.1) 102 (4.2) 800 (3.9) 

6 to 11 years Boys White 711 (9.1) 667 (9.0) 446 (8.9) 

Black 249 (9.0) 137 (9.0) 584 (9.0) Mexican American 51 (9.0) 60 (9.2) 565 (9.0) 

Girls White 722 (9.1) 631 (9.1) 428 (9.1) 

Black 268 (9.0) 155 (9.0) 538 (9.0) Mexican American 45 (8.9) 40 (9.3) 581 (8.9) 

12 to 17 years Boys White 764 (14.9) 786 (15.1) 282 (14.9) 

Black 252 (14.9) 155 (15.1) 412 (15.0) 

Mexican American 42 (15.0) 49 (15.0) 406 (15.0) 

Girls White 749 (15.0) 695 (15.1) 344 (15.0) 

Black 251 (14.8) 159 (15.0) 450 (14.9) 

Mexican American 36 (14.9) 37 (15.2) 421 (14.8) 

a	 Race was recoded in the first two examinations (using data concerning ancestry/national origin) to create comparable categor

surveys. 

b	 Mean ages are shown in parentheses. 

Source:	 Freeman et al., 2006. 

Page Child-Specific Exposure Factors Handbook 

8-28 September 2008 
 

Table 8-17. Mean BMI (kg/m2) Levels and Change in the Mean Z-Scores by Race-Ethnicity and Sex Examination Yeara Increase in Mean z-sc

From 1971-1974 to 1999

Race 1971-1974 1976-1980 1988-1994 1999-2002 BMI Weight 

Overall White 18.0b 18.0 18.8 19.0 +0.33 +0.36 

Black 17.8 18.2 19.1 20.0 +0.61 +0.63 Mexican-American 18.6 18.8 19.5 20.1 +0.32 +0.52 

Sex Boys White 17.9 18.0 18.8 19.0 +0.37 +0.42 

Black 17.7 17.8 18.8 19.6 +0.53 +0.58 Mexican-American 18.6 18.9 19.4 20.3 +0.38 +0.67 

Girls White 18.0 18.0 18.7 19.0 +0.30 +0.32 

Black 17.9 18.6 19.5 20.4 +0.71 +0.69 Mexican-American 18.5 18.6 19.6 19.9 +0.25 +0.35 

Age (years) 

2 to 5 White 15.8 15.7 16.0 16.2 +0.21 +0.22 

Black 15.8 15.7 15.9 16.2 +0.34 +0.32 Mexican-American 16.5 16.2 16.5 16.5 -0.02 +0.29 

6 to 11 White 16.7 16.9 17.6 17.9 +0.42 +0.47 

Black 16.5 17.1 17.9 18.7 +0.67 +0.69 Mexican-American 16.9 17.7 18.5 18.8 +0.50 +0.65 

12 to 17 White 20.7 20.6 21.8 22.0 +0.32 +0.35 

Black 20.4 20.9 22.4 23.7 +0.72 +9,77 Mexican-American 21.6 21.5 22.6 24.0 +0.37 +0.55 

a Secular trends for BMI, BMI-for-age, weight-for-age, and height-for-age were each statistically significant at the 0.001 leve

BMI, BMI-for-age, 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. 

Child-Specific Exposure Factors Handbook Page 

September 2008 8-29 
 

 

Table 8-18. Prevalence of Overweight and Obesitya Among Children 

Examination year Increase in Prevalence F

1974 to 1999-20

Race 1971-1974 1976-1980 1988-1994 1999-2002 Overweight Ob

Overall White 5% (1)b 5% (1) 9% (2) 12% (3) +8 

Black 6% (1) 7% (2) 12% (3) 18% (5) +12 

Mexican-American 8% (1) 10% (1) 14% (4) 21% (5) +12 

Sex 

Boys White 5% (1) 5% (1) 10% (2) 13% (4) +8 

Black 6% (2) 5% (1) 11% (3) 16% (5) +10 

Mexican-American 8% (1) 12% (1) 15% (4) 24% (4) +16 

Girls White 5% (1) 5% (1) 9% (2) 12% (2) +7 

Black 6% (1) 9% (2) 14% (3) 21% (6) +14 

Mexican-American 8% (2) 7% (0) 14% (3) 17% (4) +9 

Age (years) 

2 to 5 White 4% (1) 3% (1) 5% (1) 9% (3) +5 

Black 7% (3) 4% (0) 8% (3) 9% (4) +2 

Mexican-American 10% (5) 11% (3) 12% (5) 13% (5) +3 

6 to 11 White 4% (0) 6% (1) 11% (3) 13% (4) +10 

Black 4% (0) 9% (3) 15% (3) 20% (5) +15 

Mexican-American 6% (0) 11% (0) 17% (4) 22% (5) +16 

12 to 17 White 6% (1) 4% (0) 11% (2) 13% (2) +7 

Black 8% (1) 8% (1) 13% (3) 22% (6) +14 

Mexican-American 9% (0) 8% (1) 14% (2) 25% (5) +15 

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. 

Page Child-Specific Exposure Factors Handbook 

8-30 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-19. 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 (grams) 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 

4,000-4499 289,098 167,269 22,149 64,704 

4,500-4999 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 

Percent 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 grams (5 lb 8 oz). e Very low birth weight is birth weight less than 1,500grams (3 lb 4 oz). 

Source: Martin et al., 2007. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-31
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-20. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using NHANES II Data 

Males (kg) Females (kg) Overall (kg) 

Age Groupa 

Mean SD N Mean SD N Mean SD N 

0 to 1 year 9.4 1.3 179 8.8 1.3 177 9.1 1.2 356 

1 to 2 years 11.8 1.6 370 10.8 1.4 336 11.3 1.5 706 

2 to 3 years 13.6 1.8 375 13.0 1.5 336 13.3 1.6 711 

3 to 4 years 15.6 1.9 418 14.9 2.1 366 15.2 1.8 784 

4 to 5 years 17.8 2.4 404 17.0 2.3 396 17.4 2.4 800 

5 to 6 years 19.8 2.8 397 19.6 3.2 364 19.7 2.8 761 

6 to 7 years 23.0 3.7 133 22.1 3.9 135 22.5 3.6 268 

7 to 8 years 25.1 3.8 148 24.7 4.6 157 24.8 3.8 305 

8 to 9 years 28.2 5.6 147 27.8 4.8 123 28.1 5.6 270 

9 to 10 years 31.1 5.8 145 31.8 7.3 149 31.4 5.9 294 

10 to 11 years 36.4 7.2 157 36.1 7.7 136 36.2 7.1 293 

11 to 12 years 40.2 9.8 155 41.8 10.1 140 41.0 9.9 295 

12 to 13 years 44.2 9.8 145 46.4 10.1 147 45.4 10.0 292 

13 to 14 years 49.8 11.4 173 50.9 11.2 162 50.4 11.5 335 

14 to 15 years 57.1 10.7 186 54.7 10.7 178 55.9 10.5 364 

15 to 16 years 61.0 10.4 184 55.1 9.0 145 58.0 9.9 329 

16 to 17 years 67.1 11.7 178 58.1 9.6 170 62.4 10.9 348 

17 to 18 years 66.7 11.3 173 59.6 10.4 134 63.3 10.7 307 

18 to 19 years 71.0 12.0 164 59.0 10.2 170 64.6 10.9 334 

19 to 20 years 71.7 11.3 148 60.1 10.1 158 65.3 10.3 306 

20 to 21 years 71.6 12.0 114 60.5 10.7 162 65.2 10.9 276 a Data were converted from ages in months to ages in years. For instance, age 1–2 years represents ages from 12 to 23 months.
 

SD = Standard Deviation.
 

N = Number of individuals.
 

Source: Portier et al., 2007. 

Page Child-Specific Exposure Factors Handbook 

8-32 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-21. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using NHANES III Data 

Males (kg) Females (kg) Overall (kg) 

Age Groupa 

Mean SD N Mean SD N Mean SD N 

0 to 1 years 8.5 1.5 902 7.8 1.6 910 8.17 1.7 1,812 

1 to 2 years 11.6 1.5 660 10.9 1.4 647 11.2 1.5 1,307 

2 to 3 years 13.6 1.5 644 13.2 1.8 624 13.4 1.8 1,268 

3 to 4 years 15.8 2.3 516 15.4 2.2 587 15.6 2.2 1,103 

4 to 5 years 17.6 2.4 549 17.9 3.2 537 17.8 3.2 1,086 

5 to 6 years 20.1 3.0 497 20.2 3.5 554 20.2 3.5 1,051 

6 to 7 years 23.2 5.0 283 22.6 4.7 272 22.9 4.8 555 

7 to 8 years 26.3 5.0 269 26.3 6.2 274 26.4 6.2 543 

8 to 9 years 30.1 6.9 266 29.8 6.7 248 30.0 6.7 514 

9 to 10 years 34.4 7.9 281 34.3 9.0 280 34.4 9.0 561 

10 to 11 years 37.3 8.6 297 37.9 9.5 258 37.7 9.4 555 

11 to 12 years 42.5 10.5 281 44.2 10.5 275 43.4 10.3 556 

12 to 13 years 49.1 11.1 203 49.1 11.6 236 49.1 11.7 439 

13 to 14 years 54.0 12.9 187 55.7 13.2 220 54.8 13.0 407 

14 to 15 years 63.7 17.1 188 58.3 11.8 220 60.6 12.2 408 

15 to 16 years 66.8 14.9 187 58.3 10.1 197 61.7 10.7 384 

16 to 17 years 68.6 14.9 194 61.5 12.8 215 65.2 13.6 409 

17 to 18 years 72.7 13.3 196 62.4 11.9 217 67.6 12.9 413 

18 to 19 years 71.2 14.3 176 61.5 14.2 193 66.4 15.3 369 

19 to 20 years 73.0 12.8 168 63.6 14.5 193 68.3 15.6 361 

20 to 21 years 72.5 13.4 149 61.7 12.9 180 66.1 13.8 329 a Data were converted from ages in months to ages in years. For instance, age 1–2 years represents ages from 12 to 23 months.
 

SD = Standard Deviation.
 

N = Number of individuals.
 

Source: Portier et al., 2007. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-33
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-22. Estimated Mean Body Weights of Males and Females by Single-Year Age Groups Using NHANES IV Data 

Males (kg) Females (kg) Overall (kg) 

Age Groupa 

Mean SD N Mean SD N Mean SD N 

0 to 1 year 9.3 1.8 116 9.3 1.5 101 9.3 1.5 217 

1 to 2 years 11.3 1.4 144 11.5 1.9 98 11.4 1.8 242 

2 to 3 years 13.7 2.0 130 13.3 1.9 113 13.5 2.0 243 

3 to 4 years 16.4 2.3 105 15.2 2.1 77 15.9 2.2 182 

4 to 5 years 18.8 2.6 95 18.1 3.2 87 18.5 3.3 182 

5 to 6 years 20.2 3.3 65 20.7 4.9 92 20.6 4.9 157 

6 to 7 years 22.9 4.3 94 22.0 4.5 74 22.5 4.6 168 

7to 8 years 28.1 5.6 100 26.0 6.2 82 27.4 6.5 182 

8 to 9 years 31.9 8.6 100 30.8 7.2 89 31.3 7.3 189 

9 to 10 years 36.1 7.5 76 36.0 8.4 84 36.2 8.5 160 

10 to 11 years 39.5 9.0 92 39.4 10.2 84 39.5 10.2 176 

11 to 12 years 42.0 10.2 84 47.2 12.2 97 44.6 11.6 181 

12 to 13 years 49.4 12.7 158 51.6 12.3 160 50.3 11.9 318 

13 to 14 years 54.9 16.2 161 59.8 15.3 156 56.9 14.6 317 

14 to 15 years 65.1 19.9 137 59.9 13.3 158 61.5 13.7 295 

15 to 16 years 68.2 15.7 142 63.4 13.9 126 65.9 14.4 268 

16 to 17 years 72.5 18.6 153 63.4 16.0 142 68.0 17.1 295 

17 to 18 years 75.4 17.9 146 59.9 11.9 128 66.6 13.2 274 

18 to 19 years 74.8 15.9 131 65.0 15.2 139 70.2 16.4 270 

19 to 20 years 80.1 17.2 129 68.7 17.4 132 74.6 19.0 261 

20 to 21 years 80.0 15.5 37 66.3 15.5 44 74.3 17.4 81 a Data were converted from ages in months to ages in years. For instance, age 1–2 years represents ages from 12 to 23 months.
 

SD = Standard Deviation.
 

N = Number of individuals.
 

Source: Portier et al., 2007. 

Page Child-Specific Exposure Factors Handbook 

8-34 September 2008 
 

 

 

Table 8-23. Estimated Body Weights of Typical Age Groups of Interest in U.S. EPA Risk Assessmentsa 

Age Group NHANES Males (kg) Females (kg) Overall (kg) 

Mean SD N Mean SD N Mean SD N 

II 17.0 4.6 2,097 16.3 4.7 1,933 16.7 4.5 4,030 

1 to 6 years 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 

II 45.2 17.6 1,618 43.9 15.9 1,507 44.8 17.5 3,125 

7 to 16 years 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 

a 

SD 

N 

Estimates were weighted using the sample weights provided with each survey. 

= Standard Deviation. 

= Number of individuals. 

Source: Portier et al., 2007. 

Table 8-24. Estimated Percentile Distribution of Body Weight by Fine Age Categories Derived From 1994-96, 1998 CSFII
 

Weight (kilograms)
 

Age Group Sample 

Size Mean Percentile 

1st 5th 10th 25th 50th 75th 90th 95th 99th 

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 

88 

245 

411 

678 

1,002 

994 

4,112 

1,553 

975 

360 

383 

4 

5 

7 

9 

12 

14 

18 

30 

54 

67 

69 

1a 

2a

4a

6a

8a 

10a 

11 

16a 

29a 

41a 

45a 

2a 

3a 

5 

7 

9 

10 

13 

18 

33 

46a 

48a 

3a 

4 

5 

7 

9 

13 

20 

36 

50 

51 

3 

4 

6 

8 

10 

12 

16 

23 

44 

56 

58 

3 

5 

7 

9 

11 

14 

18 

27 

52 

63 

66 

4 

6 

8 

10 

13 

16 

20 

35 

61 

73 

77 

4a 

6 

9

11 

14 

18 

23 

41 

72 

86 

89 

5a 

7a 

10 

12 

15 

19 

25 

45 

82 

100a 

100a 

5a 

8a

12a 

13a 

19a 

22a 

32 

57a 

95a 

114a 

117a 

a 

Source: 

Sample size does meet minimum reporting requirements as described in the “Third Report on Nutrition Monitoring in 

the United States” (LSRO, 1995). 

Kahn and Stralka, 2008. 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Child-Specific Exposure Factors Handbook Page
 

September 2008 8-35
 
 

 Table 8-25. Estimated Percentile Distribution of Body Weight By Fine Age Categories With Confidence Interval Weight (Kilograms) Mean 90th Percentile 95th Percen

Sample 90% CI 90% BI 9

Age Group Size Estimate Estimate Estimate Lower Upper Lower Upper Lower 

Bound Bound Bound Bound Bound 

4a 4a 5a 5a 5a 

Birth to 1 month 88 4 3 4 1 to <3 months 245 5 5 5 6 6 7 7a 7 

3 to <6 months 411 7 7 7 9 9 9 10 10 6 to <12 months 678 9 9 9 11 11 11 12 12 1 to <2 years 1,002 12 12 12 14 14 15 15 15 2 to <3 years 994 14 14 14 18 17 18 19 18 3 to <6 years 4,112 18 18 18 23 23 23 25 25 6 to <11 years 1,553 30 29 30 41 41 43 45 44 11 to <16 years 975 54 53 55 72 70 75 82 81 

100a 95a 

16 to <18 years 360 67 66 68 86 84 95 100a 95a 18 to <21 years 383 69 68 70 89 88 95 a Sample size does meet minimum reporting requirements as described in the “Third Report on Nutrition Monitoring in the United States

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. Source: Kahn and Stralka, 2008. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

Table 8-26. Fetal Weight (grams) Percentiles Throughout Pregnancy 

Gestational Age 

(weeks) 

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 

weeks’ gestation. 

Source: Brenner et al., 1976. 

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Table 8-27. Neonatal Weight by Gestational Age for
 

Males and Females Combined
 

 Gestational Age
 

(weeks) 

Weight (g) 

5th
 10th 25th 50th 75th 90th 95th 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

38 

39 

40 

41 

42 

43 

450 

523 

609 

707 

820 

947 

1,090 

1,249 

1,422 

1,608 

1,804 

2,006 

2,210 

2,409 

2,595 

2,762 

2,900 

3,002 

3,061 

490 

568 

660 

765 

884 

1,020 

1,171 

1,338 

1,519 

1,714 

1,919 

2,129 

2,340 

2,544 

2,735 

2,904 

3,042 

3,142 

3,195 

564 

652 

754 

870 

1,003 

1,151 

1,317 

1,499 

1,696 

1,906 

2,125 

2,349 

2,572 

2,786 

2,984 

3,155 

3,293 

3,388 

3,432 

660 

760 

875 

1,005 

1,153 

1,319 

1,502 

1,702 

1,918 

2,146 

2,383 

2,622 

2,859 

3,083 

3,288 

3,462 

3,597 

3,685 

3,717 

772 

885 

1,015 

1,162 

1,327 

1,511 

1,713 

1,933 

2,169 

2,416 

2,671 

2,927 

3,177 

3,412 

3,622 

3,798 

3,930 

4,008 

4,026 

889 

1,016 

1,160 

1,322 

1,504 

1,706 

1,928 

2,167 

2,421 

2,687 

2,959 

3,230 

3,493 

3,736 

3,952 

4,127 

4,254 

4,322 

4,324 

968 

1,103 

1,257 

1,430 

1,623 

1,836 

2,070 

2,321 

2,587 

2,865 

3,148 

3,428 

3,698 

3,947 

4,164 

4,340 

4,462 

4,523 

4,515 

Source: Doubilet et al., 1997. 

Child-Specific Exposure Factors Handbook 

Chapter 8 - Body Weight 

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Child-Specific 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. 

Children’s exposure from contaminated fruits 

and vegetables may differ from that of adults because of 

differences in the types and amounts of food eaten. 

Also, for many foods, the intake per unit body weight is 

greater for children than for adults. Common fruits and 

vegetables eaten by children include apple juice, fresh 

apples, orange juice, fresh pears, fresh peaches, carrots, 

fresh bananas, succulent garden peas, and succulent 

garden beans (Goldman, 1995). 

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 children during 

the survey period. These data are generated by 

averaging intake across only the children in the survey 

who consumed these food items. Per capita intake rates 

are generated by averaging consumer-only intakes over 

the entire population of children (including those 

children that reported no intake). In general, per capita 

intake rates are appropriate for use in exposure 

assessments for which average dose estimates for 

children are of interest because they represent both 

children who ate the foods during the survey period and 

children 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 asconsumed weight. 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. 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. Ideally, aftercooking food concentrations should be combined with 

the as-consumed intake rates. In the absence of data, it 

is reasonable to assume that no change in contaminant 

concentration occurs after cooking. 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, the reader is referred 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 

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Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

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, the reader is referred to Section 9.4. 

The purpose of this chapter is to provide intake 

data for fruits and vegetables among children. 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. 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. 

9.2 RECOMMENDATIONS 

Table 9-1 presents a summary of the 

recommended values for per capita and consumer-only 

intake of fruits and vegetables, on an as-consumed 

basis. Confidence ratings for the fruit and vegetable 

intake recommendations for general population children 

are provided in Table 9-2. 

The U.S. EPA analysis of data from the 1994-96 

and 1998 Continuing Survey of Food Intake by

Individuals (CSFII) was used in selecting recommended 

intake rates for general population children. The U.S. 

EPA analysis was conducted using 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. Also, the CSFII 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, for 

broad categories of food (i.e., total fruits and total 

vegetables), because they 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. It should also be noted that because these 

recommendations are based on 1994-96 and 1998 

CSFII data, they may not reflect the most recent 

changes that may have occurred in consumption 

patterns. More current data from the National Health 

and Nutrition Survey (NHANES) will be incorporated 

as the data become available and are analyzed. 

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Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-1. Recommended Values for Intake of Fruits and Vegetables, As Consumeda 

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 Fruits 

Birth to 1 year 5.7 21 10 26 

See Tables 

9-3 and 9-4 

U.S. EPA 

Analysis of 

CSFII, 

1994-96 and 

1998. 

1 to <2 years 6.2 19 6.9 19 

2 to < 3 years 6.2 19 6.9 19 

3 to <6 years 4.6 14 5.1 15 

6 to <11 years 2.4 8.8 2.7 9.3 

11 to <16 years 0.8 3.5 1.1 3.8 

16 to <21 years 0.8 3.5 1.1 3.8 

Total Vegetables 

Birth to 1 year 4.5 15 6.2 16 

See Tables 

9-3 and 9-4 

U.S. EPA 

Analysis of 

CSFII, 

1994-96 and 

1998. 

1 to <2 years 6.9 17 6.9 17 

2 to <3 years 6.9 17 6.9 17 

3 to <6 years 5.9 15 5.9 15 

6 to <11 years 4.1 9.9 4.1 9.9 

11 to <16 years 2.9 6.9 2.9 6.9 

16 to <21 years 2.9 6.9 2.9 6.9 

Individual Fruits and Vegetables - See Tables 9-5 and 9-6 

a Analysis was conducted using slightly different 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. 

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Child-Specific 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 was 

adequate. The survey sampled more than 11,000 

individuals up to age 18 years. However, samples size 

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 1994 and 1998. 

Data were collected for two non-consecutive days. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The CSFII data are publicly available. 

The methodology used was clearly described; 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. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were provided for total fruits and total 

vegetables. Means were provided for individuals 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 likely to be greater for 

individual fruits and vegetables. 

Medium 

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Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-2. Confidence in Recommendations for Intake of Fruits and Vegetables (continued) 

General Assessment Factors Rationale Rating 

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 analysis of these data has not 

been peer reviewed outside the Agency. 

There was 1 key study. 

Medium 

Overall Rating 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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Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

9.3 INTAKE STUDIES 

The primary source of recent information on 

consumption rates of fruits and vegetables among 

children is the U.S. Department of Agriculture’s 

(USDA) CSFII. Data from the 1994-96 CSFII and the 

1998 Children’s supplement to the 1994-96 CSFII have 

been used in various studies to generate children’s 

consumer-only and per capita intake rates for both 

individual fruits and vegetables and total fruits and 

vegetables. The CSFII is a series of surveys designed 

to measure the kinds and amounts of foods eaten by 

Americans. The CSFII 1994-96 was conducted 

between January 1994 and January 1997 with a target 

population of non-institutionalized individuals in all 50 

states and Washington, D.C. 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 1994-96 and was intended to be merged with 

CSFII 1994-96 to increase the sample size for children. 

The merged surveys are designated as CSFII 1994-96, 

1998. Additional information on these surveys can be 

obtained at 

http://www.ars.usda.gov/Services/docs.htm?docid=14531. 

The CSFII 1994-96, 1998 collected dietary 

intake data through in-person interviews on 2 nonconsecutive 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. Over 11,000 of the sample persons 

represented children up to 18 years of age. The 2-day 

response rate for the 1994-1996 CSFII was 

approximately 76 percent. The 2-day response rate for 

CSFII 1998 was 82 percent. 

The CSFII 1994-96, 98 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 fours years of the surveys can be combined. 

USDA recommends that all 4 years be combined in 

order to provide an adequate sample size for children. 

9.3.1 Key Fruits and Vegetables Intake Study 

9.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 1998 

For many years, the U.S. EPA’s Office of 

Pesticide Programs (OPP) has used food consumption 

data collected by the U.S. Department of Agriculture 

(USDA) for its dietary risk assessments. Most recently, 

OPP, in cooperation with USDA’s Agricultural 

Research Service (ARS), used data from the 1994-96, 

1998 CSFII to develop the Food Commodity Intake 

Database (FCID). CSFII 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 553 

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/). 

The fruit and vegetable items/groups selected 

for the U.S. EPA analysis included total fruits and total 

vegetables, and individual fruits such as: apples, 

bananas, peaches, pears, strawberries, citrus fruits, 

pome fruit, stone fruit, and tropical fruits; and 

individual vegetables such as: asparagus, beets, 

broccoli, cabbage, carrots, corn, cucumbers, lettuce, 

okra, onions, peas, peppers, pumpkin, beans, tomatoes, 

white potatoes, bulb vegetables, fruiting vegetables, 

leafy vegetables, legumes, and small stalk stem 

vegetables. Appendix 9A presents the food codes and 

definitions used to determine the various fruits and 

vegetables used in the analysis. Intake rates for these 

food items/groups represent intake of all forms of the 

product (e.g., both home produced and commercially 

produced). Children who provided data for two 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. Two-day 

average intake rates were calculated for all individuals 

in the database for each of the food items/groups. 

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Child-Specific Exposure Factors Handbook 

Chapter 9 - Intake of Fruits and Vegetables 

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 four-year, two-day sample weights provided in the 

1994-96, 1998 CSFII to adjust the data for the sample 

population to reflect the national population. 

Summary statistics were generated on both a 

per capita and a consumer only basis. For per capita 

intake, both users and non-users of the food item were 

included in the analysis. Consumer only intake rates 

were calculated using data for only those individuals 

who ate the food item of interest during the survey 

period. Intake data from the CSFII were based on asconsumed (i.e., cooked or prepared) forms of the food 

items/groups. 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. Percentiles of the 

intake rate distribution (i.e., 1st, 5th, 10th, 25th, 50th, 

75th, 90th, 95th, 99th, and 100th percentile) were also 

provided for total fruits and total vegetables. Data were 

provided for the following age groups of children: birth 

to <1 year, 1 to <2 years, 3 to <5 years, 6 to <12 years, 

and 13 to <19 years. Because these data were 

developed for use in U.S. EPA’s pesticide registration 

program, the 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 as-consumed per capita 

intake data for total fruits and vegetables in g/kg-day; 

as-consumed consumer only intake data for total fruits 

and vegetables in g/kg-day are provided in Table 9-4. 

Table 9-5 provides per capita intake data for individual 

fruits and vegetables and Table 9-6 provides consumer 

only intake data for individual fruits and vegetables. 

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 longterm 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 shortterm 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 shortterm 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. 

The strengths of U.S. EPA’s analysis are that 

it provides distributions of intake rates for various age 

groups of children, normalized by body weight. The 

analysis uses the 1994-96, 1998 CSFII data set which 

was designed to be representative of the U.S. 

population. The data set includes four years of intake 

data combined, and is based on a two-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. Also, the analysis 

was conducted using 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). 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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Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

9.3.2	 Relevant Fruit and Vegetable Intake 

Studies 

9.3.2.1	 USDA, 1999 - Food and Nutrient Intakes by 

Children 1994-96, 1998, Table Set 17 

USDA (1999) calculated national probability 

estimates of food and nutrient intake by children based 

on all 4 years of the CSFII (1994-96 and 1998) for 

children age 9 years and under, and on CSFII 1994-96 

only for individuals age 10 years and over. Sample 

weights were used 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 nonconsumers were included in the analysis. 

USDA (1999) 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. Tables 9-7 through 9-10 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. 

The advantage of the USDA (1999) study is 

that it uses the 1994-96, 98 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 a one-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. 

9.3.2.2	 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 1994-96 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. A total of 4,939 of 

these respondents were children, ages 2 to 19 years of 

age. Only dietary intake data from users of the 

specified food were used in the analysis (i.e., consumers 

only data). 

Table 9-1 presents serving size data for 

selected fruits and vegetables. 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 

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Child-Specific Exposure Factors Handbook 

Chapter 9 - Intake of Fruits and Vegetables 

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. 

9.3.2.3	 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 oversampled 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 percent for the 

recruitment interview. Of the recruited households, 

there was a response rate of 94 percent for the dietary 

recall interviews (Devaney et al., 2004). The 

characteristics of the FITS study population is shown in 

Table 9-12. 

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 9-13 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 percent for 4 to 

6 month olds to 81.6 percent for 19 to 24 month olds. 

Table 9-14 provides the top five vegetables consumed 

by age group. Some of the highest percentages ranged 

from baby food carrots (9.6 percent) in the 4 to 6 month 

old group to french fries (25.5 percent) in the 19 to 24 

month old group. Table 9-15 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 percent to 4 to 6 month 

olds to 77.2 percent for 12 to 14 month olds. Table 9­

16 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 were 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). 

9.3.2.4	 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). 

The total sample size described by WIC participants 

and non-participants is shown in Table 9-17. 

The foods consumed were analyzed by 

tabulating the percentage of infants who consumed 

specific foods/food groups per day (Ponza et al., 2004). 

Child-Specific Exposure Factors Handbook Page 

September 2008 9-9 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Weighted data were used in all of the analyses used in 

the study (Ponza et al., 2004). Table 9-17 presents the 

demographic data for WIC participants and nonparticipants. Table 9-18 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 (Table 9-18). 

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 9.3.2.3. 

9.3.2.5	 Menella et al., 2006 - Feeding Infants and 

Toddlers Study: The Types of Foods Fed to 

Hispanic Infants and Toddlers 

Menella 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 

(Menella 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 

and 1,228 non-Hispanic), and 12 to 24 months (N = 124 

Hispanic and 871 non-Hispanic) of age. 

Table 9-19 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 month old 

Hispanic infants were more likely to eat fruits than nonHispanic infants in this age group. Table 9-20 

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 nonHispanic 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 9.3.2.3 for the FITS 

data. 

9.3.2.6	 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 Feeding Infants

and Toddlers Study (FITS). The FITS is a crosssectional 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 9.3.2.3 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 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. Tables 9-21 and 9-22 

present the average portion sizes for fruits and 

vegetables for infants and toddlers, respectively. 

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 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). 

Page Child-Specific Exposure Factors Handbook 

9-10 September 2008 
 100
 −
 W
  IR IR
 =
 (Eqn. 9-1) 

  dw ww 100
 

 

 

 

 

   100 − W C

ww = Cdw 

  100 (Eqn. 9-2)	 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 9 - Intake of Fruits and Vegetables 

If necessary, wet weight (e.g., as-consumed) recommendations for response. Environ 

intake rates may be converted to dry weight intake rates Health Perspect 103(6):13-17. 

using the moisture content percentages presented in Mennella, J.; Ziegler, P.; Briefel, R.; Novak, T. (2006) 

Table 9-23 and the following equation: Feeding Infants and Toddlers Study: the types 

of foods fed to Hispanic infants and toddlers. 

J Am Diet Assoc 106 (Suppl 1): S96-S106. 

Ponza, M.; Devaney, B.; Ziegler, P.; Reidy, K.; 

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: 

Squatrito, C. (2004) Nutrient intakes and food 

choices of infants and toddlers participating in 

WIC. J Am Diet Assoc 104 (Suppl): S71­

S79. 

Smiciklas-Wright, H.; Mitchell, D.C.; Mickle, S.J.; 

Cook, A.J.; Goldman, J.D. (2002) Foods 

commonly eaten in the United States: 

Quantities consumed per eating occasion and 

in a day, 1994-1996. U.S. Department of 

Agriculture NFS Report No. 96-5, prepublication version, 252 pp. 

USDA.	 (1999) Food and nutrient intakes by children 

1994-96, 1998: Table Set 17. Beltsville, MD: 

Food Surveys Research Group, Beltsville 

where: 

Cww = wet weight intake rate; 

Cdw = dry weight intake rate; and 

W = percent water content. 

The moisture data presented in Table 9-23 are 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(Suppl 1): S8­

S13. 

Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L. 

(2004) Feeding Infants and Toddlers Study: 

what foods are infants and toddlers eating. J 

Am Diet Assoc 104 (Suppl):S22-S30. 

Fox, M.K.; 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 (Suppl 1):S66-S76. 

Goldman, L. (1995) Children - unique and vulnerable. 

Environmental risks facing children and 

Human Nutrition Research Center, 

Agricultural Research Service, U.S. 

Department of Agriculture. 

USDA (2007) USDA National Nutrient Database for 

Standard Reference, Release 20. Agricultural 

Research Service Nutrient Data Laboratory 

Home Page, 

http://www.ars.usda.gov/ba/bhnrc/ndl 

U.S. EPA.	 (2005) Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants. 

U.S. Environmental Protection Agency, 

Washington, D.C., EPA/630/P-03/003F. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-11
 
Table 9-3. Per Capita Intake of Fruits and Vegetables (g/kg-day as consumed) 

Age Group N Percent Consuming Mean SE Percentiles 1st 5th 10th 25th 50th 75th 90th 95th 

Fruits 

Birth to 1 year 1,486 56.4 5.7 0.3 0.0 0.0 0.0 0.0 1.5 9.6 17.1 21.3 

1 to 2 years 2,096 89.5 6.2 0.2 0.0 0.0 0.0 0.5 4.7 9.4 14.6 18.5 3 to 5 years 4,391 90.0 4.6 0.1 0.0 0.0 0.0 0.2 3.2 7.0 11.4 14.4 6 to 12 years 2,089 88.3 2.4 0.1 0.0 0.0 0.0 0.1 1.3 3.3 6.4 8.8 

13 to 19 years 1,222 73.2 0.8 0.1 0.0 0.0 0.0 0.0 0.1 1.1 2.4 3.5 

Vegetables 

Birth to 1 year 1,486 72.1 4.5 0.2 0.0 0.0 0.0 0.0 2.7 7.4 12.2 14.8 

1 to 2 years 2,096 99.7 6.9 0.2 0.0 0.7 1.5 3.2 5.6 9.3 13.9 17.1 3 to 5 years 4,391 100.0 5.9 0.1 0.0 0.8 1.4 2.8 4.7 7.7 11.7 14.7 

6 to 12 years 2,089 99.9 4.1 0.1 0.1 0.6 1.0 1.8 3.2 5.3 7.8 9.9 13 to 19 years 1,222 100.0 2.9 0.1 0.0 0.4 0.7 1.4 2.4 3.8 5.5 6.9 

N SE 

= Sample size. = Standard error. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

9-1

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Table 9-4. Consumer Only Intake of Fruits and Vegetables (g/kg-day as consumed) 

Age Group N Mean SE 

Percentiles 

1st 5th 10th 25th 50th 75th 90th 95th 99th 

Fruits 

Birth to 1 year 830 10.1 0.4 0.0 0.4 1.2 3.7 8.5 14.4 20.4 26.4 34.7 

1 to 2 years 1,878 6.9 0.2 0.0 0.0 0.1 2.2 5.4 10.1 15.3 19.0 27.1 

3 to 5 years 3,957 5.1 0.1 0.0 0.0 0.0 1.0 3.8 7.5 11.9 15.0 22.8 

6 to 12 years 1,846 2.7 0.1 0.0 0.0 0.0 0.3 1.7 3.7 6.7 9.3 14.8 13 to 19 years 898 1.1 0.1 0.0 0.0 0.0 0.0 0.5 1.5 2.9 3.7 7.6 

Vegetables 

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 

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 

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 

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 

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 N SE 

= Sample size. = Standard error. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

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Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) 

Age Group N Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming M

Apples Asparagus Bananas Bea

Birth to 1 year 1,486 34.6 2.32 0.13 0.21 0.01 0.00 40.68 1.24 0.06 21.6 01 to 2 years 2,096 44.8 1.79 0.09 0.77 0.02 0.01 62.76 1.77 0.09 46.8 03 to 5 years 4,391 44.6 1.64 0.05 0.54 0.01 0.00 60.74 0.93 0.04 43.0 06 to 12 years 2,089 38.2 0.83 0.05 0.66 0.01 0.00 57.69 0.38 0.03 38.8 013 to 19 years 1,222 22.5 0.20 0.02 0.56 0.00 0.00 42.09 0.13 0.02 55.4 0

Beets Berries and Small Fruit Broccoli Bulb Veg

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

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

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 06 to 12 years 2,089 0.8 0.01 0.00 73.4 0.40 0.03 11.0 0.14 0.02 97.3 013 to 19 years 1,222 0.7 0.00 0.00 97.7 0.19 0.01 8.3 0.06 0.01 12.3 0

Cabbage Carrots Citrus Fruits Cor

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

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 13 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 16 to 12 years 2,089 9.5 0.06 0.01 44.4 0.22 0.01 16.0 0.26 0.02 98.9 013 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

Page Child-Specific Exposure Factors Handbook 

9-14 September 2008 
 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) Age Group N Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming M

Cucumbers Cucurbits Fruiting Vegetables Leafy Ve

Birth to 1 year 1,486 1.7 0.00 0.00 14.0 0.45 0.04 25.50 0.32 0.04 44.2 01 to 2 years 2,096 20.5 0.11 0.01 31.3 0.72 0.06 92.14 1.56 0.06 82.1 0

3 to 5 years 4,391 29.3 0.16 0.02 38.7 0.83 0.07 95.38 1.46 0.03 86.9 0

6 to 12 years 2,089 32.6 0.14 0.02 39.9 0.54 0.06 95.87 1.05 0.03 89.5 0

13 to 19 years 1,222 41.3 0.11 0.03 46.7 0.32 0.08 96.08 0.79 0.03 90.3 0

Legumes Lettuce Okra Onio

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

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

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

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

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

Peaches Pears Peas Pepp

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

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

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

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

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

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-15
 
 

Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) 

Age Group N Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming M

Pome Fruit Pumpkins Root Tuber Vegetables Stalk, Stem 

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

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

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

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

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

Strawberries Stone Fruit Tomatoes Tropical 

Birth to 1 year 1,486 6.8 0.02 0.00 29.20 1.15 0.10 21.5 0.30 0.03 42.2 11 to 2 years 2,096 33.5 0.19 0.03 53.62 0.60 0.04 80.7 1.50 0.05 70.1 1

3 to 5 years 4,391 37.1 0.14 0.01 57.45 0.38 0.02 85.7 1.40 0.03 69.7 1

6 to 12 years 2,089 37.3 0.10 0.01 56.83 0.23 0.02 86.9 1.00 0.03 67.0 0

13 to 19 years 1,222 26.8 0.05 0.01 41.08 0.09 0.01 90.2 0.74 0.03 54.5 0

White Potatoes 

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 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 

vegetables with higher percentages consuming. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

9-16 September 2008 
 

Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) Age Group N Mean SE N Mean SE N Mean SE N Mean 

Apples Asparagus Bananas Beans Birth to 1 year 496 6.71 0.31 3 2.59 1.16 605 3.04 0.12 313 2.00 

1 to 2 years 947 4.00 0.15 19 1.99 0.54 1,328 2.82 0.12 996 1.63 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 6 to 12 years 792 2.17 0.12 13 1.77 0.43 1,214 0.66 0.05 833 0.82 13 to 19 years 271 0.90 0.06 4 0.56 0.08 511 0.30 0.04 472 0.49 

Beets Berries and Small Fruits Broccoli Bulb Vegeta

Birth to 1 year 6 1.42 0.87 229 0.81 0.07 49 2.09 0.33 489 0.22 

1 to 2 years 13 0.98 0.32 1,396 1.38 0.06 242 2.11 0.16 1,957 0.32 3 to 5 years 36 0.90 0.20 3,166 0.99 0.04 475 1.67 0.09 4,207 0.28 6 to 12 years 16 0.66 0.33 1,523 0.54 0.04 213 1.29 0.16 2,040 0.22 13 to 19 years 9 0.20 0.12 679 0.27 0.03 102 0.69 0.07 1,194 0.20 

Cabbage Carrots Citrus Fruits Corn 

Birth to 1 year 15 0.61 0.41 179 1.39 0.20 37 2.79 0.53 671 1.05 1 to 2 years 160 0.73 0.11 999 0.87 0.05 336 3.06 0.20 2,027 1.17 3 to 5 years 369 0.78 0.07 2,048 0.74 0.03 751 2.75 0.15 4,334 1.26 6 to 12 years 190 0.63 0.11 904 0.50 0.03 324 1.60 0.12 2,064 0.88 13 to 19 years 106 0.40 0.06 482 0.27 0.02 157 0.90 0.15 1,176 0.45 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-17
 
 

Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) 

Age Group N Mean SE N Mean SE N Mean SE N Mean 

Cucumbers Cucurbits Fruiting Vegetables Leafy Veget

Birth to 1 year 25 0.28 0.11 213 3.19 0.29 371 1.24 0.11 639 0.65 1 to 2 years 439 0.52 0.05 682 2.29 0.17 1,927 1.70 0.06 1,729 0.87 3 to 5 years 1,266 0.56 0.05 1,694 2.15 0.17 4,180 1.53 0.03 3,815 0.77 6 to 12 years 667 0.43 0.06 833 1.34 0.15 2,014 1.10 0.03 1,860 0.62 13 to 19 years 500 0.26 0.06 563 0.69 0.16 1,176 0.82 0.03 1,101 0.47 

Legumes Lettuce Okra Onions 

Birth to 1 year 754 2.34 0.11 15 0.17 0.02 4 1.50 0.54 481 0.22 1 to 2 years 2,037 1.34 0.08 481 0.58 0.04 29 0.64 0.19 1,948 0.31 3 to 5 years 4,308 0.86 0.06 1,415 0.62 0.03 34 1.16 0.32 4,200 0.27 6 to 12 years 2,045 0.49 0.03 858 0.53 0.02 21 0.62 0.15 2,030 0.21 13 to 19 years 1,168 0.29 0.02 669 0.40 0.03 12 0.43 0.13 1,190 0.19 

Peaches Pears Peas Peppers 

Birth to 1 year 344 3.47 0.28 217 4.55 0.28 417 1.60 0.09 224 0.05 1 to 2 years 1,067 0.93 0.08 354 2.33 0.16 609 1.21 0.06 1,627 0.06 3 to 5 years 2,461 0.48 0.03 711 1.59 0.12 888 1.02 0.07 3,706 0.06 6 to 12 years 1,150 0.26 0.03 382 0.81 0.07 346 0.68 0.06 1,784 0.05 13 to 19 years 480 0.15 0.03 72 0.45 0.09 168 0.48 0.06 1,041 0.05 

Page Child-Specific Exposure Factors Handbook 

9-18 September 2008 
 

Table 9-6. Consumer Only Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) Age Group N Mean SE N Mean SE N Mean SE N Mean 

Pome Fruit Pumpkins Root Tuber Vegetables Stalk, Stem Ve

Birth to 1 year 572 7.60 0.34 3 1.06 0.71 916 4.21 0.19 24 0.56 

1 to 2 years 1,097 4.21 0.13 15 1.08 0.51 2,087 3.40 0.09 272 0.48 

3 to 5 years 2,291 3.68 0.08 36 0.56 0.10 4,388 2.96 0.07 502 0.38 

6 to 12 years. 1,012 2.03 0.10 37 0.52 0.11 2,089 2.09 0.07 218 0.32 

13 to 19 years 320 0.87 0.06 14 0.42 0.16 1,221 1.36 0.06 190 0.20 

Strawberries Stone Fruit Tomatoes Tropical Fr

Birth to 1 year 96 0.26 0.06 418 3.95 0.25 315 1.42 0.13 630 3.09 

1 to 2 years 729 0.57 0.08 1,130 1.13 0.08 1,684 1.86 0.06 1,476 2.81 

3 to 5 years 1,710 0.38 0.03 2,556 0.66 0.03 3,764 1.63 0.03 3,106 1.57 

6 to 12 years. 783 0.28 0.02 1,194 0.41 0.03 1,832 1.15 0.03 1,407 0.75 13 to 19 years 326 0.18 0.03 508 0.21 0.03 1,098 0.82 0.03 652 0.35 

White Potatoes 

Birth to 1 year 577 1.60 0.15 1 to 2 years 1,918 2.14 0.09 3 to 5 years 4,147 1.84 0.06 6 to 12 years. 1,963 1.29 0.06 13 to 19 years 1,131 1.01 0.05 

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 f

vegetables with higher percentages consuming. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-19
 
 

Table 9-7. Mean Quantities of Vegetables Consumed Daily by Sex and Age, Per Capita (g/day) 

Age Group Sample Size Total 

White Potatoes 

Dark Green 

Vegetables 

Deep 

Yellow 

Vegetables 

Tomatoes 

Lettuce, 

lettucebased 

salads 

Green 

beans 

Total Fried 

Corn, 

green 

peas, lima 

beans 

Males and Females 

Under 1 year 1 year 2 years 

1 to 2 years 

3 years 4 years 5 years 

3 to 5 years 5 years and under 

1,126 1,016 1,102 2,118 1,831 1,859 

884 

4,574 7,818 

57 79 87 83 91 97 

103 

97 88 

9 

26 32 29 34 37 44 38 31 

1 

11 17 14 17 19 22 20 16 

2 5 4 5 5 6 4 5 4 

19 

9 5 7 5 5 6 5 7 

1a 

7 

11 

9 

13 11 12 12 10 

a,b 

1 2 1 2 3 3 3 2 

6 8 7 7 5 5 6 5 6 

5 9 

10 

9 

11 12 12 11 10 

Males 

6 to 9 years 6 to 11 yers 12 to 19 years 

787 

1,031 

737 

110 115 176 

47 50 85 

26 27 44 

4 5 6 

5 5 6 

16 16 28 

5 5 

12 

5 5 

3a 

11 11 10 

Females 

6 to 9 years 6 to 11 years 12 to 19 years 

704 969 732 

110 116 145 

42 46 61 

22 25 31 

5 5 9 

4 4 4 

14 15 18 

6 7 

12 

5 5 4 

13 12 

8 

Males and Females 

9 years and under 19 years and under 

9,309 

11,287 

97 

125 

37 53 

19 27 

4 6 

6 6 

12 17 

3 7 

6 5 

11 10 

a Estimate is not statistically reliable due to small samples size reporting intake. b 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, 1999. 

Page Child-Specific Exposure Factors Handbook 

9-20 September 2008 
 

Table 9-8. Percentage of Individuals Consuming Vegetables, by Sex and Age (%) Age Group Sample Size Total White Potatoes Dark Green Vegetables Deep Yellow Vegetables Tomatoes Lettuce, lettuce- based salads Total Fried Green beans Corn, green peas, lima beans 

Males and Females Under 1 year 1 year 2 years 1 to 2 years 3 years 4 years 5 years 3 to 5 years 5 years and under 1,126 1,016 1,102 2,118 1,831 1,859 884 4,574 7,818 47.2 73.3 78.4 75.9 80.5 80.7 83.0 81.4 75.4 12.3 40.4 46.7 43.6 46.7 47.3 50.7 48.2 42.3 4.3 25.2 34.5 29.9 34.7 34.8 38.3 35.9 30.1 2.3 6.4 7.6 7.0 7.0 7.2 4.6 6.3 6.1 20.5 13.3 10.5 11.8 10.7 12.0 13.3 12.0 13.0 1.8 18.0 30.8 24.6 34.1 33.0 36.5 34.5 27.2 0.2a 3.9 7.5 5.7 8.3 10.0 13.4 10.6 7.6 7.8 13.7 11.5 12.6 10.1 9.0 10.4 9.9 10.5 8.5 17.6 15.0 16.2 14.6 16.4 16.1 15.7 15.0 

Males 

6 to 9 years 6 to 11 years 12 to 19 years 

787 

1,031 

737 

78.8 79.3 78.2 

47.9 48.7 49.5 

38.0 38.4 38.6 

6.3 6.1 3.6 

12.5 12.4 

8.0 

38.2 38.7 43.0 

13.1 13.9 23.8 

7.8 6.7 3.5 

15.0 13.8 

7.4 

Females 

6 to 9 years 6 to 11 years 12 to 19 years 

704 969 732 

80.5 81.7 79.5 

48.2 50.8 46.4 

36.3 38.9 34.6 

5.9 5.4 7.0 

11.9 11.4 10.6 

33.8 33.5 35.3 

15.8 17.1 25.1 

8.4 7.8 4.4 

15.9 15.1 

7.4 

Males and Females 

9 years and under 19 years and under 

9,309 

11,287 

77.1 78.3 

44.6 46.8 

32.9 35.3 

6.1 5.6 

12.7 11.2 

30.7 34.6 

10.3 16.6 

9.6 7.0 

15.2 11.9 

a Estimate is not statistically reliable due to small samples size reporting intake. 

Note: Percentages shown are representative of the first day of each participant’s survey response. Source: USDA, 1999. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-21
 
Table 9-9. Mean Quantities of Fruits Consumed Daily by Sex and Age, Per Capita (g/day) 

Citrus Fruits and 

Juices Other fruits, mixtures, and juices 

Age Group Sample Size Total 

Total Juices 

Dried 

fruits 

Total Apples 

Bananas Melons 

and 

berries 

Other 

fruits and 

mixtures 

(mainly 

fruit) 

Males and Females 

Under 1 year 1,126 131 4 4 -a,b 126 14 10 1a 39 

1 year 1,016 267 47 42 2 216 22 23 8 29 2 years 1,102 276 65 56 2 207 27 20 10 20 

1 to 2 years 2,118 271 56 49 2 212 24 22 9 24 

3 years 1,831 256 61 51 1 191 27 18 13 24 4 years 1,859 243 62 52 1 177 31 17 14 22 

5 years 884 218 55 44 -a,b 160 31 14 13 24 

3 to 5 years 4,574 239 59 49 1 176 30 16 13 23 

5 years and under 7,818 237 52 44 1 182 26 17 10 26 

Males 

6 to 9 years 787 194 58 51 -a,b 133 32 11 21 20 6 to 11 years 1,031 183 67 60 -a,b 113 28 11 16 19 12 to 19 years 737 174 102 94 1a 70 13 8 11a 10 

Females 

6 to 9 years 704 180 63 54 1a 113 23 10 10 25 

6 to 11 years 969 169 64 54 -a,b 103 21 8 8 23 12 to 19 years 732 157 72 67 -a,b 83 13 5 15 14 

Males and Females 

9 years and under 9,309 217 55 47 1 159 27 15 12 24 19 years and under 11,287 191 70 62 1 118 21 11 12 19 

a Estimate is not statistically reliable due to small samples size reporting intake. b 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, 1999. 

9-2

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e Child-Specific Exposure Fa

S

ct

e

o

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s 

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a

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d

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0

o

0

o

8 

k 
Table 9-10. Percentage of Individuals Consuming, Fruits by Sex and Age (%) 

Citrus Fruits and Other fruits, mixtures, and juices Juices 

Age Group 

Sample Dried Other Total 

Size fruits Melons fruits and 

Total Juices Total Apples Bananas and mixtures 

berries (mainly 

fruit) 

Males and Females 

Under 1 year 1,126 59.7 3.6 2.7 0.4a 59.0 15.7 13.3 1.8 29.9 

1 year 1,016 81.0 23.6 19.0 5.9 73.0 23.4 25.1 6.9 26.5 2 years 1,102 76.6 30.6 23.4 5.3 64.7 24.0 20.2 8.5 19.4 

1 to 2 years 2,118 78.8 27.2 21.3 5.6 68.8 23.7 22.6 7.7 22.9 

3 years 1,831 74.5 27.9 21.4 4.1 64.2 22.4 17.5 7.8 20.1 4 years 1,859 72.6 28.0 21.8 3.0 62.1 23.7 15.7 7.6 20.0 5 years 884 67.6 26.9 19.5 1.3a 56.9 21.9 12.6 7.4 19.0 

3 to 5 years 4,574 71.6 27.6 20.9 2.8 61.0 22.7 15.3 7.6 19.7 5 years and under 7,818 72.6 24.6 18.8 3.5 63.5 22.2 17.6 6.9 22.0 

Males 

6 to 9 years 787 59.0 24.8 20.5 0.8a 49.1 20.3 8.7 7.3 16.8 

6 to 11 years 1,031 56.5 25.2 21.6 1.1a 44.2 18.2 8.0 6.6 15.4 12 to 19 years 737 44.5 24.7 21.7 1.0a 27.1 8.2 6.0 4.1 7.1 

Females 

6 to 9 years 704 64.9 27.9 22.3 1.5a 50.4 17.3 8.8 7.4 20.4 6 to 11 years 969 62.1 27.7 21.5 1.1a 47.2 16.2 7.3 7.4 19.0 12 to 19 years 732 45.6 22.4 18.1 1.1a 30.2 8.2 4.4 6.0 11.3 

Males and Females 

9 years and under 9,309 68.3 25.2 19.8 2.5 58.0 20.9 14.0 7.1 20.6 19 years and under 11,287 57.8 24.8 20.1 1.8 44.4 15.2 9.7 6.2 15.5 

a Estimate is not statistically reliable due to small samples size reporting intake.
 

Note: Percentages shown are representative of the first day of each participant’s survey response.
 Source: USDA, 1999. 

SCehpitledm

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8 

Exposure Factors Handbook 

9-

Pa2g

3 

e 
 

Table 9-11. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and 

Percentage of Individuals Using These Foods in Two Days 

Quantity consumed per eating occasion (grams) 

2 to 5 years 6 to 11 years 12 to 19 years 

Food category Male and Female Male and Female Male Fem

(N = 2,109) (N = 1,432) (N = 696) (N = 

PC Mean. SEM PC Mean SEM PC Mean SEM PC Me

Raw Vegetables 

Carrots 10.4 27 2 17.8 32 2 9.2 35 6 11.9 32 Cucumbers 6.4 32 4 6.6 39 6 6.1 71a 22a 6.8 48 

Lettuce 34.0 17 1 40.8 26 1 56.0 32 3 52.3 34 

Onions 3.9 9 2 4.5 17 2 11.1 28 4 7.9 23 Tomatoes 14.8 31 2 14.0 42 4 25.7 49 5 23.9 44 

Cooked Vegetables 

Beans (string) 16.8 50 2 12.1 71 6 8.3 85 9 7.6 78 Broccoli 7.2 61 3 5.6 102 16 3.9 127a 17a 5.7 10

Carrots 6.0 48 4 3.8 46 5 2.8 81a 16a 2.1 75Corn 18.9 68 3 22.2 79 4 12.8 125 9 12.3 10Peas 8.4 48 3 6.8 72 9 3.6 115a 15a 2.4 93Potatoes (French-fried) 32.7 52 1 33.7 67 2 41.7 97 3 38.1 8Potatoes (home-fried and hash-browned) 9.3 85 5 10.1 93 6 10.1 145 13 6.1 13Potatoes (baked) 7.6 70 4 8.2 95 6 8.6 152 15 8.8 11Potatoes (boiled) 4.8 81 9 2.7 103a 17a 2.0 250a 40a 3.2 14Potatoes (mashed) 14.8 118 6 13.3 162 12 14.6 245 16 11.9 17

Fruits 

Apples (raw) 26.8 106 2 21.9 123 3 11.7 149 9 12.4 12Apples (cooked and applesauce) 10.1 118 5 9.0 130 7 2.3 153a 19a 2.6 20

Apple juice 26.3 207 5 12.2 223 10 7.8 346 22 8.5 36Bananas (raw) 25.0 95 2 16.5 105 3 10.3 122 6 8.4 11Oranges (raw) 11.1 103 5 10.5 114 5 4.3 187a 38a 5.4 10Orange juice 34.4 190 4 30.9 224 6 30.8 354 16 29.5 30

a Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation
 

PC = Percent consuming at least once in 2 days.
 SEM = Standard error of the mean.
 Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data). 

Page Child-Specific Exposure Factors Handbook 

9-24 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-12. Characteristics of the FITS Sample Population 

Sample Size Percentage of Sample 

Gender 

Male 

Female 

1,549 

1,473 

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 

Child’s Ethnicity 

Hispanic or Latino 

Non-Hispanic or Latino 

Missing 

367 

2,641 

14 

Child’s Race 

White 

Black 

Other 

2,417 

225 

380 

Urbanicity 

Urban 

Suburban 

Rural 

Missing 

1,389 

1,014 

577 

42 

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 

Receives WIC 

Yes 

No 

Missing 

821 

2,196 

5 

Sample Size (Unweighted) 3,022 

51.3 

48.7 

28.5 

16.0 

22.5 

12.4 

10.2 

10.4 

12.1 

87.4 

0.5 

80.0 

7.4 

12.6 

46.0 

33.6 

19.1 

1.3 

1.6 

1.6 

7.3 

11.9 

23.9 

19.5 

10.3 

9.0 

14.9 

27.2 

72.6 

0.2 

100.0 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Devaney et al., 2004. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-25
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-13. 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 7 to 8 9 to 11 12 to 14 15 to 18 19 to 24 

months months months months months 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. 

Page Child-Specific Exposure Factors Handbook 

9-26 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-14. 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-27
 
 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-15. 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 12 to 14 15 to 18 19 to 24 

months months months 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 Fruita 

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. 

Page Child-Specific Exposure Factors Handbook 

9-28 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-16. 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-29
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-17. Characteristics of WIC Participants and Non-participantsa (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 

Gender 

Male 55 54 55 51 57 52
 

Female
 45 46 45 49 43 48 

Child’s Ethnicity **   

Hispanic or Latino 20 11 24 8 22 10 

Non-Hispanic or 80 89 76 92 78 89 

 Latino 

Child’s Race **  ** ** 

White 63 84 63 86 67 84 

Black 15 4 17 5 13 5 

Other 22 11 20 9 20 11 

Child In Day Care ** * 

Yes 39 38 34 46 43 53
 

No 61 62 66 54 57 47
 

Age of Mother **   

14 to 19 18 1 13 1 9 1 

20 to 24 33 13 38 11 33 14 

25 to 29 29 29 23 30 29 26 

9 33 15 36 18 34 30 to 34 

9 23 11 21 11 26 35 or Older 2 2 1 1 0 1 Missing 

Mother’s Education **  ** ** 

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 

7 53 9 51 9 48 Completed College 2 1 2 0 1 2 Missing 

Parent’s Marital Status   **  

Married 49 93 57 93 58 88
 

Not Married 50 7 42 7 41 11
 

Missing 1 1 1 0 1 1
 

Page Child-Specific Exposure Factors Handbook 

9-30 September 2008 
Table 9-17. Characteristics of WIC Participants and Non-participants a (Percentages) (continued) 

Infants 4 to 6 months Infants 7 to 11 months Toddlers 12 to 24 months 

WIC 

Participant Non-participant 

WIC 

Participant Non-participant 

WIC 

Participant Non-participant 

Mother or Female Guardian Works ** * 

 Yes 46 

 No 53 

 Missing 1 

51 

48 

 1 

45 

54 

 1 

60 

40 

 0 

55 

45 

 0 

61 

38 

 1 

Urbanicity ** ** ** 

 Urban 34 

 Suburban 36 

 Rural 28 

 Missing 2 

Sample Size 265 

(Unweighted) 

 55 

 31 

 13 

 1 

597 

 37 

 31 

 30 

 2 

351 

 50 

 34 

 15 

 1 

808 

 35 

 35 

 28 

 2 

205 

 48 

 35 

 16 

 2 

791 

a 

WIC 

 X2 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 X2 test are listed next to the variable under the column labeled non-participants for 

each of the three age groups. * P<0.05; **P>0.01; non-participants significantly different from WIC participants on the variable. 

= Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Ponza et al., 2004. 

Child-Specific Exposure Factors Handbook 

Chapter 9 - Intake of Fruits and Vegetables 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-31
 
Table 9-18. 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 NonParticipant participant WIC NonParticipant participant WIC NonParticipant participant 

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 

 3.9* 

 0.1** 

 0.0 

28.1 

 6.4 

 2.4* 

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 

39.2* 

36.9 

4.0 

3.8 

 0.5** 

64.7 

48.4 

22.9 

14.3 

10.3 

81.0** 

57.4* 

35.9** 

24.3** 

17.3** 

58.5 

 3.8 

56.4 

43.6 

22.3 

74.6** 

6.5 

 70.9** 

 57.0** 

25.3 

Sample Size (unweighted) 265 597 351 808 205 791 

* 

** 

WIC 

= P<0.05 non-participants significantly different from WIC participants. 

= P<0.01 non-participants significantly different from WIC participants. 

= Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Ponza et al. 2004. 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9-32 September 2008 
Table 9-19. 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 Non-Hispanic 

(n=84) (n=538) 

Hispanic Non-Hispanic 

(n=163) (n=1,228) 

Hispanic Non-Hispanic 

(n=124) (n=871) 

Fruits 

Any Fruit or 100% Fruit Juice 

 AnyFruita 

 100%Fruit Juice 

Fruit Preparation 

 BabyFood Fruit 

 Non-Baby Food Fruit 

 CannedFruit 

 FreshFruit 

45.0 

39.4 

19.3 

32.6 

 9.1† 

 2.3† 

 9.1*† 

35.9 

28.8 

15.3 

28.4 

 1.3† 

-

-

86.2 

68.1 

57.8 

42.9* 

35.8 

 8.8 

30.0** 

86.8 

76.0 

47.7 

58.1 

27.4 

13.7 

17.7 

84.6 

67.6 

64.1 

 5.6† 

64.2 

12.1** 

59.3 

87.2 

71.5 

58.9 

 6.3 

68.0 

26.2 

53.1 

Vegetables 

Any Vegetable or 100% Vegetable 

b Juice

Type of Preparation 

 BabyFood Vegetables 

 CookedVegetables 

 RawVegetables b Types of Vegetables 

 DarkGreen Vegetablesc 

d DeepYellow Vegetables

 Starchy Vegetable: 

 WhitePotatoes 

 French Fries/Fried Potatoes 

 Baked/Mashed 

 OtherStarchy Vegetablese 

f OtherNon-starchy Vegetables

30.0 

25.7 

 4.2† 

 2.3† 

-

21.0 

 1.4† 

-

-

 5.0† 

 8.1† 

27.3 

25.4 

 2.4† 

-

-

18.2 

 2.3† 

-

-

 4.0 

 8.0 

66.2 

34.4* 

33.2 

 8.3† 

 3.3† 

32.2 

20.7 

 5.7† 

14.4† 

 6.7** 

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 

 4.1† 

71.4 

25.0 

11.4† 

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	 

b	 

c 

d	 

e	 

f	 

-	

* 

** 

†	 

Total includes all baby food and non-baby food fruits and excludes 100% fruit juices and juice drinks. 

Total includes commercial baby food, cooked vegetables, raw vegetables, and 100% vegetable juices. 

Reported dark green vegetables include broccoli, spinach, romaine lettuce and other greens such as kale. 

Reported yellow vegetables include carrots, pumpkin, sweet potatoes, and winter squash. 

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. 

Reported non-starchy vegetables include asparagus, cauliflower, cabbage, onions, green beans, mixed vegetables, peppers, and 

tomatoes. 

= Less than 1 percent of the group consumed this food on a given day. 

= Significantly different from non-Hispanic at the P<0.05. 

= Significantly different from non-Hispanic at the P>0.01. 

= Statistic is potentially unreliable because of a high coefficient of variation. 

Source:	 Mennella et al., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 9 - Intake of Fruits and Vegetables 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-33
 
Table 9-20. Top Five Fruits and Vegetables Consumed by Hispanic and Non-Hispanic Infants 

and Toddlers Per Age Group a 

Ethnicity 

Hispanic Non-Hispanic 

Top Fruits By Age Group 

4 to 5 months Bananas (16.3%) 

Apples (14.7%) 

Peaches (10.9%) 

Melons (3.5%) 

Pears (2.5%) 

Apples (12.5%) 

Bananas (10.0%) 

Pears (5.9%) 

Peaches (5.8%) 

Prunes (1.6%) 

6 to 11 months Bananas (35.9%) 

Apples (29.7%) 

Pears (15.2%) 

Peaches (11.7%) 

Melons (4.7%) 

Apples (32.9%) 

Bananas (31.5%) 

Pears (17.5%) 

Peaches (13.9%) 

Apricots (3.7%) 

12 to 24 months Bananas (41.5%) 

Apples (25.7%) 

Berries (8.5%) 

Melons (7.6%) 

Pears (7.3%) 

Bananas (30.9%) 

Apples (22.0%) 

Grapes (12.3%) 

Peaches (9.6%) 

Berries (8.7%) 

Top Vegetables By Age Group 

4 to 5 months Carrots (9.9%) 

Sweet Potatoes (6.8%) 

Green Beans (5.8%) 

Peas (5.0%) 

Squash (4.3%) 

Sweet Potatoes (7.5%) 

Carrots (6.6%) 

Green Beans (5.9%) 

Squash (5.4%) 

Peas (3.8%) 

6 to 11 months 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 months 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. 

Source: Mennella, et al., 2006. 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9-34 September 2008 
Table 9-21. Average Portion Sizes per Eating Occasion of Fruits and Vegetables 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± SEM 

Fruits and Juices 

All fruits tablespoon 3.6±0.19 4.7±0.11 5.8±0.17 

 Babyfood fruit tablespoon 3.3±0.16 4.6±0.11 5.6±0.17 

 Babyfood peaches tablespoon 3.6±0.37 4.4±0.26 5.3±0.36 

 Babyfood pears tablespoon 3.5±0.46 4.5±0.21 6.0±0.40 

 Babyfood bananas tablespoon 3.4±0.23 5.0±0.21 5.9±0.35 

 Babyfood applesauce tablespoon 3.7±0.29 4.6±0.17 5.6±0.25 

 Cannedfruit tablespoon - 4.5±0.59 4.8±0.25 

 Freshfruit 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 

 Babyfood vegetables tablespoon 4.0±0.20 5.9±0.16 6.6±0.21 

 Babyfood green beans tablespoon 3.5±0.33 5.1±0.28 6.1±0.50 

 Babyfood squash tablespoon 4.3±0.47 5.6±0.30 6.9±0.41 

 Babyfood sweet tablespoon 4.3±0.31 6.1±0.34 7.2±0.69 

 Babyfood 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 

 Deepyellow vegetables tablespoon - 3.2±0.59 3.2±0.39 

 Mashedpotatoes tablespoon - 4.1±0.67 2.8±0.37 

 Greenbeans tablespoon - 3.2±0.62 5.0±0.61 

- = Cell size was too small to generate a reliable estimate.
 

N = Number of respondents.
 

SEM = Standard error.
 

Source: Fox et al., 2006.
 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-35
 
Table 9-22. 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± SEM 

Fruits and Juices 

All fruits 

 Cannedfruit 

 Freshfruit 

 Freshapple 

cup 

cup 

cup 

cup, slice 

1 medium 

0.4±0.02 

0.3±0.02 

0.4±0.02 

0.4±0.05 

0.3±0.04 

0.5±0.03 

0.4±0.03 

0.5±0.03 

0.6±0.07 

0.5±0.06 

0.6±0.03 

0.4±0.04 

0.6±0.03 

0.8+0.14 

0.6±0.11 

 Freshbanana cup, slice 

1 medium 

0.4+0.02 

0.6±0.03 

0.5±0.03 

0.7±0.03 

0.5±0.03 

0.7±0.04 

 Freshgrapes 

 100%juice 

 Orange/orange blends 

 Apple/apple blends 

cup 

fluid ounce 

fluid ounce 

fluid ounce 

0.2±0.01 

3.7±0.15 

3.3+0.38 

3.6±0.21 

0.3±0.03 

5.0±0.20 

4.5±0.33 

4.5±0.29 

0.3±0.02 

5.1±0.18 

5.2±0.35 

4.9±0.27 

 Grape fluid ounce 3.6±0.38 5.6±0.43 4.7±0.31 

Vegetables 

All vegetables 

 Cookedvegetables, 

 excluding french fries 

 Deepyellow vegetables 

 Corn 

 Peas 

 Greenbeans 

 Mashedpotatoes 

 Baked, boiled potatoes 

 Frenchfries 

cup 

cup 

cup 

cup 

cup 

cup 

cup 

cup 

cup 

0.4±0.02 

0.3±0.03 

0.2±0.03 

0.2±0.03 

0.2±0.02 

0.4±0.05 

0.3±0.05 

0.3±0.05 

0.4±0.05 

0.4±0.03 

0.3±0.03 

0.3±0.05 

0.2±0.03 

0.2±0.02 

0.4±0.05 

0.4±0.05 

0.4±0.06 

0.6±0.05 

0.4±0.02 

0.3±0.02 

0.3±0.05 

0.2±0.03 

0.2±0.02 

0.3±0.03 

0.3±0.05 

-

0.6±0.05 

-

N 

SEM 

Cell size too small to generate reliable estimate.
 

= Number of respondents.
 

= Standard error of the mean.
 

Source: Fox et al., 2006.
 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9-36 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-23. 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 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-37
 
Table 9-23. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued) 

Food 

Moisture Content 

Raw Cooked 

Comments 

Plums - dried (prunes) 

Plums 

Quinces 

Raspberries 

Strawberries 

Tangerine - juice 

Tangerines 

Watermelon 

30.92 

87.23 

83.80 

85.75 

90.95 

88.90 

85.17 

91.45 

84.02* 

89.97* 

87.00* 

89.51* 

*canned juice pack 

*frozen unsweetened 

*canned sweetened 

*canned juice pack 

Vegetables 

Alfalfa seeds - sprouted 

Artichokes - globe & French 

Artichokes - Jerusalem 

Asparagus 

Bamboo shoots 

Beans - dry - blackeye peas (cowpeas) 

Beans - dry - hyacinth (mature seeds) 

Beans - dry - navy (mature seeds) 

Beans - dry - pinto (mature seeds) 

Beans - lima 

Beans - snap - green - yellow 

Beets 

Beets - tops (greens) 

Broccoli 

Brussel sprouts 

Cabbage - Chinese (pak-choi) 

Cabbage - red 

Cabbage - savoy 

Carrots 

Cassava (yucca blanca) 

Cauliflower 

Celeriac 

Celery 

Chives 

Cole slaw 

Collards 

Corn - sweet 

Cress - garden 

Cucumbers - peeled 

Dandelion - greens 

Eggplant 

Endive 

Garlic 

Kale 

Kohlrabi 

92.82 

84.94 

78.01 

93.22 

91.00 

77.20 

87.87 

79.15 

81.30 

70.24 

90.27 

87.58 

91.02 

90.69 

86.00 

95.32 

90.39 

91.00 

88.29 

59.68 

91.91 

88.00 

95.43 

90.65 

81.50 

90.55 

75.96 

89.40 

96.73 

85.60 

92.41 

93.79 

58.58 

84.46 

91.00 

84.08 

92.63 

95.92 

75.48 

86.90 

76.02 

93.39 

67.17 

89.22 

87.06 

89.13 

89.25 

88.90 

95.55 

90.84 

92.00 

90.17 

93.00 

92.30 

94.11 

91.86 

69.57 

92.50 

89.80 

89.67 

91.20 

90.30 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

boiled, drained 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9-38 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9-23. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued) 

Food 

Moisture Content 

Comments 

Raw Cooked 

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 & liquid 

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 

Towelgourd 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 

Source: USDA, 2007. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9-39
 
 

 

Child-Specific Exposure Factors Handbook 

Chapter 9 - Intake of Fruits and Vegetables 

APPENDIX 9A
 

CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS FRUITS AND
 

VEGETABLES USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9A-1
 
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data 

Food Category EPA Food Commodity Codes 

TOTAL FRUITS AND VEGETABLES 

Total Fruits 95000010 Acerola 

11000090 Apple, dried 

11000091 Apple, dried-babyfood 

11000070 Apple, fruit with peel 

11000080 Apple, peeled fruit 

11000081 Apple, peeled fruit-babyfood 

11000110 Apple, sauce 

11000111 Apple, sauce-babyfood 

12000120 Apricot 

12000130 Apricot, dried 

12000121 Apricot-babyfood 

95000200 Avocado 

95000230 Banana 

95000240 Banana, dried 

95000241 Banana, dried-babyfood 

95000231 Banana-babyfood 

13010550 Blackberry 

13020570 Blueberry 

13020571 Blueberry-babyfood 

13010580 Boysenberry 

95000600 Breadfruit 

95000740 Canistel 

95000890 Cherimoya 

12000900 Cherry 

12000901 Cherry-babyfood 

10001060 Citrus citron 

10001070 Citrus hybrids 

95001120 Coconut, dried 

95001110 Coconut, meat 

95001111 Coconut, meat-babyfood 

95001130 Coconut, milk 

11001290 Crabapple 

95001300 Cranberry 

95001310 Cranberry, dried 

95001301 Cranberry-babyfood 

13021360 Currant 

13021370 Currant, dried 

95001410 Date 

13011420 Dewberry 

08001480 Eggplant 

13021490 Elderberry 

95001510 Feijoa 

95001530 Fig 

95001540 Fig, dried 

13021740 Gooseberry 

95001750 Grape 

95001780 Grape, raisin 

10001800 Grapefruit 

95001830 Guava 

95001831 Guava-babyfood 

13021910 Huckleberry 

95001920 Jaboticaba 

95001930 Jackfruit 

95001950 Kiwifruit 

10001970 Kumquat 

10001990 Lemon 

10002010 Lemon, peel 

10002060 Lime 

13012080 Loganberry 

95002090 Longan 

11002100 Loquat 

95002110 Lychee 

95002120 Lychee, dried 

95002140 Mamey apple 

95002150 Mango 

95002160 Mango, dried 

95002151 Mango-babyfood 

95002270 Mulberry 

12002300 Nectarine 

10002400 Orange 

10002420 Orange, peel 

95002450 Papaya 

95002460 Papaya, dried 

95002451 Papaya-babyfood 

95002520 Passionfruit 

95002521 Passionfruit-babyfood 

95002540 Pawpaw 

12002600 Peach 

12002610 Peach, dried 

12002611 Peach, dried-babyfood 

12002601 Peach-babyfood 

11002660 Pear 

11002670 Pear, dried 

11002661 Pear-babyfood 

95002770 Persimmon 

95002790 Pineapple 

95002800 Pineapple, dried 

95002791 Pineapple-babyfood 

95002830 Plantain 

95002840 Plantain, dried 

12002850 Plum 

12002870 Plum, prune, dried 

12002871 Plum, prune, dried-babyfood 

12002860 Plum, prune, fresh 

12002861 Plum, prune, fresh-babyfood 

12002851 Plum-babyfood 

95002890 Pomegranate 

10003070 Pummelo 

11003100 Quince 

13013200 Raspberry 

13013201 Raspberry-babyfood 

95003330 Sapote, Mamey 

95003460 Soursop 

95003510 Spanish lime 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9A-2 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Total Fruits 

(continued) 

95003580 Starfruit 

95003590 Strawberry 

95003591 Strawberry-babyfood 

95003610 Sugar apple 

95003680 Tamarind 

10003690 Tangerine 

Total Vegetables 18000020 Alfalfa, seed 

04010050 Amaranth, leafy 

01030150 Arrowroot, flour 

01030151 Arrowroot, flour-babyfood 

95000160 Artichoke, globe 

01030170 Artichoke, Jerusalem 

04010180 Arugula 

95000190 Asparagus 

09020210 Balsam pear 

95000220 Bamboo, shoots 

19010290 Basil, dried leaves 

19010291 Basil, dried leaves-babyfood 

19010280 Basil, fresh leaves 

19010281 Basil, fresh leaves-babyfood 

06020330 Bean, cowpea, succulent 

06030360 Bean, kidney, seed 

06030380 Bean, lima, seed 

06020370 Bean, lima, succulent 

06030390 Bean, mung, seed 

06030400 Bean, navy, seed 

06030410 Bean, pink, seed 

06030420 Bean, pinto, seed 

06010430 Bean, snap, succulent 

06010431 Bean, snap, succulent-babyfood 

01010500 Beet, garden, roots 

01010501 Beet, garden, roots-babyfood 

02000510 Beet, garden, tops 

95000540 Belgium endive 

05010610 Broccoli 

05020630 Broccoli raab 

05010620 Broccoli, Chinese 

05010611 Broccoli-babyfood 

05010640 Brussels sprouts 

05010690 Cabbage 

05020700 Cabbage, Chinese, bok choy 

05010720 Cabbage, Chinese, mustard 

05010710 Cabbage, Chinese, napa 

95000730 Cactus 

09010750 Cantaloupe 

04020760 Cardoon 

01010780 Carrot 

01010781 Carrot-babyfood 

09010800 Casaba 

01030820 Cassava 

01030821 Cassava-babyfood 

05010830 Cauliflower 

01010840 Celeriac 

04020850 Celery 

04020851 Celery-babyfood 

04020870 Celtuce 

09020880 Chayote, fruit 

06030990 Chickpea, flour 

06030980 Chickpea, seed 

06030981 Chickpea, seed-babyfood 

01011000 Chicory, roots 

02001010 Chicory, tops 

09021020 Chinese waxgourd 

19011030 Chive 

04011040 Chrysanthemum, garland 

19021050 Cinnamon 

19021051 Cinnamon-babyfood 

19011180 Coriander, leaves 

19011181 Coriander, leaves-babyfood 

19021190 Coriander, seed 

19021191 Coriander, seed-babyfood 

04011380 Dandelion, leaves 

01031390 Dasheen, corm 

02001400 Dasheen, leaves 

19011440 Dill 

19021430 Dill, seed 

04021520 Fennel, Florence 

03001640 Garlic 

03001650 Garlic, dried 

03001651 Garlic, dried-babyfood 

01031660 Ginger 

01031670 Ginger, dried 

01031661 Ginger-babyfood 

01011680 Ginseng, dried 

95001770 Grape, leaves 

06031820 Guar, seed 

06031821 Guar, seed-babyfood 

19011840 Herbs, other 

19011841 Herbs, other-babyfood 

05021940 Kale 

05011960 Kohlrabi 

03001980 Leek 

19012020 Lemongrass 

04012040 Lettuce, head 

04012050 Lettuce, leaf 

19012200 Marjoram 

19012201 Marjoram-babyfood 

08002340 Okra 

03002370 Onion, dry bulb 

03002380 Onion, dry bulb, dried 

03002381 Onion, dry bulb, dried-babyfood 

03002371 Onion, dry bulb-babyfood 

03002390 Onion, green 

95002430 Palm heart, leaves 

19012490 Parsley, dried leaves 

19012491 Parsley, dried leaves-babyfood 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9A-3
 
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Total Vegetables 

(continued) 

04012480 

01012500 

01012510 

01012511 

06032560 

06032561 

06012570 

06032580 

06022590 

06022550 

06022551 

08002700 

08002710 

08002711 

08002701 

19022740 

19022741 

08002720 

08002730 

08002721 

95002750 

01032960 

01032970 

01032971 

01032980 

01032981 

01033000 

01033001 

01032990 

01032991 

09023080 

04013130 

01013160 

02003170 

01013140 

02003150 

05023180 

04023220 

Parsley, leaves 

Parsley, turnip rooted 

Parsnip 

Parsnip-babyfood 

Pea, dry 

Pea, dry-babyfood 

Pea, edible podded, succulent 

Pea, pigeon, seed 

Pea, pigeon, succulent 

Pea, succulent 

Pea, succulent-babyfood 

Pepper, bell 

Pepper, bell, dried 

Pepper, bell, dried-babyfood 

Pepper, bell-babyfood 

Pepper, black and white 

Pepper, black and white-babyfood 

Pepper, nonbell 

Pepper, nonbell, dried 

Pepper, nonbell-babyfood 

Peppermint 

Potato, chips 

Potato, dry (granules/ flakes) 

Potato, dry (granules/ flakes)-babyfood 

Potato, flour 

Potato, flour-babyfood 

Potato, tuber, w/o peel 

Potato, tuber, w/o peel-babyfood 

Potato, tuber, w/peel 

Potato, tuber, w/peel-babyfood 

Pumpkin 

Radicchio 

Radish, Oriental, roots 

Radish, Oriental, tops 

Radish, roots 

Radish, tops 

Rape greens 

Rhubarb 

01013270 

01013310 

02003320 

19013340 

95003351 

03003380 

06003480 

06003481 

06003470 

19023540 

19023541 

09023560 

09023561 

09023570 

09023571 

01033660 

01033661 

04023670 

01033710 

08003740 

08003750 

08003780 

08003781 

08003760 

08003761 

08003770 

08003771 

95003800 

08003751 

01033870 

05023890 

01013880 

95003970 

95003980 

09013990 

01034070 

01034060 

Rutabaga 

Salsify, roots 

Salsify, tops 

Savory 95003350 Seaweed 

Seaweed-babyfood 

Shallot 

Soybean, flour 

Soybean, flour-babyfood 

Soybean, seed 

Spices, other 

Spices, other-babyfood 

Squash, summer 

Squash, summer-babyfood 

Squash, winter 

Squash, winter-babyfood 

Sweet potato 

Sweet potato-babyfood 

Swiss chard 

Tanier, corm 

Tomatillo 

Tomato 

Tomato, dried 

Tomato, dried-babyfood 

Tomato, paste 

Tomato, paste-babyfood 

Tomato, puree 

Tomato, puree-babyfood 

Tomato, Tree 

Tomato-babyfood 

Turmeric 

Turnip, greens 

Turnip, roots 

Water chestnut 

Watercress 

Watermelon 

Yam bean 

Yam, true 

INDIVIDUAL FRUIT CATEGORIES 

Apples 11000090 

11000091 

11000070 

11000100 

11000101 

Apple, dried 

Apple, dried-babyfood 

Apple, fruit with peel 

Apple, juice 

Apple, juice-babyfood 

11000080 

11000081 

11000110 

11000111 

Apple, peeled fruit 

Apple, peeled fruit-babyfood 

Apple, sauce 

Apple, sauce-babyfood 

Bananas 95000230 

95000240 

95000241 

95000231 

Banana 

Banana, dried 

Banana, dried-babyfood 

Banana-babyfood 

95002830 

95002840 

Plantain 

Plantain, dried 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9A-4 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Berries and Small 

Fruits 

13010550 Blackberry 

13010580 Boysenberry 

13011420 Dewberry 

13012080 Loganberry 

13013200 Raspberry 

13013201 Raspberry-babyfood 

13020570 Blueberry 

13020571 Blueberry-babyfood 

13021360 Currant 

13021370 Currant, dried 

13021490 Elderberry 

13021740 Gooseberry 

13021910 Huckleberry 

95001300 Cranberry 

95001301 Cranberry-babyfood 

95001310 Cranberry, dried 

95001750 Grape 

95001770 Grape, leaves 

95001780 Grape, raisin 

95001950 Kiwifruit 

95002270 Mulberry 

95003590 Strawberry 

95003591 Strawberry-babyfood 

Citrus Fruits 10001060 Citrus citron 

10001070 Citrus hybrids 

10001800 Grapefruit 

10001970 Kumquat 

10001990 Lemon 

10002010 Lemon, peel 

10002060 Lime 

10002400 Orange 

10002420 Orange, peel 

10003070 Pummelo 

10003690 Tangerine 

Peaches 12002600 Peach 

12002610 Peach, dried 

12002611 Peach, dried-babyfood 

12002601 Peach-babyfood 

Pears 11002660 Pear 

11002670 Pear, dried 

11002680 Pear, juice 

11002681 Pear, juice-babyfood 

11002661 Pear-babyfood 

Pome Fruits 11000070 Apple, fruit with peel 

11000080 Apple, peeled fruit 

11000081 Apple, peeled fruit-babyfood 

11000090 Apple, dried 

11000091 Apple, dried-babyfood 

11000110 Apple, sauce 

11000111 Apple, sauce-babyfood 

11001290 Crabapple 

11002100 Loquat 

11002660 Pear 

11002661 Pear-babyfood 

11002670 Pear, dried 

11003100 Quince 

Strawberries 95003590 Strawberry 

95003591 Strawberry-babyfood 

Stone Fruits 12000120 Apricot 

12000121 Apricot-babyfood 

12000130 Apricot, dried 

12000900 Cherry 

12000901 Cherry-babyfood 

12002300 Nectarine 

12002600 Peach 

12002601 Peach-babyfood 

12002610 Peach, dried 

12002611 Peach, dried-babyfood 

12002850 Plum 

12002851 Plum-babyfood 

12002860 Plum, prune, fresh 

12002861 Plum, prune, fresh-babyfood 

12002870 Plum, prune, dried 

12002871 Plum, prune, dried-babyfood 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9A-5
 
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Tropical Fruits 95000010 

95000220 

95000230 

95000231 

95000240 

95000241 

95000600 

95000740 

95000890 

95001110 

95001111 

95001120 

95001130 

95001410 

95001510 

95001530 

95001540 

95001830 

95001831 

95001930 

95002090 

95002110 

95002120 

Acerola 

Avocado 

Banana 

Banana-babyfood 

Banana, dried 

Banana, dried-babyfood 

Breadfruit 

Canistel 

Cherimoya 

Coconut, meat 

Coconut, meat-babyfood 

Coconut, dried 

Coconut, milk 

Date 

Feijoa 

Fig 

Fig, dried 

Guava 

Guava-babyfood 

Jackfruit 

Longan 

Lychee 

Lychee, dried 

95002140 

95002150 

95002151 

95002160 

95002450 

95002451 

95002460 

95002520 

95002521 

95002540 

95002790 

95002791 

95002800 

95002830 

95002840 

95002890 

95003330 

95003460 

95003510 

95003580 

95003610 

95003680 

Mamey apple 

Mango 

Mango-babyfood 

Mango, dried 

Papaya 

Papaya-babyfood 

Papaya, dried 

Passionfruit 

Passionfruit-babyfood 

Pawpaw 

Pineapple 

Pineapple-babyfood 

Pineapple, dried 

Plantain 

Plantain, dried 

Pomegranate 

Sapote, Mamey 

Soursop 

Spanish lime 

Starfruit 

Sugar apple 

Tamarind 

INDIVIDUAL VEGETABLE CATEGORIES 

Asparagus 95000190 Asparagus 

Beans 06030350 

06030300 

06030320 

06020310 

06030340 

06020330 

06030360 

06030380 

Bean, greatnorthern, seed 

Bean, black, seed 

Bean, broad, seed 

Bean, broad, succulent 

Bean, cowpea, seed 

Bean, cowpea, succulent 

Bean, kidney, seed 

Bean, lima, seed 

06020370 

06030390 

06030400 

06030410 

06030420 

06010430 

06010431 

Bean, lima, succulent 

Bean, mung, seed 

Bean, navy, seed 

Bean, pink, seed 

Bean, pinto, seed 

Bean, snap, succulent 

Bean, snap, succulent-babyfood 

Beets 01010500 

01010501 

02000510 

Beet, garden, roots 

Beet, garden, roots-babyfood 

Beet, garden, tops 

Broccoli 05010610 

05010611 

Broccoli 

Broccoli-babyfood 

Bulb Vegetables 03001640 

03001650 

03001651 

03001980 

03002370 

Garlic 

Garlic, dried 

Garlic, dried-babyfood 

Leek 

Onion, dry bulb 

03002371 

03002380 

03002381 

03002390 

03003380 

Onion, dry bulb-babyfood 

Onion, dry bulb, dried 

Onion, dry bulb, dried-babyfood 

Onion, green 

Shallot 

Cabbage 05010690 

05010720 

05010710 

Cabbage 

Cabbage, Chinese, mustard 

Cabbage, Chinese, napa 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9A-6 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Carrots 01010780 Carrot 

Corn 15001220 Corn, field, bran 

15001200 Corn, field, flour 

15001201 Corn, field, flour-babyfood 

15001210 Corn, field, meal 

15001211 Corn, field, meal-babyfood 

15001230 Corn, field, starch 

15001231 Corn, field, starch-babyfood 

15001260 Corn, pop 

15001270 Corn, sweet 

15001271 Corn, sweet-babyfood 

Cucumbers 09021350 Cucumber 

Cucurbit 09010750 Cantaloupe 09021350 Cucumber 

Vegetables 09010800 Casaba 

09011870 Honeydew melon 

09013990 Watermelon 

09020210 Balsam pear 

09020880 Chayote, fruit 

09021020 Chinese waxgourd 

09023080 Pumpkin 

09023090 Pumpkin, seed 

09023560 Squash, summer 

09023561 Squash, summer-babyfood 

09023570 Squash, winter 

09023571 Squash, winter-babyfood 

Fruiting Vegetables 08001480 Eggplant 

08002340 Okra 

08002700 Pepper, bell 

08002701 Pepper, bell-babyfood 

08002710 Pepper, bell, dried 

08002711 Pepper, bell, dried-babyfood 

08002720 Pepper, nonbell 

08002721 Pepper, nonbell-babyfood 

08002730 Pepper, nonbell, dried 

08003740 Tomatillo 

08003750 Tomato 

08003751 Tomato-babyfood 

08003760 Tomato, paste 

08003761 Tomato, paste-babyfood 

08003770 Tomato, puree 

08003771 Tomato, puree-babyfood 

08003780 Tomato, dried 

08003781 Tomato, dried-babyfood 

Leafy Vegetables 02000510 Beet, garden, tops 04021520 Fennel, Florence 

(Brassica and 02001010 Chicory, tops 04023220 Rhubarb 

Nonbrassica) 02001400 Dasheen, leaves 

02003150 Radish, tops 

02003170 Radish, Oriental, tops 

02003320 Salsify, tops 

04010050 Amaranth, leafy 

04010180 Arugula 

04011040 Chrysanthemum, garland 

04011330 Cress, garden 

04011340 Cress, upland 

04011380 Dandelion, leaves 

04011500 Endive 

04012040 Lettuce, head 

04012050 Lettuce, leaf 

04012480 Parsley, leaves 

04013130 Radicchio 

04013550 Spinach 

04013551 Spinach-babyfood 

04020760 Cardoon 

04020850 Celery 

04020851 Celery-babyfood 

04020870 Celtuce 

04023670 Swiss chard 

05010610 Broccoli 

05010611 Broccoli-babyfood 

05010620 Broccoli, Chinese 

05010640 Brussels sprouts 

05010690 Cabbage 

05010710 Cabbage, Chinese, napa 

05010720 Cabbage, Chinese, mustard 

05010830 Cauliflower 

05011960 Kohlrabi 

05020630 Broccoli raab 

05020700 Cabbage, Chinese, bok choy 

05021170 Collards 

05021940 Kale 

05022290 Mustard greens 

05023180 Rape greens 

05023890 Turnip, greens 

95000540 Belgium endive 

95003350 Seaweed 

95003351 Seaweed - babyfood 

95003980 Watercress 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9A-7
 
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Legume Vegetables 06003470 

06003480 

06003481 

06003490 

06003491 

06010430 

06010431 

06012570 

06020310 

06020330 

06020370 

06022550 

06022551 

06022590 

06030300 

06030320 

Soybean, seed 

Soybean, flour 

Soybean, flour-babyfood 

Soybean, soy milk 

Soybean, soy milk-babyfood or infant 

formula 

Bean, snap, succulent 

Bean, snap, succulent-babyfood 

Pea, edible podded, succulent 

Bean, broad, succulent 

Bean, cowpea, succulent 

Bean, lima, succulent 

Pea, succulent 

Pea, succulent-babyfood 

Pea, pigeon, succulent 

Bean, black, seed 

Bean, broad, seed 

06030340 

06030350 

06030360 

06030380 

06030390 

06030400 

06030410 

06030420 

06030980 

06030981 

06030990 

06031820 

06031821 

06032030 

06032560 

06032561 

06032580 

Bean, cowpea, seed 

Bean, great northern, seed 

Bean, kidney, seed 

Bean, lima, seed 

Bean, mung, seed 

Bean, navy, seed 

Bean, pink, seed 

Bean, pinto, seed 

Chickpea, seed 

Chickpea, seed-babyfood 

Chickpea, flour 

Guar, seed 

Guar, seed-babyfood 

Lentil, seed 

Pea, dry 

Pea, dry-babyfood 

Pea, pigeon, seed 

Lettuce 04012040 

04012050 

Lettuce, head 

Lettuce, leaf 

Okra 08002340 Okra 

Onions 03002370 

03002380 

03002381 

03002371 

03002390 

Onion, dry bulb 

Onion, dry bulb, dried 

Onion, dry bulb, dried-babyfood 

Onion, dry bulb-babyfood 

Onion, green 

Peas 06032560 

06032561 

06012570 

06032580 

06022590 

Pea, dry 

Pea, dry-babyfood 

Pea, edible podded, succulent 

Pea, pigeon, seed 

Pea, pigeon, succulent 

06022550 

06022551 

Pea, succulent 

Pea, succulent-babyfood 

Peppers 08002700 

08002710 

08002711 

08002701 

08002720 

Pepper, bell 

Pepper, bell, dried 

Pepper, bell, dried-babyfood 

Pepper, bell-babyfood 

Pepper, nonbell 

08002730 

08002721 

Pepper, nonbell, dried 

Pepper, nonbell-babyfood 

Pumpkin 09023080 

09023090 

Pumpkin 

Pumpkin, seed 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Page Child-Specific Exposure Factors Handbook 

9A-8 September 2008 
Table 9A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Root and Tuber 

Vegetables 

01030150 

01030151 

01030170 

01010500 

01010501 

02000510 

01010520 

01010521 

01010670 

01010780 

01010781 

01030820 

01030821 

01010840 

01011000 

01031390 

01031660 

01031670 

01031661 

01011680 

01011900 

01012500 

Arrowroot, flour 

Arrowroot, flour-babyfood 

Artichoke, Jerusalem 

Beet, garden, roots 

Beet, garden, roots-babyfood 

Beet, garden, tops 

Beet, sugar 

Beet, sugar-babyfood 

Burdock 

Carrot 

Carrot-babyfood 

Cassava 

Cassava-babyfood 

Celeriac 

Chicory, roots 

Dasheen, corm 

Ginger 

Ginger, dried 

Ginger-babyfood 

Ginseng, dried 

Horseradish 

Parsley, turnip rooted 

01012510 

01012511 

01032960 

01032970 

01032971 

01032980 

01032981 

01033000 

01033001 

01032990 

01032991 

01013160 

01013140 

01013270 

01033660 

01033661 

01033710 

01033870 

01013880 

95003970 

01034070 

01034060 

Parsnip 

Parsnip-babyfood 

Potato, chips 

Potato, dry (granules/ flakes) 

Potato, dry (granules/ flakes)-babyfood 

Potato, flour 

Potato, flour-babyfood 

Potato, tuber, w/o peel 

Potato, tuber, w/o peel-babyfood 

Potato, tuber, w/peel 

Potato, tuber, w/peel-babyfood 

Radish, Oriental, roots 

Radish, roots 

Rutabaga 

Sweet potato 

Sweet potato-babyfood 

Tanier, corm 

Turmeric 

Turnip, roots 

Water chestnut 

Yam bean 

Yam, true 

Stalk and Stem 

Vegetable and 

Edible Fungi 

95000160 

95000190 

95000220 

95002280 

95002430 

Artichoke, globe 

Asparagus 

Bamboo, shoots 

Mushroom 

Palm heart, leaves 

Tomatoes 08003750 

08003780 

08003781 

08003760 

08003761 

Tomato 

Tomato, dried 

Tomato, dried-babyfood 

Tomato, paste 

Tomato, paste-babyfood 

08003770 

08003771 

08003751 

Tomato, puree 

Tomato, puree-babyfood 

Tomato-babyfood 

White Potatoes 01032960 

01032970 

01032971 

01032980 

01032981 

Potato, chips 

Potato, dry (granules/ flakes) 

Potato, dry (granules/ flakes)-babyfood 

Potato, flour 

Potato, flour-babyfood 

01033000 

01033001 

01032990 

01032991 

Potato, tuber, w/o peel 

Potato, tuber, w/o peel-babyfood 

Potato, tuber, w/peel 

Potato, tuber, w/peel-babyfood 

Child-Specific Exposure Factors Handbook
 

Chapter 9 - Intake of Fruits and Vegetables
 

Child-Specific Exposure Factors Handbook Page
 

September 2008 9A-9
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

10 INTAKE OF FISH AND SHELLFISH fishermen are interviewed while fishing), the target 

10.1 INTRODUCTION population is anyone who fishes at the locations being 

Contaminated finfish and shellfish are potential studied; generally, in a creel study, the probability of 

sources of human exposure to toxic chemicals. Pollutants being sampled is not the same for all members of the 

are carried in the surface waters, but also may be stored target population. For instance, if the survey is conducted 

and accumulated in the sediments as a result of complex for one day at a site, then it will include all persons who 

physical and chemical processes. Consequently, finfish fish there daily, but only about 1/7 of the people who fish 

and shellfish are exposed to these pollutants and may there weekly, 1/30th of the people who fish there 

become sources of contaminated food. Exposure to some monthly, etc. In this example, the probability of being 

contaminants may be of concern for children because they sampled (or inverse weight) is seen to be proportional to 

may be less able to metabolize, detoxify, and excrete the frequency of fishing. However, if the survey involves 

these substances (Moya, 2004). interviewers revisiting the same site on multiple days, and 

Accurately estimating exposure to a toxic persons are only interviewed once for the survey, then the 

chemical among a population that consumes fish from a probability of being in the survey is not proportional to 

polluted water body requires an estimation of intake rates frequency; in fact, it increases less than proportionally 

of the caught fish by both fishermen and their families. with frequency. At the extreme of surveying the same site 

Commercially caught fish are marketed widely, making every day over the survey period with no re-interviewing, 

the prediction of an individual's consumption from a all members of the target population would have the same 

particular water body or contaminant source difficult. probability of being sampled regardless of fishing 

Since the catch of recreational and subsistence fishermen frequency, implying that the survey weights should all 

is not "diluted" by fish from other water bodies, these equal one. On the other hand, if the survey protocol calls 

individuals and their families represent the population that for individuals to be interviewed each time an interviewer 

is most vulnerable to exposure by intake of contaminated encounters them (i.e., without regard to whether they were 

fish from a specific location. This chapter focuses on previously interviewed), then the inverse weights will 

intake rates of fish. Note that in this section the term fish again be proportional to fishing frequency, no matter how 

refers to both finfish and shellfish. Intake rates for the many times interviewers revisit the same site. Note that 

general population, and recreational and Native American when individuals can be interviewed multiple times, the 

fishing populations are addressed, and data are presented results of each interview are included as separate records 

for intake rates for both marine and freshwater fish, when in the data base and the survey weights should be 

available. inversely proportional to the expected number of times 

Survey data on fish consumption have been that an individual’s interviews are included in the data 

collected using a number of different approaches which base. 

need to be considered when interpreting the results. The U.S. EPA has prepared a review of and an 

Typical surveys seek to draw inferences about a larger evaluation of five different survey methods used for 

population from a smaller sample of that population. This obtaining fish consumption data. They are: 

larger population, from which the survey sample is taken 

and to which the results of the survey are generalized, is • Recall-Telephone Survey; 

denoted the target population of the survey. In order to • Recall-Mail Survey; 

generalize from the sample to the target population, the • Recall-Personal Interview; 

probability of being sampled must be known for each • Diary; and 

member of the target population. This probability is • Creel Census. 

reflected in weights assigned to survey respondents, with 

weights being inversely proportional to sampling The reader is referred to U.S. EPA (1998) Guidance for 

probability. When all members of the target population Conducting Fish and Wildlife Consumption Surveys for 

have the same probability of being sampled, all weights more detail on these survey methods and their advantages 

can be set to one and essentially ignored. For example, in and limitations. The type of survey used, its design, and 

a mail or phone study of licensed anglers, the target any weighting factors used in estimating consumption 

population is generally all licensed anglers in a particular should be considered when interpreting survey data for 

area, and in the studies presented, the sampling exposure assessment purposes. For surveys used in this 

probability is essentially equal for all target population handbook, respondents are typically adults who have 

members. In a creel study (i.e., a study in which 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

reported on fish intake for children living in their 

households. 

The recommendations for fish and shellfish 

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. EPA for this factor. 

Following the recommendations, the studies on fish 

ingestion among the general population (Section 10.3), 

marine recreational angler households (Section 10.4), 

freshwater recreational households (Section 10.5), and 

Native American populations (Section 10.6) are 

summarized. Information is provided on the key study 

that forms 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 the reader with added perspective on the current 

state-of-knowledge pertaining to ingestion of fish and 

shellfish among children. Information on serving size 

(Section 10.7), and other factors (Section 10.8) 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 (total, marine, 

freshwater/estuarine); 

? 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. 

Fish consumption rates are recommended for 

various ages of children in 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 (2002) analysis of data from 

the U.S. Department of Agriculture (USDA) Continuing 

Survey of Food Intake by Individuals (CSFII) 1994­

1996, 1998. Per capita and consumer-only values for 

children ages 3 to < 6, 6 to <11, 11 to < 16, and 16 to < 

18 years, by habitat (i.e., marine, freshwater/estuarine, or 

total fish), are shown in Table 10-1. It should be noted, 

however, that the key general population study presented 

in this chapter pre-dated the age groups recommended by 

U.S. EPA in Guidance on Selecting Age Groups for 

Monitoring and Assessing Childhood Exposures to 

Environmental Contaminants (U.S. EPA, 2005). Thus, 

recommended values were not available for children less 

than 3 years old or 18 to < 21. The confidence ratings for 

the fish intake recommendations for the general 

population are presented in Table 10-2. Note that the fish 

intake values presented in Table 10-1 are reported as 

uncooked fish weights. The CSFII 1994-1996, 1998 

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, 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 since the 

concentration in the cooked fish is likely to be higher, if 

the mass of the contaminant remains constant after 

cooking. Therefore, it is more conservative and 

appropriate to use uncooked fish intake rates. 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. Both "asprepared" (i.e., as-consumed) and uncooked general 

population fish intake values are presented in this 

handbook so that the assessor can choose the intake data 

that best matches the concentration data that are being 

used. 

The CSFII data on which the general population 

recommendations are based, are short-term survey data 

and should not be used to estimate the distribution over the 

long term. Also, it is important to note that a limitation 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

associated with these data is that the total amount of fish 10.4 of this chapter to determine if the values presented 

reported by respondents included fish from all sources are applicable to their specific assessment. 

(e.g., fresh, frozen, canned, domestic, international For recreational freshwater fish intake, the West et 

origin). The CSFII surveys did not identify the source of al. (1989) study was conducted in Michigan to estimate 

the fish consumed. This type of information may be intake based on 7-day recall and the frequency of fish 

relevant for some assessments. It should also be noted meals over each of the four seasons. Based on a U.S. 

that because these recommendations are based on 1994­ EPA analysis of the data, mean recreational freshwater 

1996, 1998 CSFII data, they may not reflect any recent fish intake rates were 5.6, 7.9, and 7.3 grams/day for 

changes that may have occurred in consumption patterns. children ages 1 to 5 years (N = 121), 6 to 10 years (N = 

Recommended values should be selected that are 151), and 11 to 20 years (N = 349), respectively. Benson 

relevant to the assessment, choosing the appropriate age et al. (2001) reported median freshwater sports-caught 

groups and source of fish (i.e., freshwater/estuarine, fish intake rates of 1.2 and 1.7 grams/day for children, 

marine, and total fish). In some cases a different study or ages 0 to 14 years, in Minnesota (N = 582) and North 

studies may be particularly relevant to the needs of an Dakota (N = 343), respectively. Readers are referred to 

assessment, in which case results from that specific study the studies provided in Section 10.5 of this chapter to 

or studies may be used instead of the recommended determine if the values presented are applicable to their 

values provided here. For example, it may be specific assessment. 

advantageous to use available regional or site-specific Fish consumption data for Native American 

estimates if the assessment targets a particular region or children are very limited, and fish consumption rates, 

site. In addition, seasonal, gender, and fish species habits, and patterns can vary among tribes and other subvariations should be considered when appropriate, if data populations. Therefore, fish intake data for a particular 

are available. tribe may not be representative of other tribes. Available 

Recommendations are not provided for recreational data on fish consumption among this population is 

marine fish intake, recreational freshwater fish intake, or presented in Section 10.6. These data should be used, as 

intake among Native American children because the appropriate. 

available data are limited to certain geographic areas 

and/or tribes and cannot be readily generalized to the U.S. 

population as a whole. However, data from two relevant 

recreational marine studies (KCA, 1994 and Alcoa, 1998); 

two relevant recreational freshwater studies (West et al., 

1989 and Benson et al., 2001); and four Native American 

studies (CRITFC, 1994; Toy et al., 1996; Duncan, 2000; 

and Polissar et al., 2006) are provided in this chapter. 

Assessors may use these data, if appropriate to the 

scenarios being assessed. These studies were performed 

at various study locations using various age groups of 

children. 

For recreational marine fish intake, the KCA 

(1994) study was conducted in Delaware using the age 

groups 0 to 9 years and 10 to 19 years and the Alcoa 

(1998) study was conducted in Texas using the age groups 

<6 years and 6 to 19 years. Mean recreational marine fish 

intake values in the KCA (1994) study were 6 grams/day 

and 11.4 grams/day for the 0 to 9 years (N = 73) and 10 to 

19 years (N = 102), respectively. The Alcoa (1998) study 

provided mean recreational marine intake values for 

finfish at 11.4 grams/day for the children <6 years old (N 

= 320) and 15.6 grams/day for children 6 to 19 years old 

(N = 749). Mean shellfish values were 0.4 grams/day and 

0.7 grams/day for the same age groups, respectively. 

Readers are referred to the studies provided in Section 

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September 2008 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

a Table 10-1. Recommended Values for General Population Fish Intake

Per Capita Consumer Only 

Age Group Mean 95 th Percentile Mean 95 th Percentile Multiple Source Percentiles

g/day g/kg-day g/day g/kg-day g/day g/kg-day g/day g/kg-day 

Total Fish 

3 to < 6 years 7.7 0.43 51 3.0 74 4.2 184 10 6 to < 11 years 8.5 0.28 56 1.9 95 3.2 313* 8.7* 11 to < 16 years 12 0.23 87 1.5 113 2.2 308* 6.2* 16 to < 18 years 11 0.16 84 1.3 136* 2.1* 357* 6.6* U.S. EPA 

Marine Fish Analysis of

CSFII, 3 to < 6 years 5.5 0.31 39 2.3 66 3.7 165 9.3* See Tables 1994-96 and

6 to < 11 years 5.6 0.20 38 1.5 78 2.8 202* 8.0* 10-7 through 1998. 10-10 11 to < 16 years 7.6 0.15 56 1.3 102 2.0 262* 5.2* (Rates are for 

16 to < 18 years 6.1 0.10 29 0.46 126* 2.0* 353* 6.5* uncooked

weight) Freshwater/Estuarine Fish

3 to < 6 years 2.2 0.12 12 0.71 40 2.3 129 7.2* 6 to < 11 years 3.0 0.08 13 0.35 61 1.8 248* 6.2* 11 to < 16 years 4.3 0.08 26 0.48 71 1.3 199* 4.4* 16 to < 18 years 4.6 0.07 19 0.29 100* 1.4* 242* 3.3* * The sample size does not meet the minimum reporting requirements, as described in the Third Report on Nutrition Monitoring in the United

States (LSRO, 1995).

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). Thus, data were not presented for children less than 3 years old or for 18 to < 21 years. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific 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 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 the exposure factor of interest. 

The survey was conducted nationwide and was 

representative of the general U.S. population. 

The most current CSFII 1994-96; 98 data were used. 

Data were collected for two non-consecutive days. 

High 

Clarity and Completeness 

Accessibility

 Reproducibility

 Quality Assurance 

The primary data are accessible through USDA. 

The methodology was clearly presented; enough 

information was available to allow for reproduction of the 

results. 

Quality assurance of CSFII 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. Otherwise, the sources of 

uncertainty were minimal. 

Medium 

Evaluation and Review 

Peer Review

 Number and Agreement of Studies 

The primary data were reviewed by USDA; U.S. EPA 

review conducted a review of the secondary data analysis 

for fish intake. 

The number of studies is 1. 

Medium 

Overall Rating High (mean) 

Medium (upper 

percentile) 

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Child-Specific Exposure Factors Handbook 

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 2002 - Estimated Per Capita Fish 

Consumption in the United States 

U.S. EPA’s Office of Water used data from the 

1994-96 CSFII and its 1998 Children’s Supplement 

(referred to collectively as CSFII 1994-96, 1998) to 

generate fish intake estimates. Participants in the 

CSFII 1994-96, 98 provided two non-consecutive days 

of dietary data. 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 7 

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 two reporting days for all fishrelated 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 one of the 

two 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 who had two-day dietary intake data. 

A total of 7,429 of these individuals were children 

between the ages of 3 and 17 years. Data for these 

children were used in estimating fish intake in g/day. 

Slightly fewer children were used in the fish intake 

rates estimated in units of g/kg-day because body 

weights were not reported for some individuals. 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. These weights were used to project the 

estimates for the 7,429 children in the data set to 

58,923,560 children in the U.S. population. 

U.S. EPA (2002) reported means and estimates 

of the 90th, 95th, and 99th percentiles of fish intake. 

Tables 10-3 through 10-10 present these statistics for 

daily average fish consumption. These data are 

presented for selected age groups: 3 to 5, 6 to 10, 11 to 

15, and 16 to 17 years of age. Tables 10-3 and 10-4 

present per capita fish consumption, on an as-consumed 

basis, in g/day and in mg/kg-day, respectively. Tables 

10-5 and 10-6 provide consumer-only fish intake data, 

on an as-consumed basis, in units of g/day and mg/kgday, respectively. Tables 10-7 through 10-10 provide 

per capita and consumer only fish intake data (g/day 

and mg/kg-day) on an uncooked equivalent basis. 

The advantages of this study are that the data 

used were from the CSFII survey, which had a large 

sample size and was representative of the U.S. 

population. The CSFII survey was also designed to 

give unbiased estimates of food consumption (U.S. 

EPA, 2002). In addition, through use of the USDA 

recipe files, the analysis included all fish eaten (i.e., 

both fish eaten alone and in mixtures). 

10.3.2 Relevant General Population Studies 

10.3.2.1 U.S. EPA, 1996 - National Human Activity 

Pattern Survey (NHAPS) 

The U.S. EPA (1996) 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 as part 

of the National Human Activity Pattern Survey 

(NHAPS). Over 9,000 individuals from 48 contiguous 

states participated in NHAPS. Approximately 4,700 

participants also provided information on seafood 

consumption, with 2,980 responding that they ate 

seafood (including shellfish, eel, or squid) in the last 

month. Over 900 of these participants were children 

between the ages of 1 and 17 years. The survey was 

conducted between October 1992 and September 1994. 

Data were collected on the (1) number of people that 

ate seafood in the last month, (2) the number of 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

servings of seafood consumed, and (3) whether the 

seafood consumed was caught or purchased. The 

participant responses were weighted according to 

selected demographics such as age, gender, and race to 

ensure that results were representative of the U.S. 

population. In order to conform to the standardized age 

categories used in this handbook, U.S. EPA 

subsequently accessed the source data from U.S. EPA 

(1996) and recalculated the relevant statistics using the 

age categories recommended in Guidance on Selecting 

Age Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. EPA, 

2005). The results of U.S. EPA’s analysis are shown in 

Table 10-11. 

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 for each age group 

from other studies (see Section 10.7.1). Using the 

mean value for serving size and the number of servings 

per month from Table 10-11, the age-specific amount 

of seafood eaten per month can be estimated. 

The advantages of NHAPS is 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 intakes from this study are comparable to those 

observed in the U.S. EPA CSFII analysis. It should be 

noted that an all inclusive description for seafood was 

not presented in U.S. EPA (1996) or in the NHAPS 

data. It is not known if processed or canned seafood 

and seafood mixtures are included in the seafood 

category. 

10.3.2.2 Moya et al., 2008 - Estimates of Fish 

Consumption Rates for Consumers of 

Bought and Sel-caught fish in Connecticut, 

Florida, Minnesota, and North Dakota 

Moya et al. (2008) analyzed the raw data from 

three fish consumption studies to derive fish 

consumption rates for various age, gender, 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, sports 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 percent for the general population and 

10 percent for anglers), but was considered to be 

adequate by the study authors (Balcom et al., 1999). 

Data from this survey were available for 54 children, 

ages 0 to 15 years. 

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). Data from this survey were 

available for 1,160 children, ages 0 to 15 years. 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 from this survey were available for 

273 children, ages 0 to 15 years (151 in Minnesota and 

122 in North Dakota). Data on purchased and caught 

fish were collected for the general population, anglers, 

new mothers, and Native American tribes. The survey 

also collected information of the species of fish eaten. 

Additional information on this study can be found in 

Benson et al. (2001). 

Moya et al. (2008) utilized the data from these 

three studies to generate intake rates for three age 

groups of children (i.e., 1 to <6 years, 6 to <11 years, 

and 11 to <16 years). These data represented the 

general population of children 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 10-12 presents the intake rates for the 

general population of children who consumed fish and 

shellfish in g/kg-day, as-consumed. Table 10-13 

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). Table 10-14 

provides estimated fish intake rates among the general 

populations and angler populations from Connecticut, 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Minnesota, and North Dakota. While the data in Tables 

10-13 and 10-14 do not pertain specifically to children, 

they provide an indication of the proportion of fish 

consumption that is either caught or bought among the 

sample population, and similarities and/or differences 

between fish intake among the general population and 

anglers. 

10.4 MARINE RECREATIONAL STUDIES 

10.4.1 Relevant Marine Recreational Studies 

10.4.1.1 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. One was a field survey of 

fishermen as they returned from their fishing trips and 

the second part was 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, gender, 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). A total of 1,717 of 

these were children between the ages of 0 and 19 years 

of age. 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. Followup phone interviews typically occurred 

two 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. 

Table 10-15 presents the results of the study 

for children who consumed fish (i.e., consumers only). 

Children, ages 0 to 9 years old, had a mean fish 

consumption rate of 6.0 g/day (N = 73), while children, 

ages 10 to 19 years old, had a mean fish consumption 

rate of 11.4 g/day (N = 102). 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). 

One limitation of this study is that information 

on fish consumption by children is based on anglers’ 

recall of amount of fish eaten. Also, the study was 

limited to one geographic area and may not be 

representative of the U.S. population. 

10.4.1.2 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 1996/97 to evaluate the quantity and 

species of finfish and shellfish consumed by individuals 

who fish at Lavaca Bay. The target population for this 

study was residents of three Texas counties: Calhoun, 

Victoria, and Jackson (over 70 percent 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 

percent from Calhoun, 30 percent from Victoria, and 20 

percent 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 percent. Data were collected from the 

households for men, women, and children. There were 

4,489 records with valid information and of those 

records, 320 were for small children (less than 6 years 

old) and 749 records for youths (6 to 19 years old). 

The information collected as part of the survey 

included recreational fishing trip information for 

November 1996 (i.e., fishing site, site facilities, 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

distance traveled, number and species caught), selfcaught 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. Red drum was 

the most commonly consumed self-caught fish, 

followed by speckled sea trout, flounder, all other 

finfish and black drum. For shellfish, the order from 

highest to lowest amount consumed was oysters, blue 

crab, and shrimp. 

Table 10-16 presents the mean and upperpercentile consumption rates of self-caught fish, 

expressed as grams per day, for small children (<6 

years of age) and youths (ages 6 to 19 years of age). 

Small children consumed an average of 11.4 grams of 

finfish per day while youths consumed an average of 

15.6 grams daily. Small children consumed an average 

of 0.4 g/day of shellfish, while youths consumed an 

average of 0.7 g/day. Note that these data represent the 

amount of self-caught fish that is consumed from all 

locations (i.e., not just from Lavaca Bay). Table 10-17 

shows the average number of meals consumed by each 

age group of children and the average portion size in 

grams (converted from ounces) for these meals. Small 

children and youths consumed slightly less than three 

meals per month of finfish and less than one meal per 

month of shellfish. For finfish, youths consumed an 

average, per meal, portion size of 187 grams, and small 

children consumed less than 128 grams per meal. 

Youths consumed an average shellfish portion size of 

71 grams per meal, while small children consumed 57 

grams per meal. 

The study authors noted that since the survey 

relied on the anglers’ recall of meal frequency and 

portion, fish consumption may have been 

overestimated. Also, the study was conducted at one 

geographic location and may not be representative of 

the U.S. population. 

10.5	 FRESHWATER RECREATIONAL 

STUDIES 

10.5.1	 Relevant Freshwater Recreational Studies 

10.5.1.1 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 licences. 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 seven 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 to give the 

overall percentage of household fish meals that came 

from recreational sources. A sample of 2,600 

individuals were 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 

percent.. The responses represented a total of 621 

children between the ages of 1 and 20 years. 

U.S. EPA obtained the raw data from the West 

et al. (1989) survey and analyzed it to estimate mean 

fish intake rates for children. Only respondents with 

information on both short term and usual intake were 

included in this analysis. For the analysis, 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 described as less, about the same, 

and more than the 8 ounce picture. U.S. EPA examined 

the percentiles of the distributions of fish meal sizes 

reported in Pao et al. (1982), derived from the 1977­

1978 USDA National Food Consumption Survey 

(NCFS), 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 percent 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 therefore 5, 8, 

and 12 ounces for fish meals described as less, about 

the same, and more than the 8 ounce picture, 

respectively. It should be noted that the mean serving 

size from Pao et al. (1982) was about 5 ounces, well 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

below the value of 8 ounces most commonly reported 

by respondents in the West et al. (1989) survey. 

Table 10-18 displays the mean number of total 

and recreational fish meals for each household member 

between age 1 and 20 years based on the seven day 

recall data. Also shown are mean fish intake rates 

derived by applying the weights described above to 

each fish meal. Intake was calculated in units of both 

grams/day and grams/kg body weight/day. 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 

percent of the survey respondents (i.e., licensed 

anglers) and about 84 percent of the respondents who 

fished in the prior year reported some household 

recreational fish consumption. 

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 response 

rate of this survey, 47 percent, was relatively low and 

it was conducted in one geographic location. This 

study was conducted in the winter and spring months of 

1989. 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. 

10.5.1.2 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. For the entire population, approximately 

1,570 surveys were returned completed (out of 7,835 

that were mailed out). Information on fish consumption 

by children was collected if they were a part of a 

respondent household. Data were collected for a total 

of 604 children (ages 0 to 14 years) in Minnesota and a 

total of 375 children (ages 0 to 14 years) in North 

Dakota. Among these respondents, data on sportcaught fish intake were available for 582 Minnesota 

children and 343 North Dakota children. Table 10-19 

presents the recreational freshwater intake rates for 

children (ages 0 to 14 years). Rates for both purchased 

and sports-caught fish are provided. For Minnesota, the 

50th percentile sports-caught fish consumption rate was 

1.2 grams/day and the 95th percentile rate was 14.6 

grams/day. For North Dakota, the 50th percentile 

sports-caught fish consumption rate was 1.7 grams/day, 

and the 95th percentile rate was 23.3 grams/day. Intake 

rates of purchased fish were higher for both Minnesota 

(3.6 grams/day 50th percentile; 30.9 grams/day 95th 

50th percentile) and North Dakota (4.7 grams/day 

percentile; 42.8 grasm/day 95th percentile). 

An advantage of this study is its large overall 

sample size. A limitation of the study is the broad age 

range of children used (i.e., 0 to 14 years). Also, the 

study was limited to two states. Therefore, the results 

may not be representative of the U.S. population as a 

whole.. 

10.6 NATIVE AMERICAN STUDIES 

10.6.1 Relevant Native American Studies 

10.6.1.1 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. The 

overall response rate was 69 percent yielding a sample 

size of 513 tribal members, 18 years old and above. 

Interviews were performed in person at a central 

location on the member’s reservation. 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 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

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., selfcaught, 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). In order to ensure an adequate 

sample size from each tribe, the study was designed to 

give nearly equal sample sizes for 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 

percent, 744 individuals were selected at random from 

lists of eligible patients; the numbers from each tribe 

were approximately equal. 

Intake rates were calculated for children for 

which both the number of fish meals per week and 

serving size information were available. A total of 49 

percent 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 percent reported that they obtained fish from 

either self-harvesting, family or friends, at tribal 

ceremonies or from tribal distributions. Of all fish 

consumed, 41 percent came from self or family 

harvesting, 11 percent from the harvest of friends, 35 

percent from tribal ceremonies or distribution, 9 percent 

from stores and 4 percent 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 five 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 percent for salmon, followed by 46.5 percent (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. Table 10-20 presents the fish intake 

distribution for children under 5 years of age (N = 194). 

The mean intake rate was 19.6 g/day (N = 194) and the 

95th percentile was approximately 70 g/day. These 

mean intake rates include both consumers and nonconsumers. 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 10-21 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 since 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 since 

non-consumers may have thought their contribution to 

the survey would be meaningless; if such were the case, 

this study would overestimate the mean 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 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

into a single pooled data set is somewhat problematic. 

The data presented in Table 10-20 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. However, it is one of a relative few 

studies aimed at the fish consumption patterns of 

Native Americans. It should be noted that the selection 

process for children may be biased because the 204 

children included in the study were not selected 

independently, but were identified through a parent’s 

patient registration file. This indicates that children 

from larger households would be less likely to be 

chosen to participate in the study than would be the 

case if the children themselves, rather than the parents, 

were randomly selected. 

10.6.1.2 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 fourteen tribes in the region. 

Commercial fishing is a major source of income for 

members of both tribes; some members the Squaxin 

Island tribe also participate in commercial shellfishing. 

Both tribes participate in subsistence fishing and 

shellfishing. 

Fish consumption patterns for the two tribes 

were estimated using a survey in which sample sizes 

were calculated separately for each tribe. This allowed 

separate analyses to be conducted for each tribe. The 

appropriate sample size was calculated based on the 

enrolled population of each tribe and a desired 

confidence interval of ±20 percent from the mean, with 

an additional 25 percent 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 five 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 ages 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. Interviews were 

conducted between February and May 1994. The 

response rate for adults was 77 percent for the Squaxin 

Island tribe and 76 percent for the Tulalip tribes. 

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 (Table 10­

22). Squaxin Island children tended to consume more 

fish than Tulalip children (mean 0.83 g/kg-day vs. 0.24 

g/kg-day). The data were insufficient to allow reanalysis to fit the data to the standard U.S. EPA age 

categories used elsewhere in this handbook. 

One limitation associated with this study is 

that although data from the Tulalip and Squaxin Island 

tribes may be representative of consumption rates of 

children in these specific tribes, fish consumption rates, 

habits, and patterns can vary among tribes and other 

sub-populations; 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. 

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. 

There might also be a possible bias due to the time the 

survey was conducted; many species in the survey are 

seasonal. For example, because of the timing of the 

survey, respondents may have overestimated annual 

consumption. 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

10.6.1.3 Duncan, 2000 - Fish Consumption Survey of 

the Squamish Indian Tribe of the Port 

Madison Indian Reservation, Puget Sound 

Region 

The Squamish Tribal Council conducted a 

study of the Squamish 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 Squamish Tribe. The 

second objective was to identify cultural practices and 

attributes that affect consumption rates, patterns and 

habits of members of the Squamish Tribe. 

A systematic random sample of adults, defined 

as individuals age 16 years and older, were selected 

from a sorted Tribal enrollment roster. The study had 

a participation rate of 64.8 percent, 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 six 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 six 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. 

Interviewers collected data for 31 children 

under six years of age. Table 10-23 provides the 

consumption rates for children in units of g/kg-day for 

all respondents. Table 10-24 provides consumption 

rates for consumers only. Because all of the children 

involved in the study consumed some form of fish, the 

consumption distribution of all fish is the same in both 

tables. The mean, median, and 95th percentile 

consumption rates of all fish were 1.5 g/kg-day, 0.72 

g/kg-day, and 7.3 g/kg-day, respectively. These values 

are significantly greater than those presented for the 

Tulalip and Squaxin Island tribes (Toy et al., 1996; see 

Section 10.6.1.2). 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 consumption rates to a population 

of interest using data from tribal studies. 

A limitation of this study is that the sample 

size for children was fairly small (31 children). An 

important attribute of this survey is that it provided 

consumption rates by individual type of fish and 

shellfish. 

10.6.1.4 Polissar et al., 2006 - A Fish Consumption 

Survey of the Tulalip and Squaxin Island 

Tribes of the Puget Soun d 

Region–Consumption Rates fo r 

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, gender, 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 

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 genders. 

The consumption rates for groups of fish differed 

between the tribes. The distribution of consumption 

rates was skewed toward large values. The estimated 

mean consumption rate of all fish was 0.45 g/kg-day for 

the Tulalip children and 2.9 g/kg-day for the Squaxin 

Island children (Table 10-25). Table 10-26 presents 

consumption rates for children by species and gender. 

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, 

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Chapter 10 - Intake of Fish and Shellfish 

as described in Section 10.6.1.2, 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. 

10.7	 SERVING SIZE STUDY 

10.7.1	 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 1994-96 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. A total of 4,939 of these respondents were 

children, ages 2 to 19 years of age. Only dietary intake 

data from users of the specified food were used in the 

analysis (i.e., consumers only data). 

Table 10-27 and Table 10-28 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 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 by respondents were not provided by the 

respondents, standard recipes were used. As a result, 

10.8	 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, aand 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. The 

reader is referred to U.S. EPA (2003) for a detailed 

review of these studies. Additionally, 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. 

10.8.1	 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., mg 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 presented in 

Table 10-29 and the following equation: 

⎡100−W

⎢

⎣

⎤

⎥

⎦

IRdw IR ww = (Eqn. 10-1) the estimates of the quantity of some food types are 100
 based on assumptions about the types and quantities of 

ingredients consumed as part of mixed foods. 

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Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

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: 

⎡100 −W ⎤ Cww = Cdw ⎣

⎢ 100 ⎦⎥ (Eqn. 10-2) 

where: 

Cww = wet weight intake 

rate; 

Cdw = dry weight intake 

rate; and 

W = percent water 

content. 

The moisture content data presented in Table 10-29 are 

for selected fish taken from USDA, 2007. 

10.8.2	 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. 

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 10-29 and the following equation: 

⎡ L ⎤ IRlw = IR ww ⎢ (Eqn. 10-3) ⎣100 ⎦

⎥

where: 

IRlw = lipid weight intake 

rate; 

IRww = wet weight intake 

rate; and 

L =	 	 percent lipid (fat) 

content. 

Alternately, wet weight residue levels in fish may be 

estimated by multiplying the levels based on fat by the 

fraction of fat per product as follows: 

Cww = Clw 

⎡

⎣

⎢ ⎤

⎦

⎥

L

100 (Eqn. 10-4) 

where: 

Cww = wet weight intake 

rate; 

Clw = lipid weight intake 

rate; 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 10-29 are for selected fish taken from USDA, 

2007. 

10.9	 REFERENCES FOR CHAPTER 10 

Alcoa (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.; Hirsch D.W. (1999) 

Quantification of seafood consumption rates 

for Connecticut. Report prepared for the 

Connecticut Department of Environmental 

Protection, Office of Long Island Sound 

Programs, Hartford, CT. Contract No. CWF332-R. 

Benson, S.; Crocker, C.; Erjavec, J.; Jensen, R.R.; 

Nyberg, C.M.; Wixo, C.Y.; Zola, J.M. (2001) 

Fish consumption survey: Minnesota and 

North Dakota. Report prepared for the U.S. 

Department of Energy by the Energy and 

Environmental Research Center, University of 

North Dakota, Grand Forks, ND. DOE 

Cooperative Agreement No, DE-FC26-

98FT40321. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-15
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

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. Technical Report 94-3. Portland, OR: 

CRITFC. 

Degner, R.L.; Adams, C.M.; Moss, S.D.; Mack, S.K. 

(1994) Per capita fish and shellfish 

consumption in Florida. Gainesville, FL: 

University of Florida. 

Duncan, M. (2000) Fish consumption survey of the 

Squamish Indian Tribe of the Port Madison 

Indian Reservation, Puget Sound Region. 

Squamish, WA: The Squamish Tribe, Port 

Madison Indian Reservation. 

KCA Research Division (1994) Fish consumption of 

Delaware recreational fishermen and their 

households. Prepared for the State of 

Delaware, Department of Natural Resources 

and Environmental Control in support of the 

Delaware Estuary Program, Dover, DE. 

LSRO	 	 (1995) Life Sciences Research Office, 

Federation of American Societies for 

Experimental Biology Prepared for the 

Interagency Board for Nutrition Monitoring 

and Related Research. Third Report on 

Nutrition Monitoring in the United States: 

Volume 1. U.S. Government Printing Office, 

Washington, DC. 

Moya, J. (2004) Overview of fish consumption rates in 

the United States. Hum Eco Risk Assess 

10:1195-1211. 

Moya, J.; Itkin, C.; Selevan, S.G.; Rogers, J.W.; 

Clickner, R.P. (2008) Estimates of fish 

consumption rates for consumers of bought 

and self-caught fish in Connecticut, Florida, 

Minnesota, and North Dakota. Sci Tot 

Environ (in press). 

Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J. 

(1982) Foods commonly eaten by individuals: 

amount per day and per eating occasion. U.S. 

Department of Agriculture. Home Economic 

Report No. 44. 

Polissar, N.L.; Neradilek, B.; Liao, S.; Toy, K.A.; 

Mittelstaedt, G.D. (2006) A fish consumption 

survey of the Tulalip and Squaxin Island tribes 

of the Puget Sound region – Consumption 

rates for fish-consumers only. Report 

prepared by Mountain-Whisper-Light 

Statistical Consulting, Seattle, WA. 

Smiciklas-Wright, H.; Mitchell, D.C.; Mickle, S.J.; 

Cook, A.J.; Goldman, J.D. (2002) Foods 

commonly eaten in the United States 1994­

1996: Quantities consumed per eating 

occasion and in a day. U.S. Department of 

Agriculture. Agricultural Research Center 

NFS Report No. 96-5, 264 pp. 

Toy, K.A.; Polissar, N.L.; Liao, S.; Mittelstaedt, G.D. 

(1996) A fish consumption survey of the 

Tulalip and Squaxin Island Tribes of the Puget 

Sound Region. Marysville, WA: Tulalip 

Tribes, Department of Environment. 

USDA, Agricultural Research Service. (2007) USDA 

National Nutrient Database for Standard 

Reference, Release 20. Nutrient Data 

Laboratory Home Page: 

http://www.ars.usda.gov/ba/bhnrc/ndl. 

U.S. EPA (1996) Descriptive statistics tables from a 

detailed analysis of the National Human 

Activity Pattern Survey (NHAPS) data. 

Washington, DC: Office of Research and 

Development. EPA/600/R-96/148. 

U.S. EPA (1998) Guidance for conducting fish and 

wildlife consumption surveys. Washington, 

DC: Office of Water. EPA-823-B-98-007. 

U.S.	 EPA (2002) Estimated Per Capita Fish 

Consumption in the United States. 

Washington, DC: Office of Water. 

EPA/821/C-02/003. 

U.S.	 EPA (2003) Exposure and human health 

reassessment of 2,3,7,8-tetrachlorodibenzo-pdioxin (TCDD) and related compounds, Part 

1: Estimating exposure to dioxin-like 

compounds, Volume 2: Properties, 

environmental levels, and background 

exposures. (National Academy of Sciences 

Review Draft). Washington, DC: Office of 

Research and Development, National Center 

for Environmental Assessment . 

www.epa.gov/NCEA/dioxin. 

U.S. EPA (2005) Guidance on selecting age groups for 

monitoring and assessing childhood exposures 

to environmental contaminants. Washington, 

DC: U.S. Environmental Protection Agency. 

EPA/630/P-03/003F. 

West, P.C.; Fly, M.J.; Marans, R.; Larkin, F. (1989) 

Michigan sport anglers fish consumption 

survey. A report to the Michigan Toxic 

Substance Control Commission. Michigan 

Department of Management and Budget 

Contract No. 87-20141. 

Page Child-Specific Exposure Factors Handbook 

10-16 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-3. Per Capita Distribution of Fish (Finfish and Shellfish) Intake

 General Population Children Ages 3 to 17 Years - g/day, As-Consumed 

Age (years) Sample Size Mean (90% CI) 90th % (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,391 

1,670 

1,005 

363 

1.5 (1.2-1.8) 

2.1 (1.4-2.9) 

3.0 (2.2-3.8) 

3.4 (1.6-5.3) 

0.1 (0.0-1.0) 

0.0 (0.0-0.6) 

1.4 (0.5-5.5) 

0.0 (0.0-1.5) 

5.1 (4.1-6.2) 

5.9 (3.2-13) 

18 (15-21) 

13* (5.2-29)

 39 (33-44) 

61* (51-86) 

70* (56-75) 

81* (42-117) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,391 

1,670 

1,005 

363

 3.7 (3.2-4.3) 

4.2 (3.5-4.9) 

5.5 (4.2-6.7) 

4.7 (2.9-6.4) 

11 (10-13) 

13 (9.7-17) 

14 (9.8-21) 

0.0 (0.0-6.9) 

28 (24-29) 

29 (28-34) 

39 (31-50) 

24* (7.8-71)

 60 (52-71) 

79* (49-84) 

102* (84-114) 

108* (68-119) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,391 

1,670 

1,005 

363 

5.2 (4.6-5.8) 

6.3 (5.3-7.3) 

8.5 (6.9-10) 

8.1 (5.4-11) 

19 (15-21) 

24 (21-27) 

28 (25-31) 

19 (7.0-41) 

35 (31-40) 

40 (34-51) 

60 (53-74) 

74* (29-90) 

72 (67-81) 

108* (92-131) 

122* (107-132) 

142* (108-200) 

a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Table 10-4. Per Capita Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed 

Age (years) Sample Size Mean (90% CI) 90th % (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,112 

1,553 

975 

360 

83 (67-99) 

59 (39-79) 

53 (42-64) 

49 (23-76) 

0 (0-55) 

0 (0-5) 

27 (0-78) 

0 (0-33) 

284 (240-353) 

178 (88-402) 

312 (253-390) 

213* (106-390)

 2,317 (1,736-2,463) 

1,662* (1,433-2,335) 

1,237* (950-1,521) 

1,186* (600-2,096) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,112 

1,553 

975 

360 

209 (182-237) 

150 (123-177) 

109 (84-133) 

75 (46-103) 

614 (525-696) 

416 (326-546) 

338 (179-413) 

0 (0-124) 

1,537 (1,340-1,670) 

1,055 (969-1,275) 

821 (629-1,034) 

381* (132-951) 

3,447 (3,274-3,716) 

2,800* (2,021-3,298) 

1,902* (1,537-2,366) 

1,785* (1,226-2,342) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,112 

1,553 

975 

360 

292 (259-326) 

209 (176-242) 

162 (133-191) 

124 (83-165) 

1,057 (931-1,232) 

780 (644-842) 

570 (476-664) 

261 (110-600) 

1,988 (1,813-2,147) 

1,357 (1,173-1,452) 

1,051 (991-1,313) 

1,029* (390-1,239) 

4,089 (3,733-4,508) 

3,350* (2,725-4,408) 

2,305* (1,908-2,767) 

2,359* (2,096-2,676) 

a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-17
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-5. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - g/day, As-Consumed 

Age (years) Sample Size Mean (90% CI) 90th % (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

442 

147 

107 

28 

27 (23-31) 

43 (32-55) 

49 (39-59) 

76* (59-93) 

73 (65-79) 

122* (83-187) 

127* (104-148) 

159* (151-171) 

96 (87-110) 

187* (115-260) 

150* (135-193) 

168* (159-484)

 159* (136-260) 

260* (172-261) 

307* (193-384) 

372* (171-484) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

682 

217 

122 

37

 45 (41-48) 

59 (53-66) 

72 (60-85) 

97* (65-129) 

91 (84-105) 

129 (112-158) 

165* (158-203) 

219* (180-238) 

119 (102-143) 

159* (135-219) 

204* (169-227) 

238* (180-293) 

228* (169-293) 

243* (219-292) 

246* (214-269) 

365* (230-428) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

834 

270 

172 

52 

50 (46-54) 

71 (64-77) 

80 (70-89) 

104* (75-133) 

103 (94.5-125) 

155 (130-183) 

167* (154-193) 

201* (167-243) 

134 (121-152) 

218* (198-261) 

209* (206-257) 

242* (216-484) 

260* (195-293) 

281* (260-292) 

285* (264-327) 

451* (293-484) 

a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Table 10-6. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - mg/kg-day, As-Consumed 

Age (years) Sample Size Mean (90% CI) 90th % (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

416 

132 

101 

28 

1,532 (1,320-1,743) 

1,296 (1,004-1,588) 

869 (725-1,013) 

1,063* (781-1,346) 

4,307 (3,472-4,624) 

3,453* (2,626-4,671) 

2,030* (1,628-2,104) 

2,293* (2,096-2,577) 

5,257 (4,926-5,746) 

4,675* (3,459-8,816) 

3,162* (2,104-3,601) 

2,505* (2,096-6,466)

 10,644* (9,083-12,735) 

8,314* (4,684-9,172) 

4,665* (3,597-7,361) 

5,067* (2,295-6,466) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

640 

203 

120 

37 

2,492 (2,275-2,709) 

2,120 (1,880-2,361) 

1,427 (1,203-1,651) 

1,534* (1,063-2,004) 

5,303 (4,873-5,930) 

4,950 (4,043-5,384) 

2,971* (2,858-3,741) 

3,602* (2,974-4,685) 

6,762 (6,097-7,168) 

5,817* (5,333-6,596) 

4,278* (3,026-4,766) 

4,475* (3,068-4,685) 

11,457* (7,432-14,391) 

8,092* (6,146-9,184) 

5,214* (4,647-5,646) 

4,982* (3,467-5,238) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

779 

250 

164 

52 

2,828 (2,608-3,049) 

2,375 (2,199-2,551) 

1,533 (1,384-1,682) 

1,578* (1,187-1,969) 

5,734 (5,268-6,706) 

5,135 (4,684-5,816) 

3,207* (2,945-3,485) 

3,468* (2,676-4,752) 

7,422 (6,907-8,393) 

6,561* (5,404-8,816) 

3,925* (3,485-4,764) 

4,504* (3,709-6,466) 

13,829* (11,349-14,391) 

9,179* (8,130-10,485) 

5,624* (4,764-6,929) 

5,738* (4,752-6,466) a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Page Child-Specific Exposure Factors Handbook 

10-18 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-7. Per Capita Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight 

Age (years) Sample Size Mean (90% CI) 90th (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,391 

1,670 

1,005 

363 

2.2 (1.8-2.6) 

3.0 (1.9-4.1) 

4.3 (3.2-5.4) 

4.6 (2.2-6.9) 

0.1 (0.0-1.5) 

0.0 (0.0-0.5) 

2.3 (0.1-7.7) 

0.0 (0.0-1.9) 

12 (10-14) 

13 (4.8-20) 

26 (21-29) 

19* (13-37)

 52 (46-62) 

78* (64-111) 

95* (83-110) 

109* (58-155) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,391 

1,670 

1,005 

363

 5.5 (4.8-6.2) 

5.6 (4.6-6.5) 

7.6 (5.9-9.4) 

6.1 (3.7-8.4) 

20 (17-23) 

19 (14-24) 

25 (16-35) 

0.0 (0.0-9.3) 

39 (38-41) 

38 (38-42) 

56 (45-67) 

29* (12-91)

 82 (73-95) 

100* (63-111) 

132* (110-149) 

136* (92.0-177) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,391 

1,670 

1,005 

363 

7.7 (6.9-8.6) 

8.5 (7.1-10) 

12 (9.7-14) 

11 (7.0-14) 

33 (28-34) 

33 (27-38) 

43 (37-51) 

29 (9.4-49) 

51 (46-57) 

56 (50-70) 

87 (70-103) 

84* (42-114) 

101 (89.1-111) 

144* (117-183) 

171* (148-176.8) 

193* (121-266) 

a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight 

Age (years) Sample Size Mean (90% CI) 90th % (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,112 

1,553 

975 

360 

124 (103-146) 

84 (55-112) 

77 (60-94) 

65 (30-100) 

0 (0-83) 

0 (0-1) 

20 (0-116) 

0 (0-23) 

712 (599-784) 

354 (116-685) 

477 (411-618) 

285* (167-491)

 3,091 (2,495-3,475) 

2,322* (1,856-2,994) 

1,610* (1,358-2,203) 

1,542* (760-2,767) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,112 

1,553 

975 

360 

309 (270-348) 

198 (161-235) 

153 (117-189) 

98 (58-137) 

1,108 (984-1,332) 

600 (474-733) 

481 (361-609) 

0 (0-177) 

2,314 (2,096-2,481) 

1,481 (1,310-1,549) 

1,251 (808-1,390) 

460* (197-1,079) 

4,608 (4,301-5,354) 

3,684* (2,458-4,353) 

2,381* (2,162-3,207) 

2,148* (1,648-3,901) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

4,112 

1,553 

975 

360 

433 (385-482) 

282 (235-328) 

231 (186-275) 

163 (108-219) 

1,841 (1,555-1,957) 

1,045 (745-1,219) 

824 (657-952) 

406 (145-756) 

2,964 (2,790-3,194) 

1,854 (1,638-2,175) 

1,531 (1,362-1,850) 

1,272* (558-1,500) 

5,604 (5,231-6,135) 

4,371* (3,433-5,814) 

3,651* (2,745-3,795) 

3,544* (2,767-3,946) 

a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-19
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-9. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - g/day, Uncooked Fish Weight 

Age (years) Sample Size Mean (90% CI) 90th % (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

442 

147 

107 

28 

40 (35-46) 

61 (44-79) 

71 (58-83) 

100* (80-121) 

95 (86-102) 

157* (117-250) 

173* (166-196) 

203* (197-248) 

129 (120-142) 

248* (150-381) 

199* (173-296) 

242* (206-643)

 205* (200-381) 

386* (221-401) 

392* (296-514) 

501* (241-643) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

682 

217 

122 

37

 66 (60-71) 

78 (67-89) 

102 (86-118) 

126* (80-171) 

125 (114-150) 

150 (129-201) 

220* (205-265) 

281* (241-354) 

165 (139-190) 

202* (165-317) 

262. (227-307) 

353* (241-390) 

316* (227-390) 

350* (223-392) 

320* (277-379) 

530* (291-650) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

834 

270 

172 

52 

74 (69-79) 

95 (85-106) 

113.(99-127) 

136* (97-174) 

149 (136-165) 

200 (177-235) 

227* (205-296) 

242* (206-358) 

184 (172-223) 

313* (254-381) 

308* (271-348) 

357* (266-643) 

363* (310-391) 

387* (381-401) 

380* (353-409) 

645* (390-650) 

a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Table 10-10. Consumer Only Distribution of Fish (Finfish and Shellfish) Intake 

General Population Children Ages 3 to 17 Years - mg/kg-day, Uncooked Fish Weight 

Age (years) Sample 

Size Mean (90% CI) 90th % (90% BI)a 95th % (90% BI)a 99th % (90% BI)a 

Freshwater/Estuarine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

416 

132 

101 

28 

2,292 (2,012-2,572) 

1,830 (1,416-2,245) 

1,273 (1,082-1,464) 

1,401* (1,058-1,744) 

5,852 (4,703-6,068) 

4,688* (3,673-5,987) 

2,777* (2,091-3,026) 

2,971* (2,743-3,692) 

7,160 (6,950-7,442) 

6,207* (4,767-12,926) 

4,419* (3,026-5,522) 

3,279* (2,767-8,577)

 15,600* (11,877-18,670) 

12,365* (6,763-12,926) 

5,717* (5,457-9,852) 

6,819* (3,221-8,577) 

Marine 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

640 

203 

120 

37 

3,689 (3,395-3,982) 

2,787 (2,417-3,157) 

2,020 (1,741-2,327) 

2,007* (1,302-2,712) 

7,253 (6,777-8,504) 

5,910 (4,813-7,365) 

4,224* (3,744-4,781) 

4,468* (3,880-7,802) 

9,270 (8,415-9,991) 

8,001* (6,375-8,707) 

5,195* (3,859-6,448) 

6,537* (3,991-7,802) 

16,100* (11,980-17,989) 

10,754* (8,707-12,055) 

6,839* (6,076-8,970) 

7,886* (4,661-7,958) 

All Fish 

Ages 3 to 5 

Ages 6 to 10 

Ages 11 to 15 

Ages 16 to 17 

779 

250 

164 

52 

4,198 (3,894-4,502) 

3,188 (2,923-3,452) 

2,199 (1,950-2,449) 

2,066* (1,529-2,603) 

8,061 (7,366-9,223) 

6,544 (6,013-8,707) 

4,387* (3,785-5,522) 

3,902* (3,536-7,892) 

10,444 (9,475-12,261) 

8,654* (7,086-11,756) 

6,234* (4,420-7,589) 

6,594* (4,661-8,577) 

17,874* (15,290-18,670) 

12,785* (10,930-13,979) 

8,345* (6,076-8,970) 

8,210* (7,892-8,577) 

a 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” (LSRO, 1995). 

CI = Confidence interval. 

BI = Bootstrap interval. 

Source: U.S. EPA, 2002. 

Page Child-Specific Exposure Factors Handbook 

10-20 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-11. Number of General Population Respondents Reporting Consumption of a 

Specified Number of Servings of Seafood in 1 Month, and Source of Seafood Eaten 

Number of Servings in a Month Source of Seafood 

Age Group N 

Mostly Mostly (years) 0 1-2 3-5 6-10 11-19 20+ DK Purchased Caught DK 

0 to <1 34 27 5 2 0 0 0 0 7 0 0 

1 to <2 49 30 12 4 2 0 0 1 15 3 1 

2 to <3 59 34 12 7 4 1 0 1 24 1 0 

3 to <6 169 80 42 26 13 1 1 6 78 8 3 

6 to <11 224 117 45 36 12 4 3 7 98 4 5 

11 to <16 236 128 50 42 6 1 1 8 98 3 7 

16 to <21 220 110 41 37 18 4 2 8 96 5 9 

DK = Don’t know. 

N = Sample size. 

Source: U.S. EPA re-analysis of data in U.S. EPA, 1996. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-21
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-12. Fish Consumption Among General Population Children in Four States,

Consumers Only, g/kg-day As-Consumed

Percentiles

Age Group N Mean CI 10 th 25 th 50 th 75 th 90 th 95 th Maximum (years) 

Connecticut 

1 to <6 14 0.61 0.42-0.81 0.16 0.26 0.55 0.83 1.4 1.6 1.6 6 to <11 22 0.59 0.040-0.77 0.14 0.23 0.47 0.96 1.2 1.3 1.5 11 to <16 18 0.32 0.17-0.46 0.07 0.14 0.19 0.38 0.52 0.84 1.3 

Florida 

1 to <6 420 2.3 2.05-2.63 0.5 1.0 1.7 2.8 4.7 6.8 14.6 6 to <11 375 1.1 0.98-1.22 0.28 0.52 0.81 1.4 2.2 3.0 9.4 11 to <16 365 0.85 0.73-0.98 0.20 0.36 0.63 0.99 1.6 2.2 11.0 

Minnesota 

1 to <6 46 0.58 0.32-0.85 0.07 0.15 0.46 0.73 1.1 1.8 8.0 6 to <11 42 0.38 0.21-0.54 0.05 0.07 0.25 0.47 1.0 1.4 5.3 11 to <16 63 0.24 0.16-0.31 0.03 0.06 0.21 0.32 0.55 0.59 1.4 

North Dakota 

1 to <6 28 0.70 0.24-1.17 0.05 0.12 0.23 0.68 1.6 3.8 6.8 6 to <11 41 0.56 0.31-0.81 0.11 0.21 0.30 0.66 1.2 1.5 4.3 11 to <16 53 0.41 0.23-0.59 0.06 0.12 0.22 0.54 1.0 1.3 2.3 N = Sample size.CI = Confidence interval. Source: Moya et al, 2008. 

Page Child-Specific Exposure Factors Handbook 

10-22 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish Table 10-13. Fish Consumption Among General Population in Four States According to Caught or Bought Status, g/kg-day As-Consumed Percentiles Category N Mean CI Maximum 10 th 25 th 50 th 75 th 90 th 95 th Connecticut Eats Caught Only 1 0.01 - - - - - - - 0.01 Eats Caught and Bought 70 0.49 0.36-0.61 0.10 0.17 0.34 0.75 1.1 1.3 2.2 Eats Bought Only 291 0.48 0.40-0.57 0.06 0.16 0.32 0.61 1.1 1.4 7.0 Florida Eats Caught Only 511 0.76 0.66-0.86 0.15 0.30 0.50 0.90 1.7 2.3 7.4 

Eats Caught and Bought 701 1.8 1.6-2.1 0.50 0.76 1.2 2.0 3.4 5.1 34 Eats Bought Only 6545 0.85 0.81-0.89 0.18 0.30 0.54 0.98 1.8 2.5 24 

Minnesota 

Eats Caught Only 38 0.16 0.05-0.26 0.02 0.03 0.08 0.25 0.37 0.51 0.57 Eats Caught and Bought 555 0.40 0.27-0.52 0.08 0.11 0.23 0.49 0.70 1.3 9.2 Eats Bought Only 200 0.23 0.18-0.28 0.02 0.05 0.14 0.26 0.56 0.91 8.0 

North Dakota 

Eats Caught Only 30 0.21 0.09-0.32 0.05 0.09 0.14 0.22 0.33 0.51 1.8 Eats Caught and Bought 359 0.39 0.29-0.49 0.07 0.13 0.23 0.43 0.82 1.3 4.3 Eats Bought Only 157 0.25 0.13-0.36 0.03 0.05 0.10 0.24 0.53 0.97 6.8 N = Sample size.CI = Confidence interval. Source: Moya et al., 2008. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-23
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-14. Fish Consumption Among General Population and Anglers in Three States, 

g/kg-day As-Consumed 

Percentiles

Category N Mean 

10th 25th 50th 75th 90th 95th 99th 

Connecticut 

Anglers 244 0.66 0.10 0.20 0.40 0.80 1.6 2.1 3.5 

General Population 362 0.48 0.07 0.16 0.32 0.63 1.1 1.4 2.4 

Minnesota 

Anglers 1,109 0.32 0.05 0.10 0.18 0.34 0.67 0.99 2.2 

General Population 793 0.33 0.04 0.10 0.20 0.34 0.65 1.1 1.8 

North Dakota 

Anglers 808 0.34 0.05 0.10 0.20 0.39 0.81 1.2 2.0 

General Population 546 0.34 0.05 0.09 0.19 0.35 0.74 1.2 2.2 

N = Sample size. 

Source: Moya et al., 2008. 

Table 10-15. Recreational Fish Consumption in Delaware 

Consumers Only 

Age Group N Mean consumption 

(g/day)a Standard Error (%) 

0 to 9 years 

10 to 19 years 

73 

102 

6.0 

11.4 

13.4 

16.8 a Converted from ounces/day; 1 ounce = 28.35 grams. 

Source: KCA Research Division, 1994. 

Page Child-Specific Exposure Factors Handbook 

10-24 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-16. Consumption of Self-Caught Fish by Recreational Anglers 

Lavaca Bay, Texas, g/day 

Age Group N Mean 95% Upper Confidence 

Limit on Mean 

90th or 95th Percentile of 

Distributiona 

Finfish 

Small children (<6 years) 320 11.4 14.2 30.3 

Youths (6 to 19 years) 749 15.6 17.8 45.4 

Shellfish 

Small children (<6 years) 320 0.4 0.6 2.0 

Youths (6 to 19 years) 749 0.7 1.0 4.5 

a The 90th percentile values are presented for finfish. For shellfish, the 95th percentile value is provided because 

less than 90 percent of the individuals consumed shellfish, resulting in a 90th percentile of zero. 

Source: Alcoa, 1998. 

Table 10-17. Number of Meals and Portion Sizes of Self-Caught Fish Consumed by Recreational Anglers
 


Lavaca Bay, Texas
 


Portion Size Number of Meals (grams)a 

Age Group 95% Upper 95% Upper

Mean Confidence Mean Confidence Limit on 

Limit on Mean Mean 

Finfish 

Small children (<6 years) 2.6 3.1 128 133 

Youths (6 to 19 years) 2.4 2.7 187 196 

Shellfish 

Small children (<6 years) 0.3 0.5 57 68 

Youths (6 to 19 years) 0.3 0.4 71 82 a Converted from ounces; 1 ounce = 28.35 grams. 

Source: Alcoa, 1998. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-25
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-18. Mean Fish Intake Among Individuals Who Eat Fish and 
 

Reside in Households With Recreational Fish Consumption - Michigan
 


Intake 

Meals/Week 

Age Group N g/day g/kg-day 

All Fish Recreational Fish Total Fish Recreational Fish Total Fish Recreational Fish 

1 to 5 years 121 0.46 0.22 11.4 5.6 0.74 0.37 

6 to 10 years 151 0.49 0.28 13.6 7.9 0.48 0.28 

11 to 20 years 349 0.41 0.23 12.3 7.3 0.22 0.12 

N = Sample size. 

Source: U.S. EPA analysis, using data from West et al., 1989. 

Table 10-19. Consumption of Sports-caught and Purchased Fish by 
 

Minnesota and North Dakota Children, Ages 0 to 14 Years (g/day)
 

Percentile 

N 

50th 75th 90th 95th 

Minnesota 

Sports-caught 1.2 3.3 8.3 14.6 582 Purchased 3.6 8.7 19.2 30.9 

North Dakota 

Sports-caught 1.7 5.1 13.1 23.3 343 Purchased 4.7 11.6 26.3 42.8 

Source: Benson et al., 2001. 

Page Child-Specific Exposure Factors Handbook 

10-26 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-20. Fish Consumption Rates among Native American Children (age 5 years and under)a 

Grams/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 

Note: 

Source: 

Sample size = 194; unweighted mean = 19.6 grams/day; unweighted standard error = 1.94. 

Data are compiled from the Umatilla, Nez Perce, Yakama, and Warm Springs tribes of the Columbia River Basin. 

CRITFC, 1994. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 10-27
 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-21. Number of Fish Meal Eaten per Month and Fish Intake Among Native American Children who Consume Particular Species 

Species N 

Unweighted Mean 

Fish Meals/Month 

Unweighted SE Unweighted Mean 

Intake (g/day) 

Unweighted SE 

Salmon 

Lamprey 

Trout 

Smelt 

Whitefish 

Sturgeon 

Walleye 

Squawfish 

Sucker 

Shad 

164 

37 

89 

39 

21 

21 

5 

2 

4 

3 

2.3 

0.89 

0.96 

0.40 

3.5 

0.43 

0.22 

0.00 

0.35 

0.10 

0.16 

0.27 

0.12 

0.09 

2.83 

0.12 

0.20 

-

0.22 

0.06 

19 

8.1 

8.8 

3.8 

21 

4.0 

2.0 

0.0 

2.6 

1.1 

1.5 

2.8 

1.4 

0.99 

16 

1.3 

1.5 

-

1.7 

0.57 

SE = Standard error. 

Source: CRITFC, 1994. 

Page Child-Specific Exposure Factors Handbook 

10-28 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-22. Consumption Rates for Native American Children, Age Birth to Five Years (g/kg-day) 

Fish Category Mean (SE) 95% CI 50th percentile 90th percentile 

Tulalip Tribes (N = 21) 

Shellfish 0.13 (0.056) (0.014, 0.24) 0.0 0.60 

Total finfish 0.11 (0.030) (0.056, 0.17) 0.060 0.29 

Total, all fish 0.24 (0.077) (0.088, 0.39) 0.078 0.74 

Squaxin Island Tribe (N = 48) 

Shellfish 0.23 (0.053) (0.13, 0.37) 0.045 0.57 

Total finfish 0.25 (0.063) (0.13, 0.37) 0.061 0.83 

Total, all fish 0.83 (0.14) (0.55, 1.1) 0.51 2.1 

Both Tribes Combined (weighted) 

Shellfish 0.18 (0.039) (0.10, 0.25) 0.012 0.57 

Total finfish 0.18 (0.035) (0.10, 0.25) 0.064 0.32 

Total, all fish 0.53 (0.081) (0.37, 0.69) 0.17 1.4 

SE = Standard error. 

CI = Confidence interval. 

N = Sample size. 

Source: Toy et al., 1996. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-29
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-23. 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 clamsHorse clamsButter clamsGeoduckCocklesOystersMusselsMoon snailsShrimpDungeness crabRed rock crabScallopsSquidSea urchinSea cucumber 

313131313131313131313131313131 

0.0950.0220.021

0.110.12

0.0190.0010.0000.093

0.30

0.0070.0110.002

0.0

0.0 

0.0510.0130.0140.0410.0790.0120.001

-

0.038

0.13

0.0030.0060.002

--

0.00.00.0

0.033

0.00.00.0

-

0.0190.0530.001

0.00.0

--

0.20

0.0480.048

0.190.27

0.0430.002

-

0.170.55

0.0140.0220.005

--

0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0 

0.031

0.00.0

0.027

0.00.00.00.0

0.0040.047

0.00.00.00.00.0 

0.0630.006

0.0

0.12

0.0540.056

0.00.0

0.059

0.17

0.0

0.005

0.00.00.0 

0.18

0.0480.041

0.250.24

0.058

0.00.0

0.39

1.3

0.0460.031

0.00.00.0 

0.760.270.250.84

1.2

0.21

0.011

0.0

0.71

2.7

0.0640.089

0.00.00.0 

1.6

0.350.42

1.12.4

0.36

0.026

0.0

0.98

2.8

0.082

0.170.41

0.00.0 

Group Aa 

Group Bb Group Cc Group Dd Group Fe 

3131313131 

0.27

0.004

0.130.030.24 

0.12

0.0020.0400.0110.075 

0.043

0.0

0.0520.0080.094 

0.50

0.008

0.21

0.053

0.39 

0.00.00.00.00.0 

0.063

0.0

0.0360.0100.092 

0.22

0.0

0.21

0.037

0.25 

0.53

0.015

0.34

0.081

0.68 

2.1

0.038

0.840.19

1.6 

3.6

0.069

1.0

0.34

1.9 

All FinfishAll ShellfishAll Seafood 

313131 

0.680.80

1.5 

0.170.270.35 

0.350.260.80 

1.01.32.2 

0.026

0.0

0.042 

0.310.290.72 

0.740.80

2.0 

2.12.33.3 

3.55.07.3 

4.17.99.1 

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.

N = Sample size.SE = Standard errorLCL = Lower confidence limitUCL = Upper confidence limitP5...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. 

Page Child-Specific Exposure Factors Handbook 

10-30 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-24. 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 0.13 0.068 0.043 0.066 0.20 

Horse clams 12 0.058 0.032 0.009 0.046 0.31 

Butter clams 6 0.11 0.066 0.032 0.20 -

Geoduck 22 0.16 0.054 0.053 0.23 0.55 

Cockles 10 0.36 0.23 0.078 0.29 2.2 

Oysters 10 0.060 0.035 0.015 0.074 0.34 

Mussels 1 0.026 - - - -

Moon snails 0 - - - - -

Shrimp 17 0.17 0.064 0.035 0.30 0.62 

Dungeness crab 21 0.44 0.18 0.082 0.305 2.3 

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 0.13 0.11 0.25 0.60 

Group Bb 5 0.023 0.012 0.017 0.043 -

Group Cc 25 0.16 0.048 0.048 0.24 0.49 

Group Dd 17 0.055 0.019 0.033 0.064 0.14 

Group Fe

 (tuna/other finfish) 24 0.31 0.092 0.18 0.34 1.0 

All finfish 31 0.68 0.17 0.31 0.74 2.1 

All shellfish 28 0.89 0.30 0.36 0.85 2.5 

All seafood 31 1.5 0.35 0.72 2.0 3.4 

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. 

N = Sample size. 

SE = Standard error. 

- = No data. 

Source: Duncan, 2000. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-31
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-25. Fish Consumption Rates for Tulalip and Squaxin Island Children 

Consumers Only (g/kg-day) 

Percentilesb 

Speciesa 

N Mean SD 5th 10th 25th 50th 75th 90th 95th 

Squaxin Island Tribe 

Anadromous fish 33 0.39 1.3 0.005 0.006 0.030 0.049 0.13 0.69 0.79 

Pelagic fish 21 0.16 0.25 0.010 0.014 0.019 0.044 0.11 0.55 0.71 

Bottom fish 18 0.17 0.36 - 0.006 0.014 0.026 0.050 0.48 -

Shellfish 31 2.3 8.6 0.006 0.025 0.050 0.26 0.40 0.77 4.5 

Other fish 30 0.58 0.58 0.012 0.051 0.11 0.40 0.57 1.6 1.6 

All finfish 35 0.54 1.3 0.005 0.007 0.046 0.062 0.22 1.7 2.3 

All fish 36 2.9 8.4 0.012 0.019 0.24 0.70 1.5 2.8 7.7 

Tulalip Tribe 

Anadromous fish 14 0.15 0.23 - 0.012 0.026 0.045 0.14 0.33 -

Pelagic fish 7 0.15 0.18 - - 0.027 0.053 0.17 - -

Bottom fish 2 0.044 0.005 - - - 0.041 - - -

Shellfish 11 0.31 0.39 - 0.012 0.034 0.036 0.52 0.80 -

Other fish 1 0.12 0.12 - - - - - - -

All finfish 15 0.31 0.33 - 0.027 0.082 0.133 0.43 0.73 -

All fish 15 0.45 0.53 - 0.066 0.088 0.22 0.60 0.88 - a	 	 Anadromous included: salmon, steelhead,and smelt. Pelagic included: cod, pollock, sablefish, rockfish, 

greenling, herring, spiny dogfish, perch, mackarel, and shark. Bottom included: halibut, sole/flounder, 

sturgeon, skate, eel, and grunters. Shellfish included: clams, cockles, mussels, oysters, shrimp, crabs, snails, 

scallops, squid, sea urchins, geoduck, limpets, lobster, bullhead, manta ray, razor clam, chitons, octopus, 

abalone, barnacles, and crayfish. Other included canned tuna and trout, b	 	 Due to the small sample size for some fish groups, some percentiles could not be computed. A percentile was 

only calculated if it was between 100%*1/(N+1) and 100%*N/(N+1), where N is the number of consumers of a 

species group. 

N 	 = Sample size. 

SD 	 = Standard deviation. 

-	 = No data. 

Source:	 	 Polissar et al., 2006. 

Page Child-Specific Exposure Factors Handbook 

10-32 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-26. Fish Consumption Rates by Gender for Tulalip and Squaxin Island Children

 Consumers Only (g/kg-day) 

Percentilesb 

Speciesa Gender N Mean SD 5th 10th 25th 50th 75th 90th 95th 

Squaxin Island Tribe 

Anadromous fish Male 15 0.70 1.9 - 0.009 0.026 0.062 0.33 1.1 -

Female 18 0.16 0.25 - 0.005 0.025 0.046 0.090 0.60 -

Pelagic fish Male 8 0.10 0.14 - - 0.015 0.058 0.099 - -

Female 13 0.18 0.28 - 0.015 0.020 0.040 0.11 0.68 -

Bottom fish Male 6 0.038 0.057 - - 0.016 0.020 0.026 - -

Female 12 0.24 0.44 - 0.005 0.010 0.028 0.11 0.74 -

Shellfish Male 13 0.28 0.24 - 0.036 0.047 0.24 0.35 0.46 -

Female 18 3.8 11.2 - 0.008 0.050 0.23 0.49 1.3 -

Other fish Male 13 0.84 0.66 - 0.11 0.23 0.45 1.5 1.6 -

Female 17 0.40 0.46 - 0.013 0.096 0.31 0.49 0.61 -

All finfish Male 15 0.79 1.9 - 0.009 0.038 0.062 0.52 1.5 -

Female 20 0.37 0.72 0.005 0.005 0.037 0.071 0.18 1.4 2.1 

All fish Male 15 1.7 2.0 - 0.061 0.48 1.2 1.9 2.4 -

Female 21 3.7 10.7 0.008 0.014 0.16 0.60 0.92 2.8 16.4 

Tulalip Tribe 

Anadromous fish Male 7 0.061 0.052 - - 0.023 0.034 0.067 - -

Female 7 0.24 0.31 - - 0.032 0.080 0.20 - -

Pelagic fish Male 5 0.11 0.081 - - 0.044 0.053 0.13 - -

Female 2 0.27 0.35 - - - 0.017 - - -

Bottom fish Male 0 - - - - - - - - -

Female 2 0.044 0.005 - - - 0.041 - - -

Shellfish Male 5 0.14 0.22 - - 0.012 0.027 0.11 - -

Female 6 0.43 0.46 - - 0.034 0.22 0.65 - -

Other fish Male 0 - - - - - - - - -

Female 1 0.12 0.12 - - - - - - -

All finfish Male 8 0.21 0.18 - - 0.087 0.13 0.32 - -

Female 7 0.43 0.44 - - 0.045 0.17 0.65 - -

All fish Male 8 0.20 0.17 - - 0.071 0.12 0.23 - -

Female 7 0.75 0.67 - - 0.16 0.49 0.84 - - a	 	 Anadromous included: salmon, steelhead,and smelt. Pelagic included: cod, pollock, sablefish, rockfish, greenling, 

herring, spiny dogfish, perch, mackarel, and shark. Bottom included: halibut, sole/flounder, sturgeon, skate, eel, 

and grunters. Shellfish included: clams, cockles, mussels, oysters, shrimp, crabs, snails, scallops, squid, sea 

urchins, geoduck, limpets, lobster, bullhead, manta ray, razor clam, chitons, octopus, abalone, barnacles, and 

crayfish. Other included canned tuna and trout, b	 	 Due to the small sample size for some fish groups, some percentiles could not be computed. A percentile was only 

calculated if it was between 100%*1/(N+1) and 100%*N/(N+1), where N is the number of consumers of a species 

group. 

N 	 = Sample size. 

SD 	 = Standard deviation. 

-	 = No data. 

Source:	 	 Polissar et al., 2006. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-33
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-27. Distribution of Quantity of Canned Tuna Consumed (grams) Per Eating Occasion, by Age and Sex 

Age (years)-Sex Group Mean SE 

5th 10th 25th 

Percentiles 

50th 75th 90th 95th 

2 to 5 

Male-Female 38 3 7* 8 15 29 55 73 85* 

6 to 11 

Male-Female 57 8 14* 20* 26 49 59 99* 157* 

12 to 19 

Male 

Female 

84* 

64 

12* 

6 

-

14* 

18* 

18* 

49* 

28* 

74 

56 

97* 

77* 

162* 

105* 

-

156* 

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). 

Table 10-28. 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*
 


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). 

Page Child-Specific Exposure Factors Handbook 

10-34 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

FINFISH 

Anchovy, European 

Bass, Freshwater 

Bass, Striped 

Bluefish 

Burbot 

Butterfish 

Carp 

Catfish, Channel, Farmed 

Catfish, Channel, Wild 

Cavier, Black and Red 

Cisco 

Cod, Atlantic 

Cod, Pacific 

Croaker, Atlantic 

Cusk 

Dolphinfish 

Drum, Freshwater 

Eel 

Flatfish, Flounder, and Sole 

Grouper 

Haddock 

Halibut, Atlantic and Pacific 

Halibut, Greenland 

Herring, Atlantic 

Herring, Pacific 

Ling 

73.37 

50.30 

4.84 

9.71 

Raw 

Canned in oil, drained solids 

75.66 

68.79 

3.69 

4,73 

Raw 

Cooked, dry heat 

79.22 

73.36 

2.33 

2.99 

Raw 

Cooked, dry heat 

70.86 

62.64 

4.24 

5.44 

Raw 

Cooked, dry heat 

79.26 

73.41 

0.81 

1.04 

Raw 

Cooked, dry heat 

74.13 

66.83 

8.02 

10.28 

Raw 

Cooked, dry heat 

76.31 

69.63 

5.60 

7.17 

Raw 

Cooked, dry heat 

75.38 

71.58 

7.59 

8.02 

Raw 

Cooked, dry heat 

80.36 

77.67 

2.82 

2.85 

Raw 

Cooked, dry heat 

47.50 17.90 -­

78.93 

1.91 

69.80 

11.90 

Raw 

Smoked 

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 

81.28 

76.00 

0.63 

0.81 

Raw 

Cooked, dry heat 

78.03 

59.76 

3.17 

12.67 

Raw 

Cooked, breaded and fried 

76.35 

69,68 

0.69 

0.88 

Raw 

Cooked, dry heat 

77.55 

71.22 

0.70 

0.90 

Raw 

Cooked, dry heat 

77.33 

70.94 

4.93 

6.32 

Raw 

Cooked, dry heat 

69.26 

59.31 

11.66 

14.95 

Raw 

Cooked, dry heat 

79.06 

73.16 

1.19 

1.53 

Raw 

Cooked, dry heat 

79.22 

73.36 

1.02 

1.30 

Raw, mixed species 

Cooked, dry heat 

79.92 

74.25 

71.48 

0.72 

0.93 

0.96 

Raw 

Cooked, dry heat 

Smoked 

77.92 

71.69 

2.29 

2.94 

Raw 

Cooked, dry heat 

70.27 

61.88 

13.84 

17.74 

Raw 

Cooked, dry heat 

72.05 

64.16 

59.70 

55.22 

9.04 

11.59 

12.37 

18.00 

Raw 

Cooked, dry heat 

Kippered 

Pickled 

71.52 

63.49 

13.88 

17.79 

Raw 

Cooked, dry heat 

79.63 

73,88 

0.64 

0.82 

Raw 

Cooked, dry heat 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-35
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (continued) 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

Lingcod 

Mackerel, Atlantic 

Mackerel, Jack 

Mackerel, King 

Mackerel, Pacific and Jack 

Mackerel, Spanish 

Milkfish 

Monkfish 

Mullet, Striped 

Ocean Perch, Atlantic 

Perch 

Pike, Northern 

Pike, Walleye 

Pollock, Atlantic 

Pollock, Walleye 

Pompano, Florida 

Pout, Ocean 

Rockfish, Pacific 

Roe 

Roughy, Orange 

Sablefish 

Salmon, Atlantic, Farmed 

Salmon, Atlantic, WIld 

Salmon, Chinook 

Salmon, Chum 

Salmon, Coho, Farmed 

Salmon, Coho, Wild 

81.03 

75.68 

63.55 

53.27 

69.17 

75.85 

69.04 

70.15 

61.73 

71.67 

68.46 

70.85 

62.63 

83.24 

78.51 

77.01 

70.52 

78.70 

72.69 

79.13 

73.25 

78.92 

72.97 

79.31 

73.47 

78.18 

72.03 

81.56 

74.06 

71.12 

62.97 

81.36 

76.10 

79.26 

73.41 

67.73 

58.63 

75.67 

66.97 

71.02 

62.85 

60.14 

68.90 

64.75 

68.50 

59.62 

71.64 

65.60 

72.00 

75.38 

68.44 

70.77 

70.47 

67.00 

72.66 

71.50 

65.39 

1.06 

1.36 

13.89 

17.81 

6.30 

2.00 

2.56 

7.89 

10.12 

6.30 

6.32 

6.73 

8.63 

1.52 

1.95 

3.79 

4.86 

1.63 

2.09 

0.92 

1.18 

0.69 

0.88 

1.22 

1.56 

0.98 

1.26 

0.80 

1.12 

9.47 

12.14 

0.91 

1.17 

1.57 

2.01 

6.42 

8.23 

0.70 

0.90 

15.30 

19.62 

20.14 

10.85 

12.35 

6.34 

8.13 

10.43 

13.38 

4.32 

3.77 

4.83 

5.50 

7.67 

8.23 

5.93 

4.30 

7.50 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Canned, drained solids 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Smoked 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Smoked 

Raw 

Cooked, dry heat 

Drained solids with bone 

Raw 

Cooked, dry heat 

Raw 

Cooked, dry heat 

Cooked, moist heat 

Page Child-Specific Exposure Factors Handbook 

10-36 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued) 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

Salmon, Pink 

Salmon, Sockeye 

Sardine, Atlantic 

Sardine, Pacific 

Scup 

Sea Bass 

Seatrout 

Shad, American 

Shark, mixed species 

Sheepshead 

Smelt, Rainbow 

Snapper 

Spot 

Sturgeon 

Sucker, white 

Sunfish, Pumpkinseed 

Surimi 

Swordfish 

Tilapia 

Tilefish 

Trout, Mixed Species 

Trout, Rainbow, Farmed 

Trout, Rainbow, Wild 

Tuna, Fresh, Bluefin 

Tuna, Fresh, Skipjack 

Tuna, Fresh, Yellowfin 

Tuna, Light 

Tuna, White 

76.35 

69.68 

68.81 

3.45 

4.42 

6.05 

Raw 

Cooked, dry heat 

Canned, solids with bone and liquid 

70.24 

61.84 

67.51 

8.56 

10.97 

7.31 

Raw 

Cooked, dry heat 

Canned, drained solids with bone 

59.61 11.45 Canned in oil, drained solids with bone 

66.65 10.46 Canned in tomato sauce, drained solids with bone 

75.37 

68.42 

2.73 

3.50 

Raw 

Cooked, dry heat 

78.27 

72.14 

2.00 

2.56 

Raw 

Cooked, dry heat 

78.09 

71.91 

3.61 

4.63 

Raw 

Cooked, dry heat 

68.19 

59.22 

13.77 

17.65 

Raw 

Cooked, dry heat 

73.58 

60.09 

4.51 

13.82 

Raw 

Cooked, batter-dipped and fried 

77.97 

69.04 

2.41 

1.63 

Raw 

Cooked, dry heat 

78.77 

72.79 

2.42 

3.10 

Raw 

Cooked, dry heat 

76.87 

70.35 

1.34 

1.72 

Raw 

Cooked, dry heat 

75.95 

69.17 

4.90 

6.28 

Raw 

Cooked, dry heat 

76.55 

69.94 

62.50 

4.04 

5.18 

4.40 

Raw 

Cooked, dry heat 

Smoked 

79.71 

73.99 

2.32 

2.97 

Raw 

Cooked, dry heat 

79.50 

73.72 

0.70 

0.90 

Raw 

Cooked, dry heat 

76.34 0.90 -

75.62 

68.75 

4.01 

5.14 

Raw 

Cooked, dry heat 

78.08 

71.59 

1.70 

2.65 

Raw 

Cooked, dry heat 

78.90 

70.24 

2.31 

4.69 

Raw 

Cooked, dry heat 

71.42 

63.36 

6.61 

8.47 

Raw 

Cooked, dry heat 

72.73 

67.53 

5.40 

7.20 

Raw 

Cooked, dry heat 

71.87 

70.50 

3.46 

5.82 

Raw 

Cooked, dry heat 

68.09 

59.09 

4.90 

6.28 

Raw 

Cooked, dry heat 

70.58 

62.28 

1.01 

1.29 

Raw 

Cooked, dry heat 

70.99 

62.81 

0.95 

1.22 

Raw 

Cooked, dry heat 

59.83 

74.51 

8.21 

0.82 

Canned in oil, drained solids 

Canned in water, drained solids 

64.02 

73.19 

8.08 

2.97 

Canned in oil, drained solids 

Canned in water, drained solids 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-37
 

Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued) 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

Turbot, European 

Whitefish, mixed species 

Whiting, mixed species 

Wolffish, Atlantic 

Yellowtail, mixed species 

76.95 

70.45 

2.95 

3.78 

Raw 

Cooked, dry heat 

72.77 

65.09 

70.83 

5.86 

7.51 

0.93 

Raw 

Cooked, dry heat 

Smoked 

80.27 

74.71 

1.31 

1.69 

Raw 

Cooked, dry heat 

79.90 

74.23 

2.39 

3.06 

Raw 

Cooked, dry heat 

74.52 

67.33 

5.24 

6.72 

Raw 

Cooked, dry heat 

SHELLFISH 

Abalone 

Clam 

Crab, Alaska King 

Crab, Blue 

Crab, Dungeness 

Crab, Queen 

Crayfish, Farmed 

Crayfish, Wild 

Cuttlefish 

Lobster, Northern 

Lobster, Spiny 

Mussel, Blue 

Octopus 

Oyster, Eastern 

74.56 

60.10 

0.76 

6.78 

Raw 

Coofed, fried 

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 

79.57 

77.55 

74.66 

0.60 

1.54 

0.46 

Raw 

Cooked, moist heat 

Imitation, made from surimi 

79.02 

79.16 

77.43 

71.00 

1.08 

1.23 

1.77 

7.52 

Raw 

Canned 

Cooked, moist heat 

Crab cakes 

79.18 

73.31 

0.97 

1.24 

Raw 

Cooked, moist heat 

80.58 

75.10 

1.18 

1.51 

Raw 

Cooked, moist heat 

84.05 

80.80 

0.97 

1.30 

Raw 

Cooked, moist heat 

82.24 

79.37 

0.95 

1.20 

Raw 

Cooked, moist heat 

80.56 

61.12 

0.70 

1.40 

Raw 

Cooked, moist heat 

76.76 

76.03 

0.90 

0.59 

Raw 

Cooked, moist heat 

74.07 

66.76 

1.51 

1.94 

Raw 

Cooked, moist heat 

80.58 

61.15 

2.24 

4.48 

Raw 

Cooked, moist heat 

80.25 

60.50 

1.04 

2.08 

Raw 

Cooked, moist heat 

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 

Page Child-Specific Exposure Factors Handbook 

10-38 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-29. Mean Percent Moisture and Total Fat Content for Selected Species (Continued) 

Species Moisture Content 

(%) 

Total Fat Content 

(%) Comments 

Oyster, Pacific 

Scallop, mixed species 

Shrimp 

Squid 

82.06 

64.12 

2.30 

4.60 

Raw 

Cooked, moist heat 

78.57 

58.44 

73.10 

0.76 

10.94 

1.40 

Raw 

Cooked, breaded and fried 

Steamed 

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 

78.55 

64.54 

1.38 

7.48 

Raw 

Cooked, fried 

Source: USDA, 2007. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 10-39
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific 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. 

Children’s exposure from contaminated meats, 

dairy products, and fats may differ from that of adults 

because of differences in the type and amounts of food 

eaten. Also, for many foods, the intake per unit body 

weight is greater for children than for adults. Common 

meats, dairy products, and fats eaten by children 

include non-fat milk solids, milk fat and solids, lean 

beef, and milk sugar (lactose) (Goldman, 1995). 

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, 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 children 

during the survey period averaged across only the 

children who consumed these food items during the 

survey period. Per capita intake rates are generated by 

averaging consumer-only intakes over the entire 

population of children. In general, per capita intake 

rates are appropriate for use in exposure assessment for 

which average dose estimates for children are of interest 

because they represent both children who ate the foods 

during the survey period and children 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 

consume the food in question. Total intake refers to the 

sum of all meats, diary 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 asconsumed weight. 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. 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. Ideally, aftercooking food concentrations should be combined with 

the as-consumed intake rates. In the absence of data, it 

is reasonable to assume that no change in contaminant 

concentration occurs after cooking. 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, the reader is referred 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, 

the reader is referred to Sections 11.5 and 11.6 of this 

chapter. 

The purpose of this chapter is to provide intake 

data for meats, diary products, and fats among children. 

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 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-1
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

based on the key studies identified by U.S. EPA for this 

factor. Following the recommendations, the key studies 

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 among 

children. 

11.2 RECOMMENDATIONS 

Table 11-1 presents a summary of the 

recommended values for per capita and consumers-only 

intake of meats, diary products, and fats, on an asconsumed basis. Confidence ratings for the meats, 

dairy products, and fat intake recommendations for 

general population children are provided in Table 11-2. 

U.S. EPA analyses of data from the 1994-96 and 

1998 Continuing Survey of Food Intake among 

Individuals (CSFII) were used in selecting 

recommended intake rates for general population 

children. The U.S. EPA analysis of meat and dairy 

products was conducted using 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 U.S. EPA analysis of fat intake data 

from the CSFII used the age groups recommended by 

U.S. EPA (2005). The CSFII data on which the 

recommendations for meats, dairy products, and fats are 

based are short-term survey data and may not 

necessarily reflect the long-term distribution of average 

daily intake rates. However, for these broad categories 

of food (i.e., total meats and diary products), because 

they 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. It should be noted that because these 

recommendations are based on 1994-96 and 1998 

CSFII data, they may not reflect the most recent 

changes that may have occurred in consumption 

patterns. 

Page Child-Specific Exposure Factors Handbook 

11-2 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific 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, As Consumed 

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 Meatsa 

Birth to 1 year 1.2 6.7 3.0 9.2 

See Tables 11-3 

and 11-4 

U.S. EPA 

Analysis of 

CSFII, 1994­

96 and 1998. 

1 to <2 years 4.1 9.8 4.2 9.8 

2 to <3 years 4.1 9.8 4.2 9.8 

3 to <6 years 4.1 9.4 4.2 9.4 

6 to <11 years 2.9 6.5 2.9 6.5 

11 to <16 years 2.1 4.8 2.1 4.8 

16 to <21 years 2.1 4.8 2.1 4.8 

Total Dairy Productsa 

Birth to 1 year 13 49 16 58 

See Tables 11-3 

and 11-4 

U.S. EPA 

Analysis of 

CSFII, 1994­

96 and 1998. 

1 to <2 years 37 88 37 88 

2 to <3 years 37 88 37 88 

3 to <6 years 23 49 23 49 

6 to <11 years 14 32 14 32 

11 to <16 years 5.6 16 5.6 16 

16 to <21 years 5.6 16 5.6 16 

Individual Meat and Dairy Products - See Tables 11-5 and 11-6 

Total Fats 

Birth to <1 month 5.2 16 7.8 16 

See Tables 11­

20 and 11-24 

U.S. EPA 

Analysis of 

CSFII, 1994­

96 and 1998. 

1 to <3 months 4.5 11 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 

a Analysis was conducted using slightly different 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. 

Child-Specific Exposure Factors Handbook Page
 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodology and data analysis was adequate. 

The survey sampled approximately 11,000 children. An 

analysis of primary data was conducted. 

No physical measurements were taken. The method relied 

on recent recall of meats and diary 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 1994 and 1998. 

Data were collected for two non-consecutive days. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The CSFII data are publicly available. 

The methodology used was clearly described; 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. 

High 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Full distributions were provided for total meats, total diary 

products, and total fats. Means were provided for 

individual meats and diary 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 diary products, and total 

fats. Uncertainty is likely to be greater for individual 

meats and diary products. 

Medium 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-2. Confidence in Recommendations for Intake of Meats, Diary Products, and Fats (continued) 

General Assessment Factors Rationale Rating 

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 analysis of these data has not been 

peer reviewed outside the Agency. 

There was 1 key study for intake of meat and diary 

products and 1 key study for fat intake. Both were based on the 

1994-96, 1998 CSFII. 

Medium 

Overall Rating High confidence in 

the averages; 

Low confidence in the 

long-term upper 

percentiles 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

11.3 INTAKE STUDIES 

The primary source of recent information on 

consumption rates of meat and diary products among 

children is the U.S. Department of Agriculture’s 

(USDA) CSFII. Data from the 1994-96 CSFII and the 

1998 Children’s supplement to the 1994-96 CSFII have 

been used in various studies to generate children’s 

consumer-only and per capita intake rates for both 

individual meats and diary products and total meats and 

diary products. The CSFII is a series of surveys 

designed to measure the kinds and amounts of foods 

eaten by Americans. The CSFII 1994-96 was 

conducted between January 1994 and January 1997 

with a target population of non-institutionalized 

individuals in all 50 states and Washington, D.C. 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 1994-96 and was intended 

to be merged with CSFII 1994-96 to increase the 

sample size for children. The merged surveys are 

designated as CSFII 1994-96, 1998. Additional 

information on these surveys can be obtained at 

http://www.ars.usda.gov/Services/docs.htm?docid=14 

531. 

The CSFII 1994-96, 1998 collected dietary 

intake data through in-person interviews on 2 nonconsecutive 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. Over 11,000 of the sample persons 

represented children up to 18 years of age. The 2-day 

response rate for the 1994-1996 CSFII was 

approximately 76 percent. The 2-day response rate for 

CSFII 1998 was 82 percent. 

The CSFII 1994-96, 98 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 fours years of the surveys can be combined. 

USDA recommends that all 4 years be combined in 

order to provide an adequate sample size for children. 

11.3.1 Key Meat and Diary Intake Study 

11.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 

1998 

For many years, the U.S. EPA’s Office of 

Pesticide Programs (OPP) has used food consumption 

data collected by the U.S. Department of Agriculture 

(USDA) for its dietary risk assessments. Most recently, 

OPP, in cooperation with USDA’s Agricultural 

Research Service (ARS), used data from the 1994-96, 

1998 CSFII to develop the Food Commodity Intake 

Database (FCID). CSFII 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 animal 

(or plant) parts consumed by humans as food; when 

such items are raw or unprocessed, they are referred to 

as "raw agricultural commodities." For example, a beef 

stew may contain the commodities beef, carrots, and 

potatoes. FCID contains approximately 553 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/). 

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. Appendix 11A presents 

the food codes and definitions used to determine the 

various meats and dairy products used in the analysis. 

Intake rates for these food items/groups represent intake 

of all forms of the product (e.g., both home produced 

and commercially produced). Children who provided 

data for two 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. 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 four-year, two-day sample 

weights provided in the 1994-96, 1998 CSFII to adjust 

the data for the sample population to reflect the national 

population. 

Summary statistics were generated on both 

a per capita and a consumer only basis. For per capita 

intake, both users and non-users of the food item were 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

included in the analysis. Consumer only intake rates 

were calculated using data for only those individuals 

who ate the food item of interest during the survey 

period. Intake data from the CSFII are based on asconsumed (i.e., cooked or prepared) forms of the food 

items/groups. Summary statistics, including: number of 

observations, percentage of the population consuming 

the meat or 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 100th 

percentile were also provided for total meats and dairy 

products. Data were provided for the following age 

groups of children: birth to <1 year, 1 to <2 years, 3 to 

<5 years, 6 to <12 years, and 13 to <19 years. Because 

these data were developed for use in U.S. EPA’s 

pesticide registration program, the 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 as-consumed per capita 

intake data for total meats and dairy products in g/kgday; as-consumed consumer-only intake data for total 

meats and dairy products in g/kg-day are provided in 

Table 11-4. Table 11-5 provides per capita intake data 

for certain individual meats and dairy products and 

Table 11-6 provides consumer only intake data for 

these individual meats and dairy products. 

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 longterm 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 dairy 

products) 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 products (i.e., total meats 

and dairy products). 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. 

The strengths of U.S. EPA’s analysis are 

that it provides distributions of intake rates for various 

age groups of children, normalized by body weight. 

The analysis uses the 1994-96, 1998 CSFII data set 

which was designed to be representative of the U.S. 

population. The data set includes four years of intake 

data combined, and is based on a two-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. Also, the analysis 

was conducted using slightly different age groups that 

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, 1999a - Food and Nutrient Intakes 

by Children 1994-96, 1998, Table Set 17 

USDA (1999a) calculated national 

probability estimates of food and nutrient intake by 

children based on all 4 years of the CSFII (1994-96 and 

1998) for children age 9 years and under and on CSFII 

1994-96 only for individuals age 10 years and over. 

Sample weights were used 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 nonconsumers 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. Tables 11-7 and 11-8 present 

data on the mean quantities (grams) of meat and eggs 

consumed per individual for one day, and the 

percentage of survey individuals consuming meats and 

eggs on that survey day. Tables 11-9 and 11-10 present 

similar data for dairy products. Data on mean intakes 

or mean percentages are based on respondents’ day-1 

intakes. 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

The advantage of the USDA (1999a) study 

is that it uses the 1994-96, 98 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 

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 one

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. 

11.3.2.2	 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 1994-96 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 2 and above, who 

provided 2 days of dietary intake information. A total 

of 4,939 of these respondents were children, ages 2 to 

19 years of age. Only dietary intake data from users of 

the specified food were used in the analysis (i.e., 

consumers only data). 

Table 11-11 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 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. 

11.3.2.3	 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 oversampled 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 percent for the 

recruitment interview. Of the recruited households, 

there was a response rate of 94 percent for the dietary 

recall interviews (Devaney et al., 2004). The 

characteristics of the FITS study population is shown in 

Table 11-12. 

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 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

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 11-13 provides the percentage of 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 percent for 4 to 6 month olds to 97.2 

percent for 19 to 24 month olds (Table 11-13). 

The advantages of this study were 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). 

11.3.2.4	 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 = 1159) and 12 to 24 months (N= 996). The 

total sample size described by WIC participant and nonparticipant is shown in Table 11-14. 

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 11-14 presents the 

demographic data for WIC participants and nonparticipants. Table 11-15 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 (Table 11-15). 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 the 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 one-associated 

with the FITS data and are described previously in 

Section 11.3.2.3. 

11.3.2.5	 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 

(Menella 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 

and 1,228 non-Hispanic), and 12 to 24 months (N = 124 

Hispanic and 871 non-Hispanic) of age. 

Table 11-16 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 nonHispanic 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 11.3.2.3 for the FITS 

data. 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

11.3.2.6	 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 11.3.2.3 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. 

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. Tables 

11-17 and 11-18 present the average portion sizes of 

meats and dairy products for infants and toddlers, 

respectively. 

11.4	 FAT INTAKE 

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 1994–96, 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 0 and 1 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 ten 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 was 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 approximately 

11,000 CSFII child respondents who had provided body 

weights and who had completed both days of the twoday 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, 

and nuts/seeds/beans/legumes/tubers) and 98 

demographic cohorts. Fat intake was calculated as a 

two-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-body-weight basis is heavily skewed towards 

young children, and an analysis across the entire 

American population was desired. For infants, the “less 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

than one 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 percent of 

each age group. The selected individuals made up a 

survey population of 1,175 children. 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 reanalysis of the some of the data was conducted for this 

chapter to conform with U.S. EPA’s recommended age 

groups for children. The results of this re-analysis are 

presented in Tables 11-19 through 11-26 for individuals 

less than 21 years of age. Only intake rates of all fats 

are provided in these tables; the reader is referred to 

U.S. EPA (2007) for fat intake rates from individual 

food sources. Tables 11-19 and 11-20 present intake 

rates of all fats for the whole population (i.e., per 

capita) in g/day and g/kg-day, respectively. Table 11­

21 and 11-22 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 11-23 in g/day and in Table 11-24 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; 

and 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. 

Data for 6-month old to 17-year old individuals 

collected during 1973 to 1982 are presented in Tables 

11-25 and 11-26 (Frank et al., 1986). Data are 

presented for total fats, animal fats, vegetable fats, and 

fish fats in units of g/day (Table 11-25) and g/kg/day 

(Table 11-26). 

11.4.2.2	 CDC, 1994 - Dietary Fat and Total Foodenergy Intake: Third National Health and 

Nutrition Examination Survey, Phase 1, 

1988-91 

The Centers for Disease Control and 

Prevention (CDC, 1994) used data from NHANES III 

to calculate daily total food energy intake (TFEI), total 

dietary fat intake, and saturated fat intake for the U.S. 

population during 1988 to 1991. The sample 

population comprised 20,277 individuals ages 2 months 

and above, of which 14,801 respondents (73 percent 

response rate) provided dietary information based on a 

24-hour recall. Of these, 6,870 were children between 

the ages of 2 months and 19 years. TFEI was defined 

as “all nutrients (i.e., protein, fat, carbohydrate, and 

alcohol) derived from consumption of foods and 

beverages (excluding plain drinking water) measured in 

kilocalories (kcal).” Total dietary fat intake was 

defined as “all fat (i.e., saturated and unsaturated) 

derived from consumption of foods and beverages 

measured in grams” (CDC, 1994). 

The authors estimated and provided data on 

the mean daily TFEI and the mean percentages of TFEI 

from total dietary fat grouped by age and gender. The 

overall mean daily TFEI for the total population was 

2,095 kcal, of which 34 percent (712 kcal or 82 g) was 

from total dietary fat. Based on this information, the 

mean daily fat intake was calculated for the various age 

groups and genders (see Appendix 11B for detailed 

calculation). Table 11-27 presents the grams of fat per 

day obtained from the daily consumption of foods and 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

beverages grouped by age and gender for the U.S. 

population, based on this calculation. 

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 

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. 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 11-28 and the following equation: 

 L
  meats and dairy products, then the dry weight units IRlw = IR ww 

100
  (Eqn. 11-3) 

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 where: 

using the moisture content percentages presented in IRlw = lipid weight intake rate; 

Table 11-28 and the following equation: = wet weight intake rate; and Irww 

L = percent lipid (fat) content. 

(Eqn. 11-1) 100 − W  IRdw IR 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 

= 

  ww 100 

where: follows: 

IRdw = dry weight intake rate;  L
  IRww = wet weight intake rate; and 

W = percent water content 

Cww = Clw (Eqn. 11-4) 

  100
 

Alternatively, dry weight residue levels in meat and where:
 

dairy products may be converted to wet weight residue C = wet weight intake rate;
 ww 

levels for use with wet weight (e.g., as-consumed)	 C = lipid weight intake rate; and lw 

intake rates as follows: L = percent lipid (fat) content. 

(Eqn. 11-2) The resulting residue levels may then be used in 100 − W  C

ww 

Cdw conjunction with wet weight (e.g., as-consumed) 

consumption rates. The total fat content data presented 

in Table 11-28 are for selected meat and dairy products 

= 

  100 

where: taken from USDA, 2007. 

Cww = wet weight intake rate; 

Cdw = dry weight intake rate; and 

W = percent water content. 

The moisture content data presented in Table 11-28 are 

for selected meats and dairy products taken from USDA 

(2007). 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

11.7	 REFERENCES FOR CHAPTER 11 

CDC. (1994) Dietary fat and total food-energy intake: 

Third National Health and Nutrition 

Examination Survey, Phase 1, 1988-91. Center 

for Disease Control. Morbidity and Mortality 

Weekly Report, February 25, 1994: 43(7)118­

125. 

Cresanta, J.L.; Farris, R.P.; Croft, J.B.; Frank, G.C.; 

Berenson, G.S. (1988) Trends in fatty acid 

intakes of 10-year-old children, 1973-1982. 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(Suppl 1): S8­

S13. 

Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L. (2004) 

Feeding Infants and Toddlers Study: what 

foods are infants and toddlers eating. J Am 

Diet Assoc 104 (Suppl): S22-S30. 

Fox, M.K.; 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 (Suppl 1): S66-S76. 

Frank, G.C.; Webber, L.S.; Farris, R.P.; Berenson, G.S. 

(1986) Dietary databook: quantifying dietary 

intakes of infants, children, and adolescents, the 

Bogalusa heart study, 1973-1983. National 

Research and Demonstration Center ­

Arteriosclerosis, Louisiana State University 

Medical Center, New Orleans, Louisiana. 

Goldman, L. (1995) Children - unique and vulnerable. 

Environmental risks facing children and 

recommendations for response. Environ Health 

Perspect 103(6):13-17. 

Mennella, J.; 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 (Suppl 1): S96-S106. 

Nicklas, T.A. (1995) Dietary studies of children: The 

Bogalusa Heart Study experience. J Am Diet 

Assoc 95:1127-1133. 

Nicklas, T.A.; Webber, L.S.; Srinivasan, S.R.; 

Berenson, G.S. (1993) Secular trends in 

dietary intakes and cardiovascular risk factors 

in 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 (Suppl): S71-S79. 

Smiciklas-Wright, H.; Mitchell, D.C.; Mickle, S.J.; 

Cook, A.J.; Goldman, J.D. (2002) Foods 

commonly eaten in the United States: quantities 

consumed per eating occasion and in a day, 

1994-1996. U.S. Department of Agriculture 

NFS Report No. 96-5, pre-publication version, 

252 pp. 

USDA. (1999a) Food and nutrient intakes by children 

1994-96, 1998: Table Set 17. Beltsville, MD: 

Food Surveys Research Group, Beltsville 

Human Nutrition Research Center, Agricultural 

Research Service, U.S. Department of 

Agriculture. 

USDA. (1999b) USDA Nutrient Database for Standard 

Reference, Release 13. Agricultural Research 

Service, Nutrient Data Laboratory. 

http://www.nal.usda.gov/fnic/foodcomp 

USDA. (2000) 1994–96, 1998 Continuing Survey of 

Food Intakes by Individuals (CSFII). CDROM. Agricultural Research Service, 

Beltsville Human Nutrition Research Center, 

Beltsville, MD. Available from the National 

Technical Information Service, Springfield, 

VA; PB-2000-500027. 

USDA. (2007) USDA National Nutrient Database for 

Standard Reference, Release 20. Agricultural 

Research Service, Nutrient Data Laboratory 

Home Page, 

http://www.ars.usda.gov/ba/bhnrc/ndl 

U.S. EPA.	 (2000) Food commodity intake database 

[FCID raw data file]. Office of Pesticide 

Programs, Washington, DC. Available from the 

National Technical Information Service, 

Springfield, VA; PB2000-5000101. 

U.S. EPA.	 (2005) Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants. 

U.S. Environmental Protection Agency, 

Washington, D.C., EPA/630/P-03/003F. 

U.S. EPA. (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). National Center for 

Environmental Assessment, Washington, DC; 

EPA/600/R-05/021F. Available from the 

National Technical Information Service, 

Sp r ingfield , VA, and online at 

http://www.epa.gov/ncea. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-13
 
Table 11-3. Per Capita Intake of Total Meat and Dairy Products (g/kg-day as consumed) 

Age Group N Percent Consuming Mean SE Percentiles 1st 5th 10th 25th 50th 75th 90th 95th 

Total Meat 

Birth to 1 year 1,486 40.0 1.2 0.1 0.0 0.0 0.0 0.0 0.0 1.6 4.2 6.7 

1 to 2 years 2,096 97.3 4.1 0.1 0.0 0.2 0.8 1.9 3.6 5.7 8.0 9.8 

3 to 5 years 4,391 98.8 4.1 0.05 0.0 0.6 1.2 2.2 3.6 5.4 7.7 9.4 

6 to 12 years 2,089 98.7 2.9 0.05 0.0 0.4 0.8 1.5 2.5 3.8 5.4 6.5 

13 to 19 years 1,222 98.8 2.1 0.05 0.0 0.2 0.5 1.0 1.9 2.7 3.8 4.8 

Total Dairy 

Birth to 1 year 1,486 79.5 12.6 0.9 0.0 0.0 0.0 1.0 8.0 14.1 24.1 48.7 

1 to 2 years 2,096 99.8 36.7 0.7 0.4 3.9 7.7 17.4 31.3 49.8 72.1 88.3 3 to 5 years 4,391 100.0 23.3 0.3 1.1 4.2 7.0 13.0 20.8 30.9 42.0 49.4 

6 to 12 years 2,089 100.0 13.6 0.4 0.3 1.8 3.5 6.7 11.7 18.5 26.0 31.5 13 to 19 years 1,222 99.8 5.6 0.2 0.01 0.2 0.5 1.5 4.2 8.1 12.5 15.5 

N SE 

= Sample size. 

= Standard error. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

11-

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Table 11-4. Consumer Only Intake of Total Meat and Dairy Products (g/(kg-day as consumed) Age Group N Mean SE Percentiles 1st 5th 10th 25th 50th 75th 90th 95th 

Total Meat Birth to 1 year 575 3.0 0.2 0.01 0.1 0.3 1.0 2.2 4.2 7.4 9.2 

1 to 2 years 2,044 4.2 0.1 0.04 0.6 1.0 2.1 3.6 5.7 8.1 9.8 

3 to 5 years 4,334 4.2 0.1 0.04 0.8 1.2 2.2 3.6 5.5 7.7 9.4 

6 to 12 years 2,065 2.9 0.1 0.1 0.5 0.9 1.5 2.5 3.9 5.4 6.5 13 to 19 years 1,208 2.1 0.1 0.02 0.3 0.6 1.1 1.9 2.8 3.8 4.8 

Total Dairy 

Birth to 1 year 1,192 15.9 1.0 0.03 0.8 1.9 5.8 10.2 16.0 27.7 57.5 

1 to 2 years 2,093 36.8 0.7 0.4 4.2 7.8 17.4 31.3 49.8 72.1 88.3 

3 to 5 years 4,390 23.3 0.3 1.1 4.2 7.0 13.0 20.8 30.9 42.0 49.4 

6 to 12 years 2,089 13.6 0.4 0.3 1.8 3.5 6.7 11.7 18.5 26.0 31.5 

13 to 19 years 1,221 5.6 0.2 0.01 0.3 0.5 1.5 4.2 8.1 12.5 15.5 

N = Sample size. 

SE = Standard error. Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

SCehpitledm

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Exposure Factors Handbook 

11-

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Table 11-5. Per Capita Intake of Individual Meats and Dairy Products (g/kg-day as consumed) 

Age Group N 

Percent 

Consuming Mean SE Percent Consuming Mean SE Percent Consuming Mean SE Percent Consuming 

Beef Pork Poultry 

Birth to 1 year 1 to 2 years 3 to 5 years 6 to 12 years 13 to 19 years 

1,486 

2,096 4,391 

2,089 

1,222 

25.3 

85.5 90.8 

92.7 

91.1 

0.41 

1.7 1.8 

1.3 

1.0 

0.04 0.06 0.04 

0.04 

0.05 

17.7 69.7 79.8 

82.4 

81.5 

0.15 0.72 0.84 

0.59 

0.40 

0.02 0.03 0.02 

0.03 

0.03 

30.1 73.7 73.0 

67.1 

65.5 

0.66 

1.7 1.5 

0.93 

0.68 

0.05 0.05 0.03 

0.03 

0.03 

27.9 92.3 95.1 

95.8 

95.4 

N SE 

= Sample size. 

= Standard error. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

Table 11-6. Consumer Only Intake of Individual Meats and Dairy Products (g/kg-day as consumed) 

Age Group N Mean SE N Mean SE N Mean SE N Me

Beef Pork Poultry Eg

Birth to 1 year 1 to 2 years 3 to 5 years 6 to 12 years 13 to 19 years 

361 

1,795 3,964 

1,932 1,118 

1.6 

2.0 1.9 

1.4 1.1 

0.2 

0.06 0.04 

0.04 0.05 

248 

1,488 3,491 1,731 1,002 

0.83 

1.0 1.1 

0.72 0.50 

0.08 

0.04 0.03 

0.03 0.03 

434 

1,552 3,210 1,421 

808 

2.2 2.2 2.0 1.4 1.0 

0.1 

0.06 0.04 0.04 0.04 

402 

1,936 4,171 2,001 1,167 

11

0.0.0.

N SE 

= Sample size. 

= Standard error. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 

11-

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Table 11-7. Mean Quantities of Meat and Eggs consumed Daily by Sex and Age, Per Capita (g/day) Age Group Sample Size Total Beef Pork Lamb, veal, game Organ meats Frankfurters, sausages, luncheon meats Poultry Total Chicken Egg

Males and Females Under 1 year 1 year 2 years 1 to 2 years 3 years 4 years 5 years 3 to 5 years 5 years 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 

1a 

5 7 6 8 

10 14 11 

8 

-

a,b 

2 6 4 6 6 6 6 5 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

b 

-

b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

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 

Males 

6 to 9 years 6 to 11 years 12 to 19 years 

787 

1,031 

737 

151 154 250 

18 19 30 

7 7 

12 

-

a,b 

-

a,b 

1a 

-

a,b 

-

a,b 

0 

24 24 28 

23 22 31 

21 20 26 

11 12 22 

Females 

6 to 9 years 6 to 11 years 12 to 19 years 

704 969 732 

121 130 158 

17 18 21 

4 5 5 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

-

a,b 

18 19 15 

19 20 21 

16 17 19 

10 11 13 

Males and Females 

9 years and under 19 years and under 

9,309 

11,287 

110 152 

12 18 

5 7 

-

b 

-

a,b 

-

a,b 

-

a,b 

19 20 

18 22 

17 19 

12 14 

a Estimate is not statistically reliable due to small sample size reporting intake. b 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-17
 
Table 11-8. Percentage of Individuals Consuming Meats and Eggs, by Sex and Age (%) 

Age Group Sample Size Total Beef Pork Lamb, veal,

game 

Organ

meats 

Frankfurters,

sausages,

luncheon

meats 

Poultry 

Egg

Total Chicken 

Males and Females 

Under 1 year1 year2 years  1 to 2 years 3 years 4 years 5 years  3 to 5 years  5 years and under 

1,1261,0161,1022,1181,8311,859

884

4,5747,818 

26.077.485.281.486.286.287.186.577.5 

2.1

11.916.214.113.816.118.216.013.7 

1.1 a

7.3

14.911.213.313.813.213.411.2 

0.2 a 

0.8 a 0.8 a 0.8 a 0.5 a 0.5 a 0.6 a

0.50.6 

0.2 a 

0.2 a 0.2 a 0.2 a 

a,b

0.2 a 0.2 a 0.2 a 0.2 a 

6.1

26.333.229.936.437.035.136.130.4 

6.3

24.027.625.828.327.427.727.824.5 

5.0

23.125.624.426.025.124.825.322.6 

6.7

22.27.25.19.16.16.17.18.

Males 

6 to 9 years 6 to 11 years 12 to 19 years 

787

1,031

737 

87.487.886.8 

20.122.024.2 

11.912.215.8 

0.4 a 

0.4 a 0.6 a 

0.1 a

 0.2 a

0.0 

37.436.231.8 

24.822.920.6 

22.320.517.6 

15.15.17.

Females 

6 to 9 years 6 to 11 years 12 to 19 years 

704969732 

84.686.580.1 

19.420.222.0 

9.2

10.011.2 

0.4 a 

0.4 a 0.1 a 

0.2 a 0.1 a 0.1 a 

33.533.124.6 

23.122.921.6 

20.219.818.9 

13.13.15.

Males and Females 

9 years and under19 years and under 

9,309

11,287 

80.982.8 

16.119.6 

10.912.1 

0.50.4 

0.2 a 

0.1 a 

24.322.7 

24.322.7 

22.020.1 

17.16.

a Estimate is not statistically reliable due to small sample size reporting intake.b Value less than 0.5, but greater than 0.

Note: Percentages shown are representative of the first day of each participant’s survey response.

Source: USDA, 1999a. 

Page Child-Specific Exposure Factors Handbook 

11-18 September 2008 
 

Table 11-9. Mean Quantities of Dairy Products Consumed Daily by Sex and Age, Per Capita (g/day) Age Group Sample Size Total Milk and Milk Products Milk, Milk Drinks, Yogurt Total Fluid Milk Yogurt Total Whole Lowfat Skim Milk Desser

Males and Females Under 1 year 1 year 2 years 1 to 2 years 3 years 4 years 5 years 3 to 5 years 5 years 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 

5a 

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 

Males 

6 to 9 years 6 to 11 years 12 to 19 years 

787 

1,031 

737 

450 450 409 

405 402 358 

343 335 303 

127 121 

99 

176 172 158 

29 33 40 

6 6 

31 35 29 

Females 

6 to 9 years 6 to 11 years 12 to 19 years 

704 969 732 

380 382 269 

337 336 220 

288 283 190 

105 108 

66 

146 136 

92 

26 29 30 

4 4 

29 30 29 

Males and Females 

9 years and under 19 years and under 

9,309 

11,287 

453 405 

417 362 

323 291 

153 121 

141 135 

22 29 

8 6 

23 27 

a Estimate is not statistically reliable due to small sample size reporting intake. b 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-19
 
 

Table 11-10. Percentage of Individuals Consuming Dairy Products, by Sex and Age (%) 

Age Group Sample Size 

Total 

Milk and 

Milk 

Products 

Milk, milk drinks, yogurt 

Total 

Fluid Milk 

Yogurt 

Total Whole Lowfat Skim 

Milk 

Desser

Males and Females 

Under 1 year 1 year 2 years 

1 to 2 years 

3 years 4 years 5 years 

3 to 5 years 5 years 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 

0.2a 

1.5a 

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 

Males 

6 to 9 years 6 to 11 years 12 to 19 years 

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 

1.7a 

24.0 25.0 13.6 

Females 

6 to 9 years 6 to 11 years 12 to 19 years 

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 

2.2a 

24.1 22.4 17.1 

Males and Females 

9 years and under 

19 years 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 

a 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. 

Page Child-Specific Exposure Factors Handbook 

11-20 September 2008 
Table 11-11. Quantity (as consumed) of Meat and Dairy Products Consumed Per Eating Occasion and Percentage of Individuals Using These Food

Quantity consumed per eating occasion (grams) 

Food category 

2 to 5 years old 6 to 11 years old 12 to 19 years old 

Male and Female 

(N = 2,109) 

Male and Female 

(N = 1,432) 

Male 

(N = 696) 

F

(N 

PC Mean SEM PC Mean SEM PC Mean SEM PC 

Meats 

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 44 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 

Dairy Products 

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 

a 

PC SEM 

Indicates a statistic that is potentially unreliable because of small sample size or large coefficient of variation.
 = Percent consuming at least once in 2 days.
 = Standard error of the mean.
 

Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data). 

S

C

e

h

p

i

t

l

e

d

m

-S

b

p

e

e

r 

c

2

if

0

i

0

c 

8 

Exposure Factors Handbook 

11-

Pa

2

g

1 

e 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-12. Characteristics of the FITS Sample Population 

Sample Size Percentage of Sample 

Gender 

Male 

Female 

1,549 

1,473 

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 

Child’s Ethnicity 

Hispanic or Latino 

Non-Hispanic or Latino 

Missing 

367 

2,641 

14 

Child’s Race 

White 

Black 

Other 

2,417 

225 

380 

Urbanicity 

Urban 

Suburban 

Rural 

Missing 

1,389 

1,014 

577 

42 

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 

Receives WIC 

Yes 

No 

Missing 

821 

2,196 

5 

Sample Size (Unweighted) 3,022 

51.3 

48.7 

28.5 

16.0 

22.5 

12.4 

10.2 

10.4 

12.1 

87.4 

0.5 

80.0 

7.4 

12.6 

46.0 

33.6 

19.1 

1.3 

1.6 

1.6 

7.3 

11.9 

23.9 

19.5 

10.3 

9.0 

14.9 

27.2 

72.6 

0.2 

100.0 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Devaney et al., 2004. 

Page Child-Specific Exposure Factors Handbook 

11-22 September 2008 
Table 11-13. Percentage of Infants and Toddlers Consuming 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 to14 15 to18 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 

 Reduce-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 

 BabyFood 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 

 OtherProtein Soources 2.7 9.7 36.1 59.2 66.8 68.9 

Dried Beans and Peas, Vegetarian Meat 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, Chilli, 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 Meat b 

 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 

 Fishand 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 two-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. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-23
 
 

 

 

Table 11-14. Characteristics of WIC Participants and Non-participants a (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 

Gender 

 Male 55 

 Female 45 

Child’s Ethnicity 

 Hispanic or Latino 20 

 Non-Hispanic or Latino 80 

Child’s Race 

 White 69 

 Black 15 

 Other 22 

Child In Day Care 

 Yes 39 

 No 61 

Age of Mother 

 14to19years 18 

 20to24years 33 

 25to29years 29 

 30to34years 9 

 35years or Older 9 

 Missing 2 

Mother’s Education 

 11th Grade or Less 23 

 Completed High School 35 

 SomePostsecondary 33 

 Completed College 7 

 Missing 2 

Parent’s Marital Status 

 Married 49 

 NotMarried 50 

 Missing 1 

Mother or Female Guardian Works 

 Yes 46 

 No 53 

 Missing 1 

Urbanicity 

 Urban 34 

 Suburban 36 

 Rural 28 

 Missing 2 

 Sample Size (Unweighted) 265 

54 

46 

** 

11 

89 

** 

84 

 4 

11 

38 

62 

** 

 1 

13 

29 

33 

23 

 2 

** 

 2 

19 

26 

53 

 1 

** 

93 

 7 

 1 

51 

48 

 1 

** 

 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 

** 

8 

92 

** 

86 

 5 

 9 

** 

46 

54 

** 

 1 

11 

30 

36 

21 

 1 

** 

 2 

20 

27 

51 

 0 

** 

93 

 7 

 0 

** 

60 

40 

 0 

** 

 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 

** 

10 

89 

** 

84 

 5 

11 

* 

53 

47 

** 

 1 

14 

26 

34 

26 

 1 

** 

 3 

19 

28 

48 

 2 

** 

88 

11 

 1 

* 

61 

38 

 1 

** 

 48 

 35 

 16 

 2 

791 

a 

WIC 

Source: 

X 

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 X2 test are listed next to the variable under the column labeled non-participants for 

each of the three age groups. *P<0.05; **P>0.01; non-participants significantly different from WIC participants on the variable. 

= Special Supplemental Nutrition Program for Women, Infants, and Children. 

Ponza et al., 2004. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Page Child-Specific Exposure Factors Handbook 

11-24 September 2008 
 

 

 

Table 11-15. Food Choices for Infants and Toddlers by WIC Participation Status 

Infants 4 to 6 months 

WIC NonParticipant participant 

Infants 7 to 11 months Toddlers 12 to 24 months 

WIC NonParticipant participant WIC Non-


Participant participant
 

Cow’s Milk 1.0 0.6 11.4 13.2 92.3 85.8* 

Meat or Other Protein Sources 

 BabyFood Meat 

 Non-Baby Meat 

 Eggs 

 Peanut Butter, Nuts, Seeds 

 Cheese 

 Yogurt 

0.9 

3.7 

0.9 

0.0 

0.0 

0.8 

2.0 

0.5** 

0.6 

0.0 

0.6 

1.4 

 3.3 

25.0 

 8.5 

 1.4 

 9.0 

5.5 

 3.6 

22.0 

 4.2** 

 1.3 

12.5 

 13.3** 

 0.0 

77.7 

24.1 

12.9 

38.5 

 9.3 

 0.3 

75.1 

23.0 

 9.8 

38.8 

 18.9** 

Sample Size (unweighted) 265 597 351 808 205 791 

* 

** 

WIC 

Source: 

= P<0.05; non-participants significantly different from WIC participants. 

= P<0.01; non-participants significantly different from WIC participants. 

= Special Supplemental Nutrition Program for Women, Infants, and Children. 

Ponza et al., 2004. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-25
 
Table 11-16. 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 

Hispanic Non-Hispanic 

(N=84) (N=538) 

Age 6 to 11months Age 12 to 24 months 

Hispanic Non-Hispanic 

(N=163) (N=1,228) 

Hispanic Non-Hispanic 

(N=124) (N=871) 

Milk 

Fed Any Cow’s or Goat Milk 

 FedCow’s Milk
 

 Whole
 

 Reduced Fat or Non-fat
 

Meat or Other Protein Sources 

 AnyMeat or Protein Sourcea
 

 Non-Baby Food Meat
 

 OtherProtein Sources
 

 Beansand Peas
 

 Eggs
 

 Cheese
 

 Yogurt
 

 Protein Sources in Mixed Dishes 

 BabyFood dinners b Soup

Types of Meat a 

 Beef 

 Chicken and Turkey 

 Hotdogs, Sausages, and Cold Cuts 

 Pork/Ham 

-


-


-


9.7†
 

-


1.4†
 

1.4†
 

-


-


-


7.5†
 

6.9†
 

-


-

-

-

-

-

-

-

5.3
 

-


-


-


-


-


-


4.4
 

3.9
 

-


-

-

-

-

 7.5† 

 5.6† 

 2.2† 

71.6 

22.5 

26.5 

 5.8† 

 9.5 

11.2 

 7.7 

44.8 

24.7* 

16.3** 

5.0† 

11.2 

 7.2† 

 3.8† 

11.3 

 8.3 

 3.0 

62.0 

19.2 

21.2 

 1.8 

 4.2 

 9.4 

 9.8 

41.6 

35.3 

 5.1 

 4.6 

11.9 

 3.4 

 1.7 

85.6 

61.7 

29.0 

90.3 

72.3 

70.1 

19.1* 

26.4 

29.3 

15.7 

33.3 

 3.5† 

23.4* 

25.2 

46.5 

14.8 

11.7 

87.7 

66.3 

27.0 

94.7 

76.0 

65.3 

 6.5 

22.5 

40.2 

17.0 

22.7 

 3.9 

10.7 

16.0 

43.6 

23.3 

12.1 

a	 

b	 

-	

* 

** 

† 

N 

Source:	 

Includes baby food and non-baby food sources. 

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. 

= Less than 1 percent of the group consumed this food on a given day. 

= Significantly different from non-Hispanic at the P<0.05. 

= Significantly different from non-Hispanic at the P>0.01. 

= Statistic is potentially unreliable because of a high coefficient of variation. 

= Sample size. 

Mennella et al., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Page Child-Specific Exposure Factors Handbook 

11-26 September 2008 
Table 11-17. Average Portion Sizes Per Eating Occasion of Meats and Dairy Products 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) 

9 to 11 months 

(N=687) 

Non-baby food meats 

Cheese 

Scrambled eggs 

Yogurt 

Baby food dinners 

ounce 

ounce 

cup 

ounce 

ounce 

Mean± SEM 

-

-

-

-

2.9±0.24 

0.9±0.16 

-

-

-

3.3±0.09 

0.8±0.05 

0.7±0.05 

0.2±0.02 

3.1±0.20 

3.8±0.11 

-

N 

SEM 

= Cell size was too small to generate a reliable estimate.
 

= Number of respondents.
 

= Standard error of the mean.
 

Source: Fox et al., 2006.
 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-27
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-18. 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 12 to 14 months 15 to 18 months 19 to 24 months Reference unit (N=371) (N=312) (N=320) 

Mean ± SEM 

Milk 

Milk fluid ounce 5.6±0.14 5.9±0.14 6.2±0.17 

Milk, as a beverage fluid ounce 5.7±0.14 6.1±0.14 6.4±0.17 

Milk, on cereal fluid ounce 3.4±0.37 2.7±0.26 3.6±0.29 

Meats and other protein sources 

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 ounce 1.3±0.13 1.5±0.13 1.5±0.12 

Chicken, breadeda ounce 1.5±0.14 1.5±0.13 1.8±0.12 

nugget 2.4±0.22 2.4±0.21 2.8±0.19 

Scrambled eggs cup 0.2±0.02 0.3±0.03 0.3±0.02 

Peanut butter tablespoon 0.7±0.08 0.7±0.09 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.
 

SEM = Standard error of the mean.
 

Source: Fox et al., 2006.
 

Page Child-Specific Exposure Factors Handbook 

11-28 September 2008 
 

 

 

Table 11-19. Total Fat Intake (Per capita; g/day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th 100th 

Birth to <1 year 

all 

female 

male 

Birth to <1 month 

all 

female 

male 

1 to <3 months 

all 

female 

male 

3 to <6 months 

all 

female 

male 

6 to <12 months 

all 

female 

male 

1 to <2 years 

all 

female 

male 

2 to <3 years 

all 

female 

male 

3 to <6 years 

all 

female 

male 

6 to <11 years 

all 

female 

male 

11 to <16 years 

all 

female 

male 

16 to <21 years 

all 

female 

male 

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 

743 

372 

371 

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 

85 

79 

92 

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 

47 

39 

53 

0.03 

0.03 

0.04 

0 

0 

0 

0 

0 

0 

0.10 

0.02 

0.15 

8.5 

5.1 

11 

24 

25 

23 

27 

24 

29 

34 

33 

35 

41 

38 

43 

42 

37 

50 

37 

35 

41 

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 

54 

49 

57 

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 

76 

75 

77 

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 

108 

96 

114 

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 

168 

154 

186 

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 

463 

317 

463 

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. 

Based on U.S. EPA, 2007. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-29
 
 

 

 

Table 11-20. Total Fat Intake (Per capita; g/kg-day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th 100th 

Birth to <1 year 

all 

female 

male 

Birth to <1 month 

all 

female 

male 

1 to <3 months 

all 

female 

male 

3 to <6 months 

all 

female 

male 

6 to <12 months 

all 

female 

male 

1 to <2 years 

all 

female 

male 

2 to <3 years 

all 

female 

male 

3 to <6 years 

all 

female 

male 

6 to <11 years 

all 

female 

male 

11 to <16 years 

all 

female 

male 

16 to <21 years 

all 

female 

male 

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 

743 

372 

371 

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 

1.3 

1.1 

1.4 

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 

0.80 

0.69 

0.86 

0.66 

0.56 

0.73 

0.01 

0.01 

0.01 

0 

0 

0 

0 

0 

0 

0.01 

0.00 

0.02 

1.0 

0.66 

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 

0.54 

0.48 

0.63 

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 

0.91 

1.2 

0.81 

0.75 

0.85 

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 

1.2 

1.1 

1.2 

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 

1.6 

1.4 

1.7 

8.9 

8.7 

9.2 

16 

13 

18 

11 

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 

2.7 

2.1 

2.9 

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 

6.0 

4.4 

6.0 

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. 

Based on U.S. EPA, 2007. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Page Child-Specific Exposure Factors Handbook 

11-30 September 2008 
 

 

 

Table 11-21. Total Fat Intake (Consumers Only; g/day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th 100th 

Birth to <1 year 

all 

female 

male 

Birth to <1 month 

all 

female 

male 

1 to <3 months 

all 

female 

male 

3 to <6 months 

all 

female 

male 

6 to <12 months 

all 

female 

male 

1 to <2 year 

all 

female 

male 

2 to <3 years 

all 

female 

male 

3 to <6 years 

all 

female 

male 

6 to <11 years 

all 

female 

male 

11 to <16 years 

all 

female 

male 

16 to <21 years 

all 

female 

male 

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 

743 

372 

371 

31 

30 

32 

26 

26 

25 

29 

28 

31 

30 

29 

31 

33 

32 

34 

46 

45 

46 

51 

49 

52 

59 

56 

61 

68 

64 

72 

80 

69 

91 

85 

79 

92 

16 

16 

16 

13 

11 

17 

14 

12 

16 

16 

16 

17 

16 

17 

16 

19 

18 

20 

21 

20 

21 

22 

21 

23 

24 

22 

25 

38 

29 

42 

47 

39 

53 

7.0 

5.1 

9.0 

6.7 

7.8 

-

5.8 

4.3 

8.5 

2.5 

1.2 

4.6 

8.9 

6.2 

11 

24 

25 

23 

27 

24 

29 

34 

33 

35 

41 

38 

43 

42 

37 

50 

37 

35 

41 

24 

24 

25 

17 

17 

-

24 

21 

27 

24 

24 

25 

25 

24 

25 

33 

33 

32 

37 

35 

39 

44 

43 

45 

50 

48 

55 

56 

49 

64 

54 

49 

57 

32 

32 

33 

27 

25 

-

31 

30 

31 

32 

31 

33 

34 

34 

34 

43 

43 

44 

48 

46 

50 

56 

54 

59 

66 

61 

70 

74 

65 

84 

76 

75 

77 

41 

40 

41 

32 

32 

-

35 

35 

38 

40 

39 

39 

43 

43 

44 

55 

54 

56 

60 

59 

61 

70 

68 

72 

81 

77 

86 

97 

82 

111 

108 

96 

114 

61 

58 

62 

52 

39 

-

53 

46 

59 

54 

52 

53 

62 

62 

62 

79 

77 

80 

87 

83 

89 

99 

96 

103 

111 

101 

115 

145 

123 

163 

168 

154 

186 

107 

92 

107 

64 

52 

64 

75 

50 

75 

107 

72 

107 

100 

92 

100 

159 

116 

159 

197 

127 

197 

218 

194 

218 

179 

156 

179 

342 

259 

342 

463 

317 

463 

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. 

Based on U.S. EPA, 2007. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-31
 
 

 

 

Table 11-22. Total Fat Intake (Consumers Only; g/kg-day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th 100th 

 Birth to <1 year 

all 

female 

male 

Birth to <1 month 

all 

female 

male 

1 to <3 months 

all 

female 

male 

3 to <6 months 

all 

female 

male 

6 to <12 months 

all 

female 

male 

1 to <2 years 

all 

female 

male 

2 to <3 years 

all 

female 

male 

3 to <6 years 

all 

female 

male 

6 to <11 years 

all 

female 

male 

11 to <16 years 

all 

female 

male 

16 to <21 years 

all 

female 

male 

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 

743 

372 

371 

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 

1.3 

1.1 

1.4 

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 

0.66 

0.56 

0.73 

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 

0.54 

0.48 

0.63 

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 

0.81 

0.75 

0.85 

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 

1.2 

1.1 

1.2 

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 

1.6 

1.4 

1.7 

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 

2.7 

2.1 

2.9 

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 

6.0 

4.4 

6.0 

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. 

Based on U.S. EPA, 2007. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Page Child-Specific Exposure Factors Handbook 

11-32 September 2008 
 

 

 

Table 11-23. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th 100th 

Birth to <1 year 

all 

female 

male 

1 to <2 years 

all 

female 

male 

2 to <3 years 

all 

female 

male 

3 to <6 years 

all 

female 

male 

6 to <11 years 

all 

female 

male 

11 to <16 years 

all 

16 to <21 years 

all 

11 to 20 years 

all 

female 

male 

140 

70 

70 

109 

54 

55 

103 

58 

45 

461 

217 

244 

198 

71 

127 

96 

68 

165 

53 

112 

45 

45 

45 

75 

68 

81 

79 

77 

81 

88 

84 

92 

94 

88 

97 

133 

167 

146 

117 

160 

16 

15 

17 

20 

16 

22 

20 

16 

24 

25 

24 

25 

25 

21 

27 

53 

64 

60 

30 

65 

28 

26 

28 

52 

52 

54 

55 

55 

52 

62 

59 

66 

66 

58 

69 

85 

98 

90 

81 

94 

35 

35 

34 

61 

57 

67 

64 

65 

61 

72 

68 

76 

77 

70 

78 

95 

122 

105 

92 

117 

45 

45 

44 

74 

70 

78 

74 

74 

73 

84 

80 

90 

88 

86 

91 

121 

154 

139 

111 

151 

54 

54 

53 

85 

78 

90 

85 

79 

90 

102 

95 

103 

105 

100 

112 

154 

189 

168 

140 

191 

77 

69 

79 

108 

89 

125 

116 

109 

121 

135 

130 

136 

140 

123 

168 

223 

278 

254 

162 

276 

100 

92 

100 

159 

114 

159 

133 

116 

133 

218 

194 

218 

178 

156 

178 

342 

463 

463 

195 

463 

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. 

Based on U.S. EPA, 2007. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-33
 
 

 

 

Table 11-24. Total Fat Intake - Top 10% of Animal Fat Consumers (Consumers Only; g/kg-day) 

Age Groupa N Mean SE 

Percentiles 

10th 25th 50th 75th 95th 100th 

 Birth to <1 year 

all 

female 

male 

1 to <2 years 

all 

female 

male 

2 to <3 years 

all 

female 

male 

3 to <6 years 

all 

female 

male 

6 to <11 years 

all 

female 

male 

11 to <16 years 

all 

16 to <21 years 

all 

11 to 20 years 

all 

female 

male 

140 

70 

70 

109 

54 

55 

103 

58 

45 

461 

217 

244 

198 

71 

127 

96 

68 

165 

53 

112 

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 

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 

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 

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 

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 

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 

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 

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 

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. 

Based on U.S. EPA, 2007. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Page Child-Specific Exposure Factors Handbook 

11-34 September 2008 
 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-25. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day) 

Age N Mean SD 

Percentiles 

Minimum 

10th 25th 50th 75th 90th 

Maximum 

Total Fat Intake 

6 months 

1 year 

2 years 

3 years 

4 years 

10 years 

13 years 

15 years 

17 years 

125 37.1 17.5 18.7 25.6 33.9 46.3 60.8 3.4 

99 59.1 26.0 29.1 40.4 56.1 71.4 94.4 21.6 

135 86.7 41.3 39.9 55.5 79.2 110.5 141.1 26.5 

106 91.6 38.8 50.2 63.6 82.6 114.6 153.0 32.6 

219 98.6 56.1 46.0 66.8 87.0 114.6 163.3 29.3 

871 93.2 50.8 45.7 60.5 81.4 111.3 154.5 14.6 

148 107.0 53.9 53.0 69.8 90.8 130.7 184.1 9.8 

108 97.7 48.7 46.1 65.2 85.8 124.0 165.2 10.0 

159 107.8 64.3 41.4 59.7 97.3 140.2 195.1 8.5 

107.6 

152.7 

236.4 

232.5 

584.6 

529.5 

282.2 

251.3 

327.4 

Total Animal Fat Intake

6 months 

1year 

2 years 

3 years 

4 years 

10 years 

13 years 

15 years 

17 years 

125 18.4 16.0 0.7 4.2 13.9 28.4 42.5 0.0 

99 36.5 20.0 15.2 23.1 33.0 45.9 65.3 0.0 

135 49.5 28.3 20.1 28.9 42.1 66.0 81.4 10.0 

106 50.1 29.4 21.3 29.1 42.9 64.4 88.9 14.1 

219 50.8 31.7 21.4 28.1 42.6 66.4 92.6 5.9 

871 54.1 39.6 20.3 30.6 45.0 64.6 97.5 0.0 

148 56.2 39.8 19.8 28.5 44.8 72.8 109.4 4.7 

108 53.8 35.1 15.9 28.3 44.7 67.9 105.8 0.6 

159 64.4 48.5 15.2 30.7 51.6 86.6 128.8 2.6 

61.1 

127.1 

153.4 

182.6 

242.2 

412.3 

209.6 

182.1 

230.3 

Total Vegetable Fat Intake 

6 months 

1 year 

2 years 

3 years 

4 years 

10 years 

13 years 

15 years 

17 years 

125 9.2 12.8 0.6 1.2 2.8 11.6 29.4 0.0 

99 15.4 14.3 3.7 6.1 11.3 18.1 38.0 0.2 

135 19.3 16.3 3.8 7.9 14.8 26.6 42.9 0.7 

106 21.1 15.5 3.9 8.6 18.7 26.6 45.2 1.0 

219 24.5 18.6 5.7 10.4 21.8 33.3 48.5 0.9 

871 23.7 21.6 4.3 9.5 18.3 30.6 49.0 0.6 

148 34.3 27.4 8.4 17.9 31.2 44.6 57.5 0.0 

108 27.3 22.8 5.1 11.9 22.6 38.1 54.4 0.7 

159 25.7 21.3 4.2 11.7 20.8 32.9 47.6 0.0 

53.2 

70.2 

96.6 

70.4 

109.0 

203.7 

238.3 

132.2 

141.5 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-35
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-25. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day) (continued) 

Age N Mean SD 

Percentiles 

Minimum 

10th 25th 50th 75th 90th 

Maximum 

Total Fish Fat Intake 

6 months 

1 year 

2 years 

3 years 

4 years 

10 years 

13 years 

15 years 

17 years 

125 0.05 0.1 0.0 0.0 0.0 0.0 0.1 0.0 

99 0.05 0.2 0.0 0.0 0.0 0.0 0.0 0.0 

135 0.04 0.2 0.0 0.0 0.0 0.0 0.0 0.0 

106 0.1 0.6 0.0 0.0 0.0 0.0 0.0 0.0 

219 2.3 31.1 0.0 0.0 0.0 0.0 0.0 0.0 

871 0.3 1.5 0.0 0.0 0.0 0.0 0.0 0.0 

148 0.3 2.2 0.0 0.0 0.0 0.0 0.0 0.0 

108 0.4 1.5 0.0 0.0 0.0 0.0 1.5 0.0 

159 0.5 2.0 0.0 0.0 0.0 0.0 0.4 0.0 

0.9 

1.9 

1.9 

4.5 

459.2 

19.2 

25.4 

9.5 

15.3 

N 

SD 

Source: 

= Sample size. 

= Standard deviation. 

Frank et al., 1986. 

Page Child-Specific Exposure Factors Handbook 

11-36 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-26. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg-day) 

Age N Mean SD 

Percentiles 

Minimum 

10th 25th 50th 75th 90th Maximum 

Total Fat Intake 

6 months 

1 year 

2 years 

3 years 

4 years 

10 years 

13 years 

15 years 

17 years 

125 4.9 2.3 2.4 3.3 4.7 6.2 8.0 0.4 

99 6.1 2.8 3.0 4.1 5.7 7.5 9.5 2.3 

132 7.0 3.3 3.4 4.5 6.2 8.6 11.9 2.1 

106 6.4 2.7 3.6 4.6 5.5 8.2 9.9 2.2 

218 6.1 3.7 2.9 4.0 5.2 7.0 10.0 2.0 

861 2.7 1.5 1.2 1.7 2.4 3.3 4.5 0.3 

147 2.3 1.3 1.0 1.5 2.0 2.8 3.8 0.2 

105 1.7 0.8 0.8 1.2 1.5 2.1 3.1 0.2 

149 1.8 1.0 0.7 0.9 1.6 2.2 3.1 0.2 

13.2 

16.4 

18.7 

16.7 

38.2 

13.9 

10.2 

4.7 

6.2 

Total Animal Fat Intake

6 months 

1 year 

2 years 

3 years 

4 years 

10 years 

13 years 

15 years 

17 years 

125 2.4 2.1 0.08 0.6 2.0 3.7 5.5 0.0 

99 3.8 2.1 1.7 2.4 3.4 4.9 6.5 0.0 

132 4.0 2.3 1.7 2.3 3.4 5.2 6.7 0.7 

106 3.5 2.0 1.6 2.1 3.1 4.2 6.1 0.9 

218 3.1 2.1 1.3 1.7 2.6 4.0 5.4 0.4 

861 16 1.2 0.6 0.8 1.3 1.9 2.8 0.00 

147 1.2 0.9 0.4 0.6 0.9 1.6 2.3 0.08 

105 1.0 0.6 0.3 0.5 0.8 1.3 1.9 0.01 

149 1.0 0.8 0.3 0.5 0.8 1.4 2.0 0.05 

9.0 

13.6 

13.4 

13.1 

15.4 

10.8 

5.2 

3.1 

4.2 

Total Vegetable Fat Intake 

6 months 

1year 

2 years 

3 years 

4 years 

10 years 

13 years 

15 years 

17 years 

125 1.2 1.8 0.08 0.2 0.4 1.6 4.1 0.0 

99 1.6 1.6 0.4 0.6 1.2 1.9 3.8 0.02 

132 1.6 1.4 0.3 0.7 1.1 2.0 3.5 0.06 

106 1.5 1.1 0.3 0.6 1.4 2.0 3.0 0.08 

218 1.5 1.2 0.4 0.6 1.2 2.1 2.8 0.06 

861 0.7 0.6 0.1 0.3 0.5 0.9 1.4 0.02 

147 0.8 0.8 0.2 0.4 0.6 0.9 1.3 0.0 

105 0.5 0.4 0.09 0.2 0.4 0.7 0.9 0.01 

149 0.4 0.4 0.07 0.2 0.4 0.6 0.9 0.0 

8.2 

7.6 

8.5 

5.1 

7.3 

4.2 

8.6 

2.2 

2.1 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-26. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg-day) (continued) 

Age N Mean SD 

Percentiles 

Minimum Maximum 

10th 25th 50th 75th 90th 

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 Child-Specific Exposure Factors Handbook 

11-38 September 2008 
 

 

 

Table 11-27. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gendera 

Age Group 

Total Males Females 

N Mean Fat Intake 

(g/day) N Mean Fat Intake 

(g/day) N Mean Fat Intake 

(g/day) 

2 to 11months 

1 to 2 years 

3 to 5 year 

6 to 11 years 

12 to 16 years 

16 to 19 years 

871 

1,231 

1,647 

1,745 

711 

785 

37.5 

50.0 

60.4 

74.2 

85.2 

100.5 

439 

601 

744 

868 

338 

308 

38.3 

51.6 

62.3 

79.4 

98.1 

123.2 

432 

630 

803 

877 

373 

397 

36.8 

48.4 

57.7 

69.0 

71.3 

77.5 

a	 

N	 

Source:	 

Total dietary fat intake includes all fat (i.e., saturated and unsaturated) derived from consumption of foods and beverages (excluding plain drinking water). = Sample size. 

Adapted from CDC, 1994. 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Child-Specific Exposure Factors Handbook Page
 

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Table 11-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Productsa 

Product Moisture 

Content 

(%) 

Total Fat 

Content 

(%) 

Comment 

Meats 

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 

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 

5.55 

8.05 

8.41 

Raw 

Cooked, roasted 

Cooked, stewed 

Chicken (broilers or fryers) 

Duck (domesticated) 

Turkey (all classes) 

75.46 

63.79 

65.99 

59.45 

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 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11-28. Mean Percent Moisture and Total Fat Content of Selected Meat and Dairy Productsa (continued) 

Product 

Moisture 

Content 

(%) 

Total Fat 

Content 

(%) 

Comment 

Dairy 

Milk 

Cream 

Butter 

Cheese 

Yogurt 

Eggs 

Whole 

Human 

Lowfat (1%) 

Reduced fat (2%) 

Skim or fat free 

Half and half 

Light (coffee cream or table cream) 

Heavy-whipping 

Sour 

Sour, reduced fat 

American 

Cheddar 

Swiss 

Cream 

Parmesan 

Cottage, lowfat 

Colby 

Blue 

Provolone 

Mozzarella 

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 

Source: 

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. 

USDA, 2007. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11-41
 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

APPENDIX 11A
 

CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS MEATS AND
 

DAIRY PRODUCTS USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11A-1 Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data 

Food Category EPA Food Commodity Codes 

Total Meats 21000440 Beef, meat 

21000441 Beef, meat-babyfood 

21000450 Beef, meat, dried 

21000460 Beef, meat byproducts 

21000461 Beef, meat byproducts-babyfood 

21000470 Beef, fat 

21000471 Beef, fat-babyfood 

23001730 Goat, liver 

24001890 Horse, meat 

25002900 Pork, meat 

25002901 Pork, meat-babyfood 

25002910 Pork, skin 

25002920 Pork, meat byproducts 

25002921 Pork, meat byproducts-babyfood 

25002930 Pork, fat 

25002931 Pork, fat-babyfood 

25002940 Pork, kidney 

25002950 Pork, liver 

26003390 Sheep, meat 

26003391 Sheep, meat-babyfood 

26003400 Sheep, meat byproducts 

26003410 Sheep, fat 

26003411 Sheep, fat-babyfood 

26003420 Sheep, kidney 

26003430 Sheep, liver 

28002210 Meat, game 

29003120 Rabbit, meat 

40000930 Chicken, meat 

40000931 Chicken, meat-babyfood 

40000940 Chicken, liver 

21000480 Beef, kidney 

21000490 Beef, liver 

21000491 Beef, liver-babyfood 

23001690 Goat, meat 

23001700 Goat, meat byproducts 

23001710 Goat, fat 

23001720 Goat, kidney 

40000950 Chicken, meat byproducts 

40000951 Chicken, meat byproducts-babyfood 

40000960 Chicken, fat 

40000961 Chicken, fat-babyfood 

40000970 Chicken, skin 

40000971 Chicken, skin-babyfood 

50003820 Turkey, meat 

50003821 Turkey, meat-babyfood 

50003830 Turkey, liver 

50003831 Turkey, liver-babyfood 

50003840 Turkey, meat byproducts 

50003841 Turkey, meat byproducts-babyfood 

50003850 Turkey, fat 

50003851 Turkey, fat-babyfood 

50003860 Turkey, skin 

50003861 Turkey, skin-babyfood 

60003010 Poultry, other, meat 

60003020 Poultry, other, liver 

60003030 Poultry, other, meat byproducts 

60003040 Poultry, other, fat 

60003050 Poultry, other, skin 

Total Dairy 27002220 Milk, fat 

27002221 Milk, fat - baby food/infant formula 

27012230 Milk, non-fat solids 

27012231 Milk, non-fat solids-baby food/infant 

formula 

27022240 Milk, water 

27022241 Milk, water-babyfood/infant formula 

27032251 Milk, sugar (lactose)-baby food/infant 

formula 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Table 11A-1 Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data (continued) 

Food Category EPA Food Commodity Codes 

Beef 21000440 Beef, meat 

21000441 Beef, meat-babyfood 

21000450 Beef, meat, dried 

21000460 Beef, meat byproducts 

21000461 Beef, meat byproducts-babyfood 

21000470 Beef, fat 

21000471 Beef, fat-babyfood 

21000480 Beef, kidney 

21000490 Beef, liver 

21000491 Beef, liver-babyfood 

Eggs 70001450 Egg, whole 

70001451 Egg, whole-babyfood 

70001460 Egg, white 

70001461 Egg, white (solids)-babyfood 

70001470 Egg, yolk 

70001471 Egg, yolk-babyfood 

Pork 25002900 Pork, meat 

25002901 Pork, meat-babyfood 

25002910 Pork, skin 

25002920 Pork, meat byproducts 

25002921 Pork, meat byproducts-babyfood 

25002930 Pork, fat 

25002931 Pork, fat-babyfood 

25002940 Pork, kidney 

25002950 Pork, liver 

Poultry 40000930 Chicken, meat 

40000931 Chicken, meat-babyfood 

40000940 Chicken, liver 

40000950 Chicken, meat byproducts 

40000951 Chicken, meat byproducts-babyfood 

40000960 Chicken, fat 

40000961 Chicken, fat-babyfood 

40000970 Chicken, skin 

40000971 Chicken, skin-babyfood 

50003820 Turkey, meat 

50003821 Turkey, meat-babyfood 

50003830 Turkey, liver 

50003831 Turkey, liver-babyfood 

50003840 Turkey, meat byproducts 

50003841 Turkey, meat byproducts-babyfood 

50003850 Turkey, fat 

50003851 Turkey, fat-babyfood 

50003860 Turkey, skin 

50003861 Turkey, skin-babyfood 

60003010 Poultry, other, meat 

60003020 Poultry, other, liver 

60003030 Poultry, other, meat byproducts 

60003040 Poultry, other, fat 

60003050 Poultry, other, skin 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11A-3
 
 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

APPENDIX 11B
 

SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED
 

ON CDC (1994) DATA
 

Child-Specific Exposure Factors Handbook Page
 

September 2008 11B-1
 
 

 

 

kcal g − fat g − fat 

0.34 × 2,095 × X = 82 day day day 

g − fat 

∴ X = 0.12 kcal 

kcal g− fat g− fat 

1,591 × 0.33 × 0.12 = 63 day kcal day 

Child-Specific Exposure Factors Handbook 

Chapter 11 - Intake of Meats, Dairy Products and Fats 

Sample Calculation of Mean Daily Fat Intake Based on 

CDC (1994) Data 

CDC (1994) provided data on the mean daily 

total food energy intake (TFEI) and the mean 

percentages of TFEI from total dietary fat grouped by 

age and gender. The overall mean daily TFEI was 

2,095 kcal for the total population and 34 percent (or 82 

g) of their TFEI was from total dietary fat (CDC, 1994). 

Based on this information, the amount of fat per kcal 

was calculated as shown in the following example. 

where 0.34 is the fraction of fat intake, 2,095 is the total 

food intake, and X is the conversion factor from 

kcal/day to g-fat/day. 

Using the conversion factor shown above 

(i.e., 0.12 g-fat/kcal) and the information on the mean 

daily TFEI and percentage of TFEI for the various 

age/gender groups, the daily fat intake was calculated 

for these groups. An example of obtaining the grams of 

fat from the daily TFEI (1,591 kcal/day) for children 

ages 3-5 years and their percent TFEI from total dietary 

fat (33 percent) is as follows: 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific 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 are needed. 

Children’s exposure from contaminated foods 

may differ from that of adults because of differences in 

the type and amounts of food eaten. Also, for many 

foods, the intake per unit body weight is greater for 

children than for adults. Common grain products eaten 

by children include milled rice, oats, and wheat flour 

(Goldman, 1995). 

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, 

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 

children during the survey period. These data are 

generated by averaging intake across only the children 

in the survey who consumed these food items. Per 

capita intake rates are generated by averaging 

consumer-only intakes over the entire population of 

children (including those children that reported no 

intake). In general, per capita intake rates are 

appropriate for use in exposure assessments for which 

average dose estimates for children are of interest 

because they represent both children who ate the foods 

during the survey period and children 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 asconsumed weight. 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. 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. Ideally, aftercooking food concentrations should be combined with 

the as-consumed intake rates. In the absence of data, it 

is reasonable to assume that no change in contaminant 

concentration occurs after cooking. 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, the reader is referred 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, the reader is referred to Section 12.4. 

The purpose of this chapter is to 

provide intake data for grain products among children. 

The recommendations for ingestion rates of grain 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

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. 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-of-knowledge 

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, on an as- consumed basis. 

Confidence ratings for the grain intake 

recommendations for general population children are 

provided in Table 12-2. 

The U.S. EPA analysis of data from the 1994­

96 and 1998 Continuing Survey of Food Intake among 

Individuals (CSFII) was used in selecting recommended 

intake rates for general population children. The U.S. 

EPA analysis was conducted using 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. Also, the CSFII 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, for 

broad categories of food (i.e., total grains), because 

they 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. It should also be noted that because these 

recommendations are based on 1994-96 and 1998 

CSFII data, they may not reflect the most recent 

changes that may have occurred in consumption 

patterns. More current data from the National Health 

and Nutrition Survey (NHANES) will be incorporated 

as the data become available and are analyzed. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-1. Recommended Values for Intake of Grains, As Consumeda 

Per Capita	 	 Consumers Only 

Multiple Age Group	 	 Mean 95 Source th Percentile Mean 95th Percentile Percentiles 

g/kg-day g/kg-day g/kg-day g/kg-day 

Total Grains 

Birth to 1 year 2.5 8.6 3.6 9.2 

1 to <2 years 6.4 12 6.4 12 

U.S. EPA 2 to <3 years 6.4 12 6.4 12 Analysis of 

3 to <6 years 6.3 12 6.3 12 See Tables CSFII, 

1994-96 and 12-3 and 6 to <11 years 4.3 8.2 4.3 8.2 1998. 12-4 

11 to <16 years 2.5 5.1 2.5 5.1 

16 to <21 years 2.5 5.1 2.5 5.1 

Individual Grain Products - See Tables 12-5 and 12-6 

a	 	 Analysis was conducted using slightly different 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. 

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Child-Specific Exposure Factors Handbook 

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 The survey methodology and data analysis was 

adequate. The survey sampled more than 11,000 

individuals up to age 18 years. An analysis of primary 

data was conducted. 

Minimal (or defined) Bias No physical measurements were taken. The method 

relied on recent recall of grain products eaten. 

High 

Applicability and Utility 

Exposure Factor of Interest The key study was directly relevant to grain intake. 

Representativeness The data were demographically representative of the 

U.S. population (based on stratified random sample). 

Currency 

Data Collection Period 

Data were collected between 1994 and 1998. 

Data were collected for two non-consecutive days. 

Medium 

Clarity and Completeness 

Accessibility The CSFII data are publicly available. 

Reproducibility The methodology used was clearly described; enough 

information was included to reproduce the results. 

Quality Assurance Quality assurance of the CSFII data was good; quality 

control of the secondary data analysis was not well 

described. 

High 

Variability and Uncertainty 

Variability in Population Full distributions were provided for total grains. 

Means were provided for individual grain products. 

Minimal Uncertainty Data collection was based on recall 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 grains. Uncertainty is likely to be greater 

for individual grain products. 

Medium 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-2. Confidence in Recommendations for Intake of Grain Products (continued) 

General Assessment Factors Rationale Rating 

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 analysis of these data has not 

been peer reviewed outside the Agency. 

There was 1 key study. 

Medium 

Overall Rating High confidence in the 

averages; 

Low confidence in the 

long-term upper 

percentiles 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

12.3 INTAKE STUDIES 

The primary source of recent information on 

consumption rates of grain products among children is 

the U.S. Department of Agriculture’s (USDA) CSFII. 

Data from the 1994-96 CSFII and the 1998 children’s 

supplement to the 1994-96 CSFII have been used in 

various studies to generate children’s consumer-only 

and per capita intake rates for both individual grain 

products and total grains. The CSFII is a series of 

surveys designed to measure the kinds and amounts of 

foods eaten by Americans. The CSFII 1994-96 was 

conducted between January 1994 and January 1997 

with a target population of non-institutionalized 

individuals in all 50 states and Washington, D.C. 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 1994-96 and was intended 

to be merged with CSFII 1994-96 to increase the 

sample size for children. The merged surveys are 

designated as CSFII 1994-96, 1998. Additional 

information on these surveys can be obtained at 

http://www.ars.usda.gov/Services/docs.htm?docid=14531. 

The CSFII 1994-96, 1998 collected dietary 

intake data through in-person interviews on 2 nonconsecutive 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. Over 11,000 of the sample persons 

represented children up to 18 years of age. The 2-day 

response rate for the 1994-1996 CSFII was 

approximately 76 percent. The 2-day response rate for 

CSFII 1998 was 82 percent. 

The CSFII 1994-96, 98 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 fours years of the surveys can be combined. 

USDA recommends that all 4 years be combined in 

order to provide an adequate sample size for children. 

12.3.1 Key Grain Intake Study 

12.3.1.1 U.S. EPA Analysis of CSFII 1994-96, 

1998 

For many years, the U.S. EPA’s Office of 

Pesticide Programs (OPP) has used food consumption 

data collected by the U.S. Department of Agriculture 

(USDA) for its dietary risk assessments. Most recently, 

OPP, in cooperation with USDA’s Agricultural 

Research Service (ARS), used data from the 1994-96, 

1998 CSFII to develop the Food Commodity Intake 

Database (FCID). CSFII 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 553 

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/). 

The grain items/groups selected for the 

U.S. EPA analysis included total grains, and individual 

grain products such as cereal and rice. Appendix 12A 

presents the food codes and definitions used to 

determine the various grain products used in the 

analysis. Intake rates for these food items/groups 

represent intake of all forms of the product (e.g., both 

home produced and commercially produced). Children 

who provided data for two 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. 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 four-year, two-day sample 

weights provided in the 1994-96, 1998 CSFII to adjust 

the data for the sample population to reflect the national 

population. 

Summary statistics were generated on both 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

a per capita and a consumer only basis. For per capita 

intake, both users and non-users of the food item were 

included in the analysis. Consumer-only intake rates 

were calculated using data for only those individuals 

who ate the food item of interest during the survey 

period. Intake data from the CSFII are based on asconsumed (i.e., cooked or prepared) forms of the food 

items/groups. Summary statistics, including: number of 

observations, percentage of the population consuming 

the grain product being analyzed, mean intake rate, and 

standard error of the mean intake rate were calculated 

for total grains and selected individual grain products. 

Percentiles of the intake rate distribution (i.e., 1st, 5th, 

10th, 25th, 50th, 75th, 90th, 95th, 99th, and 100th 

percentile were also provided for total grains. Data 

were provided for the following age groups of children: 

birth to <1 year, 1 to <2 years, 3 to <5 years, 6 to <12 

years, and 13 to <19 years. Because these data were 

developed for use in U.S. EPA’s pesticide registration 

program, the 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 as-consumed per 

capita intake data for total grains in g/kg-day; asconsumed consumer only intake data for total grains in 

g/kg-day are provided in Table 12-4. Table 12-5 

provides per capita intake data for individual grain 

products and Table 12-6 provides consumer only intake 

data for individual grain products. 

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 longterm 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 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 only for 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 grains, only 

the mean, standard error, and percent consuming are 

provided. 

The strengths of U.S. EPA’s analysis are 

that it provides distributions of intake rates for various 

age groups of children, normalized by body weight. 

The analysis uses the 1994-96, 1998 CSFII data set 

which was designed to be representative of the U.S. 

population. The data set includes four years of intake 

data combined, and is based on a two-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. Also, the analysis 

was conducted using slightly different age groups that 

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, 1999 - Food and Nutrient Intakes 

by Children 1994-96, 1998, Table Set 17 

USDA (1999) calculated national 

probability estimates of food and nutrient intake by 

children based on all 4 years of the CSFII (1994-96 and 

1998) for children age 9 years and under, and on CSFII 

1994-96 only for individuals age 10 years and over. 

Sample weights were used 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 nonconsumers were included in the analysis. 

USDA (1999) 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. Tables 12-7 and 12-8 present 

data on the mean quantities (grams) of grain products 

consumed per individual for one day, and the 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

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 advantages of USDA (1999) study is 

that it uses the 1994-96, 98 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 

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 one-day, and shortterm 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. 

12.3.2.2	 	 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 1994-96 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 2 and above, who provided 2 days of 

dietary intake information. A total of 4,939 of these 

respondents were children, ages 2 to 19 years of age. 

Only dietary intake data from users of the specified 

food were used in the analysis (i.e., consumers only 

data ). 

Table 12-9 presents serving size data for 

selected grain products. 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. 

12.3.2.3	 	 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 interviewwas 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 oversampled children in the 4 to 6 and 9 to11 months age 

groups; sample weights were adjusted for non-response, 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

over sampling , and under coverage of some subgroups. 

The response rate for the FITS was 73 percent for the 

recruitment interview. Of the recruited households, 

there was a response rate of 94 percent for the dietary 

recall interviews (Devaney et al., 2004). The 

characteristics of the FITS study population is shown in 

Table 12-10. 

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 12-11 provides the percentage of infants 

and toddlers consuming different types of grains or 

grain products at least once in a day. The percentages 

of children eating any type of grain or grain product 

ranged from 65.8 percent for 4 to 6 month olds to 99.2 

percent for 19 to 24 month olds. 

The advantages of this study were that the 

study population 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). 

12.3.2.4	 	 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). 

The total sample size described by WIC participants 

and non-participants is shown in Table 12-12. 

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 12-12 presents the 

demographic data for WIC participants and nonparticipants. Table 12-13 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 (Table 12­

13). Nonparticipants, 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 

were not provided. Other limitations are those 

associated with the FITS data, as described previously 

in Section 12.3.2.3. 

12.3.2.5	 	 Mennella et al., 2006 - Feeding Infants 

and Toddlers Study: The Types of Foods 

Fed to Hispanic Infants and Toddlers 

Menella 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 (Menella 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 and 1,228 non-Hispanic), and 12 to 24 months 

(N = 124 Hispanic and 871 non-Hispanic) of age. 

Table 12-14 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 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

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 

12.3.2.3 for the FITS data. 

12.3.2.6	 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 12.3.2.3 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. Tables 12-15 and 12-16 

present the average portion sizes for grain products for 

infants and toddlers, respectively. 

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 12-17 and the following equation:

⎡100 −W ⎤ IRdw = IR 

ww ⎣

⎢ 100 ⎦⎥ (Eqn. 12-1) 

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:

⎡100 −W ⎤ C

ww = Cdw ⎢ ⎥ (Eqn. 12-2) ⎣ 100 ⎦

where: 

Cww = wet weight intake rate; 

Cdw = dry weight intake rate; and 

W = percent water content. 

The moisture data presented in Table 12-17 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(Suppl 1): S8-

S13. 

Fox, M.K.; Pac, S.; Devaney, B.; Jankowski, L. (2004) 

Feeding infants and toddlers study: what 

foods are infants and toddlers eating. J Am 

Diet Assoc 104 (Suppl): S22-S30. 

Fox, M.K.; 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 (Suppl 1): S66-S76. 

Goldman, L. (1995) Children - unique and vulnerable. 

Environmental risks facing children and 

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Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

recommendations for response. Environ 

Health Perspect 103(6):13-17. 

Mennella, J.; 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 (Suppl 1): S96. 

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 (Suppl): S71­

S79. 

Smiciklas-Wright, H.; Mitchell, D.C.; Mickle, S.J.; 

Cook, A.J.; Goldman, J.D. (2002) Foods 

commonly eaten in the United States: 

Quantities consumed per eating occasion and 

in a day, 1994-1996. U.S. Department of 

Agriculture NFS Report No. 96-5, prepublication version, 252 pp. 

USDA.	 (1999) Food and nutrient intakes by children 

1994-96, 1998: Table Set 17. Beltsville, MD: 

Food Surveys Research Group, Beltsville 

Human Nutrition Research Center, 

Agricultural Research Service, U.S. 

Department of Agriculture. 

USDA. (2007) USDA National Nutrient Database for 

Standard Reference, Release 20. Agricultural 

Research Service, Nutrient Data Laboratory 

Home Page, 

http://www.ars.usda.gov/ba/bhnrc/ndl 

U.S. EPA.	 (2005) Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants. 

U.S. Environmental Protection Agency, 

Washington, D.C., EPA/630/P-03/003F. 

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Page Child-Specific Exposure Factors Handbook 

12-12 September 2008 Table 12-3. Per Capita Intake of Total Grains (g/kg-day as consumed) Age Group N Percent Consuming Mean SE 1st 5th 10th 25th Percentiles 50th 75th 90th 95th 

Birth to 1 year 1,486 70.5 2.5 0.1 0.0 0.0 0.0 0.0 1.6 3.8 6.2 8.6 

1 to 2 years 2,096 99.8 6.4 0.1 1.1 2.1 2.8 4.2 5.9 7.9 10.4 12.1 1

3 to 5 years 4,391 100.0 6.3 0.1 1.8 2.6 3.2 4.3 5.9 7.8 9.9 11.5 1

6 to 12 years 2,089 100.0 4.3 0.1 0.9 1.7 2.0 2.8 4.0 5.4 7.0 8.2 1

13 to 19 years 1,222 100.0 2.5 0.05 0.4 0.8 1.1 1.5 2.3 3.1 4.4 5.1 

N = Sample size. SE = Standard error. Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. Table 12-4. Consumer Only Intake of Total Grains (g/kg-day as consumed) Percentiles Age Group N Mean SE 1st 5th 10th 25th 50th 75th 90th 95th 99th 

Birth to 1 year 1,048 3.6 0.1 0.1 0.3 0.6 1.4 2.8 4.8 7.4 9.2 13.4 

1 to 2 years 2,092 6.4 0.1 1.2 2.1 2.8 4.2 5.9 7.9 10.4 12.1 16.8 

3 to 5 years 4,389 6.3 0.1 1.8 2.6 3.2 4.3 5.9 7.8 9.9 11.5 15.6 

6 to 12 years 2,089 4.3 0.1 0.9 1.7 2.0 2.8 4.0 5.4 7.0 8.2 11.1 

13 to 19 years 1,222 2.5 0.05 0.4 0.8 1.1 1.5 2.3 3.1 4.4 5.1 7.9 

N = Sample size. SE = Standard error. Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-5. Per Capita Intake of Individual Grain Products (g/kg-day as consumed) 

Cereal Rice 

Age Group N Percent Percent Mean SE Mean SE Consuming Consuming 

Birth to 1 year 1,486 74.6 4.0 0.14 60.2 0.74 0.04 

1 to 2 years 2,096 99.8 8.4 0.08 86.4 0.57 0.03 

3 to 5 years 4,391 100.0 8.7 0.07 87.9 0.50 0.03 

6 to 12 years 2,089 100.0 6.2 0.06 88.0 0.35 0.02 

13 to 19 years 1,222 100.0 4.1 0.06 85.8 0.27 0.02 

N = Sample size. 

SE = Standard error. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII . 

Table 12-6. Consumer Only Intake of Individual Grain Products (g/kg-day as consumed) 

Cereal Rice 

Age Group N Mean SE N Mean SE 

Birth to 1 year 1,116 5.4 0.16 900 1.23 0.07 

1 to 2 years 2,092 8.4 0.08 1,819 0.67 0.04 

3 to 5 years 4,389 8.7 0.07 3,869 0.57 0.03 

6 to 12 years 2,089 6.2 0.06 1,847 0.40 0.02 

13 to 19 years 1,222 4.1 0.06 1,038 0.31 0.03 

N = Sample size. 

SE = Standard error. 

Source: Based on unpublished U.S. EPA analysis of 1994-96, 1998 CSFII . 

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Table 12-7. Mean Quantities of Grain Products Consumed Daily by Sex and Age, Per Capita (g/day) 

Quick 

Cereals and Pasta Cakes, breads, Yeast, cookies, pancakes, Sample breads, pastries, Age Group Total Ready-to-eat French Size and rolls Total Rice Pasta pies cereals toast Cracker

popcorn

pretzels

corn chi

Males and Females 

1a Under 1year 1,126 56 2 2 1 2 1 3 

1 year 1,016 192 16 16 11 9 9 9 16 

2 years 1,102 219 26 26 16 15 12 12 22 

1 to 2 years 2,118 206 21 21 13 12 11 11 19 

3 years 1,831 242 30 30 19 13 12 16 23 4 years 1,859 264 36 36 22 15 11 17 30 5 years 884 284 41 41 24 17 11 15 33 

3 to 5 years 4,574 264 36 36 22 15 11 16 29 5 years and under 7,818 219 27 27 16 13 10 12 22 

1 7 9 8 

11 13 13 12 

9 

Males 

6 to 9 years 787 310 45 77 28 18 15 23 39 6 to 11 years 1,031 318 46 80 31 16 18 23 40 2 to 19 years 737 406 54 82 29 27 17 26 49 

16 15 19 

Females 

6 to 9 years 704 284 43 61 21 12 15 18 42 6 to 11 years 969 280 43 62 20 14 15 19 42 12 to 19 years 732 306 40 67 17 19 22 15 37 

13 14 15 

Males and Females 

9 years and under 9,309 250 34 64 20 14 12 16 30 19 years and under 11,287 298 40 69 22 17 15 18 36 

12 14 

a 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, 1999. 

Page Child-Specific Exposure Factors Handbook 

12-14 September 2008 
 

Table 12-8. Percentage of Individuals Consuming Grain Products, by Sex and Age (%) Age Group Sample Size Total Yeast, breads, and rolls Cereals and Pasta Quick breads, pancakes, French toast Total Ready-to­ eat cereals Rice Pasta Cakes, cookies, pastries, pies Cracker

popcorn

pretzels

corn chips 

Males and Females Under 1 year 1 year 2 years 1 to 2 years 3 years 4 years 5 years 3 to 5 years 

5 years and under 

1,126 1,016 1,102 2,118 1,831 1,859 

884 

4,574 7,818 

70.6 

98.2a 

99.0a 

98.7 

99.4a 

99.5a 99.9a 99.6a 

95.8 

10.9 48.4 58.7 53.7 64.1 67.0 69.2 66.8 55.5 

62.8 70.6 71.1 70.9 69.7 69.1 70.4 69.7 69.3 

9.1 

45.3 51.9 48.7 53.3 54.8 54.9 54.3 46.9 

3.4 

11.3 14.4 12.9 11.1 11.4 11.4 11.3 10.9 

2.1 9.4 9.4 9.4 8.6 7.1 6.8 7.5 7.5 

4.4 

23.0 27.5 25.3 28.8 28.6 25.2 27.5 24.0 

16.5 47.0 46.6 46.8 46.1 52.3 52.4 50.3 45.0 

10.3 39.0 37.9 38.4 38.5 39.4 32.1 36.7 34.1 

Males 

6 to 9 years 6 to 11 years 12 to 19 years 

787 

1,031 

737 

98.9a 

99.0a 98.2a 

69.8 69.1 62.7 

62.6 64.0 44.6 

50.8 52.4 33.2 

10.5 

9.7 

10.0 

7.4 8.1 5.9 

28.1 27.1 24.4 

52.5 52.3 41.3 

36.0 33.8 27.2 

Females 

6 to 9 years 6 to 11 years 12 to 19 years 

704 969 732 

99.7a 

99.3a 97.6a 

71.5 71.0 60.9 

61.2 59.3 45.9 

47.6 45.6 30.3 

9.0 9.4 8.6 

7.9 7.1 9.3 

26.3 27.1 19.8 

57.1 55.0 40.6 

38.3 37.1 30.9 

Males and Females 

9 years and under 19 years and under 

9,309 

11,287 

97.2 97.6 

61.6 62.4 

66.4 57.6 

47.9 41.7 

10.5 

9.9 

7.6 7.6 

25.3 24.2 

48.9 46.1 

35.3 32.5 

a 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, 1999. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 12-15
 

 

Table 12-9. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and 

Percentage of Individuals Using These Foods in Two Days 

Quantity consumed per eating occasion (grams) 

2 to 5 years 6 to 11 years 12 to 19 years 

Male and Female Male and Female Male Fema

Food category (N = 2,109) (N = 1,432) (N = 696) (N = 7

PC Mean SEM PC Mean SEM PC Mean SEM PC Mea

White bread 66.9 34 a 67.1 42 1 61.3 56 1 57.9 47 

Whole grain and wheat bread 24.3 37 1 20.5 44 1 14.5 60 2 17.6 53 

Rolls 40.0 39 1 53.5 48 1 61.9 69 2 48.8 51 

Biscuits 8.3 38 2 9.7 48 3 12.2 72 4 10.3 55 Tortillas 14.6 32 2 16.4 47 2 22.9 76 5 20.1 56 

Quickbreads and muffins 9.6 55 4 9.6 67 5 11.0 125 12 11.0 79 

Doughnuts and sweet rolls 11.3 59 2 13.4 69 2 17.3 102 12 13.8 78 

Crackers 25.4 17 1 17.2 26 2 10.6 39 5 14.2 26 

Cookies 51.0 28 1 46.7 37 2 29.0 53 3 31.8 42 

Cake 14.6 70 3 19.7 79 4 15.1 99 9 15.5 85 

Pie 2.9 76 8 5.6 116 8 6.6 188 15 4.8 138

Pancake and waffles 19.1 49 1 21.5 77 3 13.5 96 6 8.2 74 

Cooked cereal 16.8 211 10 9.0 245 14 5.2 310b 29b 6.0 256

Oatmeal 10.4 221 9 5.7 256 19 2.4 348b 45b 2.3 321

Ready-to-eat cereal 72.9 33 1 67.3 47 1 45.6 72 3 46.3 52 

Corn Flakes 11.2 33 2 13.1 42 2 10.4 62 4 8.7 49 

Toasted Oat Rings 20.6 30 1 12.5 45 2 7.3 62 5 8.1 42 

Rice 29.6 84 3 24.6 124 6 24.2 203 10 28.8 15

Pasta 49.4 90 3 41.4 130 5 33.4 203 9 37.8 15

Macaroni and cheese 17.8 159 8 13.2 217 13 7.5 408 46 10.7 26

Spaghetti with tomato sauce 16.8 242 11 11.5 322 18 10.1 583 46 8.5 47Pizza 23.7 86 3 32.8 108 6 39.6 205 13 30.5 14

Corn chips 19.6 29 2 25.6 33 2 26.9 58 5 25.1 44 

Popcorn 11.6 20 1 12.7 31 2 7.8 54 5 10.5 37 

a Indicates a SEM 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.
 


PC = Percent consuming at least once in 2 days.
 
SEM = Standard error of the mean.
 
Source: Smiciklas-Wright et al., 2002 (based on 1994-1996 CSFII data). 

Page Child-Specific Exposure Factors Handbook 

12-16 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-10. Characteristics of the FITS Sample Population 

Sample Size Percentage of Sample 

Gender 

Male 1,549 

Female 1,473 

Age of Child 

4 to 6 months 862 

7 to 8 months 483 

9 to 11 months 679 

12 to 14 months 374 

15 to 18 months 308 

19 to 24 months 316 

Child’s Ethnicity 

Hispanic or Latino 367 

Non-Hispanic or Latino 2,641 

Missing 14 

Child’s Race 

White 2,417 

Black 225 

Other 380 

Urbanicity 

Urban 1,389 

Suburban 1,014 

Rural 577 

Missing 42 

Household Income 

Under $10,000 48 

$10,000 to $14,999 48 

$15,000 to $24,999 221 

$25,000 to $34,999 359 

$35,000 to $49,999 723 

$50,000 to $74,999 588 

$75,000 to $99,999 311 

$100,000 and Over 272 

Missing 452 

Receives WIC 

Yes 821 

No 2,196 

Missing 5 

Sample Size (Unweighted) 3,022 

51.3 

48.7 

28.5 

16.0 

22.5 

12.4 

10.2 

10.4 

12.1 

87.4 

0.5 

80.0 

7.4 

12.6 

46.0 

33.6 

19.1 

1.3 

1.6 

1.6 

7.3 

11.9 

23.9 

19.5 

10.3 

9.0 

14.9 

27.2 

72.6 

0.2 

100.0 

WIC = Special Supplemental Nutrition Program for Women, Infants, and Children. 

Source: Devaney et al., 2004. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 12-17
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-11. 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 

Noninfant 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 g sugar per 100 g.
 
 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.
 


Page Child-Specific Exposure Factors Handbook 

12-18 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-12. Characteristics of WIC Participants and Nonparticipantsa (Percentages) 

(Unweighted) 

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 

Gender 

Male 55 54 55 51 57 52 

Female 45 46 45 49 43 48 

Child’s Ethnicity   **  

Hispanic or Latino 20 11 24 8 22 10 

Non-Hispanic or Latino 80 89 76 92 78 89 

Child’s Race **   

White 69 84 63 86 67 84 

Black 15 4 17 5 13 5 

Other 22 11 20 9 20 11 

Child In Day Care **  * 

Yes 39 38 34 46 43 53 

No 61 62 66 54 57 47 

Age of Mother **   

14 to 19 18 1 13 1 9 1 

20 to 24 33 13 38 11 33 14 

25 to 29 29 29 23 30 29 26 

30 to 34 9 33 15 36 18 34 

35 or Older 9 23 11 21 11 26 

Missing 2 2 1 1 0 1 

Mother’s Education **  ** ** 

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   **  

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 ** * 

Yes 46 51 45 60 55 61 

No 53 48 54 40 45 38 

Missing 1 1 1 0 0 1 

Urbanicity ** ** ** 

Urban 

Suburban 

Rural 

Missing 

Sample Size 

34 

36 

28 

2 

265 

55 

31 

13 

1 

597 

37 

31 

30 

2 

351 

50 

34 

15 

1 

808 

35 

35 

28 

2 

205 

48 

35 

16 

2 

791 

a X2 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 X2 test are listed next to the variable under the column labeled non-participants 

for each of the three age groups. *P<0.05; **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. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 12-19
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-13. 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 

Infant Cereals 69.7 62.5 74.7 69.7 13.5 9.2 

Noninfant Cereals, Total 0.9 0.5 21.7 38.5* 58.1 56.0 

Not Pre-sweetened 0.5 0.5 18.7 32.9* 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 

* = 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. 

Page Child-Specific Exposure Factors Handbook 

12-20 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-14. 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 to11 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 56.5 56.9 95.0 93.5 97.1 98.9 

Infant Cereal 55.2 56.5 74.1 73.6 15.9 9.3 

Noninfant Cereal - - 18.5* 29.2 45.3 57.8 

Breadsa 1.4† - 18.2 15.1 44.0 52.9 

Tortillas 1.4† - 4.0† - 6.7†* 0.6† 

Crackers, Pretzels, Rice Cakes 1.3† - 27.8 22.5 35.6 46.9 

Pancakes, Waffles, French Toast - - 1.4† 4.3 13.0 16.0 

Rice and Pastab - - 20.1* 10.3 44.3 32.9 

Rice - - 15.9** 4.7 26.9†* 13.0 

Grains in Mixed Dishes - - 15.9 13.0 38.8* 54.4 

Sandwiches - - 4.0† 4.6 24.2 24.9 

Burrito, Taco, Enchilada, Nachos - - 1.3† - 2.1† 3.0 

Macaroni and Cheese - - 3.0† 3.1 10.1 15.5 

Pizza - - - 1.4 1.0**† 9.7 

Spaghetti, Ravioli, Lasagna - - 8.3† 4.6 9.3† 12.1 a Does not include bread in sandwiches. Sandwiches are included in mixed dishes. Includes tortillas, also shown separately. b 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. 

- = Less than 1 percent of the group consumed this food on a given day. 

* = Significantly different from non-Hispanic at the P<0.05. 

** = Significantly different from non-Hispanic at the P>0.01. 

† = Statistic is potentially unreliable because of a high coefficient of variation. 

Source: Mennella et al., 2006. 

Child-Specific Exposure Factors Handbook Page
 


September 2008 12-21
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-15. Average Portion Sizes Per Eating Occasion of Grain Products 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) 

9 to 11 months 

(N=687) 

Mean± SEM 

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 

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. 

SEM = Standard error of the mean. 

Source: Fox et al., 2006. 

Table 12-16. Average Portion Sizes Per Eating Occasion of Grain Products Commonly Consumed by
 

Toddlers from the 2002 Feeding Infants and Toddlers Study
 

12 to 14 months 15 to 18 months 19 to 24 months 

Food Group Reference Unit (N=371) (N=312) (N=320) 

Mean± SEM 

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 

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. 

SEM = Standard error of the mean. 

Source: Fox et al., 2006. 

Page Child-Specific Exposure Factors Handbook 

12-22 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12-17. Mean Moisture Content of Selected Grain Products Expressed as 

Percentages of Edible Portions
 

Food 

Raw 

Moisture Content 

Cooked 

Comments 

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 

Source: USDA, 2007. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 12-23
 
 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

APPENDIX 12A
 


CODES AND DEFINITIONS USED TO DETERMINE THE VARIOUS GRAIN
 


PRODUCTS USED IN THE U.S. EPA ANALYSIS OF CSFII DATA IN FCID
 


Child-Specific Exposure Factors Handbook Page
 


September 2008 12A-1
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Table 12A-1. Food Codes and Definitions Used in Analysis of the 1994-96, 1998 USDA CSFII Data 

Total Grains 95000060 

15000250 

15000251 

15000260 

15000261 

15000270 

15000650 

15000660 

15001200 

15001201 

15001210 

15001211 

15001220 

15001230 

15001231 

15001260 

15001270 

15001271 

15002260 

15002310 

15002320 

15002321 

15002330 

Amaranth, grain 

Barley, pearled barley 

Barley, pearled barley-babyfood 

Barley, flour 

Barley, flour-babyfood 

Barley, bran 

Buckwheat 

Buckwheat, flour 

Corn, field, flour 

Corn, field, flour-babyfood 

Corn, field, meal 

Corn, field, meal-babyfood 

Corn, field, bran 

Corn, field, starch 

Corn, field, starch-babyfood 

Corn, pop 

Corn, sweet 

Corn, sweet-babyfood 

Millet, grain 

Oat, bran 

Oat, flour 

Oat, flour-babyfood 

Oat, groats/rolled oats 

15002331 

95003060 

95003110 

15003230 

15003231 

15003240 

15003241 

15003250 

15003251 

15003260 

15003261 

15003280 

15003290 

15003440 

15003810 

15003811 

15004010 

15004011 

15004020 

15004021 

15004030 

15004040 

15004050 

Oat, groats/rolled oats-babyfood 

Psyllium, seed 

Quinoa, grain 

Rice, white 

Rice, white-babyfood 

Rice, brown 

Rice, brown-babyfood 

Rice, flour 

Rice, flour-babyfood 

Rice, bran 

Rice, bran-babyfood 

Rye, grain 

Rye, flour 

Sorghum, grain 

Triticale, flour 

Triticale, flour-babyfood 

Wheat, grain 

Wheat, grain-babyfood 

Wheat, flour 

Wheat, flour-babyfood 

Wheat, germ 

Wheat, bran 

Wild rice 

Cereal Grains 15000250 

15000251 

15000260 

15000261 

15000270 

15000650 

15000660 

15001200 

15001201 

15001210 

15001211 

15001220 

15001230 

15001231 

15001240 

15001241 

15001260 

15001270 

15001271 

15002260 

15002310 

15002320 

15002321 

15002330 

15002331 

Barley, pearled barley 

Barley, pearled barley-babyfood 

Barley, flour 

Barley, flour-babyfood 

Barley, bran 

Buckwheat 

Buckwheat, flour 

Corn, field, flour 

Corn, field, flour-babyfood 

Corn, field, meal 

Corn, field, meal-babyfood 

Corn, field, bran 

Corn, field, starch 

Corn, field, starch-babyfood 

Corn, field, syrup 

Corn, field, syrup-babyfood 

Corn, pop 

Corn, sweet 

Corn, sweet-babyfood 

Millet, grain 

Oat, bran 

Oat, flour 

Oat, flour-babyfood 

Oat, groats/rolled oats 

Oat, groats/rolled oats-babyfood 

15003230 

15003231 

15003240 

15003241 

15003250 

15003251 

15003260 

15003261 

15003280 

15003290 

15003440 

15003450 

15003810 

15003811 

15004010 

15004011 

15004020 

15004021 

15004030 

15004040 

15004050 

95000060 

95003060 

95003110 

Rice, white 

Rice, white-babyfood 

Rice, brown 

Rice, brown-babyfood 

Rice, flour 

Rice, flour-babyfood 

Rice, bran 

Rice, bran-babyfood 

Rye, grain 

Rye, flour 

Sorghum, grain 

Sorghum, syrup 

Triticale, flour 

Triticale, flour-babyfood 

Wheat, grain 

Wheat, grain-babyfood 

Wheat, flour 

Wheat, flour-babyfood 

Wheat, germ 

Wheat, bran 

Wild rice 

Amaranth, grain 

Psyllium, seed 

Quinoa, grain 

Page Child-Specific Exposure Factors Handbook 

12A-2 September 2008 
 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 12 - Intake of Grain Products 

Rice 15003260 Rice, bran 15003250 Rice, flour 

15003261 

15003240 

Rice, bran-babyfood 

Rice, brown 

15003251 

15003230 

Rice, flour-babyfood 

Rice, white 

15003241 Rice, brown-babyfood 15003231 Rice, white-babyfood 

Child-Specific Exposure Factors Handbook Page
 


September 2008 12A-3
 

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

13 INTAKE OF  HOME­PRODUCED          

FOODS

13.1 INTRODUCTION

Ingestion of home­produced  foods can be a

pathway for exposure to environmental contaminants.

Home­produced foods can become contaminated in a

variety of 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 may also 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 homeproduced foods, may be potentially exposed if these

foods become contaminated. Exposure via the

consumption of home­produced foods may be a

significantroute of exposure forthese populations(U.S.

EPA, 1989; U.S. EPA, 1996). For example,

consumption of home­produced fruits, vegetables,

game, and fish has been shown to have an impact on

blood lead levelsin areas where soil lead contamination

exists (U.S. EPA, 1994).  At Superfund sites where soil

contamination is found, ingestion of home­produced

foods has been considered a potential route of exposure

(U.S. EPA, 1991; U.S. EPA, 1993). Assessing

exposuresto individuals who consume home­produced

foodsrequires knowledge of intake rates ofsuch foods.

Data from the 1987­1988 Nationwide Food

Consumption Survey (NFCS) were used to generate

intake rates for home­produced foods (U.S. EPA,

1997).  Until 1988, USDA conducted the NFCS every

10 yearsto 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

among 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 home­produced foods.  Thus,

the 1987­1988 NFCS data set is currently the best

available source of information for this factor.

The 1987­1988NFCS was conducted between

April 1987 and August 1988.    The survey used a

statisticalsampling technique designed to ensure that all

seasons, geographic regions of the 48 conterminous

statesin the U.S., and socioeconomic and demographic

groups were represented (USDA, 1994).  There were

two components of the NFCS.    The household

component collected information over a seven­day

period on the socioeconomic and demographic

characteristics of households, and the types, amount,

value, and sources of foods consumed by the household

(USDA, 1994).    The individual intake component

collected information on food intakes of individuals

within each household over a three­day period (USDA,

1993).  The sample size for the 1987­1988 survey was

approximately 4,300 households (over 10,000

individuals; approximately 3,000 children).  This was

a decrease over the previoussurvey conducted in 1977­

1978,which sampled approximately 15,000 households

(over 36,000 individuals) (USDA, 1994).  The sample

size was lower in the 1987­1988 survey as a result of

budgetary constraints and low response rate (38 percent

for the household survey and 31percent for the

individual survey) (USDA, 1993). The methods used

to analyze the 1987­1988 NFCS data and the results of

these analyses that pertain to children are presented in

Section 13.3.

13.2 RECOMMENDATIONS

The data presented in thissection may be used

to assess exposure to contaminants in foods grown,

raised, or caught at a specific site. The recommended

values for and mean upper percentile (i.e., 95th

percentile)intake rates among consumers ofthe various

home­produced food groups are presented in Table 13­

1; these rates can be converted to per capita rates by

multiplying by the fraction ofthe population consuming

these food groups during the survey period (See Section

13.3).  Table 13­2 presents the confidence ratings for

home­produced food intake.  The data presented in this

chapter for consumers of home­produced foods

represent average daily intake rates of food

items/groups over the seven­day survey period and do

not account for variations in eating habits during the

rest of the year; thusthe recommended upper percentile

values, as well as the percentiles of the distributions

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

presented in Section 13.3 may not necessarily reflect

the long­term distribution of average daily intake of

home produced foods.

Because the home­produced food intake rates

presented in this chapter 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

to intake rates to those that are representative of foods

“as consumed”. Additional conversions may be

necessary 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 home­produced foods are over 20 years old and may

not be reflective of current eating patterns among

consumers of home­produced foods. Although USDA

and others have conducted other food consumption

studies since the release of the 1987­1988 NFCS, these

studies do not include information on home­produced

foods.

Recommended home­produced food intake

rates are not provided for children under 1 year of age

because the methodology used is based on

apportionment of home­produced foods used by a

household among the members of that household that

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 home­produced

food brought into the home. Also,recommended homeproduced food intake rates are not provided for

individual food items for children because, in general,

the sample size was too small to provide reliable data

for individual age groups. However, if intake rates are

needed for age groups under 1 year of age or for food

items other than the major food groups presented here,

data in Section 13.3 on the fraction of household intake

that is home­produced may be used in conjunction with

age­specific intake rates presented elsewhere in this

handbook to estimate intake of home produced foods

(U.S. EPA, 1997).

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13­2 September 2008
 
                        

           

         

         

         

         

           

         

         

         

         

           

         

         

         

         

   

           

         

         

         

         

                             

             

                         

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13­1. Summary of Recommended Values for Intake of Home­produced Foods (Consumers Only)

Age Groupa

Mean 95th Percentile Multiple

Percentiles Source

g/kg­day

Home­produced Fruits

1 to 2 years

3 to 5 years

6 to 11 years

12 to 19 years

8.7

4.1

3.6

1.9

60.6

8.9

15.8

8.3

See Table 13­4 U.S. EPA Analysis of

1987­1988 NFCS

Home­produced Vegetables

1 to 2 years

3 to 5 years

6 to 11 years

12 to 19 years

5.2

2.5

2.0

1.5

19.6

7.7

6.2

6.0

See Table 13­4 U.S. EPA Analysis of

1987­1988 NFCS

Home­produced Meats

1 to 2 years

3 to 5 years

6 to 11 years

12 to 19 years

3.7

3.6

3.7

1.7

10.0

9.1

14.0

4.3

See Table 13­4 U.S. EPA Analysis of

1987­1988 NFCS

Home Caught Fish

1 to 2 years

3 to 5 years

6 to 11 years

12 to 19 years

­

b

­

2.8

1.5

­

­

7.1

4.7

See Table 13­4 U.S. EPA Analysis of

1987­1988 NFCS

a

b

Analysis was conducted priorto Agency’sissuance of Guidance on Selecting Age Groupsfor Monitoring and

Assessing Childhood Exposures to Environmental Contaminants (U.S. EPA, 2005).

Data not presented for age groups/food groups where less than 20 observations were available.

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13­2. Confidence in Recommendations for Intake of Home­produced Foods

General Assessment Factors Rationale Rating

Soundness

Adequacy of Approach

Minimal (or Defined) Bias

The 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

3,000 children).

Non­response bias can not 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 analysis specifically addressed

home­produced intake.

Data from a nationwide survey,

representative of the general U.S.

population was used.

The data were collected in 1987­1988.

Household data were collected over 1

week.

Low (Means & Short­term distributions)

Low (Long­term distributions)

Clarity and Completeness

Accessibility

Reproducibility

Quality Assurance

The methods used described to analyze

the data are described in detail in this

handbook; the primary data are

accessible through USDA.

Sufficient detail on the methods used to

analyze the data are presented to allow

for the results to be reproduced.

Quality assurance of NFCS data was

good; quality control of the secondary

data was sufficient.

High

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13­2. Confidence in Recommendations for Intake of Home­produced Food (continued)

General Assessment Factors Rationale Rating

Variability and Uncertainty

Variability in Population

Uncertainty

Full distributions of home­produced

intake rates were provided.

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 U.S. EPA.

The number of studies is 1.

Medium

Overall Rating Low­Medium (means and short­term

distributions)

Low (long­term distributions)

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

13.3 KEY STUDY FOR INTAKE OF HOMEPRODUCED FOODS

13.3.1 U.S. EPA Analysis of NFCS 1987­1988

U.S.EPA’sNationalCenterforEnvironmental

Assessment (NCEA) analyzed USDA's 1987­1988

NFCS data to generate intake rates for home­produced

foods(U.S. EPA, 1997). For the purposes of thisstudy,

home­produced foods were defined as homegrown

fruits and vegetables, meat and dairy products derived

from consumer­raised livestock or game meat, and

home caught fish. The food groups selected for

analysis of children’s home­produced food intake

included major food groups such as total fruits, total

vegetables, total meats, total dairy, total fish and

shellfish. These food groups were identified in the

NFCS data base according to NFCS­defined food

codes. Appendix 13A presents the codes and

definitions used to determine these major food groups.

Foods with these codes, for which the source was

identified as home­produced, were included in the

analysis. This chapter presents the intake rate data for

these major food groups, except total dairy, for various

age ranges of children. An insufficient number of

observations (i.e., less than 30 households) were

available to allowfor estimates of home­produced dairy

products. Also, child­specific intake rates for

individual food items (e.g., carrots, citrus fruit) were

not estimated because, in general, the sample size was

too small to provide reliable data for the individual age

groups of interest.

The USDA data were adjusted by applying the

sample weights calculated by USDA to the data set

prior to analysis. The USDA sample weights were

designed to “adjust for survey non­response and other

vagaries of the sample selection process” (USDA,

1987­1988). 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, 1987­1988). The unweighted

it could not be used directly to measure consumption of

home­produced food because the individual component

does not identify the source of the food item (i.e., as

home­produced or not). Therefore, an analytical

method which incorporated data from both the

household and individual survey components was

developed to estimate individual home­produced food

intake. The USDA household data were used to

determine (1) the amount of each home­produced food

item used during a week by household members and (2)

the number of meals eaten in the household by each

household member during a week. 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, etc. 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 age­specific serving sizesfor

each food item. These serving sizes were used during

subsequent analyses to generate home­produced food

intake rates for individual household members.

Assuming that the proportion of the household quantity

of each home­produced 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 home­produced food were calculated for all

members of the survey population using the following

general equation:


   mi

qi 

w = w
  n  (Eqn. 13­1) i f 
 ∑ mi

qi 
  i=1 

where:

 

sample included approximately 3,000 children (ages <1

to 19 years), which was weighted to reflect nearly 54

million children.

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,

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

wi = Home­produced amount of food

item/group attributed to member i

during the week (g/week);

wf = Total quantity of home­produced

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 home­produced food group

was determined by dividing the weekly value (wi

) by

seven. Intake rates were indexed to the self­reported

body weight of the survey respondent and reported in

units of g/kg­day. For the major food groups (fruits,

vegetables, meats, and fish), distributions of homeproduced intake among consumers were generated by

age group. Consumers were defined as members of

survey households who reported consumption of the

food group of interest during the one week survey

period.

The age categories used in the analysis were as

follows: 1 to 2 years; 3 to 5 years; 6 to 11 years; and 12

to 19 years Because this analysis was conducted prior

to issuance of U.S. EPA’s Guidance on Selecting Age

Groups for Monitoring and Assessing Childhood

Exposuresto Environmental Contaminants(U.S. EPA,

2005), the age groups used are not entirely consistent

with recent guidelines. Intake rates were not calculated

for children under 1 year because their diet differs

markedly from that of other household members, and

thus, the assumption that all household members share

all foods would be invalid for this age group.

The intake data presented here for consumers

of home­produced foods and the total number of

individualssurveyed may be used to calculate the mean

and the percentiles of the distribution of homeproduced food consumption in the overall population

(consumers and non­consumers) as follows:

Assuming thatIRp isthe home­produced intake

rate of the food group at the pth percentile and Nc is the

weighted number of individuals consuming the homeproduced 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 x Nc) individuals below the pth percentile.

Therefore, the percentile that corresponds to a

particular intake rate (IRp)forthe overall distribution of

home­produced food consumption (including

consumers and non­consumers) can be obtained by:

 P   x Nc + (NT − Nc )

th  100  (Eqn. 13­2) P = 100 x overall NT

Table 13­3 displaysthe weighted numbers NT,

as well as the unweighted total survey sample sizes, for

each age category. Table 13­4 presents homeproduced intake rates for fruits, vegetables, meats, and

fish. These intake rates are based on the amount of

household food consumption as well as age­specific

serving size data.

USDAestimated preparation lossesfor various

foods (USDA, 1975). For meats, a net cooking loss,

which includes dripping and volatile losses, and a net

post­cooking loss, which involves losses from cutting,

bones, excess fat, scraps and juices, were derived for a

variety of cuts and cooking methods. For total meats,

U.S. EPA has averaged these losses across all meat

types, cuts and cooking methods to obtain a mean net

cooking loss and a mean net post­cooking loss. Mean

percentage values for all meats and fish are provided in

Table 13­5. For individual fruits and vegetables,

USDA (1975) also gave cooking and post­cooking

losses. These data, averaged across all types of fruits

and vegetables to give mean net cooking and post

cooking losses, are also provided in Table 13­5.

The following formula can be used to convert

the home­produced intake rates tabulated here to rates

reflecting actual consumption:

I = I × (1­ L ) × (1− L ) (Eqn. 13­3) A 1 2

where:

IA = the adjusted intake rate;

I = the tabulated intake rate;

L1 = the cooking or preparation loss; and

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

L2 = the post­cooking loss.

For fruits, corrections based on post­cooking

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 removal of skin, peel, core, caps, pits,

stems, and defects, or draining of liquids from canned

or frozen forms.

In calculating ingestion exposure, assessors

should use consistent forms(e.g., “as­consumed” or dry

weight) in combining intake rates with contaminant

concentrations, as discussed in Chapter 9 of this

handbook.

The USDA 1987­1988 NFCS household data

were also used to estimate the fraction of household

intake that can be attributed to home­produced foods

(Table 13­6). The analysis was conducted for the major

food groups (i.e., total meat, dairy, fruits, vegetables,

and fish), as well as for a variety of individual food

items (e.g., apples, tomatoes, beef, etc.). The fraction

of intake that was home­produced was calculated asthe

ratio of total intake of the home­produced food

item/group by the survey population to the total intake

of all forms of the food by the survey population. The

food codes used in this analysis are presented in

Appendix 13­B.

The USDA NFCS data set is the largest

publicly available source of information on homeproduced food consumption habitsin the United States.

The advantages of using this data set are that it is

expected to be representative ofthe 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 short­term dietary recall and the

intake distributions generated fromthis data set may not

accurately reflect long­term intake patterns, particularly

with respect to 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 here may

also be biased by assumptions that are inherent in the

analytical method utilized. The analytical method may

not capture all high­end consumers within households

because average serving sizes are used in calculating

the proportion of home­produced food consumed by

each household member. Thus, for instance, in a twoperson household where one member had high intake

and one had low intake, the method used here 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 homeproduced food used within the household. However,

not all family members may consume each homeproduced food item and serving sizes allocated here

may not be entirely representative of the portion of

household foods consumed by each familymember. As

was mentioned earlier, no analyses were performed for

children under 1 year age.

The preparation loss factors discussed above

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, etc. It should also be noted that because

this analysis is based on the 1987­1988 NFCS, it may

notreflectrecent changesin food consumption patterns.

The low response rate associated with the 1987­1988

NFCS also contributes to the uncertainty of the homeproduced intake rates generated using these data.

13.4 REFERENCES FOR CHAPTER 13

USDA (1975) Food yields summarized by different

stages of preparation. Agricultural Handbook

No. 102. Washington, DC. U.S. Department

of Agriculture, Agriculture Research Service.

USDA (1987­1988) Dataset: Nationwide Food

Consumption Survey 1987/88 Household

Food Use. Washington, DC. U.S.

Department of Agriculture. 1987/88 NFCS

Database.

USDA (1992) Changes in food consumption and

expenditures in American households during

the 1980's. Washington, DC. U.S.

Department of Agriculture. Statistical

Bulletin No. 849.

USDA (1993) Food and nutrient intakes by individuals

in the United States, 1 Day, 1987­1988.

Nationwide Food Consumption Survey 1987­

1988, NFCS Report No. 87­I­1.

Page Child­Specific Exposure Factors Handbook
 

13­8 September 2008
 
              

         

       

        

             

         

           

       

     

                 

                 

              

         

             

   

     

              

     

            

     

        

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

USDA (1994) Food consumption and dietary levels of

households in the United States, 1987­1988.

U.S. Department of Agriculture, Agricultural

Research Service. Report No. 87­H­1.

U.S. EPA (1989) Risk Assessment Guidance for

Superfund (RAGS): Volume I, Human Health

Evaluation Manual, Part A. Office of Solid

Waste andEmergency Response,Washington,

DC. EPA/540/1­89/002. Available online at

http://www.epa.gov/oswer/riskassessment/ra

gsa/index.htm

U.S.	 EPA (1991) Record of Decision. ROD ID

EPA/ROD/R10­91­029.

U.S.	 EPA (1993) Record of Decision. ROD ID

EPA/ROD/R04­93­166.

U.S. EPA (1994) Validation strategy for the Integrated

Exposure Uptake Biokinetic Model for Lead

in Children. Office of Solid Waste and

Emergency Response, Washington DC.

EPA/540/R­94­039. Available online at

http://www.epa.gov/superfund/lead/products

/valstrat.pdf

U.S. EPA (1996) Soil Screening Fact Sheet Guidance.

EPA/540/F­95/041. Available online at

http://www.epa.gov/superfund/health/conme

dia/soil/index.htm

U.S. EPA (1997) Exposure Factors Handbook. Office

of Research and Development, Washington,

DC. EPA/600/P­95/002F. Available online at

http://cfpub.epa.gov/ncea/cfm/recordisplay.c

fm?deid=12464

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September 2008 13­9
 
Table 13­3. Weighted and Unweighted Number of Observations (Individuals)

Child­specific Analysis of Food Intake

for NFCS Data Used in

Age Group

Number of Observations

weighted unweighted

<1 year 2,814,000 156

1 to 2 years 5,699,000 321

3 to 5 years 8,103,000 461

6 to 11 years 16,711,000 937

12 to 19 years 20,488,000 1,084

Total 53,815,000 2,959

weighted

unweighted

=

=

Weighted number of

Unweighted number

observations.

of observations.

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Page Child­Specific Exposure Factors Handbook
 

13­10 September 2008
 
Table 13­4. Consumer Only Intake of Home­produced Foods (g/kg­day)a

Nc Nc %

Age wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100

(years)

Home­produced Fruits

 

 1 to 2 360,000 23 6.3 8.7 3.1 1.0 1.1 1.3 1.6 3.5 8.0 19.3 60.6 60.6 60.6 3 to 5 550,000 34 6.8 4.1 1.5 0.0 0.0 0.4 1.0 1.9 2.7 6.0 8.91 48.3 48.3 6 to 11 1,044,000 75 6.3 3.6 0.7 0.0 0.2 0.4 0.7 1.3 3.1 11.8 15.8 32.2 32.2 12 to 19 1,189,000 67 5.8 1.9 0.4 0.1 0.1 0.3 0.4 0.7 2.4 6.8 8.3 18.5 18.5

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Home­produced Vegetables

 

 

 

 

1 to 2 951,000 53 16.7 5.2 0.9 0.0 0.2 0.4 1.2 3.3 5.8 13.1 19.6 27.0 27.0 3 to 5 1,235,000 76 15.2 2.5 0.3 0.0 0.1 0.4 0.7 1.3 3.9 6.4 7.7 10.6 12.8 6 to 11 3,024,000 171 18.1 2.0 0.3 0.0 0.1 0.2 0.4 0.9 2.2 4.6 6.2 17.6 23.6 12

 

to 19 3,293,000 183 16.1 1.5 0.1 0.0 0.1 0.1 0.3 0.8 1.8 3.7 6.0 7.7 9.0

 

 

 

 

 

 

 

 

 

 

 

 

Home­produced Meats

 

 

 

 

 1 to 2 276,000 22 4.8 3.7 0.6 0.4 1.0 1.0 1.2 2.7 4.7 8.7 10.0 11.5 11.5 3 to 5 396,000 26 4.9 3.6 0.5 0.8 0.8 1.5 2.2 2.8 3.7 7.8 9.1 13.0 13.0 6 to 11 1,064,000 65 6.4 3.7 0.5 0.4 0.7 0.7 1.3 2.1 4.7 8.0 14.0 15.3 15.3 12

 

to 19 1,272,000 78 6.2 1.7 0.2 0.2 0.3 0.5 0.6 1.2 2.4 3.7 4.3 6.8 7.5

 

 

 

 

 

 

 

 

 

 

Home­caught Fish

 

 

 

 

 

 

 

 

1 to 2 82,000 6 1.4 * * * * * * * * * * * *

 

3 to 5 142,000 11 1.8 * * * * * * * * * * * *6 to 11 382,000 29 2.3 2.8 0.8 0.2 0.2 0.2 0.2 0.6 1.0 3.7 7.1 7.9 25.3

12 to 19 346,000 21 1.7 1.5 0.4 0.2 0.2 0.2 0.2 0.3 1.0 1.8 4.7 6.7 8.4

 

 

 

 

 

 

 

 

 

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).

SE = Standard error.

P = Percentile of the distribution.

Nc wgtd = Weighted number of consumers.

Nc unwgtd= Unweighted number of consumers in survey.

* = Less than 20 observations.

Source: Based on U.S. EPA's analyses of the 1987­1988 NFCS.

 

 

Child­Specific Exposure Factors Handbook

Chapter 13­ Intake of Home­Produced Foods

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September 2008 13­11
 
     

         

Table 13­5.     Percent Weight Losses from Food Preparation

Food Group Mean Net Preparation/Cooking Loss (%) Mean Net Post Cooking (%)

Meatsa

Fish and shellfishd

Fruits

g Vegetables

29.7b

31.5b

25.4e

12.4h

29.7c

10.5c

30.5f

22i

a

b

c

d

e

f

g

h

i

Source:

Averaged over various cuts and preparation methods for various meats including beef, pork, chicken, turkey,

lamb, and veal.

Includes dripping and volatile losses during cooking.

Includes losses from cutting, shrinkage, excess fat, bones, scraps, and juices.

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.

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.

Averaged over apples and peaches.     Include losses from draining cooked forms.

Averaged over various vegetables, to include: asparagus, beets, broccoli, cabbage, carrots, corn, cucumbers,

lettuce, lima beans, okra, onions, green peas, peppers, pumpkins, snap beams, tomatoes, and potatoes.

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.

Includes losses from draining or removal of skin. Based on potatoes only.

U.S. EPA, 1997 (Derived from USDA, 1975).

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Page Child­Specific Exposure Factors Handbook
 

13­12 September 2008
 
               

   

   

   

   

   

     

   

       

   

   

   

   

   

   

   

   

   

     

   

   

   

   

   

     

   

         

   

   

     

   

   

   

   

     

         

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13­6. Fraction of Food Intake that is Home­produced

All Households Households who

garden

Households who farm

Total Fruits

Apples

Peaches

Pears

Strawberries

Other Berries

Citrus

Other

0.04

0.030

0.147

0.067

0.111

0.217

0.038

0.042

0.101

0.070

0.316

0.169

0.232

0.306

0.087

0.107

0.161

0.292

0.461

0.606

0.057

0.548

0.005

0.227

All Households Households who

garden

Households who farm

Total Vegetables

Asparagus

Beets

Broccoli

Cabbage

Carrots

Corn

Cucumbers

Lettuce

Lima Beans

Okra

Onions

Peas

Peppers

Pumpkin

Snap Beans

Tomatoes

White Potatoes

0.068

0.063

0.203

0.015

0.038

0.043

0.078

0.148

0.010

0.121

0.270

0.056

0.069

0.107

0.155

0.155

0.184

0.038

0.173

0.125

0.420

0.043

0.099

0.103

0.220

0.349

0.031

0.258

0.618

0.148

0.193

0.246

0.230

0.384

0.398

0.090

0.308

0.432

0.316

0.159

0.219

0.185

0.524

0.524

0.063

0.103

0.821

0.361

0.308

0.564

0.824

0.623

0.616

0.134

All Households Households who

raise animals/hunt Households who farm

Total Meats

Beef

Game

Pork

Poultry

0.024

0.038

0.276

0.013

0.011

0.306

0.485

0.729

0.242

0.156

0.319

0.478

­

0.239

0.151

All Households Households who

raise animals Households who farm

Total Dairy

Eggs

0.012

0.014

0.207

0.146

0.254

0.214

All Households Households who

fish ­­

Total fish 0.094 0.325 ­­

­ = No data.

Source: U.S. EPA Analysis of 1987­1988 NFCS.

Child­Specific Exposure Factors Handbook Page
 

September 2008 13­13
 
           

                 

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

APPENDIX 13A
 

FOOD CODES AND DEFINITIONS USED IN CHILD­SPECIFIC ANALYSIS
 

OF THE 1987­1988 USDA NFCS DATA TO ESTIMATE HOME­PRODUCED INTAKE RATES
 

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13A­1. Food Codes and Definitions Used in Child­specific Analysis of the 1987­1988 USDA NFCS Data

to Estimate Intake of Home­produced Foods

Food Product Household Code/Definitiona Individual Code

MAJOR FOOD GROUPS

Total Fruits 50­ Fresh Fruits

citrus

other vitamin­C 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 readyto­eat dinners; includes baby foods except mixtures/dinners)

7­ Vegetables (all forms)

white potatoes & PR 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 readyto­eat 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 non­meat

items; frozen plate meals; soups and gravies with

meat, poultry and fish base; and gelatin­based drinks;

includes baby foods)

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13A­1. Food Codes and Definitions Used in Child­specific Analysis of the 1987­1988 USDA NFCS Data

to Estimate Intake of Home­produced Foods (continued)

Food Product Household Code/Definition1 Individual Code

MAJOR FOOD GROUPS

Total Dairy 40­ Milk Equivalent

fresh fluid milk

processed milk

cream and cream substitutes

frozen desserts with milk

cheese

dairy­based dips

(does not include soups, sauces, gravies, mixtures, and readyto­eat 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, milk­based meal replacements,

and infant formulas)

Total Fish 452­ Fish, Shellfish

various species

fresh, frozen, commercial, dried

(does not include soups, sauces, gravies, mixtures, and readyto­eat dinners)

26­ Fish, Shellfish

various species and forms

(excludes meat, poultry, and fish with non­meat

items; frozen plate meals; soups and gravies with

meat, poultry and fish base; and gelatin­based drinks) a Food items within these categories that were identified by the household as being home­produced or home­caught (i.e., source code pertaining to home

produced foods) were included in the analysis.

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September 2008 13A­3
 
     

         

               

         

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

APPENDIX 13B

1987­1988 NFCS FOOD CODES AND DEFINITIONS USED IN ESTIMATING FRACTION OF

HOUSEHOLD FOOD INTAKE THAT IS HOME­PRODUCED

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13B­1. Food Codes and Definitions Used in Analysis of the 1987­1988 USDA NFCS Household Data to

Estimate Fraction of Food Intake that is Home­produced

Food Product

Household Code/Definition

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 ready­to­eat dinners)

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 ready­to­eat dinners)

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 ready­to­eat dinners)

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 ready­to­eat dinners; includes baby food)e

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13B­1. Food Codes and Definitions Used in Analysis of the 1987­1988 USDA NFCS Household Data to

Estimate Fraction of Food Intake that is Home­produced (continued)

Food Product

Household Code/Definition

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)

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 ready­to­eat dinners)

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 ready­to­eat dinners; includes baby foods)

Beef 441­ Beef

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except mixtures)

Pork 442­ Pork

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except mixtures)

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13B­1. Food Codes and Definitions Used in Analysis of the 1987­1988 USDA NFCS Household Data to Estimate Fraction

of Food Intake that is Home­produced (continued)

Food Product Household Code/Definition

Game 445­ Variety Meat, Game

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except mixtures)

Poultry 451­ Poultry

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except mixtures)

Eggs 46­ Eggs (fresh equivalent)

fresh

processed eggs, substitutes

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except mixtures)

Broccoli 4912­ Fresh Broccoli (and home canned/froz.)

5111203 Broccoli, comm. canned

52112­ Comm. Frozen Broccoli

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except 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 ready­to­eat dinners; 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 ready­to­eat dinners; includes baby

foods except mixtures)

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 ready­to­eat dinners; includes baby

foods except 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 ready­to­eat dinners; includes baby

foods except mixtures; does not include succotash)

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Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

Table 13B­1. Food Codes and Definitions Used in Analysis of the 1987­1988 USDA NFCS Household Data to

Estimate Fraction of Food Intake that is Home­produced (continued)

Food Product

Household Code/Definition

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 ready­to­eat dinners; includes baby

foods except mixtures)

Lettuce 4945­ Fresh Lettuce, French Endive (and home canned/froz.)

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except 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 ready­to­eat dinners; includes baby

foods except mixtures)

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. Blackeye, 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 ready­to­eat dinners; includes baby

foods except mixtures)

Cucumbers 4952­ Fresh Cucumbers (and home canned/froz.)

(does not include soups, sauces, gravies, mixtures, and ready­to­eat dinners; includes baby

foods except 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 ready­to­eat dinners; 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 ready­to­eat dinners; includes baby foods except mixtures)

Child­Specific Exposure Factors Handbook Page
 

September 2008 13B­5
 
     

         

Table 13B­1.     Food Codes and

Estimate

Definitions

Fraction of

Used

Food

in Analysis of the 1987­1988

Intake that is Home­produced

USDA NFCS

(continued)

Household Data to

Food Product

Household Code/Definition

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 Cranberry­Orange Relish

52233­ Comm. Frozen Berries (not strawberries)

5332404 Blackberry Juice (home and comm. canned)

5423114 Dried Berries (not strawberries)

(does not include ready­to­eat dinners; includes baby foods 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 ready­to­eat dinners; includes baby foods 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 ready­to­eat dinners; includes baby foods except mixtures)

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

5361 Fresh Citrus and Citrus Blend Juice

(includes baby foods; excludes dried fruits)

Juice

Other

Fruits

502­ Fresh Other Vitamin C­Rich Fruits

503­ Fresh Other Fruits

5122­ Comm. Canned Fruits Other than Citrus

5222­ Frozen Strawberries

5332­ Frozen Other than Citr. or Vitamin C­Rich Fr.

5333­ Canned Fruit Juice Other than Citrus

5352­ Frozen Juices Other than Citrus

5362­      Aseptically Packed Fruit Juice Other than Citr.

542­ Fresh Fruit Juice Other than Citrus Dry Fruits

(includes baby foods; excludes dried fruits)

Child­Specific Exposure Factors Handbook

Chapter 13 ­ Intake of Home­Produced Foods

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Child-Specific Exposure Factors Handbook 

Chapter 14 - Total Food Intake 

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 

among children. To assess chemical exposure through 

this pathway, information on food ingestion rates is 

needed. Per capita and consumers only data on food 

consumption rates for various food items and food 

categories are reported in Chapters 9 through 13 of this 

handbook. These intake rates were estimated by U.S. 

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, 1998, 

U.S. EPA (2007) derived distributions to characterize 

(1) 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). 

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 key study on total 

food intake is summarized. 

14.2 RECOMMENDATIONS 

A summary of recommended values for total 

food intake, on an as-consumed basis, is presented in 

Table 14-1. The confidence ratings for these 

recommendations are presented in Table 14-2. The 

recommended intake rates for children are based on 

data from the U.S. EPA (2007) analysis of CSFII data. 

However, 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 

entirely consistent with the age groups recommended in 

the 2005 guidance. Therefore, a re-analysis of the data 

was conducted to conform with U.S. EPA’s 

recommended age groups for children. 

Because these recommendations are based on 

1994-96 and 1998 CSFII data, they may not reflect 

recent changes that may have occurred in consumption 

patterns. In addition, these distributions 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, for the broad categories of 

foods used in this analysis (e.g., total foods, total fruits, 

total vegetables, etc.), because they 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. 

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Child-Specific Exposure Factors Handbook 

Chapter 14 - Total Food Intake 

Table 14-1. Recommended Values for Per Capita Total Food Intake, As Consumed 

Age Group 

Mean 95th Percentile Multiple 

Percentiles Source 

g/kg-day 

Birth to <1 month 20 61 

See Table 14-3 

U.S. EPA re-analysis of 

CSFII 1994-96, 98 data 

(Based on U.S. EPA, 

2007) 

1 to <3 months 16 40 

3 to <6 months 28 65 

6 to <12 months 56 134 

1 to <2 years 90 161 

2 to <3 years 74 126 

3 to <6 years 61 102 

6 to <11 years 40 70 

11 to <16 years 24 45 

16 to <21 years 18 35 

Note: 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. 

Page Child-Specific Exposure Factors Handbook 

14-2 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 14 - Total Food Intake 

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 methodology was adequate and the analytical 

approach was competently executed. The study size was very 

large; sample size varied with age. The response rate was 

good. The key study analyzed primary data on recall of 

ingestion. 

No direct measurements were taken. The study relied on 

survey data. 

High 

Applicability and Utility 

Exposure Factor of Interest 

Representativeness 

Currency 

Data Collection Period 

The analysis was specifically designed to address food intake. 

The population studied was 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. 

Ingestion rates were estimated based on short-term data 

collected in the CSFII 1994-96, 1998. 

Medium 

Clarity and Completeness 

Accessibility 

Reproducibility 

Quality Assurance 

The 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. 

Quality assurance methods were not described in the study 

report. 

Medium 

Variability and Uncertainty 

Variability in Population 

Uncertainty 

Short term distributions 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. 

Other sources of uncertainty were minimal. 

Medium 

Evaluation and Review 

Peer Review 

Number and Agreement of Studies 

The USDA CSFII survey received a high level of peer review. 

U.S. EPA (2007) analysis was also peer-reviewed; however, 

the re-analysis of these data using the new age categories was 

not peer reviewed outside the Agency. 

Only one key study was available for this factor 

Medium 

Overall Rating Medium 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-3
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 14 - Total Food Intake 

14.3 KEY STUDY OF TOTAL FOOD INTAKE 

14.3.1 U.S. EPA Re-analysis of 1994-96, 1998 CSFII, 

Based on U.S. EPA (2007) - Analysis of Total 

Food Intake and Composition of Individual’s 

Diet Based on USDA’s 1994–96, 1998 

Continuing Survey of Food Intakes by 

Individuals (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 

1994–96 CSFII and its 1998 Supplemental Children’s 

Survey were designed to obtain data from a statistically 

representative sample of noninstitutionalized 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 two non-consecutive days. For 

both survey days, data were collected by an in-home 

interviewer. The day two 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 

1994-96 survey and 1998 supplement are referred to 

collectively as CSFII 1994-96, 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 1994-96, 1998 are 

discussed in detail in USDA (2000). 

For the analysis of total food intake, food 

commodity codes provided in U.S. EPA’s Food 

Commodity Intake Database (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. Total food intake was 

calculated for various age groups of children. 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 (i.e., below the 10th percentile of total 

intake), a central group (i.e., the 45th to 55th percentile 

of total intake), and a group at the high end of the 

distribution of total intake (i.e., 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 was 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, central 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, and 12 to 

19 years. The data were tabulated in units of g/kg-day 

and g/day. 

In order to conform to the standard age 

categories recommended in Guidance on Selecting Age 

Page Child-Specific Exposure Factors Handbook 

14-4 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 14 - Total Food Intake 

Groups for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. EPA, 

2005) and used in this handbook, each of the tables 

from U.S. EPA (2007) was modified by re-analyzing 

the source data and applying the new 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). The results of this re-analysis are presented in 

Tables 14-3 through 14-11. Distributions of total food 

intake are presented in Table 14-3 in units of g/day and 

g/kg-day. Tables 14-4 and 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. Tables 14-6 through 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 (Table 14-6), total meat intake (Table 

14-7), total meat and dairy intake (Table 14-8), total 

fish intake (Table 14-9), total fruit and vegetable intake 

(Table 14-10), and total dairy intake (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 1994-96, 

98 CSFII data set have both advantages and limitations 

with regard to estimating food intake rates. The large 

sample size (more than 20,000 persons; approximately 

10,000 children) 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 United States population that 

included children and low income groups. However, 

the survey design is of limited utility for assessing small 

and potentially at-risk subpopulations based on 

ethnicity, medical status, geography, or other factors 

such as activity level. Another limitation is that data 

are based on a two-day survey period and, as such, may 

not accurately reflect long-term eating patterns. This is 

particularly true for the tails (extremes) of the 

distribution of food intake. 

14.4	 REFERENCES FOR CHAPTER 14 

USDA (2000) 1994–96, 1998 Continuing survey of 

food intakes by individuals (CSFII). CD-ROM. 

Agricultural Research Service, Beltsville Human 

Nutrition Research Center, Beltsville, MD. 

Available from the National Technical 

Information Service, Springfield, VA; PB-2000­

500027. 

U.S. EPA	 (2000) Food commodity intake database 

[FCID raw data file]. Office of Pesticide 

Programs, Washington, DC. Available from the 

National Technical Information Service, 

Springfield, VA; PB2000-5000101. 

U.S. EPA (2005) Guidance on selecting age groups for 

monitoring and assessing childhood exposures to 

envir o nme n t a l c o n t aminants. U.S. 

Environmental Protection Agency, Washington, 

D.C., EPA/630/P-03/003F. Available from the 

National Technical Information Service, 

S p r i n g f i e l d , V A, a n d o nl i n e a t 

www.epa.gov/ncea. 

U.S. EPA	 (2007) Analysis of total food intake and 

composition of individual’s diet based on 

USDA’s 1994–96, 1998 continuing survey of 

food intakes by individuals (CSFII). National 

Center for Environmental Assessment, 

Washington, DC; EPA/600/R-05/062F. 

Available from the National Technical 

Information Service, Springfield, VA, and online 

at www.epa.gov/ncea. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-5
 
 

Table 14-3. Per Capita Total Food Intake 

Age Group N a cons. Ntotalb PC Mean SE Percentile 1 5 10 25 50 75 90 95 

Total Food Intake (g/day, as consumed) 

Birth to <1 month 59 88 67.0% 67 59 0 0 0 0 67 108 142 221 

1 to <3 month 183 245 74.7% 80 70 0 0 0 0 94 120 168 188 

3 to <6 month 6 to <12 month 1 to <2 years 2 to <3 years 3 to <6 years 6 to <11 years 11 to <16 years 16 to <21 years 

385 

676 

1,002 

994 

4,112 1,553 

975 743 

411 

678 

1,002 

994 

4,112 1,553 

975 743 

93.7% 

99.7% 

100% 

100% 

100% 100% 100% 100% 

197 

507 

1,039 

1,024 

1,066 1,118 1,209 1,184 

150 

344 

407 

377 

380 372 499 634 

0 

34 

216 

312 

416 438 343 308 

0 

141 

414 

491 

548 586 536 467 

12 

191 

570 

575 

629 680 657 556 

100 

283 

770 

752 

805 846 851 750 

167 

413 

998 

994 

1,020 1,052 1,124 1,061 

286 

600 

1,244 

1,257 

1,276 1,344 1,491 1,447 

385 

925 

1,556 

1,517 

1,548 1,642 1,860 1,883 

476 

1,220 

1,756 

1,649 

1,746 1,825 2,179 2,283 

Total Food Intake (g/kg-day, as consumed) 

Birth to <1 month 59 88 67.0% 20 18 0 0 0 0 19 33 43 61 

1 to <3 month 183 245 74.7% 16 14 0 0 0 0 18 25 36 40 3 to <6 month 385 411 93.7% 28 21 0 0 2 15 24 38 53 65 

6 to <12 month 676 678 99.7% 56 36 3 17 22 33 47 66 99 134 

1 to <2 years 2 to <3 years 3 to <6 years 6 to <11 years 11 to <16 years 16 to <21 years 

1,002 

994 

4,112 

1,553 

975 743 

1,002 

994 

4,112 

1,553 

975 743 

100% 

100% 

100% 

100% 

100% 100% 

90 

74 

61 

40 

24 18 

37 

29 

24 

17 

11 

9 

17 

23 

21 

10 

5 5 

38 

34 

30 

17 

9 6 

48 

39 

34 

21 

11 

8 

65 

52 

44 

28 

16 

12 

85 

72 

57 

38 

22 

16 

109 

92 

73 

49 

30 

22 

137 

113 

91 

61 

38 

30 

161 

126 

102 

70 

45 

35 

a b 

PC SE 

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 because human milk was not included in the total food intake estimates presented here. Sample size. = Percent consuming. = Standard error. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

14-6 September 2008 
Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed) 

Food Group N a cons. N totalb PC Mean SE Percentile 1 5 10 25 50 75 90 95 

Age Birth to <1month 

Total Food Intake 59 88 67.0% 67 59 0 0 0 0 67 108 142 221 

Total Dairy Intake Total Meat Intake 

51 

0 

88 

88 

58.0% 

0.0% 

41 

-

38 

-

0 

-

0 

-

0 

-

0 

-

40 

-

72 

-

81 

-

156 

-

Total Egg Intake Total Fish Intake 

0 0 

88 88 

0.0% 0.0% 

--

--

--

--

--

--

--

--

--

--

Total Grain Intake 5 88 5.7% - - - - - - - - - - Total Vegetable Intake Total Fruit Intake 

27 

2 

88 88 

30.7% 

2.3% 

5 

-

23 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0.29 

-

16 

-

32 

-

Total Fat Intake 58 88 65.9% 19 16 0 0 0 0 20 32 38 64 

Age 1 to <3 months 

Total Food Intake 183 245 74.7% 80 70 0 0 0 0 94 120 168 188 

Total Dairy Intake Total Meat Intake 

147 

1 

245 

245 

60.0% 

0.4% 

37 

-

40 

-

0 

-

0 

-

0 

-

0 

-

19 

-

72 

-

89 

-

103 

-

Total Egg Intake Total Fish Intake 

0 0 

245 245 

0.0% 0.0% 

--

--

--

--

--

--

--

--

--

--

Total Grain Intake 44 245 18.0% 1 5 0 0 0 0 0 0 3 9 Total Vegetable Intake Total Fruit Intake 

88 23 

245 245 

35.9% 

9.4% 

15 

4 

33 

21 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.92 

0 

74 

0 

94 

31 

Total Fat Intake 176 245 71.8% 21 17 0 0 0 0 27 34 42 49 

Age 3 to <6 months 

Total Food Intake 385 411 93.7% 197 150 0 0 12 100 167 286 385 476 

Total Dairy Intake Total Meat Intake 

308 

44 

411 411 

74.9% 10.7% 

56 

2 

56 

7 

0 

0 

0 

0 

0 

0 

0 

0 

60 

0 

85 

0 

109 

1 

124 

13 

Total Egg Intake Total Fish Intake 

28 

1 

411 411 

6.8% 

0.2% 

0.23 

-

3 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0.49 

-

Total Grain Intake 284 411 69.1% 8 11 0 0 0 0 4 11 21 27 

Total Vegetable Intake Total Fruit Intake 

263 218 

411 411 

64.0% 53.0% 

34 68 

46 

102 

0 0 

0 0 

0 0 

0 0 

13 15 

58 99 

102 196 

120 282 

Total Fat Intake 357 411 86.9% 28 17 0 0 0 20 30 38 45 53 

S

C

e

h

p

i

t

l

e

d

m

-S

b

p

e

e

r 

c

2

if

0

i

0

c 

8 

Exposure Factors Handbook 

14

Pa

-

g

7 

e 
 

Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed) (continued) 

Food Group 

N

a cons.

N

totalb PC Mean SE 

Percentile 

1 5 10 25 50 75 90 95 

Age 6 to <12 months 

Total Food Intake Total Dairy Intake Total Meat Intake 

676 

628 

500 

678 

678 

678 

99.7% 

92.6% 

73.7% 

507 

151 

22 

344 

246 

27 

34 

0 0 

141 

0 0 

191 

0.52 

0 

283 

26 

0.013 

413 

71 

14 

600 

124 

32 

925 

401 

59 

1,220 

722 

78 

Total Egg Intake Total Fish Intake 

352 

34 

678 678 

51.9% 

5.0% 

6 

0.62 

13 

3 

0 0 

0 0 

0 0 

0 0 

0.019 

0 

2 

0 

22 

0 

42 

0 

Total Grain Intake 653 678 96.3% 33 28 0 0.83 6 14 28 45 66 84 

Total Vegetable Intake Total Fruit Intake 

662 

639 

678 

678 

97.6% 

94.2% 

91 

169 

67 

142 

0 0 

2 0 

14 17 

41 70 

81 

147 

127 232 

180 335 

231 425 

Total Fat Intake 661 678 97.5% 31 16 0 2 7 23 31 40 51 58 

Age 1 to <2 years 

Total Food Intake 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 

0.27 

0 

0 

19 

25 

4 

15 

570 

94 

6 

0.0014 

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 

Age 2 to <3 years 

Total Food Intake Total Dairy Intake Total Meat Intake 

994 

994 

981 

994 

994 

994 

100% 

100% 

98.7% 

1,024 

383 

60 

377 

243 

41 

312 

6 

0 

491 

54 

8 

575 

104 

14 

752 

201 

31 

994 

346 

51 

1,257 

510 

80 

1,517 

709 

115 

1,649 

838 

139 

Total Egg Intake Total Fish Intake 

943 

190 

994 

994 

94.9% 

19.1% 

18 

4 

24 

12 

0 

0 

0 

0 

0.070 

0 

1 

0 

7 

0 

27 

0 

50 

13 

60 

26 

Total Grain Intake 993 994 99.9% 81 35 16 32 41 58 78 99 126 147 Total Vegetable Intake Total Fruit Intake 

994 

970 

994 

994 

100% 

97.6% 

145 279 

89 

230 

18 

0 

45 

2 

57 

25 

86 

117 

128 

231 

178 

382 

249 

594 

302 

750 

Total Fat Intake 994 994 100% 42 18 11 17 22 30 40 51 65 73 

Page Child-Specific Exposure Factors Handbook 

14-8 September 2008 
 

Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed) (continued) 

Food Group 

N

a cons.

N

totalb PC Mean SE 

Percentile 

1 5 10 25 50 75 90 95 

Age 3 to <6 years 

Total Food Intake 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% 

1066 

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 

0.00032 

0 

44 

56 

2 

23 

629 

121 

20 

0.065 

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 

1,74

805 

163 

59 

36 

175 

329 

642 

85 

Age 6 to <11 years 

Total Food Intake 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% 

1118 

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 

0.0019 

0 

54 

76 

1 

27 

680 

126 

24 

0.13 

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 

1,82

837 

195 

58 

38 

201 

410 

545 

95 

Age 11 to <16 years 

Total Food Intake 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% 

1209 

368 

114 

19 

9 

136 

280 

195 

69 

499 343 536 

291 1 25 

75 1 18 27 0 0.00087 

24 0 0 

63 33 56 

146 65 105 

202 0 0.000073 

33 18 28 

657 

43 

32 

0.12 

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 

2,17

948 

244 

72 

62 

249 

552 

635 

131 

Child-Specific Exposure Factors Handbook Page 

September 2008 14-9 
 

Table 14-4. Per Capita Intake of Total Food and Intake of Major Food Groups (g/day, As Consumed) (continued) 

Food Group N a cons. Ntotalb PC Mean SE Percentile 1 5 10 25 50 75 90 95 

Age 16 to <21 years 

Total Food Intake 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% 

1184 

283 

139 

21 10 

150 

325 

168 

74 

634 

279 

127 

30 33 

93 

204 

237 

42 

308 

0.24 

0 

0 0 

13 

43 

0 

13 

467 

8 

12 

0 0 

48 

86 

0 

22 

556 

19 

28 

0.078 

0 

58 

128 

0.0022 

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 

a b 

PC SE -

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 because human milk was not included in the total food intake estimates presented here. Sample size. = Percent consuming. = Standard error. = Data not reported where the number of consumers was less than 20. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

14-10 September 2008 
Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed) 

Food Group N a cons. N totalb PC Mean SE Percentile 1 5 10 25 50 75 90 95 

Age Birth to <1month 

Total Food Intake 59 88 67.0% 20 18 0 0 0 0 19 33 43 61 

Total Dairy Intake Total Meat Intake 

51 

0 

88 

88 

58.0% 

0.0% 

12 

-

12 

-

0 

-

0 

-

0 

-

0 

-

13 

-

21 

-

25 

-

43 

-

Total Egg Intake Total Fish Intake 

0 0 

88 88 

0.0% 0.0% 

--

--

--

--

--

--

--

--

--

--

Total Grain Intake 5 88 5.7% - - - - - - - - - - 

Total Vegetable Intake Total Fruit Intake 

27 

2 

88 88 

30.7% 

2.3% 

2 

-

6 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0.11 

-

4 

-

12 

-

Total Fat Intake 58 88 65.9% 6 5 0 0 0 0 6 9 11 18 

Age 1 to <3 months 

Total Food Intake 183 245 74.7% 16 14 0 0 0 0 18 25 36 40 

Total Dairy Intake Total Meat Intake 

147 

1 

245 

245 

60.0% 

0.4% 

8 

-

9 

-

0 

-

0 

-

0 

-

0 

-

4 

-

15 

-

20 

-

26 

-

Total Egg Intake Total Fish Intake 

0 0 

245 245 

0.0% 0.0% 

--

--

--

--

--

--

--

--

--

--

Total Grain Intake 44 245 18.0% 0.23 1 0 0 0 0 0 0 1 2 Total Vegetable Intake Total Fruit Intake 

88 23 

245 245 

35.9% 

9.4% 

3 

1 

6 

5 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.18 

0 

13 

0 

17 

7 

Total Fat Intake 176 245 71.8% 4 4 0 0 0 0 5 7 9 11 

Age 3 to <6 months 

Total Food Intake 385 411 93.7% 28 21 0 0 2 15 24 38 53 65 

Total Dairy Intake Total Meat Intake 

308 

44 

411 411 

74.9% 10.7% 

8 

0.21 

8 

0.97 

0 

0 

0 

0 

0 

0 

0 

0 

8 

0 

12 

0 

16 

0.12 

20 

1 

Total Egg Intake Total Fish Intake 

28 

1 

411 411 

6.8% 0.2% 

0.024 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0 

-

0.055 

-

Total Grain Intake 284 411 69.1% 1 2 0 0 0 0 1 1 3 4 

Total Vegetable Intake 263 411 64.0% 5 7 0 0 0 0 2 8 14 18 Total Fruit Intake 218 411 53.0% 9 15 0 0 0 0 2 13 29 37 Total Fat Intake 357 411 86.9% 4 3 0 0 0 2 4 6 7 8 

S

C

e

h

p

i

t

l

e

d

m

-S

b

p

e

e

r 

c

2

if

0

i

0

c 

8 

Exposure Factors Handbook 

14-

Pa

1

g

1 

e 
 

Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed) (continued) 

Food Group 

N

a cons.

N

totalb PC Mean SE 

Percentile 

1 5 10 25 50 75 90 95 

Age 6 to <12 months 

Total Food Intake 676 678 99.7% 56 36 3 17 22 33 47 66 99 134 

Total Dairy Intake Total Meat Intake 

628 

500 

678 

678 

92.6% 

73.7% 

16 

2 

26 

3 

0 

0 

0 

0 

0.068 

0 

3 

0.0017 

8 

1 

14 

4 

38 

6 

72 

8 

Total Egg Intake Total Fish Intake 

352 

34 

678 678 

51.9% 

5.0% 

0.58 

0.064 

1 

0.35 

0 0 

0 0 

0 0 

0 0 

0.0023 

0 

0.21 

0 

2 

0 

4 

0 

Total Grain Intake 653 678 96.3% 4 3 0 0.097 0.67 2 3 5 7 9 

Total Vegetable Intake Total Fruit Intake 

662 639 

678 678 

97.6% 94.2% 

10 19 

8 

16 

0 0 

0.26 

0 

2 

2 

5 

8 

9 

16 

14 

26 

20 

36 

25 

46 

Total Fat Intake 661 678 97.5% 3 2 0 0.20 0.77 2 3 4 6 7 

Age 1 to <2 years 

Total Food Intake 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 

0.27 

6 

10 

22 

3 

37 

30 

3 2 

0.88 

3 

7 

18 

2 

17 

0.10 

0 0 

0 

0.87 

0.65 

0 

0.73 

38 

3 

0.023 

0 

0 

2 

2 

0.41 

1 

48 

8 

0.59 

0.000098 

0 

2 

3 3 

2 

65 

20 

2 

0.085 

0 

4 

6 

9 

2 

85 

38 

3 

0.37 

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 

Age 2 to <3 years 

Total Food Intake 994 994 100% 74 29 23 34 39 52 72 92 113 126 

Total Dairy Intake Total Meat Intake 

994 

981 

994 

994 

100% 

98.7% 

28 

4 

18 

3 

0.42 

0 

4 

0.55 

7 

1 

14 

2 

24 

4 

37 

6 

52 

8 

63 

9 

Total Egg Intake Total Fish Intake 

943 190 

994 994 

94.9% 19.1% 

1 

0.27 

2 

0.89 

0 

0 

0 

0 

0.0051 

0 

0.098 

0 

0.49 

0 

2 

0 

4 

0.91 

4 

2 

Total Grain Intake 993 994 99.9% 6 3 1 2 3 4 5 7 9 10 

Total Vegetable Intake Total Fruit Intake 

994 970 

994 994 

100% 

97.6% 

10 20 

6 

17 

1 0 

3 

0.14 

4 

2 

6 8 

9 

16 

13 

27 

18 

44 

22 

56 

Total Fat Intake 994 994 100% 3 1 0.72 1 1 2 3 4 5 5 

Page Child-Specific Exposure Factors Handbook 

14-12 September 2008 
 

Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed) (continued) 

Food Group 

N

a cons.

N

totalb PC Mean SE 

Percentile 

1 5 10 25 50 75 90 95 

Age 3 to <6 years 

Total Food Intake 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 

0.89 

0.29 

6 

10 

14 

3 

24 

15 

3 

1 

0.88 

3 

5 

13 

1 

21 

0.83 

0 

0 

0 

2 

2 

0 

0.85 

30 34 

4 7 

0.61 1 

0.000022 0.0035 

0 0 

2 3 

3 4 

0.13 0.94 

1 2 

44 

12 

2 

0.081 

0 

4 

6 

5 

2 

57 

20 

4 

0.32 

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 

Age 6 to <11 years 

Total Food Intake 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 

0.55 

0.21 

4 

7 7 

2 

17 

10 

2 

1 

0.66 

2 

4 7 

1 

10 

0.35 

0 

0 

0 

0.92 

1 0 

0.60 

17 21 

2 4 

0.44 0.82 

0.000084 0.0034 

0 0 2 2 

2 3 

0.049 0.24 

0.91 1 

28 

7 

2 

0.054 

0 3 

5 

2 

1 

38 

13 

3 

0.21 

0 4 

7 

5 

2 

49 

20 

4 

0.72 

0 5 

9 

10 

3 

61 

27 

6 

2 

0.79 

7 

12 

16 

3 

70 

33 

7 

2 

1 

8 

15 

21 

4 

Age 11 to <16 years 

Total Food Intake Total Dairy Intake Total Meat Intake Total Egg Intake Total Fish Intake Total Grain Intake Total Vegetable Intake Total Fruit Intake 

975 

975 

970 930 

167 975 

975 923 

975 

975 

975 975 

975 975 

975 975 

100% 

100% 

99.5% 95.4% 

17.1% 

100% 

100% 

94.7% 

24 

7 

2 

0.36 

0.16 

3 

5 

4 

11 

6 

1 

1 

0.48 

1 

3 

4 

5 

0.021 

0.022 

0 0 

0.62 

1 

0 

9 11 

0.38 0.82 

0.35 0.63 

0.000015 0.0021 

0 0 

0.94 1 

2 2 

0.000001 0.13 

16 

3 

1 

0.033 

0 

2 3 

0.64 

22 

6 

2 

0.14 

0 

2 5 

3 

30 

10 

3 

0.45 

0 

3 7 

6 

38 

15 

4 

1 

0.57 

5 9 

10 

45 

20 

5 

1 

1 

5 

11 

14 

Total Fat Intake 975 975 100% 1 1 0.35 0.48 0.61 1 1 2 2 3 

Child-Specific Exposure Factors Handbook Page 

September 2008 14-13 
 

Table 14-5. Per Capita Intake of Total Food and Intake of Major Food Groups (g/kg-day, As Consumed) (continued) 

Food Group N a cons. Ntotalb PC Mean SE Percentile 1 5 10 25 50 75 90 95 

Age 16 to <21 years 

Total Food Intake Total Dairy Intake Total Meat Intake Total Egg Intake Total Fish Intake 

743 

742 

730 

703 143 

743 

743 

743 

743 743 

100% 

99.9% 

98.3% 

94.6% 19.2% 

18 

4 

2 

0.31 0.15 

9 

4 

2 

0.43 0.51 

5 

0.0058 

0 

0 0 

6 

0.13 0.18 

0 0 

8 

0.28 0.49 

0.0012 

0 

12 

0.88 0.95 

0.018 

0 

16 

3 2 

0.11 

0 

22 

6 3 

0.44 

0 

30 

10 

4 

0.96 

0.51 

35 

12 

5 

1 

1 

Total Grain Intake Total Vegetable Intake Total Fruit Intake Total Fat Intake 

743 

743 

671 

743 

743 

743 

743 

743 

100% 

100% 

90.3% 

100% 

2 

5 

3 

1 

1 

3 

4 

1 

0.17 

0.61 

0 

0.21 

0.65 

1 0 

0.33 

0.85 

2 

0.000030 

0.47 

1 

3 

0.049 

1 

2 

4 

1 

1 

3 

6 

4 

1 

4 

8 

7 

2 

5 

10 

10 

2 

a b 

PC SE -

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 because human milk was not included in the total food intake estimates presented here. Sample size. = Percent consuming. = Standard error. = Data not reported where the number of consumers was less than 20. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

14-14 September 2008 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

H

Co

Intake Percent Intake Percent Intak

Age Birth to <1month (g/day, as consumed) Age Birth to <1month (g/kg-day, as consu

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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 Foods 0 0.0% 20 100.0% 58 Total Dairy 0 0.0% 14 70.5% 35 Total Meats 0 0.0% 0 0.0% 0 Total Fish 0 0.0% 0 0.0% 0 Total Eggs 0 0.0% 0 0.0% 0 Total Grains 0 0.0% 0 0.0% 1 Total Vegetables 0 0.0% 0.012 0.1% 6 Total Fruits 0 0.0% 0 0.0% 0 Total Fats a 0 0.0% 6 29.4% 16 

Age 1 to <3 months (g/day, as consumed) Age 1 to <3 months (g/kg-day, as consum

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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% 0.033 0.0% 27 13.0% 0 0.0% 27 28.4% 49 23.6% 

Total Foods 0 0.0% 18 100.0% 44 Total Dairy 0 0.0% 9 51.9% 20 Total Meats 0 0.0% 0 0.0% 0.012 Total Fish 0 0.0% 0 0.0% 0 Total Eggs 0 0.0% 0 0.0% 0 Total Grains 0 0.0% 0.19 1.1% 0.23 Total Vegetables 0 0.0% 3 18.9% 7 Total Fruits 0 0.0% 0 0.0% 5 Total Fats a 0 0.0% 5 27.7% 11 

Age 3 to <6 months (g/day, as consumed) Age 3 to <6 months (g/kg-day, as consum

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

1 100.0% 166 100.0% 507 100.0% 

0.038 3.0% 69 41.9% 90 17.8% 

0 0.0% 0.38 0.2% 4 0.8% 0 0.0% 0 0.0% 0.42 0.1% 0 0.0% 0.50 0.3% 0.60 0.1% 

0.93 74.5% 8 4.9% 14 2.8% 0.14 10.9% 27 16.3% 73 14.4% 0.12 9.9% 24 14.6% 284 56.0% 

0.017 1.3% 34 20.4% 36 7.2% 

Total Foods 0.26 100.0% 24 100.0% 73 Total Dairy 0 0.5% 9 37.3% 13 Total Meats 0 0.0% 0.11 0.5% 0.62 Total Fish 0 0.0% 0 0.0% 0.056 Total Eggs 0 0.0% 0 0.0% 0.03Total Grains 0.22 85.0% 0.95 4.0% 2 Total Vegetables 0.019 7.4% 5 20.8% 11 Total Fruits 0.017 6.7% 4 15.0% 40 Total Fats a 0.00059 0.2% 5 21.3% 5 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-15
 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 6 to <12 months (g/day, as consumed) Age 6 to <12 months (g/kg-day, as con

Total Foods 124 100.0% 414 100.0% 1,358 100.0% Total Foods 15 100.0% 47 100.0% 

Total Dairy Total Meats 

33 

3 

26.4% 

2.4% 

72 

19 

17.5% 

4.6% 

770 

47 

56.7% 

3.5% 

Total Dairy Total Meats 

4 

0.34 

25.4% 

2.3% 

6 2 

13.8% 

4.9% 

Total Fish 0.25 0.2% 1 0.3% 0.28 0.0% Total Fish 0.033 0.2% 0.090 0.2% 0

Total Eggs Total Grains 

0.62 

11 

0.5% 9.1% 

7 

37 

1.6% 

8.9% 

8 

50 

0.6% 

3.7% 

Total Eggs Total Grains 

0.13 

2 

0.9% 

10.7% 

0.69 

4 

1.5% 

9.1% 

Total Vegetables 

Total Fruits 

30 30 

24.2% 24.4% 

90 

151 

21.9% 36.5% 

121 314 

8.9% 

23.1% 

Total Vegetables Total Fruits 

3 

4 

21.9% 

25.9% 

10 

19 

22.4% 

40.0% 

Total Fats a 14 11.6% 35 8.4% 44 3.2% Total Fats a 2 11.4% 4 7.5% 

Age 1 to <2 years (g/day, as consumed) Age 1 to <2 years (g/kg-day, as cons

Total Foods 407 100.0% 998 100.0% 1,859 100.0% Total Foods 35 100.0% 85 100.0% Total Dairy Total Meats 

113 

28 

27.8% 

6.9% 

487 

46 

48.8% 

4.6% 

1,008 

66 

54.2% 

3.5% 

Total Dairy Total Meats 

10 

3 

29.5% 

7.5% 

41 

4 

48.1% 

4.7% 

Total Fish 1 0.3% 3 0.3% 4 0.2% Total Fish 0.14 0.4% 0.46 0.5% 0

Total Eggs Total Grains 

9 

44 

2.2% 

10.8% 

16 

63 

1.6% 

6.3% 

22 

81 

1.2% 

4.3% 

Total Eggs Total Grains 

0.74 

4 

2.1% 

10.9% 

1 5 

1.4% 6.0% 

Total Vegetables Total Fruits 

82 

100 

20.1% 24.6% 

101 238 

10.2% 23.8% 

165 446 

8.9% 

24.0% 

Total Vegetables Total Fruits 

7 

8 

18.6% 

23.0% 

10 

19 

11.9% 

22.8% 

Total Fats a 24 5.8% 38 3.8% 61 3.3% Total Fats a 2 6.4% 3 3.8% 

Age 2 to <3 years (g/day, as consumed) Age 2 to <3 years(g/kg-day, as consu

Total Foods Total Dairy Total Meats 

448 118 

50 

100.0% 

26.3% 11.1% 

989 370 

60 

100.0% 

37.4% 

6.1% 

1,760 

698 

72 

100.0% 

39.7% 

4.1% 

Total Foods Total Dairy Total Meats 

32 

8 4 

100.0% 

24.8% 11.2% 

72 

26 

4 

100.0% 

36.3% 

5.3% 

Total Fish 1 0.3% 4 0.4% 7 0.4% Total Fish 0.11 0.4% 0.18 0.2% 0

Total Eggs Total Grains 

12 62 

2.7% 

13.7% 

14 86 

1.4% 8.7% 

24 98 

1.4% 5.6% 

Total Eggs Total Grains 

1 

4 

3.6% 

13.8% 

1 

6 

1.7% 

8.0% 

Total Vegetables Total Fruits 

98 70 

21.9% 15.6% 

145 255 

14.6% 25.8% 

185 609 

10.5% 34.6% 

Total Vegetables Total Fruits 

7 

5 

22.0% 

16.2% 

10 

21 

13.3% 

29.8% 

Total Fats a 31 6.8% 44 4.4% 56 3.2% Total Fats a 2 7.1% 3 3.9% 

Page Child-Specific Exposure Factors Handbook 

14-16 September 2008 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age 3 to <6 years (g/day, as consumed) Age 3 to <6 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

527 100.0% 1,020 100.0% 1,817 100.0% 144 27.3% 378 37.0% 728 40.1% 

53 10.0% 72 7.0% 94 5.2% 

3 0.6% 5 0.5% 9 0.5% 

11 2.0% 15 1.5% 24 1.3% 76 14.4% 103 10.1% 132 7.3% 

117 22.3% 163 16.0% 233 12.8% 

76 14.4% 216 21.2% 509 28.0% 34 6.5% 50 4.9% 68 3.7% 

Total Foods 28 100.0% 57 100.0% Total Dairy 8 27.3% 21 36.6% Total Meats 3 10.4% 4 7.1% Total Fish 0.14 0.5% 0.27 0.5% 0Total Eggs 0.59 2.1% 0.92 1.6% Total Grains 4 14.0% 6 9.9% Total Vegetables 6 22.0% 9 16.0% Total Fruits 4 15.2% 13 22.1% Total Fats a 2 6.4% 3 4.8% 

Age 6 to <11 years (g/day, as consumed) Age 6 to <11 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

565 100.0% 1,060 100.0% 1,886 100.0% 147 26.1% 370 34.9% 766 40.6% 

65 11.4% 95 9.0% 104 5.5% 

2 0.3% 6 0.6% 10 0.5% 

10 1.7% 16 1.5% 22 1.2% 89 15.8% 116 10.9% 157 8.3% 

136 24.1% 203 19.2% 294 15.6% 

66 11.6% 178 16.8% 426 22.6% 39 6.8% 58 5.5% 76 4.0% 

Total Foods 16 100.0% 38 100.0% Total Dairy 4 26.2% 15 38.6% Total Meats 2 11.9% 3 8.1% Total Fish 0.075 0.5% 0.20 0.5% 0Total Eggs 0.28 1.8% 0.62 1.6% 0Total Grains 2 14.7% 4 10.8% Total Vegetables 4 24.7% 7 18.0% Total Fruits 2 11.2% 6 14.9% Total Fats a 1 7.3% 2 5.3% 

Age 11 to <16 years (g/day, as consumed) Age 11 to <16 years (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

513 100.0% 1,127 100.0% 2,256 100.0% 

92 17.9% 308 27.3% 808 35.8% 71 13.9% 116 10.3% 172 7.6% 

4 0.8% 7 0.6% 16 0.7% 

10 1.9% 20 1.8% 28 1.2% 84 16.3% 133 11.8% 207 9.2% 

162 31.6% 258 22.9% 459 20.3% 

42 8.2% 203 18.0% 420 18.6% 40 7.8% 64 5.7% 114 5.0% 

Total Foods 8 100.0% 22 100.0% Total Dairy 1 17.3% 6 26.9% Total Meats 1 14.7% 2 10.3% Total Fish 0.072 0.9% 0.19 0.8% 0Total Eggs 0.15 1.8% 0.49 2.2% 0Total Grains 1 16.6% 3 11.7% Total Vegetables 3 31.7% 5 23.4% Total Fruits 0.60 7.2% 4 17.4% Total Fats a 0.70 8.3% 1 5.9% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-17
 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 16 to <21 years (g/day, as consumed) Age 16 to <21 years (g/kg-day, as con

Total Foods Total Dairy Total Meats 

438 

56 61 

100.0% 

12.8% 14.0% 

1,060 

219 141 

100.0% 

20.7% 13.3% 

2,590 

759 272 

100.0% 

29.3% 10.5% 

Total Foods Total Dairy Total Meats 

6 

0.76 

0.97 

100.0% 

12.2% 

15.6% 

16 

4 

2 

100.0% 

23.8% 

11.5% 

Total Fish 7 1.5% 11 1.1% 14 0.5% Total Fish 0.10 1.7% 0.15 1.0% 0

Total Eggs Total Grains 

8 

67 

1.9% 

15.2% 

17 

138 

1.6% 

13.0% 

29 

241 

1.1% 9.3% 

Total Eggs Total Grains 

0.11 

0.92 

1.8% 

14.8% 

0.24 

2 

1.6% 

13.1% 

0

Total Vegetables Total Fruits 

148 

48 

33.8% 

11.0% 

312 

138 

29.4% 

13.1% 

620 

487 

23.9% 

18.8% 

Total Vegetables Total Fruits 

2 

0.64 

34.0% 

10.2% 

5 

2 

30.0% 

10.9% 

Total Fats a 33 7.6% 72 6.8% 136 5.3% Total Fats a 0.50 8.1% 1 7.1% 

a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other fo

meats. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

14-18 September 2008 
 

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 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end Consumers Mid-range Consumers 

Intake Percent Intake Percent In

Age Birth to <1month (g/day, as consumed) b Age Birth to <1month (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

67 100.0% - - - -41 61.5% - - - -

0 0.0% - - - -0 0.0% - - - -0 0.0% - - - -

0.44 0.7% - - - -

5 7.7% - - - -

0.88 1.3% - - - -

19 28.3% - - - -

Total Foods 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 0.14 0.7% - - Total Vegetables 2 7.7% - - Total Fruits 0.21 1.1% - - Total Fats a 6 28.4% - - 

Age 1 to <3 months (g/day, as consumed) c Age 1 to <3 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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% - - 0.18 0.1% 

15 18.6% - - 3 2.1% 

4 5.2% - - 0 0.0% 

21 26.4% - - 42 28.2% 

Total Foods 16 100.0% - - Total Dairy 8 47.9% - - Total Meats 0 0.0% - - 0Total Fish 0 0.0% - - Total Eggs 0 0.0% - - Total Grains 0.23 1.4% - - 0Total Vegetables 3 16.8% - - 0Total Fruits 0.91 5.6% - - Total Fats a 4 26.5% - - 

Age 3 to <6 months (g/day, as consumed) d Age 3 to <6 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

181 100.0% - - 316 100.0% 

55 30.1% - - 62 19.7% 

0 0.0% - - 16 4.9% 0 0.0% - - 0.44 0.1% 

0.092 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 Foods 26 100.0% - - Total Dairy 8 30.6% - - Total Meats 0 0.0% - - Total Fish 0 0.0% - - 0Total Eggs 0.012 0.0% - - 0Total Grains 0.97 3.7% - - Total Vegetables 4 16.9% - - Total Fruits 8 32.2% - - Total Fats a 4 15.6% - - 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-19
 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 6 to <12 months (g/day, as consumed) Age 6 to <12 months (g/kg-day, as con

Total Foods 347 100.0% 466 100.0% 922 100.0% Total Foods 40 100.0% 48 100.0% 

Total Dairy Total Meats 

80 

0 

23.0% 

0.0% 

108 

14 

23.2% 

2.9% 

384 

85 

41.6% 

9.3% 

Total Dairy Total Meats 

9 0 

22.6% 

0.0% 

11 

1 

23.9% 

3.0% 

Total Fish 0.13 0.0% 0.34 0.1% 0.19 0.0% Total Fish 0.016 0.0% 0.053 0.1% 

Total Eggs Total Grains 

2 

24 

0.5% 

6.8% 

3 

29 

0.6% 

6.2% 

11 

51 

1.2% 

5.6% 

Total Eggs Total Grains 

0.19 

3 

0.5% 

6.6% 

0.45 

3 

1.0% 

6.0% 

0

Total Vegetables Total Fruits 

69 

143 

19.8% 41.3% 

116 162 

24.8% 34.8% 

135 216 

14.7% 23.4% 

Total Vegetables Total Fruits 

8 

17 

19.7% 

41.9% 

10 

17 

21.9% 

36.5% 

Total Fats a 27 7.7% 31 6.7% 43 4.6% Total Fats a 3 7.8% 3 7.1% 

Age 1 to <2 years (g/day, as consumed) Age 1 to <2 years (g/kg-day, as consu

Total Foods 921 100.0% 992 100.0% 1,229 100.0% Total Foods 82 100.0% 90 100.0% Total Dairy Total Meats 

464 

2 

50.4% 

0.2% 

483 

39 

48.7% 

4.0% 

460 

128 

37.4% 

10.4% 

Total Dairy Total Meats 

41 

0.15 

49.9% 

0.2% 

46 

3 

50.5% 

3.8% 

Total Fish 3 0.3% 2 0.2% 6 0.5% Total Fish 0.24 0.3% 0.25 0.3% 0

Total Eggs Total Grains 

8 

56 

0.9% 

6.1% 

14 

64 

1.5% 

6.5% 

24 

78 

1.9% 

6.4% 

Total Eggs Total Grains 

0.65 

5 

0.8% 

6.1% 

1 

6 

1.4% 

6.1% 

Total Vegetables Total Fruits 

97 

250 

10.5% 27.2% 

113 228 

11.3% 23.0% 

189 290 

15.4% 23.6% 

Total Vegetables Total Fruits 

9 

22 

11.1% 

27.3% 

10 

21 

10.8% 

22.7% 

Total Fats a 30 3.3% 38 3.8% 57 4.6% Total Fats a 3 3.3% 3 3.8% 

Age 2 to <3 years (g/day, as consumed) Age 2 to <3 years(g/kg-day, as consu

Total Foods Total Dairy Total Meats 

950 426 

7 

100.0% 

44.9% 

0.7% 

947 373 

52 

100.0% 

39.3% 

5.4% 

1,131 

374 

148 

100.0% 

33.0% 

13.1% 

Total Foods Total Dairy Total Meats 

71 

31 

0.51 

100.0% 

44.2% 

0.7% 

68 

26 

4 

100.0% 

37.7% 

5.5% 

Total Fish 4 0.5% 4 0.5% 2 0.2% Total Fish 0.34 0.5% 0.18 0.3% 0

Total Eggs Total Grains 

12 73 

1.3% 7.7% 

18 76 

1.9% 8.1% 

21 90 

1.9% 8.0% 

Total Eggs Total Grains 

0.94 

6 

1.3% 

7.8% 

0.92 

6 

1.3% 

8.3% 

Total Vegetables Total Fruits 

104 279 

10.9% 29.4% 

146 226 

15.4% 23.8% 

202 232 

17.9% 20.5% 

Total Vegetables Total Fruits 

8 

21 

11.1% 

29.6% 

10 

18 

15.1% 

26.7% 

Total Fats a 29 3.0% 40 4.2% 62 5.5% Total Fats a 2 3.1% 3 4.0% 

Page Child-Specific Exposure Factors Handbook 

14-20 September 2008 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age 3 to <6 years (g/day, as consumed) Age 3 to <6 years (g/kg-day, as consu

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

991 100.0% 1,037 100.0% 1,246 100.0% 419 42.3% 376 36.3% 389 31.2% 

10 1.0% 65 6.3% 176 14.1% 

7 0.7% 6 0.5% 4 0.3% 

10 1.0% 16 1.5% 24 1.9% 98 9.9% 101 9.8% 117 9.4% 

128 13.0% 170 16.4% 217 17.4% 257 25.9% 238 22.9% 243 19.5% 

35 3.6% 48 4.7% 73 5.9% 

Total Foods 57 100.0% 59 100.0% Total Dairy 24 42.1% 23 38.2% Total Meats 0.56 1.0% 4 6.0% Total Fish 0.35 0.6% 0.29 0.5% 0Total Eggs 0.56 1.0% 0.81 1.4% Total Grains 6 9.9% 6 9.5% Total Vegetables 7 13.0% 9 15.8% Total Fruits 15 26.1% 13 22.0% Total Fats a 2 3.6% 3 4.8% 

Age 6 to <11 years (g/day, as consumed) Age 6 to <11 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

1028 100.0% 1,087 100.0% 1,300 100.0% 

424 41.3% 386 35.5% 382 29.4% 

11 1.1% 79 7.3% 206 15.8% 

6 0.6% 5 0.5% 4 0.3% 

13 1.3% 15 1.4% 17 1.3% 

121 11.8% 117 10.7% 136 10.4% 164 16.0% 212 19.5% 270 20.7% 214 20.8% 191 17.6% 198 15.2% 

40 3.9% 59 5.4% 81 6.2% 

Total Foods 36 100.0% 39 100.0% Total Dairy 15 41.5% 15 38.7% Total Meats 0.38 1.0% 3 7.0% Total Fish 0.31 0.9% 0.32 0.8% 0Total Eggs 0.44 1.2% 0.42 1.1% 0Total Grains 4 11.5% 4 10.7% Total Vegetables 5 15.1% 7 19.1% Total Fruits 8 21.7% 6 15.6% Total Fats a 1 3.8% 2 5.1% 

Age 11 to <16 years (g/day, as consumed) Age 11 to <16 years (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

1043 100.0% 1,194 100.0% 1,606 100.0% 

342 32.8% 377 31.6% 435 27.1% 

17 1.6% 101 8.5% 268 16.7% 13 1.3% 7 0.6% 7 0.4% 17 1.6% 13 1.1% 21 1.3% 

116 11.1% 144 12.1% 159 9.9% 227 21.7% 260 21.8% 404 25.2% 238 22.8% 202 16.9% 204 12.7% 

44 4.2% 67 5.6% 106 6.6% 

Total Foods 19 100.0% 22 100.0% Total Dairy 6 31.5% 6 27.0% Total Meats 0.31 1.6% 2 8.8% Total Fish 0.28 1.5% 0.12 0.5% 0Total Eggs 0.28 1.5% 0.29 1.3% 0Total Grains 2 11.6% 3 11.7% Total Vegetables 4 22.2% 5 24.1% Total Fruits 4 23.1% 4 18.9% Total Fats a 0.83 4.4% 1 5.7% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 16 to <21 years (g/day, as consumed) Age 16 to <21 years (g/kg-day, as con

Total Foods Total Dairy Total Meats 

922 

307 

12 

100.0% 

33.3% 

1.3% 

1,084 

280 115 

100.0% 

25.8% 10.6% 

1,957 

403 385 

100.0% 

20.6% 19.7% 

Total Foods Total Dairy Total Meats 

15 

4 

0.19 

100.0% 

30.3% 

1.3% 

18 

4 2 

100.0% 

24.0% 

9.6% 

Total Fish 20 2.1% 9 0.9% 12 0.6% Total Fish 0.32 2.2% 0.18 1.0% 0

Total Eggs Total Grains 

14 

131 

1.5% 

14.2% 

15 

147 

1.4% 

13.6% 

31 

231 

1.6% 

11.8% 

Total Eggs Total Grains 

0.21 

2 

1.4% 

14.5% 

0.35 

2 

1.9% 

12.8% 

0

Total Vegetables Total Fruits 

215 

151 

23.3% 

16.4% 

287 

147 

26.5% 

13.5% 

532 

226 

27.2% 

11.6% 

Total Vegetables Total Fruits 

4 

3 

24.6% 

17.8% 

5 

3 

27.5% 

15.7% 

Total Fats a 42 4.5% 73 6.7% 139 7.1% Total Fats a 0.67 4.6% 1 6.2% 

a b c d 

Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other fomeats. All individuals in this sample group consumed 0 grams/day of meat. Therefore, results are reported in the low-end decile. 

Only one individual in this sample group consumed more than 0 grams/day of meat. This result is reported in the high-end decile. All other 

reported in the low-end decile. All individuals in this sample group below the 89th percentile consumed 0 grams/day of meat. Therefore, only high-end and low-end consum

reported. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

14-

Pag22 e Child-Specific Exposure Fa

S

cteopr

te

s 

mHbaenr d2b0o0o8 

k 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age Birth to <1month (g/day, as consumed) Age Birth to <1month (g/kg-day, as co

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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% 

0.031 0.3% 0 0.0% 4 2.2% 

8 66.1% 2 3.4% 0.78 0.4% 0 0.0% 0 0.0% 0 0.0% 3 27.1% 18 29.2% 52 28.4% 

Total Foods 4 100.0% 18 100.0% Total Dairy 0 0.0% 12 67.1% 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 0.0086 0.2% 0 0.0% Total Vegetables 2 64.4% 0.65 3.7% 0Total Fruits 0 0.0% 0 0.0% Total Fats a 1 27.5% 5 29.2% 

Age 1 to <3 months (g/day, as consumed) Age 1 to <3 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

36 100.0% 84 100.0% 166 100.0% 

0 0.0% 19 22.4% 109 65.6% 0 0.0% 0 0.0% 0.037 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 

0.32 0.9% 1 1.2% 1 0.8% 

21 58.8% 42 50.7% 4 2.7% 

2 4.3% 0.034 0.0% 6 3.7% 

10 26.7% 21 25.4% 45 27.2% 

Total Foods 7 100.0% 14 100.0% Total Dairy 0 0.0% 3 24.0% Total Meats 0 0.0% 0 0.0% 0Total Fish 0 0.0% 0 0.0% Total Eggs 0 0.0% 0 0.0% Total Grains 0.054 0.8% 0.29 2.0% 0Total Vegetables 4 57.8% 7 48.7% 0Total Fruits 0.37 5.4% 0.0067 0.0% Total Fats a 2 26.4% 4 25.0% 

Age 3 to <6 months (g/day, as consumed) Age 3 to <6 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

121 100.0% 204 100.0% 334 100.0% 

0 0.0% 60 29.7% 159 47.7% 0 0.0% 0.55 0.3% 5 1.4% 0 0.0% 0 0.0% 0.43 0.1% 0 0.0% 0.30 0.1% 0.64 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 Foods 17 100.0% 30 100.0% Total Dairy 0 0.0% 8 26.5% Total Meats 0 0.0% 0.19 0.6% 0Total Fish 0 0.0% 0 0.0% 0Total Eggs 0 0.0% 0.10 0.3% 0Total Grains 0.78 4.5% 1 3.7% Total Vegetables 6 37.1% 3 11.2% Total Fruits 7 41.7% 14 46.0% Total Fats a 2 12.6% 3 11.4% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-23
 
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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 6 to <12 months (g/day, as consumed) Age 6 to <12 months (g/kg-day, as con

Total Foods 253 100.0% 403 100.0% 1,284 100.0% Total Foods 29 100.0% 43 100.0% 

Total Dairy Total Meats 

1 

0.68 

0.5% 

0.3% 

71 

17 

17.6% 

4.1% 

827 

45 

64.5% 

3.5% 

Total Dairy Total Meats 

0.12 

0.083 

0.4% 

0.3% 

8 

2 

18.0% 

4.7% 

Total Fish 0 0.0% 1 0.4% 0.28 0.0% Total Fish 0 0.0% 0.14 0.3% 0

Total Eggs Total Grains 

3 

22 

1.0% 

8.5% 

3 

32 

0.7% 

8.0% 

7 

45 

0.5% 

3.5% 

Total Eggs Total Grains 

0.32 

2 

1.1% 

8.0% 

0.39 

3 

0.9% 

7.1% 

0

Total Vegetables Total Fruits 

95 

110 

37.7% 43.4% 

82 

166 

20.3% 41.1% 

108 209 

8.4% 

16.3% 

Total Vegetables Total Fruits 

11 

13 

38.2% 

43.4% 

9 

17 

20.0% 

40.4% 

Total Fats a 17 6.7% 32 8.0% 41 3.2% Total Fats a 2 6.7% 4 8.3% 

Age 1 to <2 years (g/day, as consumed) Age 1 to <2 years (g/kg-day, as consu

Total Foods 569 100.0% 1,014 100.0% 1,687 100.0% Total Foods 51 100.0% 82 100.0% 

Total Dairy Total Meats 

46 30 

8.0% 5.2% 

456 

43 

45.0% 

4.2% 

1,165 

52 

69.0% 

3.1% 

Total Dairy Total Meats 

4 3 

7.7% 5.5% 

38 

4 

45.6% 

5.3% 

Total Fish 2 0.4% 2 0.2% 3 0.2% Total Fish 0.13 0.2% 0.22 0.3% 0

Total Eggs Total Grains 

12 54 

2.0% 9.5% 

13 64 

1.3% 6.3% 

19 65 

1.1% 3.8% 

Total Eggs Total Grains 

1 

5 

2.1% 

9.5% 

1 

6 

1.6% 

7.2% 

Total Vegetables Total Fruits 

128 264 

22.5% 46.4% 

114 278 

11.3% 27.4% 

111 209 

6.6% 

12.4% 

Total Vegetables Total Fruits 

11 

24 

22.2% 

46.6% 

11 

19 

13.0% 

22.7% 

Total Fats a 25 4.5% 36 3.6% 59 3.5% Total Fats a 2 4.5% 3 3.8% 

Age 2 to <3 years (g/day, as consumed) Age 2 to <3 years(g/kg-day, as consu

Total Foods Total Dairy Total Meats 

641 

57 45 

100.0% 

9.0% 6.9% 

981 348 

59 

100.0% 

35.5% 

6.0% 

1,546 

883 

60 

100.0% 

57.1% 

3.9% 

Total Foods Total Dairy Total Meats 

46 

4 3 

100.0% 

8.2% 7.4% 

73 

24 

5 

100.0% 

32.6% 

6.5% 

Total Fish 4 0.6% 3 0.3% 4 0.3% Total Fish 0.19 0.4% 0.25 0.3% 0

Total Eggs Total Grains 

21 75 

3.2% 

11.8% 

18 86 

1.9% 8.7% 

20 86 

1.3% 5.6% 

Total Eggs Total Grains 

1 

5 

3.2% 

11.6% 

1 

6 

1.6% 

8.7% 

Total Vegetables Total Fruits 

155 240 

24.1% 37.5% 

148 264 

15.1% 26.9% 

143 286 

9.2% 

18.5% 

Total Vegetables Total Fruits 

11 

18 

23.6% 

38.7% 

11 

22 

14.9% 

29.9% 

Total Fats a 32 5.0% 42 4.3% 55 3.6% Total Fats a 2 5.2% 3 4.3% 

14-

Pag24 e Child-Specific Exposure Fa

S

cteopr

te

s 

mHbaenr d2b0o0o8 

k 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age 3 to <6 years (g/day, as consumed) Age 3 to <6 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

702 100.0% 1,043 100.0% 1,646 100.0% 

75 10.7% 352 33.8% 878 53.3% 52 7.5% 79 7.6% 88 5.4% 

5 0.7% 5 0.5% 5 0.3% 

15 2.2% 16 1.5% 19 1.2% 85 12.0% 107 10.2% 121 7.3% 

159 22.6% 167 16.0% 191 11.6% 258 36.7% 251 24.1% 259 15.8% 

35 5.0% 51 4.9% 67 4.1% 

Total Foods 39 100.0% 59 100.0% Total Dairy 4 10.8% 20 33.6% Total Meats 3 7.6% 4 7.1% Total Fish 0.33 0.8% 0.22 0.4% 0Total Eggs 0.87 2.2% 0.93 1.6% 0Total Grains 5 12.0% 6 10.0% Total Vegetables 9 22.7% 10 16.1% Total Fruits 14 36.1% 15 25.0% Total Fats a 2 5.1% 3 4.7% 

Age 6 to <11 years (g/day, as consumed) Age 6 to <11 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

725 100.0% 1,061 100.0% 1,727 100.0% 

76 10.5% 366 34.5% 883 51.1% 66 9.2% 91 8.6% 105 6.1% 

6 0.8% 7 0.7% 6 0.3% 

16 2.3% 17 1.6% 18 1.1% 

101 13.9% 116 10.9% 151 8.7% 202 27.9% 205 19.4% 245 14.2% 198 27.3% 178 16.7% 221 12.8% 

43 6.0% 56 5.3% 73 4.2% 

Total Foods 21 100.0% 38 100.0% Total Dairy 2 11.6% 13 34.8% Total Meats 2 9.9% 3 8.2% Total Fish 0.18 0.8% 0.22 0.6% 0Total Eggs 0.52 2.4% 0.52 1.4% 0Total Grains 3 14.1% 4 10.9% Total Vegetables 6 27.0% 7 18.7% Total Fruits 6 25.9% 7 17.8% Total Fats a 1 6.2% 2 5.4% 

Age 11 to <16 years (g/day, as consumed) Age 11 to <16 years (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

727 100.0% 1,111 100.0% 2,045 100.0% 

38 5.2% 299 26.9% 1,004 49.1% 58 8.0% 118 10.6% 161 7.9% 10 1.4% 11 1.0% 12 0.6% 16 2.2% 22 2.0% 26 1.3% 

103 14.2% 137 12.4% 181 8.9% 234 32.2% 265 23.9% 332 16.2% 213 29.3% 176 15.8% 204 10.0% 

42 5.8% 66 6.0% 104 5.1% 

Total Foods 12 100.0% 23 100.0% Total Dairy 0.59 4.9% 6 26.0% Total Meats 1 9.3% 2 10.9% Total Fish 0.15 1.3% 0.14 0.6% 0Total Eggs 0.30 2.5% 0.34 1.5% 0Total Grains 2 14.2% 3 11.5% Total Vegetables 4 32.4% 6 24.5% Total Fruits 3 27.0% 4 17.1% Total Fats a 0.75 6.3% 1 6.1% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 16 to <21 years (g/day, as consumed) Age 16 to <21 years (g/kg-day, as con

Total Foods Total Dairy Total Meats 

610 

22 42 

100.0% 

3.5% 6.8% 

1,017 

204 128 

100.0% 

20.1% 12.6% 

2,379 

923 256 

100.0% 

38.8% 10.8% 

Total Foods Total Dairy Total Meats 

9 

0.35 

0.63 

100.0% 

3.8% 

6.8% 

15 

3 

2 

100.0% 

19.1% 

13.4% 

Total Fish 12 1.9% 12 1.2% 8 0.3% Total Fish 0.17 1.8% 0.14 0.9% 0

Total Eggs Total Grains 

13 

87 

2.2% 

14.3% 

19 

140 

1.8% 

13.8% 

28 

233 

1.2% 

9.8% 

Total Eggs Total Grains 

0.19 

1 

2.0% 

14.6% 

0.28 

2 

1.8% 

14.3% 

0

Total Vegetables Total Fruits 

202 

177 

33.1% 

29.1% 

305 

133 

29.9% 

13.1% 

492 

282 

20.7% 

11.9% 

Total Vegetables Total Fruits 

3 

3 

34.0% 

28.1% 

5 

2 

30.4% 

12.2% 

Total Fats a 34 5.6% 68 6.6% 127 5.3% Total Fats a 0.51 5.5% 1 6.8% 

a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foo

meats. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

14-26 September 2008 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age Birth to <1month (g/day, as consumed)b Age Birth to <1month (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

67 100.0% - - - -41 61.5% - - - -

0 0.0% - - - -0 0.0% - - - -0 0.0% - - - -

0.44 0.7% - - - -

5 7.7% - - - -

0.88 1.3% - - - -

19 28.3% - - - -

Total Foods 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 0.14 0.7% - - Total Vegetables 2 7.7% - - Total Fruits 0.21 1.1% - - Total Fats a 6 28.4% - - 

Age 1 to <3 months (g/day, as consumed)b Age 1 to <3 months (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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 Foods 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 0.23 1.4% - - Total Vegetables 3 16.6% - - Total Fruits 0.90 5.5% - - Total Fats a 4 26.5% - - 

Age 3 to <6 months (g/day, as consumed) c Age 3 to <6 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

196 100.0% - - 410 100.0% 

55 28.3% - - 159 38.8% 

2 0.8% - - 28 6.8% 0 0.0% - - 17 4.1% 

0.22 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 Foods 28 100.0% - - Total Dairy 8 28.9% - - Total Meats 0.20 0.7% - - Total Fish 0 0.0% - - Total Eggs 0.022 0.1% - - 0Total Grains 1 3.8% - - Total Vegetables 5 17.1% - - Total Fruits 9 33.9% - - Total Fats a 4 14.5% - - 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-27
 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 6 to <12 months (g/day, as consumed)d Age 6 to <12 months (g/kg-day, as con

Total Foods 799 100.0% - - 770 100.0% Total Foods 81 100.0% - - 

Total Dairy Total Meats 

334 

38 

41.8% -

4.7% -

- 287 - 46 

37.3% 

6.0% 

Total Dairy Total Meats 

34 

4 

41.8% -

4.7% -

- 

- 

Total Fish 0 0.0% - - 7 0.9% Total Fish 0 0.0% - - 0

Total Eggs Total Grains 

11 47 

1.4% -5.9% -

- 14 - 66 

1.9% 8.6% 

Total Eggs Total Grains 

1 

5 

1.4% -

5.9% -

- 

- 

Total Vegetables Total Fruits 

101 227 

12.6% -28.4% -

- 117 - 194 

15.3% 25.2% 

Total Vegetables Total Fruits 

10 

23 

12.6% -

28.4% -

- 

- 

Total Fats a 37 4.7% - - 36 4.7% Total Fats a 4 4.7% - - 

Age 1 to <2 years (g/day, as consumed) d Age 1 to <2 years (g/kg-day, as consu

Total Foods 1032 100.0% - - 1,139 100.0% Total Foods 90 100.0% - - 

Total Dairy Total Meats 

496 

46 

48.1% -

4.5% -

- 461 - 56 

40.5% 

4.9% 

Total Dairy Total Meats 

43 

4 

48.2% -

4.4% -

- 

- 

Total Fish 0 0.0% - - 26 2.3% Total Fish 0 0.0% - - 

Total Eggs Total Grains 

14 65 

1.4% -6.3% -

- 19 - 76 

1.7% 6.7% 

Total Eggs Total Grains 

1 

6 

1.3% -

6.2% -

- 

- 

Total Vegetables Total Fruits 

118 247 

11.4% -24.0% -

- 151 - 300 

13.2% 26.3% 

Total Vegetables Total Fruits 

10 

22 

11.4% -

24.0% -

- 

- 

Total Fats a 39 3.8% - - 43 3.8% Total Fats a 3 3.8% - - 

Age 2 to <3 years (g/day, as consumed) d Age 2 to <3 years(g/kg-day, as consu

Total Foods Total Dairy Total Meats 

1015 

381 

62 

100.0% -

37.6% -

6.1% -

- 1,107 - 424 - 53 

100.0% 

38.3% 

4.8% 

Total Foods Total Dairy Total Meats 

73 

28 

4 

100.0% -

37.9% -

6.0% -

- 

- 

- 

Total Fish 0 0.0% - - 31 2.8% Total Fish 0 0.0% - - Total Eggs Total Grains 

18 81 

1.8% -7.9% -

- 17 - 84 

1.6% 7.6% 

Total Eggs Total Grains 

1 

6 

1.7% -

7.9% -

- 

- 

Total Vegetables Total Fruits 

144 276 

14.2% -27.2% -

- 142 - 304 

12.8% 27.4% 

Total Vegetables Total Fruits 

10 

20 

14.1% -

27.0% -

- 

- 

Total Fats a 42 4.2% - - 43 3.9% Total Fats a 3 4.2% - - 

Page Child-Specific Exposure Factors Handbook 

14-28 September 2008 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age 3 to <6 years (g/day, as consumed)d Age 3 to <6 years (g/kg-day, as consu

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

1,053 100.0% - - 1,156 100.0% 

390 37.1% - - 399 34.5% 

76 7.2% - - 62 5.3% 

0 0.0% - - 43 3.7% 

16 1.5% - - 17 1.4% 

101 9.6% - - 103 8.9% 168 15.9% - - 193 16.7% 237 22.5% - - 273 23.6% 

50 4.8% - - 50 4.3% 

Total Foods 60 100.0% - - Total Dairy 22 37.1% - - Total Meats 4 7.1% - - Total Fish 0 0.0% - - Total Eggs 0.88 1.5% - - Total Grains 6 9.5% - - Total Vegetables 9 15.8% - - Total Fruits 14 22.7% - - Total Fats a 3 4.7% - - 

Age 6 to <11 years (g/day, as consumed) d Age 6 to <11 years (g/kg-day, as consu

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

1,109 100.0% - - 1,234 100.0% 

408 36.8% - - 430 34.8% 

89 8.0% - - 76 6.2% 

0 0.0% - - 51 4.1% 

15 1.3% - - 22 1.8% 

119 10.7% - - 126 10.2% 208 18.8% - - 233 18.9% 190 17.1% - - 218 17.7% 

58 5.2% - - 61 4.9% 

Total Foods 40 100.0% - - Total Dairy 15 37.0% - - Total Meats 3 7.9% - - Total Fish 0 0.0% - - Total Eggs 0.53 1.3% - - 0Total Grains 4 10.7% - - Total Vegetables 7 18.5% - - Total Fruits 7 17.3% - - Total Fats a 2 5.2% - - 

Age 11 to <16 years (g/day, as consumed) d Age 11 to <16 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

1,197 100.0% - - 1,378 100.0% 

372 31.1% - - 397 28.8% 117 9.8% - - 104 7.5% 

0 0.0% - - 72 5.2% 

17 1.4% - - 28 2.0% 

135 11.3% - - 146 10.6% 277 23.1% - - 310 22.5% 190 15.8% - - 226 16.4% 

69 5.8% - - 76 5.5% 

Total Foods 24 100.0% - - Total Dairy 7 31.1% - - Total Meats 2 9.7% - - Total Fish 0 0.0% - - Total Eggs 0.34 1.4% - - 0Total Grains 3 11.3% - - Total Vegetables 5 22.9% - - Total Fruits 4 16.2% - - Total Fats a 1 5.7% - - 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-29
 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 16 to <21 years (g/day, as consumed)d Age 16 to <21 years (g/kg-day, as con

Total Foods 1,171 100.0% - - 1,339 100.0% Total Foods 18 100.0% - - Total Dairy Total Meats 

288 143 

24.6% -12.2% -

- 261 - 139 

19.5% 10.4% 

Total Dairy Total Meats 

4 2 

24.5% -11.9% -

- - 

Total Fish 0 0.0% - - 86 6.5% Total Fish 0 0.0% - - Total Eggs Total Grains 

20 

146 

1.7% -

12.5% -

- 21 - 162 

1.6% 

12.1% 

Total Eggs Total Grains 

0.30 

2 

1.7% -

12.5% -

- 0

- 

Total Vegetables Total Fruits 

325 

160 

27.8% -

13.7% -

- 357 

- 219 

26.6% 

16.3% 

Total Vegetables Total Fruits 

5 

2 

27.9% -

13.9% -

- 

- 

Total Fats a 75 6.4% - - 80 6.0% Total Fats a 1 6.4% - - 

a b c d 

Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foomeats. All individuals in this sample group consumed 0 grams/day of fish. Therefore, only low-end consumers are reported. Only one individual in this sample group consumed more than 0 grams/day of fish. Therefore, this sample is reported in the high-end consumother samples are placed in the low-end consumer group. All individuals in this sample group below the 80th percentile consumed 0 grams/day of fish. Therefore, only high-end and low-end consum

reported. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

14-30 September 2008 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age Birth to <1month (g/day, as consumed)b Age Birth to <1month (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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% 

0.58 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 Foods 14 100.0% - - Total Dairy 10 69.6% - - Total Meats 0 0.0% - - Total Fish 0 0.0% - - Total Eggs 0 0.0% - - Total Grains 0.18 1.3% - - 0Total Vegetables 0 0.0% - - Total Fruits 0 0.0% - - Total Fats a 4 29.1% - - 

Age 1 to <3 months (g/day, as consumed) b Age 1 to <3 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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% 

0.91 1.9% - - 2 1.0% 

0 0.0% - - 89 52.0% 0 0.0% - - 18 10.2% 

14 28.9% - - 40 23.4% 

Total Foods 11 100.0% - - Total Dairy 7 69.4% - - Total Meats 0 0.0% - - Total Fish 0 0.0% - - Total Eggs 0 0.0% - - Total Grains 0.17 1.7% - - 0Total Vegetables 0 0.0% - - Total Fruits 0 0.0% - - Total Fats a 3 29.0% - - 

Age 3 to <6 months (g/day, as consumed) Age 3 to <6 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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% 0.43 0.3% 0 0.0% 0 0.0% 0.58 0.4% 0.094 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 Foods 11 100.0% 21 100.0% Total Dairy 7 68.1% 8 37.2% Total Meats 0 0.0% 0.32 1.5% 0Total Fish 0 0.0% 0.057 0.3% Total Eggs 0 0.0% 0.10 0.5% 0Total Grains 0.35 3.2% 1 6.6% Total Vegetables 0 0.0% 3 15.1% Total Fruits 0 0.0% 4 20.8% Total Fats a 3 28.5% 4 16.9% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-31
 
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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 6 to <12 months (g/day, as consumed) Age 6 to <12 months (g/kg-day, as con

Total Foods 189 100.0% 461 100.0% 951 100.0% Total Foods 21 100.0% 57 100.0% 

Total Dairy Total Meats 

91 

8 

48.3% 

4.0% 

129 

17 

28.0% 

3.6% 

207 

37 

21.8% 

3.9% 

Total Dairy Total Meats 

10 

0.73 

48.1% 

3.6% 

19 

2 

33.2% 

4.3% 

Total Fish 0.80 0.4% 0.80 0.2% 0.16 0.0% Total Fish 0.088 0.4% 0.063 0.1% 0

Total Eggs Total Grains 

4 

23 

1.9% 

12.1% 

9 

31 

1.9% 

6.8% 

8 

41 

0.8% 

4.3% 

Total Eggs Total Grains 

0.34 

2 

1.7% 

11.4% 

0.59 

4 

1.0% 

6.5% 

0

Total Vegetables Total Fruits 

18 15 

9.4% 7.7% 

83 

158 

18.1% 34.3% 

160 459 

16.8% 48.2% 

Total Vegetables Total Fruits 

2 

2 

9.3% 

8.4% 

10 

18 

16.9% 

30.8% 

Total Fats a 31 16.3% 31 6.8% 35 3.6% Total Fats a 3 16.8% 4 6.6% 

Age 1 to <2 years (g/day, as consumed) Age 1 to <2 years (g/kg-day, as consu

Total Foods 796 100.0% 1,048 100.0% 1,499 100.0% Total Foods 68 100.0% 88 100.0% 

Total Dairy Total Meats 

578 

35 

72.7% 

4.5% 

535 

46 

51.0% 

4.4% 

425 

62 

28.4% 

4.2% 

Total Dairy Total Meats 

49 

3 

71.8% 

4.7% 

44 

4 

49.6% 

4.5% 

Total Fish 0.93 0.1% 3 0.3% 5 0.4% Total Fish 0.16 0.2% 0.24 0.3% 0

Total Eggs Total Grains 

8 

49 

1.0% 

6.2% 

16 

65 

1.5% 

6.2% 

17 

77 

1.1% 

5.1% 

Total Eggs Total Grains 

0.77 

4 

1.1% 

6.2% 

1 

6 

1.2% 

6.9% 

Total Vegetables Total Fruits 

56 26 

7.1% 3.2% 

123 210 

11.7% 20.1% 

179 687 

11.9% 45.8% 

Total Vegetables Total Fruits 

5 

2 

7.1% 

3.4% 

11 

18 

12.6% 

20.5% 

Total Fats a 36 4.6% 41 3.9% 39 2.6% Total Fats a 3 4.7% 3 3.7% 

Age 2 to <3 years (g/day, as consumed) Age 2 to <3 years(g/kg-day, as consu

Total Foods Total Dairy Total Meats 

601 308 

53 

100.0% 

51.2% 

8.8% 

942 352 

59 

100.0% 

37.4% 

6.3% 

1,589 

384 

64 

100.0% 

24.1% 

4.0% 

Total Foods Total Dairy Total Meats 

43 

22 

4 

100.0% 

51.3% 

8.8% 

69 

27 

4 

100.0% 

39.3% 

6.0% 

Total Fish 2 0.3% 4 0.5% 5 0.3% Total Fish 0.14 0.3% 0.25 0.4% 0

Total Eggs Total Grains 

14 72 

2.3% 

12.0% 

18 80 

2.0% 8.5% 

20 91 

1.3% 5.7% 

Total Eggs Total Grains 

0.99 

5 

2.3% 

12.0% 

1 6 

1.9% 8.6% 

Total Vegetables Total Fruits 

81 24 

13.4% 

4.0% 

141 237 

15.0% 25.1% 

202 765 

12.7% 48.1% 

Total Vegetables Total Fruits 

6 

2 

13.8% 

3.7% 

10 

17 

14.0% 

24.6% 

Total Fats a 38 6.3% 40 4.2% 46 2.9% Total Fats a 3 6.3% 3 4.1% 

14-

Pag32 e Child-Specific Exposure Fa

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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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age 3 to <6 years (g/day, as consumed) Age 3 to <6 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

731 100.0% 1,014 100.0% 1,594 100.0% 388 53.1% 385 38.0% 401 25.1% 

60 8.2% 74 7.3% 81 5.1% 

4 0.5% 7 0.7% 9 0.6% 

13 1.7% 14 1.4% 21 1.3% 92 12.5% 96 9.4% 113 7.1% 92 12.5% 174 17.1% 231 14.5% 27 3.6% 199 19.6% 668 41.9% 45 6.1% 49 4.9% 53 3.3% 

Total Foods 40 100.0% 58 100.0% Total Dairy 21 52.7% 22 38.2% Total Meats 3 8.6% 4 7.0% Total Fish 0.17 0.4% 0.32 0.6% 0Total Eggs 0.63 1.6% 0.81 1.4% Total Grains 5 12.4% 6 10.3% Total Vegetables 5 13.0% 10 16.5% Total Fruits 1 3.4% 11 19.5% Total Fats a 2 6.1% 3 4.9% 

Age 6 to <11 years (g/day, as consumed) Age 6 to <11 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

784 100.0% 1,068 100.0% 1,664 100.0% 385 49.2% 406 38.0% 448 26.9% 

76 9.7% 88 8.3% 98 5.9% 

5 0.6% 6 0.6% 8 0.5% 

16 2.1% 16 1.5% 17 1.0% 

105 13.3% 117 11.0% 127 7.6% 103 13.2% 213 19.9% 313 18.8% 

26 3.4% 144 13.5% 559 33.6% 48 6.2% 59 5.5% 64 3.9% 

Total Foods 23 100.0% 38 100.0% Total Dairy 11 47.0% 14 37.6% Total Meats 2 10.1% 3 8.9% Total Fish 0.18 0.8% 0.15 0.4% 0Total Eggs 0.53 2.3% 0.58 1.5% 0Total Grains 3 13.8% 5 11.8% Total Vegetables 3 13.8% 7 19.1% Total Fruits 0.82 3.6% 5 13.3% Total Fats a 1 6.4% 2 5.4% 

Age 11 to <16 years (g/day, as consumed) Age 11 to <16 years (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

709 100.0% 1,149 100.0% 1,911 100.0% 301 42.4% 362 31.5% 395 20.7% 

91 12.8% 112 9.7% 146 7.7% 

3 0.4% 10 0.8% 14 0.7% 

13 1.8% 20 1.7% 24 1.3% 

106 15.0% 136 11.8% 165 8.6% 125 17.7% 286 24.9% 458 24.0% 

13 1.9% 136 11.8% 597 31.2% 49 6.9% 66 5.8% 87 4.5% 

Total Foods 12 100.0% 23 100.0% Total Dairy 5 42.0% 8 33.1% Total Meats 1 12.4% 2 9.8% Total Fish 0.054 0.5% 0.12 0.5% 0Total Eggs 0.22 1.9% 0.40 1.7% 0Total Grains 2 14.8% 3 12.1% Total Vegetables 2 18.2% 5 23.0% Total Fruits 0.25 2.2% 3 12.3% Total Fats a 0.81 7.0% 1 5.9% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-33
 
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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 16 to <21 years (g/day, as consumed) Age 16 to <21 years (g/kg-day, as con

Total Foods Total Dairy Total Meats 

624 

238 

76 

100.0% 

38.1% 12.2% 

970 

203 112 

100.0% 

21.0% 11.5% 

2,353 

449 245 

100.0% 

19.1% 10.4% 

Total Foods Total Dairy Total Meats 

9 

4 1 

100.0% 

39.0% 11.7% 

16 

3 

2 

100.0% 

21.0% 

12.7% 

Total Fish 8 1.2% 15 1.6% 17 0.7% Total Fish 0.13 1.4% 0.13 0.8% 0

Total Eggs Total Grains 

21 

100 

3.3% 

16.1% 

16 

138 

1.6% 

14.2% 

30 

211 

1.3% 9.0% 

Total Eggs Total Grains 

0.31 

1 

3.4% 

16.2% 

0.41 

2 

2.5% 

14.6% 

0

Total Vegetables Total Fruits 

109 

18 

17.5% 

2.9% 

283 

121 

29.2% 

12.5% 

615 

644 

26.1% 

27.4% 

Total Vegetables Total Fruits 

2 

0.17 

17.9% 

1.8% 

5 

1 

30.7% 

9.1% 

Total Fats a 46 7.3% 66 6.8% 116 4.9% Total Fats a 0.66 7.2% 1 7.5% 

a b 

Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foomeats. All individuals in this sample group below the 75th percentile consumed 0 grams/day of fruits and vegetables. Therefore, only high-end and 

consumer groups are reported. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

14-

Pag34 e Child-Specific Exposure Fa

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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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age Birth to <1month (g/day, as consumed) Age Birth to <1month (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

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% 

0.031 0.3% 0 0.0% 4 2.2% 

8 66.1% 2 3.4% 0.78 0.4% 0 0.0% 0 0.0% 0 0.0% 3 27.1% 18 29.2% 52 28.4% 

Total Foods 4 100.0% 18 100.0% Total Dairy 0 0.0% 12 67.1% 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 0.0086 0.2% 0 0.0% Total Vegetables 2 64.4% 0.65 3.7% 0Total Fruits 0 0.0% 0 0.0% Total Fats a 1 27.5% 5 29.2% 

Age 1 to <3 months (g/day, as consumed) Age 1 to <3 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

36 100.0% 84 100.0% 166 100.0% 

0 0.0% 19 22.4% 109 65.6% 0 0.0% 0 0.0% 0.037 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 

0.32 0.9% 1 1.2% 0 0.8% 

21 58.8% 42 50.7% 4 2.7% 

2 4.3% 0.034 0.0% 6 3.7% 

10 26.7% 21 25.4% 45 27.2% 

Total Foods 7 100.0% 14 100.0% Total Dairy 0 0.0% 3 24.0% Total Meats 0 0.0% 0 0.0% 0Total Fish 0 0.0% 0 0.0% Total Eggs 0 0.0% 0 0.0% Total Grains 0.054 0.8% 0.29 2.0% 0Total Vegetables 4 57.8% 7 48.7% 0Total Fruits 0.37 5.4% 0.0067 0.0% Total Fats a 2 26.4% 4 25.0% 

Age 3 to <6 months (g/day, as consumed) Age 3 to <6 months (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

132 100.0% 217 100.0% 346 100.0% 

0 0.0% 59 27.0% 160 46.3% 

0.59 0.4% 2 1.0% 4 1.1% 

0 0.0% 0 0.0% 0.44 0.1% 0 0.0% 0.38 0.2% 0.64 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 Foods 19 100.0% 32 100.0% Total Dairy 0 0.0% 8 24.8% Total Meats 0.10 0.5% 0.22 0.7% 0Total Fish 0 0.0% 0 0.0% 0Total Eggs 0 0.0% 0.11 0.3% 0Total Grains 0.84 4.5% 1 3.8% Total Vegetables 7 35.6% 4 13.7% Total Fruits 8 43.0% 14 45.8% Total Fats a 2 12.2% 3 10.7% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-35
 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 6 to <12 months (g/day, as consumed) Age 6 to <12 months (g/kg-day, as con

Total Foods 317 100.0% 368 100.0% 1,285 100.0% Total Foods 36 100.0% 43 100.0% 

Total Dairy Total Meats 

0.045 

11 

0.0% 

3.4% 

71 

16 

19.2% 

4.4% 

833 

41 

64.8% 

3.2% 

Total Dairy Total Meats 

0.0062 

1 

0.0% 

3.5% 

8 

2 

18.2% 

4.8% 

Total Fish 0.0086 0.0% 1 0.3% 0.28 0.0% Total Fish 0 0.0% 0.15 0.3% 0

Total Eggs Total Grains 

3 

27 

0.9% 

8.6% 

5 

23 

1.4% 

6.3% 

6 

46 

0.5% 

3.6% 

Total Eggs Total Grains 

0.35 

3 

1.0% 

7.9% 

0.92 

3 

2.1% 

7.7% 

0

Total Vegetables Total Fruits 

114 137 

35.9% 43.3% 

75 

147 

20.4% 39.9% 

106 211 

8.2% 

16.4% 

Total Vegetables Total Fruits 

13 

16 

35.3% 

44.6% 

8 

18 

17.9% 

40.7% 

Total Fats a 20 6.4% 30 8.2% 40 3.1% Total Fats a 2 6.3% 4 8.1% 

Age 1 to <2 years (g/day, as consumed) Age 1 to <2 years (g/kg-day, as consu

Total Foods 601 100.0% 989 100.0% 1,700 100.0% Total Foods 55 100.0% 86 100.0% Total Dairy Total Meats 

40 43 

6.7% 7.1% 

451 

51 

45.6% 

5.2% 

1,170 

45 

68.8% 

2.6% 

Total Dairy Total Meats 

3 4 

6.1% 7.2% 

38 

4 

44.0% 

4.8% 

Total Fish 3 0.5% 4 0.4% 3 0.2% Total Fish 0.28 0.5% 0.50 0.6% 0

Total Eggs Total Grains 

14 57 

2.3% 9.5% 

15 65 

1.5% 6.5% 

18 63 

1.1% 3.7% 

Total Eggs Total Grains 

1 

5 

2.3% 

9.5% 

2 

6 

1.8% 

6.9% 

Total Vegetables Total Fruits 

139 268 

23.1% 44.7% 

120 240 

12.1% 24.3% 

112 226 

6.6% 

13.3% 

Total Vegetables Total Fruits 

12 

25 

21.8% 

46.3% 

11 

21 

13.0% 

24.5% 

Total Fats a 29 4.8% 38 3.8% 58 3.4% Total Fats a 3 4.7% 3 3.7% 

Age 2 to <3 years (g/day, as consumed) Age 2 to <3 years(g/kg-day, as consu

Total Foods Total Dairy Total Meats 

661 

48 61 

100.0% 

7.3% 9.3% 

996 348 

63 

100.0% 

34.9% 

6.3% 

1,528 

885 

55 

100.0% 

57.9% 

3.6% 

Total Foods Total Dairy Total Meats 

47 

3 4 

100.0% 

7.2% 9.4% 

72 

24 

4 

100.0% 

33.7% 

6.2% 

Total Fish 2 0.3% 6 0.6% 5 0.3% Total Fish 0.16 0.3% 0.27 0.4% 0

Total Eggs Total Grains 

25 78 

3.8% 

11.9% 

20 82 

2.1% 8.2% 

19 86 

1.3% 5.6% 

Total Eggs Total Grains 

2 

5 

3.7% 

11.6% 

1 

6 

1.5% 

8.5% 

Total Vegetables Total Fruits 

163 237 

24.7% 35.8% 

144 279 

14.5% 28.0% 

137 277 

9.0% 

18.1% 

Total Vegetables Total Fruits 

12 

17 

24.6% 

36.4% 

10 

22 

14.0% 

30.2% 

Total Fats a 37 5.5% 41 4.1% 55 3.6% Total Fats a 3 5.5% 3 4.2% 

Page Child-Specific Exposure Factors Handbook 

14-36 September 2008 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers 

Intake Percent Intake Percent Intake Percent 

Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent In

Age 3 to <6 years (g/day, as consumed) Age 3 to <6 years (g/kg-day, as consu

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

725 100.0% 1,047 100.0% 1,612 100.0% 

64 8.9% 355 33.9% 886 55.0% 75 10.4% 72 6.9% 70 4.3% 

4 0.6% 6 0.5% 6 0.4% 

19 2.6% 15 1.4% 18 1.1% 87 12.1% 104 9.9% 116 7.2% 

168 23.2% 173 16.5% 183 11.3% 253 34.9% 257 24.5% 251 15.6% 

40 5.6% 49 4.7% 63 3.9% 

Total Foods 41 100.0% 58 100.0% Total Dairy 4 8.8% 20 34.2% Total Meats 4 10.6% 4 6.6% Total Fish 0.22 0.5% 0.29 0.5% 0Total Eggs 1 2.6% 0.87 1.5% 0Total Grains 5 12.1% 6 9.9% Total Vegetables 10 23.8% 9 16.3% Total Fruits 14 34.0% 14 24.7% Total Fats a 2 5.7% 3 4.7% 

Age 6 to <11 years (g/day, as consumed) Age 6 to <11 years (g/kg-day, as cons

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

766 100.0% 1,053 100.0% 1,722 100.0% 

63 8.2% 372 35.4% 892 51.8% 99 12.9% 80 7.6% 87 5.1% 

6 0.8% 5 0.5% 6 0.4% 

17 2.2% 14 1.3% 17 1.0% 

105 13.7% 113 10.7% 152 8.8% 221 28.9% 214 20.3% 242 14.0% 194 25.3% 175 16.6% 227 13.2% 

49 6.4% 56 5.3% 70 4.1% 

Total Foods 25 100.0% 38 100.0% Total Dairy 2 8.1% 13 34.2% Total Meats 3 13.2% 3 8.0% Total Fish 0.19 0.8% 0.19 0.5% 0Total Eggs 0.55 2.3% 0.67 1.8% 0Total Grains 3 13.6% 4 10.7% Total Vegetables 7 29.5% 8 19.7% Total Fruits 6 24.4% 7 17.8% Total Fats a 2 6.6% 2 5.2% 

Age 11 to <16 years (g/day, as consumed) Age 11 to <16 years (g/kg-day, as con

Total Foods Total Dairy Total Meats Total Fish Total Eggs Total Grains Total Vegetables Total Fruits Total Fats a 

747 100.0% 1,094 100.0% 2,020 100.0% 

22 3.0% 307 28.0% 1,017 50.3% 

102 13.6% 101 9.2% 134 6.7% 

8 1.1% 9 0.8% 12 0.6% 

20 2.7% 18 1.6% 25 1.2% 

104 13.9% 133 12.2% 181 9.0% 239 32.0% 265 24.2% 322 16.0% 197 26.4% 180 16.4% 204 10.1% 

47 6.2% 62 5.6% 100 5.0% 

Total Foods 13 100.0% 22 100.0% Total Dairy 0.38 2.9% 6 27.3% Total Meats 2 13.8% 2 9.6% Total Fish 0.14 1.0% 0.14 0.6% 0Total Eggs 0.35 2.6% 0.36 1.7% 0Total Grains 2 13.7% 3 12.2% Total Vegetables 4 33.0% 5 23.3% Total Fruits 3 25.7% 4 17.8% Total Fats a 0.83 6.2% 1 5.9% 

Child-Specific Exposure Factors Handbook Page
 

September 2008 14-37
 
 

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 

Consumers 

Mid-range 

Consumers 

High-end 

Consumers Food 

Group 

Low-end 

Consumers 

Mid-range 

Consumers 

Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent In

Age 16 to <21 years (g/day, as consumed) Age 16 to <21 years (g/kg-day, as con

Total Foods Total Dairy Total Meats 

647 

8 

101 

100.0% 

1.2% 

15.7% 

1,095 

197 

125 

100.0% 

18.0% 

11.4% 

2,233 

950 

197 

100.0% 

42.5% 

8.8% 

Total Foods Total Dairy Total Meats 

10 

0.12 

2 

100.0% 

1.2% 

15.1% 

17 

3 

2 

100.0% 

16.6% 

13.6% 

Total Fish 8 1.2% 16 1.5% 8 0.4% Total Fish 0.11 1.1% 0.16 0.9% 0

Total Eggs Total Grains 

12 

90 

1.8% 

13.9% 

28 

162 

2.5% 

14.8% 

27 

217 

1.2% 

9.7% 

Total Eggs Total Grains 

0.17 

1 

1.7% 

14.1% 

0.39 

2 

2.2% 

14.0% 

0

Total Vegetables Total Fruits 

228 

152 

35.2% 

23.5% 

324 

154 

29.6% 

14.1% 

438 

249 

19.6% 

11.2% 

Total Vegetables Total Fruits 

4 

2 

35.8% 

23.9% 

5 

3 

28.6% 

16.1% 

Total Fats a 37 5.8% 73 6.7% 114 5.1% Total Fats a 0.58 5.6% 1 6.5% 

a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foo

meats. 

Source: Based on U.S. EPA analysis of 1994-96, 1998 CSFII. 

Page Child-Specific Exposure Factors Handbook 

14-38 September 2008 
     

         

   

             

             

         

               

                

               

                 

       

         

           

                   

          

               

           

               

             

             

               

               

               

              

                 

           

            

             

               

             

          

               

             

       

           

              

               

             

               

             

                 

             

           

         

              

               

                 

             

                

             

          

             

             

          

             

             

           

               

             

                

           

           

             

               

           

             

               

           

       

                 

               

        

                 

            

              

             

             

     

             

               

           

             

             

          

                 

                 

                

               

             

           

             

             

           

                 

           

                    

Child­Specific 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 benefitsto nursing infants, including protection

against infection, increases in cognitive development,

and avoidance of allergies due to intolerance to cow’s

milk (AAP, 2005). Ingestion of human milk has also

been associated with a reduction in risk of postneonatal

death in the U.S. (Chen and Rogan, 2004). The

American Academy of Pediatrics recommends

exclusive breastfeeding for approximately the first six

months and supports the continuation of breastfeeding

for the first year and beyond if desired by the mother

and child (AAP, 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 breast­fed infants in the lipid portion

of human milk. Water soluble chemicals may also

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 breast­feeding occurs. Information on the fat

content of human milk is also needed for estimating

dose from human milk residue concentrationsthat have

been indexed to lipid content.

Severalstudies have generated data on human

milk intake. Typically, human milk intake has been

measured over a 24­hour 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 24­hour 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 bottlefed 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

significantlydifferent 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., 2002). 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 among 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 15­1).

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 EPA for this

factor. Following the recommendations, key studies on

human milk intake are summarized. Relevant data on

lipid content and fat intake, breast­feeding duration, and

the estimated percentage of the U.S. population that

breast­feeds are also 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 (Dewey et al., 1992; Drewett et

al.,1993; Gonzalez­Cossio et al., 1998). These studies

are not included in this chapter because they do no

focus on the exposure factor ofinterest. Otherstudiesin

the literature focus on formula intake. Since some baby

formula are prepared by adding water, these data are

presented in chapter 3 ­ Water Intake.

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 utilized

by the studiesto 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)

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

and Arcus­Arth et al. (2005), data were not presented

on a body weight basis. This is particularly important

since intake rates may be higher on a body weight basis

for younger infants. Also, the data used to derive the

recommendations are over 15 years old and the sample

size of the studies was small. Other populations of

concern such as mothers highly committed to

breastfeeding,sometimesfor periodslongerthan 1 year,

may not be captured by the studies presented in this

chapter.

15.2.1 Human Milk Intake

Asummary ofrecommended valuesfor human

milk and lipid intake rates is presented in Table 15­1

and the confidence ratings for these recommendations

are presented in Table 15­2. The human milk intake

rates for nursing infants that have been reported in the

studies described in this section are summarized in

Table 15­3 in units of mL/day and in Table 15­4 in

units of mL/kg­day (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. In order 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 Arcus­Arth et al.

(2005) were compiled for each month of the first year

of life. Recommendations were converted to mL/day

using a density of human milk of 1.03 g/mL rounded up

to two significant figures. Only two studies (i.e., Butte

et al., 1984 and Arcus­Arth 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, these were estimated by adding

two standard deviations to the mean value.

Recommendationsfor upper percentiles, whenmultiple

studies were available, were calculated as the midpoint

of the range of upper percentile values of the studies

available for each age in months. These month­bymonth intakes were composited to yield intake ratesfor

the standardized age groups by calculating a weighted

average. Recommendations are provided for the

population of exclusively breastfed infants since this

population may have higher exposures than partially

breastfed infants. Exclusively breastfed in this

chapter refers to infants whose sole source of milk

comes from human milk, with no other milk

substitutes. Partially breastfed 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 breastfed asinfants 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

Recommended lipid intake rates are presented

in Table 15­5. The table parallels the human milk

intake tables (Table 15­ 3). With the exception of the

data from Butte et al. (1984), the rates were calculated

assuming a lipid content of 4% (Butte et al.,1984; NAS,

1991; Maxwell and Burmaster, 1993). 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. Lipid intake rates on a body weight basis are

presented in Table 15­6. These were calculated from

the values presented in Table 15­4 multiplied by 4%

lipid content.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­1. Recommended Values for Human Milk And Lipid Intake Rates for Exclusively Breastfed Infants

Age Group

Mean Upper Percentilea

Source

mL/day mL/kg­day mL/day mL/kg­day

Human Milk Intake

Birth to <1 month 510 150 950 220 b

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

6 to <12 months 620 83 1,000 130 b, c, e, g

Lipid Intake h

Birth to <1 month 20 6.0 38 8.7 i

1 to <3 months 27 5.5 40 8.0 d, i

3 to <6 months 30 4.2 42 6.0 d, i

6 to <12 months 25 3.3 42 5.2 i

a Upper percentile is reported as mean plus 2 standard deviations. b Neville et al., 1988. c Pao et al., 1980. d Butte et al., 1984. e Dewey and Lönnerdal, 1983. f Butte et al., 2000. g Dewey et al., 1991b. h The recommended value for the lipid content of human milk is 4.0 percent. See Section 15.5. i Arcus­ Arth et al., 2005.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­2. 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 were relatively small (7­108).

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 8 studies indicated

correcting data for insensible water loss. Some biases may be

introduced by including partially­breastfed 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. Population 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 1980­2000. 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 to

day 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

Not very well characterized. Mothers committed to breastfeeding

over 1 year were not captured.

Not correcting for insensible water loss may underestimate intake.

Low

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­2. Confidence in Recommendations for Human Milk Intake (continued)

General Assessment Factors Rationale Rating

Evaluation and Review

Peer Review

Number and Agreement of Studies

The studies appeared in peer review journals.

There are 8 key studies. The results of studies from

different researchers are in agreement.

High

Overall Rating Medium

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­3. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast­fed 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 Mean Upper

0 <1 6 to 13 511 951 Neville et al., 1988 511 951 511 951

1

11

37

12

16

600

729

679 d

673

918

981

889

1,057

Pao et al., 1980

Butte et al., 1984

Neville et al., 1988

Dewey and Lönnerdal, 1983

670 961

692 977

2

10 to 12

19

40

679 d

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

740

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

­ed

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 1,000

622 1,024

7 12 700 1,000 Neville et al., 1988 700 1,006

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., 1991a; 1991b

Butte et al., 2000

410 904 410 904

a Calculated as the mean of the means. b Upper percentile is reported as mean plus 2 standard deviations. c Middle of the range of upper percentiles. d Calculated for infants 1 to < 2 months old. e Standard deviations and upper percentiles not calculated for small sample sizes.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­4. Human Milk Intake Rates Derived from Key Studies for Exclusively Breast­fed Infants (mL/kg/day)

Age

(months)

Number

of

Children

Mean

Intake

(mL/kgday)

Upper

Percentile

Consumption

(mL/kg­day)a

Source

Weighted Mean Intake

and Upper Percentile Consumption

(across all Key Studies)

(mL/kg­day)

Individual Age Composite Age

Groups

Meanb Upperc Mean Upperc

0 <1 9 to 25 150 217 Arcus­Arth et al, 2005 150 217 150 217

1 37

25

154

150

200

198

Butte et al., 1984

Arcus­Arth et al, 2005

152 199

144 187

2 40

25

125

144

161

188

Butte et al., 1984

Arcus­Arth et al, 2005

135 175

3 37

108

114

127

152

163

Butte et al., 1984

Arcus­Arth et al, 2005

121 158

111 149 4 41

57

108

112

142

148

Butte et al., 1984

Arcus­Arth et al, 2005

110 145

5 26 100 140 Arcus­Arth et al, 2005 100 140

6 39 101 141 Arcus­Arth et al, 2005 101 141

7 8 75 125 Arcus­Arth et al, 2005 75 125 83 130

9 57 72 118 Arcus­Arth et al, 2005 72 118

12 42 47 101 Arcus­Arth et al, 2005 47 101 47 101

a Calculated as the mean of the means. b Upper percentile is reported as mean plus 2 standard deviations. c Middle of the range of upper percentiles.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­5. Lipid Intake Rates Derived from Key Studies for Exclusively Breastfed 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 41

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

17

17

16

35

37

37

Neville et al., 1988

Dewey et al., 1991a; 1991b

Butte et al., 2000

16 36 16 36

a Except for Butte et al. 1984, values were calculated from table 15­3 using 4% lipid content. b Upper percentile is reported as mean plus 2 standard deviations. c Calculated as the mean of the means. d Middle of the range of upper percentiles. e Standard deviations and upper percentiles not calculated for small sample sizes.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­6. Lipid Intake Rates Derived from Key Studies for Exclusively Breast­fed Infants (mL/kg/day)a

Age

(months)

Number

of

Children

Mean Intake

(mL/kg­day)

Upper

Percentile

Consumption

(mL/kg­day)b

Source

Weighted Mean Intake

and Upper Percentile Consumptionb

(across all Key Studies)

(mL/kg­day)

Individual Age Composite Ages

Groups

Meanc Upperd Meane Upperd

0 <1 9 to 25 6.0 8.7 Arcus­Arth et al, 2005 6.2 8.7 6.0 8.7

37 5.7 9.1 Butte et al., 1984 1 5.9 8.9 25 6.0 8.7 Arcus­Arth et al, 2005

5.5 8.0

40 4.3 6.7 Butte et al., 1984 2 5.1 7.1 25 5.8 7.5 Arcus­Arth et al, 2005

37 3.7 6.1 Butte et al., 1984 3 4.4 6.3 108 5.1 6.5 Arcus­Arth et al, 2005

41 3.7 6.3 Butte et al., 1984 4.2 6.0 4 4.1 6.1 57 4.5 5.9 Arcus­Arth et al, 2005

5 26 4.0 5.6 Arcus­Arth et al, 2005 4.0 5.8

6 39 4.0 5.6 Arcus­Arth et al, 2005 4.0 5.6

7 8 3.0 5.0 Arcus­Arth et al, 2005 3.0 5.0

9 57 2.9 4.7 Arcus­Arth et al, 2005 2.9 4.7

3.3 5.2

12 42 1.9 4.0 Arcus­Arth et al, 2005 1.9 4.0 1.9 4.1

a Except for Butte et al. 1984, values were calculated from table 15­4 using 4% lipid

content. b Upper percentile is reported as mean plus 2 standard deviations. c Calculated as the mean of the means. d Middle of the range of upper percentiles.

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Child­Specific Exposure Factors Handbook

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 Breast­fed Infants

Pao et al. (1980) conducted a study of 22

healthy nursing infants to estimate human milk intake

rates. Infants were categorized as completely breast­fed

or partially breast­fed. Breastfeeding mothers were

recruited through LaLeche League groups. Except for

one black infant, all other infants were from white

middle­class families in southwestern Ohio. The goal

of the study was to enroll infants as close to one month

of age as possible and to obtain records near one, three,

six, and nine 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 24­hour 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 24­hour periods. Mean daily human

milk intake rates for the infants surveyed at each time

interval are presented in Table 15­7. These data (Table

15­7) are presented as they are reported in Pao et al.

(1980). For completely breast­fed 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 breast­fed 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 thisstudy isthat data for both

exclusively and partially breast­fed 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 ofinfantsin 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 Breast­fed Infants from

1 to 6 Months: Relation to Growth and

Fatness

Dewey and Lönnerdal (1983) monitored the

dietary intake of 20 nursing infants between the ages of

1 and 6 months. The number of study participants

dropped to 13 by the end of the sixth month. Most of

the infants in the study were exclusively breast­fed.

One infant’s intake was supplemented by formula

during the first and second month of life. During the

third, fourth, and fifth 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 sixth month.

According to Dewey andLönnerdal(1983),themothers

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

24­hour test weighings per month. Human milk intake

rates for the various age groups are presented in Table

15­8. Human milk intake averaged 673, 782, and 896

mL/day at 1, 3, and 6 months of age, respectively.

The advantage of thisstudy isthat it evaluated

nursing infants for a period of 6 months based on two

24­hour 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. Some infants

during the study period were given some formula (i.e.,

up to 5 infants during the fifth month). Without the raw

data, these subjects could not be excluded from the

study results. Thus, these subjects may affect the

results when deriving recommendationsfor exclusively

breastfed infants.

15.3.3	 Butte et al., 1984 ­ Human Milk Intake and

Growth in Exclusively Breast­fed Infants

Human milk intake was studied in exclusively

breast­fed infants during the first 4 months oflife (Butte

et al., 1984). Nursing mothers were recruited through

the Baylor Milk Bank Program in Texas. Forty­five

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

upper­socioeconomic stratum and had a mean age of

28.0 ± 3.1 years. A total of 41 mothers were white, 2

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

were Hispanic, 1 was Asian, and 1 was West Indian.

Infant growth progressed satisfactorily over the course

of the study.

The amount of milk ingested over a 24­hour

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 mean and standard deviation milk intake

difference based on weighing the bottle before and after

nine successive feedings, was estimated to be 3.2 ± 3.1

g. Test weighing occurred over a 24­hour period for

most study participants, but intake among several

infants wasstudied over longer periods(48 to 96 hours)

to assess individual variation in intake. It was reported

that 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 ofinfantformula and

rice water for 6 days during the fourth month because of

inadequate milk production. Converting values

reported as g/day to mL/day, using a conversion factor

of 1.03 g/mL, mean human milk intake ranged from702

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

(Table 15­9). Intakes were also calculated on the basis

of body weight (Table 15­9). Based on the results of

test weighings conducted over 48 to 96 hours, the

overall mean variation in individual daily intake was

estimated to be 7.9 ± 3.6 percent.

The advantage of this study is that data for a

larger number of exclusively breast­fed infants were

collected than in previous studies. However, data were

collected for infants up to 4 months and day­to­day

variability was not characterized for all infants. It was

reported that 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 fromthe study results. Therefore,

values derived from thisstudy for exclusively breastfed

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 first year of life.

The mothers were all multiparous, nonsmoking,

Caucasian women of middle­ to upper­socioeconomic

status living in Denver, CO. All women in the study

practiced exclusive breast­feeding 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/wk) after 4 months in three infants. The

estimated human milk intakesfor thisstudy are listed in

Table 15­10. Converting values reported as g/day to

mL/day, using a conversion factor of 1.03 g/mL, mean

humanmilk intakes were 748 mL/day, 713mL/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 during only a 24­hour

period. Consequently, these intake rates are based on

short­term data that do not account for day­to­day

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 be

an underestimate for the intake of exclusively breastfed

infants.

15.3.5	 Dewey et al., 1991a, b ­ (a) Maternal

Versus Infant Factors Related to Human

Milk Intake and Residual Volume: The

DARLING Study; (b) Adequacy of Energy

Intake Among Breast­fed 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 breast­fed for at least the first 12 months of life

(Dewey et al., 1991a, b). Subjects were non­randomly

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

selected through letters to new parents using birth

listing. 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. Seventy­three 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 did not consume solid foods until after the

first 4 months of age. The mothers were highly

educated and of “relatively high socioeconomic status.”

Humanmilk intake was estimated byweighing

the infants before and after each feeding and correcting

for insensible water loss. Test weighings were

conducted over a 4­day 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. 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 788 mL/day at 3 months and

435 mL/day at 12 months (Table 15­11). Based on the

estimated intakes at 3 months of age, variability

between individuals (coefficient of variation ([CV] =

16.3%) was higher than the average day­to­day

variability ([CV] = 8.9 ± 5.4%) for the infants in the

study (Dewey et al., 1991a).

The advantages ofthisstudy are that data were

collected over a relatively long­time (4 days) period at

each test interval, which would account for some dayto­day infant variability, and corrections for insensible

water loss were made. Data from this study are

assumed to represent exclusively breastfed infants,

since mothers were specifically recruited for that

purpose. It is, however, unclear from the Dewey et al.,

1991a 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 impact of infant feeding mode on growth and body

composition during the first two years of life. The

study was conducted in the Houston, Texas 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 3­month or 6­month study intervals, the

feeding history was taken. The mothers or caretakers

were questioned about breastfeeding 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 3­day

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 measured before and after each feeding. Using a

pre­weighing and post­weighing method, the intake of

formula and other foods and beverages was determined

for 3 days by the mothers using a digital scale and

recorded on predetermined forms.

The average duration of breastfeeding was

11.4 months (SD = 5.8). Butte et al.(2000) reported

that infants were exclusively breastfed for at least the

first four months except for the following: one was

weaned at 109 days, another received formula at 102

days and another given cereal at 106 days. The infant

feeding characteristics are shown in Table 15­12. The

intake of human milk for the infants are shown in Table

15­13. Converting valuesreported 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) (Table 15­13). Feeding practices by

percent for infants are shown in Table 15­14. The

mean weights are provided in Table 15­15.

Advantages of this study are that it provides

intake data for breastfed infantsforthe first four months

of life. The study also provides the mean weights for

the infants by feeding type and by gender. The

limitations of the study are that the sample size is small

and it is limited to one geographical location. The

authors did not indicate if results were corrected for

insensible weight loss. Since mothers could introduce

formula after 4 months, only the data for the 3­month

old infants can be considered exclusively breastfed.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

15.3.7	 Arcus­Arth et al., 2005 ­ Human Milk and

Lipid Intake Distributions for Assessing

Cumulative Exposure and Risk

Arcus­Arth et al. (2005) derived population

distributions for average daily milk and lipid intakes in

g/kg day for infants 0­6 months and 0­12 months of age

for infants fed according to the American Academy of

Pediatrics (AAP) recommendations. The AAP

recommends exclusively breastfeeding for the first 6

months of life, human milk as the only source of milk

age 1 year, with the introduction of solid foods after 6

months. The distributions were derived based on data

in the peer reviewed literature and datasets supplied by

the publication authors for infants 7 days and older

(Arcus­Arth et al., 2005). As cited in Arcus­Arth et al.

(2005), data sources included Dewey et al. (1991a,

199b), 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

ratesfor infants breastfed exclusively over the first year

and provides a regression line of intake versus age for

estimating short­term exposures. Arcus­Arth derived

human milk intake ratesfor the entire infant population

(nursing and non­nursing) from U.S. data on

consumption, prevalence and duration. Arcus­Arth et

al. (2005) defined exclusive breastfeeding (EBF) as

“breast milk is the sole source of calories, with no or

insignificant calories form other liquid or solid food

sources.” Predominant breastfeeding was described by

Arcus­Arth et al. (2005) as “breast milk isthe sole milk

source with significant caloriesfrom other foods.” The

data that were consistent with AAP advice were used to

construct the AAP dataset (Arcus­Arth et al., 2005).

The 0­12 months EBF dataset was created using 0­6

month AAP data and data from the EBF infants older

than 6 months of age. Because there are no data in the

AAP dataset for any individual infant followed at

regular, frequent intervals over the 12 month period,

population distributions were derived with assumptions

regarding individualintake variability overtime (ArcusArth et al., 2005). Two methods were used. In Method

1, the average population daily intake at each age is

described by a regression line, assuming normality.

Arcus­Arth et al. (2005) noted that age specific intake

data were consistent with the assumption of normality.

In Method 2, intake over time is simulated for 2500

hypothetical infants and the distribution intakes derived

from 2500 individual intakes (Arcus­Arth et al., 2005).

The population intake distribution was derived

following Method 1. Table 15­16 presents the means,

and standard deviations for intake data at different

ages; the variability was greatest for the 2 youngest and

3 oldest age groups. The values in Table 15­6 using

Method 1 were used to derive recommendations

presented in Table 15­4 since it provides data for the

fine age categories. 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/kg­day at 1 month, 127 mL/kg­day at 3 months, 101

mL/kg­day at 6 months, and 47 mL/kg­day at 12

months(Table 15­16). Time weighted average intakes

for larger age groups (i.e., 0 ­ 6 months, 0 ­ 12 months)

are presented in Table 15­17.

An advantage of this study is that it was

designed to represent the infant  population whose

mothersfollow the AAP recommendations. Intake was

calculated on a body weight basis. In addition, the data

used to derive the distributions were from peer

reviewed literature and datasets 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

breastfed infants today (Arcus­Arth et al., 2005). The

limitations of the study are that the data used were from

mothersthat were predominantly white, well nourished

and from mid or high socioeconomic status. ArcusArth 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 (Arcus­Arth et al., 2005).

According to Arcus­Arth et al. (2005), “Although few

infants are exclusively breastfed for 12 months, the

EBF distributions may represent a more highly exposed

subpopulation ofinfants exclusively breastfed in excess

of 6 months.”

15.4	 KEY STUDIES ON LIPID CONTENT

AND LIPID INTAKE FROM HUMAN

MILK

Human milk contains over 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 oftime that an infant

nurses, and 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%

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

± 0.4%) (NAS, 1991). This value is supported by

variousstudiesthat evaluated lipid content from human

milk. 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 Breast­fed 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 breast­fed infants. The study was

conducted with over 40 women during a 4­month

period. The mean lipid content of human milk at

various infants’ ages is presented in Table 15­18. The

overall lipid content for the 4­month study period was

3.43 ± 0.69 %  (3.4%). Butte et al. (1984) also

calculated lipid intakes from 24­hour human milk

intakes and the lipid content of the human milk

samples. Lipid intake was estimated to range from22.9

mL/day (3.7 mL/kg­day) to 27.2 mL/day (5.7 mL/kgday).

The number of women included in this study

was small, and these women were selected primarily

from middle to upper socioeconomic classes. Thus,

data on human milk lipid content from this study may

not be entirely representative of human milk lipid

content among the U.S. population. Also, these

estimates are based on short­term data, and day­to­day

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 first year of

lactation. Nursing mothers were recruited through the

Nursing Mothers’ Association of Australia. All infants

were completely breastfed on demand for at least 4

months. Complementary solid food was introduced

between 4­6 months of age. Mothers consumed their

own ad libitum diets throughout the study. Seventeen

mothersinitially 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 6months

due to the cessation of sample collection from 11

mothers, the maximum period of exclusive breastfeeding.

Milk samples were collected before and after

each feed from each breast over a 24­28 hour period.

Milk yield was determined by weighing the mother

before and after each feed from each breast. Insensible

waterloss was accounted for by weighing the mother 20

minutes after the end of each feeding. The rate of water

loss during this 20 minutes 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 ofthe 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.

Mean human milk production and composition

at each age interval are presented in Table 15­19. The

mean 24 hour milk production from both breasts was

798 (SD= 232) mL. The mean fat, lactose, and protein

contents(g/L) were 37.4 (SE= 0.6), 61.4 (SE =0.6), and

9.16 (SE= 0.19), respectively. Composition did not

vary between left and right breasts or preferred and

non­preferred breasts. Milk production was constant

for the first 6 months and thereafter steadily declined.

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 the changes in fat content.

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 mother­infant 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.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

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 5

healthy nursing women to determine the content of fat

in human milk and fat intake by infants during the first

year of lactation. Nursing mothers were recruited

through the Australian Breastfeeding Association or

from private healthcare facilities. All infants were

completely breastfed on demand for at least 4 months.

Complementary solid food wasintroduced between 4­6

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 24­28 hour period.

Fore­ and hind­milk 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

this 20 minutes was used to calculate insensible water

loss during the feeding.

Changes in volume of human milk produced

and milk fat content over the first year of lactation is

presented in Table 15­20. The mean volumes of milk

produced for both breasts combined were 812.13,

790.34, 911.38, 810.20, 677.35, and 505.10 mL/day at

1, 2, 4, 6, 9,and 12 months, respectively. The average

daily intake over the 12 months was 751.09 mL/day

with a mean fat content of 35.52 g/L. Their was a

significant difference in the proportional composition of

fatty acids over the course of lactation. Table 15­21

provides average fatty acid composition over the first

12 months of lactation. Additionally, fatty acid

composition varied over 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 mother­infant

pairs in the study was small (5 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	 Arcus­Arth et al., 2005 ­ Human Milk and

Lipid Intake Distributions for Assessing

Cumulative Exposure and Risk

Arcus­Arth et al. (2005) derived population

distributions for average daily milk and lipid intakes in

g/kg day for infants 0­6 months and 0­12 months of age

for infants fed according to the American Academy of

Pediatrics(AAP) recommendations. Lipid intakes were

calculated from lipid content and milk intakes were

measured on the same infant (Arcus­Arth et al., 2005).

Table 15­22 provides lipid intakes based on data from

Dewey et al. 1991a and Table 15­23 provides lipid

intakes calculated assuming 4% lipid content and milk

intake in the AAP dataset. Arcus­Arth 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 datasetssupplied 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

upper­socioeconomic status, however human milk

volume in mL/day is similar among all women except

for severely malnourished women (Arcus­Arth et al.,

2005). The authors noted that “although few infants are

exclusively breastfed for 12 months, the exclusively

breastfed distributions may represent a more highly

exposed subpopulation of infants exclusively breastfed

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

breastfed infants today (Arcus­Arth et al., 2005).

15.4.5	 Kent et al., 2006 ­ Volume and Frequency

of Breastfeeding 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 to 6 months 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 testweighing procedures with no correction for infant

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

insensible water loss. On average, infants had 11 ± 3

breastfeedings per day (range= 6 to18). The intervals

between feedings was 2 hours and 18 minutes ± 43

minutes (range = 4 minutes to 10 hours and 58

minutes). The 24­hour average human milk intake was

765 ± 164 mL/day (range = 464 to 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%).

Thisstudy examined breastfeeding 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 groupsto 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 5000 infants between birth

and 1 year of age to simulate a distribution of daily lipid

intake from human milk. The hypothetical population

represented both bottle­fed and breast­fed infants aged

1 to 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 breast­fed infants

under the age of 12 months (i.e., approximately 22%).

A model was used to simulate intake among 1113 of the

5000 infants that were expected to be breast­fed. The

results of the model indicated that lipid intake among

nursing infants under 12 months of age can be

characterized by a normal distribution with a mean of

26.0 mL/day and a standard deviation of 7.2 mL/day

(Table 15­24). The model assumesthat nursing infants

are completely breast­fed and does not account for

infants who are breast­fed 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

breast­fed infants. These results are also 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 EPA recommended

age categories. The estimated mean lipid intake rate

represents the average daily intake for nursing infants

under 12 months of age. The study 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

There are many factors that 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, gender, food supplementation, the frequency of

breast­feeding sessions per day, the duration of breastfeeding per 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

To monitor progress towards achieving the

CDC Healthy People 2010 breastfeeding objectives

(initiation and duration), Scanlon et al. (2007) analyzed

data from the National Immunization Survey (NIS).

NIS uses random­digit 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 conduced annually

by the CDC to obtain national,state, and selected urban

area estimation on vaccinations rates among U.S.

children age 19­35 months. The interviewresponse rate

for years 2001­2006 ranged between 64.5% and 76.1%.

Questions regarding breastfeeding were added to the

NIS survey in 2001. The sample population wasinfants

born during 2000­2004. Scanlon et al. (2007), noted

that because data in their analysis are for children aged

19­35 months at the time of the NIS interview, each

cross­sectional survey includes children from birth

cohorts that span 3 calendar years; the breastfeeding

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

data were analyzed by year of birth during 2000­2004

(birth year cohort instead if survey year).

Among infants born in 2000, breastfeeding

rates were 70.9% (CI= 69.0­72.8) for the postpartum

period (in hospital before discharge), 34.2% (CI= 32.2­

36.2) at 6 months, and 15.7 (CI= 14.2­17.2) at 12

months. For infants born in 2004, these rates had

increased to 73.8% (CI= 72.8­74.8) for the postpartum

period, 41.5% (CI= 40.4­42.6) at 6 months, and 20.9

(CI= 20.0­21.8) at 12 months. Rates of breastfeeding

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

income­to­poverty ratio of <100% (23.9%). Table 15­

25 provides data for exclusive breastfeeding through 3

and 6 months by socioeconomic characteristics for

infants born in 2004.

Scanlon et al. (2007) noted the following

limitations that could affect the utility of these data: (1)

breastfeeding behavior was based on retrospective selfreport by mothers or other caregivers, whose responses

might be subject to recall bias, (2) the NIS question that

defines early postpartum breastfeeding or initiation,

"Was[child's name] ever breastfed 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 aged 19­35 months, some bias might remain.

The advantage of the study is that is representative of

the U.S. infant population.

The rate of breastfeeding initiation in the

United States is near the national goal of 75%

established in Healthy People 2010 (Ruowei et al.

2005). Using the data obtained from the NIS survey

conducted throughout 2002 for children who were 19 to

35 months old, Ruowi et al. (2005) shows that overall,

71.4% of children surveyed had ever been breastfed.

The percentage of children who are breastfed drops to

35.1% at 6 months and to 16.1% at 12 months (Rouwei

et al. 2005). These data also revealed significant

differences in breastfeeding participation related to

race/ethnicity, day care andWICparticipation,maternal

age, socioeconomic status, and geographical area.

Overall, 51.5% of mothers of non­Hispanic black

children reported to ever breastfed their infants

compared to 72.1% of mothers of non­Hispanic white

children. Non­Hispanic black infants were exclusively

breastfed at 6 months at a rate of 5.4% compared to

14.6% of non­Hispanic white infants and 13.8% of

Hispanic infants. Infants who attended day care and

infants whose mothersreceived WIC benefits were less

likely to have ever been breastfed. Mothers with higher

socioeconomic status and older mothers were more

likely to have ever breastfed their infants.

CDC (2007) developed the breastfeeding

report card. The CDC National Immunization Program

in partnership with the CDC National Center for Health

Statistics, conductsthe NIS within all 50 states, District

of Columbia, and selected geographic areas within the

states. Five breastfeeding goals are in the Healthy

People 2010 report. The Breastfeeding Report Card

presents data for each state for the following categories

of infants: ever breastfed, breastfed at 6 months,

breastfed at 12months, exclusive breastfeeding through

3month, and exclusive breastfeeding through 6months.

These indicators are used to measure a state’s ability to

promote, protect, and support breastfeeding. These

data for the estimated percentage of infants born in

2004 are presented in Table 15­26. The weighted

sample number is 17,654 for the U.S. population. The

advantage of this report is that it provides data for each

state and isrepresentative of the U.S. infant population.

Analysis of breastfeeding practices in other

developing countries was also found in the literature.

Marriott et al. (2007) researched feeding practices in

developing countries in the first year of life, based on

24­hour recall data. Marriott et al. (2007), used

secondary data from the Demographic and Health

Surveys (DHS) for more than 35,000 infants in twenty

countries. This survey has 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, intake and

household variables and 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 breasfeeding

and had fed other liquids and solid foodsto their infants

in the previous 24 hours. The data incorporated were

from between 1999 and 2003. Marriott et al. (2007)

selected the youngest child less than 1 year old in each

ofthe families; multiples were included such astwins 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

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

other than water and infant formulas were collapsed

into broader food categories for cross­country

comparisons(Marriott et al., 2007). Tinned, powdered,

and any otherspecified animal milks were collapsed. In

addition, all other liquids such as herbal teas, fruit

juices, and sugar water (excluding unique countryspecific liquids) were collapsed into other liquids and

the 10 types of solid food groups into an any­solidfoods category (Marriott et al., 2007). Data were

pooled from the 20 countries to provide a large sample

size and increase statistical power. Tables 15­27 and

15­28 present the percentage of mothers that were

currently breastfeeding and separately had fed their

infants other liquids or solid food by age groups. Table

15­29 presents the pooled data summary for the study

period. The current breastfeedingwas consistent across

countries for both age groups; the countries that

reported the highest percentages of current

breastfeeding for the 0 to 6 months old infants also

reported the highest percentages in the 6 to12 month

old infants. Pooled data show that 96.6% of the 0 to 6

months old infants and 87.9% of the 6 to 12 month old

infants were breastfeeding. Feeding of other fluids was

lowest in the 0 to 6 months 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 differencesin breastfeeding practices.

Li and Grummer­Strawn (2002)investigated ethnic and

racial disparities in lactation in the United States using

data from the Third National Health and Nutrition

Examinations Survey (NHANES III) that was

conducted between 1988­1994. 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 to 71 months of age at time of interview.

The NHANES III response rate for children

participating was approximately 94 percent (Li and

Grummer­Strawn, 2002). Data for a total of 2,863

exclusively breastfed, 6,140 ever breastfed, and 6,123

continued breastfed children were included in the

analysis (Li and Grummer­Strawn, 2002). The

proportion of children ever­breastfed was 60% among

non­Hispanic whites, 26% among non­Hispanic blacks,

and 54% among Mexican Americans. This number

decreased to 27, 9, and 23 respectively by 6 months.

Children fed exclusively human milk at 4 months was

also significantly lower for blacks at 8.5%, compared to

22.6% for whites and 14.1% for Mexican­Americans.

The racial and ethnic differences in proportion of

children ever breastfed is presented in Table 15­30, the

proportion of children who received any breast milk at

6 months are presented in Table 15­31, and the

proportion of children exclusively breastfed at 4months

is presented in Table 15­32.

Li and Grummer­Strawn (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

household head was used as a proxy. The advantages

of this study is that it is representative of the U.S.

children’s population.

Data from some older studies provide

historical information on breastfeeding practices in the

U.S. These data are provided here to show trendsin the

U.S. population. In 1991, the National Academy of

Sciences (NAS) reported that the percentage of

breast­feeding 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 breastfeeding

during the first 6 months of life. The Ross Laboratory

Mothers’s 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 breast­feeding through 1995 and

compared them with those in 1989.

The survey demonstratesincreasesin both the

initiation of breast­feeding and continued breast­feeding

at 6 months of age between 1989 and 1991. Table 15­

33 presents the percent of breast­feeding in hospitals

and at 6 months of age by selected demographic

characteristics. In 1995, the incidence of breast­feeding

at birth and at 6 months for all infants was

approximately 59.7% and 21.6 %, respectively. The

largest increases in the initiation of breast­feeding

between 1989 and 1995 occurred among women who

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

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 U.S., 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 breast­feedingwas highest among

women who were greater than 35 years of age, earned

more than $25,000 per year, and were college educated,

did not participate in the WIC program, and were living

in the Mountain and Pacific regions of the U.S.

Data on the actual length of time that infants

continue to breast­feed beyond 5 or 6 months were

limited (NAS, 1991). However, Maxwell and

Burmaster (1993) estimated that approximately 22

percent of infants under 1 year of age are breast­fed.

This estimate was based on a reanalysis of survey data

in Ryan et al. (1991) collected by Ross Laboratories

(Maxwell and Burmaster, 1993). Studies have also

indicated that breast­feeding 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 2003). The percentages of mothers who breast

feed, based on ethnic background and demographic

variables, are presented in Table 15­34. 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 well­nourished Swedish mothers.

Lönnerdal et al. (1976) stated that these resultsindicate

that human milk quality and quantity are not affected by

maternal malnutrition. However, Brown et al. (1986a,

b) noted that the lactational capacity and energy

concentration of marginally­nourished women in

Bangladesh were “modestly less than in better

nourished mothers.” Human milk intake rates for

infants of marginally­nourished 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 of age

(Brown et al., 1986a). Brown et al. (1986a) observed

that humanmilk fromwomen with larger measurements

of armcircumference and tricepsskinfold thickness had

higher concentrations of fat and energy than mothers

with less body fat. Positive correlations between

maternal weight and milk fat concentrations were also

observed. These results suggest that milk composition

may be affected by maternal nutritional status.

15.6.3 Frequency and Duration of Feeding

Hofvander et al. (1982) reported on the

frequency of feeding among 25 bottle­fed and 25

breast­fed infants at ages 1, 2, and 3 months. The mean

number of meals for these age groups was

approximately 5 meals/day (Table 15­35). Neville et al.

(1988) reported slightly higher mean feeding

frequencies. The mean number of meals per day for

exclusively breast­fed infants was 7.3 at ages 2 to 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 16­18 minutes.

Buckley (2001) studied the breastfeeding

patterns, dietary intake, and growth measurement of

children who continued to breastfeed beyond 1 year of

age. The sample was 38 mother­child pairsliving 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 breastfeeding a

1­year old or older child (Buckley, 2001). The

participants were recruited through local medical

consultants and the La Leche League members. The

children selected asthe finalstudy subjects consisted of

22 boys and 16 girls with ages ranging from 12 to 43

month old. The data were collected using a 7­day

breastfeeding diary. The frequency and length of

breastfeeding varied with the age of the child (Buckley,

2001). The author noted a statistically significant

difference in the mean number of breastfeeding

episodes per day and the average total minutes of

breastfeeding between the 1, 2, and 3 year old groups.

Table 15­36 provides the comparison of breastfeeding

patterns between age groups. An advantage of this

study is that the frequency and duration data are based

primarily on a 7­day diary and some dietary recall.

Limitations of the study are the small sample size and

that it is limited to one geographical area.

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

15.7	 REFERENCES FOR CHAPTER 15

AAP (2005) Breast feeding and the use of human milk.

Policy Statement. Pediatrics. 115(2): 496­

5 0 6 . ava i l a b l e o n l i n e a t

http://aappolicy.aappublications.org/cgi/cont

ent/full/pediatrics;115/2/496

Abbott Laboratories (2003) Breastfeeding Trends ­

2003. Ross Mothers Survey, Ross Products

Division,Columbus, OH.

Albernaz, E.;Victora, C.G.; Haisma, H.; Wright, A.;

Coward, W.A. (2003) Lactation counseling

increases breast­feeding duration but not

breastmilk intake as measured by isotopic

methods. J Nutr. 133: 205–210.

Arcus­Arth, A.; Krowech, G.; Zeise, L. (2005) Human

milk and Lipid Intake Distributions for

assessing Cumulative Exposure and Risk. J

Expos Anal Environ Epidemiol. 15: 357­365.

Bonuck, K.A.; 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: 1413­1426.

Brown, K.H.; Akhtar, N.A.; Robertson, A.D.; Ahmed,

M.G. (1986a) Lactational capacity of

marginally nourished mothers: relationships

between maternal nutritional status and

quantity and proximate composition of milk.

Pediatrics. 78: 909­919.

Brown, K.H.; Robertson, A.D.; Akhtar, N.A.	 (1986b)

Lactational capacity of marginally nourished

mothers: infants' milk nutrient consumption

and patterns of growth. Pediatrics. 78: 920­

927.

Butte, N.F.; Garza, C.; Smith, E.O.; Nichols, B.L.

(1984) Human milk intake and growth in

exclusively breast­fed infants. J Pediatr.

104:187­195.

Butte, N.; Wong, W.; Hopkinson, J.; Smith E.; Ellis, J.

(2000) Infant feeding mode affects early

growth and body composition. Pediatrics.

106; 1355­1366.

Buckley, K. (2001) Long­term breastfeeding:

nourishment or nurtance. J Hum Lactat.

17(4):304­311.

CDC.	 (2007) Breastfeeding report card 2007.

Breastfeeding practices­results from the

National Immunization Survey. Available on

line at http://www.cdc.gov/breastfeeding/data

Chen, A.; Rogan, W.J. (2004) Breastfeeding and the

risk of postneonatal death in the United States.

Pediatrics. 113: 435­439.

Dewey, K.G.; Lönnerdal, B. (1983) Milk and nutrient

intake of breast­fed infants from 1 to 6

months:relation to growth and fatness. J

Pediatr Gastroenterol Nutr. 2:497­506.

Dewey, K.G.; Heinig, J.; Nommsen, L.A.; Lönnerdal,

B. (1991a) Maternal versus infant factors

related to human milk intake and residual

volume: the DARLING study. Pediatrics.

87:829­837.

Dewey, K.G.; Heinig, J.; Nommsen, L.; Lönnerdal, B.

(1991b) Adequacy of energy intake among

breast­fed infants in the DARLING study:

relationships to growth, velocity, morbidity,

and activity levels. J Pediatr. 119:538­547.

Dewey, K.G.; Peerson, J.M.; Heinig, M.J.; Nommsen,

L.A.; Lonnerdal, B. (1992) Growth patterns

of breast­fed infantsin affluent(United States)

and poor(Peru) communities: implicationsfor

timing of complementary feeding. Am J Clin

Nutr. 56: 1012­1018.

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: 880­891.

Ferris, A.M.; Neubauer, S.H.; Bendel, R.B.; Green,

K.W.; Ingardia, C.J.; Reece, E.A. (1993)

Perinatal lactation protocol and outcome in

mothers with and without insulin­dependent

diabetes mellitus. Am J Clin Nutr. 58: 43–48.

Gonzalez­Cossio,T.; Habicht, J.P.; Rasmussen, K.M.;

Delgado, H.L. (1998) Impact of food

supplementation during lactation on infant

breast­milk intake and on the proportion of

infants exclusively breast­fed. J Nutr.

128:1692­1702.

Hofvander, Y.; Hagman, U.; Hillervik, C.; Siolin, S.

(1982) The amount of milk consumed by 1­3

months old breast or bottled­fed infants. Acta

Paediatrica Scand. 71: 953­958.

Kent,	 J.C.; Mitoulas, L.R.; Cregan, M.D.; Ramsay,

D.T.; Doherty, D.A.; Hartmann, P.E. (2006)

Volume and frequency of breastfeeding and

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

fat content of breast milk throughout the day.

Pediatrics. 117:387­395.

Li, R.; Grummer­Strawn, L. (2002) Racial and ethnic

disparities in breastfeeding among Unites

States infants: third national health and

nutrition examination survey, 1988­1994.

Birth. 29(4):251­257.

Lönnerdal, B.; Forsum, E.; Gebre­Medhim, M.;

Hombraes, L. (1976) Human milk

composition in Ethiopian and Swedish

mothers: lactose, nitrogen, and protein

contents. Am J Clin Nutr. 29:1134­1141.

Marriott, M.; Campbell, L.; Hirsch, E.; and Wilson, D.

(2007) Preliminary data from demographic

and health surveys on infant feeding in 20

developing countries. J. Nutr. Vol 137: 518S523S.

Maxwell, N.I.; Burmaster, D.E. (1993) A simulation

model to estimate a distribution of lipid intake

from human milk during the first year of life.

J Expo Anal Environ Epidemiol. 3:383­406.

Mitoulas, L.; Kent, J.; Cox, D.; Owens, R.; Sherriff, J.;

Hartman, P. (2002) Variation in fat, lactose,

and protein in human milk over 24 h and

throughout the first year of lactation. Br J

Nutr. 88:29­37.

Mitoulas, L.; Gurrin, L.; Doherty, D.; Sherriff, J.;

Hartman, P. (2003) Infant intake of fatty

acids from human milk over the first year of

lactation. Br J Nutr. 90:979­986.

National Academy of Sciences (NAS). (1991)

Nutrition during lactation. Washington, DC.

National Academy Press.

Neubauer, S. H.; Ferris, A.M.; Chase, C.G.; Fanelli J.,

Thompson, C.A.; Lammi­Keefe, C.J.; Clark,

R. M.; Jensen, R. G.; Bendel, R. B.; Green,

K. W. (1993) Delayed lactogenesisin women

with insulin­dependent diabetes mellitus. Am

J Clin Nutr. 1993: 58:54–60.

Neville, M.C.; Keller, R.; Seacat, J.; Lutes, V.; Neifert,

M.; et al. (1988) Studies in human lactation:

milk volumes in lactating women during the

onset of lactation and full lactation. Am J Clin

Nutr. 48:1375­1386.

Pao, E.M.; Hines, J.M.; Roche, A.F. (1980) Milk

intakes and feeding patterns of breast­fed

infants. J Am Diet Assoc. 77:540­545.

Ryan, A.S.; Rush, D.; Krieger, F.W.; Lewandowski,

G.E. (1991) Recent declines in breastfeeding

in the United States, 1984­1989. Pediatrics.

88:719­727.

Ryan, A.S. (1997) The resurgence of breastfeeding in

the United States. Pediatrics. 99(4):e12.

http://www.pediatrics.org/cqi/content/full/99

/4/e12.

Salmenpera, L.; Perheentupa, J.,; Siimes, M.A. (1985)

Exclusively breast­fed healthy infants grow

slower than reference infants. Pediatr Res.

19: 307–312.

Scanlon, K.S.; Grummer­Strawn, L.; Shealy, K.R.;

Jefferds, M.E.; Chen, J.; Singleton, J.A..

(2007) Breastfeeding Trends and Updated

National Health Objectives for Exclusive

Breastfeeding ­ United States, Birth Years

2000­2004. MMWR 56(30):760­763.

Stuff J.E.; Nichols B.L. (1989) Nutrient intake and

growth performance of older infants fed

human milk. J Pediatr. 1989: 115:959–968.

Wright, C.M.; Parkinson, K.; Scott, J.	 (2006) Breastfeeding in a UK urban context: who breastfeeds, for how long and doesit matter? Public

Health Nutr. 9(6):686­691.

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Table 15­7.     Daily Intakes of Human Milk

Age Number of Infants

Intake

Mean ± SDa (mL/day)

Intake Range

(mL/day)

Completely

1 month

3 months

6 months

Breast­fed

11

2

1

600 ± 159

833

682

426 ­ 989

645 ­ 1,000

616 ­ 786

Partially Breast­fed

1 month

3 months

6 months

9 months

4

11

6

3

485 ± 79

467 ± 100

395 ± 175

<554

398

242

147

451

­ 655

­ 698

­ 684

­ 732

a Data expressed as mean ± standard deviation.

Source: Pao et al., 1980.

Table 15­8.     Human Milk Intakes for Infants Aged 1 to 6 Months

Age Number of Infants

Intake

Mean ± SD Intake Range

(mL/day) (mL/day)

1 month 16 673 ± 192 341­1,003

2 months 19 756 ± 170 449­1,055

3 months 16 782 ± 172 492­1,053

4 months 13 810 ± 142 593­1,045

5 months 11 805 ± 117 554­1,045

6 months 11 896 ± 122 675­1,096

Source: Dewey and Lönnerdal, 1983.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

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Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­9. Human Milk Intake Among Exclusively Breast­fed Infants During the First 4 Months of Life

Age Number of

Infants

Intake (mL/day)a

Mean ± SD

Intake (mL/kg­day)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/kg­day were converted to units of mL/day and mL/kg­day 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/kg­day).

SD = Standard deviation.

Source: Butte et al., 1984.

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­23
 
Table 15­10.     Human Milk Intake During a 24­hour Period

Age

(days) Number of Infants

Intake ( mL/day)a Intake by Age Category

(mL/day)a,c

Mean ± SD Range

1 6 43 ± 68 b ­30­145

2 9 177 ± 83 43­345

3 10 360 ± 149 203­668

4 10 438 ± 171 159­674

5 11 483 ± 125 314­715

6 9 493 ± 162 306­836

7

8

7

8

556 ± 162

564 ± 154

394­817

398­896 511 ± 220

9 9 563 ± 74 456­699

10 9 569 ± 128 355­841

11 8 597 ± 163 386­907

14 9 634 ± 150 404­895

21 10 632 ± 82 538­763

28 13 748 ± 174 481­1,111

35 12 649 ± 114 451­903

42

49

12

10

690 ± 108

688 ± 112

538­870

543­895 679 ± 105

56 12 674 ± 95 540­834

90 10 713 ± 111 595­915 713 ± 111

120 12 690 ± 97 553­822 690 ± 97

150 12 814 ± 130 668­1,139 814 ± 130

180 13 744 ± 117 493­909 744 ± 117

210 12 700 ± 150 472­935 700 ± 150

240 9 604 ± 204 280­973 604 ± 204

270 12 600 ± 214 217­846 600 ± 214

300 11 535 ± 227 125­868 535 ± 227

330 8 538 ± 233 117­835 538 ± 233

360 8 391 ± 243 63­748 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

b

(density of     human milk).

Negative value due to insensible weight loss correction. c 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.

SD     = Standard deviation.

Source: Neville et al., 1988.

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Chapter 15 ­ Human Milk Intake

Page            Child­Specific Exposure Factors Handbook
 

15­24          September 2008
 
                  

         

   

   

   

   

                                 

         

     

     

          

         

           

               

                 

                 

                   

     

     

        

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­11. Human Milk Intake Estimated by the Darling Study

Age Number of Infants Intake (mL/day)

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 15­12. Mean Breastfed Infants Characteristics a

Boys (N=14) Girls (N=26)

Ethnicity (White, Black, Hispanic, Asian) (N) 10/1/2/1

Duration of Breastfeeding (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.

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­25
 
Table 15­13. Mean Human Milk Intake of Breastfed 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

N

3­day average; values

1.03 g/mL (density of

    = Number of infants.

reported by the author in units

human milk); mean ± standard

of g/day were

deviation.

converted to units of mL/day by dividing by

Source: Butte et al., 2000.

Table 15­14. Feeding Practices by Percent of Infants

Age

Infants 3

months

6

months

9

months

12

months

18

months

24

months

                                         Percentage

Infants Still Breastfed 100 80 58 38 25 5

Breastfed Infants Given Formula 0 40 48 30 10 2

Formula­fed Infants     Given Breast Milk 100 100 94 47 6 0

Use of Cow’s Milk for Breastfed Infants ­ ­ 8 65 82 88

Use of Cow’s Milk for Formula­fed Infants ­ ­ 28 67 89 92

Source: Butte et al., 2000.

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Chapter 15 ­ Human Milk Intake

Page            Child­Specific Exposure Factors Handbook
 

15­26          September 2008
 
Table 15­15. Body Weight of Breastfed a Infants

Age

Weight (kg)

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

N 

Mean ± standard deviation.

= Number of infants.

Source: Butte et al., 2000.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­27
 
Table 15­16. AAP Dataset Milk Intake Rates at Different Ages

Age Mean

(mL/kg day)a

SD

(mL/kg day)a

CV Skewnessb Statistic

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

b

SD

CV

N 

Source:

Values reported by the author in units of g/kg­day were converted

dividing by 1.03 g/mL (density of human milk).

Statistic/SE: ­2 < Statistic/SE < +2     suggests a normal distribution

= Standard deviation.

= Coefficient of variation.

= Number of infants.

Arcus­Arth et al., 2005.

to units of mL/kg­day by

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Page            Child­Specific Exposure Factors Handbook
 

15­28          September 2008
 
Table 15­17. Average Daily Human Milk Intake (mL/kg day) a

Averaging Period Mean (SD) Population Percentile

AAP 0 to 6 months

        Method 1

        Method 2

AAP 0 to 12 months

        Method 1

        Method 2

EBF 0 to 12 months

General Pop.

        0 to 6 months

        0 to 12 months

126 (21)

123 (7)

98 (22)

99 (5)

110 (21)

79

51

5 10 25 50 75 90 95 99

92

112

61

90

75

0

0

99

114

69

92

83

0

0

112

118

83

95

95

24

12

126

123

98

99

110

92

49

140

127

113

102

124

123

85

152

131

127

105

137

141

108

160

133

135

107

144

152

119

174

138

150

110

159

170

138

a

Source:

Values reported by the author in units

1.03 g/mL (density of human milk).

Arcus­Arth et al., 2005.

of g/kg­day were converted to units of mL/kg­day by dividing by

                            

   

       

   

   

   

   

   

   

   

   

   

   

   

   

             

                                     

               

     

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­18. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast­fed 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/kg­day)b

Mean ± SD

1

2

3

4

37

40

37

41

36.2 ± 7.5

34.4 ± 6.8

32.2 ± 7.8

34.8 ± 10.8

3.6

3.4

3.2

3.5

27 ± 8

24 ± 7

23 ± 7

25 ± 8

5.7 ± 1.7

4.3 ± 1.2

3.7 ± 1.2

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/kg­day 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.

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­29
 
Table 15­19.     Human Milk Production and Composition Over the First 12 Months of Lactation a

Volume, per Breast Fat Lactose Protein Energy

Age Group (mL/24h) (g/L) (g/L) (g/L) (kJ/mL)

(months)

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 breast­fed to 4 months and complementary solid food was introduced between 4­6

months.

SE = Standard error.

N  = Number of infants.

Source: Mitoulas et al., 2002.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

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15­30          September 2008
 
Table 15­20. Changes in Volume of Human

First Year

Milk Produceda
 of Lactation

and Milk Fat Content Over the
 

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

SE

NS

P

Infants were completely breast­fed

months.

= Standard error.

= No statistical difference.

= Probability.

to 4 months, and complementary solid food was introduced between 4­6

Source: Mitoulas et al., 2003.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­31
 
Table 15­21.     Changes in Fatty Acid Composition of Human Milk Over the First Year of Lactation (g/100 g total fatty acids)

Fatty Acid

Medium­chain

Saturated

Odd­chain

Saturated

Long­chain

Saturated

Monounsaturated

TransPolyunsaturated

1 month

Mean SE

14.2 0.4

0.9 0.01

34.1 0.3

37.5 0.2

2.0 0.08

12.7 0.2

2 months

Mean SE

13.9 0.6

0.9 0.02

33.7 0.3

33.7 0.4

2.2 0.1

9.5 0.2

4 months

Mean SE

12.0 0.5

0.8 0.02

32.8 0.3

38.6 0.5

2.2 0.09

11.8 0.4

6 months

Mean SE

11.5 0.2

0.8 0.03

31.8 0.6

37.5 0.5

4.6 0.02

13.4 0.6

9 months

Mean SE

14.1 0.3

0.8 0.02

31.4 0.6

37.3 0.5

1.7 0.2

8.0 0.1

12 months

Mean SE

17.0 0.4

0.8 0.02

33.9 0.6

33.0 0.5

1.8 0.09

6.7 0.03

SE

Source:

= Standard

Mitoulas et

error.

al., 2003.

Table 15­22. Comparison of Lipid Content Assumptions (mL/kg­day)a

Lipid Content

Calculation

Used in Mean Population Percentile

Measured b Lipid Content 3.6

5 10 25 50 75 90 95 99

2.0 2.3 2.9 3.6 4.3 4.9 5.2 5.9

4% Lipid Contentc 3.9 2.5 2.8 3.3 3.8 4.4 4.9 5.2 5.8

a

b

c

    Values reported by the author in units of g/kg­day were converted to units

g/mL (density of human milk).

Lipid intake derived from lipid content and milk intake measurements.

Lipid intake derived using 4% lipid content value and milk intake.

of mL/kg­day by dividing by 1.03

Source: Arcus­Arth et al., 2005.

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Chapter 15 ­ Human Milk Intake

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15­32          September 2008
 
Table 15­23.     Distribution of Average Daily Lipid Intake (mL/kg day) assuming 4% Milk Lipid Content

Mean Population Percentile

AAP Infants 0 to 12 months 3.9

5 10 25 50 75 90 95 99

2.4 2.8 3.3 3.9 4.5 5.1 5.4 6.0

a	 Values reported by the author in

g/mL (density of human milk).

units of g/kg­day were converted to units of mL/kg­day by dividing by 1.03

Source:	 Arcus­Arth     et al., 2005.

Table 15­24. Predicted Lipid Intakes for Breast­fed 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 a 1.0 mL/day a 51.0 mL/daya 26.0 mL/daya 7.2 mL/day

a Values reported by the author in

(density of human milk).

units of g/day were converted to units of mL/day by dividing by 1.03 g/mL

Source: Maxwell and Burmaster, 1993.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­33
 
Table 15­25. Socio­economic Characteristics of Exclusively Breastfed Infants Born in 2004

Percent of Exclusive Breastfeeding Infants Through 3 and 6 Months

3 months 6 months

Characteristic % 95% CI % 95% CI

U.S. Overall (N=17,654) 30.5 29.4­31.6 11.3 10.5­12.1

Infant Sex

Male 30.7 29.1­32.3 10.8 9.8­11.8

a Female 30.3 28.7­31.9 11.7 10.5­12.9

Race/Ethnicity (child)

Hispanic 30.8 28.3­33.3 11.5 9.7­13.3

White, a non­Hispanic 33.0 31.6­34.4 11.8 10.9­12.7

Black, non­Hispanic b 19.8 17.0­22.6 b 7.3 5.5­9.1

Asian, non­Hispanic 30.6 25.0­36.2 14.5 10.0­19.0

Other 29.3 24.9­33.7 12.2 9.2­15.2

Maternal Age (years)

<20 b 16.8 10.3­23.3 b 6.1 1.5­10.7

20 to 29 b 26.2 24.4­28.0 b 8.4 7.3­9.5

$30a 34.6 33.2­36.0 13.8 12.7­14.9

Household Head Education

<High school b 23.9 21.0­26.8 b 9.1 7.1­11.1

High school b 22.9 20.9­24.9 b 8.2 7.0­9.4

Some college b 32.8 30.3­35.3 b 12.3 10.2­14.4

a College graduate 41.5 39.7­43.3 15.4 14.1­16.7

Marital Status

Marrieda 35.4 34.0­36.8 13.4 12.4­14.4

Unmarried b 18.8 16.9­20.7 b 6.1 5.0­7.2

Residence

MSA, a center city 30.7 29.0­32.4 11.7 10.5­12.9

MSA, non­center city 32.8 30.9­34.7 12.1 10.8­13.4

Non­MSA b 23.9 21.8­26.0 b 8.2 6.9­9.5

Poverty income ratio (%)

<100 b 23.9 21.6­26.2 b 8.3 6.9­9.7

100 to <184 b 26.6 23.8­29.4 b 8.9 7.2­10.6

185 to <349 b 33.2 30.9­35.5 b 11.8 10.3­13.3

$350a 37.7 35.7­39.7 14.0 12.6­15.4

a

  

b

N 

Referent group.

p<0.05 by chi­square test, compared

= Number of infants.
 

with referent group.
 

MSA = Metropolitan statistical area.
 

Source: Scanlon et al., 2007.

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Chapter 15 ­ Human Milk Intake

Page            Child­Specific Exposure Factors Handbook
 

15­34          September 2008
 
                  

       

       

           

                  

   

                                 

                                      

                                     

               

       

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table15­26. Geographic­specific Breastfeeding Percent Rates Among Children Born in 2004 a

State N Ever

Breastfed

Breastfed at 6

Months

Breastfed at 12

Months

Exclusive

Breastfeeding

Through 3 Months

Exclusive Breastfeeding

Through 6 Months

U.S. National 17,654 73.8 41.5 20.9 30.5 11.3

Alabama 310 52.1 25.4 11.5 19.3 4.9

Alaska 217 84.8 60.9 31.8 47.2 24.3

Arizona 543 83.5 46.5 23.4 38.8 14.3

Arkansas 200 59.2 23.2 8.5 15.8 6.2

California 1,702 83.8 52.9 30.4 38.7 17.4

Colorado 249 85.9 42 23.6 36.2 10.8

Connecticut 249 79.5 44.6 23.7 35.6 10.1

Delaware 213 63.6 35.7 14.6 26.3 11.4

Dist of Columbia 292 68.0 40.0 21.4 27.8 9.8

Florida 955 77.9 37.5 15.6 27.8 9.1

Georgia 582 68.2 38.0 16.8 25.6 11

Hawaii 221 81 50.5 35.5 37.8 15.8

Idaho 183 85.9 49.0 22.6 38.7 10.3

Illinois 561 72.5 40.9 17.6 31.6 10

Indiana 472 64.7 34.6 18.0 28.3 10.4

Iowa 193 74.2 44.9 20.0 37.6 11.6

Kansas 480 74.4 42.2 16.9 30.0 9.2

Kentucky 245 59.1 26.4 14.4 25.3 7.5

Louisiana 429 50.7 19.2 8.3 15.2 2.8

Maine 203 76.3 46.6 27.6 42.1 15.9

Maryland 512 71.0 40.2 21.2 32.1 8.6

Massachusetts 469 72.4 42.1 19.0 32.7 11.9

Michigan 604 63.4 36.4 18.6 27.4 8.3

Minnesota 202 80.9 46.5 23.8 33.9 16.1

Mississippi 287 50.2 23.3 8.2 19.0 8

Missouri 327 67.3 32.5 15.8 26.6 7.4

Montana 232 87.7 53.8 28.8 50.9 18.3

Nebraska 228 79.3 47.6 21.8 31.7 9.8

Nevada 281 79.7 45.6 21.9 31.9 10.3

New Hampshire 228 73.7 48.7 27.5 34.3 13.6

New Jersey 631 69.8 45.1 19.4 27.0 11.8

New Mexico 420 80.7 41.2 21.1 32.9 14.3

New York 533 73.8 50.0 26.9 26.0 11.4

North Carolina 220 72.0 34.2 18.3 23.0 6.9

North Dakota 285 73.1 45.1 19.5 39.4 15.4

Ohio 617 59.6 33.3 12.9 27.2 9.8

Oklahoma 280 67.1 29.6 12.7 23.0 10.6

Oregon 191 88.3 56.4 33.5 41.5 19.9

Pennsylvania 757 66.6 35.2 16.8 27.1 8

Rhode Island 291 69.1 31.2 14.0 31.2 9.5

South Carolina 314 67.4 30.0 11.1 26.6 5.4

South Dakota 315 71.1 40.5 23.4 32.2 12.2

Tennessee 671 71.2 32.6 16.6 26.7 11.9

Texas 1,439 75.4 37.3 18.7 25.2 7.1

Utah 190 84.5 55.6 28.1 39.8 10.2

Vermont 190 85.2 55.3 34.1 47.3 15.9

Virginia 259 79.1 49.8 25.6 32.6 13.4

Washington 615 88.4 56.6 32.3 49.6 22.5

West Virginia 224 59.3 26.8 14.0 21.3 5.2

Wisconsin 478 72.1 39.6 19.0 32.5 13.4

Wyoming 246 80.5 42.9 18.5 36.2 11.4 a Exclusive breastfeeding information is from the 2006 NIS survey data only and is defined as ONLY breast milk­ No

solids, no water, no other liquids. Sample sizes appearing in the NIS breastfeeding tables are slightly smaller than the

numbers published in other NIS publications due to the fact that in the DNPA breastfeeding analyses, the sample was

limited to records with valid responses to the breastfeeding questions.

N = Number of infants.

Source: CDC, 2007.

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­35
 
Table 15­27.     Percentage of Mothers in Developing Countries by Feeding Practices for Infants 0 to 6 Months Old a

Country Breastfeeding Water Milk Formula Other Liquids Solid Foods

Ethiopia

Ghana

Kenya

Malarwi

Nambia

Nigeria

Uganda

Zamibia

Zimbabwe

Armenia

Egypt

Jordan

Bangladesh

Cambodia

India

Indonesia

Nepal

Philippines

Vietnam

Kazakhstan

Pooled

98.8

99.6

99.7

100

95.3

99.1

98.7

99.6

100

86.1

95.5

92.4

99.6

98.9

98.1

92.8

100

80.5

98.7

94.4

96.6

26.3

41.9

60

46

65.4

78.2

15.1

52.6

63.9

62.7

22.9

58.5

30.2

87.9

40.2

37

23.3

53.4

45.9

53.7

45.9

19

6.7

35.1

1.4

0

9.2

20.3

2.1

1.6

22.9

11.1

3

13.6

2.1

21.2

0.7

12.3

4.4

16.9

21.4

11.9

0

3.5

4.8

1.7

0

12.7

1.5

2.7

3.2

13.1

4.3

25.1

5.3

3.3

0

24.2

0

30

0.8

8.2

9

10.8

4.3

35.9

5.2

17.9

17.9

10.3

6.7

9

48.1

27.6

13.8

19.7

6.7

7.1

8.7

2.8

12.4

8.9

37.4

15.1

5.3

15.6

46.3

42.3

33.4

18.5

11.4

31.2

43.7

23.9

13.2

20.2

20.3

16.6

6.5

43

9.3

16.8

18.7

15.4

21.9

a

Source:

Percentage of mothers

liquid or solid food in

Marriott et al., 2007.

who stated

the past 24

that they

hours by

currently breast­feed and separately had fed

country for infants age 0 to 6 months old.

their infants 4 categories of

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Chapter 15 ­ Human Milk Intake

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15­36          September 2008
 
                                  

                                 

                                     

       

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Table 15­28. Percentage of Mothers in Developing Countries by Feeding Practices for Infants 6 to 12 Months Olda

Country Breastfeeding Water Milk Formula Other Liquids Solid Foods

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

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

Nigeria 97.8 91.6 14.4 13.4 27.4 70.4

Uganda 97.4 65.9 32.1 1.6 56.2 82.1

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

Armenia 53.4 91.1 56.9 11.6 85.3 88.1

Egypt 89.1 85.9 36.8 16.7 48.5 75.7

Jordan 65.7 99.3 24.3 28.8 57.7 94.9

Bangladesh 96.2 87.7 29.8 10.1 21.9 65.2

Cambodia 94.4 97.5 3.7 6.7 29 81

India 94.9 81.4 45 0 25.2 44.1

Indonesia 84.8 85.4 4.9 38.8 35.4 87.9

Nepal 98.8 84.3 32 0 15.8 71.5

Philippines 64.4 95.1 12.2 47.1 31 88

Vietnam 93.2 95 36.1 5.3 37.9 85.8

Kazakhstan 81.2 74.3 85.4 11.4 91.8 85.9

Pooled 87.9 87.4 29.6 15.1 41.6 80.1

a Percentage of mothers who stated that they currently breast­feed and separately had fed their infants 4 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.

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­37
 
Table 15­29.     Population

Selected Feeding

Weighted Averages of Mothers Who Reported
 

Practices During the Previous 24­hours
 

Feeding Practices

Infant Age

0 to 6 months 6 to 12 months

Percentage (weighted N)

Current Breast­feeding 96.6 (22,781)     87.9 (18,944)

Gave Infant:

    Water 45.9 (10,767) 87.4 (18,6663)

       Tinned, Powdered, or Other Milk 11.9 (2,769) 29.6 (6,283)

       Commercial Formula 9.0 (1,261) 15.1 (1,911)

       Other Liquids 15.1 (3,531) 41.6 (8,902)

       Any Solid Food 21.9 (5,131) 80.1 (17,119)

N = Number of infants.

Source: Marriott et al., 2007.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Page            Child­Specific Exposure Factors Handbook
 

15­38          September 2008
 
     

         

     

Table 15­30.     Racial and Ethnic Differences in Proportion of Children Ever Breastfed, NHANES III (1988­1994)

Absolute Difference (%,SE)a

Non­Hispanic White Non­Hispanic Black Mexican American 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

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

$2,500

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 to 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 to 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

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

$30

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 to 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

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

$30

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

Poverty income ratio (%)

<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

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

$350

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 Grummer­Strawn, 2002.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­39
 
Table 15­31.

Received

Racial and Ethnic

Any Human Milk

Differences

at 6 Months

in Proportion of Children Who

(NHANES III, 1988­1994)

Non­Hispanic White Non­Hispanic Black Mexican American

Absolute Difference (%,SE)

White vs Black White vs Mexican

American

Characteristic N % (SE) No. % (SE) N % (SE) % (SE) % (SE)

All infants 1863 26.8 1.6 1,842 8.5 0.9 2,112 23.1 1.4 18.3 (1.7)b 3.7 (2.1)c

Infant sex

Male 900 27.6 2.3 912 8.5 1.1 1,029 22.3 1.6 19.1 (2.6)b 5.2 (2.6)a

Female 963 26.1 1.8 930 8.6 1.1 1,083 24.0 2.0 17.5 (2.1)a 2.1 (2.7)c

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)a ­4.3 (5.7)c

$2,500 1,733 28.3 1.8 1,581 9.0 0.9 1,832 23.1 1.7 19.3 (1.8)b 5.2 (2.3)a

Maternal age (years)

<20 174 10.2 2.9 380 4.7 1.4 380 11.6 1.7 5.5 (3.0)c ­1.3 (3.8)c

20 to 24 461 13.4 2.4 559 7.5 1.1 646 23.8 2.4 5.9 (2.5)a ­10.4 (3.3)b

25 to 29 651 29.3 2.6 503 10.9 2.0 624 24.6 2.6 18.4 (3.5)b 4.8 (3.6)c

$30 573 39.0 2.6 389 10.7 1.7 452 30.0 2.8 28.4 (3.3)b 9.0 (3.6)a

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)a ­6.2 (4.1)c

High school 622 19.9 1.7 771 5.0 1.0 478 22.4 2.5 14.9 (2.0)b 2.5 (3.1)c

Some college 396 26.8 2.4 317 16.6 2.5 225 28.4 5.3 10.2 (3.5)b ­1.6 (6.1)c

College graduate 502 42.2 2.9 139 21.1 3.2 74 45.5 7.3 21.1 (5.2)b 3.4 (7.6)c

Smoking during pregnancy

Yes 524 11.3 1.5 402 4.3 1.1 198 9.3 2.2 7.0 (1.9)b 2.1 (2.7)c

No 1,331 32.7 2.1 1,427 9.8 1.1 1,911 24.5 1.5 22.9 (2.3)b 8.1 (2.6)b

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)b 7.8 (2.7)b

25.0 to 29.9 282 19.0 2.4 482 8.2 1.9 534 26.4 1.9 10.8 (3.2)b 7.4 (3.0)a

$30 204 20.4 4.1 415 7.3 1.6 357 17.2 3.0 13.1 (4.4)b 3.3 (5.2)c

Residence

Metropolitan 760 29.7 2.5 941 11.8 1.3 1,378 23.5 1.7 17.9 (2.4)b 6.1 (3.1)c

Rural 1,103 24.6 2.4 901 4.9 0.9 734 22.5 2.8 19.7 (2.2)b 2.2 (3.4)c

Region

Northeast 316 21.0 2.2 258 9.7 1.8 12 43.6 16.0 11.3 (1.8)b ­22.6 (16.5)c

Midwest 553 28.8 2.1 344 9.8 2.4 170 18.2 4.7 19.0 (3.7)b 10.6 (6.2)c

South 746 20.1 2.8 1,073 5.9 1.0 693 17.2 2.8 14.3 (2.8)b 2.9 (4.2)c

West 248 42.7 4.7 167 19.3 3.3 1,237 25.9 1.4 23.4 (5.3)b 16.8 (5.1)b

Poverty income ratio (%)

100 to <185 387 23.5 2.9 390 9.9 1.8 486 23.4 2.7 13.6 (3.9)b 0 (4.1)c

185 to <350 670 30.4 2.7 293 10.0 2.4 287 27.6 4.4 20.4 (4.0)b 2.9 (4.8)c

$350 443 33.0 3.0 105 15.2 2.8 74 32.3 9.0 17.8 (4.2)b 0.7 (9.5)c

Unknown 108 13.3 3.8 149 6.4 2.9 280 26.7 4.5 7.0 (5.3)c ­13.4 (6.6)a

a

b

c

p <0.05.

p <0.01.

No statistical difference.

N = Number of individuals.

SE = Standard error.

Source: Li and Grummer­Strawn, 2002.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Page            Child­Specific Exposure Factors Handbook
 

15­40          September 2008
 
     

         

     

Table 15­32.     Racial and Ethnic Differences in Proportion of Children Exclusively

Non­Hispanic

Bre

White

astfed at 4 Months

Non­Hispanic

(NHAN

Black

ES III, 1991­1994)

Mexican American

Absolute Difference (%,SE)

White vs Black White vs Mexican

Characteristic

All infants

Infant sex

Male

N

824

394

%

22.6

22.3

(SE)

1.7

1.9

N

906

454

%

8.5

7.0

(SE)

1.5

1.6

N

957

498

%

20.4

20.7

(SE)

1.4

1.5

%

14.1

15.3

(SE)

(2.2)b

(2.6)b

Am

%

2.3

1.5

erican

(SE)

(1.6)c

(1.8)c

Female

Infant birth

<2500

weight

430

(g)

50

23.0

15.2

2.2

7.1

452

118

10.0

7.0

2.2

2.3

459

66

20.0

5.6

1.8

1.8

12.9

8.2

(3.0)b

(8.1)c

3.0

9.5

(2.1)c

(6.9)c

$2500

Maternal age

<20

774

(years)

76

23.1

6.6

1.8

3.2

786

172

8.8

6.4

1.6

2.1

880

170

21.6

12.1

1.4

2.5

14.4

0.2

(2.2)b

(3.7)c

1.5

­5.6

(1.6)c

(3.8)c

20 to 24 205 11.4 2.2 273 7.4 2.4 319 21.0 2.3 4.0 (2.7)c ­9.6 (3.2)b

25 to 29 271 21.6 2.3 254 8.6 2.5 256 22.1 2.5 13.0 (3.2)b ­0.5 (3.2)c

$ 270 30

Household head education

<High school 146

34.8

9.5

2.7

3.5

201

256

11.9

2.0

2.6

0.7

210

563

23.6

19.7

3.1

1.8

22.9

7.5

(4.2)b

(3.6)a

11.1

­10.2

(3.7)b

(4.0)a

High school 277 14.5 2.7 406 7.1 2.1 222 18.8 3.6 7.4 (3.2)a ­4.3 (4.7)c

Some college 175 30.8 3.8 141 17.4 3.0 120 21.0 3.9 13.4 (4.7)b 9.8 (6.1)c

College

Smoking

Yes

graduate

during

219

pregnancy

224

34.1

10.0

3.9

2.8

92

168

17.4

5.4

4.7

2.2

37

64

31.5

3.2

4.5

1.8

16.7

4.6

(6.9)a

(3.7)c

2.6

6.8

(6.3)c

(3.4)c

No

Maternal

<25.0

body mass

596

index

597

27.2

24.8

2.1

2.1

730

407

9.4

8.0

1.9

1.9

892

417

21.7

19.4

1.5

1.9

17.8

16.8

(2.8)b

(3.0)b

5.6

5.4

(2.0)a

(2.3)a

25.0 to 29.9 117 19.7 4.3 230 8.6 1.9 261 23.1 3.4 11.1 (4.6)a ­3.4 (4.9)c

$30

Residence

Metropolitan

91

312

15.4

24.4

3.8

3

230

535

9.0

11.0

2.9

2.0

184

608

15.9

19.6

2.3

1.6

6.4

13.4

(5.2)c

(3.5)b

­0.5

4.8

(4.6)c

(2.8)c

Rural

Region

Northeast

512

138

21.3

20.0

1.8

1.4

371

131

4.2

11.1

1.3

2.9

349

10

22.3

9.4

3.3

9.5

17.1

8.8

(1.8)b

(2.2)b

­1.1

10.6

(3.0)c

(8.7)c

Midwest 231 26.5 3.2 143 12.6 5.6 98 19.2 4.1 13.9 (7.6)c 7.4 (3.7)c

South 378 14.1 2.8 574 5.9 1.4 383 15.9 3.1 8.2 (1.9)b ­1.8 (3.7)c

West

Poverty income

<100

ratio

77

(%)

116

34.7

13.1

2.7

3.3

58

448

12.5

5.7

5.0

1.6

466

471

23.0

18.4

1.3

1.8

22.2

7.4

(5.4)b

(3.5)a

11.7

­5.3

(2.5)

(3.1)c

100 to <185 166 18.9 3.2 197 10.6 2.8 234 21.9 4.1 8.3 (3.3)a ­3 (6.1)c

185 to <350 274 25.1 3.2 145 12.9 4.3 132 26.4 4.2 12.2 (5.0)a ­1.3 (4.1)c

$350 235 27.4 4.1 57 12.8 3.5 37 17.0 5.0 14.6 (5.0)b 10.4 (5.2)c

Unkno

a

b

wn 33 16.5

p <0.05.

p <0.01.

7.6 59 7.3 3.7 83 16.1 5.1 9.2 (8.6)c 0.4 (9.5)c

c No statistical difference.

N = Number of individuals.

SE = Standard error.

Source: Li and Grummer­Strawn, 2002.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­41
 
     

            

                 

           

Table 15­33.     Percentage of Mothers Breast­feeding Newborn Infants in the Hospital and Infants at 5

United States in 1989 and 1995, by Ethnic Background and Selected Demographic

or 6 Months

Variables
 

of Age in the
 

Characteristic
 

Percentage of Mothers Breast­Feeding
 

In Hospital At 6 Months

1989 1995 a Change 1989 1995 a Change

All Infants

White

Black

Hispanic

Maternal Age (years)

<20

20 to 24

25 to 29

30 to 34

35+

Total Family Income

<$10,000

$10,000 to $14,999

$15,000 to $24,999

$25,000

Maternal Education

Grade School

High School

College

Maternal Employment

Employed Full Time

Employed Part Time

Not Employed

Birth Weight

Low (#2,500 g)

Normal

Parity

Primiparous

Multiparous

WIC c Participation

Participant

Nonparticipant

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

58.5

23.0

48.4

30.2

45.2

58.8

65.5

66.5

31.8

47.1

54.7

66.3

31.7

42.5

70.7

50.8

59.4

51.0

36.2

53.5

52.6

51.7

34.2

62.9

52.2

47.4

47.6

55.9

43.8

37.9

46.0

70.2

70.3

59.7

64.3

37.0

61.0

42.8

52.6

63.1

68.1

70.0

41.8

51.7

58.8

70.7

43.8

49.7

74.4

60.7

63.5

58.0

47.7

60.5

61.6

57.8

46.6

71.0

61.2

53.8

54.6

61.9

54.8

44.1

54.4

75.1

75.1

14.4

9.9

60.9

26.0

41.7

16.4

7.3

4.0

5.3

31.4

9.8

7.5

6.6

38.2

16.9

5.2

19.5

6.9

13.7

31.8

13.1

17.1

11.8

36.3

12.9

17.2

13.5

14.7

10.7

25.1

16.4

18.3

7.0

6.8

18.1

21.0

6.4

13.9

5.6

11.5

21.1

29.3

34.0

8.2

13.9

18.9

25.5

11.5

12.4

28.8

8.9

21.1

21.6

9.8

18.8

15.1

21.1

8.4

23.8

18.6

16.8

16.7

18.4

13.7

11.5

13.6

28.3

26.6

21.6

24.1

11.2

19.6

9.1

14.6

22.9

29.0

33.8

11.4

15.4

19.8

28.5

17.1

15.0

31.2

14.3

23.4

25.0

12.6

22.3

19.5

23.6

12.7

29.2

22.2

19.6

18.9

21.4

18.6

13.0

17.0

30.3

30.9

19.3

14.8

75.0

41.0

62.5

27.0

8.5

(1.0)b

(0.6)b

39.0

10.8

4.8

11.8

48.7

21.0

8.3

60.7

10.9

15.7

28.6

18.6

29.1

11.8

51.2

22.7

19.4

16.7

13.2

16.3

35.8

13.0

25.0

7.1

16.2

a

b

c

Source:

The percent change was calculated using the following formula: % breastfed in 1984 ­ %   breastfed

Figures in parentheses indicate a decrease in the rate of breastfeeding from 1989 to 1995.

WIC indicates Women, Infants, and Children supplemental food program.

Ryan, 1997.

in 1989 / % breastfed in 1984.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Page Child­Specific Exposure Factors Handbook
 

15­42 September 2008
 
Table 15­34.     Percentage of Mothers Breast­feeding Newborn Infants

Months of Age in the United States in 2003, by Ethnic Background

in the Hospital and Infants

and Selected Demographic

at 6 and 12
 

Variables
 

Characteristic

Percentage of Mothers Breast­Feeding

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

Parity
 

Primiparous

Multiparous

WIC a
 Participation

Participant

Nonparticipant

U.S. Census Region
 

New England

Middle Atlantic

East North Central

West North Central

South Atlantic

East South Central

West South Central

Mountain

Pacific

9oz

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

Source:

WIC indicates

Abbott, 2003.

Women, Infants, and Children supplemental food program.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

Child­Specific Exposure Factors Handbook Page
 

September 2008 15­43
 
Table 15­35.     Number of Meals Per Day

Age (months) Bottle­fed Infants a (meals/day)

Breast­fed

(meals/day) a

1 5.4 (4­7) 5.8 (5­7)

2 4.8 (4­6) 5.3 (5­7)

3 4.7 (3­6) 5.1 (4­8)

a Data expressed as mean with range in parentheses.

Source: Hofvander et al., 1982.

Table 15­36.     Comparison of Breastfeeding Patterns Between Age and Groups (Mean ±SD)

Breastfeeding Episodes per Day 5.8 ± 2.6 6.8 ± 2.4 2.5 ± 2.0

Total Time Breastfeeding (min/day) 65.2 ± 44.0 102.2 ± 51.4 31.2 ± 24.6

Length of Breastfeeding (min/episode) 10.8 ± 6.1 14.2 ± 6.1 11.6 ± 5.6

SD = Standard deviation

Source: Buckley, 2001.

Child­Specific Exposure Factors Handbook

Chapter 15 ­ Human Milk Intake

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

16 ACTIVITY FACTORS 

16.1 INTRODUCTION 

As a consequence of a child’s immaturity and 

small stature, certain activities and behaviors specific to 

children place them at higher risk to certain 

environmental agents (Chance and Harmsen, 1998). 

Individual or group activities are important 

determinants of potential exposure, because toxic 

chemicals introduced into the environment may not 

cause harm to a child until an activity is performed that 

subjects the child to contact with those contaminants. 

An activity or time spent in a given activity will vary 

among children on the basis of, for example, culture, 

ethnicity, hobbies, location, gender, age, socioeconomic 

characteristics, and personal preferences. However, 

limited information is available regarding ethnic, 

cultural and socioeconomic differences in children’s 

choice of activities or time spent in a given activity. 

It is difficult to accurately collect/record data for 

a child’s activity patterns (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 (Hubal 

et al., 2000). Behavioral patterns, preferred activities, 

and developmental stages result in different exposures 

for children than for adults (Chance and Harmsen, 

1998). Other factors that may affect children’s activity 

patterns include: social status, economics, and the 

cultural practices of their families. 

This chapter summarizes data on how much time 

children spend participating in various activities in 

various microenvironments. Information on the 

frequency of performing various activities is also 

provided. 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. 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 children. 

16.2 RECOMMENDATIONS 

Assessors are commonly interested in 

quantitative information describing several types of 

time use data for children including: time spent indoors 

and outdoors; time spent bathing, showering, and 

swimming; and time spent playing on various types of 

surfaces. The recommended values for these factors are 

summarized in Table 16-1. Note that, except for 

swimming, all activity factors are reported in units of 

minutes/day. Time spent swimming is reported in units 

of minutes/month. These data are based on two 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). 

The confidence ratings for the recommendations are 

presented in Table 16-2. 

The recommendations for total time spent 

indoors and the total time spent outdoors are based on 

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 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. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

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. The recommended 

values for time spent indoors at a residence, duration of 

showering and bathing, and time spent swimming are 

based on a U.S. EPA re-analysis of the source data from 

U.S. EPA (1996). Likewise, the recommended values 

for 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). 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-1. Recommended Values for Activity Factors 

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 

1,440 

1,432 

1,414 

1,301 

1,353 

1,316 

1,278 

1,244 

1,260 

1,248 

-

-

-

-

-

-

-

-

-

-

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. See Table 16-10. 

U.S. EPA re-analysis of source data from U.S. EPA, 1996 

for age groups from 1 to < 21 years. See Table 16-14. 

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 

0 

8 

26 

139 

36 

76 

107 

132 

100 

102 

-

-

-

-

-

-

-

-

-

-

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. See Table 16-10. 

U.S. EPA re-analysis of source data from U.S. EPA, 1996 

for age groups from 1 to < 21 years. See Table 16-14. 

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 

1,108 

1,065 

979 

957 

893 

889 

833 

1,440 

1,440 

1,296 

1,355 

1,275 

1,315 

1,288 

U.S. EPA re-analysis of source data from U.S. EPA, 1996. 

Doers only. See Table 16-11. 

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. Doers only. See Table 16-18. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-1. Recommended Values for Activity Factors (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. Doers only. See Table 16-18. 

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 

96 

105 

116 

137 

151 

139 

145 

-

-

181 

181 

181 

181 

181 

U.S. EPA re-analysis of source data from U.S. EPA, 1996. 

Doers only. See Table 16-21. 

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 

43 

53 

60 

67 

67 

83 

-

121 

121 

121 

121 

121 

-

U.S. EPA re-analysis of source data from U.S. EPA, 1996. 

Doers only. See Table 16-22. 

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 

52 

68 

62 

79 

73 

75 

60 

-

121 

121 

121 

121 

121 

-

U.S. EPA re-analysis of source data from U.S. EPA, 1996. 

Doers only. See Table 16-22. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-1. Recommended Values for Activity Factors (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 

33 

56 

47 

63 

63 

49 

30 

-

121 

121 

121 

121 

120 

-

U.S. EPA re-analysis of source data from U.S. EPA, 1996. 

Doers only. See Table 16-22. 

- Percentiles were not calculated for sample sizes less than 10. 

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. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-2. Confidence in Recommendations for Activity Factors 

General Assessment Factors Rationale Rating 

Soundness 

Adequacy of Approach 

Minimal (or Defined) Bias 

The survey methodologies and data analyses were adequate. 

In the U.S. EPA (1996) study, responses were weighted 

according to this demographic data. 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. 

U.S. EPA (1996) was a nationally representative survey of 

the U.S. population; 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. 

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 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

16.3 ACTIVITY PATTERNS 

This section briefly describes published time-use 

studies that provide information on time-activity 

patterns of children in the U.S. For a detailed 

description of the studies, the reader is referred to the 

Exposure Factors Handbook (U.S. EPA, 1997). 

16.3.1	 KEY 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 percent. 

One child was selected from each household. If the 

selected child was 8 years old or less, 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 

socio-demographic 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 four 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 ten 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 6-3. 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 percent of the respondents 

reported missing activity time. 

Table 16-4 presents the mean time spent in 

the 10 activity categories by age and gender. Because 

the original source data were available, U.S. EPA reanalyzed 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 16-5 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 16-6 presents the distribution of time 

across six 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 percent of respondents spent time at 

home (mean of 1,086 minutes/day for these individuals 

only). Tables 16-7 and 16-8 show the average time 

spent in the six locations grouped by age and gender, 

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 

16-7 by the standardized age categories used in this 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

handbook. There were relatively large differences 

among the age groups in time expenditure for 

educational settings (Table 16-7). There were small 

differences in time expenditure at the six locations by 

region, but time spent in school decreased in the 

summer months compared to other seasons (Table 16­

8). 

Table 16-9 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 16-9 have been modified to 

conform to the standardized categories used in this 

handbook. 

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 16-10 

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-hr) data; therefore, the data set obtained may 

be biased. Other limitations are: 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., gender, 

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, gender, 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 - National Human Activity 

Pattern Survey (NHAPS) 

U.S. EPA (1996) analyzed data collected by 

the National Human Activity Pattern Survey (NHAPS). 

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 percent, overall. If the chosen respondent was a 

child too young to interview, 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 subgroups of the U.S. 

population (i.e., by gender, age, race, employment 

status, census region, season, etc.). The participants’ 

responses were 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 gender, age 

group, census region, and the day-of-week and seasonal 

responses were equally distributed. Saturdays and 

Sundays were over sampled to ensure an adequate 

weekend sample. 

Tables 16-11 through 16-24 provide data 

from the NHAPS study. In most cases, the source data 

from U.S. EPA have been reviewed and re-analyzed by 

U.S. EPA to conform to the age categories 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

recommended in Guidance for Monitoring and 

Assessing Childhood Exposures to Environmental 

Contaminants (U.S. EPA, 2005) and used in this 

handbook. 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. For each 

location or activity, statistics were calculated for the 

entire survey population (i.e., whole population) and for 

the subset of the survey population that reported being 

in the location or doing the activity in question (i.e., 

doers only). When the sample size was 10 persons or 

fewer, percentile values were not calculated. Also note 

that some of these activities were not necessarily 

mutually exclusive (e.g. time spent in active sports 

likely overlaps with exercise time). 

Table 16-11 presents data for the time 

children spent in various rooms of the house (i.e., 

kitchen, living room, dining room, bathroom, bedroom, 

and garage), and all rooms combined. Table 16-12 

presents data for time spent in other indoor locations 

(i.e., restaurants, indoors at school, and 

grocery/convenience stores). Table 16-13 presents data 

for the time children spent outdoors on school 

grounds/playgrounds, parks or golf courses, or pool 

rivers, or lakes. Table 16-14 provides data on time 

spent in indoor and outdoor environments. 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

15 presents data for the time spent in various types of 

vehicles (i.e., car, truck/van, bus), and in all vehicles 

combined. Table 16-16 presents data for the time 

children spent in various major activity categories (i.e., 

sleeping, napping, eating, attending school, outdoor 

recreation, active sports, exercise, and walking). 

Table 16-17 through 16-19 provide data 

related to showering, bathing, and handwashing 

activities. Tables 16-20 and 16-21 provide data on 

monthly swimming (in a freshwater pool) frequency by 

the number of respondents and swimming duration, 

respectively. Table 16-22 provides data on the time 

children spent playing on dirt, sand/gravel, or grass, and 

Table 16-23 provides data on the number of minutes 

spent near excessive dust. Table 16-24 provides 

information on time spent in the presence of smokers. 

For this data set, the authors’ original age categories 

were used because the methodology used to generate 

the data could not be reproduced. 

The advantages of the NHAPS data set are 

that it is representative of the U.S. population and it has 

been adjusted to be balanced geographically, 

seasonally, and for day/time. Also, it is inclusive of all 

ages, genders, 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. 

16.3.2	 RELEVANT STUDIES 

16.3.2.1	 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 fourth grade and 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

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 16-25. On weekdays, 

children spend about 40 percent of their time sleeping, 

20 percent in school, and 10 percent eating, and 

performing personal care activities (Timmer et al., 

1985). The data in Table 16-25 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 16-26 presents the mean time children 

spent during weekdays and weekends performing major 

activities by five 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, 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 per 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 16-27 

summarizes the results of this analysis by age group and 

time 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 

because parents assisted younger children with keeping 

their diaries and with interviews, any bias that may have 

been created by having younger children record their 

data should have been minimized. 

16.3.2.2	 Robinson and Thomas, 1991 - Time Spent 

i n A c t i v i t i e s , L o c a t i o n s , a n d 

Microenvironments: A California-National 

Comparison 

Robinson and Thomas (1991) reviewed and 

compared data from the 1987-88 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. Of 

these respondents, 183 were children, ages 12 to17 

years in the CARB study and 340 were children, ages 

12 to 17 years, in the national study. Robinson and 

Thomas (1991) defined a set of 16 microenvironments 

based on the activity and location codes employed in 

the two studies. The mean durations of time spent in 

the 16 microenvironments by children, ages 12 to 17 

years, are presented in Table 16-28. In both studies, 

children spent the majority of their time sleeping, and 

engaging in leisure and work/study-related activities. 

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. In 

addition, 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 reanalyzed to conform to the standardized age categories 

used in this handbook. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

16.3.2.3	 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 athome and at-school activities for male and female 

children and adolescents. CARB performed two studies 

from 1987 to 1990; the first was focused on adults (18 

years and older) and adolescents (12-17 years old), and 

the second focused on children (6-11 years old). The 

targeted groups were noninstitutionalized 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 two groups, “at home” (any activity at 

principal residence) and “away.” Each activity was 

assigned to one of three 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 were 

determined for the aggregate age groups, as shown in 

Table 16-29. 

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 children were 

assigned a low or moderate inhalation rate rate (Table 

16-30). 

The aggregate time periods spent at home in 

each activity are shown in Table 16-31. Aggregate time 

spent at home performing different activities was 

compared between genders. There were no significant 

differences between adolescent males and females in 

any of the activity groups (Table 16-32). In children, 

ages 6-11 years, differences between gender and age 

were observed at the low inhalation rate levels. There 

were significant differences between two age groups (6­

8 years, and 9-11 years) and gender at the moderate 

inhalation rate level (Table 16-33). 

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 one 

geographic location, collected more that a decade ago. 

Thus, it may not be representative of current activities 

among the general population of the U.S. 

16.3.2.4	 U.S. EPA, 2000 - Consolidated Human 

Activity Database (CHAD) 

The Consolidated Human Activity Database 

(CHAD), available online at 

http://www.epa.gov/chadnet1/, was developed by the 

U.S. EPA's National Exposure Research Laboratory 

(NERL) to provide access to existing human activity 

data for use in exposure and risk assessment efforts. 

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 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

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 (Glenn et al., 2000). 

16.3.2.5	 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 

Hubal et al. (2000) reviewed available data 

from CHAD, including activity pattern data, to 

characterize and assess environmental exposures to 

children. CHAD contains 3,009 person-days of 

macroactivity data for 2,640 children less than 12 years 

of age (Hubal et al., 2000) (Table 16-34). The number 

of hours these children spent in various 

microenvironments are shown in Table 16-35 and the 

time they spent in various activities indoors at home is 

shown in Table 16-36. 

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 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 

Hubal et al. (2000) using CHAD data downloaded in 

2000, sorted according to the age groups recommended 

in Guidance for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants (U.S. EPA, 

2005). The results are shown in Tables 16-37 and 16­

38. In this analysis, individual study participants within 

CHAD whose behavior patterns were measured over 

multiple days were treated as multiple one-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. 

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 one 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 percent) 

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 16-39. The frequency (days/week), 

duration (hours/day), and total hours per week spent 

playing outdoors was determined for those children 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

identified as “players” (Table 16-40). 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 16-41. 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 16-42 compares 

mean play duration data from SCS-II to similar 

activities identified in NHAPS (U.S. EPA, 1996). 

Table 16-43 compares the number of times per day a 

child washed his or her hands, based on data from SCSII and NHAPS. As indicated in Tables 16-42 and 16­

43, where comparison is possible, NHAPS and SCS-II 

results showed similarities in observed behaviors. 

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, gender, 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 on time spent outdoors for people who 

spent >0 time outdoors (i.e., doers) are presented in 

Table 16-44. 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 gender 

differences in time spent outdoors by age cohorts was 

also conducted. Table 16-45 presents descriptive 

statistics and the results of the two-sample 

Kolmogorov-Smirnov (KS) test for this evaluation. As 

shown in Table 16-45, there were statistically 

significant gender differences in time spent outdoors 

starting with the 6 to 10 year old age category. 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 (Table 16-46), there 

were statistically significant effects for all the factors 

evaluated, with gender, weather, and day type being the 

most important variables. Regarding time spent in 

motor vehicles (Table 16-47), precipitation was the 

only factor found to have no significant effects (Graham 

and McCurdy, 2004). 

Based on the results of these analysis, 

Graham and McCurdy (2004) noted that “besides age 

and gender, 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 gender should be used as 

‘‘first-order’’ attributes, followed by physical activity 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

level, daily maximum temperature, and day type 

(weekend/weekday or day-of-the-week/working status) 

(Graham and McCurdy, 2004). 

16.3.2.8	 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 

(CDS) to the Panel Study of Income Dynamics (PSID). 

The PSID is a 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 one randomly 

selected weekday and one 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 diary data from 2,831 children 

participating in the CDS, Vandewater et al., (2004) 

estimated the time in minutes over the two-day study 

period (i.e., sum of time spent on one weekday and one 

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 16-48 presents the means and 

standard deviations for the time spent in the selected 

activities by age and gender. 

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. 

16.3.2.9	 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 one randomly selected weekday and one 

randomly selected weekend day (Juster et al., 2004). 

Tables 16-49 and 16-50 present the mean 

time children spent (in minutes/day) performing major 

activities on weekdays and weekend days, respectively, 

for the years 1981-82 and 2002-2003. Table 16-51 

shows the weekly time spent in these activities for the 

years 1981-82 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. 

16.3.2.10 U.S. Department of Labor, 2007 - American 

Time Use Survey, 2006 Results 

The American Time Use Study (ATUS) has 

been conducted annually since 2003 by the U.S. 

Department of Labor’s Bureau of Labor Statistics (U.S. 

DL, 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. Data were 

collected for all days of the week, including weekends 

(i.e., 10 percent of the individuals were interviewed 

about their activities on one of the five weekdays, and 

25 percent of the individuals were interviewed about 

their activities on one of the two weekend days). 

Demographic information, including age, gender, 

race/ethnicity, marital status, and educational level were 

also collected, and sample weights were applied to 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

records to “reduce bias in the estimates due to 

differences in sampling and response rates across 

subpopulations and days of the week.” Data were 

collected for 17 major activities, that were subsequently 

composited into 12 categories for publication of the 

results. Estimates of time use in these 12 major 

categories are presented in Table 16-52. These data 

represent the average hours per day spent by male, 

female, and all children ages 15 to 19 years in the 

various categories. Table 16-52 also provides a more 

detailed breakdown of the Leisure and Sports category 

for all children, ages 15 to 19 years old. 

16.3.2.11 Nader et al. 2008 - Moderate-to-Vigorous 

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 moderateto-vigorous 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 of a minimum of 60 minutes per day. 

Children’s activity levels were recorded for four to 

seven days using an accelerometer. The study 

participants included 517 boys and 515 girls. The study 

found that at age 9 children engaged in 3 hours of 

MVPA per day. By age 15, the amount of time 

engaged in MVPA was dropped to 49 minutes/day on 

weekdays and 35 minutes per 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 moderate-tovigorous activities by various age groups are presented 

in Table 16-53. The study did not provide information 

about the amount of time spent at specific activities. 

16.4	 REFERENCES FOR CHAPTER 16 

Chance,	 W.G.; Harmsen, E. (1998) Children are 

different: environmental contaminants and 

children’s health. Can J Public Health 

89(Supplement):59-513. 

Funk, L.; Sedman, R.; Beals, J.A.J.; Fountain, R. 

(1998) Quantifying the distribution of 

inhalation exposure in human populations: 

distributions of time spent by adults, 

adolescents, and children at home, at work, 

and at school. Risk Anal 18(1):47-56. 

Garlock, T.J.; Shirai, J.H.; Kissel, J.C. (1999) Adult 

responses to a survey of soil contact related 

behaviors. J Expo Anal Environ Epidemiol 

9:134-142. 

Glenn, G.; Stallings, C.; Tippett, J.; Smith, L. (2000) 

CHAD’s user guide: Extracting human 

activity information from CHAD on the PC. 

Prepared for the U.S. EPA National 

Exposure Research Laboratory by ManTech 

Environmental Technology, Inc. 

Graham,	 S.E.; McCurdy, T. (2004) Developing 

meaningful cohorts for human exposure 

models. J Expo Anal Environ Epidemiol 

14:23-43. 

Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McCurdy, 

T.R.; Berry, M.R.; Rigas, M.L.; Zartarian, 

V.G.; Freeman, N.G. (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 Persp 108:475­

485. 

Johnson, T. (1989) Human Activity Patterns in 

Cincinnati, Ohio. Palo Alto, CA: Electric 

Power Research Institute. 

Juster, F.T.; Hill, M.S.; Stafford, F.P.; Parsons, J.E. 

(1983) Study description. 1975-1981 time 

use longitudinal panel study. Ann Arbor, 

MI: The University of Michigan, Survey 

Research Center, Institute for Social 

Research. 

Juster, T.; Ono, H.; Stafford, F. (2004) Changing times 

of American youth: 1981-2003. Institute for 

Social Research, University of Michigan, 

Ann Arbor, Michigan. Available on-line at 

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 Database. 

J Expo Anal Environ Epidemiol 10:566-578. 

Nader , P.R.; Bradley, R.H.; Houts, R.M.; McRitchie, 

S.L.; O’Brien, M. (2008) Moderate-tovigorous physical activity from ages 9 to 15 

years. JAMA, 300(3):295-305. 

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Child-Specific Exposure Factors Handbook 

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Robinson, J.P.; Thomas, J. (1991) Time spent in 

activities, locations, and microenvironments: 

a California-National Comparison Project 

report. Las Vegas, NV: U.S. Environmental 

Protection Agency, Environmental 

Monitoring Systems Laboratory. 

Timmer, S.G.; Eccles, J.; O'Brien, K. (1985) How 

children use time. In: Juster, F.T.; Stafford, 

F.P.; eds. Time, goods, and well-being. Ann 

Arbor, MI: University of Michigan, Survey 

Research Center, Institute for Social 

Research, pp. 353-380. 

U.S. Department of Health and Human Services and 

U.S. Department of Agriculture. (2005) 

Dietary Guidelines for Americans, 2005. 6th 

edition, Washington, DC, Government 

Printing Office. Available online at 

http://www.health.gov/dietaryguidelines/dg 

a2005/document/pdf/DGA2005.pdf U.S. 

Department	 of Labor (U.S. DL), Bureau of Labor 

Statistics. (2007) American Time Use Survey 

- 2006 Results. News release issued at 

http://www.bls.gov/tus on June 28, 2007. 

U.S. EPA (1996) Descriptive statistics tables from a 

detailed analysis of the National Human 

Activity Pattern Survey (NHAPS) data. 

Washington, DC: Office of Research and 

Development. EPA/600/R-96/148. 

U.S.	 EPA (1997) Exposure Factors Handbook. 

Washington, DC: National Center for 

Environmental Assessment, Office of 

Research and Development. EPA/600/P95/002Fa,b,c. 

U.S. EPA (2000) Consolidated Human Activity 

Database (CHAD). U.S. EPA/NERL. 

Available online at 

http://www.epa.gov/chadnet1/ 

U.S. EPA. (2005) Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants. 

U.S. Environmental Protection Agency, 

Washington, D.C., EPA/630/P-03/003F. 

Vandewater, E.A.; Shim, M.; Caplovitz, A.G. (2004) 

Linking obesity and activity level with 

children’s television and video game use. J 

Adolesc 27:71-85. 

Wiley, J.A.; Robinson, J.P.; Cheng, Y.; Piazza, T.; 

Stork, L.; Plasden, K. (1991) Study of 

children’s activity patterns. California 

Environmental Protection Agency, Air 

Resources Board Research Division. 

Sacramento, CA. 

Wong, E.Y.; Shirai, J.H; Garlock, T.J.; Kissel, J.C. 

(2000) Adult proxy responses to a survey of 

children’s dermal soil contact activities. J 

Expo Anal Environ Epidemiol 10:509-517. 

Page Child-Specific Exposure Factors Handbook 

16-16 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-3. 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 

Goods/Services e 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/Social i 15 17 87 60 490 Visiting with Others 

Recreation j 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 an 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-17
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

c 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-4. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
 

Ten Major Activity Categories, by Age and Gender
 

Boys 

(Unweighted) 

Activity 

Categorya 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 

Yearsb 

Birth to 11 

Years 

Work-related 0 0 0 1 8 9 10 12 13 11 

Household 12 30 49 28 35 44 44 61 63 58 

Childcare 0 0 0 0 0 0 0 0 3 2 

Goods/Services 0 16 14 28 27 14 28 22 24 26 

Personal Needs and Care 910 1,143 937 919 903 889 802 726 707 802 

Education 180c 0 75 70 33 69 67 120 120 100 

Organizational Activities 0 0 0 0 7 0 5 11 16 6 

Entertainment/Social 0 0 0 0 8 6 15 15 43 18 

Recreation 0 0 26 104 314 304 294 265 227 228 

Communication/Passive 

Leisure 338 250 339 292 106 103 175 208 226 226 

Sample Sizes 

(Unweighted) 3 7 15 31 54 62 151 239 62 624 

Girls 

Activity 

Categorya 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 

Yearsb 

Birth to 11 

Years 

Work-related 0 0 5 1 3 22 9 10 19 11 

Household 28 29 23 25 45 65 49 67 78 58 

Childcare 0 0 0 0 0 0 0 2 9 2 

Goods/Services 0 18 14 24 24 34 31 26 15 26 

Personal Needs and Care 1,123 1,115 971 922 894 858 820 747 703 802 

Education 0 0 110 94 25 40 81 134 151 100 

Organizational Activities 0 0 0 0 0 2 3 8 13 6 

Entertainment/Social 0 0 0 1 13 6 16 17 52 18 

Recreation 0 0 10 147 256 305 270 224 175 228 

Communication/Passive 

Leisure 290 278 308 226 179 107 161 203 225 189 

Sample Sizes 4 10 11 23 43 50 151 225 59 576 

a	 See Table 16-3 for a description of what is included in each activity category. b	 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. 

The data for this age group and category are two values of zero and one of 540. 

Note:	 Column totals may not sum to 1,440 due to rounding. 

Source:	 U.S. EPA analysis of source data used by Wiley et al., 1991. 

Page Child-Specific Exposure Factors Handbook 

16-18 September 2008 
 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-5. 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 Bay Rest of All 

(Jan-Mar) (Apr-June) (July-Sept) (Oct-Dec) Seasons Coast 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 799 774 815 789 794 799 785 794 794 Care 

Education 124 137 49 131 110 109 115 109 110 

Organizational 3 5 5 3 4 2 6 6 4 Activities 

Entertainment/Social 14 12 12 22 15 17 10 16 15 

Recreation 221 243 282 211 239 230 241 249 239 

Communication/ 203 180 189 195 192 206 190 175 192 Passive Leisure 

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 318 204 407 271 1,200 224 263 713 1,200 (Unweighted) 

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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-19
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-6. Time (minutes/day) Children Under 12 Years of Age Spent in 

Six 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. 

Page Child-Specific Exposure Factors Handbook 

16-20 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-7. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
 

Six Location Categories, Grouped by Age and Gender
 

(Unweighted) 

Boys 

Location Category 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 938 1,295 1,164 1,189 1,177 1,161 1,102 1,016 1,010 1,079 

School/Childcare 0 1 26 53 73 86 79 110 99 89 

Friend's/Other's House 418 40 127 63 54 69 89 110 111 95 

Stores, Restaurants, 

Shopping Places 0 14 21 36 29 22 24 23 20 24 

In-transit 77 51 69 63 56 61 67 64 72 65 

Other Locations 7 40 33 36 52 41 78 116 127 88 

Don't Know/Not Coded 0 0 0 0 0 0 0 0 0 0 

Sample Sizes 

(Unweighted) 3 7 15 31 54 62 151 239 62 624 

Girls 

Location Category 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 1,285 1,341 1,151 1,192 1,162 1,065 1,118 1,012 862 1,058 

School/Childcare 0 0 109 99 56 61 78 116 128 95 

Friend's/Other's House 0 12 44 32 109 103 66 119 193 103 

Stores, Restaurants, 

Shopping Places 0 13 20 15 21 40 32 25 24 27 

In-transit 73 56 42 58 55 86 78 70 95 74 

Other Locations 83 19 73 43 38 86 67 97 137 84 

Don't Know/Not Coded 0 0 0 0 0 0 1 0 0 0 

Sample Sizes 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. 

Note:	 Column totals may not sum to 1,440 due to rounding. 

Source:	 U.S. EPA analysis of source data used by Wiley et al., 1991. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-21
 
 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-8. Mean Time (minutes/day) Children Under 12 Years of Age Spent in 

Six Location Categories, Grouped by Season and Region 

Season Region of California 

Location Category Winter Spring Summer Fall All Southern Bay Rest of All 

(Jan-Mar) (Apr-June) (July-Sept) (Oct-Dec) Seasons Coast Area State Regions 

Home 1,091 1,042 1,097 1,081 1,078 1,078 1,078 1,078 1,078 

School/Childcare 119 141 52 124 109 113 103 108 109 

Friend's/Other's 

House 69 75 108 69 80 73 86 86 80 

Stores, Restaurants, 

Shopping Places 22 21 30 24 24 26 23 23 24 

In transit 75 75 60 65 69 71 73 63 69 

Other Locations 63 85 93 76 79 79 76 81 79 

Don't Know/Not 

Coded <1 <1 <1 <1 <1 <1 <1 <1 <1 

All Locationsa 1,439 1,439 1,440 1,439 1,439 1,439 1,440 1,440 1,439 

Sample Sizes 

(Unweighted N's) 318 204 407 271 1,200 224 263 713 1,200 

a The column totals may not sum to 1,440 due to rounding. 

Source: Wiley et al., 1991. 

Page Child-Specific Exposure Factors Handbook 

16-22 September 2008 
 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-9. Mean Time (minutes/day) Children Under 12 Years of Age Spent in
 

Proximity to Two Potential Sources of Exposure, Grouped by All Respondents, Age, and Gender
 

Boys Potential 

Birth to	 1 to <3 3 to <6 6 to <12 1 to <2 2 to <3 3 to <6 6 to <11 11 Birth to 11 Exposures 1Month Months Months Months Years Years Years Years Yearsa Years 

Gasoline Fumes 3 9 0 2 1 4 2 2 7 3 

Gas Oven Fumes 0 0 2 2 1 3 0 1 0 1 

Sample Sizes 3	 7 15 31 54 62 151 239 62 624 (Unweighted N's) 

Girls 

Potential 

Birth to	 1 to <3 3 to <6 6 to <12 1 to <2 2 to <3 3 to <6 6 to <11 11 Birth to 11 Exposures 1Month Months Months Months Years Years Years Years Yearsa Years 

Gasoline Fumes 0 3 0 3 1 2 1 2 1 2 

Gas Oven Fumes 0 0 0 0 0 3 2 1 0 1 

Sample Sizes 4 10 11 23 43 50 151 225 59 576 (Unweighted N's) 

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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-23
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

c 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-10. Mean Time (minutes/day) Children Under 12 Years of Age
 

Spent Indoors and Outdoors, Grouped by Age and Gender
 

Age Group N 

Boys 

Indoorsa Outdoorsb N 

Girls 

Indoorsa Outdoorsb 

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 Yearsc 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. 

Page Child-Specific Exposure Factors Handbook 

16-24 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined 

Whole Population and Doers Only 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-25
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined 

Whole Population and Doers Only (continued) 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 

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 

Page Child-Specific Exposure Factors Handbook 

16-26 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined 

Whole Population and Doers Only (continued) 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-27
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-11. Time Spent (minutes/day) in Various Rooms at Home and in All Rooms Combined 

Whole Population and Doers Only (continued) 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 (NHAPS). 

Page Child-Specific Exposure Factors Handbook 

16-28 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations 

Whole Population and Doers Only 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Restaurants - Whole Population 

Birth to <1 63 13 0 0 0 0 0 0 0 0 45 69 105 194 330 

1 to <2 118 7 0 0 0 0 0 0 0 0 30 62 88 102 120 

2 to <3 118 9 0 0 0 0 0 0 0 0 45 62 92 111 120 

3 to <6 357 7 0 0 0 0 0 0 0 0 21 52 90 120 130 

6 to <11 497 6 0 0 0 0 0 0 0 0 15 45 85 110 180 

11 to <16 466 10 0 0 0 0 0 0 0 0 35 60 90 137 315 

16 to <21 481 35 0 0 0 0 0 0 0 20 105 240 380 466 645 

Restaurants - DOERS ONLY 

Birth to <1 10 85 10 - - - - - - - - - - - 330 

1 to <2 15 58 5 6 8 12 21 33 55 83 99 110 116 118 120 

2 to <3 17 63 20 21 22 24 28 45 60 80 102 116 118 119 120 

3 to <6 43 57 4 7 9 10 16 30 45 90 120 120 122 126 130 

6 to <11 57 54 5 5 6 10 15 30 45 60 107 124 140 158 180 

11 to <16 78 59 2 3 7 10 18 30 45 65 102 141 223 283 315 

16 to <21 135 126 1 4 5 10 17 30 60 170 334 437 537 546 645 

School - Whole Population 

Birth to <1 63 4 0 0 0 0 0 0 0 0 0 0 46 100 165 

1 to <2 118 13 0 0 0 0 0 0 0 0 0 22 156 453 665 

2 to <3 118 23 0 0 0 0 0 0 0 0 0 193 414 503 545 

3 to <6 357 75 0 0 0 0 0 0 0 0 416 540 569 589 630 

6 to <11 497 187 0 0 0 0 0 0 0 397 444 480 552 601 665 

11 to <16 466 201 0 0 0 0 0 0 0 420 459 495 578 630 855 

16 to <21 481 131 0 0 0 0 0 0 0 308 430 495 566 629 855 

School - DOERS ONLY 

Birth to <1 2 - 60 - - - - - - - - - - - 165 

1 to <2 8 - 5 - - - - - - - - - - - 665 

2 to <3 11 251 10 10 10 10 10 83 269 388 510 528 538 542 545 

3 to <6 71 379 5 23 34 110 160 228 418 540 570 590 615 627 630 

6 to <11 235 396 5 64 129 195 305 370 400 435 480 540 612 643 665 

11 to <16 229 409 15 38 96 132 290 395 420 450 495 559 631 696 855 

16 to <21 171 367 15 22 31 90 185 270 388 440 525 576 726 801 855 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-29
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-12. Time Spent (minutes/day) at Selected Indoor Locations 

Whole Population and Doers Only (continued) 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 (NHAPS). 

Page Child-Specific Exposure Factors Handbook 

16-30 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-13. Time Spent (minutes/day) in Selected Outdoor Locations 

Whole Population and Doers Only 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

School Grounds/Playground - Whole Population 

Birth to <1 63 2 0 0 0 0 0 0 0 0 0 0 0 53 140 

1 to <2 118 0 0 0 0 0 0 0 0 0 0 0 0 0 0 

2 to <3 118 4 0 0 0 0 0 0 0 0 0 0 50 131 175 

3 to <6 357 5 0 0 0 0 0 0 0 0 0 0 64 127 625 

6 to <11 497 8 0 0 0 0 0 0 0 0 10 60 121 170 315 

11 to <16 466 10 0 0 0 0 0 0 0 0 20 80 120 160 570 

16 to <21 481 8 0 0 0 0 0 0 0 0 0 50 135 180 510 

School Grounds/Playground - DOERS ONLY 

Birth to <1 1 - 140 - - - - - - - - - - - 140 

1 to <2 0 - - - - - - - - - - - - - -

2 to <3 5 - 10 - - - - - - - - - - - 175 

3 to <6 12 138 20 22 24 31 42 59 118 138 150 364 521 573 625 

6 to <11 52 80 10 10 10 10 15 30 59 106 169 217 280 298 315 

11 to <16 62 72 3 4 5 5 5 21 53 95 149 178 217 360 570 

16 to <21 34 116 10 10 10 13 18 46 95 161 201 305 418 464 510 

Parks or Golf Courses - Whole Population 

Birth to <1 63 3 0 0 0 0 0 0 0 0 0 0 45 63 85 

1 to <2 118 3 0 0 0 0 0 0 0 0 0 0 0 25 360 

2 to <3 118 12 0 0 0 0 0 0 0 0 0 24 126 246 755 

3 to <6 357 10 0 0 0 0 0 0 0 0 0 71 163 220 585 

6 to <11 497 16 0 0 0 0 0 0 0 0 0 72 328 483 665 

11 to <16 466 19 0 0 0 0 0 0 0 0 0 114 265 452 1,065 

16 to <21 481 22 0 0 0 0 0 0 0 0 0 150 381 546 870 

Parks or Golf Courses - DOERS ONLY 

Birth to <1 3 - 30 - - - - - - - - - - - 85 

1 to <2 2 - 30 - - - - - - - - - - - 360 

2 to <3 7 - 21 - - - - - - - - - - - 755 

3 to <6 26 144 25 26 28 31 44 63 113 165 273 388 505 545 585 

6 to <11 34 236 25 30 35 43 52 73 123 394 568 644 662 663 665 

11 to <16 38 237 15 15 15 15 27 86 164 266 470 851 954 1,010 1,065 

16 to <21 47 225 1 7 14 15 24 60 160 308 557 633 677 773 870 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-31
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-13. Time Spent (minutes/day) in Selected Outdoor Locations 

Whole Population and Doers Only (continued) 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Pool, River, or Lake - Whole Population 

Birth to <1 63 0 0 0 0 0 0 0 0 0 0 0 0 0 0 

1 to <2 118 1 0 0 0 0 0 0 0 0 0 0 0 0 118 

2 to <3 118 12 0 0 0 0 0 0 0 0 0 14 228 352 435 

3 to <6 357 5 0 0 0 0 0 0 0 0 0 0 85 163 630 

6 to <11 497 9 0 0 0 0 0 0 0 0 0 0 220 295 375 

11 to <16 466 4 0 0 0 0 0 0 0 0 0 0 60 160 235 

16 to <21 481 8 0 0 0 0 0 0 0 0 0 0 145 240 570 

Pool, River, or Lake - DOERS ONLY 

Birth to <1 0 - - - - - - - - - - - - - -

1 to <2 1 - 118 - - - - - - - - - - - 118 

2 to <3 6 - 95 - - - - - - - - - - - 435 

3 to <6 9 - 45 - - - - - - - - - - - 630 

6 to <11 24 178 25 26 27 32 46 75 155 294 319 359 370 373 375 

11 to <16 16 121 58 58 59 59 60 60 85 206 225 228 232 234 235 

16 to <21 22 179 20 22 24 31 40 55 125 238 415 548 564 567 570 

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 (NHAPS). 

Page Child-Specific Exposure Factors Handbook 

16-32 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-14. Mean Time Spent (minutes/day) Inside and Outside, by Age Category 

Age (years) N Average Indoor Minutesa 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 (NHAPS). 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-33
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined 

Whole Population and Doers Only 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Car - Whole Population 

Birth to <1 63 36 0 0 0 0 0 0 10 49 107 171 208 220 235 

1 to <2 118 41 0 0 0 0 0 0 20 60 98 151 246 336 390 

2 to <3 118 33 0 0 0 0 0 0 20 50 90 126 163 187 215 

3 to <6 357 43 0 0 0 0 0 0 20 60 117 155 221 272 620 

6 to <11 497 37 0 0 0 0 0 0 15 55 102 146 185 212 630 

11 to <16 466 39 0 0 0 0 0 0 15 55 99 150 254 302 900 

16 to <21 481 61 0 0 0 0 0 8 40 90 155 195 249 321 380 

Car - DOERS ONLY 

Birth to <1 35 65 2 5 7 10 14 20 40 73 159 203 218 227 235 

1 to <2 68 72 5 8 10 10 15 30 58 85 147 186 323 363 390 

2 to <3 73 54 4 4 4 8 10 24 42 65 118 141 181 197 215 

3 to <6 227 67 4 4 5 7 10 25 45 88 150 180 267 327 620 

6 to <11 317 58 1 2 2 5 10 20 40 82 127 163 202 300 630 

11 to <16 286 64 1 3 5 5 10 20 40 75 122 193 279 338 900 

16 to <21 364 81 2 9 10 10 17 30 60 105 180 210 275 334 380 

Truck (Pickup or Van) - Whole Population 

Birth to <1 63 2 0 0 0 0 0 0 0 0 0 0 0 42 110 

1 to <2 118 2 0 0 0 0 0 0 0 0 0 0 52 81 90 

2 to <3 118 14 0 0 0 0 0 0 0 0 14 31 124 201 955 

3 to <6 357 5 0 0 0 0 0 0 0 0 0 30 60 114 245 

6 to <11 497 7 0 0 0 0 0 0 0 0 15 45 95 110 240 

11 to <16 466 9 0 0 0 0 0 0 0 0 15 59 153 181 352 

16 to <21 481 11 0 0 0 0 0 0 0 0 25 90 150 190 445 

Truck (Pickup or Van) - DOERS ONLY 

Birth to <1 1 - 110 - - - - - - - - - - - 110 

1 to <2 5 - 20 - - - - - - - - - - - 90 

2 to <3 15 109 10 10 10 10 11 15 30 53 188 434 746 851 955 

3 to <6 34 53 1 2 4 8 10 16 30 59 117 207 222 233 245 

6 to <11 69 48 1 4 6 10 10 15 30 65 110 124 151 186 240 

11 to <16 62 67 5 5 5 5 7 15 35 89 180 185 258 299 352 

16 to <21 70 78 5 5 5 10 11 22 54 115 170 213 238 304 445 

Page Child-Specific Exposure Factors Handbook 

16-34 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-15. Time Spent (minutes/day) in Selected Vehicles and All Vehicles Combined 

Whole Population and Doers Only (continued) 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 

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 (NHAPS). 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-35
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-16. Time Spent (minutes/day) in Selected Activities 

Whole Population and Doers Only 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Sleeping/Napping - Whole Population 

Birth to <1 63 782 485 519 546 579 613 668 762 873 1,011 1,080 1,121 1,144 1,175 

1 to <2 118 779 360 483 510 579 627 700 780 855 925 962 987 1098 1,320 

2 to <3 118 716 270 365 470 523 594 635 708 805 870 917 937 944 990 

3 to <6 357 681 0 480 510 539 573 630 675 735 795 840 893 916 1,110 

6 to <11 497 613 120 295 390 458 510 570 625 660 720 750 831 868 945 

11 to <16 466 569 0 320 376 415 450 510 558 630 705 762 809 907 1,015 

16 to <21 481 537 0 239 295 360 390 450 525 615 690 750 840 906 1,317 

Sleeping/Napping - DOERS ONLY 

Birth to <1 63 782 485 519 546 579 613 668 762 873 1,011 1,080 1,121 1,144 1,175 

1 to <2 118 779 360 483 510 579 627 700 780 855 925 962 987 1,098 1,320 

2 to <3 118 716 270 365 470 523 594 635 708 805 870 917 937 944 990 

3 to <6 356 683 420 491 510 540 578 630 675 738 795 840 893 916 1,110 

6 to <11 497 613 120 295 390 458 510 570 625 660 720 750 831 868 945 

11 to <16 465 571 150 341 379 415 450 510 560 630 705 762 809 907 1,015 

16 to <21 480 538 85 252 299 360 390 450 525 615 690 751 840 906 1,317 

Eating - Whole Population 

Birth to <1 63 117 0 6 12 36 45 73 110 145 194 224 334 345 345 

1 to <2 118 98 0 10 10 29 40 60 90 120 167 206 233 244 270 

2 to <3 118 92 15 15 15 20 30 60 89 120 157 176 198 208 270 

3 to <6 357 78 0 0 0 15 28 45 75 105 135 150 180 217 265 

6 to <11 497 65 0 0 0 10 20 35 60 88 115 139 155 176 255 

11 to <16 466 52 0 0 0 0 10 30 45 74 100 120 146 162 205 

16 to <21 481 52 0 0 0 0 0 20 40 65 105 135 192 210 630 

Eating - DOERS ONLY 

Birth to <1 62 118 10 16 23 40 46 77 110 148 195 224 335 345 345 

1 to <2 117 99 10 10 12 30 40 60 90 120 167 206 234 244 270 

2 to <3 118 92 15 15 15 20 30 60 89 120 157 176 198 208 270 

3 to <6 349 80 2 10 15 20 30 45 75 105 135 150 180 218 265 

6 to <11 480 67 5 10 10 15 20 40 60 90 115 140 157 179 255 

11 to <16 432 56 2 5 7 10 20 30 50 75 100 125 148 163 205 

16 to <21 426 59 2 5 9 10 15 30 45 75 105 144 197 210 630 

Page Child-Specific Exposure Factors Handbook 

16-36 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-16. Time Spent (minutes/day) in Selected Activities 

Whole Population and Doers Only (continued) 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Attending School Full-Time - Whole Population 

Birth to <1 63 11 0 0 0 0 0 0 0 0 0 0 83 265 550 

1 to <2 118 28 0 0 0 0 0 0 0 0 0 204 546 594 665 

2 to <3 118 65 0 0 0 0 0 0 0 0 334 502 564 618 710 

3 to <6 357 73 0 0 0 0 0 0 0 0 392 510 558 581 630 

6 to <11 497 183 0 0 0 0 0 0 0 390 435 460 525 570 645 

11 to <16 466 187 0 0 0 0 0 0 0 409 445 464 487 500 595 

16 to <21 481 117 0 0 0 0 0 0 0 270 408 445 489 551 825 

Attending School Full-Time - DOERS ONLY 

Birth to <1 3 - 60 - - - - - - - - - - - 550 

1 to <2 9 - 20 - - - - - - - - - - - 665 

2 to <3 20 385 20 37 53 103 119 226 458 520 576 632 679 694 710 

3 to <6 71 366 30 37 66 128 165 203 395 510 558 583 615 627 630 

6 to <11 234 389 60 125 164 211 311 370 390 425 460 497 570 600 645 

11 to <16 217 401 10 86 108 270 343 385 415 440 467 485 505 548 595 

16 to <21 162 347 20 46 78 126 195 270 370 420 459 519 567 609 825 

Outdoor Recreation -Whole Population 

Birth to <1 63 0 0 0 0 0 0 0 0 0 0 0 0 0 0 

1 to <2 118 0 0 0 0 0 0 0 0 0 0 0 0 0 0 

2 to <3 118 4 0 0 0 0 0 0 0 0 0 0 15 28 370 

3 to <6 357 6 0 0 0 0 0 0 0 0 0 0 60 172 630 

6 to <11 497 7 0 0 0 0 0 0 0 0 0 0 142 226 574 

11 to <16 466 6 0 0 0 0 0 0 0 0 0 0 142 191 465 

16 to <21 481 6 0 0 0 0 0 0 0 0 0 0 103 189 570 

Outdoor Recreation - DOERS ONLY 

Birth to <1 0 - - - - - - - - - - - - - -

1 to <2 0 - - - - - - - - - - - - - -

2 to <3 4 - 15 - - - - - - - - - - - 370 

3 to <6 11 207 30 30 30 30 30 60 150 240 585 608 621 626 630 

6 to <11 17 204 60 60 60 60 66 120 165 245 351 403 506 540 574 

11 to <16 22 138 5 5 5 5 11 60 126 180 234 411 446 456 465 

16 to <21 13 228 30 35 41 57 77 130 180 300 420 480 534 552 570 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-37
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-16. Time Spent (minutes/day) in Selected Activities 

Whole Population and Doers Only (continued) 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Active Sports - Whole Population 

Birth to <1 63 15 0 0 0 0 0 0 0 0 60 90 131 143 155 

1 to <2 118 20 0 0 0 0 0 0 0 0 68 131 180 201 270 

2 to <3 118 27 0 0 0 0 0 0 0 0 110 180 257 319 390 

3 to <6 357 40 0 0 0 0 0 0 0 30 135 242 330 408 630 

6 to <11 497 51 0 0 0 0 0 0 0 60 172 272 371 435 975 

11 to <16 466 53 0 0 0 0 0 0 0 74 168 245 309 425 1,065 

16 to <21 481 35 0 0 0 0 0 0 0 0 145 180 285 386 565 

Active Sports - DOERS ONLY 

Birth to <1 13 75 25 26 26 28 31 40 60 90 132 143 150 153 155 

1 to <2 24 96 10 15 19 30 33 60 73 131 180 201 240 255 270 

2 to <3 26 124 15 18 20 26 30 41 98 179 253 314 360 375 390 

3 to <6 97 149 15 20 29 30 30 60 120 180 315 354 559 625 630 

6 to <11 175 146 2 12 15 20 30 60 110 193 312 393 450 522 975 

11 to <16 179 137 5 5 15 15 30 60 115 180 261 314 442 533 1,065 

16 to <21 117 143 5 15 15 20 30 60 120 180 272 371 501 519 565 

Exercise - Whole Population 

Birth to <1 63 13 0 0 0 0 0 0 0 0 0 0 122 354 670 

1 to <2 118 2 0 0 0 0 0 0 0 0 0 0 25 30 150 

2 to <3 118 1 0 0 0 0 0 0 0 0 0 0 0 0 60 

3 to <6 357 3 0 0 0 0 0 0 0 0 0 0 0 54 525 

6 to <11 497 5 0 0 0 0 0 0 0 0 0 0 100 137 450 

11 to <16 466 5 0 0 0 0 0 0 0 0 0 30 70 114 245 

16 to <21 481 8 0 0 0 0 0 0 0 0 0 60 151 176 300 

Exercise - DOERS ONLY 

Birth to <1 2 - - - - - - - - - - - - - -

1 to <2 4 - - - - - - - - - - - - - -

2 to <3 1 - - - - - - - - - - - - - -

3 to <6 7 - - - - - - - - - - - - - -

6 to <11 20 124 15 17 19 25 30 60 100 146 226 284 384 417 450 

11 to <16 28 75 20 21 23 27 30 42 60 101 128 148 194 219 245 

16 to <21 41 99 15 15 15 25 30 40 90 145 180 240 260 280 300 

Page Child-Specific Exposure Factors Handbook 

16-38 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-16. Time Spent (minutes/day) in Selected Activities 

Whole Population and Doers Only (continued) 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Walking - Whole Population 

Birth to <1 63 6 0 0 0 0 0 0 0 0 9.2 29 64 104 160 

1 to <2 118 2 0 0 0 0 0 0 0 0 0 10 40 58 60 

2 to <3 118 3 0 0 0 0 0 0 0 0 10 17 45 54 60 

3 to <6 357 3 0 0 0 0 0 0 0 0 4 20 35 60 60 

6 to <11 497 4 0 0 0 0 0 0 0 0 14 30 40 55 170 

11 to <16 466 10 0 0 0 0 0 0 0 0 30 55 79 130 190 

16 to <21 481 8 0 0 0 0 0 0 0 0 20 45 90 127 410 

Walking - DOERS ONLY 

Birth to <1 9 - 4 - - - - - - - - - - - 160 

1 to <2 9 - 4 - - - - - - - - - - - 60 

2 to <3 19 19 1 1 1 2 2 7 10 28 51 56 58 59 60 

3 to <6 44 20 1 1 1 1 2 5 15 30 56 60 60 60 60 

6 to <11 118 18 1 1 1 2 2 5 10 25 40 51 65 94 170 

11 to <16 190 25 1 1 1 2 3 5 14 30 60 78 134 154 190 

16 to <21 128 30 1 1 2 2 3 5 18 32 62 120 148 175 410 

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 (NHAPS). 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-39
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-17. Number of Showers Taken per Day, by Number of Respondents 

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 = Total number. 

Source: U.S. EPA re-analysis of source data from U.S. EPA, 1996 (NHAPS). 

Page Child-Specific Exposure Factors Handbook 

16-40 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing and Showering 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-41
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-18. Time Spent (minutes) Bathing, Showering, and in Bathroom Immediately after Bathing and Showering (continued) 

Age 

(years) 

N Mean Min 

Percentiles 

Max 

1 2 5 10 25 50 75 90 95 98 99 

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 (NHAPS). 

Page Child-Specific Exposure Factors Handbook 

16-42 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-19. Range of Number of Times Washing the Hands at Specified Daily Frequencies by the Number of Respondents 

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 = Total number.
 

DK = Respondents answered "don't know".
 

Source: U.S. EPA re-analysis of source data from U.S. EPA, 1996 (NHAPS).
 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-43
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

0

0

0

0

2

0

0 

0

0

0

0

0

1

0 

0

0

1

5

7

2

0 

0

0

0

0

0

1

0 

0

0

0

1

0

0

0 

0

0

0

0

1

0

0 

Table 16-20. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents 

0

0

0

1

0

0

0 

0

0

0

0

0

0

0 

Times/Month 

Age 

(years) 

0

0

2

0

5

1

1
 

0

0

0

0

0

0

0
 

10 11 12 13 14 15 16 

Birth to <1 10 

(years) 18 20 23 24 25 26 28 29 30 32 40 42 45 50 60 DK 

0 

0 

0 

0 

0 

0 

0

0

0

0

0

0

0

1 

1to < 2 

2 to <3 18 

1

0

2

2

6

4

5 

0

0

0

1

0

0

0 

3 to <6 45 

6 to <11 76 15 10 

9

0

0

1

0

0

1

0 

1

0

0

3

3

2

3 

11 to <16 66 19 10 

16 to <21 50 

8

0

1

1

2

3

3

1 

0

0

1

0

0

0

0 

Times/Month
 

Age
 

7

0

0

0

1

1

1

2 

0

0

0

0

0

0

0 

Birth to <1 10 

6

2

0

1

1

3

4

2 

0

0

0

0

0

0

2 

1to < 2 

2 to <3 18 

5

0

1

1

2

5

5

6 

0

0

0

3 to <6 45 1

1

0

1 

6 to <11 76 

11 to <16 66 

4

0

0

0

5

5

3

6 

0

0

0

0

1

0

16 to <21 50 0

3

1

1

1

6

5

6

2 

0

0

0

0

0

0

0 

= Doer sample size. 

DK = Respondents answered “don't know”. 

2

4

3

4

7 

6 

0

0

0

2

3

2

6 

Source: U.S. EPA re-analysis of source data from U.S. EPA, 1996 (NHAPS). 

1

1

2

3

5 

6 

0

0

0

0

0

1

0 

8 

8

N

N

N

Page Child-Specific Exposure Factors Handbook 

16-44 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-21. Time Spent (minutes/month) Swimming in Freshwater Swimming Pool 

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 

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 (NHAPS). 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-45
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass 

Whole Population and Doers only 

Percentiles 

Age (years) N Mean Min Max 

1 2 5 10 25 50 75 90 95 98 99 

Playing on Dirt - Whole Population 

Birth to <1 11 15 0 0 0 0 0 0 0 10 20 71 

1 to <2 37 20 0 0 0 0 0 0 0 10 84 121 

2 to <3 61 18 0 0 0 0 0 0 0 20 60 120 

3 to <6 179 29 0 0 0 0 0 0 0 59 120 121 

6 to <11 98 28 0 0 0 0 0 0 0 60 120 121 

11 to <16 35 25 0 0 0 0 0 0 1 30 77 120 

16 to <21 7 9 0 - - - - - - - - -

Playing on Dirt - DOERS ONLY 

Birth to <1 5 33 2 - - - - - - - - - - - 121 

1 to <2 13 56 5 5 5 5 6 10 45 120 121 121 121 121 121 

2 to <3 24 47 5 5 5 5 7 15 30 60 121 121 121 121 121 

3 to <6 82 63 1 1 1 1 6 30 60 120 121 121 121 121 121 

6 to <11 44 63 2 3 5 10 15 30 60 120 121 121 121 121 121 

11 to <16 18 49 1 2 2 4 9 19 30 60 120 120 121 121 121 

16 to <21 2 30 30 - - - - - - - - - - - 30 

Playing on Sand/Gravel - Whole Population 

Birth to <1 10 4 0 - - - - - - - - - - - 20 

1 to <2 37 17 0 0 0 0 0 0 0 30 60 84 121 121 121 

2 to <3 58 24 0 0 0 0 0 0 0 30 120 121 121 121 121 

3 to <6 186 30 0 0 0 0 0 0 2 60 120 121 121 121 121 

6 to <11 101 30 0 0 0 0 0 0 0 60 120 121 121 121 121 

11 to <16 36 30 0 0 0 0 0 0 0 38 120 121 121 121 121 

16 to <21 8 42 0 - - - - - - - - - - - 121 

Playing on Sand/Gravel - DOERS ONLY 

Birth to <1 2 18 15 - - - - - - - - - - - 20 

1 to <2 15 43 5 5 5 5 7 15 30 60 103 121 121 121 121 

2 to <3 26 53 1 1 1 1 3 10 30 120 121 121 121 121 121 

3 to <6 93 60 3 3 3 5 8 25 60 90 121 121 121 121 121 

6 to <11 46 67 5 7 10 11 15 30 60 120 121 121 121 121 121 

11 to <16 16 67 1 3 5 12 15 26 60 120 121 121 121 121 121 

16 to <21 4 83 30 - - - - - - - - - - - 121 

Page Child-Specific Exposure Factors Handbook 

16-46 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-22. Time Spent (minutes/day) Playing on Dirt, Sand/Gravel, or Grass 

Whole Population and Doers Only (continued) 

Age (years) N Mean Min 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 

Max 

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 

-

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 (NHAPS). 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-47
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-23. Time Spent (minutes/day) Working or Being Near Excessive Dust in the Air 

Age (years) N 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 

-

-

-

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 (NHAPS). 

Table 16-24. Time Spent (minutes/day) with Smokers Present 

Age 

(years) 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 

224 318 314 21 1 25 105 190 475 775 1,050 

256 246 244 15 1 10 60 165 360 595 774 

1,140 

1,210 

864 

1,305 

1,250 

1,020 

1,440 

1,440 

1,260 

N 

Min 

Max 

Source: 

= Doer sample size. 

= Minimum. 

= Maximum. 

U.S. EPA, 1996 (NHAPS). 

Page Child-Specific Exposure Factors Handbook 

16-48 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-25. Mean Time Spent (minutes/day) Performing Major Activities, by Age, Sex and Type of Day 

Age (3 to 11 years) Age (12 to 17 years) 

Activity Weekdays Weekends Weekdays Weekends 

Boys Girls Boys Girls Boys Girls Boys Girls 

(N=118) (N=111) (N=118) (N=111) (N=77) (N=83) (N=77) (N=83) 

Market Work 16 0 7 4 23 21 58 25 

Household Work 17 21 32 43 16 40 46 89 

Personal Care 43 44 42 50 48 71 35 76 

Eating 81 78 78 84 73 65 58 75 

Sleeping 584 590 625 619 504 478 550 612 

School 252 259 - - 314 342 - -

Studying 14 19 4 9 29 37 25 25 

Church 7 4 53 61 3 7 40 36 

Visiting 16 9 23 37 17 25 46 53 

Sports 25 12 33 23 52 37 65 26 

Outdoors 10 7 30 23 10 10 36 19 

Hobbies 3 1 3 4 7 4 4 7 

Art Activities 4 4 4 4 12 6 11 9 

Playing 137 115 177 166 37 13 35 24 

TV 117 128 181 122 143 108 187 140 

Reading 9 7 12 10 10 13 12 19 

Household Conversations 10 11 14 9 21 30 24 30 

Other Passive Leisure 9 14 16 17 21 14 43 33 

NA 22 25 20 29 14 17 10 4 

Percent of Time Accounted for 94 92 93 89 93 92 88 89 

by Activities Above 

N = Sample size. 

NA = Unknown. 

- = No data. 

Source: Timmer et al., 1985. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-49
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-26. Mean Time Spent (minutes/day) in Major Activities, by Type of Day for Five Different Age Groups 

Activity 

Weekday Weekend 

Significant 

Effects 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 

NA 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. 

NA = Unknown. 

- = No data. 

Source: Timmer et al., 1985. 

Page Child-Specific Exposure Factors Handbook 

16-50 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-27. 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-51
 
 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-28. Mean Time Spent (minutes/day) in Various Microenvironments, 

Children Ages 12 to 17 Years National and California Surveys 

National Data 

Mean (Standard Error)a 

Microenvironment All Doers Onlyb 

N = 340 

Autoplaces 2 (1) 73 

Restaurant/Bar 9 (2) 60 

In-vehicle/Internal Combustion 79 (7) 88 

In-Vehicle/Other 0 (0) 12 

Physical/Outdoors 32 (8) 130 

Physical/Indoors 15 (3) 87 

Work/Study-Residence 22 (4) 82 

Work/Study-Other 159 (14) 354 

Cooking 11 (3) 40 

Other Activities/Kitchen 53 (4) 64 

Chores/Child 91 (7) 92 

Shop/Errands 26 (4) 68 

Other/Outdoors 70 (13) 129 

Social/Cultural 87 (10) 120 

Leisure-Eat/Indoors 237 (16) 242 

Sleep/Indoors 548 (31) 551 

CARB Data 

Mean (Standard Error)a 

Microenvironment All Doer Onlyb 

N = 183 

Autoplaces 16 (8) 124 

Restaurant/Bar 16 (4) 44 

In-Vehicle/Internal Combustion 78 (11) 89 

In-Vehicle/Other 1 (0) 19 

Physical/Outdoors 32 (7) 110 

Physical/Indoors 20 (4) 65 

Work/Study-Residence 25 (5) 76 

Work/Study-Other 196 (30) 339 

Cooking 3 (1) 19 

Other Activities/Kitchen 31 (4) 51 

Chores/Child 72 (11) 77 

Shop/Errands 14 (3) 50 

Other/Outdoors 58 (8) 78 

Social/Cultural 63 (14) 109 

Leisure-Eat/Indoors 260 (27) 270 

Sleep/Indoors 557 (44) 560 a Weighted values. b Doers only = respondents who reported participating in each activity/microenvironment. 

Source: Robinson and Thomas, 1991. 

Page Child-Specific Exposure Factors Handbook 

16-52 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-29. Gender and Age Groups 

Age Group a N 

6 to 8 years (males) 145 

6 to 8 years (females) 124 

9 to 11 years (males) 156 

9 to 11 years(females) 160 

12 to 17 years (males) 98 

12 to 17 years (females) 85 

a Children under the age of 6 were excluded because there were 

too few responses in the CARB study. 

N = Sample size. 

Source: Funk et al., 1998. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-53
 
 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-30. Assignment of At-Home Activities to Inhalation Rate Levels for Children 

Low Moderate 

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 

Source: Funk et al., 1998. 

Page Child-Specific Exposure Factors Handbook 

16-54 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

c 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-31. Aggregate Time Spent (minutes/day) At-Home in Activity Groups, by Adolescents and Childrena 

Activity Group 

Mean 

Adolescents 

SD Mean 

Children 

SD 

Low 789 230 823 153 

Moderate 197 131 241b 136 

High 1 11 3 17 

Highparticipants c 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). 

Represents time spent at-home by individuals participating in high inhalation rate level activities (i.e., doers). 

SD = Standard deviation. 

Source: Funk et al., 1998. 

Table 16-32. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender (Adolescents) 

Activity Group 

Mean 

Male 

SD Mean 

Female 

SD 

Low 775 206 804 253 

Moderate 181 126 241 134 

High 2 16 0 0 

SD = Standard deviation. 

Source: Funk et al., 1998. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-55
 
 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-33. Comparison of Mean Time Spent (minutes/day) At-Home, by Gender and Age for Childrena 

Males Females 

Activity 

Group 6-8 Years 9-11 Years 6-8 Years 9-11 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 

Highparticipant b 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. 

Page Child-Specific Exposure Factors Handbook 

16-56 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-34. Number of Person-Days/Individualsa for Children in CHAD Database 

Age Group All Studies Californiab Cincinnatic NHAPS-Air NHAPS-Water 

0 Year 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 three days of activity pattern data were obtained from each participant in this study, the number 

of person-days of data is approximately three 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: Hubal et al., 2000. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-57
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-35. Time Spent (hours/day) in Various Microenvironments, by Age 

Average Time ± Standard Deviation (Percent >0 Hours) 

Age (years) 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: Hubal et al., 2000. 

Page Child-Specific Exposure Factors Handbook 

16-58 September 2008 
 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-36. Mean Time Children Spent (hours/day) Doing Various
 

Macroactivities While Indoors at Home
 

Mean Time (Percent >0 Hours) 

Age 

Sleep or Shower or Watch TV or Read, Write, Think, Relax, (years) Eat Play Games Nap Bathe Listen to Radio Homework 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: Hubal et al., 2000. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-59
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-37. Time Children Spent (hours/day) in Various Microenvironments, by Age 

Recast into New Standard Age Categories 

Indoors at Home Outdoors at Home Indoors at School Outdoors at Park In Vehicle 

Age Group N Mean % Mean % Mean % Mean % Mean % 

Time Doing TIme Doing Time Doing Time Doing TIme Doing 

Birth to <1 month 123 19.6 98 1.7 21 4.3 3 1.3 3 1.3 63 

1 to <3 months 33 20.9 100 1.8 9 0.2 3 1.6 9 1.3 27 

3 to <6 months 120 19.6 100 0.8 8 7.8 7 1.3 6 1.1 14 

6 to <12 months 287 19.1 99 1.1 15 7.6 8 1.8 5 1.3 14 

1 to <2 years 728 19.2 99 1.4 34 6.4 9 1.5 5 1.1 27 

2 to <3 years 765 18.2 99 1.8 38 6.8 12 2.1 7 1.3 28 

3 to <6 years 2,110 17.3 100 1.9 43 5.9 26 1.6 10 1.3 29 

6 to <11 years 3,283 15.7 99 1.9 40 6.5 44 2.1 17 1.1 29 

11 to <16 years 2,031 15.5 97 1.7 30 6.6 45 2.6 15 1.3 42 

16 to <21 years 1,005 14.6 98 1.4 20 5.7 33 3.1 10 1.7 90 

N = Sample size. 

Source: Based on data source used by Hubal et al., 2000 (CHAD). 

Page Child-Specific Exposure Factors Handbook 

16-60 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-38. Time Children Spent (hours/day) in Various Macroactivities While Indoors at Home
 

Recast Into New Standard Age Categories
 

Shower or Watch TV/ Read, Write, Think, Relax, Eat Sleep or Nap Play Games Bathe Listen to Radio Homework Passive 

Age Group N 

Mean % Mean % Mean % Mean % Mean % Mean % Mean % 

Time Doing Time Doing Time Doing Time Doing Time Doing Time Doing 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 used by Hubal et al., 2000 (CHAD). 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-61
 
 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-39. Number and Percentage of Respondents with Children and Those Reporting
 

Outdoor Playa Activities in both Warm and Cold Weather
 

Warm Cold Respondents Child non- Child Playersa Weather Weather Players in Both Seasons with Children Players Playersa Players Source 

N N % N % N N % 

SCS-II base 197 128 65.0 69 35.0 127 100 50.8 

SCS-II over 483 372 77.0 111 23.0 370 290 60.0 sample 

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. 

Page Child-Specific Exposure Factors Handbook 

16-62 September 2008 
 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-40. 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 16-41. 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-63
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-42. NHAPS and SCS-II Play Durationa Comparison
 

Mean Play Duration
 O2 testb 

Data Source (minutes/day) 

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 2x2 Chi-square test for contingency between NHAPS and SCS-II. 

Source: Wong et al., 2000. 

Table 16-43. NHAPS and SCS-II Hand Wash Frequencya Comparison 

Data 

Source Season 

Percentb Reporting Frequency (times/day) of: 

O2 testc 

0 1-2 3-5 6-9 10-19 20-29 30+ “Don’t 

Know” 

NHAPS 

SCS-II 

NHAPS 

SCS-II 

Cold 3 18 51 17 7 1 1 3 

Cold 1 16 50 11 7 1 0 15 p = 0.06 

Warm 3 18 51 15 7 2 1 4 

Warm 0 12 46 16 10 1 0 13 p = 0.001 

a 

b 

c 

Source: 

Selected previous day activities in NHAPS; average day outdoor play on bare dirt or mixed grass and dirt in SCS-II. 

Results are reported as percentage of total for clarity. Incidence data were used in statistical tests. 

2x2 Chi-square test for contingency between NHAPS and SCS-II. 

Wong et al., 2000. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-44. 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 

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 x 100). 

Source: Graham and McCurdy, 2004. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 16-65
 
 

Table 16-45. Comparison of Daily Time Spent Outdoors (minutes/day),
 

Considering Gender and Age Cohort (Doers Only)a
 

Time Spent Outdoors in Minutes K-S Testb 

Age Group Gender N Minimum Median Maximum Mean SD COV (%) Dn P 2 D 

< 1 month Male 35 7 68 700 116 144 125 0.24 0.90 0.3964 

Female 22 2 58 333 73 78 106 - - - 

1 to 2 months Male 4 4 58 165 71 68 95 Cannot Test 

Female 1 225 225 225 225 - 0 

3 to 5 months Male 20 10 86 210 89 56 63 0.42 0.96 0.3158 

Female 7 50 140 510 187 153 81 

6 to 11 Male 53 10 60 450 95 83 87 0.07 1.00 0.3200 

months 

Female 38 5 68 270 86 67 77 

1 year Male 184 1 80 1,035 110 114 104 0.07 0.71 0.6896 

Female 205 4 70 511 95 82 86 

2 years Male 232 1 105 550 136 105 77 0.09 1.00 0.2705 

Female 216 2 90 525 131 111 84 

3 to 5 years Male 723 1 120 972 146 119 81 0.04 0.74 0.6465 

Female 612 2 120 701 144 113 78 

6 to 10 years Male 122 1 132 1,440 173 148 86 0.09 2.05 0.0004 

8 

Female 987 2 115 1,380 148 138 93 

11 to 15 years Male 779 1 125 1,440 171 169 99 0.17 3.12 < 

0.000

Female 640 1 90 1,371 134 153 114 

16 to 17 years Male 168 2 113 810 151 147 97 0.19 1.80 0.0030 

Female 188 1 68 1,083 109 141 129 

18 to 20 years Male 184 2 95 788 162 176 109 0.20 1.84 0.0023 

Female 167 1 50 606 99 119 120 

a Only data for individuals that spent >0 time outdoors and had 30 or more records are included in the analysis.
 b The two-sample Kolmogorov-Smirnov (K-S) test H0 is that the distribution of variable 1 is the same as variable 2, using a P2 test statistic at 

SD = Standard deviation.
 COV = Coefficient of variation (SD/mean x 100).
 Source: Graham and McCurdy, 2004. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-46. 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 

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 per 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 x 100). 

Source: Graham and McCurdy, 2004. 

Child-Specific Exposure Factors Handbook Page
 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-47. Time Spent (minutes/day) in Motor Vehicles 

Based on CHAD Data (Doers Only)a 

Age Group N Time Spent in Motor Vehiicles 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 

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 per 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 x 100). 

Source: Graham and McCurdy, 2004. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-48. Time Spent (minutes/two-day period)a in Various Activities by Children Participating in the
 

Panel Study of Income Dynamics (PSID), 1997 Child Development Supplement (CDS)
 

Boys (N = 1,444) Girls (N = 1,387) 

Age Group Meana Standard 

Deviation Meana Standard Deviation 

Television Use 

1 to 5 years 197 168 184 163 

6 to 8 years 263 165 239 159 

9 to 12 years 251 185 266 194 

Electronic Game Use 

1 to 5 years 8 38 5 40 

6 to 8 years 44 113 14 39 

9 to 12 years 57 102 18 47 

Computer Use 

1 to 5 years 7 28 7 35 

6 to 8 years 13 43 8 28 

9 to 12 years 27 71 15 43 

Print Useb 

1 to 5 years 21 32 23 34 

6 to 8 years 20 37 20 32 

9 to 12 years 19 47 29 56 

Highly Active Activitiesc 

1 to 5 years 42 74 34 78 

6 to 8 years 107 123 62 92 

9 to 12 years 137 149 63 88 

Moderately Active Activitiesd 

1 to 5 years 55 81 59 92 

6 to 8 years 31 65 37 69 

9 to 12 years 40 73 46 89 

Sedentary Activitiese 

1 to 5 years 55 71 54 71 

6 to 8 years 75 77 80 84 

9 to 12 years 110 109 122 111 

a Means represent minutes spent in each activity over a 2-day period (one weekday and one weekend 

day). b Print use represents time spent using print media including reading and being read to. c Includes all sport activities such as basketball, soccer, swimming, running or bicycling. d Includes activities such as singing, camping, taking music lessons, fishing, and boating. e Includes activities such as playing board games, doing puzzles, talking on the phone, and relaxing. 

N = Sample size. 

Source: Vanderwater et al., 2004. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-49. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekday 

2002-2003 1981-1982 

Activity Category 6 to 8 9 to 11 12 to 14 15 to 17 6 to 8 9 to 11 12 to 14 15 to 17 

years years years years years years years years 

Market work 0 0 1 22 - - - 28 

Household work 25 32 38 39 15 18 27 34 

Personal care 68 66 68 73 49 40 56 60 

Eating 60 57 54 49 81 73 69 67 

Sleeping, naps 607 583 542 515 595 548 473 499 

School 406 398 395 352 292 315 344 314 

Studying 29 39 49 50 8 29 33 33 

Church 4 5 5 3 9 9 9 3 

Visiting, socializing 16 25 25 53 - - - -

Sports 10 17 33 33 24 21 40 46 

Outdoor Activities 6 6 4 6 9 8 7 11 

Hobbies 1 1 1 2 2 2 4 6 

Art Activities 8 7 7 4 4 3 3 12 

Television 94 106 111 115 99 146 142 108 

Other passive leisure 9 10 24 39 - - - -

Playing 74 56 45 35 111 65 31 14 

Reading 11 12 11 7 5 9 10 12 

Being read to 2 1 0 0 - - - -

Computer activities 6 10 25 38 - - - -

Missing data 4 8 4 6 - - - -

- = Data not provided. 

Source: Juster et al., 2004. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-50. Mean Time Spent (minutes/day) in Various Activity Categories, by Age - Weekend Day 

2002-2003 1981-1982 

Activity Category 6 to 8 9 to 11 12 to 14 15 to 17 6 to 8 9 to 11 12 to 14 15 to 17 

years years years years years years years years 

Market work 0 0 9 39 - - - 48 

Household work 81 91 100 79 27 51 72 60 

Personal care 78 72 73 77 45 44 60 51 

Eating 89 80 69 64 80 78 68 65 

Sleeping, naps 666 644 633 629 641 596 604 562 

School 3 6 7 7 - - - -

Studying 5 9 20 24 2 12 15 30 

Church 41 37 36 30 56 53 32 37 

Visiting, socializing 61 66 58 91 - - - -

Sports 23 40 40 27 30 42 51 37 

Outdoor Activities 12 12 12 11 23 39 25 26 

Hobbies 2 1 4 5 5 3 8 3 

Art Activities 11 7 9 6 4 4 7 10 

Television 155 184 181 162 136 185 169 157 

Other passive leisure 14 15 40 54 - - - -

Playing 163 134 148 59 180 92 35 21 

Reading 14 15 13 7 9 10 10 18 

Being read to 1 1 0 0 - - - -

Computer activities 12 19 39 58 - - - -

Missing data 9 8 9 11 - - - -

- = Data not provided. 

Source: Juster et al., 2004. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-51. 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 

Household work 343 

Personal care 493 

Eating 426 

Sleeping, naps 4,092 

School 1,947 

Studying 238 

Church 94 

Visiting, socializing 287 

Sports 179 

Outdoor Activities 50 

Hobbies 12 

Art Activities 48 

Television 876 

Other passive leisure 166 

Playing 485 

Reading 77 

Being read to 5 

Computer activities 165 

Missing data 45 

126 

223 

356 

508 

3,758 

1,581 

158 

125 

132 

244 

100 

27 

40 

944 

39 

440 

69 

3 

0 

1,206 

Source: Juster et al., 2004. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-52. Mean Time Use (hours/day) by Children, Ages 15 to 19 Years 

hours/day Activity Male Female All 

Personal Carea 10.26 10.34 10.30 

Eating and Drinkingb 1.02 1.11 1.07 

Household Activitiesc 0.61 0.92 0.76 

Purchasing Goods and Servicesd 0.38 0.74 0.56 

Caring for and Helping Household Memberse 0.10 0.19 0.15 

Caring for and Helping Non-Household Membersf 0.20 0.23 0.21 

Working on Work-related Activitiesg 1.53 1.24 1.39 

Educational Activitiesh 3.08 3.51 3.29 

Organizational Civic and Religious Activitiesi 0.34 0.33 0.34 

Leisure and Sportsj 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-mailk 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:	 U.S. DL, 2007. 

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Child-Specific Exposure Factors Handbook 

Chapter 16 - Activity Factors 

Table 16-53. Mean Time Spent (minutes/day) in Moderate-to-Vigorous Physical Activity 

Weekday Weekend 

Age (years) Mean (SD) Mean (SD) 

Boys Girls Both Boys Girls Both 

9 190.8(53.2) 173.3(46.4) 181.8(50.6) 184.3(68.6) 173.3(64.3) 178.6(66.6) 

11 133.0(42.9) 115.6(36.3) 124.1(40.6) 127.1(59.5) 112.6(53.2) 119.7(56.8) 

12 105.3(40.2) 86.0(32.5) 95.6(37.8) 93.4(55.3) 73.9(45.8) 83.6(51.7) 

15 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. 

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Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

17 CONSUMER PRODUCTS 

17.1 INTRODUCTION 

Consumer products may contain toxic or 

potentially toxic chemical constituents to which 

children may be exposed as a result of their use. For 

example, household cleaners can contain ammonia, 

alcohols, acids, and/or organic solvents which 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. Children can be in 

environments where adults use household consumer 

products such as cleaners, solvents, and paints. As 

such, children can be passively exposed to chemicals 

in these products. Since children 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 on 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/risk (Steenbekkers, 2001). In 

addition, the factors that influence these behaviors are 

not well studied, but some studies have shown there is 

a large variation in behavior between persons 

(Steenbekkers, 2001). This chapter presents available 

information on the amounts, frequency, and duration 

of use for various consumer products found in typical 

households. 

The studies presented in the following 

sections represent readily available surveys from which 

data were collected on the frequency and duration of 

use and amount of use of cleaning products, household 

solvent products, cosmetic and other personal care 

products, and pesticides. For a more detailed 

presentation of data on the use of consumer products 

among the general population, the reader is referred to 

the Exposure Factors Handbook (U.S. EPA, 1997). 

The National Library of Medicine Household 

Products Database is a consumer guide that provides 

information on the potential health effects of chemicals 

contained in more than 7,000 common household 

products used inside and around the home. Although, 

this database does not provide exposure factor 

information, it contains information on chemical 

ingredients and their percentages in consumer 

products, which products contain specific chemical 

ingredients, acute and chronic effects of chemical 

ingredients, and manufacturer information. These 

data could be useful when conducting an exposure 

assessment for a specific chemical/active ingredient. 

The product categories are: auto products, inside the 

home, pesticides, landscape/yard, personal care, home 

maintenance, arts and crafts, pet care, and home office. 

The database can be searched by product name, 

product type, manufacturer, and ingredient. This 

database can be found at http://hpd.nlm.nih.gov. 

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 U.S. EPA in 1987 and consumer use of 

some products listed may have changed (e.g., aerosol 

product use has declined). Therefore, the reader is 

referred to the National Library of Medicine database 

as a source of more current information. 

The U.S. EPA Source Ranking Database 

(SRD) is another source of information on consumer 

products, but does not provide exposure factor data. 

SRD can be used to perform systematic screening-level 

reviews of more than 12,000 potential indoor pollution 

sources to identify high-priority product and material 

categories for further evaluation. It also can be used to 

identify products that contain a specific chemical. 

Information on the SRD can be found at: 

http://www.epa.gov/oppt/exposure/pubs/srd.htm. 

The Soaps and Detergents 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 amount of product used. The data used were 

compiled from a number of sources including, the 

Exposure Factors Handbook (U.S. EPA, 1997), 

cosmetic associations, and data from the SDA. The 

document entitled “Exposure and Risk Screening 

Methods for Consumer Product Ingredients” can be 

found on the SDA website under: 

http://www.cleaning101.com/files/Exposure_and_ 

Risk_Screening_Methods_for_Consumer_Product_ 

Ingredients.pdf. 

Child-Specific Exposure Factors Handbook Page
 

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Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

17.2	 RECOMMENDATIONS 

Due to 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. The 

user is referred to the contents/references of this 

chapter and Chapter 17 of the Exposure Factors 

Handbook (U.S. EPA, 1997) 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, conducted surveys to 

obtain information on frequency of use of various 

cosmetic products. Three surveys were conducted to 

collect data on the frequency of use of various cosmetic 

products and selected baby products. In the first of 

these three surveys CTFA (1983) conducted a oneweek prospective survey of 47 female employees and 

relatives of employees between the ages of 13 and 61 

years. In the second survey, a cosmetic manufacturer 

conducted a retrospective survey of 1,129 of its 

customers. The third survey was conducted by a 

market research bureau which sampled 19,035 female 

consumers nationwide over a 9-1/2 month period. Of 

the 19,035 females interviewed, responses from only 

9,684 females were tabulated (CTFA, 1983). The third 

survey was designed to reflect the sociodemographic 

(i.e., age, income, etc) characteristics of the entire U.S. 

population. 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). 

To obtain the average frequency of use for 

each cosmetic product, responses were averaged for 

each product in each survey. Thus, the 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 ten percent most extreme 

frequencies of use. Therefore, the highest remaining 

frequency of use was recorded as the upper 90th 

percentile value. Table 17-2 presents the amount of 

product used per application (grams) and the average 

and 90th percentile frequency of use per day for baby 

products and various cosmetic products for all the 

surveys. 

An advantage of the frequency data obtained 

from the third survey (market research bureau) is that 

the sample population was more likely to be 

representative of the U.S. population. Another 

advantage of the third dataset 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 which will 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. While the data in this 

study were not tabulated by age of the population, the 

study included some individuals in the age groups of 

interest for this handbook. 

17.3.2	 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. Children represented approximately 2,000 

of the respondents (499 respondents under 5 years of 

age; 703 respondents between 5 and 11 years; 589 

respondents between 12 and 17 years; and 799 

respondents between 18 and 24 years). 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 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

questions that were related to exposure events. For 

children under 10 years of age, adult members of the 

households gave proxy interviews. Demographic, 

including socioeconomic (gender, age, race, education, 

etc.), geographic (census region, state, etc.), and 

temporal (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 were also collected 

on duration and frequency of use of selected consumer 

products. Tables 17-3 through 17-10 present data on 

the number of minutes that survey respondents spent in 

activities working with or being near certain consumer 

products, including: 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. 

These data are presented according to the age 

categories used in NHAPS (1 to 4 years, 5 to11 years, 

12 to17 years, and 18 to 64 years). Table 17-11 

through 17-15 present data on the number of 

respondents in these age categories that used 

fragrances, aerosol sprays, pesticides (professionallyapplied and consumer-applied), and humidifiers. 

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 consumerapplied) were re-analyzed by U.S. EPA to generate 

data for the standardized age categories. These data 

are presented in Tables 17-16 and 17-17 for age groups 

less than 1 year, 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. Data for subsets of the first year of life (e.g., 1 

to 2 months, 3 to 5 months, etc.) were not available. 

As discussed in previous chapters of this 

handbook that used NHAPS as a data source, the 

primary advantage of NHAPS 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 may also introduce 

error into the calculation of the mean. 

17.3.3	 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 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 ten 

years of age in the household, and had used a pesticide 

within the last six months, were surveyed (Bass et al., 

2001). The survey population was predominantly 

female Hispanic and represented a survey response rate 

of approximately 74 percent. Study participants were 

selected by systematic random sampling. Among the 

households sampled, 3 percent had one child less than 

10 years old, 42 percent had two children less than 10 

years old, and 23 percent had three to five children in 

this age bracket. Pesticide use was assessed by a oneon-one interview in the home. Survey questions 

pertained to household pesticides used inside the house 

for insect control and outside the house for the control 

of weeds in the garden and to repel animals from the 

garden. As part of the interview, information was 

gathered on the frequency of use. 

Table 17-18 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: 13.5 

percent of the households used pesticides more than 

once per week; 18.2 percent used the products once per 

week; 28.4 percent used the products once per month; 

15.5 percent used the products once in three months; 

10.8 percent used the products once in six months; and 

8.8 percent used the products 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 

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Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

available. However, these data are the result of a 

community-based survey and are not representative of 

the U.S. general population. 

17.3.4	 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 from April to June 2000. Three hundred 

and sixty study subjects were recruited in ten U.S. 

cities (Atlanta, Georgia; Boston, Massachusetts; 

Chicago, Illinois; Denver, Colorado; Houston, Texas; 

Minneapolis, Minnesota; St. Louis, Missouri; San 

Bernadino, California; Tampa, Florida; and Seattle, 

Washington). The survey participants were women, 

ages 19-65 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 two-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 two-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 recruited, 

86.4 percent, 83.3 percent, and 85.6 percent completed 

the study and returned the diaries for lipstick, body 

lotion, and face cream, respectively (Loretz et al., 

2005). 

The survey data are presented in Table 17-19 

and 17-20. Table 17-19 provides the mean, median, 

and standard deviations for the frequency of use. 

Table 17-20 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 

U.S. and was not based on recall data. A limitation of 

the study is that the short duration (two 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, but the study does provide information on 

a population that includes the ages of interest for this 

document. Data for children could not be separated 

from that of the rest of the survey population. 

17.3.5	 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 between October 2001 and October 2002. 

A total of 360 women were recruited from ten U.S. 

cities (Atlanta, Georgia; Boston, Massachusetts; 

Chicago, Illinois; Denver, Colorado; Houston, Texas; 

Minneapolis, Minnesota; St. Louis, Missouri; San 

Bernadino, California; Tampa, Florida; and Seattle, 

Washington). The survey participants were women, 

ages 19-65 years old, who regularly used the test 

products. Subjects kept daily records on product usage 

(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 area(s) where these products were applied. 

For shampoo, subjects recorded information on their 

hair type (length, thickness, oiliness, straight or curly, 

and color treated or not). At the end of the two week 

period, unused portions of products were returned and 

weighed. Of the 360 subjects recruited per product, 

the study was completed by 329 participants for 

hairspray, 327 for spray perfume, 326 for liquid 

foundation, and 340 participants for shampoo, body 

wash, and solid antiperspirant. 

The survey data are presented in Tables 17-21 

through 17-23. Table 17-21 provides the minimum, 

maximum, mean, and standard deviations for the 

frequency of use. Table 17-22 provides percentile 

values for the amount of product applied per 

application. Table 17-23 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 

U.S. and did not rely on recall data. A limitation of 

Page Child-Specific Exposure Factors Handbook 

17-4 September 2008 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

the study is that the short duration (two weeks) may 

not accurately reflect long-term 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, but the study does provide 

information on a population that includes the ages of 

interest for this document. Data for children could not 

be separated from that of the rest of the survey 

population. 

17.3.6	 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 January 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. (2005; 2006). A total of 360 

women, ages 18 to 69 years of age, were recruited by 

telephone to provide diary records of product use over 

a two-week period. The study subjects were 

representative of four U.S. Census regions (Northeast, 

Midwest, South, and West). A total of 295, 297, and 

299 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 application(s) over a twoweek 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. Data on the number of applications per 

day are provided in Table 17-24. The average 

amounts of product applied per use day are shown in 

Table 17-25, and the average amounts of product 

applied per application are shown in Table 17-26. 

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. The limitations of the study are that the data 

were not provided by age group, but included ages in 

the study group that are relevant for this handbook. 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. 

17.3.7	 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 the year 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, California; Minneapolis, Minnesota; 

and Columbia, Missouri. Although the study was 

designed to assess exposure to phthalates, the authors 

collected information on the percentage of the total 

participants that used the baby products. Data were 

collected from questionnaire responses of the mothers 

and at study visits. The characteristics and the percent 

of the population using the studied baby products are 

shown in Table 17-27. Of the 163 infants studied, 94 

percent of the participants used baby wipes and 54 

percent used infant shampoo. 

The advantages of this study are that it 

specifically targeted consumer products used by 

children. The percent of the study population using 

these products was captured and the data were 

collected from a diverse ethnic population. The 

limitations are 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. 

17.4	 REFERENCES FOR CHAPTER 17 

Bass, J.; Ortega, L.; Rosales, C.; Petersen, N., Philen, 

R. (2001) What’s being used at home: a 

household pesticide survey. Pub Health 

9(3):138-144. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-5
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Cosmetic, Toiletry and Fragrance Association 

(CTFA). (1983) Summary of the results of 

surveys of the amount and frequency of use of 

cosmetic products by women. Prepared by 

Environ Corporation, Washington, DC for 

CTFA Inc., Washington, DC. 

Franklin, P. (2008) Household chemicals: good 

housekeeping or occupational hazard. Eur 

Respir J 31:489-491. 

Loretz, L.; Api, A.; Barraj, L.; Burdick, J.; Dressler, 

W.; Gettings, S.; Hsu, H.; Pan, Y.; Re, T.; 

Renskers, K.; Rothenstein, A.; Scrafford, C.; 

Sewall, C. (2005) Exposure data for cosmetic 

products: lipstick, body lotion, and face 

cream. Food Chem Toxicol 43:279-291. 

Loretz, L.; Api, A.; Barraj, L.; Burdick, J.; Davis, D.; 

Dressler, W.; Gilberti, E.; Jarrett, G.; Mann, 

S.; Pan, Y.; 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. 

Loretz, L.; Api, A.; Babcock, L; Barraj, L.; Burdick, 

J.; Cater, K.; Jarrett, G.; Mann, s.; Pan, Y.; 

Re, T.; Renskers, K.; Scrafford, C. (2008) 

Exposure data for cosmetic products: Facial 

cleanser, hair conditioner, and eye shadow. 

Food Chem Toxicol 46:1516-1524. 

Sathyanarayana, S.; Karr, C.; Lozano, P., Brown, E.; 

Calafat, M. (2008) Baby care products; 

possible sources of infant phthalate exposure. 

Pedriatrics 121:260-268. 

Steenbekkers, L.P. (2001) Methods to study everyday 

use of products un households: The 

Wageningen mouthing study. Am Occup 

Hyg 45(1001):125-129. 

U.S. EPA (1987) Methods for assessing exposure to 

chemical substances - Volume 7 - Methods 

for assessing consumer exposure to chemical 

substances. Washington, DC: Office of Toxic 

Substances. EPA/560/5-85/007. 

U.S. EPA (1996) Descriptive statistics tables from a 

detailed analysis of the National Human 

Activity Pattern Survey (NHAPS) data. 

Washington, DC: Office of Research and 

Development. EPA/600/R-96/148. 

U.S.	 EPA (1997) Exposure Factors Handbook. 

Washington, DC: National Center for 

Environmental Assessment, Office of 

Research and Development. EPA/600/P95/002FC. 

U.S. EPA. (2005) Guidance on Selecting Age Groups 

for Monitoring and Assessing Childhood 

Exposures to Environmental Contaminants. 

U.S. Environmental Protection Agency, 

Washington, DC: EPA/630/P-03/003F. 

Page Child-Specific Exposure Factors Handbook 

17-6 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-1. Consumer Products Commonly Found in Some U.S. Householdsa 

Consumer Product Category Consumer Product 

Cosmetics Hygiene Products Adhesive bandages 

Bath additives (liquid) 

Bath additives (powder) 

Cologne/perfume/aftershave 

Contact lens solutions 

Deodorant/antiperspirant (aerosol) 

Deodorant/antiperspirant (wax and liquid) 

Depilatories 

Facial makeup 

Fingernail cosmetics 

Hair coloring/tinting products 

Hair conditioning products 

Hairsprays (aerosol) 

Lip products 

Mouthwash/breath freshener 

Sanitary napkins and pads 

Shampoo 

Shaving creams (aerosols) 

Skin creams (non-drug) 

Skin oils (non-drug) 

Soap (toilet bar) 

Sunscreen/suntan products 

Talc/body powder (non-drug) 

Toothpaste 

Waterless skin cleaners 

Household Furnishings Carpeting 

Draperies/curtains 

Rugs (area) 

Shower curtains 

Vinyl upholstery, furniture 

Garment Conditioning Products Anti-static spray (aerosol) 

Leather treatment (liquid and wax) 

Shoe polish 

Spray starch (aerosol) 

Suede cleaner/polish (liquid and aerosol) 

Textile water-proofing (aerosol) 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-7
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-1. Consumer Products Commonly Found in Some U.S. Householdsa (continued) 

Consumer Product Category Consumer Product 

Household Maintenance Products Adhesive (general) (liquid) 

Bleach (household) (liquid) 

Bleach (see laundry) 

Candles 

Cat box litter 

Charcoal briquets 

Charcoal lighter fluid 

Drain cleaner (liquid and powder) 

Dishwasher detergent (powder) 

Dishwashing liquid 

Fabric dye (DIY)b 

Fabric rinse/softener (liquid) 

Fabric rinse/softener (powder) 

Fertilizer (garden) (liquid) 

Fertilizer (garden) (powder) 

Fire extinguishers (aerosol) 

Floor polish/wax (liquid) 

Food packaging and packaged food 

Furniture polish (liquid) 

Furniture polish (aerosol) 

General cleaner/disinfectant (liquid) 

General cleaner (powder) 

General cleaner/disinfectant (aerosol and pump) 

General spot/stain remover (liquid) 

General spot/stain remover (aerosol and pump) 

Herbicide (garden-patio) (liquid and aerosol) 

Insecticide (home and garden) (powder) 

Insecticide (home and garden) (aerosol and pump) 

Insect repellent (liquid and aerosol) 

Laundry detergent/bleach (liquid) 

Laundry detergent (powder) 

Laundry pre-wash/soak (powder) 

Laundry pre-wash/soak (liquid) 

Laundry pre-wash/soak (aerosol and pump) 

Lubricant oil (liquid) 

Lubricant (aerosol) 

Matches 

Metal polish 

Oven cleaner (aerosol) 

Pesticide (home) (solid) 

Pesticide (pet dip) (liquid) 

Pesticide (pet) (powder) 

Pesticide (pet) (aerosol) 

Pesticide (pet) (collar) 

Petroleum fuels (home (liquid and aerosol) 

Rug cleaner/shampoo (liquid and aerosol) 

Rug deodorizer/freshener (powder) 

Room deodorizer (solid) 

Room deodorizer (aerosol) 

Scouring pad 

Toilet bowl cleaner 

Toiler bowl deodorant (solid) 

Water-treating chemicals (swimming pools) 

Page Child-Specific Exposure Factors Handbook 

17-8 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

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) 

Ceiling tile 

Caulks/sealers/fillers 

Dry wall/wall board 

Flooring (vinyl) 

House Paint (interior) (liquid) 

House Paint and Stain (exterior) (liquid) 

Insulation (solid) 

Insulation (foam) 

Paint/varnish removers 

Paint thinner/brush cleaners 

Patching/ceiling plaster 

Roofing 

Refinishing products (polyurethane, varnishes, etc.) 

Spray paints (home) (aerosol) 

Wall paneling 

Wall paper 

Wall paper glue 

Automobile-related Products Antifreeze 

Car polish/wax 

Fuel/lubricant additives 

Gasoline/diesel fuel 

Interior upholstery/components, synthetic 

Motor oil 

Radiator flush/cleaner 

Automotive touch-up paint (aerosol) 

Windshield washer solvents 

Personal Materials Clothes/shoes 

Diapers/vinyl pants 

Jewelry 

Printed material (colorprint, newsprint, photographs) 

Sheets/towels 

Toys (intended to be placed in mouths) 

a A subjective listing based on consumer use profiles. b DIY = Do It Yourself. 

Source: U.S. EPA, 1987. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-9
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products 

Product Type 

Amount of 

Product Per 

Applicationa 

(grams) 

Average Frequency of Use

 (per day) 

Upper 90th Percentile Frequency of Use

(per day)

Survey Type Survey Type

Marketb 

Cosmetic CTFA Research Co. Bureau 

Market Cosmetic CTFA Research Co. Bureau 

Baby Lotion - baby usec 

Baby Lotion - adult use 

Baby Oil - baby usec 

Baby Oil - adult use 

Baby Powder - baby usec 

Baby Powder - adult use 

Baby Cream - baby usec 

Baby Cream - adult use 

Baby Shampoo - baby usec 

Baby Shampoo - adult use 

Bath Oils 

Bath Tablets 

Bath Salts 

Bubble Baths 

Bath Capsules 

Bath Crystals 

Eyebrow Pencil 

Eyeliner 

Eye Shadow 

Eye Lotion 

Eye Makeup Remover 

Mascara 

Under Eye Cover 

Blusher & Rouge 

Face Powders 

Foundations 

Leg and Body Paints 

Lipstick & Lip Gloss 

Makeup Bases 

Makeup Fixatives 

Sunscreen 

Colognes & Toilet Water 

Perfumes 

1.4 

1.0 

1.3 

5.0 

0.8 

0.8 

– 

– 

0.5 

5.0 

14.7 

– 

18.9 

11.8 

– 

– 

– 

– 

– 

– 

– 

– 

– 

0.011 

0.085 

0.265 

– 

– 

0.13 

– 

3.18 

0.65 

0.23 

0.38 

0.22 

0.14 

0.06 

5.36 

0.13 

0.43 

0.07 

0.14 

0.02 

0.08 

0.003 

0.006 

0.088 

0.018 

0.006 

0.27 

0.42 

0.69 

0.094 

0.29 

0.79 

0.79 

1.18 

0.35 

0.46 

0.003 

1.73 

0.24 

0.052 

0.003 

0.68 

0.29 

1.0 

0.19 

1.2 

0.13 

1.5 

0.22 

1.3 

0.10 

– 

– 

0.19 

0.008 

0.013 

0.13 

0.019 

– 

0.49 

0.68 

0.78 

0.34 

0.45 

0.87 

– 

1.24 

0.67 

0.78 

0.011 

1.23 

0.64 

0.12 

– 

0.85 

0.26 

– 

0.24d 

– 

– 

0.35d 

– 

– 

– 

0.11f 

– 

0.22g 

– 

– 

– 

– 

– 

– 

0.27 

0.40 

– 

– 

0.46 

– 

0.55 

0.33 

0.47 

– 

2.62 

– 

– 

0.002 

0.56 

0.38 

0.57 

0.86 

0.14 

0.29 

8.43 

0.57 

0.43 

0.14 

0.14 

0.86e 

0.29 

0.14e 

0.14e 

0.43 

0.29e 

0.29e 

1.0 

1.43 

1.43 

0.43 

1.0 

1.29 

0.29 

2.0 

1.29 

1.0 

0.14e 

4.0 

0.86 

0.14 

0.14e 

1.71 

0.86 

2.0 

1.0 

3.0 

0.57 

3.0 

1.0 

3.0 

0.14e 

--

--

0.86 

0.14e 

0.14e 

0.57 

0.14e 

0.14e 

1.0 

1.0 

1.0 

1.0 

1.0 

1.0 

--

1.43 

1.0 

1.0 

0.14e 

2.86 

1.0 

1.0 

– 

1.43 

1.0 

-­

1.0d 

-­

-­

1.0d 

-­

-­

-­

0.43f 

-­

1.0g 

-­

-­

-­

-­

-­

-­

1.0 

1.0 

-­

-­

1.5 

-­

1.5 

1.0 

1.5 

-­

6.0 

-­

-­

0.005 

1.5 

1.5 

Page Child-Specific Exposure Factors Handbook 

17-10 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products (ontinued) 

Average Frequency of Use Upper 90th Percentile Frequency of Use

 (per day) (per day) Amount of 

Product Per Survey Type Survey Type Product Type Applicationa 

Marketb Market (grams) Cosmetic Cosmetic CTFA Research CTFA Research Co. Co. Bureau Bureau 

Powders 2.01 0.18 0.39 – 1.0 1.0 -­

Sachets 0.2 0.0061 0.034 – 0.14e 0.14e -­

Fragrance Lotion – 0.0061 -- -- 0.29e – -­

Hair Conditioners 12.4 0.4 0.40 0.27 1.0 1.0 0.86 

Hair Sprays – 0.25 0.55 0.32 1.0 1.0 1.0 

Hair Rinses 12.7 0.064 0.18 – 0.29 1.0 -­

Shampoos 16.4 0.82 0.59 0.48 1.0 1.0 1.0 

Tonics and Dressings 2.85 0.073 0.021 – 0.29 0.14e -­

Wave Sets 2.6 0.003h 0.040 -- --h 0.14 -­

Dentifrices – 1.62 0.67 2.12 2.6 2.0 4.0 

Mouthwashes – 0.42 0.62 0.58 1.86 1.14 1.5 

Breath Fresheners – 0.052 0.43 0.46 0.14 1.0 0.57 

Nail Basecoats 0.23 0.052 0.13 – 0.29 0.29 -­

Cuticle Softeners 0.66 0.040 0.10 – 0.14 0.29 -­

Nail Creams & Lotions 0.56 0.070 0.14 – 0.29 0.43 -­

Nail Extenders – 0.003 0.013 -- 0.14e 0.14e -­

Nail Polish & Enamel 0.28 0.16 0.20 0.07 0.71 0.43 1.0 

Nail Polish & Enamel 3.06 0.088 0.19 – 0.29 0.43 -­

Remover 

Nail Undercoats – 0.049 0.12 – 0.14 0.29 -­

Bath Soaps 2.6 1.53 0.95 – 3.0 1.43 -­

Underarm Deodorants 0.52 1.01 0.80 1.10 1.29 1.29 2.0 

Douches – 0.013 0.089 0.085 0.14e 0.29 0.29 

Feminine Hygiene – 0.021 0.084 0.05 1.0e 0.29 0.14 

Deodorants 

Cleansing Products (cold 1.7 0.63 0.80 0.54 1.71 2.0 1.5 

creams, cleansing lotions

 liquids & pads) 

Depilatories – 0.0061 0.051 0.009 0.016 0.14 0.033 

Face, Body & Hand Preps 3.5 0.65 – 1.12 2.0 – 2.14 

(excluding shaving preps) 

Foot Powder & Sprays – 0.061 0.079 -- 0.57e 0.29 -­

Hormones – 0.012 0.028 -- 0.57e 0.14e -­

Moisturizers 0.53 0.98 0.88 0.63 2.0 1.71 1.5 

Night Skin Care Products 1.33 0.18 0.50 – 1.0 1.0 – 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-11
 
Table 17-2. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued) 

Product Type 

Amount of 

Product Per 

Applicationa 

(g) 

Average Frequency of Use

 (per day) 

Upper 90th Percentile Frequency of Use

(per day)

Survey Type Survey Type

Marketb	 

Cosmetic	 CTFA Research Co.	 Bureau 

Market Cosmetic CTFA	 Research Co. Bureau 

Paste Masks (mud packs) 

Skin Lighteners 

Skin Fresheners & Astringents 

Wrinkle Smoothers (removers) 

Facial Cream 

Permanent Wave 

Hair Straighteners 

Hair Dye 

Hair Lighteners 

Hair Bleaches 

Hair Tints 

Hair Rinse (coloring) 

Shampoo (coloring) 

Hair Color Spray 

Shave Cream	 

3.7 

--

2.0 

0.38 

0.55 

101 

0.156 

--

--

--

– 

– 

– 

--

1.73 

0.027 

– 

0.33 

0.021 

0.0061 

0.003 

0.0007 

0.001 

0.0003 

0.0005 

0.0001 

0.0004 

0.0005 

– 

– 

0.20 

0.024 

0.56 

0.15 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

0.001 

--

0.005 

– 

– 

– 

– 

– 

– 

0.082 

0.14 

–d 

1.0 

1.0d 

0.0061 

0.0082 

0.005d 

0.004d 

0.005d 

0.02d 

0.005d 

0.02d 

0.02d 

–d 

--

0.43 

0.14d 

1.43 

1.0 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

– 

-­

-­

-­

-­

-­

0.005 

-­

0.014 

-­

-­

-­

-­

-­

-­

0.36 

a	 

b	 

c 

d	 

e	 

f 

g 

h 

Source:

Values reported are the averages of the responses reported by the twenty companies interviewed. 

(--'s) indicate no data available. 

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 were indicated by "1 or more" also ranges were used in many cases, i.e., "10-12." The average, therefore, is 

underestimated slightly. The "1 or more" designation also skew 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. 

Usage data reflected "entire household" use for both baby lotion and baby oil. 

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. 

Usage data reflected "entire household" use. 

Usage data reflected total bath product usage. 

None of the individuals surveyed reported using this product. 

 CTFA, 1983. 

Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Page Child-Specific Exposure Factors Handbook 

17-12 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-3. 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 99 100 

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 

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 17-4. 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 99 100 

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 

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 17-5. 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 99 100 

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 

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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-13
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-6. Number of Minutes Spent in Activities Working With or Near Glue (minutes/day) 

N 

Percentiles 

1 2 5 10 25 50 75 90 95 98 99 100 

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 

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 17-7. Number of Minutes Spent in Activities Working With or Near Solvents, Fumes or Strong Smelling Chemicals 

(minutes/day) 

Age Group N 

Percentiles

1 2 5 10 25 50 75 90 95 98 99 100 

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 

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 17-8. 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 99 100 

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 

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. 

Page Child-Specific Exposure Factors Handbook 

17-14 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-9. Number of Minutes Spent in Activities Working With or Near Gasoline or 

Diesel-powered Equipment, Besides Automobiles (minutes/day) 

Age Group N 

Percentiles

1 2 5 10 25 50 75 90 95 98 99 100 

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 

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 17-10. Number of Minutes Spent in Activities Working With or Near Pesticides, 

Including Bug Sprays or Bug Strips (minutes/day) 

Age Group N 

Percentiles

1 2 5 10 25 50 75 90 95 98 99 100 

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 

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 17-11. 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

1-2 3-5 6-9 10+ Don’t 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 

* = Missing Data. 

N = Number of respondents. 

Source: U.S. EPA, 1996. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-15
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-12. Number of Respondents Using Any Aerosol Spray Product for 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 40 30 9 0 0 1 0 0 0 0 0 

5 to 11 years 75 57 14 1 1 1 1 0 0 0 0 

12 to 17 years 103 53 31 12 4 1 0 0 1 1 0 

18 to 64 years 1,071 724 263 39 15 13 1 1 2 8 5 

N = Number of respondents.. 

Source: U.S. EPA, 1996. 

Table 17-13. Number of Respondents Using a Humidifier at Home 

Age Group Total N 

Frequency 

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 

N = Number of respondents. 

Source: U.S. EPA, 1996. 

Table 17-14. Number of Respondents Indicating that Pesticides Were Applied by the Professional at Home

to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 

Age Group Total N Number of Times Over a 6-month Period

Pesticides Were Applied by Professionals 

None 1-2 3-5 6-9 10+ Don’t Know 

1 to 4 years 113 60 35 11 6 1 * 

5 to 11 years 150 84 37 10 18 1 * 

12 to 17 years 143 90 40 5 6 * 2 

18 to 64 years 1,264 660 387 89 97 15 16 

* = Missing data. 

N = Number of respondents. 

Source: U.S. EPA, 1996. 

Page Child-Specific Exposure Factors Handbook 

17-16 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-15. Number of Respondents Reporting Pesticides Applied by the Consumer at Home

To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 

Age Group Total N 

Number of Times Over a 6-month

Period Pesticides Applied by Resident 

None 1-2 3-5 6-9 10+ Don’t Know 

1 to 4 years 113 46 46 15 3 3 * 

5 to 11 years 150 50 70 24 1 4 1 

12 to 17 years 143 45 64 21 5 8 * 

18 to 64 years 1,264 473 477 192 48 55 19 

Note: * = Missing Data

N = Number of respondents. 

Source: U.S. EPA, 1996. 

Table 17-16. Number of Respondents Indicating that Pesticides Were Applied by a 

Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies
 

Frequency 

Age Group Total N (number of times over a six-month period that pesticides were applied by a professional) 

None 1 to 2 3 to 5 6 to 9 10+ Don’t Know 

0 to <1 years 15 9 4 1 1 0 0 

1to <2 years 23 13 5 3 1 1 0 

2 to <3 years 32 9 15 5 3 0 0 

3 to <6 years 80 51 22 5 2 0 0 

6 to <11 years 106 59 22 7 17 1 0 

11 to <16 years 115 68 35 4 6 0 2 

16 to <21 years 87 40 36 2 5 1 3 

N = Number of respondents. 

Source: U.S. EPA re-analysis of NHAPS (U.S. EPA, 1996) data. 

Table 17-17. 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 six-month period that pesticides were applied by a resident) 

None 1 to 2 3 to 5 6 to 9 10+ Don’t Know 

0 to <1 year 15 4 8 2 0 1 0 

1to <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 

N = Number of respondents. 

Source: U.S. EPA re-analysis of NHAPS (U.S. EPA, 1996) data. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-17
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-18. Household Demographics, and Pesticide Types, Characteristics, and Frequency of Pesticide Use
 

Survey Population Demographics
 

Gender 

female 

male 

Language of Interview

Spanish

English

Reading Skills

able to read English

able to read Spanish

Number in household 

2-3 people

4-5 people

6-8 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 

Numbera Percenta 

90 

17 

72 

35 

71 

95 

25 

59 

23 

37 

45 

25 

75 

9 

9 

8 

4 

55 

22 

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 

Pesticide Use 

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 

135 

10 

3 

67 

30 

14 

11 

7 

7 

4 

4 

83 

55 

72 

5 

5 

132 

10 

5 

20 

27 

42 

23 

16 

13 

75 

24 

17 

16 

91.2

6.8

2.0

45.3

20.3

9.4

7.4

4.7

4.7

2.7

2.7

56.1

37.2

48.6

3.4

3.4

89.2

6.8

3.4 

13.5

18.2

28.4

15.5

10.8

8.8 

50.7

15.2

11.5

10.8

a 

Source: 

Totals may not add to 107 participants or 148 products, and percentages may not add to 100 due to some non-responses to survey questions. 

Bass et al., 2001. 

Page Child-Specific Exposure Factors Handbook 

17-18 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-19. Frequency of Use of Cosmetic Products 

Product Type N Number of Applications per Day

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 & 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. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-19
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-20. 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 & 

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 

Page Child-Specific Exposure Factors Handbook 

17-20 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-20. 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 & 

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 & 

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 

b 

c 

GM 

GSD 

Gof 

Note: 

Derived as the ratio of the total amount used to the number of use days. 

Derived as the ratio of the total amount used to the total number of applications during the survey. 

None of the tested distributions provided a good fit. 

= Geometric mean. 

= Geometric standard deviation. 

= Goodness of fit. 

Data are for women, ages 19 to 65 years. 

Source: Loretz et al., 2005. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-21
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-21. 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. 

Page Child-Specific Exposure Factors Handbook 

17-22 September 2008 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products Table 17-22. Average Amount of Product Applied per Application a (grams) Hairspray Hairspray Solid Summary Statistics (aerosol) (pump) Spray Perfume Liquid Foundation Shampoo Body Wash Antiperspirant N 163 b 161 b 310 b 321 b 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 

99thc 11.30 15.52 1.73 2.36 51.12 35.1 2.52 

Best fit distributions Lognormal Lognormal Lognormal Lognormal Lognormal Lognormal Gamma and parameters Distribution Distribution Distribution Distribution 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- 0.06 0.07 0.077 0.041 0.1328 0.486 0.339 

Smirnov) 

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 (>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 19 to 65 years).GM = Geometric mean.GSD = Geometric standard Deviation.

Source: Loretz et al., 2006. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-23
 
Table 17-23. Average Amount of Product Applied per Use Day a (grams) 

Hairspray Hairspray Solid

Summary Statistics (aerosol) (pump) Spray Perfume Liquid Foundation Shampoo Body Wash Antiperspirant 

N 163 b 161 b 310 b 321 b 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 12.72 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 99thc 15.05 23.98 2.01 2.70 51.12 43.5 4.42 

Best fit distributions Lognormal Lognormal Lognormal Lognormal Lognormal Lognormal Gamma and parameters Distribution Distribution Distribution Distribution 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- 0.05 0.05 0.075 0.047 0.8208 0.760 0.293 

Smirnov) 

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 (>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 19 to 65 years).GM = Geometric mean.GSD = Geometric standard deviation.

Source: Loretz et al., 2006. 

Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Page Child-Specific Exposure Factors Handbook 

17-24 September 2008 
Table 17-24. Average Number of Applications Per Use Daya 

Summary Statistics Facial Cleanser 

(Lathering and Non-Lathering) 

Hair Conditioner Eye Shadow 

N 

Mean 

SD 

Minimum 

Maximum 

Percentiles 

10th 

20th 

30th 

40th 

50th 

60th 

70th 

80th 

90th 

95th 

97.5th 

99thb 

295 

1.6 

0.52 

1.0 

3.2 

1.0 

1.0 

1.2 

1.4 

1.7 

1.9 

2.0 

2.0 

2.2 

2.4 

2.9b 

3.1b 

297 

1.1 

0.19 

1.0 

2.4 

1.0 

1.0 

1.0 

1.0 

1.0 

1.0 

1.0 

1.1 

1.2 

1.4 

1.8b 

2.1b 

299 

1.2 

0.33 

1.0 

2.7 

1.0 

1.0 

1.0 

1.1 

1.1 

1.1 

1.2 

1.4 

1.7 

2.0 

2.2b 

2.5b 

a 

b 

 

N 

SD 

Source: 

Derived as the ratio of the number of applications to the number of use days. 

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.. 

= Number of subjects (women, ages 18 to 69 years). 

= Standard deviation. 

Loretz et al., 2008. 

Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-25
 
Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Table 17-25. Average Amount of Product Applied Per Use Day (grams)a 

Facial Cleanser Facial Cleanser Facial Cleanser (Non- Summary Statistics (Lathering and Non- Hair Conditioner Eye shadow (Lathering) Lathering) Lathering) 

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 

99thb 12.44b 13.07b 15.29b 60.20b 0.673b 

Best fit distributions Lognormal Lognormal Lognormal Lognormal Lognormal 

and parameters distribution distribution distribution distribution 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 0.1251 0.4429 0.4064 0.8595 <0.0001 (Chi-square test) 

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)]. http://www/cdc.gov/nchs/about/major/nhanes/nhanes3/nh3gui.pdf. 

N = Number of subjects (women, ages 18 to 69 years). 

GM = Geometric mean. 

GSD = Geometric standard deviation. 

Source: Loretz et al., 2008. 

Page Child-Specific Exposure Factors Handbook 

17-26 September 2008 
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Chapter 17 - Consumer Products 

Table 17-26. Average Amount of Product Applied Per Application (grams)a 

Summary Statistics Facial Cleanser Facial Facial Cleanser 

(Lathering and Non- Cleanser (Non- Hair Conditioner Eye Shadow 

Lathering) (Lathering) Lathering) 

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 Lognormal Lognormal Extreme value Gamma Extreme value parameters distribution 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). 

GM = Geometric mean. 

SD = Geometric standard deviation. 

Source: Loretz et al., 2008. 

Child-Specific Exposure Factors Handbook Page
 

September 2008 17-27
 
Table 17-27. Characteristics of the Study Population and the Percent Using Selected Baby Care Products 

Characteristic 

Number of Participants 

Los Angeles, California 

Minneapolis, Minnesota 

Columbia, Missouri 

Gender 

Male 

Female 

Age (months) 

2-8 

9-16 

17-24 

24-28 

Infant Weight (kg) 

?10 

> 10 

Race 

White 

Hispanic/Latino 

Native American 

Asian 

Black 

Sample Number (percent) 

43 (26) 

77 (47) 

43 (26) 

84 (52) 

79 (48) 

42 (26) 

82 (50) 

30 (18) 

9 (6) 

84 (52) 

79 (48) 

131 (80) 

17 (10) 

3 (2) 

8 (5) 

4 (3) 

Product Use

Baby Lotion 

Baby Shampoo 

Baby Powder 

Diaper Cream 

Baby Wipes 

 Percent Using 

36 

54 

14 

33 

94 

Source: Sathyanarayana et al., 2008. 

Child-Specific Exposure Factors Handbook 

Chapter 17 - Consumer Products 

Page Child-Specific Exposure Factors Handbook 

17-28 September 2008 
Child-Specific Exposure Factors Handbook 

Glossary 

GLOSSARY OF TERMS 

Child-Specific Exposure Factors Handbook Page 

September 2008 G-1 
Child-Specific Exposure Factors Handbook 

Glossary 

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. 

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. 

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." 

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) - Dose rate averaged over 

a pathway-specific period of exposure expressed as a 

daily dose on a per-unit-body-weight basis. The ADD 

is used for exposure to chemicals with 

non-carcinogenic non-chronic effects. The ADD is 

usually expressed in terms of mg/kg-day or other 

mass/mass-time units. 

Benchmark Dose (BMD) or Concentration (BMC) ­

A dose or concentration that produces a predetermined 

change in response rate of an adverse effect (called the 

benchmark response or BMR) compared to 

background. 

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. 

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. 

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. 

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Child-Specific Exposure Factors Handbook 

Glossary 

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. 

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. 

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 a substance available for 

interaction with metabolic processes or biologically 

significant receptors after crossing the outer boundary 

of an organism. The potential dose is the amount 

ingested, inhaled, or applied to the skin. The applied 

Child-Specific Exposure Factors Handbook Page 

September 2008 G-3 
Child-Specific Exposure Factors Handbook 

Glossary 

dose is the amount of a substance presented to an 

absorption barrier and available for absorption 

(although not necessarily having yet crossed the outer 

boundary of the organism). The absorbed dose is the 

amount crossing a specific absorption barrier (e.g., the 

exchange boundaries of skin, lung, and digestive tract) 

through uptake processes. Internal dose is a more 

general term denoting the amount absorbed without 

respect to specific absorption barriers or exchange 

boundaries. The amount of a chemical available for 

interaction by any particular organ or cell is termed the 

delivered dose for that organ or cell. 

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 (sub)population and the changes 

developed in that organism, system, or (sub)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. 

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. 

Energy expenditures - The amount of energy 

expended by an individual during activities. 

Exposure - Contact of a chemical, physical, or 

biological agent with the outer boundary of an 

organism. Exposure is quantified as the concentration 

of the agent in the medium in contact integrated over 

the time duration of the contact. 

Exposure assessment - The determination or 

estimation (qualitative or quantitative) of the 

magnitude, frequency, or duration, and route or 

exposure. 

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 frequency - The number of exposure events 

in an exposure duration. 

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 

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Child-Specific Exposure Factors Handbook 

Glossary 

the exposure assessor in evaluating estimating, or 

quantifying exposures. 

Fate - Pattern of distribution of an agent, its 

derivatives, or metabolites in an organism, system, 

compartment, or (sub)population of concern as a result 

of transport, partitioning, transformation, or 

degradation. 

General population - The total of individuals 

inhabiting an area or making up a whole group. 

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 (sub)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 (sub)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. 

Homegrown/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 (HEC) or Dose 

(HED) - 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. 

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 :g/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. 

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 rate - Rate of inhalation, ingestion, and dermal 

contact depending on the route of exposure. For 

Child-Specific Exposure Factors Handbook Page 

September 2008 G-5 
Child-Specific Exposure Factors Handbook 

Glossary 

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 a substance penetrating 

across absorption barriers (the exchange boundaries) of 

an organism, via either physical or biological processes 

(synonymous with absorbed dose). 

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 useful for deriving exposure 

factors. 

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. 

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. 

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. 

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. 

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. 

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. 

Page Child-Specific Exposure Factors Handbook 

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Child-Specific Exposure Factors Handbook 

Glossary 

Microenvironment - Surroundings that can be treated 

as homogeneous or well characterized in the 

concentrations of an agent (e.g., home, office, 

automobile, kitchen, store). 

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. 

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. 

Outdoor settled dust - Particles that have settled onto 

outdoor objects and surfaces due to either wet or dry 

deposition. 

Oxygen consumption (VO ) - The rate at which 

oxygen is used by tissues. 

2 

Parameter uncertainty - Uncertainty regarding some 

parameter. 

Pathway - The physical course a chemical or pollutant 

takes from the source to the organism exposed. 

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. 

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. 

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September 2008 G-7 
Child-Specific Exposure Factors Handbook 

Glossary 

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. 

Questionnaire/survey response - A “question and 

answer” data collection methodology conducted via inperson 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. 

Reasonable maximum exposure (or worst case) - 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 subgroups) 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 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 

subgroups) 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 dose, 

with uncertainty factors generally applied to reflect 

limitations of the data used. Generally used in 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. 

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. 

Risk - The probability of an adverse effect in an 

organism, system, or (sub)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 

(sub)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 

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Child-Specific Exposure Factors Handbook 

Glossary 

uncertainties, of the probability of occurrence of known 

and potential adverse effects of an agent in a given 

organism, system, or (sub)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 subset 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. 

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. 

Subsistence fishermen - Individuals who consume 

fresh caught fish as a major source of food. 

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. 

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Child-Specific Exposure Factors Handbook 

Glossary 

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. 

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 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. 

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. 

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. 

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. 

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. 

Glossary entries adapted from: 

International Programme on Chemical Safety (2004). 

IPCS Risk Assessment Terminology. 

Available on-line at: 

http://www.who.int/ipcs/methods/harmoniza 

tion/areas/ipcsterminologyparts1and2.pdf 

U.S. EPA (1992) 	Guidelines for exposure assessment. 

Washington, DC: Office of Research and 

Development, Office of Health and 

Environmental Assessment. EPA/600/2­

92/001. 

U.S. EPA.	 (1997) Exposure Factors Handbook 

Revised. Washington, DC: U.S. 

Environmental Protection Agency, Office of 

Research and Development. EPA/600/P95/002F. 

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